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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/20260624_053439_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:34:37,885 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:34:37,886 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:34:37,886 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:34:37,886 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:34:37,886 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:34:37,886 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:34:37,886 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:34:37,886 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:34:37,886 - +2026-06-24 05:34:37,970 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:34:37,970 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:34:37,970 - Accelerator.num_process = 1 +2026-06-24 05:34:37,970 - Accelerator.mixed_precision = no +2026-06-24 05:34:37,980 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:34:37,980 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:34:37,980 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:34:37,980 - +2026-06-24 05:34:37,980 - ### System information ### +2026-06-24 05:34:37,980 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:34:37,980 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:34:37,980 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:34:37,980 - Machine: x86_64 +2026-06-24 05:34:37,980 - Processor: x86_64 +2026-06-24 05:34:37,980 - Available CPU cores: 8 +2026-06-24 05:34:37,980 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:34:37,980 - +2026-06-24 05:34:37,980 - ### GPU information ### +2026-06-24 05:34:37,980 - CUDA Available: True +2026-06-24 05:34:37,980 - CUDA Version: 13.0 +2026-06-24 05:34:37,981 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:34:37,981 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:34:37,981 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:34:37,981 - In addition, Triton does not directly support Windows. +2026-06-24 05:34:37,981 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:34:37,996 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:34:37,996 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:34:37,996 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:34:37,996 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:34:37,996 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:34:37,996 - +2026-06-24 05:34:37,996 - ### Python information ### +2026-06-24 05:34:37,998 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:34:37,998 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:34:37,998 - +2026-06-24 05:34:37,998 - ### Packages information ### +2026-06-24 05:34:37,999 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:34:38,000 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:34:38,000 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:34:38,001 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:34:38,001 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:34:38,002 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:34:38,002 - +2026-06-24 05:34:38,002 - ### Loading params file ### +2026-06-24 05:34:38,002 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000002.yaml +2026-06-24 05:34:38,008 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:34:38,009 - Success! Params file validated and defaults applied. +2026-06-24 05:34:38,009 - +2026-06-24 05:34:38,009 - ### Setting GPU Device ### +2026-06-24 05:34:38,010 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:34:38,010 - +2026-06-24 05:34:38,010 - Random seed: 20261846 provided by params file +2026-06-24 05:34:38,010 - ### Initializing Initializer ### +2026-06-24 05:34:38,010 - init_params are displayed below: +2026-06-24 05:34:38,010 - random_seed: 20261846 +2026-06-24 05:34:38,010 - probe_illum_type: electron +2026-06-24 05:34:38,010 - probe_kv: 200.0 +2026-06-24 05:34:38,010 - probe_conv_angle: 12.791192054748535 +2026-06-24 05:34:38,010 - probe_aberrations: {'C10': -4.824, 'C12': 0.327, 'phi12': 59.698, 'C21': 134.821, 'phi21': 127.139, 'C23': 251.001, 'phi23': 21.108, 'C30': 2393991.0, 'C32': -5988.508, 'phi32': 313.77, 'C34': -4476.031, 'phi34': 67.073, 'C41': -304813.312, 'phi41': 327.112, 'C43': 364127.75, 'phi43': 77.758, 'C45': -97685.359, 'phi45': 184.903, 'C50': -410699616.0, 'C52': -18312922.0, 'phi52': 64.88, 'C54': -17729770.0, 'phi54': 177.945, 'C56': -5185558.0, 'phi56': 49.278} +2026-06-24 05:34:38,010 - beam_kev: None +2026-06-24 05:34:38,010 - probe_dRn: None +2026-06-24 05:34:38,010 - probe_Rn: None +2026-06-24 05:34:38,010 - probe_D_H: None +2026-06-24 05:34:38,010 - probe_D_FZP: None +2026-06-24 05:34:38,010 - probe_Ls: None +2026-06-24 05:34:38,010 - meas_Npix: 128 +2026-06-24 05:34:38,010 - pos_N_scans: 256 +2026-06-24 05:34:38,010 - pos_N_scan_slow: 16 +2026-06-24 05:34:38,011 - pos_N_scan_fast: 16 +2026-06-24 05:34:38,011 - pos_scan_step_size: 0.4755619168281555 +2026-06-24 05:34:38,011 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:34:38,011 - probe_pmode_max: 6 +2026-06-24 05:34:38,011 - probe_pmode_init_pows: [0.02] +2026-06-24 05:34:38,011 - obj_omode_max: 1 +2026-06-24 05:34:38,011 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:34:38,011 - obj_Nlayer: 1 +2026-06-24 05:34:38,011 - obj_slice_thickness: 20.0 +2026-06-24 05:34:38,011 - simu_Npix: None +2026-06-24 05:34:38,011 - simu_match_mode: None +2026-06-24 05:34:38,011 - meas_permute: None +2026-06-24 05:34:38,011 - meas_reshape: [256, 128, 128] +2026-06-24 05:34:38,011 - meas_flipT: [0, 0, 0] +2026-06-24 05:34:38,011 - meas_crop: None +2026-06-24 05:34:38,011 - meas_pad: None +2026-06-24 05:34:38,011 - meas_resample: None +2026-06-24 05:34:38,011 - meas_add_source_size: None +2026-06-24 05:34:38,011 - meas_add_detector_blur: None +2026-06-24 05:34:38,011 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:34:38,011 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:34:38,011 - meas_add_poisson_noise: None +2026-06-24 05:34:38,011 - meas_export: None +2026-06-24 05:34:38,011 - probe_permute: None +2026-06-24 05:34:38,011 - probe_z_shift: None +2026-06-24 05:34:38,011 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:34:38,011 - pos_scan_flipT: None +2026-06-24 05:34:38,011 - pos_scan_affine: None +2026-06-24 05:34:38,011 - pos_scan_rand_std: 0.15 +2026-06-24 05:34:38,011 - obj_z_crop: None +2026-06-24 05:34:38,011 - obj_z_pad: None +2026-06-24 05:34:38,011 - obj_z_resample: None +2026-06-24 05:34:38,011 - meas_source: file +2026-06-24 05:34:38,011 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000002_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:34:38,011 - probe_source: simu +2026-06-24 05:34:38,011 - probe_params: None +2026-06-24 05:34:38,011 - pos_source: simu +2026-06-24 05:34:38,011 - pos_params: None +2026-06-24 05:34:38,011 - obj_source: simu +2026-06-24 05:34:38,011 - obj_params: None +2026-06-24 05:34:38,011 - tilt_source: simu +2026-06-24 05:34:38,012 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:34:38,012 - +2026-06-24 05:34:38,012 - ### Initializing cache ### +2026-06-24 05:34:38,012 - use_cached_obj = False +2026-06-24 05:34:38,012 - use_cached_probe = False +2026-06-24 05:34:38,012 - use_cached_pos = False +2026-06-24 05:34:38,012 - +2026-06-24 05:34:38,012 - ### Initializing measurements ### +2026-06-24 05:34:38,012 - Loading measurements from source = 'file' +2026-06-24 05:34:38,012 - Detected measurement file type = '.h5' +2026-06-24 05:34:38,089 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:34:38,089 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:34:38,091 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0025) +2026-06-24 05:34:38,091 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:34:38,091 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:34:38,095 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:34:38,095 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:34:38,095 - Normalizing by max of the 2D mean pattern intensity: 0.0017028856 +2026-06-24 05:34:38,096 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:34:38,097 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0356, 1.4864) +2026-06-24 05:34:38,098 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:34:38,099 - Pattern total int. statistics (min, mean, max) = (578.5764, 582.7809, 588.2803), with min/max = 98.4% +2026-06-24 05:34:38,100 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0356, 1.4864) +2026-06-24 05:34:38,100 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:34:38,100 - +2026-06-24 05:34:38,100 - ### Setting up calibration ### +2026-06-24 05:34:38,100 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:34:38,101 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:34:38,101 - Radius of fitted bright field disk (RBF) = 13.04 px with meas_Npix = 128 +2026-06-24 05:34:38,101 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2037 +2026-06-24 05:34:38,101 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:34:38,101 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:34:38,329 - Initial guess: center=(63.61, 63.63), radius=13.04, Gaussian blur std=0.50 +2026-06-24 05:34:38,341 - Final fit: center=(63.61, 63.63), radius=13.04, Gaussian blur std=0.66 +2026-06-24 05:34:38,341 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.06 px with Npix = 128 +2026-06-24 05:34:38,341 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:34:38,341 - +2026-06-24 05:34:38,341 - ### Setting init_variables dict ### +2026-06-24 05:34:38,341 - Derived values given input init_params: +2026-06-24 05:34:38,341 - kv = 200.0 kV +2026-06-24 05:34:38,341 - wavelength = 0.0251 Ang +2026-06-24 05:34:38,341 - conv_angle = 12.791192054748535 mrad +2026-06-24 05:34:38,341 - Npix = 128 px +2026-06-24 05:34:38,341 - dk = 0.0391 Ang^-1 +2026-06-24 05:34:38,341 - kMax = 2.5000 Ang^-1 +2026-06-24 05:34:38,341 - da = 0.9797 mrad +2026-06-24 05:34:38,341 - angleMax = 62.6984 mrad +2026-06-24 05:34:38,341 - RBF = 13.0567 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:34:38,341 - n_alpha = 4.9017 (# conv_angle) +2026-06-24 05:34:38,341 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:34:38,342 - Rayleigh-limited resolution = 1.1960 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:34:38,342 - Real space probe extent = 25.6000 Ang +2026-06-24 05:34:38,342 - +2026-06-24 05:34:38,342 - ### Initializing probe ### +2026-06-24 05:34:38,342 - Loading probe from source = 'simu' +2026-06-24 05:34:38,342 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:34:38,342 - Start simulating STEM probe +2026-06-24 05:34:38,342 - kv = 200.0 kV +2026-06-24 05:34:38,342 - wavelength = 0.0251 Ang +2026-06-24 05:34:38,342 - conv_angle = 12.791192054748535 mrad +2026-06-24 05:34:38,342 - Npix = 128 px +2026-06-24 05:34:38,342 - dk = 0.0391 Ang^-1 +2026-06-24 05:34:38,342 - kMax = 2.5000 Ang^-1 +2026-06-24 05:34:38,342 - alpha_max = 62.6984 mrad +2026-06-24 05:34:38,342 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:34:38,342 - Rayleigh-limited resolution = 1.1960 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:34:38,342 - Real space probe extent = 25.6000 Ang +2026-06-24 05:34:38,342 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:34:38,342 - ------------------------------------------------------------------------------------- +2026-06-24 05:34:38,342 - C1,0 C1 -4.8240 - Defocus (C10 = -df) +2026-06-24 05:34:38,342 - C1,2 A1 0.3270 59.70 2-fold astigmatism +2026-06-24 05:34:38,342 - C2,1 3*B2 134.8210 127.14 Axial coma +2026-06-24 05:34:38,342 - C2,3 A2 251.0010 21.11 3-fold astigmatism +2026-06-24 05:34:38,342 - C3,0 C3 2393991.0000 - Spherical aberration +2026-06-24 05:34:38,342 - C3,2 4*S3 -5988.5080 313.77 Axial star aberration +2026-06-24 05:34:38,343 - C3,4 A3 -4476.0310 67.07 4-fold astigmatism +2026-06-24 05:34:38,343 - C4,1 4*B4 -304813.3120 327.11 Axial coma(4th) +2026-06-24 05:34:38,343 - C4,3 4*D4 364127.7500 77.76 3-lobe aberration +2026-06-24 05:34:38,343 - C4,5 A4 -97685.3590 184.90 5-fold astigmatism +2026-06-24 05:34:38,343 - C5,0 C5 -410699616.0000 - Spherical aberration (5th) +2026-06-24 05:34:38,343 - C5,2 6*S5 -18312922.0000 64.88 Axial star aberration(5th) +2026-06-24 05:34:38,343 - C5,4 6*R5 -17729770.0000 177.94 4-lobe aberration +2026-06-24 05:34:38,343 - C5,6 A5 -5185558.0000 49.28 6-fold astigmatism +2026-06-24 05:34:38,346 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:34:38,346 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:34:38,346 - Creating 5 new probe modes from the major mode +2026-06-24 05:34:38,346 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:34:38,450 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:34:38,450 - Orthogonalizing 6 pmodes +2026-06-24 05:34:38,452 - Sorting 6 pmodes by their intensities +2026-06-24 05:34:38,453 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:34:38,454 - sum(|probe_data|**2) = 582.78, while meas_total_ints (min, mean, max) = (578.5764, 582.7809, 588.2803) +2026-06-24 05:34:38,454 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:34:38,454 - +2026-06-24 05:34:38,454 - ### Initializing probe positions ### +2026-06-24 05:34:38,454 - Loading probe positions from source = 'simu' +2026-06-24 05:34:38,454 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:34:38,454 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4756, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:34:38,454 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:34:38,456 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:34:38,456 - crop_pos 1st and last px coords (y,x) = ([16, 16], [52, 52]) +2026-06-24 05:34:38,456 - crop_pos extent (Ang) = [7.2 7.2] +2026-06-24 05:34:38,456 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:34:38,457 - +2026-06-24 05:34:38,457 - ### Initializing object ### +2026-06-24 05:34:38,457 - Loading object from source = 'simu' +2026-06-24 05:34:38,457 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:34:38,458 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:34:38,458 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 198, 198) +2026-06-24 05:34:38,458 - object extent (Z, Y, X) (Ang) = [20. 39.6 39.6] +2026-06-24 05:34:38,458 - +2026-06-24 05:34:38,458 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:34:38,458 - omode_occu (omode) = float32, (1,) +2026-06-24 05:34:38,458 - +2026-06-24 05:34:38,458 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:34:38,459 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:34:38,459 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:34:38,459 - +2026-06-24 05:34:38,459 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:34:38,459 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:34:38,459 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:34:38,459 - +2026-06-24 05:34:38,459 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:34:38,459 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:34:38,459 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:34:38,459 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:34:38,460 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:34:38,460 - crop positions (yx_min=[16 16], yx_max=[180 180]) are well contained inside object canvas (Ny,Nx) = (198, 198). +2026-06-24 05:34:38,460 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:34:38,460 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:34:38,460 - +2026-06-24 05:34:38,460 - ### Collecting reconstruction provenance ### +2026-06-24 05:34:38,460 - Reconstruction provenance is collected and initialized. +2026-06-24 05:34:38,460 - +2026-06-24 05:34:38,460 - ### Initializing loss function ### +2026-06-24 05:34:38,460 - Active loss types: +2026-06-24 05:34:38,460 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:34:38,460 - +2026-06-24 05:34:38,460 - ### Initializing constraint function ### +2026-06-24 05:34:38,460 - Active constraint types: +2026-06-24 05:34:38,460 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:34:38,460 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:34:38,461 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:34:38,461 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:34:38,461 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:34:38,461 - +2026-06-24 05:34:38,461 - ### Done initializing PtyRADSolver ### +2026-06-24 05:34:38,461 - +2026-06-24 05:34:38,586 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:34:38,586 - +2026-06-24 05:34:38,587 - ### Initializing PtychoModel model ### +2026-06-24 05:34:38,659 - ### PtychoModel optimizable variables ### +2026-06-24 05:34:38,659 - obja : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:34:38,659 - objp : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:34:38,659 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:34:38,659 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:34:38,659 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:34:38,659 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:34:38,659 - +2026-06-24 05:34:38,659 - ### Optimizable variables statitsics ### +2026-06-24 05:34:38,659 - Total measurement values : 4,194,304 +2026-06-24 05:34:38,659 - Total optimizing variables: 275,528 +2026-06-24 05:34:38,659 - Overdetermined ratio : 15.22 +2026-06-24 05:34:38,659 - +2026-06-24 05:34:38,659 - ### Model behavior ### +2026-06-24 05:34:38,659 - Tilt propagator : False +2026-06-24 05:34:38,660 - Change slice thickness : False +2026-06-24 05:34:38,660 - Detector blur : False +2026-06-24 05:34:38,660 - Preload data : True +2026-06-24 05:34:38,660 - On-the-fly meas padding : False +2026-06-24 05:34:38,660 - On-the-fly meas resample : False +2026-06-24 05:34:38,660 - On-the-fly simu match mode: None +2026-06-24 05:34:38,660 - +2026-06-24 05:34:38,701 - ### Done initializing PtychoModel model ### +2026-06-24 05:34:38,702 - +2026-06-24 05:34:38,702 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:34:38,702 - +2026-06-24 05:34:38,702 - ### Generating indices, batches, and output_path ### +2026-06-24 05:34:38,703 - d90 = 45.000 px or 9.000 Ang +2026-06-24 05:34:38,703 - Selecting indices with the 'full' mode +2026-06-24 05:34:39,161 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:34:39,236 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:34:39,236 - Original recon_dir_affixes = ['default'] +2026-06-24 05:34:39,237 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:34:39,243 - Path corrected for compatibility: +2026-06-24 05:34:39,243 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32_314_C34_-4.48e+03_phi34_67.1_C41_-3.05e+05_phi41_327_C43_3.64e+05_phi43_77.8_C45_-9.77e+04_phi45_185_C50_-4.11e+08_C52_-1.83e+07_phi52_64.9_C54_-1.77e+07_phi54_178_C56_-5.19e+06_phi56_49.3 +2026-06-24 05:34:39,243 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3 +2026-06-24 05:34:39,244 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3' is generated! +2026-06-24 05:34:39,397 - +2026-06-24 05:34:39,398 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/20260624_053439_ptyrad_log.txt ### +2026-06-24 05:34:39,398 - +2026-06-24 05:34:39,400 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:34:39,400 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:34:39,400 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:34:40,573 - Iter: 1, Total Loss: 0.8783, loss_single: 0.8783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 05:34:40,611 - Iter: 2, Total Loss: 0.8536, loss_single: 0.8536, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:34:40,647 - Iter: 3, Total Loss: 0.8352, loss_single: 0.8352, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,700 - Iter: 4, Total Loss: 0.8159, loss_single: 0.8159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,735 - Iter: 5, Total Loss: 0.7939, loss_single: 0.7939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,770 - Iter: 6, Total Loss: 0.7720, loss_single: 0.7720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,806 - Iter: 7, Total Loss: 0.7499, loss_single: 0.7499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,842 - Iter: 8, Total Loss: 0.7290, loss_single: 0.7290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,877 - Iter: 9, Total Loss: 0.7123, loss_single: 0.7123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,912 - Iter: 10, Total Loss: 0.6963, loss_single: 0.6963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,947 - Iter: 11, Total Loss: 0.6788, loss_single: 0.6788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:40,983 - Iter: 12, Total Loss: 0.6609, loss_single: 0.6609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,018 - Iter: 13, Total Loss: 0.6436, loss_single: 0.6436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,053 - Iter: 14, Total Loss: 0.6272, loss_single: 0.6272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,088 - Iter: 15, Total Loss: 0.6106, loss_single: 0.6106, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,124 - Iter: 16, Total Loss: 0.5934, loss_single: 0.5934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,159 - Iter: 17, Total Loss: 0.5780, loss_single: 0.5780, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,194 - Iter: 18, Total Loss: 0.5628, loss_single: 0.5628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,229 - Iter: 19, Total Loss: 0.5466, loss_single: 0.5466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,265 - Iter: 20, Total Loss: 0.5320, loss_single: 0.5320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,300 - Iter: 21, Total Loss: 0.5164, loss_single: 0.5164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,335 - Iter: 22, Total Loss: 0.5010, loss_single: 0.5010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,371 - Iter: 23, Total Loss: 0.4863, loss_single: 0.4863, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,405 - Iter: 24, Total Loss: 0.4707, loss_single: 0.4707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,440 - Iter: 25, Total Loss: 0.4543, loss_single: 0.4543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,475 - Iter: 26, Total Loss: 0.4394, loss_single: 0.4394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,511 - Iter: 27, Total Loss: 0.4282, loss_single: 0.4282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,546 - Iter: 28, Total Loss: 0.4177, loss_single: 0.4177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,581 - Iter: 29, Total Loss: 0.4071, loss_single: 0.4071, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,617 - Iter: 30, Total Loss: 0.3976, loss_single: 0.3976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,652 - Iter: 31, Total Loss: 0.3865, loss_single: 0.3865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,687 - Iter: 32, Total Loss: 0.3758, loss_single: 0.3758, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,722 - Iter: 33, Total Loss: 0.3677, loss_single: 0.3677, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,757 - Iter: 34, Total Loss: 0.3609, loss_single: 0.3609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,793 - Iter: 35, Total Loss: 0.3544, loss_single: 0.3544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,828 - Iter: 36, Total Loss: 0.3485, loss_single: 0.3485, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,863 - Iter: 37, Total Loss: 0.3427, loss_single: 0.3427, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,899 - Iter: 38, Total Loss: 0.3365, loss_single: 0.3365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,934 - Iter: 39, Total Loss: 0.3316, loss_single: 0.3316, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:41,970 - Iter: 40, Total Loss: 0.3263, loss_single: 0.3263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,008 - Iter: 41, Total Loss: 0.3197, loss_single: 0.3197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,043 - Iter: 42, Total Loss: 0.3145, loss_single: 0.3145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,079 - Iter: 43, Total Loss: 0.3112, loss_single: 0.3112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,114 - Iter: 44, Total Loss: 0.3084, loss_single: 0.3084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,149 - Iter: 45, Total Loss: 0.3050, loss_single: 0.3050, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,185 - Iter: 46, Total Loss: 0.3018, loss_single: 0.3018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,220 - Iter: 47, Total Loss: 0.2993, loss_single: 0.2993, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,256 - Iter: 48, Total Loss: 0.2964, loss_single: 0.2964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,291 - Iter: 49, Total Loss: 0.2937, loss_single: 0.2937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,326 - Iter: 50, Total Loss: 0.2912, loss_single: 0.2912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,362 - Iter: 51, Total Loss: 0.2889, loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,397 - Iter: 52, Total Loss: 0.2868, loss_single: 0.2868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,433 - Iter: 53, Total Loss: 0.2846, loss_single: 0.2846, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,469 - Iter: 54, Total Loss: 0.2828, loss_single: 0.2828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,504 - Iter: 55, Total Loss: 0.2814, loss_single: 0.2814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,540 - Iter: 56, Total Loss: 0.2801, loss_single: 0.2801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,575 - Iter: 57, Total Loss: 0.2787, loss_single: 0.2787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,610 - Iter: 58, Total Loss: 0.2776, loss_single: 0.2776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,646 - Iter: 59, Total Loss: 0.2766, loss_single: 0.2766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,681 - Iter: 60, Total Loss: 0.2757, loss_single: 0.2757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,717 - Iter: 61, Total Loss: 0.2750, loss_single: 0.2750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,753 - Iter: 62, Total Loss: 0.2742, loss_single: 0.2742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:34:42,789 - Iter: 63, Total Loss: 0.2734, loss_single: 0.2734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:34:42,824 - Iter: 64, 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/simulation_data1__sample_000002.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/simulation_data1__sample_000002.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7a915093174adcc2288ec6cd24e23b39fa9f35bd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/simulation_data1__sample_000002.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 12.791192054748535 + probe_aberrations: + C10: -4.823992729187012 + C12: 0.3268119692802429 + C21: 134.8209686279297 + C23: 251.00131225585938 + C30: 2393991.0 + C32: -5988.50830078125 + C34: -4476.03076171875 + C41: -304813.3125 + C43: 364127.75 + C45: -97685.359375 + C50: -410699616.0 + C52: -18312922.0 + C54: -17729770.0 + C56: -5185558.0 + phi12: 59.69768383660901 + phi21: 127.13888973904487 + phi23: 21.108124186486833 + phi32: 313.7700112244648 + phi34: 67.07319530995558 + phi41: 327.1123486359778 + phi43: 77.75825445506432 + phi45: 184.9026601536781 + phi52: 64.88032892597714 + phi54: 177.94459618202438 + phi56: 49.277547238837556 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4755619168281555 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000002_measurement.h5 + key: measurement + random_seed: 20261846 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000002 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000002/c30_small__simulation_data1__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-4.82_C12_0.327_phi12_59.7_C21_135_phi21_127_C23_251_phi23_21.1_C30_2.39e+06_C32_-5.99e+03_phi32.3/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_.6/20260624_053508_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:35:07,173 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:35:07,173 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:35:07,173 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:35:07,173 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:35:07,173 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:35:07,173 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:35:07,173 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:35:07,173 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:35:07,173 - +2026-06-24 05:35:07,283 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:35:07,283 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:35:07,283 - Accelerator.num_process = 1 +2026-06-24 05:35:07,283 - Accelerator.mixed_precision = no +2026-06-24 05:35:07,307 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:35:07,307 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:35:07,307 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:35:07,307 - +2026-06-24 05:35:07,307 - ### System information ### +2026-06-24 05:35:07,307 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:35:07,307 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:35:07,307 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:35:07,307 - Machine: x86_64 +2026-06-24 05:35:07,307 - Processor: x86_64 +2026-06-24 05:35:07,307 - Available CPU cores: 8 +2026-06-24 05:35:07,307 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:35:07,307 - +2026-06-24 05:35:07,307 - ### GPU information ### +2026-06-24 05:35:07,307 - CUDA Available: True +2026-06-24 05:35:07,307 - CUDA Version: 13.0 +2026-06-24 05:35:07,308 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:35:07,308 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:35:07,308 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:35:07,308 - In addition, Triton does not directly support Windows. +2026-06-24 05:35:07,308 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:35:07,337 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:35:07,337 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:35:07,337 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:35:07,337 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:35:07,337 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:35:07,337 - +2026-06-24 05:35:07,337 - ### Python information ### +2026-06-24 05:35:07,338 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:35:07,338 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:35:07,338 - +2026-06-24 05:35:07,338 - ### Packages information ### +2026-06-24 05:35:07,338 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:35:07,339 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:35:07,340 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:35:07,340 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:35:07,341 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:35:07,341 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:35:07,341 - +2026-06-24 05:35:07,341 - ### Loading params file ### +2026-06-24 05:35:07,341 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000004.yaml +2026-06-24 05:35:07,348 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:35:07,349 - Success! Params file validated and defaults applied. +2026-06-24 05:35:07,349 - +2026-06-24 05:35:07,349 - ### Setting GPU Device ### +2026-06-24 05:35:07,349 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:35:07,349 - +2026-06-24 05:35:07,349 - Random seed: 20261848 provided by params file +2026-06-24 05:35:07,349 - ### Initializing Initializer ### +2026-06-24 05:35:07,349 - init_params are displayed below: +2026-06-24 05:35:07,350 - random_seed: 20261848 +2026-06-24 05:35:07,350 - probe_illum_type: electron +2026-06-24 05:35:07,350 - probe_kv: 120.0 +2026-06-24 05:35:07,350 - probe_conv_angle: 15.071081161499023 +2026-06-24 05:35:07,350 - probe_aberrations: {'C10': -308.916, 'C12': 0.25, 'phi12': 217.782, 'C21': 883.007, 'phi21': 66.513, 'C23': 292.989, 'phi23': 120.944, 'C30': 3418372.25, 'C32': 775.45, 'phi32': 235.401, 'C34': 11457.985, 'phi34': 78.242, 'C41': 57754.867, 'phi41': 123.47, 'C43': -1213.19, 'phi43': 218.041, 'C45': -325368.656, 'phi45': 168.413, 'C50': 491943200.0, 'C52': 12746455.0, 'phi52': 352.811, 'C54': -13085720.0, 'phi54': 109.581, 'C56': 19757192.0, 'phi56': 45.596} +2026-06-24 05:35:07,350 - beam_kev: None +2026-06-24 05:35:07,350 - probe_dRn: None +2026-06-24 05:35:07,350 - probe_Rn: None +2026-06-24 05:35:07,350 - probe_D_H: None +2026-06-24 05:35:07,350 - probe_D_FZP: None +2026-06-24 05:35:07,350 - probe_Ls: None +2026-06-24 05:35:07,350 - meas_Npix: 128 +2026-06-24 05:35:07,350 - pos_N_scans: 256 +2026-06-24 05:35:07,350 - pos_N_scan_slow: 16 +2026-06-24 05:35:07,350 - pos_N_scan_fast: 16 +2026-06-24 05:35:07,350 - pos_scan_step_size: 0.3673764169216156 +2026-06-24 05:35:07,350 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:35:07,350 - probe_pmode_max: 6 +2026-06-24 05:35:07,350 - probe_pmode_init_pows: [0.02] +2026-06-24 05:35:07,350 - obj_omode_max: 1 +2026-06-24 05:35:07,350 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:35:07,350 - obj_Nlayer: 1 +2026-06-24 05:35:07,350 - obj_slice_thickness: 20.0 +2026-06-24 05:35:07,350 - simu_Npix: None +2026-06-24 05:35:07,350 - simu_match_mode: None +2026-06-24 05:35:07,350 - meas_permute: None +2026-06-24 05:35:07,350 - meas_reshape: [256, 128, 128] +2026-06-24 05:35:07,350 - meas_flipT: [0, 0, 0] +2026-06-24 05:35:07,350 - meas_crop: None +2026-06-24 05:35:07,350 - meas_pad: None +2026-06-24 05:35:07,350 - meas_resample: None +2026-06-24 05:35:07,350 - meas_add_source_size: None +2026-06-24 05:35:07,350 - meas_add_detector_blur: None +2026-06-24 05:35:07,350 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:35:07,350 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:35:07,350 - meas_add_poisson_noise: None +2026-06-24 05:35:07,350 - meas_export: None +2026-06-24 05:35:07,350 - probe_permute: None +2026-06-24 05:35:07,350 - probe_z_shift: None +2026-06-24 05:35:07,350 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:35:07,351 - pos_scan_flipT: None +2026-06-24 05:35:07,351 - pos_scan_affine: None +2026-06-24 05:35:07,351 - pos_scan_rand_std: 0.15 +2026-06-24 05:35:07,351 - obj_z_crop: None +2026-06-24 05:35:07,351 - obj_z_pad: None +2026-06-24 05:35:07,351 - obj_z_resample: None +2026-06-24 05:35:07,351 - meas_source: file +2026-06-24 05:35:07,351 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000004_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:35:07,351 - probe_source: simu +2026-06-24 05:35:07,351 - probe_params: None +2026-06-24 05:35:07,351 - pos_source: simu +2026-06-24 05:35:07,351 - pos_params: None +2026-06-24 05:35:07,351 - obj_source: simu +2026-06-24 05:35:07,351 - obj_params: None +2026-06-24 05:35:07,351 - tilt_source: simu +2026-06-24 05:35:07,351 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:35:07,351 - +2026-06-24 05:35:07,351 - ### Initializing cache ### +2026-06-24 05:35:07,351 - use_cached_obj = False +2026-06-24 05:35:07,351 - use_cached_probe = False +2026-06-24 05:35:07,351 - use_cached_pos = False +2026-06-24 05:35:07,351 - +2026-06-24 05:35:07,351 - ### Initializing measurements ### +2026-06-24 05:35:07,351 - Loading measurements from source = 'file' +2026-06-24 05:35:07,351 - Detected measurement file type = '.h5' +2026-06-24 05:35:07,430 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:35:07,430 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:35:07,432 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0036) +2026-06-24 05:35:07,432 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:35:07,432 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:35:07,434 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:35:07,434 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:35:07,435 - Normalizing by max of the 2D mean pattern intensity: 0.0021835053 +2026-06-24 05:35:07,435 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:35:07,436 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0277, 1.6535) +2026-06-24 05:35:07,437 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:35:07,438 - Pattern total int. statistics (min, mean, max) = (447.2535, 453.0605, 457.8853), with min/max = 97.7% +2026-06-24 05:35:07,440 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0277, 1.6535) +2026-06-24 05:35:07,440 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:35:07,440 - +2026-06-24 05:35:07,440 - ### Setting up calibration ### +2026-06-24 05:35:07,440 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:35:07,440 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:35:07,440 - Radius of fitted bright field disk (RBF) = 11.37 px with meas_Npix = 128 +2026-06-24 05:35:07,440 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1776 +2026-06-24 05:35:07,440 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:35:07,440 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:35:07,663 - Initial guess: center=(63.77, 63.61), radius=11.37, Gaussian blur std=0.50 +2026-06-24 05:35:07,677 - Final fit: center=(63.77, 63.61), radius=11.37, Gaussian blur std=0.68 +2026-06-24 05:35:07,677 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.52 px with Npix = 128 +2026-06-24 05:35:07,677 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:35:07,678 - +2026-06-24 05:35:07,678 - ### Setting init_variables dict ### +2026-06-24 05:35:07,678 - Derived values given input init_params: +2026-06-24 05:35:07,678 - kv = 120.0 kV +2026-06-24 05:35:07,678 - wavelength = 0.0335 Ang +2026-06-24 05:35:07,678 - conv_angle = 15.071081161499023 mrad +2026-06-24 05:35:07,678 - Npix = 128 px +2026-06-24 05:35:07,678 - dk = 0.0391 Ang^-1 +2026-06-24 05:35:07,678 - kMax = 2.5000 Ang^-1 +2026-06-24 05:35:07,678 - da = 1.3083 mrad +2026-06-24 05:35:07,678 - angleMax = 83.7304 mrad +2026-06-24 05:35:07,678 - RBF = 11.5197 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:35:07,678 - n_alpha = 5.5557 (# conv_angle) +2026-06-24 05:35:07,678 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:35:07,678 - Rayleigh-limited resolution = 1.3556 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:35:07,678 - Real space probe extent = 25.6000 Ang +2026-06-24 05:35:07,678 - +2026-06-24 05:35:07,678 - ### Initializing probe ### +2026-06-24 05:35:07,678 - Loading probe from source = 'simu' +2026-06-24 05:35:07,678 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:35:07,678 - Start simulating STEM probe +2026-06-24 05:35:07,678 - kv = 120.0 kV +2026-06-24 05:35:07,678 - wavelength = 0.0335 Ang +2026-06-24 05:35:07,678 - conv_angle = 15.071081161499023 mrad +2026-06-24 05:35:07,678 - Npix = 128 px +2026-06-24 05:35:07,679 - dk = 0.0391 Ang^-1 +2026-06-24 05:35:07,679 - kMax = 2.5000 Ang^-1 +2026-06-24 05:35:07,679 - alpha_max = 83.7304 mrad +2026-06-24 05:35:07,679 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:35:07,679 - Rayleigh-limited resolution = 1.3556 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:35:07,679 - Real space probe extent = 25.6000 Ang +2026-06-24 05:35:07,679 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:35:07,679 - ------------------------------------------------------------------------------------ +2026-06-24 05:35:07,679 - C1,0 C1 -308.9160 - Defocus (C10 = -df) +2026-06-24 05:35:07,679 - C1,2 A1 0.2500 217.78 2-fold astigmatism +2026-06-24 05:35:07,679 - C2,1 3*B2 883.0070 66.51 Axial coma +2026-06-24 05:35:07,679 - C2,3 A2 292.9890 120.94 3-fold astigmatism +2026-06-24 05:35:07,679 - C3,0 C3 3418372.2500 - Spherical aberration +2026-06-24 05:35:07,679 - C3,2 4*S3 775.4500 235.40 Axial star aberration +2026-06-24 05:35:07,679 - C3,4 A3 11457.9850 78.24 4-fold astigmatism +2026-06-24 05:35:07,679 - C4,1 4*B4 57754.8670 123.47 Axial coma(4th) +2026-06-24 05:35:07,679 - C4,3 4*D4 -1213.1900 218.04 3-lobe aberration +2026-06-24 05:35:07,679 - C4,5 A4 -325368.6560 168.41 5-fold astigmatism +2026-06-24 05:35:07,679 - C5,0 C5 491943200.0000 - Spherical aberration (5th) +2026-06-24 05:35:07,679 - C5,2 6*S5 12746455.0000 352.81 Axial star aberration(5th) +2026-06-24 05:35:07,679 - C5,4 6*R5 -13085720.0000 109.58 4-lobe aberration +2026-06-24 05:35:07,679 - C5,6 A5 19757192.0000 45.60 6-fold astigmatism +2026-06-24 05:35:07,682 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:35:07,682 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:35:07,682 - Creating 5 new probe modes from the major mode +2026-06-24 05:35:07,682 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:35:07,852 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:35:07,853 - Orthogonalizing 6 pmodes +2026-06-24 05:35:07,855 - Sorting 6 pmodes by their intensities +2026-06-24 05:35:07,855 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:35:07,856 - sum(|probe_data|**2) = 453.06, while meas_total_ints (min, mean, max) = (447.2535, 453.0605, 457.8853) +2026-06-24 05:35:07,856 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:35:07,856 - +2026-06-24 05:35:07,856 - ### Initializing probe positions ### +2026-06-24 05:35:07,856 - Loading probe positions from source = 'simu' +2026-06-24 05:35:07,856 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:35:07,856 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3674, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:35:07,856 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:35:07,859 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:35:07,859 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 05:35:07,859 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:35:07,859 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:35:07,859 - +2026-06-24 05:35:07,859 - ### Initializing object ### +2026-06-24 05:35:07,859 - Loading object from source = 'simu' +2026-06-24 05:35:07,859 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:35:07,860 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:35:07,861 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 05:35:07,861 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 05:35:07,861 - +2026-06-24 05:35:07,861 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:35:07,861 - omode_occu (omode) = float32, (1,) +2026-06-24 05:35:07,861 - +2026-06-24 05:35:07,861 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:35:07,861 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 05:35:07,862 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:35:07,862 - +2026-06-24 05:35:07,862 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:35:07,862 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:35:07,862 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:35:07,862 - +2026-06-24 05:35:07,862 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:35:07,862 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:35:07,862 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:35:07,862 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:35:07,862 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:35:07,862 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 05:35:07,862 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:35:07,862 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:35:07,862 - +2026-06-24 05:35:07,862 - ### Collecting reconstruction provenance ### +2026-06-24 05:35:07,862 - Reconstruction provenance is collected and initialized. +2026-06-24 05:35:07,862 - +2026-06-24 05:35:07,862 - ### Initializing loss function ### +2026-06-24 05:35:07,862 - Active loss types: +2026-06-24 05:35:07,863 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:35:07,863 - +2026-06-24 05:35:07,863 - ### Initializing constraint function ### +2026-06-24 05:35:07,863 - Active constraint types: +2026-06-24 05:35:07,863 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:35:07,863 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:35:07,863 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:35:07,863 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:35:07,863 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:35:07,863 - +2026-06-24 05:35:07,863 - ### Done initializing PtyRADSolver ### +2026-06-24 05:35:07,863 - +2026-06-24 05:35:07,987 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:35:07,987 - +2026-06-24 05:35:07,987 - ### Initializing PtychoModel model ### +2026-06-24 05:35:08,059 - ### PtychoModel optimizable variables ### +2026-06-24 05:35:08,059 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:08,059 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:08,059 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:35:08,059 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:35:08,059 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:35:08,059 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:08,060 - +2026-06-24 05:35:08,060 - ### Optimizable variables statitsics ### +2026-06-24 05:35:08,060 - Total measurement values : 4,194,304 +2026-06-24 05:35:08,060 - Total optimizing variables: 267,808 +2026-06-24 05:35:08,060 - Overdetermined ratio : 15.66 +2026-06-24 05:35:08,060 - +2026-06-24 05:35:08,060 - ### Model behavior ### +2026-06-24 05:35:08,060 - Tilt propagator : False +2026-06-24 05:35:08,060 - Change slice thickness : False +2026-06-24 05:35:08,060 - Detector blur : False +2026-06-24 05:35:08,060 - Preload data : True +2026-06-24 05:35:08,060 - On-the-fly meas padding : False +2026-06-24 05:35:08,060 - On-the-fly meas resample : False +2026-06-24 05:35:08,060 - On-the-fly simu match mode: None +2026-06-24 05:35:08,060 - +2026-06-24 05:35:08,101 - ### Done initializing PtychoModel model ### +2026-06-24 05:35:08,102 - +2026-06-24 05:35:08,102 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:35:08,102 - +2026-06-24 05:35:08,102 - ### Generating indices, batches, and output_path ### +2026-06-24 05:35:08,103 - d90 = 57.000 px or 11.400 Ang +2026-06-24 05:35:08,103 - Selecting indices with the 'full' mode +2026-06-24 05:35:08,558 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:35:08,630 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:35:08,630 - Original recon_dir_affixes = ['default'] +2026-06-24 05:35:08,630 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:35:08,636 - Path corrected for compatibility: +2026-06-24 05:35:08,636 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_1.15e+04_phi34_78.2_C41_5.78e+04_phi41_123_C43_-1.21e+03_phi43_218_C45_-3.25e+05_phi45_168_C50_4.92e+08_C52_1.27e+07_phi52_353_C54_-1.31e+07_phi54_110_C56_1.98e+07_phi56_45.6 +2026-06-24 05:35:08,636 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_.6 +2026-06-24 05:35:08,637 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_.6' is generated! +2026-06-24 05:35:08,789 - +2026-06-24 05:35:08,790 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_.6/20260624_053508_ptyrad_log.txt ### +2026-06-24 05:35:08,790 - +2026-06-24 05:35:08,792 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:35:08,792 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:35:08,792 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:35:09,986 - Iter: 1, Total Loss: 1.0463, loss_single: 1.0463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.441 sec +2026-06-24 05:35:10,023 - Iter: 2, Total Loss: 1.0182, loss_single: 1.0182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:35:10,059 - Iter: 3, Total Loss: 0.9947, loss_single: 0.9947, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,095 - Iter: 4, Total Loss: 0.9718, loss_single: 0.9718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,130 - Iter: 5, Total Loss: 0.9497, loss_single: 0.9497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,165 - Iter: 6, Total Loss: 0.9293, loss_single: 0.9293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,201 - Iter: 7, Total Loss: 0.9071, loss_single: 0.9071, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:35:10,237 - Iter: 8, Total Loss: 0.8827, loss_single: 0.8827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,272 - Iter: 9, Total Loss: 0.8579, loss_single: 0.8579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,308 - Iter: 10, Total Loss: 0.8315, loss_single: 0.8315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,343 - Iter: 11, Total Loss: 0.8068, loss_single: 0.8068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,379 - Iter: 12, Total Loss: 0.7830, loss_single: 0.7830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,414 - Iter: 13, Total Loss: 0.7590, loss_single: 0.7590, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,450 - Iter: 14, Total Loss: 0.7358, loss_single: 0.7358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,485 - Iter: 15, Total Loss: 0.7123, loss_single: 0.7123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,521 - Iter: 16, Total Loss: 0.6890, loss_single: 0.6890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,556 - Iter: 17, Total Loss: 0.6661, loss_single: 0.6661, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,592 - Iter: 18, Total Loss: 0.6433, loss_single: 0.6433, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,627 - Iter: 19, Total Loss: 0.6224, loss_single: 0.6224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,662 - Iter: 20, Total Loss: 0.6038, loss_single: 0.6038, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,715 - Iter: 21, Total Loss: 0.5867, loss_single: 0.5867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,750 - Iter: 22, Total Loss: 0.5696, loss_single: 0.5696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,786 - Iter: 23, Total Loss: 0.5533, loss_single: 0.5533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,821 - Iter: 24, Total Loss: 0.5378, loss_single: 0.5378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,857 - Iter: 25, Total Loss: 0.5234, loss_single: 0.5234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,892 - Iter: 26, Total Loss: 0.5097, loss_single: 0.5097, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,928 - Iter: 27, Total Loss: 0.4958, loss_single: 0.4958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,963 - Iter: 28, Total Loss: 0.4832, loss_single: 0.4832, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:10,999 - Iter: 29, Total Loss: 0.4717, loss_single: 0.4717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,034 - Iter: 30, Total Loss: 0.4618, loss_single: 0.4618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,069 - Iter: 31, Total Loss: 0.4532, loss_single: 0.4532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,105 - Iter: 32, Total Loss: 0.4449, loss_single: 0.4449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,140 - Iter: 33, Total Loss: 0.4375, loss_single: 0.4375, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,176 - Iter: 34, Total Loss: 0.4309, loss_single: 0.4309, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,212 - Iter: 35, Total Loss: 0.4248, loss_single: 0.4248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,247 - Iter: 36, Total Loss: 0.4195, loss_single: 0.4195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,283 - Iter: 37, Total Loss: 0.4151, loss_single: 0.4151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,318 - Iter: 38, Total Loss: 0.4113, loss_single: 0.4113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,353 - Iter: 39, Total Loss: 0.4080, loss_single: 0.4080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:35:11,388 - Iter: 40, Total Loss: 0.4052, loss_single: 0.4052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,426 - Iter: 41, Total Loss: 0.4027, loss_single: 0.4027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:35:11,461 - Iter: 42, Total Loss: 0.4004, loss_single: 0.4004, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,497 - Iter: 43, Total Loss: 0.3984, loss_single: 0.3984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,532 - Iter: 44, Total Loss: 0.3968, loss_single: 0.3968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,568 - Iter: 45, Total Loss: 0.3954, loss_single: 0.3954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,603 - Iter: 46, Total Loss: 0.3942, loss_single: 0.3942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,638 - Iter: 47, Total Loss: 0.3932, loss_single: 0.3932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,673 - Iter: 48, Total Loss: 0.3924, loss_single: 0.3924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,708 - Iter: 49, Total Loss: 0.3919, loss_single: 0.3919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,744 - Iter: 50, Total Loss: 0.3912, loss_single: 0.3912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,779 - Iter: 51, Total Loss: 0.3906, loss_single: 0.3906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:11,814 - Iter: 52, Total Loss: 0.3900, loss_single: 0.3900, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,060 - Iter: 59, Total Loss: 0.3867, loss_single: 0.3867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,096 - Iter: 60, Total Loss: 0.3863, loss_single: 0.3863, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,132 - Iter: 61, Total Loss: 0.3859, loss_single: 0.3859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,167 - Iter: 62, Total Loss: 0.3855, loss_single: 0.3855, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,202 - Iter: 63, Total Loss: 0.3852, loss_single: 0.3852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,238 - Iter: 64, 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in 0.035 sec +2026-06-24 05:35:12,450 - Iter: 70, Total Loss: 0.3829, loss_single: 0.3829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,485 - Iter: 71, Total Loss: 0.3825, loss_single: 0.3825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,521 - Iter: 72, Total Loss: 0.3822, loss_single: 0.3822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,556 - Iter: 73, Total Loss: 0.3819, loss_single: 0.3819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,591 - Iter: 74, Total Loss: 0.3816, loss_single: 0.3816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,627 - Iter: 75, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,873 - Iter: 82, Total Loss: 0.3791, loss_single: 0.3791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,908 - Iter: 83, Total Loss: 0.3788, loss_single: 0.3788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,943 - Iter: 84, Total Loss: 0.3785, loss_single: 0.3785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:12,979 - Iter: 85, Total Loss: 0.3782, loss_single: 0.3782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,014 - Iter: 86, Total Loss: 0.3779, loss_single: 0.3779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,049 - Iter: 87, Total Loss: 0.3776, loss_single: 0.3776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,084 - Iter: 88, Total Loss: 0.3773, loss_single: 0.3773, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,120 - Iter: 89, Total Loss: 0.3770, loss_single: 0.3770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,155 - Iter: 90, Total Loss: 0.3767, loss_single: 0.3767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,193 - Iter: 91, Total Loss: 0.3765, loss_single: 0.3765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:35:13,228 - Iter: 92, Total Loss: 0.3762, loss_single: 0.3762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,264 - Iter: 93, Total Loss: 0.3759, loss_single: 0.3759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,299 - Iter: 94, Total Loss: 0.3756, loss_single: 0.3756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,335 - Iter: 95, Total Loss: 0.3753, loss_single: 0.3753, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,370 - Iter: 96, Total Loss: 0.3751, loss_single: 0.3751, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,406 - Iter: 97, Total Loss: 0.3748, loss_single: 0.3748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,441 - Iter: 98, Total Loss: 0.3745, loss_single: 0.3745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,476 - Iter: 99, Total Loss: 0.3742, loss_single: 0.3742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,512 - Iter: 100, Total Loss: 0.3739, loss_single: 0.3739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:13,623 - Saving summary figures for iter 100 +2026-06-24 05:35:17,253 - ### Finished 100 iterations, averaged iter_t = 0.039048 with std = 0.040 ### +2026-06-24 05:35:17,254 - +2026-06-24 05:35:17,254 - ### The PtyRADSolver is finished in 9.267 sec ### +2026-06-24 05:35:17,254 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000004/c30_small__simulation_data1__sample_000004_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-309_C12_0.25_phi12_218_C21_883_phi21_66.5_C23_293_phi23_121_C30_3.42e+06_C32_775_phi32_235_C34_.6/simulation_data1__sample_000004.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 15.071081161499023 + probe_aberrations: + C10: -308.9161682128906 + C12: 0.24956321716308594 + C21: 883.0072021484375 + C23: 292.9891357421875 + C30: 3418372.25 + C32: 775.450439453125 + C34: 11457.9853515625 + C41: 57754.8671875 + C43: -1213.1898193359375 + C45: -325368.65625 + C50: 491943200.0 + C52: 12746455.0 + C54: -13085720.0 + C56: 19757192.0 + phi12: 217.78222093125737 + phi21: 66.5133520244463 + phi23: 120.94399012411334 + phi32: 235.40126763119554 + phi34: 78.24228264078644 + phi41: 123.46997166410247 + phi43: 218.0407982328557 + phi45: 168.41271202543476 + phi52: 352.81123591647423 + phi54: 109.58061806234147 + phi56: 45.59583621957973 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3673764169216156 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000004_measurement.h5 + key: measurement + random_seed: 20261848 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:81ab10eefec4855cb0e6bd369da2ea9a3556e7f80f6dff06c3a795920c940c4b +size 47837 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/20260624_053538_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/20260624_053538_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..4282714aecb67dfe488380e095ffd594bb4d12dd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/20260624_053538_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:35:36,649 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:35:36,649 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:35:36,649 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:35:36,649 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:35:36,649 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:35:36,649 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:35:36,649 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:35:36,649 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:35:36,649 - +2026-06-24 05:35:36,754 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:35:36,754 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:35:36,754 - Accelerator.num_process = 1 +2026-06-24 05:35:36,754 - Accelerator.mixed_precision = no +2026-06-24 05:35:36,765 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:35:36,765 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:35:36,765 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:35:36,765 - +2026-06-24 05:35:36,765 - ### System information ### +2026-06-24 05:35:36,765 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:35:36,765 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:35:36,765 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:35:36,765 - Machine: x86_64 +2026-06-24 05:35:36,766 - Processor: x86_64 +2026-06-24 05:35:36,766 - Available CPU cores: 8 +2026-06-24 05:35:36,766 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:35:36,766 - +2026-06-24 05:35:36,766 - ### GPU information ### +2026-06-24 05:35:36,766 - CUDA Available: True +2026-06-24 05:35:36,766 - CUDA Version: 13.0 +2026-06-24 05:35:36,766 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:35:36,766 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:35:36,766 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:35:36,766 - In addition, Triton does not directly support Windows. +2026-06-24 05:35:36,766 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:35:36,794 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:35:36,794 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:35:36,794 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:35:36,794 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:35:36,794 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:35:36,794 - +2026-06-24 05:35:36,794 - ### Python information ### +2026-06-24 05:35:36,796 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:35:36,796 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:35:36,796 - +2026-06-24 05:35:36,796 - ### Packages information ### +2026-06-24 05:35:36,797 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:35:36,797 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:35:36,798 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:35:36,799 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:35:36,799 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:35:36,799 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:35:36,799 - +2026-06-24 05:35:36,799 - ### Loading params file ### +2026-06-24 05:35:36,799 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000006.yaml +2026-06-24 05:35:36,806 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:35:36,807 - Success! Params file validated and defaults applied. +2026-06-24 05:35:36,807 - +2026-06-24 05:35:36,807 - ### Setting GPU Device ### +2026-06-24 05:35:36,807 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:35:36,807 - +2026-06-24 05:35:36,807 - Random seed: 20261850 provided by params file +2026-06-24 05:35:36,808 - ### Initializing Initializer ### +2026-06-24 05:35:36,808 - init_params are displayed below: +2026-06-24 05:35:36,808 - random_seed: 20261850 +2026-06-24 05:35:36,808 - probe_illum_type: electron +2026-06-24 05:35:36,808 - probe_kv: 100.0 +2026-06-24 05:35:36,808 - probe_conv_angle: 12.753067016601562 +2026-06-24 05:35:36,808 - probe_aberrations: {'C10': 13.468, 'C12': -30.276, 'phi12': 57.833, 'C21': 906.579, 'phi21': 174.005, 'C23': -612.995, 'phi23': 112.89, 'C30': 2811631.5, 'C32': -2623.853, 'phi32': 300.321, 'C34': 676.396, 'phi34': 209.604, 'C41': -310396.312, 'phi41': 107.555, 'C43': -289293.562, 'phi43': 60.982, 'C45': -353779.719, 'phi45': 42.212, 'C50': -19880760.0, 'C52': 17803310.0, 'phi52': 185.556, 'C54': 4128458.75, 'phi54': 17.824, 'C56': -9667259.0, 'phi56': 2.063} +2026-06-24 05:35:36,808 - beam_kev: None +2026-06-24 05:35:36,808 - probe_dRn: None +2026-06-24 05:35:36,808 - probe_Rn: None +2026-06-24 05:35:36,808 - probe_D_H: None +2026-06-24 05:35:36,808 - probe_D_FZP: None +2026-06-24 05:35:36,808 - probe_Ls: None +2026-06-24 05:35:36,808 - meas_Npix: 128 +2026-06-24 05:35:36,808 - pos_N_scans: 256 +2026-06-24 05:35:36,808 - pos_N_scan_slow: 16 +2026-06-24 05:35:36,808 - pos_N_scan_fast: 16 +2026-06-24 05:35:36,808 - pos_scan_step_size: 0.37385937571525574 +2026-06-24 05:35:36,808 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:35:36,808 - probe_pmode_max: 6 +2026-06-24 05:35:36,808 - probe_pmode_init_pows: [0.02] +2026-06-24 05:35:36,808 - obj_omode_max: 1 +2026-06-24 05:35:36,809 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:35:36,809 - obj_Nlayer: 1 +2026-06-24 05:35:36,809 - obj_slice_thickness: 20.0 +2026-06-24 05:35:36,809 - simu_Npix: None +2026-06-24 05:35:36,809 - simu_match_mode: None +2026-06-24 05:35:36,809 - meas_permute: None +2026-06-24 05:35:36,809 - meas_reshape: [256, 128, 128] +2026-06-24 05:35:36,809 - meas_flipT: [0, 0, 0] +2026-06-24 05:35:36,809 - meas_crop: None +2026-06-24 05:35:36,809 - meas_pad: None +2026-06-24 05:35:36,809 - meas_resample: None +2026-06-24 05:35:36,809 - meas_add_source_size: None +2026-06-24 05:35:36,809 - meas_add_detector_blur: None +2026-06-24 05:35:36,809 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:35:36,809 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:35:36,809 - meas_add_poisson_noise: None +2026-06-24 05:35:36,809 - meas_export: None +2026-06-24 05:35:36,809 - probe_permute: None +2026-06-24 05:35:36,809 - probe_z_shift: None +2026-06-24 05:35:36,809 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:35:36,809 - pos_scan_flipT: None +2026-06-24 05:35:36,809 - pos_scan_affine: None +2026-06-24 05:35:36,809 - pos_scan_rand_std: 0.15 +2026-06-24 05:35:36,809 - obj_z_crop: None +2026-06-24 05:35:36,809 - obj_z_pad: None +2026-06-24 05:35:36,809 - obj_z_resample: None +2026-06-24 05:35:36,809 - meas_source: file +2026-06-24 05:35:36,809 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000006_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:35:36,809 - probe_source: simu +2026-06-24 05:35:36,809 - probe_params: None +2026-06-24 05:35:36,809 - pos_source: simu +2026-06-24 05:35:36,809 - pos_params: None +2026-06-24 05:35:36,809 - obj_source: simu +2026-06-24 05:35:36,809 - obj_params: None +2026-06-24 05:35:36,809 - tilt_source: simu +2026-06-24 05:35:36,809 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:35:36,809 - +2026-06-24 05:35:36,809 - ### Initializing cache ### +2026-06-24 05:35:36,809 - use_cached_obj = False +2026-06-24 05:35:36,810 - use_cached_probe = False +2026-06-24 05:35:36,810 - use_cached_pos = False +2026-06-24 05:35:36,810 - +2026-06-24 05:35:36,810 - ### Initializing measurements ### +2026-06-24 05:35:36,810 - Loading measurements from source = 'file' +2026-06-24 05:35:36,810 - Detected measurement file type = '.h5' +2026-06-24 05:35:36,889 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:35:36,889 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:35:36,891 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0055) +2026-06-24 05:35:36,891 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:35:36,891 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:35:36,892 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:35:36,892 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:35:36,893 - Normalizing by max of the 2D mean pattern intensity: 0.0034246303 +2026-06-24 05:35:36,894 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:35:36,895 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.6097) +2026-06-24 05:35:36,895 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:35:36,897 - Pattern total int. statistics (min, mean, max) = (284.3222, 287.9081, 290.7194), with min/max = 97.8% +2026-06-24 05:35:36,898 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.6097) +2026-06-24 05:35:36,898 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:35:36,898 - +2026-06-24 05:35:36,898 - ### Setting up calibration ### +2026-06-24 05:35:36,898 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:35:36,898 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:35:36,898 - Radius of fitted bright field disk (RBF) = 8.72 px with meas_Npix = 128 +2026-06-24 05:35:36,898 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1363 +2026-06-24 05:35:36,898 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:35:36,898 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:35:37,120 - Initial guess: center=(63.64, 63.62), radius=8.72, Gaussian blur std=0.50 +2026-06-24 05:35:37,134 - Final fit: center=(63.64, 63.62), radius=8.72, Gaussian blur std=0.78 +2026-06-24 05:35:37,134 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.82 px with Npix = 128 +2026-06-24 05:35:37,134 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:35:37,134 - +2026-06-24 05:35:37,134 - ### Setting init_variables dict ### +2026-06-24 05:35:37,134 - Derived values given input init_params: +2026-06-24 05:35:37,134 - kv = 100.0 kV +2026-06-24 05:35:37,134 - wavelength = 0.0370 Ang +2026-06-24 05:35:37,134 - conv_angle = 12.753067016601562 mrad +2026-06-24 05:35:37,134 - Npix = 128 px +2026-06-24 05:35:37,134 - dk = 0.0391 Ang^-1 +2026-06-24 05:35:37,135 - kMax = 2.5000 Ang^-1 +2026-06-24 05:35:37,135 - da = 1.4459 mrad +2026-06-24 05:35:37,135 - angleMax = 92.5359 mrad +2026-06-24 05:35:37,135 - RBF = 8.8203 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:35:37,135 - n_alpha = 7.2560 (# conv_angle) +2026-06-24 05:35:37,135 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:35:37,135 - Rayleigh-limited resolution = 1.7705 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:35:37,135 - Real space probe extent = 25.6000 Ang +2026-06-24 05:35:37,135 - +2026-06-24 05:35:37,135 - ### Initializing probe ### +2026-06-24 05:35:37,135 - Loading probe from source = 'simu' +2026-06-24 05:35:37,135 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:35:37,135 - Start simulating STEM probe +2026-06-24 05:35:37,135 - kv = 100.0 kV +2026-06-24 05:35:37,135 - wavelength = 0.0370 Ang +2026-06-24 05:35:37,135 - conv_angle = 12.753067016601562 mrad +2026-06-24 05:35:37,135 - Npix = 128 px +2026-06-24 05:35:37,135 - dk = 0.0391 Ang^-1 +2026-06-24 05:35:37,135 - kMax = 2.5000 Ang^-1 +2026-06-24 05:35:37,135 - alpha_max = 92.5359 mrad +2026-06-24 05:35:37,135 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:35:37,135 - Rayleigh-limited resolution = 1.7705 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:35:37,135 - Real space probe extent = 25.6000 Ang +2026-06-24 05:35:37,135 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:35:37,136 - ------------------------------------------------------------------------------------ +2026-06-24 05:35:37,136 - C1,0 C1 13.4680 - Defocus (C10 = -df) +2026-06-24 05:35:37,136 - C1,2 A1 -30.2760 57.83 2-fold astigmatism +2026-06-24 05:35:37,136 - C2,1 3*B2 906.5790 174.00 Axial coma +2026-06-24 05:35:37,136 - C2,3 A2 -612.9950 112.89 3-fold astigmatism +2026-06-24 05:35:37,136 - C3,0 C3 2811631.5000 - Spherical aberration +2026-06-24 05:35:37,136 - C3,2 4*S3 -2623.8530 300.32 Axial star aberration +2026-06-24 05:35:37,136 - C3,4 A3 676.3960 209.60 4-fold astigmatism +2026-06-24 05:35:37,136 - C4,1 4*B4 -310396.3120 107.56 Axial coma(4th) +2026-06-24 05:35:37,136 - C4,3 4*D4 -289293.5620 60.98 3-lobe aberration +2026-06-24 05:35:37,136 - C4,5 A4 -353779.7190 42.21 5-fold astigmatism +2026-06-24 05:35:37,136 - C5,0 C5 -19880760.0000 - Spherical aberration (5th) +2026-06-24 05:35:37,136 - C5,2 6*S5 17803310.0000 185.56 Axial star aberration(5th) +2026-06-24 05:35:37,136 - C5,4 6*R5 4128458.7500 17.82 4-lobe aberration +2026-06-24 05:35:37,136 - C5,6 A5 -9667259.0000 2.06 6-fold astigmatism +2026-06-24 05:35:37,139 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:35:37,139 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:35:37,139 - Creating 5 new probe modes from the major mode +2026-06-24 05:35:37,139 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:35:37,332 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:35:37,333 - Orthogonalizing 6 pmodes +2026-06-24 05:35:37,335 - Sorting 6 pmodes by their intensities +2026-06-24 05:35:37,336 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:35:37,337 - sum(|probe_data|**2) = 287.91, while meas_total_ints (min, mean, max) = (284.3222, 287.9081, 290.7194) +2026-06-24 05:35:37,337 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:35:37,337 - +2026-06-24 05:35:37,337 - ### Initializing probe positions ### +2026-06-24 05:35:37,337 - Loading probe positions from source = 'simu' +2026-06-24 05:35:37,337 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:35:37,337 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3739, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:35:37,337 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:35:37,339 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:35:37,339 - crop_pos 1st and last px coords (y,x) = ([16, 16], [44, 44]) +2026-06-24 05:35:37,339 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:35:37,339 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:35:37,339 - +2026-06-24 05:35:37,339 - ### Initializing object ### +2026-06-24 05:35:37,339 - Loading object from source = 'simu' +2026-06-24 05:35:37,339 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:35:37,341 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:35:37,341 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 05:35:37,341 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 05:35:37,341 - +2026-06-24 05:35:37,341 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:35:37,341 - omode_occu (omode) = float32, (1,) +2026-06-24 05:35:37,341 - +2026-06-24 05:35:37,341 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:35:37,341 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 05:35:37,342 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:35:37,342 - +2026-06-24 05:35:37,342 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:35:37,342 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:35:37,342 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:35:37,342 - +2026-06-24 05:35:37,342 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:35:37,342 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:35:37,342 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:35:37,342 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:35:37,342 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:35:37,342 - crop positions (yx_min=[16 16], yx_max=[172 172]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 05:35:37,342 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:35:37,343 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:35:37,343 - +2026-06-24 05:35:37,343 - ### Collecting reconstruction provenance ### +2026-06-24 05:35:37,343 - Reconstruction provenance is collected and initialized. +2026-06-24 05:35:37,343 - +2026-06-24 05:35:37,343 - ### Initializing loss function ### +2026-06-24 05:35:37,343 - Active loss types: +2026-06-24 05:35:37,343 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:35:37,343 - +2026-06-24 05:35:37,343 - ### Initializing constraint function ### +2026-06-24 05:35:37,343 - Active constraint types: +2026-06-24 05:35:37,343 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:35:37,343 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:35:37,343 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:35:37,343 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:35:37,343 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:35:37,343 - +2026-06-24 05:35:37,343 - ### Done initializing PtyRADSolver ### +2026-06-24 05:35:37,343 - +2026-06-24 05:35:37,469 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:35:37,469 - +2026-06-24 05:35:37,470 - ### Initializing PtychoModel model ### +2026-06-24 05:35:37,540 - ### PtychoModel optimizable variables ### +2026-06-24 05:35:37,541 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:37,541 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:37,541 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:35:37,541 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:35:37,541 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:35:37,541 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:35:37,541 - +2026-06-24 05:35:37,541 - ### Optimizable variables statitsics ### +2026-06-24 05:35:37,541 - Total measurement values : 4,194,304 +2026-06-24 05:35:37,541 - Total optimizing variables: 267,808 +2026-06-24 05:35:37,541 - Overdetermined ratio : 15.66 +2026-06-24 05:35:37,541 - +2026-06-24 05:35:37,541 - ### Model behavior ### +2026-06-24 05:35:37,541 - Tilt propagator : False +2026-06-24 05:35:37,541 - Change slice thickness : False +2026-06-24 05:35:37,541 - Detector blur : False +2026-06-24 05:35:37,541 - Preload data : True +2026-06-24 05:35:37,541 - On-the-fly meas padding : False +2026-06-24 05:35:37,541 - On-the-fly meas resample : False +2026-06-24 05:35:37,541 - On-the-fly simu match mode: None +2026-06-24 05:35:37,541 - +2026-06-24 05:35:37,582 - ### Done initializing PtychoModel model ### +2026-06-24 05:35:37,582 - +2026-06-24 05:35:37,583 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:35:37,583 - +2026-06-24 05:35:37,583 - ### Generating indices, batches, and output_path ### +2026-06-24 05:35:37,584 - d90 = 57.000 px or 11.400 Ang +2026-06-24 05:35:37,584 - Selecting indices with the 'full' mode +2026-06-24 05:35:38,051 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:35:38,124 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:35:38,124 - Original recon_dir_affixes = ['default'] +2026-06-24 05:35:38,124 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:35:38,130 - Path corrected for compatibility: +2026-06-24 05:35:38,130 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32_300_C34_676_phi34_210_C41_-3.1e+05_phi41_108_C43_-2.89e+05_phi43_61_C45_-3.54e+05_phi45_42.2_C50_-1.99e+07_C52_1.78e+07_phi52_186_C54_4.13e+06_phi54_17.8_C56_-9.67e+06_phi56_2.06 +2026-06-24 05:35:38,130 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06 +2026-06-24 05:35:38,132 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06' is generated! +2026-06-24 05:35:38,278 - +2026-06-24 05:35:38,279 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/20260624_053538_ptyrad_log.txt ### +2026-06-24 05:35:38,279 - +2026-06-24 05:35:38,281 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:35:38,281 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:35:38,281 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:35:39,475 - Iter: 1, Total Loss: 1.1613, loss_single: 1.1613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:35:39,512 - Iter: 2, Total Loss: 1.1273, loss_single: 1.1273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:35:39,548 - Iter: 3, Total Loss: 1.0952, loss_single: 1.0952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,583 - Iter: 4, Total Loss: 1.0668, loss_single: 1.0668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,618 - Iter: 5, Total Loss: 1.0430, loss_single: 1.0430, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,653 - Iter: 6, Total Loss: 1.0186, loss_single: 1.0186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,689 - Iter: 7, Total Loss: 0.9935, loss_single: 0.9935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,724 - Iter: 8, Total Loss: 0.9708, loss_single: 0.9708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,759 - Iter: 9, Total Loss: 0.9497, loss_single: 0.9497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,794 - Iter: 10, Total Loss: 0.9265, loss_single: 0.9265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,829 - Iter: 11, Total Loss: 0.9039, loss_single: 0.9039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,864 - Iter: 12, Total Loss: 0.8820, loss_single: 0.8820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,900 - Iter: 13, Total Loss: 0.8592, loss_single: 0.8592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:35:39,935 - Iter: 14, Total Loss: 0.8341, loss_single: 0.8341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:39,971 - Iter: 15, Total Loss: 0.8085, loss_single: 0.8085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,006 - Iter: 16, Total Loss: 0.7852, loss_single: 0.7852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,041 - Iter: 17, Total Loss: 0.7626, loss_single: 0.7626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,077 - Iter: 18, Total Loss: 0.7376, loss_single: 0.7376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,112 - Iter: 19, Total Loss: 0.7110, loss_single: 0.7110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,148 - Iter: 20, Total Loss: 0.6893, loss_single: 0.6893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,183 - Iter: 21, Total Loss: 0.6689, loss_single: 0.6689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,218 - Iter: 22, Total Loss: 0.6505, loss_single: 0.6505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,254 - Iter: 23, Total Loss: 0.6355, loss_single: 0.6355, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,289 - Iter: 24, Total Loss: 0.6166, loss_single: 0.6166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,324 - Iter: 25, Total Loss: 0.5999, loss_single: 0.5999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:40,359 - Iter: 26, Total Loss: 0.5858, loss_single: 0.5858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:35:40,397 - Iter: 27, Total Loss: 0.5696, loss_single: 0.5696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:35:40,433 - Iter: 28, Total Loss: 0.5563, loss_single: 0.5563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:35:40,468 - 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Iter: 89, Total Loss: 0.3993, loss_single: 0.3993, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,645 - Iter: 90, Total Loss: 0.3990, loss_single: 0.3990, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:35:42,681 - Iter: 91, Total Loss: 0.3987, loss_single: 0.3987, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,718 - Iter: 92, Total Loss: 0.3984, loss_single: 0.3984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:35:42,754 - Iter: 93, Total Loss: 0.3981, loss_single: 0.3981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,789 - Iter: 94, Total Loss: 0.3978, loss_single: 0.3978, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,824 - Iter: 95, Total Loss: 0.3975, loss_single: 0.3975, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,860 - Iter: 96, Total Loss: 0.3972, loss_single: 0.3972, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,895 - Iter: 97, Total Loss: 0.3969, loss_single: 0.3969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,931 - Iter: 98, Total Loss: 0.3966, loss_single: 0.3966, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:42,966 - Iter: 99, Total Loss: 0.3963, loss_single: 0.3963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:43,001 - Iter: 100, Total Loss: 0.3959, loss_single: 0.3959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:35:43,115 - Saving summary figures for iter 100 +2026-06-24 05:35:46,825 - ### Finished 100 iterations, averaged iter_t = 0.038995 with std = 0.040 ### +2026-06-24 05:35:46,825 - +2026-06-24 05:35:46,825 - ### The PtyRADSolver is finished in 9.356 sec ### +2026-06-24 05:35:46,825 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..2339ee51858b763676eb2ed9410632dcf8fb5756 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/simulation_data1__sample_000006.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/simulation_data1__sample_000006.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7daf0f475573a4675f116ef9cdd0302c7d26b271 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006/c30_small__simulation_data1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_13.5_C12_-30.3_phi12_57.8_C21_907_phi21_174_C23_-613_phi23_113_C30_2.81e+06_C32_-2.62e+03_phi32.06/simulation_data1__sample_000006.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 12.753067016601562 + probe_aberrations: + C10: 13.468389511108398 + C12: -30.27562141418457 + C21: 906.5794067382812 + C23: -612.9951171875 + C30: 2811631.5 + C32: -2623.8525390625 + C34: 676.3961791992188 + C41: -310396.3125 + C43: -289293.5625 + C45: -353779.71875 + C50: -19880760.0 + C52: 17803310.0 + C54: 4128458.75 + C56: -9667259.0 + phi12: 57.8331173252764 + phi21: 174.0047518234643 + phi23: 112.89017256429281 + phi32: 300.3208769750894 + phi34: 209.6041349096776 + phi41: 107.55490689792074 + phi43: 60.9820121175707 + phi45: 42.21222197645795 + phi52: 185.55604971005988 + phi54: 17.823547686330233 + phi56: 2.0629896965804164 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37385937571525574 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000006_measurement.h5 + key: measurement + random_seed: 20261850 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000006 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000006 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/20260624_053608_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/20260624_053608_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..36b0b812edf8b63d48df01dae3bc49a5a7fcb9b2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/20260624_053608_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:36:06,341 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:36:06,342 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:36:06,342 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:36:06,342 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:36:06,342 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:36:06,342 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:36:06,342 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:36:06,342 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:36:06,342 - +2026-06-24 05:36:06,449 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:36:06,449 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:36:06,449 - Accelerator.num_process = 1 +2026-06-24 05:36:06,449 - Accelerator.mixed_precision = no +2026-06-24 05:36:06,471 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:36:06,471 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:36:06,471 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:36:06,471 - +2026-06-24 05:36:06,471 - ### System information ### +2026-06-24 05:36:06,471 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:36:06,471 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:36:06,471 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:36:06,471 - Machine: x86_64 +2026-06-24 05:36:06,471 - Processor: x86_64 +2026-06-24 05:36:06,471 - Available CPU cores: 8 +2026-06-24 05:36:06,471 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:36:06,471 - +2026-06-24 05:36:06,471 - ### GPU information ### +2026-06-24 05:36:06,472 - CUDA Available: True +2026-06-24 05:36:06,472 - CUDA Version: 13.0 +2026-06-24 05:36:06,472 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:36:06,472 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:36:06,472 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:36:06,472 - In addition, Triton does not directly support Windows. +2026-06-24 05:36:06,472 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:36:06,487 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:36:06,487 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:36:06,487 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:36:06,487 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:36:06,487 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:36:06,487 - +2026-06-24 05:36:06,487 - ### Python information ### +2026-06-24 05:36:06,489 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:36:06,489 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:36:06,489 - +2026-06-24 05:36:06,489 - ### Packages information ### +2026-06-24 05:36:06,490 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:36:06,491 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:36:06,491 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:36:06,492 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:36:06,492 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:36:06,492 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:36:06,492 - +2026-06-24 05:36:06,492 - ### Loading params file ### +2026-06-24 05:36:06,492 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000008.yaml +2026-06-24 05:36:06,499 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:36:06,500 - Success! Params file validated and defaults applied. +2026-06-24 05:36:06,500 - +2026-06-24 05:36:06,500 - ### Setting GPU Device ### +2026-06-24 05:36:06,500 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:36:06,500 - +2026-06-24 05:36:06,500 - Random seed: 20261852 provided by params file +2026-06-24 05:36:06,500 - ### Initializing Initializer ### +2026-06-24 05:36:06,501 - init_params are displayed below: +2026-06-24 05:36:06,501 - random_seed: 20261852 +2026-06-24 05:36:06,501 - probe_illum_type: electron +2026-06-24 05:36:06,501 - probe_kv: 300.0 +2026-06-24 05:36:06,501 - probe_conv_angle: 12.933050155639648 +2026-06-24 05:36:06,501 - probe_aberrations: {'C10': -307.544, 'C12': -23.624, 'phi12': 165.476, 'C21': 867.661, 'phi21': 90.944, 'C23': -871.995, 'phi23': 355.572, 'C30': -897010.875, 'C32': 5510.824, 'phi32': 174.58, 'C34': -10106.436, 'phi34': 300.845, 'C41': 422961.812, 'phi41': 233.117, 'C43': -401591.344, 'phi43': 264.827, 'C45': -308371.031, 'phi45': 279.55, 'C50': -448757952.0, 'C52': -18148220.0, 'phi52': 207.609, 'C54': -12083272.0, 'phi54': 49.521, 'C56': 15654723.0, 'phi56': 343.861} +2026-06-24 05:36:06,501 - beam_kev: None +2026-06-24 05:36:06,501 - probe_dRn: None +2026-06-24 05:36:06,501 - probe_Rn: None +2026-06-24 05:36:06,501 - probe_D_H: None +2026-06-24 05:36:06,501 - probe_D_FZP: None +2026-06-24 05:36:06,501 - probe_Ls: None +2026-06-24 05:36:06,501 - meas_Npix: 128 +2026-06-24 05:36:06,501 - pos_N_scans: 256 +2026-06-24 05:36:06,501 - pos_N_scan_slow: 16 +2026-06-24 05:36:06,501 - pos_N_scan_fast: 16 +2026-06-24 05:36:06,501 - pos_scan_step_size: 0.4713726341724396 +2026-06-24 05:36:06,501 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:36:06,501 - probe_pmode_max: 6 +2026-06-24 05:36:06,501 - probe_pmode_init_pows: [0.02] +2026-06-24 05:36:06,501 - obj_omode_max: 1 +2026-06-24 05:36:06,501 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:36:06,501 - obj_Nlayer: 1 +2026-06-24 05:36:06,501 - obj_slice_thickness: 20.0 +2026-06-24 05:36:06,501 - simu_Npix: None +2026-06-24 05:36:06,501 - simu_match_mode: None +2026-06-24 05:36:06,501 - meas_permute: None +2026-06-24 05:36:06,501 - meas_reshape: [256, 128, 128] +2026-06-24 05:36:06,501 - meas_flipT: [0, 0, 0] +2026-06-24 05:36:06,501 - meas_crop: None +2026-06-24 05:36:06,501 - meas_pad: None +2026-06-24 05:36:06,501 - meas_resample: None +2026-06-24 05:36:06,501 - meas_add_source_size: None +2026-06-24 05:36:06,501 - meas_add_detector_blur: None +2026-06-24 05:36:06,501 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:36:06,502 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:36:06,502 - meas_add_poisson_noise: None +2026-06-24 05:36:06,502 - meas_export: None +2026-06-24 05:36:06,502 - probe_permute: None +2026-06-24 05:36:06,502 - probe_z_shift: None +2026-06-24 05:36:06,502 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:36:06,502 - pos_scan_flipT: None +2026-06-24 05:36:06,502 - pos_scan_affine: None +2026-06-24 05:36:06,502 - pos_scan_rand_std: 0.15 +2026-06-24 05:36:06,502 - obj_z_crop: None +2026-06-24 05:36:06,502 - obj_z_pad: None +2026-06-24 05:36:06,502 - obj_z_resample: None +2026-06-24 05:36:06,502 - meas_source: file +2026-06-24 05:36:06,502 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000008_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:36:06,502 - probe_source: simu +2026-06-24 05:36:06,502 - probe_params: None +2026-06-24 05:36:06,502 - pos_source: simu +2026-06-24 05:36:06,502 - pos_params: None +2026-06-24 05:36:06,502 - obj_source: simu +2026-06-24 05:36:06,502 - obj_params: None +2026-06-24 05:36:06,502 - tilt_source: simu +2026-06-24 05:36:06,502 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:36:06,502 - +2026-06-24 05:36:06,502 - ### Initializing cache ### +2026-06-24 05:36:06,502 - use_cached_obj = False +2026-06-24 05:36:06,502 - use_cached_probe = False +2026-06-24 05:36:06,502 - use_cached_pos = False +2026-06-24 05:36:06,502 - +2026-06-24 05:36:06,502 - ### Initializing measurements ### +2026-06-24 05:36:06,502 - Loading measurements from source = 'file' +2026-06-24 05:36:06,502 - Detected measurement file type = '.h5' +2026-06-24 05:36:06,581 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:36:06,581 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:36:06,583 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0017) +2026-06-24 05:36:06,583 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:36:06,583 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:36:06,584 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:06,584 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:36:06,585 - Normalizing by max of the 2D mean pattern intensity: 0.0010798314 +2026-06-24 05:36:06,585 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:36:06,587 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0563, 1.5565) +2026-06-24 05:36:06,587 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:06,589 - Pattern total int. statistics (min, mean, max) = (912.6027, 921.7542, 928.0841), with min/max = 98.3% +2026-06-24 05:36:06,590 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0563, 1.5565) +2026-06-24 05:36:06,590 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:36:06,590 - +2026-06-24 05:36:06,590 - ### Setting up calibration ### +2026-06-24 05:36:06,590 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:36:06,590 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:36:06,590 - Radius of fitted bright field disk (RBF) = 16.69 px with meas_Npix = 128 +2026-06-24 05:36:06,590 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2608 +2026-06-24 05:36:06,590 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:36:06,590 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:36:06,811 - Initial guess: center=(63.61, 63.62), radius=16.69, Gaussian blur std=0.50 +2026-06-24 05:36:06,826 - Final fit: center=(63.61, 63.62), radius=16.69, Gaussian blur std=0.76 +2026-06-24 05:36:06,826 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 16.82 px with Npix = 128 +2026-06-24 05:36:06,826 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:36:06,826 - +2026-06-24 05:36:06,826 - ### Setting init_variables dict ### +2026-06-24 05:36:06,826 - Derived values given input init_params: +2026-06-24 05:36:06,826 - kv = 300.0 kV +2026-06-24 05:36:06,826 - wavelength = 0.0197 Ang +2026-06-24 05:36:06,826 - conv_angle = 12.933050155639648 mrad +2026-06-24 05:36:06,826 - Npix = 128 px +2026-06-24 05:36:06,826 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:06,826 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:06,826 - da = 0.7690 mrad +2026-06-24 05:36:06,826 - angleMax = 49.2187 mrad +2026-06-24 05:36:06,826 - RBF = 16.8171 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:36:06,826 - n_alpha = 3.8057 (# conv_angle) +2026-06-24 05:36:06,826 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:06,826 - Rayleigh-limited resolution = 0.9286 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:06,826 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:06,826 - +2026-06-24 05:36:06,826 - ### Initializing probe ### +2026-06-24 05:36:06,827 - Loading probe from source = 'simu' +2026-06-24 05:36:06,827 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:36:06,827 - Start simulating STEM probe +2026-06-24 05:36:06,827 - kv = 300.0 kV +2026-06-24 05:36:06,827 - wavelength = 0.0197 Ang +2026-06-24 05:36:06,827 - conv_angle = 12.933050155639648 mrad +2026-06-24 05:36:06,827 - Npix = 128 px +2026-06-24 05:36:06,827 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:06,827 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:06,827 - alpha_max = 49.2187 mrad +2026-06-24 05:36:06,827 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:06,827 - Rayleigh-limited resolution = 0.9286 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:06,827 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:06,827 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:36:06,827 - ------------------------------------------------------------------------------------- +2026-06-24 05:36:06,827 - C1,0 C1 -307.5440 - Defocus (C10 = -df) +2026-06-24 05:36:06,827 - C1,2 A1 -23.6240 165.48 2-fold astigmatism +2026-06-24 05:36:06,827 - C2,1 3*B2 867.6610 90.94 Axial coma +2026-06-24 05:36:06,827 - C2,3 A2 -871.9950 355.57 3-fold astigmatism +2026-06-24 05:36:06,827 - C3,0 C3 -897010.8750 - Spherical aberration +2026-06-24 05:36:06,827 - C3,2 4*S3 5510.8240 174.58 Axial star aberration +2026-06-24 05:36:06,827 - C3,4 A3 -10106.4360 300.85 4-fold astigmatism +2026-06-24 05:36:06,827 - C4,1 4*B4 422961.8120 233.12 Axial coma(4th) +2026-06-24 05:36:06,827 - C4,3 4*D4 -401591.3440 264.83 3-lobe aberration +2026-06-24 05:36:06,827 - C4,5 A4 -308371.0310 279.55 5-fold astigmatism +2026-06-24 05:36:06,828 - C5,0 C5 -448757952.0000 - Spherical aberration (5th) +2026-06-24 05:36:06,828 - C5,2 6*S5 -18148220.0000 207.61 Axial star aberration(5th) +2026-06-24 05:36:06,828 - C5,4 6*R5 -12083272.0000 49.52 4-lobe aberration +2026-06-24 05:36:06,828 - C5,6 A5 15654723.0000 343.86 6-fold astigmatism +2026-06-24 05:36:06,830 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:36:06,830 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:36:06,831 - Creating 5 new probe modes from the major mode +2026-06-24 05:36:06,831 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:36:07,066 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:36:07,067 - Orthogonalizing 6 pmodes +2026-06-24 05:36:07,080 - Sorting 6 pmodes by their intensities +2026-06-24 05:36:07,080 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:36:07,081 - sum(|probe_data|**2) = 921.75, while meas_total_ints (min, mean, max) = (912.6027, 921.7542, 928.0841) +2026-06-24 05:36:07,081 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:36:07,081 - +2026-06-24 05:36:07,081 - ### Initializing probe positions ### +2026-06-24 05:36:07,081 - Loading probe positions from source = 'simu' +2026-06-24 05:36:07,081 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:36:07,081 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4714, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:36:07,081 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:36:07,083 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:36:07,083 - crop_pos 1st and last px coords (y,x) = ([17, 16], [51, 52]) +2026-06-24 05:36:07,084 - crop_pos extent (Ang) = [7.2 7.2] +2026-06-24 05:36:07,084 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:36:07,084 - +2026-06-24 05:36:07,084 - ### Initializing object ### +2026-06-24 05:36:07,084 - Loading object from source = 'simu' +2026-06-24 05:36:07,084 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:36:07,085 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:36:07,085 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 196, 196) +2026-06-24 05:36:07,085 - object extent (Z, Y, X) (Ang) = [20. 39.2 39.2] +2026-06-24 05:36:07,086 - +2026-06-24 05:36:07,086 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:36:07,086 - omode_occu (omode) = float32, (1,) +2026-06-24 05:36:07,086 - +2026-06-24 05:36:07,086 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:36:07,086 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 05:36:07,086 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:36:07,086 - +2026-06-24 05:36:07,086 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:36:07,086 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:36:07,087 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:36:07,087 - +2026-06-24 05:36:07,087 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:36:07,087 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:36:07,087 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:36:07,087 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:36:07,087 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:36:07,087 - crop positions (yx_min=[16 16], yx_max=[180 180]) are well contained inside object canvas (Ny,Nx) = (196, 196). +2026-06-24 05:36:07,087 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:36:07,087 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:36:07,087 - +2026-06-24 05:36:07,087 - ### Collecting reconstruction provenance ### +2026-06-24 05:36:07,087 - Reconstruction provenance is collected and initialized. +2026-06-24 05:36:07,087 - +2026-06-24 05:36:07,087 - ### Initializing loss function ### +2026-06-24 05:36:07,087 - Active loss types: +2026-06-24 05:36:07,087 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:36:07,087 - +2026-06-24 05:36:07,087 - ### Initializing constraint function ### +2026-06-24 05:36:07,087 - Active constraint types: +2026-06-24 05:36:07,087 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:07,087 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:07,088 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:36:07,088 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:36:07,088 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:36:07,088 - +2026-06-24 05:36:07,088 - ### Done initializing PtyRADSolver ### +2026-06-24 05:36:07,088 - +2026-06-24 05:36:07,212 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:36:07,212 - +2026-06-24 05:36:07,212 - ### Initializing PtychoModel model ### +2026-06-24 05:36:07,284 - ### PtychoModel optimizable variables ### +2026-06-24 05:36:07,284 - obja : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:07,284 - objp : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:07,284 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:07,285 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:07,285 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:36:07,285 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:07,285 - +2026-06-24 05:36:07,285 - ### Optimizable variables statitsics ### +2026-06-24 05:36:07,285 - Total measurement values : 4,194,304 +2026-06-24 05:36:07,285 - Total optimizing variables: 273,952 +2026-06-24 05:36:07,285 - Overdetermined ratio : 15.31 +2026-06-24 05:36:07,285 - +2026-06-24 05:36:07,285 - ### Model behavior ### +2026-06-24 05:36:07,285 - Tilt propagator : False +2026-06-24 05:36:07,285 - Change slice thickness : False +2026-06-24 05:36:07,285 - Detector blur : False +2026-06-24 05:36:07,285 - Preload data : True +2026-06-24 05:36:07,285 - On-the-fly meas padding : False +2026-06-24 05:36:07,285 - On-the-fly meas resample : False +2026-06-24 05:36:07,285 - On-the-fly simu match mode: None +2026-06-24 05:36:07,285 - +2026-06-24 05:36:07,326 - ### Done initializing PtychoModel model ### +2026-06-24 05:36:07,327 - +2026-06-24 05:36:07,327 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:36:07,327 - +2026-06-24 05:36:07,327 - ### Generating indices, batches, and output_path ### +2026-06-24 05:36:07,328 - d90 = 57.000 px or 11.400 Ang +2026-06-24 05:36:07,328 - Selecting indices with the 'full' mode +2026-06-24 05:36:07,793 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:36:07,868 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:36:07,869 - Original recon_dir_affixes = ['default'] +2026-06-24 05:36:07,869 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:36:07,874 - Path corrected for compatibility: +2026-06-24 05:36:07,874 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_5.51e+03_phi32_175_C34_-1.01e+04_phi34_301_C41_4.23e+05_phi41_233_C43_-4.02e+05_phi43_265_C45_-3.08e+05_phi45_280_C50_-4.49e+08_C52_-1.81e+07_phi52_208_C54_-1.21e+07_phi54_49.5_C56_1.57e+07_phi56_344 +2026-06-24 05:36:07,874 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344 +2026-06-24 05:36:07,875 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344' is generated! +2026-06-24 05:36:08,031 - +2026-06-24 05:36:08,032 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/20260624_053608_ptyrad_log.txt ### +2026-06-24 05:36:08,032 - +2026-06-24 05:36:08,033 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:36:08,034 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:36:08,034 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:36:09,227 - Iter: 1, Total Loss: 0.7269, loss_single: 0.7269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:36:09,264 - Iter: 2, Total Loss: 0.7053, loss_single: 0.7053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:36:09,300 - Iter: 3, Total Loss: 0.6886, loss_single: 0.6886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,335 - Iter: 4, Total Loss: 0.6742, loss_single: 0.6742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,370 - Iter: 5, Total Loss: 0.6580, loss_single: 0.6580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,406 - Iter: 6, Total Loss: 0.6436, loss_single: 0.6436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,441 - Iter: 7, Total Loss: 0.6307, loss_single: 0.6307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,476 - Iter: 8, Total Loss: 0.6167, loss_single: 0.6167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,512 - Iter: 9, Total Loss: 0.6013, loss_single: 0.6013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,547 - Iter: 10, Total Loss: 0.5865, loss_single: 0.5865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,582 - Iter: 11, Total Loss: 0.5721, loss_single: 0.5721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:09,617 - Iter: 12, Total Loss: 0.5578, loss_single: 0.5578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,653 - Iter: 13, Total Loss: 0.5437, loss_single: 0.5437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,688 - Iter: 14, Total Loss: 0.5305, loss_single: 0.5305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,723 - Iter: 15, Total Loss: 0.5167, loss_single: 0.5167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:09,758 - Iter: 16, Total Loss: 0.5012, loss_single: 0.5012, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,793 - Iter: 17, Total Loss: 0.4881, loss_single: 0.4881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,829 - Iter: 18, Total Loss: 0.4770, loss_single: 0.4770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,864 - Iter: 19, Total Loss: 0.4659, loss_single: 0.4659, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,899 - Iter: 20, Total Loss: 0.4557, loss_single: 0.4557, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:09,934 - Iter: 21, Total Loss: 0.4458, loss_single: 0.4458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:09,970 - Iter: 22, Total Loss: 0.4368, loss_single: 0.4368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,009 - Iter: 23, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:36:10,044 - Iter: 24, Total Loss: 0.4185, loss_single: 0.4185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,079 - Iter: 25, Total Loss: 0.4059, loss_single: 0.4059, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,115 - Iter: 26, Total Loss: 0.3938, loss_single: 0.3938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,150 - Iter: 27, Total Loss: 0.3828, loss_single: 0.3828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,186 - Iter: 28, Total Loss: 0.3735, loss_single: 0.3735, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,221 - Iter: 29, Total Loss: 0.3649, loss_single: 0.3649, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,256 - Iter: 30, Total Loss: 0.3562, loss_single: 0.3562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,291 - Iter: 31, Total Loss: 0.3485, loss_single: 0.3485, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:10,326 - Iter: 32, Total Loss: 0.3415, loss_single: 0.3415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,361 - Iter: 33, Total Loss: 0.3345, loss_single: 0.3345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,397 - Iter: 34, Total Loss: 0.3284, loss_single: 0.3284, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,432 - Iter: 35, Total Loss: 0.3226, loss_single: 0.3226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,467 - Iter: 36, Total Loss: 0.3146, loss_single: 0.3146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,502 - Iter: 37, Total Loss: 0.3078, loss_single: 0.3078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,537 - Iter: 38, Total Loss: 0.3022, loss_single: 0.3022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,572 - Iter: 39, Total Loss: 0.2955, loss_single: 0.2955, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,608 - Iter: 40, Total Loss: 0.2891, loss_single: 0.2891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,646 - Iter: 41, Total Loss: 0.2851, loss_single: 0.2851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,682 - Iter: 42, Total Loss: 0.2826, loss_single: 0.2826, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,718 - Iter: 43, Total Loss: 0.2785, loss_single: 0.2785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:36:10,761 - Iter: 44, Total Loss: 0.2741, loss_single: 0.2741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,796 - Iter: 45, Total Loss: 0.2703, loss_single: 0.2703, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,832 - Iter: 46, Total Loss: 0.2667, loss_single: 0.2667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:36:10,867 - Iter: 47, Total Loss: 0.2644, loss_single: 0.2644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,902 - Iter: 48, Total Loss: 0.2622, loss_single: 0.2622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,938 - Iter: 49, Total Loss: 0.2601, loss_single: 0.2601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:10,973 - Iter: 50, Total Loss: 0.2583, loss_single: 0.2583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,008 - Iter: 51, Total Loss: 0.2559, loss_single: 0.2559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,044 - Iter: 52, Total Loss: 0.2542, loss_single: 0.2542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,079 - Iter: 53, Total Loss: 0.2520, loss_single: 0.2520, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,115 - Iter: 54, Total Loss: 0.2497, loss_single: 0.2497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,150 - Iter: 55, Total Loss: 0.2475, loss_single: 0.2475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,185 - Iter: 56, Total Loss: 0.2457, loss_single: 0.2457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,221 - Iter: 57, Total Loss: 0.2442, loss_single: 0.2442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,256 - Iter: 58, Total Loss: 0.2424, loss_single: 0.2424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,292 - Iter: 59, Total Loss: 0.2403, loss_single: 0.2403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,327 - Iter: 60, Total Loss: 0.2389, loss_single: 0.2389, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,362 - Iter: 61, Total Loss: 0.2378, loss_single: 0.2378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:11,397 - Iter: 62, Total Loss: 0.2365, loss_single: 0.2365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,432 - Iter: 63, Total Loss: 0.2353, loss_single: 0.2353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,467 - Iter: 64, Total Loss: 0.2343, loss_single: 0.2343, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,503 - Iter: 65, Total Loss: 0.2332, loss_single: 0.2332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,538 - Iter: 66, Total Loss: 0.2319, loss_single: 0.2319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,573 - Iter: 67, Total Loss: 0.2307, loss_single: 0.2307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,609 - Iter: 68, Total Loss: 0.2299, loss_single: 0.2299, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,644 - Iter: 69, Total Loss: 0.2290, loss_single: 0.2290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,679 - Iter: 70, Total Loss: 0.2282, loss_single: 0.2282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,715 - Iter: 71, Total Loss: 0.2274, loss_single: 0.2274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,750 - Iter: 72, Total Loss: 0.2268, loss_single: 0.2268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,785 - Iter: 73, Total Loss: 0.2262, loss_single: 0.2262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,821 - Iter: 74, Total Loss: 0.2257, loss_single: 0.2257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,856 - Iter: 75, Total Loss: 0.2251, loss_single: 0.2251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,891 - Iter: 76, Total Loss: 0.2247, loss_single: 0.2247, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,926 - Iter: 77, Total Loss: 0.2242, loss_single: 0.2242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,961 - Iter: 78, Total Loss: 0.2238, loss_single: 0.2238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:11,996 - Iter: 79, Total Loss: 0.2235, loss_single: 0.2235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,031 - Iter: 80, Total Loss: 0.2231, loss_single: 0.2231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,066 - Iter: 81, Total Loss: 0.2228, loss_single: 0.2228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:12,101 - Iter: 82, Total Loss: 0.2225, loss_single: 0.2225, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,136 - Iter: 83, Total Loss: 0.2222, loss_single: 0.2222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,172 - Iter: 84, Total Loss: 0.2219, loss_single: 0.2219, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,207 - Iter: 85, Total Loss: 0.2217, loss_single: 0.2217, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,243 - Iter: 86, Total Loss: 0.2215, loss_single: 0.2215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,277 - Iter: 87, Total Loss: 0.2213, loss_single: 0.2213, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:12,313 - Iter: 88, Total Loss: 0.2211, loss_single: 0.2211, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,348 - Iter: 89, Total Loss: 0.2209, loss_single: 0.2209, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,383 - Iter: 90, Total Loss: 0.2207, loss_single: 0.2207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,420 - Iter: 91, Total Loss: 0.2206, loss_single: 0.2206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:36:12,456 - Iter: 92, Total Loss: 0.2204, loss_single: 0.2204, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,491 - Iter: 93, Total Loss: 0.2203, loss_single: 0.2203, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,526 - Iter: 94, Total Loss: 0.2202, loss_single: 0.2202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,561 - Iter: 95, Total Loss: 0.2200, loss_single: 0.2200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,596 - Iter: 96, Total Loss: 0.2199, loss_single: 0.2199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,631 - Iter: 97, Total Loss: 0.2198, loss_single: 0.2198, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,667 - Iter: 98, Total Loss: 0.2197, loss_single: 0.2197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,702 - Iter: 99, Total Loss: 0.2196, loss_single: 0.2196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,737 - Iter: 100, Total Loss: 0.2196, loss_single: 0.2196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:12,850 - Saving summary figures for iter 100 +2026-06-24 05:36:16,637 - ### Finished 100 iterations, averaged iter_t = 0.038919 with std = 0.040 ### +2026-06-24 05:36:16,638 - +2026-06-24 05:36:16,638 - ### The PtyRADSolver is finished in 9.426 sec ### +2026-06-24 05:36:16,638 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..0739be2666b3a88ce2cdbfeb9b6153e92646c79a Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/simulation_data1__sample_000008.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/simulation_data1__sample_000008.yaml new file mode 100644 index 0000000000000000000000000000000000000000..74d96ac565394e86bc0659f2cc0c65b55a3217ce --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008/c30_small__simulation_data1__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-308_C12_-23.6_phi12_165_C21_868_phi21_90.9_C23_-872_phi23_356_C30_-8.97e+05_C32_.57e+07_phi56_344/simulation_data1__sample_000008.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 12.933050155639648 + probe_aberrations: + C10: -307.54443359375 + C12: -23.624135971069336 + C21: 867.66064453125 + C23: -871.9953002929688 + C30: -897010.875 + C32: 5510.82421875 + C34: -10106.435546875 + C41: 422961.8125 + C43: -401591.34375 + C45: -308371.03125 + C50: -448757952.0 + C52: -18148220.0 + C54: -12083272.0 + C56: 15654723.0 + phi12: 165.47571702195094 + phi21: 90.94372974209882 + phi23: 355.5720803412634 + phi32: 174.58019526103786 + phi34: 300.8448617674561 + phi41: 233.1174982595534 + phi43: 264.8271159342012 + phi45: 279.5500531430272 + phi52: 207.60881808706347 + phi54: 49.52084540726258 + phi56: 343.8609833488462 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4713726341724396 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000008_measurement.h5 + key: measurement + random_seed: 20261852 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000008 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000008 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333/20260624_053622_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333/20260624_053622_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..a59272a2e3fd9e5ccb1d5c78bafb4b7b5f44f847 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333/20260624_053622_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:36:21,408 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:36:21,408 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:36:21,408 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:36:21,408 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:36:21,408 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:36:21,408 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:36:21,408 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:36:21,408 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:36:21,408 - +2026-06-24 05:36:21,519 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:36:21,519 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:36:21,519 - Accelerator.num_process = 1 +2026-06-24 05:36:21,519 - Accelerator.mixed_precision = no +2026-06-24 05:36:21,530 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:36:21,530 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:36:21,530 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:36:21,530 - +2026-06-24 05:36:21,530 - ### System information ### +2026-06-24 05:36:21,530 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:36:21,530 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:36:21,530 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:36:21,530 - Machine: x86_64 +2026-06-24 05:36:21,530 - Processor: x86_64 +2026-06-24 05:36:21,530 - Available CPU cores: 8 +2026-06-24 05:36:21,530 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:36:21,530 - +2026-06-24 05:36:21,530 - ### GPU information ### +2026-06-24 05:36:21,530 - CUDA Available: True +2026-06-24 05:36:21,530 - CUDA Version: 13.0 +2026-06-24 05:36:21,531 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:36:21,531 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:36:21,531 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:36:21,531 - In addition, Triton does not directly support Windows. +2026-06-24 05:36:21,531 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:36:21,547 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:36:21,547 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:36:21,547 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:36:21,547 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:36:21,547 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:36:21,547 - +2026-06-24 05:36:21,547 - ### Python information ### +2026-06-24 05:36:21,549 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:36:21,549 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:36:21,549 - +2026-06-24 05:36:21,549 - ### Packages information ### +2026-06-24 05:36:21,550 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:36:21,551 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:36:21,551 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:36:21,552 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:36:21,552 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:36:21,552 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:36:21,552 - +2026-06-24 05:36:21,552 - ### Loading params file ### +2026-06-24 05:36:21,553 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000009.yaml +2026-06-24 05:36:21,559 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:36:21,560 - Success! Params file validated and defaults applied. +2026-06-24 05:36:21,560 - +2026-06-24 05:36:21,560 - ### Setting GPU Device ### +2026-06-24 05:36:21,560 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:36:21,560 - +2026-06-24 05:36:21,560 - Random seed: 20261853 provided by params file +2026-06-24 05:36:21,561 - ### Initializing Initializer ### +2026-06-24 05:36:21,561 - init_params are displayed below: +2026-06-24 05:36:21,561 - random_seed: 20261853 +2026-06-24 05:36:21,561 - probe_illum_type: electron +2026-06-24 05:36:21,561 - probe_kv: 300.0 +2026-06-24 05:36:21,561 - probe_conv_angle: 22.653152465820312 +2026-06-24 05:36:21,561 - probe_aberrations: {'C10': -266.603, 'C12': 18.172, 'phi12': 229.657, 'C21': 757.701, 'phi21': 298.59, 'C23': 881.624, 'phi23': 3.72, 'C30': 133419.656, 'C32': 9907.309, 'phi32': 59.121, 'C34': -1121.24, 'phi34': 318.911, 'C41': -363432.125, 'phi41': 242.013, 'C43': -177851.125, 'phi43': 339.07, 'C45': 41571.309, 'phi45': 55.737, 'C50': 269112576.0, 'C52': 18410188.0, 'phi52': 311.7, 'C54': 17605530.0, 'phi54': 199.502, 'C56': -788044.688, 'phi56': 333.474} +2026-06-24 05:36:21,561 - beam_kev: None +2026-06-24 05:36:21,561 - probe_dRn: None +2026-06-24 05:36:21,561 - probe_Rn: None +2026-06-24 05:36:21,561 - probe_D_H: None +2026-06-24 05:36:21,561 - probe_D_FZP: None +2026-06-24 05:36:21,561 - probe_Ls: None +2026-06-24 05:36:21,561 - meas_Npix: 128 +2026-06-24 05:36:21,561 - pos_N_scans: 256 +2026-06-24 05:36:21,561 - pos_N_scan_slow: 16 +2026-06-24 05:36:21,561 - pos_N_scan_fast: 16 +2026-06-24 05:36:21,561 - pos_scan_step_size: 0.43370673060417175 +2026-06-24 05:36:21,561 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:36:21,561 - probe_pmode_max: 6 +2026-06-24 05:36:21,561 - probe_pmode_init_pows: [0.02] +2026-06-24 05:36:21,561 - obj_omode_max: 1 +2026-06-24 05:36:21,561 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:36:21,561 - obj_Nlayer: 1 +2026-06-24 05:36:21,561 - obj_slice_thickness: 20.0 +2026-06-24 05:36:21,561 - simu_Npix: None +2026-06-24 05:36:21,561 - simu_match_mode: None +2026-06-24 05:36:21,561 - meas_permute: None +2026-06-24 05:36:21,561 - meas_reshape: [256, 128, 128] +2026-06-24 05:36:21,561 - meas_flipT: [0, 0, 0] +2026-06-24 05:36:21,561 - meas_crop: None +2026-06-24 05:36:21,561 - meas_pad: None +2026-06-24 05:36:21,561 - meas_resample: None +2026-06-24 05:36:21,562 - meas_add_source_size: None +2026-06-24 05:36:21,562 - meas_add_detector_blur: None +2026-06-24 05:36:21,562 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:36:21,562 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:36:21,562 - meas_add_poisson_noise: None +2026-06-24 05:36:21,562 - meas_export: None +2026-06-24 05:36:21,562 - probe_permute: None +2026-06-24 05:36:21,562 - probe_z_shift: None +2026-06-24 05:36:21,562 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:36:21,562 - pos_scan_flipT: None +2026-06-24 05:36:21,562 - pos_scan_affine: None +2026-06-24 05:36:21,562 - pos_scan_rand_std: 0.15 +2026-06-24 05:36:21,562 - obj_z_crop: None +2026-06-24 05:36:21,562 - obj_z_pad: None +2026-06-24 05:36:21,562 - obj_z_resample: None +2026-06-24 05:36:21,562 - meas_source: file +2026-06-24 05:36:21,562 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000009_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:36:21,562 - probe_source: simu +2026-06-24 05:36:21,562 - probe_params: None +2026-06-24 05:36:21,562 - pos_source: simu +2026-06-24 05:36:21,562 - pos_params: None +2026-06-24 05:36:21,562 - obj_source: simu +2026-06-24 05:36:21,562 - obj_params: None +2026-06-24 05:36:21,562 - tilt_source: simu +2026-06-24 05:36:21,562 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:36:21,562 - +2026-06-24 05:36:21,562 - ### Initializing cache ### +2026-06-24 05:36:21,562 - use_cached_obj = False +2026-06-24 05:36:21,562 - use_cached_probe = False +2026-06-24 05:36:21,562 - use_cached_pos = False +2026-06-24 05:36:21,562 - +2026-06-24 05:36:21,562 - ### Initializing measurements ### +2026-06-24 05:36:21,562 - Loading measurements from source = 'file' +2026-06-24 05:36:21,562 - Detected measurement file type = '.h5' +2026-06-24 05:36:21,644 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:36:21,645 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:36:21,646 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0005) +2026-06-24 05:36:21,646 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:36:21,646 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:36:21,648 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:21,648 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:36:21,649 - Normalizing by max of the 2D mean pattern intensity: 0.00036771825 +2026-06-24 05:36:21,650 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:36:21,651 - meausrements int. statistics (min, mean, max) = (0.0000, 0.1651, 1.4306) +2026-06-24 05:36:21,651 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:21,653 - Pattern total int. statistics (min, mean, max) = (2691.6978, 2705.3447, 2721.6626), with min/max = 98.9% +2026-06-24 05:36:21,654 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.1651, 1.4306) +2026-06-24 05:36:21,654 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:36:21,654 - +2026-06-24 05:36:21,654 - ### Setting up calibration ### +2026-06-24 05:36:21,654 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:36:21,654 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:36:21,654 - Radius of fitted bright field disk (RBF) = 29.22 px with meas_Npix = 128 +2026-06-24 05:36:21,654 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.4565 +2026-06-24 05:36:21,654 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:36:21,654 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:36:21,883 - Initial guess: center=(63.62, 63.63), radius=29.22, Gaussian blur std=0.50 +2026-06-24 05:36:21,899 - Final fit: center=(63.62, 63.63), radius=29.22, Gaussian blur std=0.80 +2026-06-24 05:36:21,899 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 29.46 px with Npix = 128 +2026-06-24 05:36:21,899 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:36:21,899 - +2026-06-24 05:36:21,899 - ### Setting init_variables dict ### +2026-06-24 05:36:21,900 - Derived values given input init_params: +2026-06-24 05:36:21,900 - kv = 300.0 kV +2026-06-24 05:36:21,900 - wavelength = 0.0197 Ang +2026-06-24 05:36:21,900 - conv_angle = 22.653152465820312 mrad +2026-06-24 05:36:21,900 - Npix = 128 px +2026-06-24 05:36:21,900 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:21,900 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:21,900 - da = 0.7690 mrad +2026-06-24 05:36:21,900 - angleMax = 49.2187 mrad +2026-06-24 05:36:21,900 - RBF = 29.4563 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:36:21,900 - n_alpha = 2.1727 (# conv_angle) +2026-06-24 05:36:21,900 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:21,900 - Rayleigh-limited resolution = 0.5301 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:21,900 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:21,900 - +2026-06-24 05:36:21,900 - ### Initializing probe ### +2026-06-24 05:36:21,900 - Loading probe from source = 'simu' +2026-06-24 05:36:21,900 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:36:21,900 - Start simulating STEM probe +2026-06-24 05:36:21,900 - kv = 300.0 kV +2026-06-24 05:36:21,900 - wavelength = 0.0197 Ang +2026-06-24 05:36:21,900 - conv_angle = 22.653152465820312 mrad +2026-06-24 05:36:21,900 - Npix = 128 px +2026-06-24 05:36:21,900 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:21,901 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:21,901 - alpha_max = 49.2187 mrad +2026-06-24 05:36:21,901 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:21,901 - Rayleigh-limited resolution = 0.5301 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:21,901 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:21,901 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:36:21,901 - ------------------------------------------------------------------------------------ +2026-06-24 05:36:21,901 - C1,0 C1 -266.6030 - Defocus (C10 = -df) +2026-06-24 05:36:21,901 - C1,2 A1 18.1720 229.66 2-fold astigmatism +2026-06-24 05:36:21,901 - C2,1 3*B2 757.7010 298.59 Axial coma +2026-06-24 05:36:21,901 - C2,3 A2 881.6240 3.72 3-fold astigmatism +2026-06-24 05:36:21,901 - C3,0 C3 133419.6560 - Spherical aberration +2026-06-24 05:36:21,901 - C3,2 4*S3 9907.3090 59.12 Axial star aberration +2026-06-24 05:36:21,901 - C3,4 A3 -1121.2400 318.91 4-fold astigmatism +2026-06-24 05:36:21,901 - C4,1 4*B4 -363432.1250 242.01 Axial coma(4th) +2026-06-24 05:36:21,901 - C4,3 4*D4 -177851.1250 339.07 3-lobe aberration +2026-06-24 05:36:21,901 - C4,5 A4 41571.3090 55.74 5-fold astigmatism +2026-06-24 05:36:21,901 - C5,0 C5 269112576.0000 - Spherical aberration (5th) +2026-06-24 05:36:21,901 - C5,2 6*S5 18410188.0000 311.70 Axial star aberration(5th) +2026-06-24 05:36:21,901 - C5,4 6*R5 17605530.0000 199.50 4-lobe aberration +2026-06-24 05:36:21,901 - C5,6 A5 -788044.6880 333.47 6-fold astigmatism +2026-06-24 05:36:21,904 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:36:21,904 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:36:21,904 - Creating 5 new probe modes from the major mode +2026-06-24 05:36:21,904 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:36:22,050 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:36:22,051 - Orthogonalizing 6 pmodes +2026-06-24 05:36:22,054 - Sorting 6 pmodes by their intensities +2026-06-24 05:36:22,054 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:36:22,055 - sum(|probe_data|**2) = 2705.34, while meas_total_ints (min, mean, max) = (2691.6978, 2705.3447, 2721.6626) +2026-06-24 05:36:22,055 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:36:22,055 - +2026-06-24 05:36:22,055 - ### Initializing probe positions ### +2026-06-24 05:36:22,055 - Loading probe positions from source = 'simu' +2026-06-24 05:36:22,055 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:36:22,055 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4337, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:36:22,055 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:36:22,057 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:36:22,057 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 05:36:22,057 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 05:36:22,057 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:36:22,057 - +2026-06-24 05:36:22,057 - ### Initializing object ### +2026-06-24 05:36:22,057 - Loading object from source = 'simu' +2026-06-24 05:36:22,058 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:36:22,059 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:36:22,059 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 05:36:22,059 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 05:36:22,059 - +2026-06-24 05:36:22,059 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:36:22,059 - omode_occu (omode) = float32, (1,) +2026-06-24 05:36:22,059 - +2026-06-24 05:36:22,059 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:36:22,059 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 05:36:22,060 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:36:22,060 - +2026-06-24 05:36:22,060 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:36:22,060 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:36:22,060 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:36:22,060 - +2026-06-24 05:36:22,060 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:36:22,060 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:36:22,060 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:36:22,060 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:36:22,060 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:36:22,061 - crop positions (yx_min=[15 15], yx_max=[177 177]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 05:36:22,061 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:36:22,061 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:36:22,061 - +2026-06-24 05:36:22,061 - ### Collecting reconstruction provenance ### +2026-06-24 05:36:22,061 - Reconstruction provenance is collected and initialized. +2026-06-24 05:36:22,061 - +2026-06-24 05:36:22,061 - ### Initializing loss function ### +2026-06-24 05:36:22,061 - Active loss types: +2026-06-24 05:36:22,061 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:36:22,061 - +2026-06-24 05:36:22,061 - ### Initializing constraint function ### +2026-06-24 05:36:22,061 - Active constraint types: +2026-06-24 05:36:22,061 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:22,061 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:22,061 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:36:22,061 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:36:22,061 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:36:22,061 - +2026-06-24 05:36:22,061 - ### Done initializing PtyRADSolver ### +2026-06-24 05:36:22,061 - +2026-06-24 05:36:22,184 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:36:22,184 - +2026-06-24 05:36:22,184 - ### Initializing PtychoModel model ### +2026-06-24 05:36:22,257 - ### PtychoModel optimizable variables ### +2026-06-24 05:36:22,257 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:22,257 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:22,257 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:22,257 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:22,257 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:36:22,257 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:22,257 - +2026-06-24 05:36:22,257 - ### Optimizable variables statitsics ### +2026-06-24 05:36:22,257 - Total measurement values : 4,194,304 +2026-06-24 05:36:22,257 - Total optimizing variables: 272,392 +2026-06-24 05:36:22,257 - Overdetermined ratio : 15.40 +2026-06-24 05:36:22,257 - +2026-06-24 05:36:22,257 - ### Model behavior ### +2026-06-24 05:36:22,257 - Tilt propagator : False +2026-06-24 05:36:22,257 - Change slice thickness : False +2026-06-24 05:36:22,257 - Detector blur : False +2026-06-24 05:36:22,257 - Preload data : True +2026-06-24 05:36:22,257 - On-the-fly meas padding : False +2026-06-24 05:36:22,257 - On-the-fly meas resample : False +2026-06-24 05:36:22,257 - On-the-fly simu match mode: None +2026-06-24 05:36:22,258 - +2026-06-24 05:36:22,299 - ### Done initializing PtychoModel model ### +2026-06-24 05:36:22,299 - +2026-06-24 05:36:22,299 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:36:22,299 - +2026-06-24 05:36:22,299 - ### Generating indices, batches, and output_path ### +2026-06-24 05:36:22,300 - d90 = 41.000 px or 8.200 Ang +2026-06-24 05:36:22,300 - Selecting indices with the 'full' mode +2026-06-24 05:36:22,761 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:36:22,834 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:36:22,834 - Original recon_dir_affixes = ['default'] +2026-06-24 05:36:22,834 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:36:22,841 - Path corrected for compatibility: +2026-06-24 05:36:22,841 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.91e+03_phi32_59.1_C34_-1.12e+03_phi34_319_C41_-3.63e+05_phi41_242_C43_-1.78e+05_phi43_339_C45_4.16e+04_phi45_55.7_C50_2.69e+08_C52_1.84e+07_phi52_312_C54_1.76e+07_phi54_200_C56_-7.88e+05_phi56_333 +2026-06-24 05:36:22,841 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333 +2026-06-24 05:36:22,842 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333' is generated! +2026-06-24 05:36:22,991 - +2026-06-24 05:36:22,992 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333/20260624_053622_ptyrad_log.txt ### +2026-06-24 05:36:22,992 - +2026-06-24 05:36:22,993 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:36:22,993 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:36:22,993 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:36:24,185 - Iter: 1, Total Loss: 0.3887, loss_single: 0.3887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 05:36:24,222 - Iter: 2, Total Loss: 0.3786, loss_single: 0.3786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:36:24,257 - Iter: 3, Total Loss: 0.3696, loss_single: 0.3696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,293 - Iter: 4, Total Loss: 0.3604, loss_single: 0.3604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,328 - Iter: 5, Total Loss: 0.3520, loss_single: 0.3520, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,363 - Iter: 6, Total Loss: 0.3446, loss_single: 0.3446, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,399 - Iter: 7, Total Loss: 0.3370, loss_single: 0.3370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,434 - Iter: 8, Total Loss: 0.3301, loss_single: 0.3301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,469 - Iter: 9, Total Loss: 0.3232, loss_single: 0.3232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,506 - Iter: 10, Total Loss: 0.3161, loss_single: 0.3161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:36:24,541 - Iter: 11, Total Loss: 0.3095, loss_single: 0.3095, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,577 - Iter: 12, Total Loss: 0.3038, loss_single: 0.3038, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,612 - Iter: 13, Total Loss: 0.2985, loss_single: 0.2985, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,647 - Iter: 14, Total Loss: 0.2931, loss_single: 0.2931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,682 - Iter: 15, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,718 - Iter: 16, Total Loss: 0.2823, loss_single: 0.2823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:36:24,753 - Iter: 17, Total Loss: 0.2770, loss_single: 0.2770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,789 - Iter: 18, Total Loss: 0.2723, loss_single: 0.2723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,824 - Iter: 19, Total Loss: 0.2683, loss_single: 0.2683, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,859 - Iter: 20, Total Loss: 0.2635, loss_single: 0.2635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,895 - Iter: 21, Total Loss: 0.2585, loss_single: 0.2585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,930 - Iter: 22, Total Loss: 0.2539, loss_single: 0.2539, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:24,966 - Iter: 23, Total Loss: 0.2492, loss_single: 0.2492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,001 - Iter: 24, Total Loss: 0.2438, loss_single: 0.2438, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,036 - Iter: 25, Total Loss: 0.2390, loss_single: 0.2390, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,071 - Iter: 26, Total Loss: 0.2349, loss_single: 0.2349, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,107 - Iter: 27, Total Loss: 0.2305, loss_single: 0.2305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,142 - Iter: 28, Total Loss: 0.2262, loss_single: 0.2262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,177 - Iter: 29, Total Loss: 0.2220, loss_single: 0.2220, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,212 - Iter: 30, Total Loss: 0.2181, loss_single: 0.2181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,247 - Iter: 31, Total Loss: 0.2140, loss_single: 0.2140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,283 - Iter: 32, Total Loss: 0.2102, loss_single: 0.2102, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,318 - Iter: 33, Total Loss: 0.2069, loss_single: 0.2069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,353 - Iter: 34, Total Loss: 0.2035, loss_single: 0.2035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,389 - Iter: 35, Total Loss: 0.1999, loss_single: 0.1999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,424 - Iter: 36, Total Loss: 0.1966, loss_single: 0.1966, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,460 - Iter: 37, Total Loss: 0.1933, loss_single: 0.1933, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,496 - Iter: 38, Total Loss: 0.1899, loss_single: 0.1899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:36:25,531 - Iter: 39, Total Loss: 0.1868, loss_single: 0.1868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,566 - Iter: 40, Total Loss: 0.1840, loss_single: 0.1840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,603 - Iter: 41, Total Loss: 0.1812, loss_single: 0.1812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,638 - Iter: 42, Total Loss: 0.1787, loss_single: 0.1787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,674 - Iter: 43, Total Loss: 0.1765, loss_single: 0.1765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,709 - Iter: 44, Total Loss: 0.1743, loss_single: 0.1743, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,786 - Iter: 45, Total Loss: 0.1722, loss_single: 0.1722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,822 - Iter: 46, Total Loss: 0.1698, loss_single: 0.1698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,857 - Iter: 47, Total Loss: 0.1675, loss_single: 0.1675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,892 - Iter: 48, Total Loss: 0.1657, loss_single: 0.1657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,928 - Iter: 49, Total Loss: 0.1643, loss_single: 0.1643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,964 - Iter: 50, Total Loss: 0.1624, loss_single: 0.1624, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:25,998 - Iter: 51, Total Loss: 0.1604, loss_single: 0.1604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:26,034 - Iter: 52, Total Loss: 0.1587, loss_single: 0.1587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,070 - Iter: 53, Total Loss: 0.1571, loss_single: 0.1571, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,105 - Iter: 54, Total Loss: 0.1557, loss_single: 0.1557, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,141 - Iter: 55, Total Loss: 0.1545, loss_single: 0.1545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,176 - Iter: 56, Total Loss: 0.1533, loss_single: 0.1533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,212 - Iter: 57, Total Loss: 0.1518, loss_single: 0.1518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,247 - Iter: 58, Total Loss: 0.1503, loss_single: 0.1503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,282 - Iter: 59, Total Loss: 0.1489, loss_single: 0.1489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,318 - Iter: 60, Total Loss: 0.1475, loss_single: 0.1475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,353 - Iter: 61, Total Loss: 0.1463, loss_single: 0.1463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,388 - Iter: 62, Total Loss: 0.1453, loss_single: 0.1453, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,424 - Iter: 63, Total Loss: 0.1444, loss_single: 0.1444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,459 - Iter: 64, Total Loss: 0.1435, loss_single: 0.1435, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,494 - Iter: 65, Total Loss: 0.1426, loss_single: 0.1426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,530 - Iter: 66, Total Loss: 0.1417, loss_single: 0.1417, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,565 - Iter: 67, Total Loss: 0.1409, loss_single: 0.1409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,600 - Iter: 68, Total Loss: 0.1402, loss_single: 0.1402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,635 - Iter: 69, Total Loss: 0.1394, loss_single: 0.1394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,671 - Iter: 70, Total Loss: 0.1386, loss_single: 0.1386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,706 - Iter: 71, Total Loss: 0.1380, loss_single: 0.1380, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,741 - Iter: 72, Total Loss: 0.1376, loss_single: 0.1376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,776 - Iter: 73, Total Loss: 0.1370, loss_single: 0.1370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,811 - Iter: 74, Total Loss: 0.1365, loss_single: 0.1365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:26,846 - Iter: 75, Total Loss: 0.1360, loss_single: 0.1360, loss_poissn: 0.0000, loss_pacbed: 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0.1306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:27,692 - Iter: 99, Total Loss: 0.1305, loss_single: 0.1305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:27,727 - Iter: 100, Total Loss: 0.1304, loss_single: 0.1304, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:27,838 - Saving summary figures for iter 100 +2026-06-24 05:36:31,613 - ### Finished 100 iterations, averaged iter_t = 0.03893 with std = 0.040 ### +2026-06-24 05:36:31,613 - +2026-06-24 05:36:31,613 - ### The PtyRADSolver is finished in 9.429 sec ### +2026-06-24 05:36:31,613 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009/c30_small__simulation_data1__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-267_C12_18.2_phi12_230_C21_758_phi21_299_C23_882_phi23_3.72_C30_1.33e+05_C32_9.9.88e+05_phi56_333/simulation_data1__sample_000009.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 22.653152465820312 + probe_aberrations: + C10: -266.6025390625 + C12: 18.172391891479492 + C21: 757.7008056640625 + C23: 881.6241455078125 + C30: 133419.65625 + C32: 9907.30859375 + C34: -1121.2396240234375 + C41: -363432.125 + C43: -177851.125 + C45: 41571.30859375 + C50: 269112576.0 + C52: 18410188.0 + C54: 17605530.0 + C56: -788044.6875 + phi12: 229.65743370905165 + phi21: 298.59016168092154 + phi23: 3.719704373402842 + phi32: 59.121017795174 + phi34: 318.9114497825702 + phi41: 242.0133825213881 + phi43: 339.069714929109 + phi45: 55.73730451430925 + phi52: 311.7001633776274 + phi54: 199.50210754231034 + phi56: 333.4743419987645 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.43370673060417175 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000009_measurement.h5 + key: measurement + random_seed: 20261853 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000009 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/20260624_053637_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:36:36,278 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:36:36,278 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:36:36,278 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:36:36,278 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:36:36,278 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:36:36,278 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:36:36,278 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:36:36,278 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:36:36,278 - +2026-06-24 05:36:36,385 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:36:36,385 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:36:36,385 - Accelerator.num_process = 1 +2026-06-24 05:36:36,385 - Accelerator.mixed_precision = no +2026-06-24 05:36:36,409 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:36:36,409 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:36:36,409 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:36:36,409 - +2026-06-24 05:36:36,409 - ### System information ### +2026-06-24 05:36:36,409 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:36:36,409 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:36:36,409 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:36:36,409 - Machine: x86_64 +2026-06-24 05:36:36,409 - Processor: x86_64 +2026-06-24 05:36:36,409 - Available CPU cores: 8 +2026-06-24 05:36:36,410 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:36:36,410 - +2026-06-24 05:36:36,410 - ### GPU information ### +2026-06-24 05:36:36,410 - CUDA Available: True +2026-06-24 05:36:36,410 - CUDA Version: 13.0 +2026-06-24 05:36:36,410 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:36:36,410 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:36:36,410 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:36:36,410 - In addition, Triton does not directly support Windows. +2026-06-24 05:36:36,410 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:36:36,426 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:36:36,426 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:36:36,426 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:36:36,426 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:36:36,426 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:36:36,426 - +2026-06-24 05:36:36,426 - ### Python information ### +2026-06-24 05:36:36,428 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:36:36,428 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:36:36,428 - +2026-06-24 05:36:36,428 - ### Packages information ### +2026-06-24 05:36:36,428 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:36:36,429 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:36:36,430 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:36:36,431 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:36:36,431 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:36:36,431 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:36:36,431 - +2026-06-24 05:36:36,431 - ### Loading params file ### +2026-06-24 05:36:36,431 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000010.yaml +2026-06-24 05:36:36,438 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:36:36,439 - Success! Params file validated and defaults applied. +2026-06-24 05:36:36,439 - +2026-06-24 05:36:36,439 - ### Setting GPU Device ### +2026-06-24 05:36:36,439 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:36:36,439 - +2026-06-24 05:36:36,439 - Random seed: 20261854 provided by params file +2026-06-24 05:36:36,439 - ### Initializing Initializer ### +2026-06-24 05:36:36,440 - init_params are displayed below: +2026-06-24 05:36:36,440 - random_seed: 20261854 +2026-06-24 05:36:36,440 - probe_illum_type: electron +2026-06-24 05:36:36,440 - probe_kv: 60.0 +2026-06-24 05:36:36,440 - probe_conv_angle: 12.819171905517578 +2026-06-24 05:36:36,440 - probe_aberrations: {'C10': 6.817, 'C12': -46.184, 'phi12': 189.019, 'C21': 698.398, 'phi21': 27.966, 'C23': -991.115, 'phi23': 185.988, 'C30': 2867064.25, 'C32': -7273.422, 'phi32': 270.523, 'C34': 4690.002, 'phi34': 102.292, 'C41': -229145.469, 'phi41': 278.888, 'C43': 67091.086, 'phi43': 347.245, 'C45': 209215.375, 'phi45': 265.808, 'C50': 364242912.0, 'C52': 1600665.625, 'phi52': 83.851, 'C54': 10428370.0, 'phi54': 185.356, 'C56': 17220394.0, 'phi56': 117.476} +2026-06-24 05:36:36,440 - beam_kev: None +2026-06-24 05:36:36,440 - probe_dRn: None +2026-06-24 05:36:36,440 - probe_Rn: None +2026-06-24 05:36:36,440 - probe_D_H: None +2026-06-24 05:36:36,440 - probe_D_FZP: None +2026-06-24 05:36:36,440 - probe_Ls: None +2026-06-24 05:36:36,440 - meas_Npix: 128 +2026-06-24 05:36:36,440 - pos_N_scans: 256 +2026-06-24 05:36:36,440 - pos_N_scan_slow: 16 +2026-06-24 05:36:36,440 - pos_N_scan_fast: 16 +2026-06-24 05:36:36,440 - pos_scan_step_size: 0.36360010504722595 +2026-06-24 05:36:36,440 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:36:36,440 - probe_pmode_max: 6 +2026-06-24 05:36:36,440 - probe_pmode_init_pows: [0.02] +2026-06-24 05:36:36,440 - obj_omode_max: 1 +2026-06-24 05:36:36,440 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:36:36,440 - obj_Nlayer: 1 +2026-06-24 05:36:36,440 - obj_slice_thickness: 20.0 +2026-06-24 05:36:36,440 - simu_Npix: None +2026-06-24 05:36:36,440 - simu_match_mode: None +2026-06-24 05:36:36,440 - meas_permute: None +2026-06-24 05:36:36,440 - meas_reshape: [256, 128, 128] +2026-06-24 05:36:36,440 - meas_flipT: [0, 0, 0] +2026-06-24 05:36:36,440 - meas_crop: None +2026-06-24 05:36:36,440 - meas_pad: None +2026-06-24 05:36:36,440 - meas_resample: None +2026-06-24 05:36:36,440 - meas_add_source_size: None +2026-06-24 05:36:36,441 - meas_add_detector_blur: None +2026-06-24 05:36:36,441 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:36:36,441 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:36:36,441 - meas_add_poisson_noise: None +2026-06-24 05:36:36,441 - meas_export: None +2026-06-24 05:36:36,441 - probe_permute: None +2026-06-24 05:36:36,441 - probe_z_shift: None +2026-06-24 05:36:36,441 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:36:36,441 - pos_scan_flipT: None +2026-06-24 05:36:36,441 - pos_scan_affine: None +2026-06-24 05:36:36,441 - pos_scan_rand_std: 0.15 +2026-06-24 05:36:36,441 - obj_z_crop: None +2026-06-24 05:36:36,441 - obj_z_pad: None +2026-06-24 05:36:36,441 - obj_z_resample: None +2026-06-24 05:36:36,441 - meas_source: file +2026-06-24 05:36:36,441 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000010_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:36:36,441 - probe_source: simu +2026-06-24 05:36:36,441 - probe_params: None +2026-06-24 05:36:36,441 - pos_source: simu +2026-06-24 05:36:36,441 - pos_params: None +2026-06-24 05:36:36,441 - obj_source: simu +2026-06-24 05:36:36,441 - obj_params: None +2026-06-24 05:36:36,441 - tilt_source: simu +2026-06-24 05:36:36,441 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:36:36,441 - +2026-06-24 05:36:36,441 - ### Initializing cache ### +2026-06-24 05:36:36,441 - use_cached_obj = False +2026-06-24 05:36:36,441 - use_cached_probe = False +2026-06-24 05:36:36,441 - use_cached_pos = False +2026-06-24 05:36:36,441 - +2026-06-24 05:36:36,441 - ### Initializing measurements ### +2026-06-24 05:36:36,441 - Loading measurements from source = 'file' +2026-06-24 05:36:36,441 - Detected measurement file type = '.h5' +2026-06-24 05:36:36,520 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:36:36,520 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:36:36,522 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0085) +2026-06-24 05:36:36,522 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:36:36,522 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:36:36,523 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:36,523 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:36:36,523 - Normalizing by max of the 2D mean pattern intensity: 0.0066038887 +2026-06-24 05:36:36,524 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:36:36,525 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0092, 1.2810) +2026-06-24 05:36:36,526 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:36:36,527 - Pattern total int. statistics (min, mean, max) = (150.1019, 151.0493, 152.2493), with min/max = 98.6% +2026-06-24 05:36:36,528 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0092, 1.2810) +2026-06-24 05:36:36,528 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:36:36,528 - +2026-06-24 05:36:36,529 - ### Setting up calibration ### +2026-06-24 05:36:36,529 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:36:36,529 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:36:36,529 - Radius of fitted bright field disk (RBF) = 6.68 px with meas_Npix = 128 +2026-06-24 05:36:36,529 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1043 +2026-06-24 05:36:36,529 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:36:36,529 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:36:36,752 - Initial guess: center=(63.63, 63.64), radius=6.68, Gaussian blur std=0.50 +2026-06-24 05:36:36,764 - Final fit: center=(63.63, 63.64), radius=6.68, Gaussian blur std=0.66 +2026-06-24 05:36:36,764 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.74 px with Npix = 128 +2026-06-24 05:36:36,764 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:36:36,764 - +2026-06-24 05:36:36,764 - ### Setting init_variables dict ### +2026-06-24 05:36:36,764 - Derived values given input init_params: +2026-06-24 05:36:36,764 - kv = 60.0 kV +2026-06-24 05:36:36,764 - wavelength = 0.0487 Ang +2026-06-24 05:36:36,764 - conv_angle = 12.819171905517578 mrad +2026-06-24 05:36:36,764 - Npix = 128 px +2026-06-24 05:36:36,764 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:36,764 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:36,764 - da = 1.9008 mrad +2026-06-24 05:36:36,764 - angleMax = 121.6515 mrad +2026-06-24 05:36:36,764 - RBF = 6.7441 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:36:36,764 - n_alpha = 9.4898 (# conv_angle) +2026-06-24 05:36:36,764 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:36,764 - Rayleigh-limited resolution = 2.3155 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:36,764 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:36,764 - +2026-06-24 05:36:36,764 - ### Initializing probe ### +2026-06-24 05:36:36,764 - Loading probe from source = 'simu' +2026-06-24 05:36:36,764 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:36:36,765 - Start simulating STEM probe +2026-06-24 05:36:36,765 - kv = 60.0 kV +2026-06-24 05:36:36,765 - wavelength = 0.0487 Ang +2026-06-24 05:36:36,765 - conv_angle = 12.819171905517578 mrad +2026-06-24 05:36:36,765 - Npix = 128 px +2026-06-24 05:36:36,765 - dk = 0.0391 Ang^-1 +2026-06-24 05:36:36,765 - kMax = 2.5000 Ang^-1 +2026-06-24 05:36:36,765 - alpha_max = 121.6515 mrad +2026-06-24 05:36:36,765 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:36:36,765 - Rayleigh-limited resolution = 2.3155 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:36:36,765 - Real space probe extent = 25.6000 Ang +2026-06-24 05:36:36,765 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:36:36,765 - ------------------------------------------------------------------------------------ +2026-06-24 05:36:36,765 - C1,0 C1 6.8170 - Defocus (C10 = -df) +2026-06-24 05:36:36,765 - C1,2 A1 -46.1840 189.02 2-fold astigmatism +2026-06-24 05:36:36,765 - C2,1 3*B2 698.3980 27.97 Axial coma +2026-06-24 05:36:36,765 - C2,3 A2 -991.1150 185.99 3-fold astigmatism +2026-06-24 05:36:36,765 - C3,0 C3 2867064.2500 - Spherical aberration +2026-06-24 05:36:36,765 - C3,2 4*S3 -7273.4220 270.52 Axial star aberration +2026-06-24 05:36:36,765 - C3,4 A3 4690.0020 102.29 4-fold astigmatism +2026-06-24 05:36:36,765 - C4,1 4*B4 -229145.4690 278.89 Axial coma(4th) +2026-06-24 05:36:36,765 - C4,3 4*D4 67091.0860 347.25 3-lobe aberration +2026-06-24 05:36:36,765 - C4,5 A4 209215.3750 265.81 5-fold astigmatism +2026-06-24 05:36:36,765 - C5,0 C5 364242912.0000 - Spherical aberration (5th) +2026-06-24 05:36:36,765 - C5,2 6*S5 1600665.6250 83.85 Axial star aberration(5th) +2026-06-24 05:36:36,765 - C5,4 6*R5 10428370.0000 185.36 4-lobe aberration +2026-06-24 05:36:36,765 - C5,6 A5 17220394.0000 117.48 6-fold astigmatism +2026-06-24 05:36:36,768 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:36:36,768 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:36:36,768 - Creating 5 new probe modes from the major mode +2026-06-24 05:36:36,768 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:36:36,960 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:36:36,961 - Orthogonalizing 6 pmodes +2026-06-24 05:36:36,964 - Sorting 6 pmodes by their intensities +2026-06-24 05:36:36,964 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:36:36,965 - sum(|probe_data|**2) = 151.05, while meas_total_ints (min, mean, max) = (150.1019, 151.0493, 152.2493) +2026-06-24 05:36:36,965 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:36:36,965 - +2026-06-24 05:36:36,965 - ### Initializing probe positions ### +2026-06-24 05:36:36,965 - Loading probe positions from source = 'simu' +2026-06-24 05:36:36,965 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:36:36,965 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3636, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:36:36,965 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:36:36,967 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:36:36,967 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 43]) +2026-06-24 05:36:36,968 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:36:36,968 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:36:36,968 - +2026-06-24 05:36:36,968 - ### Initializing object ### +2026-06-24 05:36:36,968 - Loading object from source = 'simu' +2026-06-24 05:36:36,968 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:36:36,969 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:36:36,969 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 05:36:36,969 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 05:36:36,969 - +2026-06-24 05:36:36,969 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:36:36,969 - omode_occu (omode) = float32, (1,) +2026-06-24 05:36:36,970 - +2026-06-24 05:36:36,970 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:36:36,970 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 05:36:36,970 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:36:36,970 - +2026-06-24 05:36:36,970 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:36:36,970 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:36:36,970 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:36:36,970 - +2026-06-24 05:36:36,970 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:36:36,970 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:36:36,971 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:36:36,971 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:36:36,971 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:36:36,971 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 05:36:36,971 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:36:36,971 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:36:36,971 - +2026-06-24 05:36:36,971 - ### Collecting reconstruction provenance ### +2026-06-24 05:36:36,971 - Reconstruction provenance is collected and initialized. +2026-06-24 05:36:36,971 - +2026-06-24 05:36:36,971 - ### Initializing loss function ### +2026-06-24 05:36:36,971 - Active loss types: +2026-06-24 05:36:36,971 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:36:36,971 - +2026-06-24 05:36:36,971 - ### Initializing constraint function ### +2026-06-24 05:36:36,971 - Active constraint types: +2026-06-24 05:36:36,971 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:36,971 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:36:36,971 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:36:36,971 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:36:36,971 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:36:36,972 - +2026-06-24 05:36:36,972 - ### Done initializing PtyRADSolver ### +2026-06-24 05:36:36,972 - +2026-06-24 05:36:37,095 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:36:37,096 - +2026-06-24 05:36:37,096 - ### Initializing PtychoModel model ### +2026-06-24 05:36:37,167 - ### PtychoModel optimizable variables ### +2026-06-24 05:36:37,167 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:37,167 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:37,167 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:37,167 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:36:37,167 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:36:37,167 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:36:37,167 - +2026-06-24 05:36:37,167 - ### Optimizable variables statitsics ### +2026-06-24 05:36:37,167 - Total measurement values : 4,194,304 +2026-06-24 05:36:37,167 - Total optimizing variables: 267,058 +2026-06-24 05:36:37,167 - Overdetermined ratio : 15.71 +2026-06-24 05:36:37,167 - +2026-06-24 05:36:37,167 - ### Model behavior ### +2026-06-24 05:36:37,167 - Tilt propagator : False +2026-06-24 05:36:37,168 - Change slice thickness : False +2026-06-24 05:36:37,168 - Detector blur : False +2026-06-24 05:36:37,168 - Preload data : True +2026-06-24 05:36:37,168 - On-the-fly meas padding : False +2026-06-24 05:36:37,168 - On-the-fly meas resample : False +2026-06-24 05:36:37,168 - On-the-fly simu match mode: None +2026-06-24 05:36:37,168 - +2026-06-24 05:36:37,208 - ### Done initializing PtychoModel model ### +2026-06-24 05:36:37,209 - +2026-06-24 05:36:37,209 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:36:37,209 - +2026-06-24 05:36:37,209 - ### Generating indices, batches, and output_path ### +2026-06-24 05:36:37,210 - d90 = 65.000 px or 13.000 Ang +2026-06-24 05:36:37,210 - Selecting indices with the 'full' mode +2026-06-24 05:36:37,678 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:36:37,751 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:36:37,752 - Original recon_dir_affixes = ['default'] +2026-06-24 05:36:37,752 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:36:37,758 - Path corrected for compatibility: +2026-06-24 05:36:37,758 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7.27e+03_phi32_271_C34_4.69e+03_phi34_102_C41_-2.29e+05_phi41_279_C43_6.71e+04_phi43_347_C45_2.09e+05_phi45_266_C50_3.64e+08_C52_1.6e+06_phi52_83.9_C54_1.04e+07_phi54_185_C56_1.72e+07_phi56_117 +2026-06-24 05:36:37,758 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117 +2026-06-24 05:36:37,759 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117' is generated! +2026-06-24 05:36:37,903 - +2026-06-24 05:36:37,904 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/20260624_053637_ptyrad_log.txt ### +2026-06-24 05:36:37,904 - +2026-06-24 05:36:37,905 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:36:37,905 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:36:37,905 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:36:39,099 - Iter: 1, Total Loss: 1.2446, loss_single: 1.2446, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:36:39,136 - Iter: 2, Total Loss: 1.1707, loss_single: 1.1707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:36:39,172 - Iter: 3, Total Loss: 1.1140, loss_single: 1.1140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,208 - Iter: 4, Total Loss: 1.0532, loss_single: 1.0532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,243 - Iter: 5, Total Loss: 0.9869, loss_single: 0.9869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,279 - Iter: 6, Total Loss: 0.9253, loss_single: 0.9253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,313 - Iter: 7, Total Loss: 0.8804, loss_single: 0.8804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:36:39,349 - Iter: 8, Total Loss: 0.8428, loss_single: 0.8428, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,385 - Iter: 9, Total Loss: 0.7982, loss_single: 0.7982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,420 - Iter: 10, Total Loss: 0.7609, loss_single: 0.7609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,455 - Iter: 11, Total Loss: 0.7257, loss_single: 0.7257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,490 - Iter: 12, Total Loss: 0.6827, loss_single: 0.6827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,525 - Iter: 13, Total Loss: 0.6416, loss_single: 0.6416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,560 - Iter: 14, Total Loss: 0.6026, loss_single: 0.6026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,596 - Iter: 15, Total Loss: 0.5681, loss_single: 0.5681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,632 - Iter: 16, Total Loss: 0.5397, loss_single: 0.5397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,667 - Iter: 17, Total Loss: 0.5132, loss_single: 0.5132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:39,702 - Iter: 18, Total Loss: 0.4897, loss_single: 0.4897, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.3760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:42,566 - Iter: 99, Total Loss: 0.3757, loss_single: 0.3757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:42,601 - Iter: 100, Total Loss: 0.3755, loss_single: 0.3755, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:36:42,711 - Saving summary figures for iter 100 +2026-06-24 05:36:46,280 - ### Finished 100 iterations, averaged iter_t = 0.038926 with std = 0.040 ### +2026-06-24 05:36:46,280 - +2026-06-24 05:36:46,280 - ### The PtyRADSolver is finished in 9.184 sec ### +2026-06-24 05:36:46,280 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/model_iter0100.hdf5 b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/model_iter0100.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..17d4fe0973b61bafcf58e6d0d1f32a51337ecf9d --- /dev/null +++ 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/simulation_data1__sample_000010.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/simulation_data1__sample_000010.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ad67883200f9bdffc2a1243cee377508c0f152e0 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/simulation_data1__sample_000010.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 12.819171905517578 + probe_aberrations: + C10: 6.817439556121826 + C12: -46.1841926574707 + C21: 698.3984985351562 + C23: -991.1152954101562 + C30: 2867064.25 + C32: -7273.42236328125 + C34: 4690.001953125 + C41: -229145.46875 + C43: 67091.0859375 + C45: 209215.375 + C50: 364242912.0 + C52: 1600665.625 + C54: 10428370.0 + C56: 17220394.0 + phi12: 189.01854580790615 + phi21: 27.966190773596992 + phi23: 185.98835970338666 + phi32: 270.5234663812351 + phi34: 102.29181584050822 + phi41: 278.8881258501829 + phi43: 347.2451235165341 + phi45: 265.80825894809516 + phi52: 83.85078319471569 + phi54: 185.35621203532367 + phi56: 117.47605719568774 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.36360010504722595 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000010_measurement.h5 + key: measurement + random_seed: 20261854 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000010 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c54432f816eddd62b57362f73bf63cfa08ff7c5185a5b0d7332168d7ae4fae86 +size 1187314 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..377ad67e8c0b643a5dc9bd625f902b21fc2f714f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000010/c30_small__simulation_data1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_6.82_C12_-46.2_phi12_189_C21_698_phi21_28_C23_-991_phi23_186_C30_2.87e+06_C32_-7..72e+07_phi56_117/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eda2f45cca1d274f93d47355351610c1c0d99ad3fc369e9d7ebd765f9bc32b22 +size 48277 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/20260624_053722_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/20260624_053722_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cd8beee063e471b3db6b228f65fdcda3e5e1cd9d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/20260624_053722_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:37:20,480 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:37:20,480 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:37:20,480 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:37:20,480 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:37:20,480 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:37:20,480 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:37:20,480 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:37:20,480 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:37:20,480 - +2026-06-24 05:37:20,587 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:37:20,587 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:37:20,587 - Accelerator.num_process = 1 +2026-06-24 05:37:20,587 - Accelerator.mixed_precision = no +2026-06-24 05:37:20,598 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:37:20,598 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:37:20,598 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:37:20,598 - +2026-06-24 05:37:20,598 - ### System information ### +2026-06-24 05:37:20,598 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:37:20,598 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:37:20,598 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:37:20,598 - Machine: x86_64 +2026-06-24 05:37:20,599 - Processor: x86_64 +2026-06-24 05:37:20,599 - Available CPU cores: 8 +2026-06-24 05:37:20,599 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:37:20,599 - +2026-06-24 05:37:20,599 - ### GPU information ### +2026-06-24 05:37:20,599 - CUDA Available: True +2026-06-24 05:37:20,599 - CUDA Version: 13.0 +2026-06-24 05:37:20,599 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:37:20,599 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:37:20,599 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:37:20,599 - In addition, Triton does not directly support Windows. +2026-06-24 05:37:20,599 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:37:20,615 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:37:20,615 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:37:20,615 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:37:20,615 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:37:20,615 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:37:20,615 - +2026-06-24 05:37:20,615 - ### Python information ### +2026-06-24 05:37:20,617 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:37:20,617 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:37:20,617 - +2026-06-24 05:37:20,617 - ### Packages information ### +2026-06-24 05:37:20,618 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:37:20,618 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:37:20,619 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:37:20,620 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:37:20,620 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:37:20,620 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:37:20,620 - +2026-06-24 05:37:20,620 - ### Loading params file ### +2026-06-24 05:37:20,620 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000013.yaml +2026-06-24 05:37:20,627 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:37:20,628 - Success! Params file validated and defaults applied. +2026-06-24 05:37:20,628 - +2026-06-24 05:37:20,628 - ### Setting GPU Device ### +2026-06-24 05:37:20,628 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:37:20,628 - +2026-06-24 05:37:20,628 - Random seed: 20261857 provided by params file +2026-06-24 05:37:20,628 - ### Initializing Initializer ### +2026-06-24 05:37:20,629 - init_params are displayed below: +2026-06-24 05:37:20,629 - random_seed: 20261857 +2026-06-24 05:37:20,629 - probe_illum_type: electron +2026-06-24 05:37:20,629 - probe_kv: 80.0 +2026-06-24 05:37:20,629 - probe_conv_angle: 16.1203670501709 +2026-06-24 05:37:20,629 - probe_aberrations: {'C10': -560.077, 'C12': 35.326, 'phi12': 330.623, 'C21': 809.986, 'phi21': 130.577, 'C23': -494.813, 'phi23': 41.647, 'C30': 3962327.75, 'C32': -7056.434, 'phi32': 211.292, 'C34': -5681.441, 'phi34': 145.407, 'C41': -223541.406, 'phi41': 123.519, 'C43': 129071.148, 'phi43': 245.656, 'C45': 124501.633, 'phi45': 192.589, 'C50': -174077264.0, 'C52': -7003224.5, 'phi52': 181.199, 'C54': 9173544.0, 'phi54': 199.834, 'C56': 11069104.0, 'phi56': 12.622} +2026-06-24 05:37:20,629 - beam_kev: None +2026-06-24 05:37:20,629 - probe_dRn: None +2026-06-24 05:37:20,629 - probe_Rn: None +2026-06-24 05:37:20,629 - probe_D_H: None +2026-06-24 05:37:20,629 - probe_D_FZP: None +2026-06-24 05:37:20,629 - probe_Ls: None +2026-06-24 05:37:20,629 - meas_Npix: 128 +2026-06-24 05:37:20,629 - pos_N_scans: 256 +2026-06-24 05:37:20,629 - pos_N_scan_slow: 16 +2026-06-24 05:37:20,629 - pos_N_scan_fast: 16 +2026-06-24 05:37:20,629 - pos_scan_step_size: 0.361175537109375 +2026-06-24 05:37:20,629 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:37:20,629 - probe_pmode_max: 6 +2026-06-24 05:37:20,629 - probe_pmode_init_pows: [0.02] +2026-06-24 05:37:20,629 - obj_omode_max: 1 +2026-06-24 05:37:20,629 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:37:20,629 - obj_Nlayer: 1 +2026-06-24 05:37:20,629 - obj_slice_thickness: 20.0 +2026-06-24 05:37:20,629 - simu_Npix: None +2026-06-24 05:37:20,629 - simu_match_mode: None +2026-06-24 05:37:20,629 - meas_permute: None +2026-06-24 05:37:20,629 - meas_reshape: [256, 128, 128] +2026-06-24 05:37:20,629 - meas_flipT: [0, 0, 0] +2026-06-24 05:37:20,629 - meas_crop: None +2026-06-24 05:37:20,629 - meas_pad: None +2026-06-24 05:37:20,629 - meas_resample: None +2026-06-24 05:37:20,629 - meas_add_source_size: None +2026-06-24 05:37:20,629 - meas_add_detector_blur: None +2026-06-24 05:37:20,629 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:37:20,630 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:37:20,630 - meas_add_poisson_noise: None +2026-06-24 05:37:20,630 - meas_export: None +2026-06-24 05:37:20,630 - probe_permute: None +2026-06-24 05:37:20,630 - probe_z_shift: None +2026-06-24 05:37:20,630 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:37:20,630 - pos_scan_flipT: None +2026-06-24 05:37:20,630 - pos_scan_affine: None +2026-06-24 05:37:20,630 - pos_scan_rand_std: 0.15 +2026-06-24 05:37:20,630 - obj_z_crop: None +2026-06-24 05:37:20,630 - obj_z_pad: None +2026-06-24 05:37:20,630 - obj_z_resample: None +2026-06-24 05:37:20,630 - meas_source: file +2026-06-24 05:37:20,630 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000013_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:37:20,630 - probe_source: simu +2026-06-24 05:37:20,630 - probe_params: None +2026-06-24 05:37:20,630 - pos_source: simu +2026-06-24 05:37:20,630 - pos_params: None +2026-06-24 05:37:20,630 - obj_source: simu +2026-06-24 05:37:20,630 - obj_params: None +2026-06-24 05:37:20,630 - tilt_source: simu +2026-06-24 05:37:20,630 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:37:20,630 - +2026-06-24 05:37:20,630 - ### Initializing cache ### +2026-06-24 05:37:20,630 - use_cached_obj = False +2026-06-24 05:37:20,630 - use_cached_probe = False +2026-06-24 05:37:20,630 - use_cached_pos = False +2026-06-24 05:37:20,630 - +2026-06-24 05:37:20,630 - ### Initializing measurements ### +2026-06-24 05:37:20,630 - Loading measurements from source = 'file' +2026-06-24 05:37:20,630 - Detected measurement file type = '.h5' +2026-06-24 05:37:20,706 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:37:20,706 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:37:20,708 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0047) +2026-06-24 05:37:20,708 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:37:20,708 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:37:20,709 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:37:20,709 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:37:20,710 - Normalizing by max of the 2D mean pattern intensity: 0.0029769363 +2026-06-24 05:37:20,710 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:37:20,712 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0204, 1.5802) +2026-06-24 05:37:20,712 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:37:20,713 - Pattern total int. statistics (min, mean, max) = (327.9684, 334.6317, 339.9153), with min/max = 96.5% +2026-06-24 05:37:20,715 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0204, 1.5802) +2026-06-24 05:37:20,715 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:37:20,715 - +2026-06-24 05:37:20,715 - ### Setting up calibration ### +2026-06-24 05:37:20,715 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:37:20,715 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:37:20,715 - Radius of fitted bright field disk (RBF) = 9.84 px with meas_Npix = 128 +2026-06-24 05:37:20,715 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1537 +2026-06-24 05:37:20,715 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:37:20,715 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:37:20,934 - Initial guess: center=(63.61, 63.64), radius=9.84, Gaussian blur std=0.50 +2026-06-24 05:37:20,949 - Final fit: center=(63.61, 63.64), radius=9.84, Gaussian blur std=0.70 +2026-06-24 05:37:20,949 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.88 px with Npix = 128 +2026-06-24 05:37:20,949 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:37:20,949 - +2026-06-24 05:37:20,949 - ### Setting init_variables dict ### +2026-06-24 05:37:20,949 - Derived values given input init_params: +2026-06-24 05:37:20,949 - kv = 80.0 kV +2026-06-24 05:37:20,949 - wavelength = 0.0418 Ang +2026-06-24 05:37:20,949 - conv_angle = 16.1203670501709 mrad +2026-06-24 05:37:20,949 - Npix = 128 px +2026-06-24 05:37:20,949 - dk = 0.0391 Ang^-1 +2026-06-24 05:37:20,949 - kMax = 2.5000 Ang^-1 +2026-06-24 05:37:20,949 - da = 1.6311 mrad +2026-06-24 05:37:20,950 - angleMax = 104.3929 mrad +2026-06-24 05:37:20,950 - RBF = 9.8829 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:37:20,950 - n_alpha = 6.4758 (# conv_angle) +2026-06-24 05:37:20,950 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:37:20,950 - Rayleigh-limited resolution = 1.5801 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:37:20,950 - Real space probe extent = 25.6000 Ang +2026-06-24 05:37:20,950 - +2026-06-24 05:37:20,950 - ### Initializing probe ### +2026-06-24 05:37:20,950 - Loading probe from source = 'simu' +2026-06-24 05:37:20,950 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:37:20,950 - Start simulating STEM probe +2026-06-24 05:37:20,950 - kv = 80.0 kV +2026-06-24 05:37:20,950 - wavelength = 0.0418 Ang +2026-06-24 05:37:20,950 - conv_angle = 16.1203670501709 mrad +2026-06-24 05:37:20,950 - Npix = 128 px +2026-06-24 05:37:20,950 - dk = 0.0391 Ang^-1 +2026-06-24 05:37:20,950 - kMax = 2.5000 Ang^-1 +2026-06-24 05:37:20,950 - alpha_max = 104.3929 mrad +2026-06-24 05:37:20,950 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:37:20,950 - Rayleigh-limited resolution = 1.5801 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:37:20,950 - Real space probe extent = 25.6000 Ang +2026-06-24 05:37:20,950 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:37:20,950 - ------------------------------------------------------------------------------------- +2026-06-24 05:37:20,950 - C1,0 C1 -560.0770 - Defocus (C10 = -df) +2026-06-24 05:37:20,951 - C1,2 A1 35.3260 330.62 2-fold astigmatism +2026-06-24 05:37:20,951 - C2,1 3*B2 809.9860 130.58 Axial coma +2026-06-24 05:37:20,951 - C2,3 A2 -494.8130 41.65 3-fold astigmatism +2026-06-24 05:37:20,951 - C3,0 C3 3962327.7500 - Spherical aberration +2026-06-24 05:37:20,951 - C3,2 4*S3 -7056.4340 211.29 Axial star aberration +2026-06-24 05:37:20,951 - C3,4 A3 -5681.4410 145.41 4-fold astigmatism +2026-06-24 05:37:20,951 - C4,1 4*B4 -223541.4060 123.52 Axial coma(4th) +2026-06-24 05:37:20,951 - C4,3 4*D4 129071.1480 245.66 3-lobe aberration +2026-06-24 05:37:20,951 - C4,5 A4 124501.6330 192.59 5-fold astigmatism +2026-06-24 05:37:20,951 - C5,0 C5 -174077264.0000 - Spherical aberration (5th) +2026-06-24 05:37:20,951 - C5,2 6*S5 -7003224.5000 181.20 Axial star aberration(5th) +2026-06-24 05:37:20,951 - C5,4 6*R5 9173544.0000 199.83 4-lobe aberration +2026-06-24 05:37:20,951 - C5,6 A5 11069104.0000 12.62 6-fold astigmatism +2026-06-24 05:37:20,954 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:37:20,954 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:37:20,954 - Creating 5 new probe modes from the major mode +2026-06-24 05:37:20,954 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:37:21,050 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:37:21,051 - Orthogonalizing 6 pmodes +2026-06-24 05:37:21,053 - Sorting 6 pmodes by their intensities +2026-06-24 05:37:21,054 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:37:21,054 - sum(|probe_data|**2) = 334.63, while meas_total_ints (min, mean, max) = (327.9684, 334.6317, 339.9153) +2026-06-24 05:37:21,055 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:37:21,055 - +2026-06-24 05:37:21,055 - ### Initializing probe positions ### +2026-06-24 05:37:21,055 - Loading probe positions from source = 'simu' +2026-06-24 05:37:21,055 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:37:21,055 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3612, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:37:21,055 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:37:21,057 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:37:21,057 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 05:37:21,057 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:37:21,057 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:37:21,057 - +2026-06-24 05:37:21,057 - ### Initializing object ### +2026-06-24 05:37:21,057 - Loading object from source = 'simu' +2026-06-24 05:37:21,057 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:37:21,059 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:37:21,059 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 05:37:21,059 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 05:37:21,059 - +2026-06-24 05:37:21,059 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:37:21,059 - omode_occu (omode) = float32, (1,) +2026-06-24 05:37:21,059 - +2026-06-24 05:37:21,059 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:37:21,059 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 05:37:21,060 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:37:21,060 - +2026-06-24 05:37:21,060 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:37:21,060 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:37:21,060 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:37:21,060 - +2026-06-24 05:37:21,060 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:37:21,060 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:37:21,060 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:37:21,060 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:37:21,060 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:37:21,060 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 05:37:21,060 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:37:21,060 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:37:21,060 - +2026-06-24 05:37:21,061 - ### Collecting reconstruction provenance ### +2026-06-24 05:37:21,061 - Reconstruction provenance is collected and initialized. +2026-06-24 05:37:21,061 - +2026-06-24 05:37:21,061 - ### Initializing loss function ### +2026-06-24 05:37:21,061 - Active loss types: +2026-06-24 05:37:21,061 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:37:21,061 - +2026-06-24 05:37:21,061 - ### Initializing constraint function ### +2026-06-24 05:37:21,061 - Active constraint types: +2026-06-24 05:37:21,061 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:37:21,061 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:37:21,061 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:37:21,061 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:37:21,061 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:37:21,061 - +2026-06-24 05:37:21,061 - ### Done initializing PtyRADSolver ### +2026-06-24 05:37:21,061 - +2026-06-24 05:37:21,185 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:37:21,185 - +2026-06-24 05:37:21,185 - ### Initializing PtychoModel model ### +2026-06-24 05:37:21,268 - ### PtychoModel optimizable variables ### +2026-06-24 05:37:21,268 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:37:21,268 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:37:21,268 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:37:21,268 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:37:21,268 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:37:21,268 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:37:21,268 - +2026-06-24 05:37:21,268 - ### Optimizable variables statitsics ### +2026-06-24 05:37:21,268 - Total measurement values : 4,194,304 +2026-06-24 05:37:21,268 - Total optimizing variables: 267,058 +2026-06-24 05:37:21,268 - Overdetermined ratio : 15.71 +2026-06-24 05:37:21,268 - +2026-06-24 05:37:21,268 - ### Model behavior ### +2026-06-24 05:37:21,268 - Tilt propagator : False +2026-06-24 05:37:21,268 - Change slice thickness : False +2026-06-24 05:37:21,268 - Detector blur : False +2026-06-24 05:37:21,268 - Preload data : True +2026-06-24 05:37:21,268 - On-the-fly meas padding : False +2026-06-24 05:37:21,268 - On-the-fly meas resample : False +2026-06-24 05:37:21,269 - On-the-fly simu match mode: None +2026-06-24 05:37:21,269 - +2026-06-24 05:37:21,310 - ### Done initializing PtychoModel model ### +2026-06-24 05:37:21,310 - +2026-06-24 05:37:21,310 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:37:21,310 - +2026-06-24 05:37:21,310 - ### Generating indices, batches, and output_path ### +2026-06-24 05:37:21,312 - d90 = 49.000 px or 9.800 Ang +2026-06-24 05:37:21,312 - Selecting indices with the 'full' mode +2026-06-24 05:37:21,771 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:37:21,846 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:37:21,847 - Original recon_dir_affixes = ['default'] +2026-06-24 05:37:21,847 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:37:21,853 - Path corrected for compatibility: +2026-06-24 05:37:21,853 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_211_C34_-5.68e+03_phi34_145_C41_-2.24e+05_phi41_124_C43_1.29e+05_phi43_246_C45_1.25e+05_phi45_193_C50_-1.74e+08_C52_-7e+06_phi52_181_C54_9.17e+06_phi54_200_C56_1.11e+07_phi56_12.6 +2026-06-24 05:37:21,853 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6 +2026-06-24 05:37:21,854 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6' is generated! +2026-06-24 05:37:22,001 - +2026-06-24 05:37:22,002 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/20260624_053722_ptyrad_log.txt ### +2026-06-24 05:37:22,002 - +2026-06-24 05:37:22,003 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:37:22,003 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:37:22,003 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:37:23,194 - Iter: 1, Total Loss: 1.1104, loss_single: 1.1104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:37:23,231 - Iter: 2, Total Loss: 1.0764, loss_single: 1.0764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:37:23,267 - Iter: 3, Total Loss: 1.0504, loss_single: 1.0504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,302 - Iter: 4, Total Loss: 1.0240, loss_single: 1.0240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,337 - Iter: 5, Total Loss: 0.9998, loss_single: 0.9998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,372 - Iter: 6, Total Loss: 0.9790, loss_single: 0.9790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,408 - Iter: 7, Total Loss: 0.9556, loss_single: 0.9556, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,444 - Iter: 8, Total Loss: 0.9310, loss_single: 0.9310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,479 - Iter: 9, Total Loss: 0.9070, loss_single: 0.9070, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,515 - Iter: 10, Total Loss: 0.8827, loss_single: 0.8827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,550 - Iter: 11, Total Loss: 0.8608, loss_single: 0.8608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,585 - Iter: 12, Total Loss: 0.8432, loss_single: 0.8432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,620 - Iter: 13, Total Loss: 0.8253, loss_single: 0.8253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,655 - Iter: 14, Total Loss: 0.8073, loss_single: 0.8073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,691 - Iter: 15, Total Loss: 0.7904, loss_single: 0.7904, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,727 - Iter: 16, Total Loss: 0.7702, loss_single: 0.7702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,762 - Iter: 17, Total Loss: 0.7521, loss_single: 0.7521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,798 - Iter: 18, Total Loss: 0.7381, loss_single: 0.7381, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,833 - Iter: 19, Total Loss: 0.7238, loss_single: 0.7238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,869 - Iter: 20, Total Loss: 0.7099, loss_single: 0.7099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,904 - Iter: 21, Total Loss: 0.6969, loss_single: 0.6969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,939 - Iter: 22, Total Loss: 0.6858, loss_single: 0.6858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:23,975 - Iter: 23, Total Loss: 0.6741, loss_single: 0.6741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:37:24,010 - Iter: 24, Total Loss: 0.6619, loss_single: 0.6619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:37:24,045 - Iter: 25, Total Loss: 0.6503, loss_single: 0.6503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,081 - Iter: 26, Total Loss: 0.6399, loss_single: 0.6399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,116 - Iter: 27, Total Loss: 0.6320, loss_single: 0.6320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:37:24,151 - Iter: 28, Total Loss: 0.6250, loss_single: 0.6250, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,187 - Iter: 29, Total Loss: 0.6170, loss_single: 0.6170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,222 - Iter: 30, Total Loss: 0.6096, loss_single: 0.6096, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,257 - Iter: 31, Total Loss: 0.6029, loss_single: 0.6029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,296 - Iter: 32, Total Loss: 0.5957, loss_single: 0.5957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:37:24,332 - Iter: 33, Total Loss: 0.5903, loss_single: 0.5903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,367 - Iter: 34, Total Loss: 0.5861, loss_single: 0.5861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,402 - Iter: 35, Total Loss: 0.5811, loss_single: 0.5811, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,437 - Iter: 36, Total Loss: 0.5764, loss_single: 0.5764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,473 - Iter: 37, Total Loss: 0.5724, loss_single: 0.5724, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,509 - Iter: 38, Total Loss: 0.5688, loss_single: 0.5688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:37:24,544 - Iter: 39, Total Loss: 0.5653, loss_single: 0.5653, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,579 - Iter: 40, Total Loss: 0.5618, loss_single: 0.5618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,615 - Iter: 41, Total Loss: 0.5585, loss_single: 0.5585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,651 - Iter: 42, Total Loss: 0.5560, loss_single: 0.5560, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,686 - Iter: 43, Total Loss: 0.5537, loss_single: 0.5537, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,721 - Iter: 44, Total Loss: 0.5512, loss_single: 0.5512, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,756 - Iter: 45, Total Loss: 0.5491, loss_single: 0.5491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,792 - Iter: 46, Total Loss: 0.5474, loss_single: 0.5474, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,827 - Iter: 47, Total Loss: 0.5459, loss_single: 0.5459, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,862 - Iter: 48, Total Loss: 0.5444, loss_single: 0.5444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,898 - Iter: 49, Total Loss: 0.5433, loss_single: 0.5433, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,933 - Iter: 50, Total Loss: 0.5426, loss_single: 0.5426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:24,969 - Iter: 51, Total Loss: 0.5418, loss_single: 0.5418, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:25,004 - Iter: 52, Total Loss: 0.5410, loss_single: 0.5410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:37:25,039 - 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Saving summary figures for iter 100 +2026-06-24 05:37:30,442 - ### Finished 100 iterations, averaged iter_t = 0.039031 with std = 0.040 ### +2026-06-24 05:37:30,443 - +2026-06-24 05:37:30,443 - ### The PtyRADSolver is finished in 9.258 sec ### +2026-06-24 05:37:30,443 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..ce36a2c23c2546dc942fddf10bd9da2c94c3edda Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/simulation_data1__sample_000013.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/simulation_data1__sample_000013.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e6c2c38c1ee835aa8da1c8d38aca236c4279bb5c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013/c30_small__simulation_data1__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-560_C12_35.3_phi12_331_C21_810_phi21_131_C23_-495_phi23_41.6_C30_3.96e+06_C32_-7.06e+03_phi32_2.6/simulation_data1__sample_000013.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 16.1203670501709 + probe_aberrations: + C10: -560.0769653320312 + C12: 35.326045989990234 + C21: 809.986083984375 + C23: -494.8126220703125 + C30: 3962327.75 + C32: -7056.43408203125 + C34: -5681.44140625 + C41: -223541.40625 + C43: 129071.1484375 + C45: 124501.6328125 + C50: -174077264.0 + C52: -7003224.5 + C54: 9173544.0 + C56: 11069104.0 + phi12: 330.6234483599579 + phi21: 130.5769337596625 + phi23: 41.64716725661196 + phi32: 211.29175171018272 + phi34: 145.4065858440808 + phi41: 123.51869823364135 + phi43: 245.65630489634944 + phi45: 192.58945066825885 + phi52: 181.19882615169863 + phi54: 199.83397277370292 + phi56: 12.622103355045292 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.361175537109375 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000013_measurement.h5 + key: measurement + random_seed: 20261857 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000013 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000013 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303/20260624_053806_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303/20260624_053806_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..6adef39886eafc0a6e823732c8167e6273122845 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303/20260624_053806_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:38:04,925 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:38:04,925 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:38:04,925 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:38:04,925 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:38:04,925 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:38:04,925 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:38:04,925 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:38:04,925 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:38:04,925 - +2026-06-24 05:38:05,031 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:38:05,031 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:38:05,031 - Accelerator.num_process = 1 +2026-06-24 05:38:05,031 - Accelerator.mixed_precision = no +2026-06-24 05:38:05,054 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:38:05,054 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:38:05,054 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:38:05,054 - +2026-06-24 05:38:05,054 - ### System information ### +2026-06-24 05:38:05,054 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:38:05,054 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:38:05,054 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:38:05,054 - Machine: x86_64 +2026-06-24 05:38:05,054 - Processor: x86_64 +2026-06-24 05:38:05,054 - Available CPU cores: 8 +2026-06-24 05:38:05,054 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:38:05,054 - +2026-06-24 05:38:05,054 - ### GPU information ### +2026-06-24 05:38:05,054 - CUDA Available: True +2026-06-24 05:38:05,054 - CUDA Version: 13.0 +2026-06-24 05:38:05,055 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:38:05,055 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:38:05,055 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:38:05,055 - In addition, Triton does not directly support Windows. +2026-06-24 05:38:05,055 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:38:05,070 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:38:05,070 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:38:05,070 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:38:05,070 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:38:05,070 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:38:05,070 - +2026-06-24 05:38:05,070 - ### Python information ### +2026-06-24 05:38:05,071 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:38:05,071 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:38:05,071 - +2026-06-24 05:38:05,071 - ### Packages information ### +2026-06-24 05:38:05,072 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:38:05,073 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:38:05,073 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:38:05,074 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:38:05,074 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:38:05,074 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:38:05,074 - +2026-06-24 05:38:05,074 - ### Loading params file ### +2026-06-24 05:38:05,075 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000016.yaml +2026-06-24 05:38:05,081 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:38:05,082 - Success! Params file validated and defaults applied. +2026-06-24 05:38:05,082 - +2026-06-24 05:38:05,082 - ### Setting GPU Device ### +2026-06-24 05:38:05,082 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:38:05,082 - +2026-06-24 05:38:05,082 - Random seed: 20261860 provided by params file +2026-06-24 05:38:05,082 - ### Initializing Initializer ### +2026-06-24 05:38:05,082 - init_params are displayed below: +2026-06-24 05:38:05,083 - random_seed: 20261860 +2026-06-24 05:38:05,083 - probe_illum_type: electron +2026-06-24 05:38:05,083 - probe_kv: 300.0 +2026-06-24 05:38:05,083 - probe_conv_angle: 10.52404499053955 +2026-06-24 05:38:05,083 - probe_aberrations: {'C10': -644.5, 'C12': -38.844, 'phi12': 109.382, 'C21': -35.942, 'phi21': 346.359, 'C23': 643.489, 'phi23': 270.924, 'C30': 1462981.375, 'C32': 4877.956, 'phi32': 147.219, 'C34': 393.031, 'phi34': 258.074, 'C41': -405787.281, 'phi41': 352.498, 'C43': -96929.461, 'phi43': 47.073, 'C45': 479755.188, 'phi45': 124.592, 'C50': 332991232.0, 'C52': -666431.125, 'phi52': 256.261, 'C54': 6416499.5, 'phi54': 101.013, 'C56': 16632105.0, 'phi56': 302.969} +2026-06-24 05:38:05,083 - beam_kev: None +2026-06-24 05:38:05,083 - probe_dRn: None +2026-06-24 05:38:05,083 - probe_Rn: None +2026-06-24 05:38:05,083 - probe_D_H: None +2026-06-24 05:38:05,083 - probe_D_FZP: None +2026-06-24 05:38:05,083 - probe_Ls: None +2026-06-24 05:38:05,083 - meas_Npix: 128 +2026-06-24 05:38:05,083 - pos_N_scans: 256 +2026-06-24 05:38:05,083 - pos_N_scan_slow: 16 +2026-06-24 05:38:05,083 - pos_N_scan_fast: 16 +2026-06-24 05:38:05,083 - pos_scan_step_size: 0.41889888048171997 +2026-06-24 05:38:05,083 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:38:05,083 - probe_pmode_max: 6 +2026-06-24 05:38:05,083 - probe_pmode_init_pows: [0.02] +2026-06-24 05:38:05,083 - obj_omode_max: 1 +2026-06-24 05:38:05,083 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:38:05,083 - obj_Nlayer: 1 +2026-06-24 05:38:05,083 - obj_slice_thickness: 20.0 +2026-06-24 05:38:05,083 - simu_Npix: None +2026-06-24 05:38:05,083 - simu_match_mode: None +2026-06-24 05:38:05,083 - meas_permute: None +2026-06-24 05:38:05,083 - meas_reshape: [256, 128, 128] +2026-06-24 05:38:05,083 - meas_flipT: [0, 0, 0] +2026-06-24 05:38:05,083 - meas_crop: None +2026-06-24 05:38:05,083 - meas_pad: None +2026-06-24 05:38:05,083 - meas_resample: None +2026-06-24 05:38:05,083 - meas_add_source_size: None +2026-06-24 05:38:05,083 - meas_add_detector_blur: None +2026-06-24 05:38:05,083 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:38:05,083 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:38:05,083 - meas_add_poisson_noise: None +2026-06-24 05:38:05,083 - meas_export: None +2026-06-24 05:38:05,083 - probe_permute: None +2026-06-24 05:38:05,083 - probe_z_shift: None +2026-06-24 05:38:05,084 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:38:05,084 - pos_scan_flipT: None +2026-06-24 05:38:05,084 - pos_scan_affine: None +2026-06-24 05:38:05,084 - pos_scan_rand_std: 0.15 +2026-06-24 05:38:05,084 - obj_z_crop: None +2026-06-24 05:38:05,084 - obj_z_pad: None +2026-06-24 05:38:05,084 - obj_z_resample: None +2026-06-24 05:38:05,084 - meas_source: file +2026-06-24 05:38:05,084 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000016_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:38:05,084 - probe_source: simu +2026-06-24 05:38:05,084 - probe_params: None +2026-06-24 05:38:05,084 - pos_source: simu +2026-06-24 05:38:05,084 - pos_params: None +2026-06-24 05:38:05,084 - obj_source: simu +2026-06-24 05:38:05,084 - obj_params: None +2026-06-24 05:38:05,084 - tilt_source: simu +2026-06-24 05:38:05,084 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:38:05,084 - +2026-06-24 05:38:05,084 - ### Initializing cache ### +2026-06-24 05:38:05,084 - use_cached_obj = False +2026-06-24 05:38:05,084 - use_cached_probe = False +2026-06-24 05:38:05,084 - use_cached_pos = False +2026-06-24 05:38:05,084 - +2026-06-24 05:38:05,084 - ### Initializing measurements ### +2026-06-24 05:38:05,084 - Loading measurements from source = 'file' +2026-06-24 05:38:05,084 - Detected measurement file type = '.h5' +2026-06-24 05:38:05,160 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:38:05,160 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:38:05,162 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0024) +2026-06-24 05:38:05,162 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:38:05,162 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:38:05,164 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:05,164 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:38:05,164 - Normalizing by max of the 2D mean pattern intensity: 0.0017218026 +2026-06-24 05:38:05,165 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:38:05,166 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0354, 1.4042) +2026-06-24 05:38:05,167 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:05,168 - Pattern total int. statistics (min, mean, max) = (575.9019, 580.2035, 584.2603), with min/max = 98.6% +2026-06-24 05:38:05,169 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0354, 1.4042) +2026-06-24 05:38:05,169 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:38:05,169 - +2026-06-24 05:38:05,169 - ### Setting up calibration ### +2026-06-24 05:38:05,169 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:38:05,169 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:38:05,169 - Radius of fitted bright field disk (RBF) = 13.54 px with meas_Npix = 128 +2026-06-24 05:38:05,169 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2116 +2026-06-24 05:38:05,169 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:38:05,169 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:38:05,389 - Initial guess: center=(63.62, 63.63), radius=13.54, Gaussian blur std=0.50 +2026-06-24 05:38:05,399 - Final fit: center=(63.62, 63.63), radius=13.54, Gaussian blur std=0.57 +2026-06-24 05:38:05,399 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.68 px with Npix = 128 +2026-06-24 05:38:05,399 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:38:05,399 - +2026-06-24 05:38:05,399 - ### Setting init_variables dict ### +2026-06-24 05:38:05,399 - Derived values given input init_params: +2026-06-24 05:38:05,399 - kv = 300.0 kV +2026-06-24 05:38:05,399 - wavelength = 0.0197 Ang +2026-06-24 05:38:05,399 - conv_angle = 10.52404499053955 mrad +2026-06-24 05:38:05,399 - Npix = 128 px +2026-06-24 05:38:05,399 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:05,399 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:05,400 - da = 0.7690 mrad +2026-06-24 05:38:05,400 - angleMax = 49.2187 mrad +2026-06-24 05:38:05,400 - RBF = 13.6846 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:38:05,400 - n_alpha = 4.6768 (# conv_angle) +2026-06-24 05:38:05,400 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:05,400 - Rayleigh-limited resolution = 1.1411 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:05,400 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:05,400 - +2026-06-24 05:38:05,400 - ### Initializing probe ### +2026-06-24 05:38:05,400 - Loading probe from source = 'simu' +2026-06-24 05:38:05,400 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:38:05,400 - Start simulating STEM probe +2026-06-24 05:38:05,400 - kv = 300.0 kV +2026-06-24 05:38:05,400 - wavelength = 0.0197 Ang +2026-06-24 05:38:05,400 - conv_angle = 10.52404499053955 mrad +2026-06-24 05:38:05,400 - Npix = 128 px +2026-06-24 05:38:05,400 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:05,400 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:05,400 - alpha_max = 49.2187 mrad +2026-06-24 05:38:05,400 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:05,400 - Rayleigh-limited resolution = 1.1411 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:05,400 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:05,400 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:38:05,400 - ------------------------------------------------------------------------------------ +2026-06-24 05:38:05,401 - C1,0 C1 -644.5000 - Defocus (C10 = -df) +2026-06-24 05:38:05,401 - C1,2 A1 -38.8440 109.38 2-fold astigmatism +2026-06-24 05:38:05,401 - C2,1 3*B2 -35.9420 346.36 Axial coma +2026-06-24 05:38:05,401 - C2,3 A2 643.4890 270.92 3-fold astigmatism +2026-06-24 05:38:05,401 - C3,0 C3 1462981.3750 - Spherical aberration +2026-06-24 05:38:05,401 - C3,2 4*S3 4877.9560 147.22 Axial star aberration +2026-06-24 05:38:05,401 - C3,4 A3 393.0310 258.07 4-fold astigmatism +2026-06-24 05:38:05,401 - C4,1 4*B4 -405787.2810 352.50 Axial coma(4th) +2026-06-24 05:38:05,401 - C4,3 4*D4 -96929.4610 47.07 3-lobe aberration +2026-06-24 05:38:05,401 - C4,5 A4 479755.1880 124.59 5-fold astigmatism +2026-06-24 05:38:05,401 - C5,0 C5 332991232.0000 - Spherical aberration (5th) +2026-06-24 05:38:05,401 - C5,2 6*S5 -666431.1250 256.26 Axial star aberration(5th) +2026-06-24 05:38:05,401 - C5,4 6*R5 6416499.5000 101.01 4-lobe aberration +2026-06-24 05:38:05,401 - C5,6 A5 16632105.0000 302.97 6-fold astigmatism +2026-06-24 05:38:05,404 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:38:05,404 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:38:05,404 - Creating 5 new probe modes from the major mode +2026-06-24 05:38:05,404 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:38:05,508 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:38:05,508 - Orthogonalizing 6 pmodes +2026-06-24 05:38:05,511 - Sorting 6 pmodes by their intensities +2026-06-24 05:38:05,511 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:38:05,512 - sum(|probe_data|**2) = 580.20, while meas_total_ints (min, mean, max) = (575.9019, 580.2035, 584.2603) +2026-06-24 05:38:05,512 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:38:05,512 - +2026-06-24 05:38:05,512 - ### Initializing probe positions ### +2026-06-24 05:38:05,512 - Loading probe positions from source = 'simu' +2026-06-24 05:38:05,512 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:38:05,512 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4189, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:38:05,512 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:38:05,514 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:38:05,514 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 05:38:05,515 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 05:38:05,515 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:38:05,515 - +2026-06-24 05:38:05,515 - ### Initializing object ### +2026-06-24 05:38:05,515 - Loading object from source = 'simu' +2026-06-24 05:38:05,515 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:38:05,516 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:38:05,516 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 193, 193) +2026-06-24 05:38:05,516 - object extent (Z, Y, X) (Ang) = [20. 38.6 38.6] +2026-06-24 05:38:05,517 - +2026-06-24 05:38:05,517 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:38:05,517 - omode_occu (omode) = float32, (1,) +2026-06-24 05:38:05,517 - +2026-06-24 05:38:05,517 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:38:05,517 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 05:38:05,517 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:38:05,517 - +2026-06-24 05:38:05,517 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:38:05,517 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:38:05,517 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:38:05,518 - +2026-06-24 05:38:05,518 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:38:05,518 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:38:05,518 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:38:05,518 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:38:05,518 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:38:05,518 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (193, 193). +2026-06-24 05:38:05,518 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:38:05,518 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:38:05,518 - +2026-06-24 05:38:05,518 - ### Collecting reconstruction provenance ### +2026-06-24 05:38:05,518 - Reconstruction provenance is collected and initialized. +2026-06-24 05:38:05,518 - +2026-06-24 05:38:05,518 - ### Initializing loss function ### +2026-06-24 05:38:05,518 - Active loss types: +2026-06-24 05:38:05,518 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:38:05,518 - +2026-06-24 05:38:05,518 - ### Initializing constraint function ### +2026-06-24 05:38:05,518 - Active constraint types: +2026-06-24 05:38:05,518 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:05,518 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:05,519 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:38:05,519 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:38:05,519 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:38:05,519 - +2026-06-24 05:38:05,519 - ### Done initializing PtyRADSolver ### +2026-06-24 05:38:05,519 - +2026-06-24 05:38:05,646 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:38:05,646 - +2026-06-24 05:38:05,646 - ### Initializing PtychoModel model ### +2026-06-24 05:38:05,717 - ### PtychoModel optimizable variables ### +2026-06-24 05:38:05,717 - obja : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:05,717 - objp : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:05,718 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:05,718 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:05,718 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:38:05,718 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:05,718 - +2026-06-24 05:38:05,718 - ### Optimizable variables statitsics ### +2026-06-24 05:38:05,718 - Total measurement values : 4,194,304 +2026-06-24 05:38:05,718 - Total optimizing variables: 271,618 +2026-06-24 05:38:05,718 - Overdetermined ratio : 15.44 +2026-06-24 05:38:05,718 - +2026-06-24 05:38:05,718 - ### Model behavior ### +2026-06-24 05:38:05,718 - Tilt propagator : False +2026-06-24 05:38:05,718 - Change slice thickness : False +2026-06-24 05:38:05,718 - Detector blur : False +2026-06-24 05:38:05,718 - Preload data : True +2026-06-24 05:38:05,718 - On-the-fly meas padding : False +2026-06-24 05:38:05,718 - On-the-fly meas resample : False +2026-06-24 05:38:05,718 - On-the-fly simu match mode: None +2026-06-24 05:38:05,718 - +2026-06-24 05:38:05,760 - ### Done initializing PtychoModel model ### +2026-06-24 05:38:05,760 - +2026-06-24 05:38:05,761 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:38:05,761 - +2026-06-24 05:38:05,761 - ### Generating indices, batches, and output_path ### +2026-06-24 05:38:05,762 - d90 = 59.000 px or 11.800 Ang +2026-06-24 05:38:05,762 - Selecting indices with the 'full' mode +2026-06-24 05:38:06,220 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:38:06,296 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:38:06,297 - Original recon_dir_affixes = ['default'] +2026-06-24 05:38:06,297 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:38:06,303 - Path corrected for compatibility: +2026-06-24 05:38:06,303 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.88e+03_phi32_147_C34_393_phi34_258_C41_-4.06e+05_phi41_352_C43_-9.69e+04_phi43_47.1_C45_4.8e+05_phi45_125_C50_3.33e+08_C52_-6.66e+05_phi52_256_C54_6.42e+06_phi54_101_C56_1.66e+07_phi56_303 +2026-06-24 05:38:06,303 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303 +2026-06-24 05:38:06,304 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303' is generated! +2026-06-24 05:38:06,455 - +2026-06-24 05:38:06,456 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303/20260624_053806_ptyrad_log.txt ### +2026-06-24 05:38:06,456 - +2026-06-24 05:38:06,457 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:38:06,457 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:38:06,457 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:38:07,655 - Iter: 1, Total Loss: 0.7657, loss_single: 0.7657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:38:07,693 - Iter: 2, Total Loss: 0.7309, loss_single: 0.7309, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:07,728 - Iter: 3, Total Loss: 0.7068, loss_single: 0.7068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,764 - Iter: 4, Total Loss: 0.6859, loss_single: 0.6859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,799 - Iter: 5, Total Loss: 0.6643, loss_single: 0.6643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,835 - Iter: 6, Total Loss: 0.6432, loss_single: 0.6432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,870 - Iter: 7, Total Loss: 0.6194, loss_single: 0.6194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,906 - Iter: 8, Total Loss: 0.5964, loss_single: 0.5964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,942 - Iter: 9, Total Loss: 0.5768, loss_single: 0.5768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:07,978 - Iter: 10, Total Loss: 0.5580, loss_single: 0.5580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,014 - Iter: 11, Total Loss: 0.5429, loss_single: 0.5429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,050 - Iter: 12, Total Loss: 0.5288, loss_single: 0.5288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,086 - Iter: 13, Total Loss: 0.5124, loss_single: 0.5124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,121 - Iter: 14, Total Loss: 0.4992, loss_single: 0.4992, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,156 - Iter: 15, Total Loss: 0.4864, loss_single: 0.4864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,192 - Iter: 16, Total Loss: 0.4715, loss_single: 0.4715, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,227 - Iter: 17, Total Loss: 0.4558, loss_single: 0.4558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,263 - Iter: 18, Total Loss: 0.4396, loss_single: 0.4396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,299 - Iter: 19, Total Loss: 0.4248, loss_single: 0.4248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,334 - Iter: 20, Total Loss: 0.4129, loss_single: 0.4129, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,370 - Iter: 21, Total Loss: 0.4028, loss_single: 0.4028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,406 - Iter: 22, Total Loss: 0.3942, loss_single: 0.3942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,442 - Iter: 23, Total Loss: 0.3871, loss_single: 0.3871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,478 - Iter: 24, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,513 - Iter: 25, Total Loss: 0.3763, loss_single: 0.3763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,548 - Iter: 26, Total Loss: 0.3726, loss_single: 0.3726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,584 - Iter: 27, Total Loss: 0.3701, loss_single: 0.3701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,619 - Iter: 28, Total Loss: 0.3679, loss_single: 0.3679, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,655 - Iter: 29, Total Loss: 0.3658, loss_single: 0.3658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,691 - Iter: 30, Total Loss: 0.3639, loss_single: 0.3639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:08,730 - Iter: 31, Total Loss: 0.3626, loss_single: 0.3626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:38:08,765 - Iter: 32, Total Loss: 0.3615, loss_single: 0.3615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,801 - Iter: 33, Total Loss: 0.3604, loss_single: 0.3604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,836 - Iter: 34, Total Loss: 0.3593, loss_single: 0.3593, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:08,871 - Iter: 35, Total Loss: 0.3584, loss_single: 0.3584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,133 - Iter: 42, Total Loss: 0.3550, loss_single: 0.3550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,168 - Iter: 43, Total Loss: 0.3547, loss_single: 0.3547, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,204 - Iter: 44, Total Loss: 0.3544, loss_single: 0.3544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,240 - Iter: 45, Total Loss: 0.3542, loss_single: 0.3542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,275 - Iter: 46, Total Loss: 0.3540, loss_single: 0.3540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:09,310 - 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016/c30_small__simulation_data1__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-644_C12_-38.8_phi12_109_C21_-35.9_phi21_346_C23_643_phi23_271_C30_1.46e+06_C32_4.66e+07_phi56_303/simulation_data1__sample_000016.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 10.52404499053955 + probe_aberrations: + C10: -644.499755859375 + C12: -38.8441276550293 + C21: -35.941925048828125 + C23: 643.4893798828125 + C30: 1462981.375 + C32: 4877.9560546875 + C34: 393.0309143066406 + C41: -405787.28125 + C43: -96929.4609375 + C45: 479755.1875 + C50: 332991232.0 + C52: -666431.125 + C54: 6416499.5 + C56: 16632105.0 + phi12: 109.3821122744934 + phi21: 346.3588108490766 + phi23: 270.92390671189463 + phi32: 147.2187716346686 + phi34: 258.0738620149994 + phi41: 352.4983586109743 + phi43: 47.072581174744435 + phi45: 124.5918712164121 + phi52: 256.2613210545748 + phi54: 101.01286291842332 + phi56: 302.96935112765357 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.41889888048171997 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000016_measurement.h5 + key: measurement + random_seed: 20261860 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000016 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/20260624_053821_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:38:19,642 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:38:19,642 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:38:19,642 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:38:19,642 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:38:19,642 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:38:19,642 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:38:19,642 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:38:19,642 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:38:19,642 - +2026-06-24 05:38:19,749 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:38:19,749 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:38:19,750 - Accelerator.num_process = 1 +2026-06-24 05:38:19,750 - Accelerator.mixed_precision = no +2026-06-24 05:38:19,760 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:38:19,760 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:38:19,760 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:38:19,760 - +2026-06-24 05:38:19,760 - ### System information ### +2026-06-24 05:38:19,760 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:38:19,760 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:38:19,760 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:38:19,760 - Machine: x86_64 +2026-06-24 05:38:19,760 - Processor: x86_64 +2026-06-24 05:38:19,760 - Available CPU cores: 8 +2026-06-24 05:38:19,760 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:38:19,761 - +2026-06-24 05:38:19,761 - ### GPU information ### +2026-06-24 05:38:19,761 - CUDA Available: True +2026-06-24 05:38:19,761 - CUDA Version: 13.0 +2026-06-24 05:38:19,761 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:38:19,761 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:38:19,761 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:38:19,761 - In addition, Triton does not directly support Windows. +2026-06-24 05:38:19,761 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:38:19,776 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:38:19,776 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:38:19,776 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:38:19,776 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:38:19,776 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:38:19,776 - +2026-06-24 05:38:19,776 - ### Python information ### +2026-06-24 05:38:19,777 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:38:19,777 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:38:19,777 - +2026-06-24 05:38:19,777 - ### Packages information ### +2026-06-24 05:38:19,778 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:38:19,779 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:38:19,779 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:38:19,780 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:38:19,780 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:38:19,780 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:38:19,780 - +2026-06-24 05:38:19,780 - ### Loading params file ### +2026-06-24 05:38:19,780 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000017.yaml +2026-06-24 05:38:19,787 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:38:19,788 - Success! Params file validated and defaults applied. +2026-06-24 05:38:19,788 - +2026-06-24 05:38:19,788 - ### Setting GPU Device ### +2026-06-24 05:38:19,788 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:38:19,788 - +2026-06-24 05:38:19,788 - Random seed: 20261861 provided by params file +2026-06-24 05:38:19,789 - ### Initializing Initializer ### +2026-06-24 05:38:19,789 - init_params are displayed below: +2026-06-24 05:38:19,789 - random_seed: 20261861 +2026-06-24 05:38:19,789 - probe_illum_type: electron +2026-06-24 05:38:19,789 - probe_kv: 160.0 +2026-06-24 05:38:19,789 - probe_conv_angle: 14.21854019165039 +2026-06-24 05:38:19,789 - probe_aberrations: {'C10': -94.929, 'C12': 7.681, 'phi12': 323.955, 'C21': -898.436, 'phi21': 64.11, 'C23': 158.82, 'phi23': 151.006, 'C30': 2785271.25, 'C32': -9873.005, 'phi32': 147.458, 'C34': -6412.708, 'phi34': 275.551, 'C41': 487812.562, 'phi41': 263.367, 'C43': -234957.234, 'phi43': 126.02, 'C45': 263359.562, 'phi45': 277.858, 'C50': -375520160.0, 'C52': -2298809.5, 'phi52': 126.856, 'C54': 12012333.0, 'phi54': 233.739, 'C56': -1895968.0, 'phi56': 259.108} +2026-06-24 05:38:19,789 - beam_kev: None +2026-06-24 05:38:19,789 - probe_dRn: None +2026-06-24 05:38:19,789 - probe_Rn: None +2026-06-24 05:38:19,789 - probe_D_H: None +2026-06-24 05:38:19,789 - probe_D_FZP: None +2026-06-24 05:38:19,789 - probe_Ls: None +2026-06-24 05:38:19,789 - meas_Npix: 128 +2026-06-24 05:38:19,789 - pos_N_scans: 256 +2026-06-24 05:38:19,789 - pos_N_scan_slow: 16 +2026-06-24 05:38:19,789 - pos_N_scan_fast: 16 +2026-06-24 05:38:19,789 - pos_scan_step_size: 0.3476966619491577 +2026-06-24 05:38:19,789 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:38:19,789 - probe_pmode_max: 6 +2026-06-24 05:38:19,789 - probe_pmode_init_pows: [0.02] +2026-06-24 05:38:19,789 - obj_omode_max: 1 +2026-06-24 05:38:19,789 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:38:19,789 - obj_Nlayer: 1 +2026-06-24 05:38:19,789 - obj_slice_thickness: 20.0 +2026-06-24 05:38:19,789 - simu_Npix: None +2026-06-24 05:38:19,789 - simu_match_mode: None +2026-06-24 05:38:19,789 - meas_permute: None +2026-06-24 05:38:19,789 - meas_reshape: [256, 128, 128] +2026-06-24 05:38:19,790 - meas_flipT: [0, 0, 0] +2026-06-24 05:38:19,790 - meas_crop: None +2026-06-24 05:38:19,790 - meas_pad: None +2026-06-24 05:38:19,790 - meas_resample: None +2026-06-24 05:38:19,790 - meas_add_source_size: None +2026-06-24 05:38:19,790 - meas_add_detector_blur: None +2026-06-24 05:38:19,790 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:38:19,790 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:38:19,790 - meas_add_poisson_noise: None +2026-06-24 05:38:19,790 - meas_export: None +2026-06-24 05:38:19,790 - probe_permute: None +2026-06-24 05:38:19,790 - probe_z_shift: None +2026-06-24 05:38:19,790 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:38:19,790 - pos_scan_flipT: None +2026-06-24 05:38:19,790 - pos_scan_affine: None +2026-06-24 05:38:19,790 - pos_scan_rand_std: 0.15 +2026-06-24 05:38:19,790 - obj_z_crop: None +2026-06-24 05:38:19,790 - obj_z_pad: None +2026-06-24 05:38:19,790 - obj_z_resample: None +2026-06-24 05:38:19,790 - meas_source: file +2026-06-24 05:38:19,790 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000017_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:38:19,790 - probe_source: simu +2026-06-24 05:38:19,790 - probe_params: None +2026-06-24 05:38:19,790 - pos_source: simu +2026-06-24 05:38:19,790 - pos_params: None +2026-06-24 05:38:19,790 - obj_source: simu +2026-06-24 05:38:19,790 - obj_params: None +2026-06-24 05:38:19,790 - tilt_source: simu +2026-06-24 05:38:19,790 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:38:19,790 - +2026-06-24 05:38:19,790 - ### Initializing cache ### +2026-06-24 05:38:19,790 - use_cached_obj = False +2026-06-24 05:38:19,790 - use_cached_probe = False +2026-06-24 05:38:19,790 - use_cached_pos = False +2026-06-24 05:38:19,790 - +2026-06-24 05:38:19,790 - ### Initializing measurements ### +2026-06-24 05:38:19,790 - Loading measurements from source = 'file' +2026-06-24 05:38:19,790 - Detected measurement file type = '.h5' +2026-06-24 05:38:19,866 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:38:19,866 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:38:19,868 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0033) +2026-06-24 05:38:19,868 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:38:19,868 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:38:19,870 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:19,870 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:38:19,870 - Normalizing by max of the 2D mean pattern intensity: 0.0018959057 +2026-06-24 05:38:19,871 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:38:19,872 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0321, 1.7515) +2026-06-24 05:38:19,873 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:19,874 - Pattern total int. statistics (min, mean, max) = (516.9763, 526.1512, 535.0197), with min/max = 96.6% +2026-06-24 05:38:19,875 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0321, 1.7515) +2026-06-24 05:38:19,875 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:38:19,875 - +2026-06-24 05:38:19,875 - ### Setting up calibration ### +2026-06-24 05:38:19,875 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:38:19,875 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:38:19,875 - Radius of fitted bright field disk (RBF) = 12.64 px with meas_Npix = 128 +2026-06-24 05:38:19,876 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1975 +2026-06-24 05:38:19,876 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:38:19,876 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:38:20,099 - Initial guess: center=(63.62, 63.63), radius=12.64, Gaussian blur std=0.50 +2026-06-24 05:38:20,111 - Final fit: center=(63.62, 63.63), radius=12.64, Gaussian blur std=0.65 +2026-06-24 05:38:20,112 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.77 px with Npix = 128 +2026-06-24 05:38:20,112 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:38:20,112 - +2026-06-24 05:38:20,112 - ### Setting init_variables dict ### +2026-06-24 05:38:20,112 - Derived values given input init_params: +2026-06-24 05:38:20,112 - kv = 160.0 kV +2026-06-24 05:38:20,112 - wavelength = 0.0285 Ang +2026-06-24 05:38:20,112 - conv_angle = 14.21854019165039 mrad +2026-06-24 05:38:20,112 - Npix = 128 px +2026-06-24 05:38:20,112 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:20,112 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:20,112 - da = 1.1137 mrad +2026-06-24 05:38:20,112 - angleMax = 71.2751 mrad +2026-06-24 05:38:20,112 - RBF = 12.7672 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:38:20,112 - n_alpha = 5.0128 (# conv_angle) +2026-06-24 05:38:20,112 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:20,112 - Rayleigh-limited resolution = 1.2231 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:20,112 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:20,112 - +2026-06-24 05:38:20,112 - ### Initializing probe ### +2026-06-24 05:38:20,112 - Loading probe from source = 'simu' +2026-06-24 05:38:20,112 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:38:20,112 - Start simulating STEM probe +2026-06-24 05:38:20,112 - kv = 160.0 kV +2026-06-24 05:38:20,113 - wavelength = 0.0285 Ang +2026-06-24 05:38:20,113 - conv_angle = 14.21854019165039 mrad +2026-06-24 05:38:20,113 - Npix = 128 px +2026-06-24 05:38:20,113 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:20,113 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:20,113 - alpha_max = 71.2751 mrad +2026-06-24 05:38:20,113 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:20,113 - Rayleigh-limited resolution = 1.2231 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:20,113 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:20,113 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:38:20,113 - ------------------------------------------------------------------------------------- +2026-06-24 05:38:20,113 - C1,0 C1 -94.9290 - Defocus (C10 = -df) +2026-06-24 05:38:20,113 - C1,2 A1 7.6810 323.95 2-fold astigmatism +2026-06-24 05:38:20,113 - C2,1 3*B2 -898.4360 64.11 Axial coma +2026-06-24 05:38:20,113 - C2,3 A2 158.8200 151.01 3-fold astigmatism +2026-06-24 05:38:20,113 - C3,0 C3 2785271.2500 - Spherical aberration +2026-06-24 05:38:20,113 - C3,2 4*S3 -9873.0050 147.46 Axial star aberration +2026-06-24 05:38:20,113 - C3,4 A3 -6412.7080 275.55 4-fold astigmatism +2026-06-24 05:38:20,113 - C4,1 4*B4 487812.5620 263.37 Axial coma(4th) +2026-06-24 05:38:20,113 - C4,3 4*D4 -234957.2340 126.02 3-lobe aberration +2026-06-24 05:38:20,113 - C4,5 A4 263359.5620 277.86 5-fold astigmatism +2026-06-24 05:38:20,113 - C5,0 C5 -375520160.0000 - Spherical aberration (5th) +2026-06-24 05:38:20,113 - C5,2 6*S5 -2298809.5000 126.86 Axial star aberration(5th) +2026-06-24 05:38:20,113 - C5,4 6*R5 12012333.0000 233.74 4-lobe aberration +2026-06-24 05:38:20,113 - C5,6 A5 -1895968.0000 259.11 6-fold astigmatism +2026-06-24 05:38:20,116 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:38:20,116 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:38:20,116 - Creating 5 new probe modes from the major mode +2026-06-24 05:38:20,116 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:38:20,221 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:38:20,222 - Orthogonalizing 6 pmodes +2026-06-24 05:38:20,224 - Sorting 6 pmodes by their intensities +2026-06-24 05:38:20,225 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:38:20,226 - sum(|probe_data|**2) = 526.15, while meas_total_ints (min, mean, max) = (516.9763, 526.1512, 535.0197) +2026-06-24 05:38:20,226 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:38:20,226 - +2026-06-24 05:38:20,226 - ### Initializing probe positions ### +2026-06-24 05:38:20,226 - Loading probe positions from source = 'simu' +2026-06-24 05:38:20,226 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:38:20,226 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3477, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:38:20,226 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:38:20,228 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:38:20,228 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 05:38:20,228 - crop_pos extent (Ang) = [5.2 5.4] +2026-06-24 05:38:20,228 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:38:20,228 - +2026-06-24 05:38:20,229 - ### Initializing object ### +2026-06-24 05:38:20,229 - Loading object from source = 'simu' +2026-06-24 05:38:20,229 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:38:20,230 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:38:20,230 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 186) +2026-06-24 05:38:20,230 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.2] +2026-06-24 05:38:20,230 - +2026-06-24 05:38:20,230 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:38:20,230 - omode_occu (omode) = float32, (1,) +2026-06-24 05:38:20,230 - +2026-06-24 05:38:20,230 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:38:20,230 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:38:20,231 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:38:20,231 - +2026-06-24 05:38:20,231 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:38:20,231 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:38:20,231 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:38:20,231 - +2026-06-24 05:38:20,231 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:38:20,231 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:38:20,231 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:38:20,231 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:38:20,231 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:38:20,232 - crop positions (yx_min=[16 15], yx_max=[170 170]) are well contained inside object canvas (Ny,Nx) = (186, 186). +2026-06-24 05:38:20,232 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:38:20,232 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:38:20,232 - +2026-06-24 05:38:20,232 - ### Collecting reconstruction provenance ### +2026-06-24 05:38:20,232 - Reconstruction provenance is collected and initialized. +2026-06-24 05:38:20,232 - +2026-06-24 05:38:20,232 - ### Initializing loss function ### +2026-06-24 05:38:20,232 - Active loss types: +2026-06-24 05:38:20,232 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:38:20,232 - +2026-06-24 05:38:20,232 - ### Initializing constraint function ### +2026-06-24 05:38:20,232 - Active constraint types: +2026-06-24 05:38:20,232 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:20,232 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:20,232 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:38:20,232 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:38:20,232 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:38:20,232 - +2026-06-24 05:38:20,232 - ### Done initializing PtyRADSolver ### +2026-06-24 05:38:20,232 - +2026-06-24 05:38:20,362 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:38:20,362 - +2026-06-24 05:38:20,362 - ### Initializing PtychoModel model ### +2026-06-24 05:38:20,434 - ### PtychoModel optimizable variables ### +2026-06-24 05:38:20,434 - obja : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:20,434 - objp : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:20,434 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:20,435 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:20,435 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:38:20,435 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:20,435 - +2026-06-24 05:38:20,435 - ### Optimizable variables statitsics ### +2026-06-24 05:38:20,435 - Total measurement values : 4,194,304 +2026-06-24 05:38:20,435 - Total optimizing variables: 266,312 +2026-06-24 05:38:20,435 - Overdetermined ratio : 15.75 +2026-06-24 05:38:20,435 - +2026-06-24 05:38:20,435 - ### Model behavior ### +2026-06-24 05:38:20,435 - Tilt propagator : False +2026-06-24 05:38:20,435 - Change slice thickness : False +2026-06-24 05:38:20,435 - Detector blur : False +2026-06-24 05:38:20,435 - Preload data : True +2026-06-24 05:38:20,435 - On-the-fly meas padding : False +2026-06-24 05:38:20,435 - On-the-fly meas resample : False +2026-06-24 05:38:20,435 - On-the-fly simu match mode: None +2026-06-24 05:38:20,435 - +2026-06-24 05:38:20,476 - ### Done initializing PtychoModel model ### +2026-06-24 05:38:20,477 - +2026-06-24 05:38:20,477 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:38:20,477 - +2026-06-24 05:38:20,477 - ### Generating indices, batches, and output_path ### +2026-06-24 05:38:20,478 - d90 = 55.000 px or 11.000 Ang +2026-06-24 05:38:20,478 - Selecting indices with the 'full' mode +2026-06-24 05:38:20,938 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:38:21,014 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:38:21,014 - Original recon_dir_affixes = ['default'] +2026-06-24 05:38:21,014 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:38:21,020 - Path corrected for compatibility: +2026-06-24 05:38:21,020 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.87e+03_phi32_147_C34_-6.41e+03_phi34_276_C41_4.88e+05_phi41_263_C43_-2.35e+05_phi43_126_C45_2.63e+05_phi45_278_C50_-3.76e+08_C52_-2.3e+06_phi52_127_C54_1.2e+07_phi54_234_C56_-1.9e+06_phi56_259 +2026-06-24 05:38:21,020 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259 +2026-06-24 05:38:21,022 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259' is generated! +2026-06-24 05:38:21,172 - +2026-06-24 05:38:21,173 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/20260624_053821_ptyrad_log.txt ### +2026-06-24 05:38:21,173 - +2026-06-24 05:38:21,175 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:38:21,175 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:38:21,175 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:38:22,373 - Iter: 1, Total Loss: 0.9095, loss_single: 0.9095, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 05:38:22,411 - Iter: 2, Total Loss: 0.8805, loss_single: 0.8805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:38:22,447 - Iter: 3, Total Loss: 0.8572, loss_single: 0.8572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,482 - Iter: 4, Total Loss: 0.8361, loss_single: 0.8361, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,518 - Iter: 5, Total Loss: 0.8175, loss_single: 0.8175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,554 - Iter: 6, Total Loss: 0.7999, loss_single: 0.7999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:22,589 - Iter: 7, Total Loss: 0.7809, loss_single: 0.7809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,624 - Iter: 8, Total Loss: 0.7615, loss_single: 0.7615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,659 - Iter: 9, Total Loss: 0.7419, loss_single: 0.7419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,696 - Iter: 10, Total Loss: 0.7237, loss_single: 0.7237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:22,731 - Iter: 11, Total Loss: 0.7089, loss_single: 0.7089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,766 - Iter: 12, Total Loss: 0.6945, loss_single: 0.6945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,802 - Iter: 13, Total Loss: 0.6794, loss_single: 0.6794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,837 - Iter: 14, Total Loss: 0.6647, loss_single: 0.6647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,873 - Iter: 15, Total Loss: 0.6518, loss_single: 0.6518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:22,908 - Iter: 16, Total Loss: 0.6412, loss_single: 0.6412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,943 - Iter: 17, Total Loss: 0.6284, loss_single: 0.6284, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:22,979 - Iter: 18, Total Loss: 0.6149, loss_single: 0.6149, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,014 - Iter: 19, Total Loss: 0.6030, loss_single: 0.6030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,050 - Iter: 20, Total Loss: 0.5917, loss_single: 0.5917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,085 - Iter: 21, Total Loss: 0.5826, loss_single: 0.5826, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,121 - Iter: 22, Total Loss: 0.5751, loss_single: 0.5751, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:23,156 - Iter: 23, Total Loss: 0.5672, loss_single: 0.5672, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,191 - Iter: 24, Total Loss: 0.5604, loss_single: 0.5604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,227 - Iter: 25, Total Loss: 0.5559, loss_single: 0.5559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,263 - Iter: 26, Total Loss: 0.5504, loss_single: 0.5504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,298 - Iter: 27, Total Loss: 0.5430, loss_single: 0.5430, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,334 - Iter: 28, Total Loss: 0.5375, loss_single: 0.5375, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,370 - Iter: 29, Total Loss: 0.5337, loss_single: 0.5337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:23,405 - Iter: 30, Total Loss: 0.5296, loss_single: 0.5296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,444 - Iter: 31, Total Loss: 0.5263, loss_single: 0.5263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:38:23,479 - Iter: 32, Total Loss: 0.5229, loss_single: 0.5229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,515 - Iter: 33, Total Loss: 0.5199, loss_single: 0.5199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,550 - Iter: 34, Total Loss: 0.5175, loss_single: 0.5175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,586 - Iter: 35, Total Loss: 0.5151, loss_single: 0.5151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,621 - Iter: 36, Total Loss: 0.5130, loss_single: 0.5130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,657 - Iter: 37, Total Loss: 0.5113, loss_single: 0.5113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,693 - Iter: 38, Total Loss: 0.5094, loss_single: 0.5094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:23,729 - Iter: 39, Total Loss: 0.5076, loss_single: 0.5076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,764 - Iter: 40, Total Loss: 0.5062, loss_single: 0.5062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,804 - Iter: 41, Total Loss: 0.5047, loss_single: 0.5047, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,839 - Iter: 42, Total Loss: 0.5032, loss_single: 0.5032, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,875 - Iter: 43, Total Loss: 0.5018, loss_single: 0.5018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,910 - Iter: 44, Total Loss: 0.5004, loss_single: 0.5004, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:23,946 - Iter: 45, Total Loss: 0.4995, loss_single: 0.4995, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:23,982 - Iter: 46, Total Loss: 0.4988, loss_single: 0.4988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,017 - Iter: 47, Total Loss: 0.4980, loss_single: 0.4980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,052 - Iter: 48, Total Loss: 0.4970, loss_single: 0.4970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,088 - Iter: 49, Total Loss: 0.4963, loss_single: 0.4963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,124 - Iter: 50, Total Loss: 0.4956, loss_single: 0.4956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,159 - Iter: 51, Total Loss: 0.4950, loss_single: 0.4950, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,195 - Iter: 52, Total Loss: 0.4943, loss_single: 0.4943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,230 - Iter: 53, Total Loss: 0.4935, loss_single: 0.4935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,266 - Iter: 54, Total Loss: 0.4929, loss_single: 0.4929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,301 - Iter: 55, Total Loss: 0.4924, loss_single: 0.4924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,337 - Iter: 56, Total Loss: 0.4919, loss_single: 0.4919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,372 - Iter: 57, Total Loss: 0.4914, loss_single: 0.4914, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:24,408 - Iter: 58, Total Loss: 0.4909, loss_single: 0.4909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,443 - Iter: 59, Total Loss: 0.4903, loss_single: 0.4903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,479 - Iter: 60, Total Loss: 0.4898, loss_single: 0.4898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,514 - Iter: 61, Total Loss: 0.4893, loss_single: 0.4893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,550 - Iter: 62, Total Loss: 0.4888, loss_single: 0.4888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,585 - Iter: 63, Total Loss: 0.4883, loss_single: 0.4883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:24,621 - Iter: 64, 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0.4751, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:25,866 - Iter: 99, Total Loss: 0.4747, loss_single: 0.4747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:25,930 - Iter: 100, Total Loss: 0.4744, loss_single: 0.4744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:26,039 - Saving summary figures for iter 100 +2026-06-24 05:38:29,685 - ### Finished 100 iterations, averaged iter_t = 0.039193 with std = 0.040 ### +2026-06-24 05:38:29,685 - +2026-06-24 05:38:29,685 - ### The PtyRADSolver is finished in 9.324 sec ### +2026-06-24 05:38:29,686 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..eac61547ec0e2c7532ba72e4c6033a72f16413ea Binary files /dev/null and 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/simulation_data1__sample_000017.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b2d1117fa1df6b5fffd99301e09f2be2f5a05eb2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017/c30_small__simulation_data1__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-94.9_C12_7.68_phi12_324_C21_-898_phi21_64.1_C23_159_phi23_151_C30_2.79e+06_C32_-9.9e+06_phi56_259/simulation_data1__sample_000017.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 14.21854019165039 + probe_aberrations: + C10: -94.92864990234375 + C12: 7.680829048156738 + C21: -898.4360961914062 + C23: 158.81991577148438 + C30: 2785271.25 + C32: -9873.0048828125 + C34: -6412.7080078125 + C41: 487812.5625 + C43: -234957.234375 + C45: 263359.5625 + C50: -375520160.0 + C52: -2298809.5 + C54: 12012333.0 + C56: -1895968.0 + phi12: 323.9551619940311 + phi21: 64.10952841776286 + phi23: 151.00556511430707 + phi32: 147.45833368961763 + phi34: 275.5512232707949 + phi41: 263.3669580934358 + phi43: 126.02037796056358 + phi45: 277.8577508327515 + phi52: 126.8564477564865 + phi54: 233.73918207780795 + phi56: 259.10773408928594 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3476966619491577 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000017_measurement.h5 + key: measurement + random_seed: 20261861 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000017 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000017 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_23.8/20260624_053850_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:38:49,222 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:38:49,222 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:38:49,222 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:38:49,222 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:38:49,222 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:38:49,222 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:38:49,222 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:38:49,222 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:38:49,222 - +2026-06-24 05:38:49,330 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:38:49,330 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:38:49,330 - Accelerator.num_process = 1 +2026-06-24 05:38:49,330 - Accelerator.mixed_precision = no +2026-06-24 05:38:49,341 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:38:49,341 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:38:49,341 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:38:49,341 - +2026-06-24 05:38:49,341 - ### System information ### +2026-06-24 05:38:49,341 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:38:49,341 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:38:49,341 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:38:49,341 - Machine: x86_64 +2026-06-24 05:38:49,341 - Processor: x86_64 +2026-06-24 05:38:49,341 - Available CPU cores: 8 +2026-06-24 05:38:49,341 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:38:49,341 - +2026-06-24 05:38:49,341 - ### GPU information ### +2026-06-24 05:38:49,342 - CUDA Available: True +2026-06-24 05:38:49,342 - CUDA Version: 13.0 +2026-06-24 05:38:49,342 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:38:49,342 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:38:49,342 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:38:49,342 - In addition, Triton does not directly support Windows. +2026-06-24 05:38:49,342 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:38:49,369 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:38:49,369 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:38:49,369 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:38:49,369 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:38:49,369 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:38:49,369 - +2026-06-24 05:38:49,369 - ### Python information ### +2026-06-24 05:38:49,371 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:38:49,371 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:38:49,371 - +2026-06-24 05:38:49,371 - ### Packages information ### +2026-06-24 05:38:49,372 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:38:49,373 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:38:49,373 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:38:49,374 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:38:49,374 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:38:49,375 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:38:49,375 - +2026-06-24 05:38:49,375 - ### Loading params file ### +2026-06-24 05:38:49,375 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000019.yaml +2026-06-24 05:38:49,381 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:38:49,382 - Success! Params file validated and defaults applied. +2026-06-24 05:38:49,382 - +2026-06-24 05:38:49,382 - ### Setting GPU Device ### +2026-06-24 05:38:49,382 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:38:49,382 - +2026-06-24 05:38:49,383 - Random seed: 20261863 provided by params file +2026-06-24 05:38:49,383 - ### Initializing Initializer ### +2026-06-24 05:38:49,383 - init_params are displayed below: +2026-06-24 05:38:49,383 - random_seed: 20261863 +2026-06-24 05:38:49,383 - probe_illum_type: electron +2026-06-24 05:38:49,383 - probe_kv: 100.0 +2026-06-24 05:38:49,383 - probe_conv_angle: 15.948391914367676 +2026-06-24 05:38:49,383 - probe_aberrations: {'C10': 69.766, 'C12': 0.828, 'phi12': 137.735, 'C21': 806.366, 'phi21': 72.501, 'C23': 639.872, 'phi23': 275.374, 'C30': 1318784.625, 'C32': 5131.736, 'phi32': 232.903, 'C34': 10844.549, 'phi34': 305.296, 'C41': 473380.062, 'phi41': 269.383, 'C43': 430438.594, 'phi43': 310.586, 'C45': -404707.938, 'phi45': 61.754, 'C50': -141360480.0, 'C52': -10318052.0, 'phi52': 75.735, 'C54': -9700552.0, 'phi54': 300.374, 'C56': 14917931.0, 'phi56': 85.759} +2026-06-24 05:38:49,383 - beam_kev: None +2026-06-24 05:38:49,383 - probe_dRn: None +2026-06-24 05:38:49,383 - probe_Rn: None +2026-06-24 05:38:49,383 - probe_D_H: None +2026-06-24 05:38:49,383 - probe_D_FZP: None +2026-06-24 05:38:49,383 - probe_Ls: None +2026-06-24 05:38:49,383 - meas_Npix: 128 +2026-06-24 05:38:49,383 - pos_N_scans: 256 +2026-06-24 05:38:49,383 - pos_N_scan_slow: 16 +2026-06-24 05:38:49,383 - pos_N_scan_fast: 16 +2026-06-24 05:38:49,383 - pos_scan_step_size: 0.34821954369544983 +2026-06-24 05:38:49,384 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:38:49,384 - probe_pmode_max: 6 +2026-06-24 05:38:49,384 - probe_pmode_init_pows: [0.02] +2026-06-24 05:38:49,384 - obj_omode_max: 1 +2026-06-24 05:38:49,384 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:38:49,384 - obj_Nlayer: 1 +2026-06-24 05:38:49,384 - obj_slice_thickness: 20.0 +2026-06-24 05:38:49,384 - simu_Npix: None +2026-06-24 05:38:49,384 - simu_match_mode: None +2026-06-24 05:38:49,384 - meas_permute: None +2026-06-24 05:38:49,384 - meas_reshape: [256, 128, 128] +2026-06-24 05:38:49,384 - meas_flipT: [0, 0, 0] +2026-06-24 05:38:49,384 - meas_crop: None +2026-06-24 05:38:49,384 - meas_pad: None +2026-06-24 05:38:49,384 - meas_resample: None +2026-06-24 05:38:49,384 - meas_add_source_size: None +2026-06-24 05:38:49,384 - meas_add_detector_blur: None +2026-06-24 05:38:49,384 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:38:49,384 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:38:49,384 - meas_add_poisson_noise: None +2026-06-24 05:38:49,384 - meas_export: None +2026-06-24 05:38:49,384 - probe_permute: None +2026-06-24 05:38:49,384 - probe_z_shift: None +2026-06-24 05:38:49,384 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:38:49,384 - pos_scan_flipT: None +2026-06-24 05:38:49,384 - pos_scan_affine: None +2026-06-24 05:38:49,384 - pos_scan_rand_std: 0.15 +2026-06-24 05:38:49,384 - obj_z_crop: None +2026-06-24 05:38:49,384 - obj_z_pad: None +2026-06-24 05:38:49,384 - obj_z_resample: None +2026-06-24 05:38:49,384 - meas_source: file +2026-06-24 05:38:49,384 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000019_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:38:49,384 - probe_source: simu +2026-06-24 05:38:49,384 - probe_params: None +2026-06-24 05:38:49,384 - pos_source: simu +2026-06-24 05:38:49,384 - pos_params: None +2026-06-24 05:38:49,384 - obj_source: simu +2026-06-24 05:38:49,384 - obj_params: None +2026-06-24 05:38:49,384 - tilt_source: simu +2026-06-24 05:38:49,384 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:38:49,385 - +2026-06-24 05:38:49,385 - ### Initializing cache ### +2026-06-24 05:38:49,385 - use_cached_obj = False +2026-06-24 05:38:49,385 - use_cached_probe = False +2026-06-24 05:38:49,385 - use_cached_pos = False +2026-06-24 05:38:49,385 - +2026-06-24 05:38:49,385 - ### Initializing measurements ### +2026-06-24 05:38:49,385 - Loading measurements from source = 'file' +2026-06-24 05:38:49,385 - Detected measurement file type = '.h5' +2026-06-24 05:38:49,463 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:38:49,463 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:38:49,465 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0032) +2026-06-24 05:38:49,465 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:38:49,465 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:38:49,466 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:49,466 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:38:49,467 - Normalizing by max of the 2D mean pattern intensity: 0.002664679 +2026-06-24 05:38:49,468 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:38:49,469 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0229, 1.2066) +2026-06-24 05:38:49,469 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:38:49,471 - Pattern total int. statistics (min, mean, max) = (372.8375, 375.3875, 377.9157), with min/max = 98.7% +2026-06-24 05:38:49,472 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0229, 1.2066) +2026-06-24 05:38:49,472 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:38:49,472 - +2026-06-24 05:38:49,472 - ### Setting up calibration ### +2026-06-24 05:38:49,472 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:38:49,472 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:38:49,472 - Radius of fitted bright field disk (RBF) = 10.94 px with meas_Npix = 128 +2026-06-24 05:38:49,472 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1709 +2026-06-24 05:38:49,472 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:38:49,472 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:38:49,702 - Initial guess: center=(63.62, 63.62), radius=10.94, Gaussian blur std=0.50 +2026-06-24 05:38:49,715 - Final fit: center=(63.62, 63.62), radius=10.94, Gaussian blur std=0.65 +2026-06-24 05:38:49,715 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.03 px with Npix = 128 +2026-06-24 05:38:49,715 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:38:49,715 - +2026-06-24 05:38:49,715 - ### Setting init_variables dict ### +2026-06-24 05:38:49,715 - Derived values given input init_params: +2026-06-24 05:38:49,715 - kv = 100.0 kV +2026-06-24 05:38:49,715 - wavelength = 0.0370 Ang +2026-06-24 05:38:49,715 - conv_angle = 15.948391914367676 mrad +2026-06-24 05:38:49,715 - Npix = 128 px +2026-06-24 05:38:49,715 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:49,716 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:49,716 - da = 1.4459 mrad +2026-06-24 05:38:49,716 - angleMax = 92.5359 mrad +2026-06-24 05:38:49,716 - RBF = 11.0303 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:38:49,716 - n_alpha = 5.8022 (# conv_angle) +2026-06-24 05:38:49,716 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:49,716 - Rayleigh-limited resolution = 1.4157 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:49,716 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:49,716 - +2026-06-24 05:38:49,716 - ### Initializing probe ### +2026-06-24 05:38:49,716 - Loading probe from source = 'simu' +2026-06-24 05:38:49,716 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:38:49,716 - Start simulating STEM probe +2026-06-24 05:38:49,716 - kv = 100.0 kV +2026-06-24 05:38:49,716 - wavelength = 0.0370 Ang +2026-06-24 05:38:49,716 - conv_angle = 15.948391914367676 mrad +2026-06-24 05:38:49,716 - Npix = 128 px +2026-06-24 05:38:49,716 - dk = 0.0391 Ang^-1 +2026-06-24 05:38:49,716 - kMax = 2.5000 Ang^-1 +2026-06-24 05:38:49,716 - alpha_max = 92.5359 mrad +2026-06-24 05:38:49,716 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:38:49,716 - Rayleigh-limited resolution = 1.4157 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:38:49,716 - Real space probe extent = 25.6000 Ang +2026-06-24 05:38:49,716 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:38:49,717 - ------------------------------------------------------------------------------------- +2026-06-24 05:38:49,717 - C1,0 C1 69.7660 - Defocus (C10 = -df) +2026-06-24 05:38:49,717 - C1,2 A1 0.8280 137.74 2-fold astigmatism +2026-06-24 05:38:49,717 - C2,1 3*B2 806.3660 72.50 Axial coma +2026-06-24 05:38:49,717 - C2,3 A2 639.8720 275.37 3-fold astigmatism +2026-06-24 05:38:49,717 - C3,0 C3 1318784.6250 - Spherical aberration +2026-06-24 05:38:49,717 - C3,2 4*S3 5131.7360 232.90 Axial star aberration +2026-06-24 05:38:49,717 - C3,4 A3 10844.5490 305.30 4-fold astigmatism +2026-06-24 05:38:49,717 - C4,1 4*B4 473380.0620 269.38 Axial coma(4th) +2026-06-24 05:38:49,717 - C4,3 4*D4 430438.5940 310.59 3-lobe aberration +2026-06-24 05:38:49,717 - C4,5 A4 -404707.9380 61.75 5-fold astigmatism +2026-06-24 05:38:49,717 - C5,0 C5 -141360480.0000 - Spherical aberration (5th) +2026-06-24 05:38:49,717 - C5,2 6*S5 -10318052.0000 75.73 Axial star aberration(5th) +2026-06-24 05:38:49,717 - C5,4 6*R5 -9700552.0000 300.37 4-lobe aberration +2026-06-24 05:38:49,717 - C5,6 A5 14917931.0000 85.76 6-fold astigmatism +2026-06-24 05:38:49,720 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:38:49,720 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:38:49,720 - Creating 5 new probe modes from the major mode +2026-06-24 05:38:49,720 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:38:50,007 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:38:50,008 - Orthogonalizing 6 pmodes +2026-06-24 05:38:50,011 - Sorting 6 pmodes by their intensities +2026-06-24 05:38:50,011 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:38:50,012 - sum(|probe_data|**2) = 375.39, while meas_total_ints (min, mean, max) = (372.8375, 375.3875, 377.9157) +2026-06-24 05:38:50,012 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:38:50,012 - +2026-06-24 05:38:50,012 - ### Initializing probe positions ### +2026-06-24 05:38:50,012 - Loading probe positions from source = 'simu' +2026-06-24 05:38:50,012 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:38:50,012 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3482, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:38:50,013 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:38:50,015 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:38:50,015 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 05:38:50,015 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 05:38:50,015 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:38:50,015 - +2026-06-24 05:38:50,015 - ### Initializing object ### +2026-06-24 05:38:50,015 - Loading object from source = 'simu' +2026-06-24 05:38:50,015 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:38:50,016 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:38:50,016 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 186) +2026-06-24 05:38:50,017 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.2] +2026-06-24 05:38:50,017 - +2026-06-24 05:38:50,017 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:38:50,017 - omode_occu (omode) = float32, (1,) +2026-06-24 05:38:50,017 - +2026-06-24 05:38:50,017 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:38:50,017 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 05:38:50,017 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:38:50,018 - +2026-06-24 05:38:50,018 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:38:50,018 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:38:50,018 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:38:50,018 - +2026-06-24 05:38:50,018 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:38:50,018 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:38:50,018 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:38:50,018 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:38:50,018 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:38:50,018 - crop positions (yx_min=[16 16], yx_max=[170 170]) are well contained inside object canvas (Ny,Nx) = (186, 186). +2026-06-24 05:38:50,018 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:38:50,018 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:38:50,018 - +2026-06-24 05:38:50,018 - ### Collecting reconstruction provenance ### +2026-06-24 05:38:50,018 - Reconstruction provenance is collected and initialized. +2026-06-24 05:38:50,018 - +2026-06-24 05:38:50,018 - ### Initializing loss function ### +2026-06-24 05:38:50,018 - Active loss types: +2026-06-24 05:38:50,018 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:38:50,019 - +2026-06-24 05:38:50,019 - ### Initializing constraint function ### +2026-06-24 05:38:50,019 - Active constraint types: +2026-06-24 05:38:50,019 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:50,019 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:38:50,019 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:38:50,019 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:38:50,019 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:38:50,019 - +2026-06-24 05:38:50,019 - ### Done initializing PtyRADSolver ### +2026-06-24 05:38:50,019 - +2026-06-24 05:38:50,148 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:38:50,148 - +2026-06-24 05:38:50,148 - ### Initializing PtychoModel model ### +2026-06-24 05:38:50,218 - ### PtychoModel optimizable variables ### +2026-06-24 05:38:50,219 - obja : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:50,219 - objp : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:50,219 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:50,219 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:38:50,219 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:38:50,219 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:38:50,219 - +2026-06-24 05:38:50,219 - ### Optimizable variables statitsics ### +2026-06-24 05:38:50,219 - Total measurement values : 4,194,304 +2026-06-24 05:38:50,219 - Total optimizing variables: 266,312 +2026-06-24 05:38:50,219 - Overdetermined ratio : 15.75 +2026-06-24 05:38:50,219 - +2026-06-24 05:38:50,219 - ### Model behavior ### +2026-06-24 05:38:50,219 - Tilt propagator : False +2026-06-24 05:38:50,219 - Change slice thickness : False +2026-06-24 05:38:50,219 - Detector blur : False +2026-06-24 05:38:50,219 - Preload data : True +2026-06-24 05:38:50,219 - On-the-fly meas padding : False +2026-06-24 05:38:50,220 - On-the-fly meas resample : False +2026-06-24 05:38:50,220 - On-the-fly simu match mode: None +2026-06-24 05:38:50,220 - +2026-06-24 05:38:50,261 - ### Done initializing PtychoModel model ### +2026-06-24 05:38:50,261 - +2026-06-24 05:38:50,261 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:38:50,262 - +2026-06-24 05:38:50,262 - ### Generating indices, batches, and output_path ### +2026-06-24 05:38:50,263 - d90 = 59.000 px or 11.800 Ang +2026-06-24 05:38:50,263 - Selecting indices with the 'full' mode +2026-06-24 05:38:50,723 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:38:50,797 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:38:50,797 - Original recon_dir_affixes = ['default'] +2026-06-24 05:38:50,797 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:38:50,804 - Path corrected for compatibility: +2026-06-24 05:38:50,804 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_233_C34_1.08e+04_phi34_305_C41_4.73e+05_phi41_269_C43_4.3e+05_phi43_311_C45_-4.05e+05_phi45_61.8_C50_-1.41e+08_C52_-1.03e+07_phi52_75.7_C54_-9.7e+06_phi54_300_C56_1.49e+07_phi56_85.8 +2026-06-24 05:38:50,804 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_23.8 +2026-06-24 05:38:50,804 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_23.8' is generated! +2026-06-24 05:38:50,955 - +2026-06-24 05:38:50,956 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_23.8/20260624_053850_ptyrad_log.txt ### +2026-06-24 05:38:50,956 - +2026-06-24 05:38:50,957 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:38:50,957 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:38:50,957 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:38:52,145 - Iter: 1, Total Loss: 0.8584, loss_single: 0.8584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:38:52,183 - Iter: 2, Total Loss: 0.8055, loss_single: 0.8055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:38:52,219 - Iter: 3, Total Loss: 0.7691, loss_single: 0.7691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,254 - Iter: 4, Total Loss: 0.7319, loss_single: 0.7319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,289 - Iter: 5, Total Loss: 0.6909, loss_single: 0.6909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,324 - Iter: 6, Total Loss: 0.6484, loss_single: 0.6484, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,360 - Iter: 7, Total Loss: 0.6137, loss_single: 0.6137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,395 - Iter: 8, Total Loss: 0.5856, loss_single: 0.5856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,431 - Iter: 9, Total Loss: 0.5546, loss_single: 0.5546, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,467 - Iter: 10, Total Loss: 0.5247, loss_single: 0.5247, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:38:52,503 - Iter: 11, Total Loss: 0.4991, loss_single: 0.4991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,538 - Iter: 12, Total Loss: 0.4796, loss_single: 0.4796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,573 - Iter: 13, Total Loss: 0.4607, loss_single: 0.4607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,609 - Iter: 14, Total Loss: 0.4393, loss_single: 0.4393, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,644 - Iter: 15, Total Loss: 0.4180, loss_single: 0.4180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,680 - Iter: 16, Total Loss: 0.3967, loss_single: 0.3967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,715 - Iter: 17, Total Loss: 0.3757, loss_single: 0.3757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,750 - Iter: 18, Total Loss: 0.3589, loss_single: 0.3589, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,785 - Iter: 19, Total Loss: 0.3442, loss_single: 0.3442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,821 - Iter: 20, Total Loss: 0.3307, loss_single: 0.3307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,856 - Iter: 21, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,891 - Iter: 22, Total Loss: 0.3183, loss_single: 0.3183, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,926 - Iter: 23, Total Loss: 0.3101, loss_single: 0.3101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,962 - Iter: 24, Total Loss: 0.3017, loss_single: 0.3017, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:52,998 - Iter: 25, Total Loss: 0.2950, loss_single: 0.2950, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,033 - Iter: 26, Total Loss: 0.2903, loss_single: 0.2903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,068 - Iter: 27, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,104 - Iter: 28, Total Loss: 0.2854, loss_single: 0.2854, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,139 - Iter: 29, Total Loss: 0.2843, loss_single: 0.2843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,175 - Iter: 30, Total Loss: 0.2825, loss_single: 0.2825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,211 - Iter: 31, Total Loss: 0.2808, loss_single: 0.2808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,246 - Iter: 32, Total Loss: 0.2796, loss_single: 0.2796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,281 - Iter: 33, Total Loss: 0.2789, loss_single: 0.2789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,316 - Iter: 34, Total Loss: 0.2784, loss_single: 0.2784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:53,352 - Iter: 35, Total Loss: 0.2779, loss_single: 0.2779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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0.2722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:55,623 - Iter: 99, Total Loss: 0.2722, loss_single: 0.2722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:55,658 - Iter: 100, Total Loss: 0.2721, loss_single: 0.2721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:38:55,770 - Saving summary figures for iter 100 +2026-06-24 05:38:59,457 - ### Finished 100 iterations, averaged iter_t = 0.039032 with std = 0.040 ### +2026-06-24 05:38:59,458 - +2026-06-24 05:38:59,458 - ### The PtyRADSolver is finished in 9.310 sec ### +2026-06-24 05:38:59,458 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019/c30_small__simulation_data1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_69.8_C12_0.828_phi12_138_C21_806_phi21_72.5_C23_640_phi23_275_C30_1.32e+06_C32_5.13e+03_phi32_23.8/simulation_data1__sample_000019.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 15.948391914367676 + probe_aberrations: + C10: 69.76608276367188 + C12: 0.8279402852058411 + C21: 806.3663330078125 + C23: 639.87158203125 + C30: 1318784.625 + C32: 5131.73583984375 + C34: 10844.548828125 + C41: 473380.0625 + C43: 430438.59375 + C45: -404707.9375 + C50: -141360480.0 + C52: -10318052.0 + C54: -9700552.0 + C56: 14917931.0 + phi12: 137.73469880226904 + phi21: 72.50139253017483 + phi23: 275.37363835237454 + phi32: 232.90322156491175 + phi34: 305.2957135589599 + phi41: 269.38260622378954 + phi43: 310.5856677503781 + phi45: 61.75380983340379 + phi52: 75.73473578136716 + phi54: 300.37420709212887 + phi56: 85.75865310538617 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.34821954369544983 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000019_measurement.h5 + key: measurement + random_seed: 20261863 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000019 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/20260624_053920_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:39:18,813 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:39:18,814 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:39:18,814 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:39:18,814 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:39:18,814 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:39:18,814 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:39:18,814 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:39:18,814 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:39:18,814 - +2026-06-24 05:39:18,920 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:39:18,920 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:39:18,920 - Accelerator.num_process = 1 +2026-06-24 05:39:18,920 - Accelerator.mixed_precision = no +2026-06-24 05:39:18,931 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:39:18,931 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:39:18,931 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:39:18,931 - +2026-06-24 05:39:18,931 - ### System information ### +2026-06-24 05:39:18,931 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:39:18,931 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:39:18,932 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:39:18,932 - Machine: x86_64 +2026-06-24 05:39:18,932 - Processor: x86_64 +2026-06-24 05:39:18,932 - Available CPU cores: 8 +2026-06-24 05:39:18,932 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:39:18,932 - +2026-06-24 05:39:18,932 - ### GPU information ### +2026-06-24 05:39:18,932 - CUDA Available: True +2026-06-24 05:39:18,932 - CUDA Version: 13.0 +2026-06-24 05:39:18,932 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:39:18,932 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:39:18,932 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:39:18,932 - In addition, Triton does not directly support Windows. +2026-06-24 05:39:18,932 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:39:18,960 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:39:18,960 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:39:18,960 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:39:18,960 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:39:18,960 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:39:18,960 - +2026-06-24 05:39:18,960 - ### Python information ### +2026-06-24 05:39:18,961 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:39:18,961 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:39:18,961 - +2026-06-24 05:39:18,961 - ### Packages information ### +2026-06-24 05:39:18,962 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:39:18,963 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:39:18,963 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:39:18,964 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:39:18,965 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:39:18,965 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:39:18,965 - +2026-06-24 05:39:18,965 - ### Loading params file ### +2026-06-24 05:39:18,965 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000021.yaml +2026-06-24 05:39:18,971 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:39:18,972 - Success! Params file validated and defaults applied. +2026-06-24 05:39:18,972 - +2026-06-24 05:39:18,972 - ### Setting GPU Device ### +2026-06-24 05:39:18,972 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:39:18,972 - +2026-06-24 05:39:18,972 - Random seed: 20261865 provided by params file +2026-06-24 05:39:18,973 - ### Initializing Initializer ### +2026-06-24 05:39:18,973 - init_params are displayed below: +2026-06-24 05:39:18,973 - random_seed: 20261865 +2026-06-24 05:39:18,973 - probe_illum_type: electron +2026-06-24 05:39:18,973 - probe_kv: 60.0 +2026-06-24 05:39:18,973 - probe_conv_angle: 15.510445594787598 +2026-06-24 05:39:18,973 - probe_aberrations: {'C10': -260.407, 'C12': 20.212, 'phi12': 354.979, 'C21': 29.497, 'phi21': 351.854, 'C23': 90.835, 'phi23': 20.097, 'C30': 2862914.75, 'C32': -767.94, 'phi32': 257.824, 'C34': -3731.398, 'phi34': 335.933, 'C41': 259644.219, 'phi41': 89.361, 'C43': -495082.625, 'phi43': 127.301, 'C45': 490340.719, 'phi45': 170.41, 'C50': 474856864.0, 'C52': 2699319.25, 'phi52': 54.866, 'C54': 14927752.0, 'phi54': 124.332, 'C56': -19181134.0, 'phi56': 322.137} +2026-06-24 05:39:18,973 - beam_kev: None +2026-06-24 05:39:18,973 - probe_dRn: None +2026-06-24 05:39:18,973 - probe_Rn: None +2026-06-24 05:39:18,973 - probe_D_H: None +2026-06-24 05:39:18,973 - probe_D_FZP: None +2026-06-24 05:39:18,973 - probe_Ls: None +2026-06-24 05:39:18,973 - meas_Npix: 128 +2026-06-24 05:39:18,973 - pos_N_scans: 256 +2026-06-24 05:39:18,973 - pos_N_scan_slow: 16 +2026-06-24 05:39:18,973 - pos_N_scan_fast: 16 +2026-06-24 05:39:18,973 - pos_scan_step_size: 0.47139033675193787 +2026-06-24 05:39:18,973 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:39:18,973 - probe_pmode_max: 6 +2026-06-24 05:39:18,973 - probe_pmode_init_pows: [0.02] +2026-06-24 05:39:18,973 - obj_omode_max: 1 +2026-06-24 05:39:18,973 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:39:18,973 - obj_Nlayer: 1 +2026-06-24 05:39:18,973 - obj_slice_thickness: 20.0 +2026-06-24 05:39:18,973 - simu_Npix: None +2026-06-24 05:39:18,973 - simu_match_mode: None +2026-06-24 05:39:18,973 - meas_permute: None +2026-06-24 05:39:18,973 - meas_reshape: [256, 128, 128] +2026-06-24 05:39:18,974 - meas_flipT: [0, 0, 0] +2026-06-24 05:39:18,974 - meas_crop: None +2026-06-24 05:39:18,974 - meas_pad: None +2026-06-24 05:39:18,974 - meas_resample: None +2026-06-24 05:39:18,974 - meas_add_source_size: None +2026-06-24 05:39:18,974 - meas_add_detector_blur: None +2026-06-24 05:39:18,974 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:39:18,974 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:39:18,974 - meas_add_poisson_noise: None +2026-06-24 05:39:18,974 - meas_export: None +2026-06-24 05:39:18,974 - probe_permute: None +2026-06-24 05:39:18,974 - probe_z_shift: None +2026-06-24 05:39:18,974 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:39:18,974 - pos_scan_flipT: None +2026-06-24 05:39:18,974 - pos_scan_affine: None +2026-06-24 05:39:18,974 - pos_scan_rand_std: 0.15 +2026-06-24 05:39:18,974 - obj_z_crop: None +2026-06-24 05:39:18,974 - obj_z_pad: None +2026-06-24 05:39:18,974 - obj_z_resample: None +2026-06-24 05:39:18,974 - meas_source: file +2026-06-24 05:39:18,974 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000021_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:39:18,974 - probe_source: simu +2026-06-24 05:39:18,974 - probe_params: None +2026-06-24 05:39:18,974 - pos_source: simu +2026-06-24 05:39:18,974 - pos_params: None +2026-06-24 05:39:18,974 - obj_source: simu +2026-06-24 05:39:18,974 - obj_params: None +2026-06-24 05:39:18,974 - tilt_source: simu +2026-06-24 05:39:18,974 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:39:18,974 - +2026-06-24 05:39:18,974 - ### Initializing cache ### +2026-06-24 05:39:18,974 - use_cached_obj = False +2026-06-24 05:39:18,974 - use_cached_probe = False +2026-06-24 05:39:18,974 - use_cached_pos = False +2026-06-24 05:39:18,974 - +2026-06-24 05:39:18,974 - ### Initializing measurements ### +2026-06-24 05:39:18,974 - Loading measurements from source = 'file' +2026-06-24 05:39:18,974 - Detected measurement file type = '.h5' +2026-06-24 05:39:19,051 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:39:19,051 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:39:19,053 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0062) +2026-06-24 05:39:19,053 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:39:19,053 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:39:19,055 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:39:19,055 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:39:19,056 - Normalizing by max of the 2D mean pattern intensity: 0.0043394598 +2026-06-24 05:39:19,056 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:39:19,058 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0140, 1.4326) +2026-06-24 05:39:19,058 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:39:19,059 - Pattern total int. statistics (min, mean, max) = (226.4771, 229.7869, 232.6598), with min/max = 97.3% +2026-06-24 05:39:19,061 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0140, 1.4326) +2026-06-24 05:39:19,061 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:39:19,061 - +2026-06-24 05:39:19,061 - ### Setting up calibration ### +2026-06-24 05:39:19,061 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:39:19,061 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:39:19,061 - Radius of fitted bright field disk (RBF) = 8.10 px with meas_Npix = 128 +2026-06-24 05:39:19,061 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1265 +2026-06-24 05:39:19,061 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:39:19,061 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:39:19,283 - Initial guess: center=(63.60, 63.64), radius=8.10, Gaussian blur std=0.50 +2026-06-24 05:39:19,294 - Final fit: center=(63.60, 63.64), radius=8.10, Gaussian blur std=0.57 +2026-06-24 05:39:19,294 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.16 px with Npix = 128 +2026-06-24 05:39:19,294 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:39:19,294 - +2026-06-24 05:39:19,294 - ### Setting init_variables dict ### +2026-06-24 05:39:19,294 - Derived values given input init_params: +2026-06-24 05:39:19,294 - kv = 60.0 kV +2026-06-24 05:39:19,294 - wavelength = 0.0487 Ang +2026-06-24 05:39:19,294 - conv_angle = 15.510445594787598 mrad +2026-06-24 05:39:19,294 - Npix = 128 px +2026-06-24 05:39:19,294 - dk = 0.0391 Ang^-1 +2026-06-24 05:39:19,295 - kMax = 2.5000 Ang^-1 +2026-06-24 05:39:19,295 - da = 1.9008 mrad +2026-06-24 05:39:19,295 - angleMax = 121.6515 mrad +2026-06-24 05:39:19,295 - RBF = 8.1599 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:39:19,295 - n_alpha = 7.8432 (# conv_angle) +2026-06-24 05:39:19,295 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:39:19,295 - Rayleigh-limited resolution = 1.9137 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:39:19,295 - Real space probe extent = 25.6000 Ang +2026-06-24 05:39:19,295 - +2026-06-24 05:39:19,295 - ### Initializing probe ### +2026-06-24 05:39:19,295 - Loading probe from source = 'simu' +2026-06-24 05:39:19,295 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:39:19,295 - Start simulating STEM probe +2026-06-24 05:39:19,295 - kv = 60.0 kV +2026-06-24 05:39:19,295 - wavelength = 0.0487 Ang +2026-06-24 05:39:19,295 - conv_angle = 15.510445594787598 mrad +2026-06-24 05:39:19,295 - Npix = 128 px +2026-06-24 05:39:19,295 - dk = 0.0391 Ang^-1 +2026-06-24 05:39:19,295 - kMax = 2.5000 Ang^-1 +2026-06-24 05:39:19,295 - alpha_max = 121.6515 mrad +2026-06-24 05:39:19,295 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:39:19,295 - Rayleigh-limited resolution = 1.9137 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:39:19,295 - Real space probe extent = 25.6000 Ang +2026-06-24 05:39:19,295 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:39:19,295 - ------------------------------------------------------------------------------------ +2026-06-24 05:39:19,296 - C1,0 C1 -260.4070 - Defocus (C10 = -df) +2026-06-24 05:39:19,296 - C1,2 A1 20.2120 354.98 2-fold astigmatism +2026-06-24 05:39:19,296 - C2,1 3*B2 29.4970 351.85 Axial coma +2026-06-24 05:39:19,296 - C2,3 A2 90.8350 20.10 3-fold astigmatism +2026-06-24 05:39:19,296 - C3,0 C3 2862914.7500 - Spherical aberration +2026-06-24 05:39:19,296 - C3,2 4*S3 -767.9400 257.82 Axial star aberration +2026-06-24 05:39:19,296 - C3,4 A3 -3731.3980 335.93 4-fold astigmatism +2026-06-24 05:39:19,296 - C4,1 4*B4 259644.2190 89.36 Axial coma(4th) +2026-06-24 05:39:19,296 - C4,3 4*D4 -495082.6250 127.30 3-lobe aberration +2026-06-24 05:39:19,296 - C4,5 A4 490340.7190 170.41 5-fold astigmatism +2026-06-24 05:39:19,296 - C5,0 C5 474856864.0000 - Spherical aberration (5th) +2026-06-24 05:39:19,296 - C5,2 6*S5 2699319.2500 54.87 Axial star aberration(5th) +2026-06-24 05:39:19,296 - C5,4 6*R5 14927752.0000 124.33 4-lobe aberration +2026-06-24 05:39:19,296 - C5,6 A5 -19181134.0000 322.14 6-fold astigmatism +2026-06-24 05:39:19,299 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:39:19,299 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:39:19,299 - Creating 5 new probe modes from the major mode +2026-06-24 05:39:19,299 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:39:19,402 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:39:19,404 - Orthogonalizing 6 pmodes +2026-06-24 05:39:19,407 - Sorting 6 pmodes by their intensities +2026-06-24 05:39:19,407 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:39:19,408 - sum(|probe_data|**2) = 229.79, while meas_total_ints (min, mean, max) = (226.4771, 229.7869, 232.6598) +2026-06-24 05:39:19,408 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:39:19,408 - +2026-06-24 05:39:19,408 - ### Initializing probe positions ### +2026-06-24 05:39:19,408 - Loading probe positions from source = 'simu' +2026-06-24 05:39:19,408 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:39:19,408 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4714, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:39:19,408 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:39:19,410 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:39:19,410 - crop_pos 1st and last px coords (y,x) = ([16, 16], [52, 52]) +2026-06-24 05:39:19,411 - crop_pos extent (Ang) = [7.2 7.2] +2026-06-24 05:39:19,411 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:39:19,411 - +2026-06-24 05:39:19,411 - ### Initializing object ### +2026-06-24 05:39:19,411 - Loading object from source = 'simu' +2026-06-24 05:39:19,411 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:39:19,412 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:39:19,412 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 196, 196) +2026-06-24 05:39:19,412 - object extent (Z, Y, X) (Ang) = [20. 39.2 39.2] +2026-06-24 05:39:19,413 - +2026-06-24 05:39:19,413 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:39:19,413 - omode_occu (omode) = float32, (1,) +2026-06-24 05:39:19,413 - +2026-06-24 05:39:19,413 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:39:19,413 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 05:39:19,413 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:39:19,413 - +2026-06-24 05:39:19,413 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:39:19,413 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:39:19,414 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:39:19,414 - +2026-06-24 05:39:19,414 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:39:19,414 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:39:19,414 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:39:19,414 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:39:19,414 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:39:19,414 - crop positions (yx_min=[16 16], yx_max=[180 180]) are well contained inside object canvas (Ny,Nx) = (196, 196). +2026-06-24 05:39:19,414 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:39:19,414 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:39:19,414 - +2026-06-24 05:39:19,414 - ### Collecting reconstruction provenance ### +2026-06-24 05:39:19,414 - Reconstruction provenance is collected and initialized. +2026-06-24 05:39:19,414 - +2026-06-24 05:39:19,414 - ### Initializing loss function ### +2026-06-24 05:39:19,414 - Active loss types: +2026-06-24 05:39:19,414 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:39:19,414 - +2026-06-24 05:39:19,414 - ### Initializing constraint function ### +2026-06-24 05:39:19,414 - Active constraint types: +2026-06-24 05:39:19,414 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:39:19,414 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:39:19,415 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:39:19,415 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:39:19,415 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:39:19,415 - +2026-06-24 05:39:19,415 - ### Done initializing PtyRADSolver ### +2026-06-24 05:39:19,415 - +2026-06-24 05:39:19,541 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:39:19,541 - +2026-06-24 05:39:19,541 - ### Initializing PtychoModel model ### +2026-06-24 05:39:19,613 - ### PtychoModel optimizable variables ### +2026-06-24 05:39:19,613 - obja : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:19,613 - objp : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:19,613 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:39:19,613 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:39:19,613 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:39:19,613 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:19,613 - +2026-06-24 05:39:19,613 - ### Optimizable variables statitsics ### +2026-06-24 05:39:19,613 - Total measurement values : 4,194,304 +2026-06-24 05:39:19,613 - Total optimizing variables: 273,952 +2026-06-24 05:39:19,613 - Overdetermined ratio : 15.31 +2026-06-24 05:39:19,613 - +2026-06-24 05:39:19,613 - ### Model behavior ### +2026-06-24 05:39:19,613 - Tilt propagator : False +2026-06-24 05:39:19,613 - Change slice thickness : False +2026-06-24 05:39:19,613 - Detector blur : False +2026-06-24 05:39:19,613 - Preload data : True +2026-06-24 05:39:19,613 - On-the-fly meas padding : False +2026-06-24 05:39:19,613 - On-the-fly meas resample : False +2026-06-24 05:39:19,613 - On-the-fly simu match mode: None +2026-06-24 05:39:19,613 - +2026-06-24 05:39:19,654 - ### Done initializing PtychoModel model ### +2026-06-24 05:39:19,654 - +2026-06-24 05:39:19,654 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:39:19,654 - +2026-06-24 05:39:19,654 - ### Generating indices, batches, and output_path ### +2026-06-24 05:39:19,656 - d90 = 61.000 px or 12.200 Ang +2026-06-24 05:39:19,656 - Selecting indices with the 'full' mode +2026-06-24 05:39:20,118 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:39:20,195 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:39:20,196 - Original recon_dir_affixes = ['default'] +2026-06-24 05:39:20,196 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:39:20,202 - Path corrected for compatibility: +2026-06-24 05:39:20,202 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-768_phi32_258_C34_-3.73e+03_phi34_336_C41_2.6e+05_phi41_89.4_C43_-4.95e+05_phi43_127_C45_4.9e+05_phi45_170_C50_4.75e+08_C52_2.7e+06_phi52_54.9_C54_1.49e+07_phi54_124_C56_-1.92e+07_phi56_322 +2026-06-24 05:39:20,202 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322 +2026-06-24 05:39:20,203 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322' is generated! +2026-06-24 05:39:20,358 - +2026-06-24 05:39:20,359 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/20260624_053920_ptyrad_log.txt ### +2026-06-24 05:39:20,359 - +2026-06-24 05:39:20,361 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:39:20,361 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:39:20,361 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:39:21,555 - Iter: 1, Total Loss: 1.2541, loss_single: 1.2541, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 05:39:21,593 - Iter: 2, Total Loss: 1.2024, loss_single: 1.2024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:39:21,629 - Iter: 3, Total Loss: 1.1646, loss_single: 1.1646, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:21,665 - Iter: 4, Total Loss: 1.1290, loss_single: 1.1290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:21,702 - Iter: 5, Total Loss: 1.0903, loss_single: 1.0903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:21,738 - Iter: 6, Total Loss: 1.0516, loss_single: 1.0516, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:21,773 - Iter: 7, Total Loss: 1.0082, loss_single: 1.0082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:21,809 - Iter: 8, Total Loss: 0.9727, loss_single: 0.9727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:21,845 - Iter: 9, Total Loss: 0.9406, loss_single: 0.9406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:21,880 - Iter: 10, Total Loss: 0.9035, loss_single: 0.9035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:21,916 - Iter: 11, Total Loss: 0.8703, loss_single: 0.8703, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:21,952 - Iter: 12, Total Loss: 0.8364, loss_single: 0.8364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:21,987 - Iter: 13, Total Loss: 0.7983, loss_single: 0.7983, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,023 - Iter: 14, Total Loss: 0.7637, loss_single: 0.7637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:22,058 - Iter: 15, Total Loss: 0.7315, loss_single: 0.7315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,093 - Iter: 16, Total Loss: 0.7010, loss_single: 0.7010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,129 - Iter: 17, Total Loss: 0.6725, loss_single: 0.6725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:22,165 - Iter: 18, Total Loss: 0.6456, loss_single: 0.6456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,201 - Iter: 19, Total Loss: 0.6240, loss_single: 0.6240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,237 - Iter: 20, Total Loss: 0.6069, loss_single: 0.6069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,272 - Iter: 21, Total Loss: 0.5915, loss_single: 0.5915, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:22,309 - Iter: 22, Total Loss: 0.5775, loss_single: 0.5775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:22,345 - Iter: 23, Total Loss: 0.5663, loss_single: 0.5663, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:22,380 - Iter: 24, Total Loss: 0.5572, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/simulation_data1__sample_000021.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/simulation_data1__sample_000021.yaml new file mode 100644 index 0000000000000000000000000000000000000000..884132b0e9ac6d2b27a4fd61547d3ebd4fe567a9 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/simulation_data1__sample_000021.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 15.510445594787598 + probe_aberrations: + C10: -260.4068908691406 + C12: 20.212034225463867 + C21: 29.497425079345703 + C23: 90.8353042602539 + C30: 2862914.75 + C32: -767.9395751953125 + C34: -3731.39794921875 + C41: 259644.21875 + C43: -495082.625 + C45: 490340.71875 + C50: 474856864.0 + C52: 2699319.25 + C54: 14927752.0 + C56: -19181134.0 + phi12: 354.97881010995616 + phi21: 351.85405320618867 + phi23: 20.09695053835959 + phi32: 257.8242049404571 + phi34: 335.9333193829958 + phi41: 89.36119540197438 + phi43: 127.30097012804927 + phi45: 170.40988665950317 + phi52: 54.86628464040337 + phi54: 124.33158636752125 + phi56: 322.13702027848706 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.47139033675193787 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000021_measurement.h5 + key: measurement + random_seed: 20261865 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000021 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:813821bc5985189b6f5019b293dfb645ad3d9c6dd98d879b3ffc955317d712c4 +size 1189010 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..434d17d4b7a2cae54aea9f463f83548a014340ad --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000021/c30_small__simulation_data1__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-260_C12_20.2_phi12_355_C21_29.5_phi21_352_C23_90.8_phi23_20.1_C30_2.86e+06_C32_-.92e+07_phi56_322/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6018f50f5ef957d39b222d1b4ec595f1175cfc8df7fcc692df10c7611cbf69f9 +size 48458 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/20260624_053949_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/20260624_053949_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f5c28d52a2008bc222425fef6f4ad993990d24dc --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/20260624_053949_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:39:48,281 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:39:48,282 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:39:48,282 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:39:48,282 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:39:48,282 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:39:48,282 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:39:48,282 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:39:48,282 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:39:48,282 - +2026-06-24 05:39:48,388 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:39:48,388 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:39:48,388 - Accelerator.num_process = 1 +2026-06-24 05:39:48,388 - Accelerator.mixed_precision = no +2026-06-24 05:39:48,399 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:39:48,399 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:39:48,399 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:39:48,399 - +2026-06-24 05:39:48,399 - ### System information ### +2026-06-24 05:39:48,399 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:39:48,399 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:39:48,399 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:39:48,399 - Machine: x86_64 +2026-06-24 05:39:48,399 - Processor: x86_64 +2026-06-24 05:39:48,399 - Available CPU cores: 8 +2026-06-24 05:39:48,399 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:39:48,399 - +2026-06-24 05:39:48,399 - ### GPU information ### +2026-06-24 05:39:48,399 - CUDA Available: True +2026-06-24 05:39:48,400 - CUDA Version: 13.0 +2026-06-24 05:39:48,400 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:39:48,400 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:39:48,400 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:39:48,400 - In addition, Triton does not directly support Windows. +2026-06-24 05:39:48,400 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:39:48,415 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:39:48,415 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:39:48,415 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:39:48,415 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:39:48,415 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:39:48,415 - +2026-06-24 05:39:48,415 - ### Python information ### +2026-06-24 05:39:48,417 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:39:48,417 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:39:48,417 - +2026-06-24 05:39:48,417 - ### Packages information ### +2026-06-24 05:39:48,417 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:39:48,418 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:39:48,419 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:39:48,419 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:39:48,420 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:39:48,420 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:39:48,420 - +2026-06-24 05:39:48,420 - ### Loading params file ### +2026-06-24 05:39:48,420 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000023.yaml +2026-06-24 05:39:48,427 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:39:48,428 - Success! Params file validated and defaults applied. +2026-06-24 05:39:48,428 - +2026-06-24 05:39:48,428 - ### Setting GPU Device ### +2026-06-24 05:39:48,428 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:39:48,428 - +2026-06-24 05:39:48,428 - Random seed: 20261867 provided by params file +2026-06-24 05:39:48,428 - ### Initializing Initializer ### +2026-06-24 05:39:48,428 - init_params are displayed below: +2026-06-24 05:39:48,428 - random_seed: 20261867 +2026-06-24 05:39:48,428 - probe_illum_type: electron +2026-06-24 05:39:48,428 - probe_kv: 30.0 +2026-06-24 05:39:48,428 - probe_conv_angle: 11.332862854003906 +2026-06-24 05:39:48,428 - probe_aberrations: {'C10': 36.279, 'C12': -4.329, 'phi12': 73.814, 'C21': -998.356, 'phi21': 149.373, 'C23': 44.748, 'phi23': 98.665, 'C30': 2559865.25, 'C32': 6667.702, 'phi32': 43.509, 'C34': -5390.595, 'phi34': 29.908, 'C41': -223545.906, 'phi41': 90.257, 'C43': -55852.965, 'phi43': 272.113, 'C45': -169776.234, 'phi45': 292.596, 'C50': -388335648.0, 'C52': -415354.938, 'phi52': 296.749, 'C54': 1196810.75, 'phi54': 222.641, 'C56': -8580711.0, 'phi56': 215.993} +2026-06-24 05:39:48,428 - beam_kev: None +2026-06-24 05:39:48,428 - probe_dRn: None +2026-06-24 05:39:48,429 - probe_Rn: None +2026-06-24 05:39:48,429 - probe_D_H: None +2026-06-24 05:39:48,429 - probe_D_FZP: None +2026-06-24 05:39:48,429 - probe_Ls: None +2026-06-24 05:39:48,429 - meas_Npix: 128 +2026-06-24 05:39:48,429 - pos_N_scans: 256 +2026-06-24 05:39:48,429 - pos_N_scan_slow: 16 +2026-06-24 05:39:48,429 - pos_N_scan_fast: 16 +2026-06-24 05:39:48,429 - pos_scan_step_size: 0.3939908444881439 +2026-06-24 05:39:48,429 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:39:48,429 - probe_pmode_max: 6 +2026-06-24 05:39:48,429 - probe_pmode_init_pows: [0.02] +2026-06-24 05:39:48,429 - obj_omode_max: 1 +2026-06-24 05:39:48,429 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:39:48,429 - obj_Nlayer: 1 +2026-06-24 05:39:48,429 - obj_slice_thickness: 20.0 +2026-06-24 05:39:48,429 - simu_Npix: None +2026-06-24 05:39:48,429 - simu_match_mode: None +2026-06-24 05:39:48,429 - meas_permute: None +2026-06-24 05:39:48,429 - meas_reshape: [256, 128, 128] +2026-06-24 05:39:48,429 - meas_flipT: [0, 0, 0] +2026-06-24 05:39:48,429 - meas_crop: None +2026-06-24 05:39:48,429 - meas_pad: None +2026-06-24 05:39:48,429 - meas_resample: None +2026-06-24 05:39:48,429 - meas_add_source_size: None +2026-06-24 05:39:48,429 - meas_add_detector_blur: None +2026-06-24 05:39:48,429 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:39:48,429 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:39:48,429 - meas_add_poisson_noise: None +2026-06-24 05:39:48,429 - meas_export: None +2026-06-24 05:39:48,429 - probe_permute: None +2026-06-24 05:39:48,429 - probe_z_shift: None +2026-06-24 05:39:48,429 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:39:48,429 - pos_scan_flipT: None +2026-06-24 05:39:48,429 - pos_scan_affine: None +2026-06-24 05:39:48,429 - pos_scan_rand_std: 0.15 +2026-06-24 05:39:48,429 - obj_z_crop: None +2026-06-24 05:39:48,429 - obj_z_pad: None +2026-06-24 05:39:48,429 - obj_z_resample: None +2026-06-24 05:39:48,429 - meas_source: file +2026-06-24 05:39:48,430 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000023_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:39:48,430 - probe_source: simu +2026-06-24 05:39:48,430 - probe_params: None +2026-06-24 05:39:48,430 - pos_source: simu +2026-06-24 05:39:48,430 - pos_params: None +2026-06-24 05:39:48,430 - obj_source: simu +2026-06-24 05:39:48,430 - obj_params: None +2026-06-24 05:39:48,430 - tilt_source: simu +2026-06-24 05:39:48,430 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:39:48,430 - +2026-06-24 05:39:48,430 - ### Initializing cache ### +2026-06-24 05:39:48,430 - use_cached_obj = False +2026-06-24 05:39:48,430 - use_cached_probe = False +2026-06-24 05:39:48,430 - use_cached_pos = False +2026-06-24 05:39:48,430 - +2026-06-24 05:39:48,430 - ### Initializing measurements ### +2026-06-24 05:39:48,430 - Loading measurements from source = 'file' +2026-06-24 05:39:48,430 - Detected measurement file type = '.h5' +2026-06-24 05:39:48,507 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:39:48,507 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:39:48,509 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0178) +2026-06-24 05:39:48,509 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:39:48,509 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:39:48,510 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:39:48,510 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:39:48,510 - Normalizing by max of the 2D mean pattern intensity: 0.017214851 +2026-06-24 05:39:48,511 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:39:48,512 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0035, 1.0312) +2026-06-24 05:39:48,513 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:39:48,514 - Pattern total int. statistics (min, mean, max) = (57.5625, 57.9494, 58.3781), with min/max = 98.6% +2026-06-24 05:39:48,515 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0035, 1.0312) +2026-06-24 05:39:48,515 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:39:48,515 - +2026-06-24 05:39:48,515 - ### Setting up calibration ### +2026-06-24 05:39:48,515 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:39:48,515 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:39:48,516 - Radius of fitted bright field disk (RBF) = 4.07 px with meas_Npix = 128 +2026-06-24 05:39:48,516 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0636 +2026-06-24 05:39:48,516 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:39:48,516 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:39:48,745 - Initial guess: center=(63.61, 63.62), radius=4.07, Gaussian blur std=0.50 +2026-06-24 05:39:48,758 - Final fit: center=(63.61, 63.62), radius=4.07, Gaussian blur std=0.67 +2026-06-24 05:39:48,758 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 4.16 px with Npix = 128 +2026-06-24 05:39:48,758 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:39:48,758 - +2026-06-24 05:39:48,758 - ### Setting init_variables dict ### +2026-06-24 05:39:48,758 - Derived values given input init_params: +2026-06-24 05:39:48,758 - kv = 30.0 kV +2026-06-24 05:39:48,758 - wavelength = 0.0698 Ang +2026-06-24 05:39:48,759 - conv_angle = 11.332862854003906 mrad +2026-06-24 05:39:48,759 - Npix = 128 px +2026-06-24 05:39:48,759 - dk = 0.0391 Ang^-1 +2026-06-24 05:39:48,759 - kMax = 2.5000 Ang^-1 +2026-06-24 05:39:48,759 - da = 2.7262 mrad +2026-06-24 05:39:48,759 - angleMax = 174.4770 mrad +2026-06-24 05:39:48,759 - RBF = 4.1570 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:39:48,759 - n_alpha = 15.3957 (# conv_angle) +2026-06-24 05:39:48,759 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:39:48,759 - Rayleigh-limited resolution = 3.7565 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:39:48,759 - Real space probe extent = 25.6000 Ang +2026-06-24 05:39:48,759 - +2026-06-24 05:39:48,759 - ### Initializing probe ### +2026-06-24 05:39:48,759 - Loading probe from source = 'simu' +2026-06-24 05:39:48,759 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:39:48,759 - Start simulating STEM probe +2026-06-24 05:39:48,759 - kv = 30.0 kV +2026-06-24 05:39:48,759 - wavelength = 0.0698 Ang +2026-06-24 05:39:48,759 - conv_angle = 11.332862854003906 mrad +2026-06-24 05:39:48,759 - Npix = 128 px +2026-06-24 05:39:48,759 - dk = 0.0391 Ang^-1 +2026-06-24 05:39:48,759 - kMax = 2.5000 Ang^-1 +2026-06-24 05:39:48,759 - alpha_max = 174.4770 mrad +2026-06-24 05:39:48,759 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:39:48,759 - Rayleigh-limited resolution = 3.7565 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:39:48,759 - Real space probe extent = 25.6000 Ang +2026-06-24 05:39:48,760 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:39:48,760 - ------------------------------------------------------------------------------------- +2026-06-24 05:39:48,760 - C1,0 C1 36.2790 - Defocus (C10 = -df) +2026-06-24 05:39:48,760 - C1,2 A1 -4.3290 73.81 2-fold astigmatism +2026-06-24 05:39:48,760 - C2,1 3*B2 -998.3560 149.37 Axial coma +2026-06-24 05:39:48,760 - C2,3 A2 44.7480 98.67 3-fold astigmatism +2026-06-24 05:39:48,760 - C3,0 C3 2559865.2500 - Spherical aberration +2026-06-24 05:39:48,760 - C3,2 4*S3 6667.7020 43.51 Axial star aberration +2026-06-24 05:39:48,760 - C3,4 A3 -5390.5950 29.91 4-fold astigmatism +2026-06-24 05:39:48,760 - C4,1 4*B4 -223545.9060 90.26 Axial coma(4th) +2026-06-24 05:39:48,760 - C4,3 4*D4 -55852.9650 272.11 3-lobe aberration +2026-06-24 05:39:48,760 - C4,5 A4 -169776.2340 292.60 5-fold astigmatism +2026-06-24 05:39:48,760 - C5,0 C5 -388335648.0000 - Spherical aberration (5th) +2026-06-24 05:39:48,760 - C5,2 6*S5 -415354.9380 296.75 Axial star aberration(5th) +2026-06-24 05:39:48,760 - C5,4 6*R5 1196810.7500 222.64 4-lobe aberration +2026-06-24 05:39:48,760 - C5,6 A5 -8580711.0000 215.99 6-fold astigmatism +2026-06-24 05:39:48,763 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:39:48,763 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:39:48,763 - Creating 5 new probe modes from the major mode +2026-06-24 05:39:48,763 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:39:48,862 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:39:48,863 - Orthogonalizing 6 pmodes +2026-06-24 05:39:48,866 - Sorting 6 pmodes by their intensities +2026-06-24 05:39:48,867 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:39:48,867 - sum(|probe_data|**2) = 57.95, while meas_total_ints (min, mean, max) = (57.5625, 57.9494, 58.3781) +2026-06-24 05:39:48,868 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:39:48,868 - +2026-06-24 05:39:48,868 - ### Initializing probe positions ### +2026-06-24 05:39:48,868 - Loading probe positions from source = 'simu' +2026-06-24 05:39:48,868 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:39:48,868 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3940, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:39:48,868 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:39:48,870 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:39:48,870 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 45]) +2026-06-24 05:39:48,870 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 05:39:48,870 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:39:48,870 - +2026-06-24 05:39:48,870 - ### Initializing object ### +2026-06-24 05:39:48,870 - Loading object from source = 'simu' +2026-06-24 05:39:48,870 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:39:48,872 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:39:48,872 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-24 05:39:48,872 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-24 05:39:48,872 - +2026-06-24 05:39:48,872 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:39:48,872 - omode_occu (omode) = float32, (1,) +2026-06-24 05:39:48,872 - +2026-06-24 05:39:48,872 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:39:48,872 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0698 Ang +2026-06-24 05:39:48,873 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:39:48,873 - +2026-06-24 05:39:48,873 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:39:48,873 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:39:48,873 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:39:48,873 - +2026-06-24 05:39:48,873 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:39:48,873 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:39:48,873 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:39:48,873 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:39:48,873 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:39:48,873 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-24 05:39:48,874 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:39:48,874 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:39:48,874 - +2026-06-24 05:39:48,874 - ### Collecting reconstruction provenance ### +2026-06-24 05:39:48,874 - Reconstruction provenance is collected and initialized. +2026-06-24 05:39:48,874 - +2026-06-24 05:39:48,874 - ### Initializing loss function ### +2026-06-24 05:39:48,874 - Active loss types: +2026-06-24 05:39:48,874 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:39:48,874 - +2026-06-24 05:39:48,874 - ### Initializing constraint function ### +2026-06-24 05:39:48,874 - Active constraint types: +2026-06-24 05:39:48,874 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:39:48,874 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:39:48,874 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:39:48,874 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:39:48,874 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:39:48,874 - +2026-06-24 05:39:48,874 - ### Done initializing PtyRADSolver ### +2026-06-24 05:39:48,874 - +2026-06-24 05:39:49,003 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:39:49,003 - +2026-06-24 05:39:49,004 - ### Initializing PtychoModel model ### +2026-06-24 05:39:49,087 - ### PtychoModel optimizable variables ### +2026-06-24 05:39:49,088 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:49,088 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:49,088 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:39:49,088 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:39:49,088 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:39:49,088 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:39:49,088 - +2026-06-24 05:39:49,088 - ### Optimizable variables statitsics ### +2026-06-24 05:39:49,088 - Total measurement values : 4,194,304 +2026-06-24 05:39:49,088 - Total optimizing variables: 269,320 +2026-06-24 05:39:49,088 - Overdetermined ratio : 15.57 +2026-06-24 05:39:49,088 - +2026-06-24 05:39:49,088 - ### Model behavior ### +2026-06-24 05:39:49,088 - Tilt propagator : False +2026-06-24 05:39:49,088 - Change slice thickness : False +2026-06-24 05:39:49,088 - Detector blur : False +2026-06-24 05:39:49,088 - Preload data : True +2026-06-24 05:39:49,088 - On-the-fly meas padding : False +2026-06-24 05:39:49,088 - On-the-fly meas resample : False +2026-06-24 05:39:49,088 - On-the-fly simu match mode: None +2026-06-24 05:39:49,088 - +2026-06-24 05:39:49,130 - ### Done initializing PtychoModel model ### +2026-06-24 05:39:49,130 - +2026-06-24 05:39:49,130 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:39:49,130 - +2026-06-24 05:39:49,130 - ### Generating indices, batches, and output_path ### +2026-06-24 05:39:49,132 - d90 = 65.000 px or 13.000 Ang +2026-06-24 05:39:49,132 - Selecting indices with the 'full' mode +2026-06-24 05:39:49,586 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:39:49,660 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:39:49,661 - Original recon_dir_affixes = ['default'] +2026-06-24 05:39:49,661 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:39:49,667 - Path corrected for compatibility: +2026-06-24 05:39:49,667 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32_6.67e+03_phi32_43.5_C34_-5.39e+03_phi34_29.9_C41_-2.24e+05_phi41_90.3_C43_-5.59e+04_phi43_272_C45_-1.7e+05_phi45_293_C50_-3.88e+08_C52_-4.15e+05_phi52_297_C54_1.2e+06_phi54_223_C56_-8.58e+06_phi56_216 +2026-06-24 05:39:49,667 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216 +2026-06-24 05:39:49,668 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216' is generated! +2026-06-24 05:39:49,810 - +2026-06-24 05:39:49,810 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/20260624_053949_ptyrad_log.txt ### +2026-06-24 05:39:49,811 - +2026-06-24 05:39:49,812 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:39:49,812 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:39:49,812 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:39:50,990 - Iter: 1, Total Loss: 1.6525, loss_single: 1.6525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:39:51,027 - Iter: 2, Total Loss: 1.5125, loss_single: 1.5125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:51,062 - Iter: 3, Total Loss: 1.3917, loss_single: 1.3917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,097 - Iter: 4, Total Loss: 1.2769, loss_single: 1.2769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,133 - Iter: 5, Total Loss: 1.1989, loss_single: 1.1989, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,168 - Iter: 6, Total Loss: 1.1269, loss_single: 1.1269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,203 - Iter: 7, Total Loss: 1.0279, loss_single: 1.0279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,238 - Iter: 8, Total Loss: 0.9457, loss_single: 0.9457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,274 - Iter: 9, Total Loss: 0.8694, loss_single: 0.8694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,309 - Iter: 10, Total Loss: 0.7896, loss_single: 0.7896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,344 - Iter: 11, Total Loss: 0.7248, loss_single: 0.7248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,379 - Iter: 12, Total Loss: 0.6559, loss_single: 0.6559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,416 - Iter: 13, Total Loss: 0.5659, loss_single: 0.5659, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:39:51,451 - Iter: 14, Total Loss: 0.4941, loss_single: 0.4941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,485 - Iter: 15, Total Loss: 0.4455, loss_single: 0.4455, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:51,521 - Iter: 16, Total Loss: 0.3977, loss_single: 0.3977, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,556 - Iter: 17, Total Loss: 0.3675, loss_single: 0.3675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,591 - Iter: 18, Total Loss: 0.3454, loss_single: 0.3454, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,626 - Iter: 19, Total Loss: 0.3222, loss_single: 0.3222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:51,661 - Iter: 20, Total Loss: 0.3094, loss_single: 0.3094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,696 - Iter: 21, Total Loss: 0.3024, loss_single: 0.3024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,731 - Iter: 22, Total Loss: 0.2984, loss_single: 0.2984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,766 - Iter: 23, Total Loss: 0.2962, loss_single: 0.2962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,802 - Iter: 24, Total Loss: 0.2940, loss_single: 0.2940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,837 - Iter: 25, Total Loss: 0.2915, loss_single: 0.2915, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,872 - Iter: 26, Total Loss: 0.2896, loss_single: 0.2896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,907 - Iter: 27, Total Loss: 0.2885, loss_single: 0.2885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,942 - Iter: 28, Total Loss: 0.2877, loss_single: 0.2877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:51,977 - Iter: 29, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,012 - Iter: 30, Total Loss: 0.2865, loss_single: 0.2865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,047 - Iter: 31, Total Loss: 0.2860, loss_single: 0.2860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,082 - Iter: 32, Total Loss: 0.2856, loss_single: 0.2856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,118 - Iter: 33, Total Loss: 0.2854, loss_single: 0.2854, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,153 - Iter: 34, Total Loss: 0.2851, loss_single: 0.2851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,188 - Iter: 35, Total Loss: 0.2850, loss_single: 0.2850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,223 - Iter: 36, Total Loss: 0.2848, loss_single: 0.2848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,258 - Iter: 37, Total Loss: 0.2847, loss_single: 0.2847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,293 - Iter: 38, Total Loss: 0.2846, loss_single: 0.2846, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,328 - Iter: 39, Total Loss: 0.2845, loss_single: 0.2845, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,363 - Iter: 40, Total Loss: 0.2844, loss_single: 0.2844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,400 - Iter: 41, Total Loss: 0.2843, loss_single: 0.2843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,435 - Iter: 42, Total Loss: 0.2842, loss_single: 0.2842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,470 - Iter: 43, Total Loss: 0.2842, loss_single: 0.2842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,505 - Iter: 44, Total Loss: 0.2841, loss_single: 0.2841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,540 - Iter: 45, Total Loss: 0.2841, loss_single: 0.2841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,575 - Iter: 46, Total Loss: 0.2840, loss_single: 0.2840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,610 - Iter: 47, Total Loss: 0.2840, loss_single: 0.2840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,645 - Iter: 48, Total Loss: 0.2839, loss_single: 0.2839, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,680 - Iter: 49, Total Loss: 0.2838, loss_single: 0.2838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,716 - Iter: 50, Total Loss: 0.2838, loss_single: 0.2838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,750 - Iter: 51, Total Loss: 0.2838, loss_single: 0.2838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:39:52,786 - Iter: 52, Total Loss: 0.2837, loss_single: 0.2837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:39:52,821 - 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Saving summary figures for iter 100 +2026-06-24 05:39:58,196 - ### Finished 100 iterations, averaged iter_t = 0.038706 with std = 0.040 ### +2026-06-24 05:39:58,196 - +2026-06-24 05:39:58,196 - ### The PtyRADSolver is finished in 9.193 sec ### +2026-06-24 05:39:58,196 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..28583955bea2037d916c4475924d85f2da80c469 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/simulation_data1__sample_000023.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/simulation_data1__sample_000023.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dbb7f8af85d7311cff388fa5fe2dabe64d7891d7 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023/c30_small__simulation_data1__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_36.3_C12_-4.33_phi12_73.8_C21_-998_phi21_149_C23_44.7_phi23_98.7_C30_2.56e+06_C32.58e+06_phi56_216/simulation_data1__sample_000023.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 30.0 + probe_conv_angle: 11.332862854003906 + probe_aberrations: + C10: 36.279170989990234 + C12: -4.329168796539307 + C21: -998.3557739257812 + C23: 44.74831771850586 + C30: 2559865.25 + C32: 6667.70166015625 + C34: -5390.59521484375 + C41: -223545.90625 + C43: -55852.96484375 + C45: -169776.234375 + C50: -388335648.0 + C52: -415354.9375 + C54: 1196810.75 + C56: -8580711.0 + phi12: 73.81381337919278 + phi21: 149.37330016683575 + phi23: 98.66461656101626 + phi32: 43.508762635655614 + phi34: 29.907940130098037 + phi41: 90.25689274935152 + phi43: 272.11334317471733 + phi45: 292.5960696275884 + phi52: 296.74855143538934 + phi54: 222.6406574312925 + phi56: 215.9934217083877 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3939908444881439 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000023_measurement.h5 + key: measurement + random_seed: 20261867 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000023 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data1__sample_000023 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242/20260624_054019_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242/20260624_054019_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..71d2dc12ce929cc3a7396f32e8722991e5345f34 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242/20260624_054019_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:40:17,703 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:40:17,703 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:40:17,703 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:40:17,703 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:40:17,703 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:40:17,703 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:40:17,703 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:40:17,703 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:40:17,703 - +2026-06-24 05:40:17,826 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:40:17,826 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:40:17,826 - Accelerator.num_process = 1 +2026-06-24 05:40:17,826 - Accelerator.mixed_precision = no +2026-06-24 05:40:17,837 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:40:17,838 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:40:17,838 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:40:17,838 - +2026-06-24 05:40:17,838 - ### System information ### +2026-06-24 05:40:17,838 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:40:17,838 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:40:17,838 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:40:17,838 - Machine: x86_64 +2026-06-24 05:40:17,838 - Processor: x86_64 +2026-06-24 05:40:17,838 - Available CPU cores: 8 +2026-06-24 05:40:17,838 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:40:17,838 - +2026-06-24 05:40:17,838 - ### GPU information ### +2026-06-24 05:40:17,838 - CUDA Available: True +2026-06-24 05:40:17,838 - CUDA Version: 13.0 +2026-06-24 05:40:17,839 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:40:17,839 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:40:17,839 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:40:17,839 - In addition, Triton does not directly support Windows. +2026-06-24 05:40:17,839 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:40:17,854 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:40:17,854 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:40:17,854 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:40:17,854 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:40:17,854 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:40:17,854 - +2026-06-24 05:40:17,854 - ### Python information ### +2026-06-24 05:40:17,855 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:40:17,855 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:40:17,855 - +2026-06-24 05:40:17,855 - ### Packages information ### +2026-06-24 05:40:17,856 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:40:17,857 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:40:17,857 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:40:17,858 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:40:17,858 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:40:17,858 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:40:17,858 - +2026-06-24 05:40:17,858 - ### Loading params file ### +2026-06-24 05:40:17,858 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data1__sample_000025.yaml +2026-06-24 05:40:17,865 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:40:17,866 - Success! Params file validated and defaults applied. +2026-06-24 05:40:17,866 - +2026-06-24 05:40:17,866 - ### Setting GPU Device ### +2026-06-24 05:40:17,866 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:40:17,866 - +2026-06-24 05:40:17,866 - Random seed: 20261869 provided by params file +2026-06-24 05:40:17,867 - ### Initializing Initializer ### +2026-06-24 05:40:17,867 - init_params are displayed below: +2026-06-24 05:40:17,867 - random_seed: 20261869 +2026-06-24 05:40:17,867 - probe_illum_type: electron +2026-06-24 05:40:17,867 - probe_kv: 160.0 +2026-06-24 05:40:17,867 - probe_conv_angle: 14.081535339355469 +2026-06-24 05:40:17,867 - probe_aberrations: {'C10': -466.196, 'C12': -4.329, 'phi12': 246.756, 'C21': 885.492, 'phi21': 330.871, 'C23': 176.589, 'phi23': 50.877, 'C30': 1715538.125, 'C32': 414.842, 'phi32': 312.871, 'C34': -6463.508, 'phi34': 335.501, 'C41': 451307.062, 'phi41': 49.985, 'C43': 149261.594, 'phi43': 0.384, 'C45': -46862.719, 'phi45': 226.431, 'C50': 297418240.0, 'C52': -5586598.0, 'phi52': 127.913, 'C54': 9159130.0, 'phi54': 4.48, 'C56': -15625374.0, 'phi56': 242.221} +2026-06-24 05:40:17,867 - beam_kev: None +2026-06-24 05:40:17,867 - probe_dRn: None +2026-06-24 05:40:17,867 - probe_Rn: None +2026-06-24 05:40:17,867 - probe_D_H: None +2026-06-24 05:40:17,867 - probe_D_FZP: None +2026-06-24 05:40:17,867 - probe_Ls: None +2026-06-24 05:40:17,867 - meas_Npix: 128 +2026-06-24 05:40:17,867 - pos_N_scans: 256 +2026-06-24 05:40:17,867 - pos_N_scan_slow: 16 +2026-06-24 05:40:17,867 - pos_N_scan_fast: 16 +2026-06-24 05:40:17,867 - pos_scan_step_size: 0.3641342520713806 +2026-06-24 05:40:17,867 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:40:17,867 - probe_pmode_max: 6 +2026-06-24 05:40:17,867 - probe_pmode_init_pows: [0.02] +2026-06-24 05:40:17,867 - obj_omode_max: 1 +2026-06-24 05:40:17,867 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:40:17,867 - obj_Nlayer: 1 +2026-06-24 05:40:17,867 - obj_slice_thickness: 20.0 +2026-06-24 05:40:17,867 - simu_Npix: None +2026-06-24 05:40:17,867 - simu_match_mode: None +2026-06-24 05:40:17,867 - meas_permute: None +2026-06-24 05:40:17,868 - meas_reshape: [256, 128, 128] +2026-06-24 05:40:17,868 - meas_flipT: [0, 0, 0] +2026-06-24 05:40:17,868 - meas_crop: None +2026-06-24 05:40:17,868 - meas_pad: None +2026-06-24 05:40:17,868 - meas_resample: None +2026-06-24 05:40:17,868 - meas_add_source_size: None +2026-06-24 05:40:17,868 - meas_add_detector_blur: None +2026-06-24 05:40:17,868 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:40:17,868 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:40:17,868 - meas_add_poisson_noise: None +2026-06-24 05:40:17,868 - meas_export: None +2026-06-24 05:40:17,868 - probe_permute: None +2026-06-24 05:40:17,868 - probe_z_shift: None +2026-06-24 05:40:17,868 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:40:17,868 - pos_scan_flipT: None +2026-06-24 05:40:17,868 - pos_scan_affine: None +2026-06-24 05:40:17,868 - pos_scan_rand_std: 0.15 +2026-06-24 05:40:17,868 - obj_z_crop: None +2026-06-24 05:40:17,868 - obj_z_pad: None +2026-06-24 05:40:17,868 - obj_z_resample: None +2026-06-24 05:40:17,868 - meas_source: file +2026-06-24 05:40:17,868 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000025_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:40:17,868 - probe_source: simu +2026-06-24 05:40:17,868 - probe_params: None +2026-06-24 05:40:17,868 - pos_source: simu +2026-06-24 05:40:17,868 - pos_params: None +2026-06-24 05:40:17,868 - obj_source: simu +2026-06-24 05:40:17,868 - obj_params: None +2026-06-24 05:40:17,868 - tilt_source: simu +2026-06-24 05:40:17,868 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:40:17,868 - +2026-06-24 05:40:17,868 - ### Initializing cache ### +2026-06-24 05:40:17,868 - use_cached_obj = False +2026-06-24 05:40:17,868 - use_cached_probe = False +2026-06-24 05:40:17,868 - use_cached_pos = False +2026-06-24 05:40:17,868 - +2026-06-24 05:40:17,868 - ### Initializing measurements ### +2026-06-24 05:40:17,868 - Loading measurements from source = 'file' +2026-06-24 05:40:17,868 - Detected measurement file type = '.h5' +2026-06-24 05:40:17,947 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:40:17,947 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:40:17,949 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0027) +2026-06-24 05:40:17,949 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:40:17,949 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:40:17,950 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:40:17,950 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:40:17,950 - Normalizing by max of the 2D mean pattern intensity: 0.0019435086 +2026-06-24 05:40:17,951 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:40:17,952 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0313, 1.4110) +2026-06-24 05:40:17,953 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:40:17,954 - Pattern total int. statistics (min, mean, max) = (509.7016, 512.3783, 515.4451), with min/max = 98.9% +2026-06-24 05:40:17,955 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0313, 1.4110) +2026-06-24 05:40:17,956 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:40:17,956 - +2026-06-24 05:40:17,956 - ### Setting up calibration ### +2026-06-24 05:40:17,956 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:40:17,956 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:40:17,956 - Radius of fitted bright field disk (RBF) = 12.49 px with meas_Npix = 128 +2026-06-24 05:40:17,956 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1951 +2026-06-24 05:40:17,956 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:40:17,956 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:40:18,176 - Initial guess: center=(63.62, 63.64), radius=12.49, Gaussian blur std=0.50 +2026-06-24 05:40:18,190 - Final fit: center=(63.62, 63.64), radius=12.49, Gaussian blur std=0.72 +2026-06-24 05:40:18,190 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.64 px with Npix = 128 +2026-06-24 05:40:18,190 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:40:18,190 - +2026-06-24 05:40:18,190 - ### Setting init_variables dict ### +2026-06-24 05:40:18,190 - Derived values given input init_params: +2026-06-24 05:40:18,190 - kv = 160.0 kV +2026-06-24 05:40:18,190 - wavelength = 0.0285 Ang +2026-06-24 05:40:18,190 - conv_angle = 14.081535339355469 mrad +2026-06-24 05:40:18,190 - Npix = 128 px +2026-06-24 05:40:18,190 - dk = 0.0391 Ang^-1 +2026-06-24 05:40:18,190 - kMax = 2.5000 Ang^-1 +2026-06-24 05:40:18,190 - da = 1.1137 mrad +2026-06-24 05:40:18,190 - angleMax = 71.2751 mrad +2026-06-24 05:40:18,190 - RBF = 12.6442 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:40:18,190 - n_alpha = 5.0616 (# conv_angle) +2026-06-24 05:40:18,190 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:40:18,190 - Rayleigh-limited resolution = 1.2350 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:40:18,190 - Real space probe extent = 25.6000 Ang +2026-06-24 05:40:18,190 - +2026-06-24 05:40:18,190 - ### Initializing probe ### +2026-06-24 05:40:18,190 - Loading probe from source = 'simu' +2026-06-24 05:40:18,190 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:40:18,191 - Start simulating STEM probe +2026-06-24 05:40:18,191 - kv = 160.0 kV +2026-06-24 05:40:18,191 - wavelength = 0.0285 Ang +2026-06-24 05:40:18,191 - conv_angle = 14.081535339355469 mrad +2026-06-24 05:40:18,191 - Npix = 128 px +2026-06-24 05:40:18,191 - dk = 0.0391 Ang^-1 +2026-06-24 05:40:18,191 - kMax = 2.5000 Ang^-1 +2026-06-24 05:40:18,191 - alpha_max = 71.2751 mrad +2026-06-24 05:40:18,191 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:40:18,191 - Rayleigh-limited resolution = 1.2350 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:40:18,191 - Real space probe extent = 25.6000 Ang +2026-06-24 05:40:18,191 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:40:18,191 - ------------------------------------------------------------------------------------ +2026-06-24 05:40:18,191 - C1,0 C1 -466.1960 - Defocus (C10 = -df) +2026-06-24 05:40:18,191 - C1,2 A1 -4.3290 246.76 2-fold astigmatism +2026-06-24 05:40:18,191 - C2,1 3*B2 885.4920 330.87 Axial coma +2026-06-24 05:40:18,191 - C2,3 A2 176.5890 50.88 3-fold astigmatism +2026-06-24 05:40:18,191 - C3,0 C3 1715538.1250 - Spherical aberration +2026-06-24 05:40:18,191 - C3,2 4*S3 414.8420 312.87 Axial star aberration +2026-06-24 05:40:18,191 - C3,4 A3 -6463.5080 335.50 4-fold astigmatism +2026-06-24 05:40:18,191 - C4,1 4*B4 451307.0620 49.98 Axial coma(4th) +2026-06-24 05:40:18,191 - C4,3 4*D4 149261.5940 0.38 3-lobe aberration +2026-06-24 05:40:18,191 - C4,5 A4 -46862.7190 226.43 5-fold astigmatism +2026-06-24 05:40:18,191 - C5,0 C5 297418240.0000 - Spherical aberration (5th) +2026-06-24 05:40:18,191 - C5,2 6*S5 -5586598.0000 127.91 Axial star aberration(5th) +2026-06-24 05:40:18,191 - C5,4 6*R5 9159130.0000 4.48 4-lobe aberration +2026-06-24 05:40:18,191 - C5,6 A5 -15625374.0000 242.22 6-fold astigmatism +2026-06-24 05:40:18,194 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:40:18,194 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:40:18,194 - Creating 5 new probe modes from the major mode +2026-06-24 05:40:18,194 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:40:18,390 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:40:18,391 - Orthogonalizing 6 pmodes +2026-06-24 05:40:18,404 - Sorting 6 pmodes by their intensities +2026-06-24 05:40:18,404 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:40:18,405 - sum(|probe_data|**2) = 512.38, while meas_total_ints (min, mean, max) = (509.7016, 512.3783, 515.4451) +2026-06-24 05:40:18,405 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:40:18,405 - +2026-06-24 05:40:18,405 - ### Initializing probe positions ### +2026-06-24 05:40:18,405 - Loading probe positions from source = 'simu' +2026-06-24 05:40:18,405 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:40:18,405 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3641, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:40:18,405 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:40:18,407 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:40:18,407 - crop_pos 1st and last px coords (y,x) = ([16, 15], [43, 43]) +2026-06-24 05:40:18,408 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:40:18,408 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:40:18,408 - +2026-06-24 05:40:18,408 - ### Initializing object ### +2026-06-24 05:40:18,408 - Loading object from source = 'simu' +2026-06-24 05:40:18,408 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:40:18,409 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:40:18,409 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 05:40:18,409 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 05:40:18,409 - +2026-06-24 05:40:18,409 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:40:18,409 - omode_occu (omode) = float32, (1,) +2026-06-24 05:40:18,409 - +2026-06-24 05:40:18,410 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:40:18,410 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:40:18,410 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:40:18,410 - +2026-06-24 05:40:18,410 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:40:18,410 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:40:18,410 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:40:18,410 - +2026-06-24 05:40:18,410 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:40:18,410 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:40:18,410 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:40:18,411 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:40:18,411 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:40:18,411 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 05:40:18,411 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:40:18,411 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:40:18,411 - +2026-06-24 05:40:18,411 - ### Collecting reconstruction provenance ### +2026-06-24 05:40:18,411 - Reconstruction provenance is collected and initialized. +2026-06-24 05:40:18,411 - +2026-06-24 05:40:18,411 - ### Initializing loss function ### +2026-06-24 05:40:18,411 - Active loss types: +2026-06-24 05:40:18,411 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:40:18,411 - +2026-06-24 05:40:18,411 - ### Initializing constraint function ### +2026-06-24 05:40:18,411 - Active constraint types: +2026-06-24 05:40:18,411 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:40:18,411 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:40:18,411 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:40:18,411 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:40:18,411 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:40:18,411 - +2026-06-24 05:40:18,412 - ### Done initializing PtyRADSolver ### +2026-06-24 05:40:18,412 - +2026-06-24 05:40:18,534 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:40:18,534 - +2026-06-24 05:40:18,534 - ### Initializing PtychoModel model ### +2026-06-24 05:40:18,605 - ### PtychoModel optimizable variables ### +2026-06-24 05:40:18,605 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:40:18,605 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:40:18,605 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:40:18,605 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:40:18,605 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:40:18,605 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:40:18,605 - +2026-06-24 05:40:18,605 - ### Optimizable variables statitsics ### +2026-06-24 05:40:18,606 - Total measurement values : 4,194,304 +2026-06-24 05:40:18,606 - Total optimizing variables: 267,058 +2026-06-24 05:40:18,606 - Overdetermined ratio : 15.71 +2026-06-24 05:40:18,606 - +2026-06-24 05:40:18,606 - ### Model behavior ### +2026-06-24 05:40:18,606 - Tilt propagator : False +2026-06-24 05:40:18,606 - Change slice thickness : False +2026-06-24 05:40:18,606 - Detector blur : False +2026-06-24 05:40:18,606 - Preload data : True +2026-06-24 05:40:18,606 - On-the-fly meas padding : False +2026-06-24 05:40:18,606 - On-the-fly meas resample : False +2026-06-24 05:40:18,606 - On-the-fly simu match mode: None +2026-06-24 05:40:18,606 - +2026-06-24 05:40:18,648 - ### Done initializing PtychoModel model ### +2026-06-24 05:40:18,648 - +2026-06-24 05:40:18,648 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:40:18,648 - +2026-06-24 05:40:18,649 - ### Generating indices, batches, and output_path ### +2026-06-24 05:40:18,650 - d90 = 41.000 px or 8.200 Ang +2026-06-24 05:40:18,650 - Selecting indices with the 'full' mode +2026-06-24 05:40:19,116 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:40:19,189 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:40:19,189 - Original recon_dir_affixes = ['default'] +2026-06-24 05:40:19,189 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:40:19,195 - Path corrected for compatibility: +2026-06-24 05:40:19,195 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_415_phi32_313_C34_-6.46e+03_phi34_336_C41_4.51e+05_phi41_50_C43_1.49e+05_phi43_0.384_C45_-4.69e+04_phi45_226_C50_2.97e+08_C52_-5.59e+06_phi52_128_C54_9.16e+06_phi54_4.48_C56_-1.56e+07_phi56_242 +2026-06-24 05:40:19,195 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242 +2026-06-24 05:40:19,196 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242' is generated! +2026-06-24 05:40:19,345 - +2026-06-24 05:40:19,346 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242/20260624_054019_ptyrad_log.txt ### +2026-06-24 05:40:19,346 - +2026-06-24 05:40:19,347 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:40:19,347 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:40:19,347 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:40:20,542 - Iter: 1, Total Loss: 0.8792, loss_single: 0.8792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:40:20,579 - Iter: 2, Total Loss: 0.8481, loss_single: 0.8481, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:40:20,615 - Iter: 3, Total Loss: 0.8235, loss_single: 0.8235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,650 - Iter: 4, Total Loss: 0.8010, loss_single: 0.8010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,686 - Iter: 5, Total Loss: 0.7762, loss_single: 0.7762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,721 - Iter: 6, Total Loss: 0.7537, loss_single: 0.7537, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,756 - Iter: 7, Total Loss: 0.7321, loss_single: 0.7321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,792 - Iter: 8, Total Loss: 0.7128, loss_single: 0.7128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,827 - Iter: 9, Total Loss: 0.6944, loss_single: 0.6944, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,862 - Iter: 10, Total Loss: 0.6706, loss_single: 0.6706, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,897 - Iter: 11, Total Loss: 0.6489, loss_single: 0.6489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,932 - Iter: 12, Total Loss: 0.6282, loss_single: 0.6282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:20,967 - Iter: 13, Total Loss: 0.6072, loss_single: 0.6072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,024 - Iter: 14, Total Loss: 0.5912, loss_single: 0.5912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,059 - Iter: 15, Total Loss: 0.5739, loss_single: 0.5739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,095 - Iter: 16, Total Loss: 0.5551, loss_single: 0.5551, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,129 - Iter: 17, Total Loss: 0.5378, loss_single: 0.5378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:40:21,165 - Iter: 18, Total Loss: 0.5210, loss_single: 0.5210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,199 - Iter: 19, Total Loss: 0.5032, loss_single: 0.5032, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:40:21,234 - Iter: 20, Total Loss: 0.4880, loss_single: 0.4880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,270 - Iter: 21, Total Loss: 0.4736, loss_single: 0.4736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,305 - Iter: 22, Total Loss: 0.4563, loss_single: 0.4563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,340 - Iter: 23, Total Loss: 0.4399, loss_single: 0.4399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:40:21,375 - Iter: 24, Total Loss: 0.4241, loss_single: 0.4241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,413 - Iter: 25, Total Loss: 0.4120, loss_single: 0.4120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:40:21,449 - Iter: 26, Total Loss: 0.4026, loss_single: 0.4026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,484 - Iter: 27, Total Loss: 0.3942, loss_single: 0.3942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,519 - Iter: 28, Total Loss: 0.3858, loss_single: 0.3858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,555 - Iter: 29, Total Loss: 0.3754, loss_single: 0.3754, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,590 - Iter: 30, Total Loss: 0.3653, loss_single: 0.3653, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,625 - Iter: 31, Total Loss: 0.3562, loss_single: 0.3562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,660 - Iter: 32, Total Loss: 0.3471, loss_single: 0.3471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,696 - Iter: 33, Total Loss: 0.3414, loss_single: 0.3414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,731 - Iter: 34, Total Loss: 0.3369, loss_single: 0.3369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:21,766 - Iter: 35, Total Loss: 0.3314, loss_single: 0.3314, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:22,015 - Iter: 42, Total Loss: 0.3008, loss_single: 0.3008, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:22,050 - Iter: 43, Total Loss: 0.2989, loss_single: 0.2989, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:40:22,085 - Iter: 44, Total Loss: 0.2974, loss_single: 0.2974, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:22,120 - Iter: 45, Total Loss: 0.2958, loss_single: 0.2958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:22,156 - Iter: 46, Total Loss: 0.2940, loss_single: 0.2940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:40:22,191 - 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025/c30_small__simulation_data1__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-466_C12_-4.33_phi12_247_C21_885_phi21_331_C23_177_phi23_50.9_C30_1.72e+06_C32_41.56e+07_phi56_242/simulation_data1__sample_000025.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 14.081535339355469 + probe_aberrations: + C10: -466.1963806152344 + C12: -4.3289289474487305 + C21: 885.4915771484375 + C23: 176.5885009765625 + C30: 1715538.125 + C32: 414.8424987792969 + C34: -6463.50830078125 + C41: 451307.0625 + C43: 149261.59375 + C45: -46862.71875 + C50: 297418240.0 + C52: -5586598.0 + C54: 9159130.0 + C56: -15625374.0 + phi12: 246.75626588104498 + phi21: 330.87105637774914 + phi23: 50.87718778773829 + phi32: 312.8711310089344 + phi34: 335.50061323869716 + phi41: 49.98486455381115 + phi43: 0.3835888132340581 + phi45: 226.43122117535282 + phi52: 127.91265454935893 + phi54: 4.480188734649463 + phi56: 242.22126615896664 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3641342520713806 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data1__sample_000025_measurement.h5 + key: measurement + random_seed: 20261869 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data1__sample_000025 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192/20260624_054529_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:45:27,647 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:45:27,647 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:45:27,647 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:45:27,647 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:45:27,647 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:45:27,647 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:45:27,647 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:45:27,647 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:45:27,647 - +2026-06-24 05:45:27,754 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:45:27,755 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:45:27,755 - Accelerator.num_process = 1 +2026-06-24 05:45:27,755 - Accelerator.mixed_precision = no +2026-06-24 05:45:27,765 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:45:27,765 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:45:27,765 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:45:27,765 - +2026-06-24 05:45:27,766 - ### System information ### +2026-06-24 05:45:27,766 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:45:27,766 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:45:27,766 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:45:27,766 - Machine: x86_64 +2026-06-24 05:45:27,766 - Processor: x86_64 +2026-06-24 05:45:27,766 - Available CPU cores: 8 +2026-06-24 05:45:27,766 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:45:27,766 - +2026-06-24 05:45:27,766 - ### GPU information ### +2026-06-24 05:45:27,766 - CUDA Available: True +2026-06-24 05:45:27,766 - CUDA Version: 13.0 +2026-06-24 05:45:27,766 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:45:27,767 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:45:27,767 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:45:27,767 - In addition, Triton does not directly support Windows. +2026-06-24 05:45:27,767 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:45:27,782 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:45:27,782 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:45:27,782 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:45:27,782 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:45:27,782 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:45:27,782 - +2026-06-24 05:45:27,782 - ### Python information ### +2026-06-24 05:45:27,784 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:45:27,784 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:45:27,784 - +2026-06-24 05:45:27,784 - ### Packages information ### +2026-06-24 05:45:27,785 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:45:27,786 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:45:27,786 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:45:27,787 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:45:27,787 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:45:27,788 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:45:27,788 - +2026-06-24 05:45:27,788 - ### Loading params file ### +2026-06-24 05:45:27,788 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000010.yaml +2026-06-24 05:45:27,794 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:45:27,795 - Success! Params file validated and defaults applied. +2026-06-24 05:45:27,795 - +2026-06-24 05:45:27,795 - ### Setting GPU Device ### +2026-06-24 05:45:27,795 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:45:27,795 - +2026-06-24 05:45:27,795 - Random seed: 20261890 provided by params file +2026-06-24 05:45:27,796 - ### Initializing Initializer ### +2026-06-24 05:45:27,796 - init_params are displayed below: +2026-06-24 05:45:27,796 - random_seed: 20261890 +2026-06-24 05:45:27,796 - probe_illum_type: electron +2026-06-24 05:45:27,796 - probe_kv: 200.0 +2026-06-24 05:45:27,796 - probe_conv_angle: 14.648444175720215 +2026-06-24 05:45:27,796 - probe_aberrations: {'C10': -280.881, 'C12': -45.001, 'phi12': 251.534, 'C21': -635.093, 'phi21': 273.773, 'C23': -597.886, 'phi23': 213.677, 'C30': -691629.875, 'C32': 5396.419, 'phi32': 30.858, 'C34': 10994.863, 'phi34': 69.616, 'C41': -327631.844, 'phi41': 224.575, 'C43': -402904.312, 'phi43': 198.993, 'C45': -285365.844, 'phi45': 268.734, 'C50': -325864064.0, 'C52': -965757.688, 'phi52': 152.598, 'C54': -3862680.5, 'phi54': 310.344, 'C56': -14337243.0, 'phi56': 192.013} +2026-06-24 05:45:27,796 - beam_kev: None +2026-06-24 05:45:27,796 - probe_dRn: None +2026-06-24 05:45:27,796 - probe_Rn: None +2026-06-24 05:45:27,796 - probe_D_H: None +2026-06-24 05:45:27,796 - probe_D_FZP: None +2026-06-24 05:45:27,796 - probe_Ls: None +2026-06-24 05:45:27,796 - meas_Npix: 128 +2026-06-24 05:45:27,796 - pos_N_scans: 256 +2026-06-24 05:45:27,796 - pos_N_scan_slow: 16 +2026-06-24 05:45:27,796 - pos_N_scan_fast: 16 +2026-06-24 05:45:27,796 - pos_scan_step_size: 0.3628361225128174 +2026-06-24 05:45:27,796 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:45:27,796 - probe_pmode_max: 6 +2026-06-24 05:45:27,796 - probe_pmode_init_pows: [0.02] +2026-06-24 05:45:27,796 - obj_omode_max: 1 +2026-06-24 05:45:27,796 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:45:27,796 - obj_Nlayer: 1 +2026-06-24 05:45:27,796 - obj_slice_thickness: 20.0 +2026-06-24 05:45:27,796 - simu_Npix: None +2026-06-24 05:45:27,797 - simu_match_mode: None +2026-06-24 05:45:27,797 - meas_permute: None +2026-06-24 05:45:27,797 - meas_reshape: [256, 128, 128] +2026-06-24 05:45:27,797 - meas_flipT: [0, 0, 0] +2026-06-24 05:45:27,797 - meas_crop: None +2026-06-24 05:45:27,797 - meas_pad: None +2026-06-24 05:45:27,797 - meas_resample: None +2026-06-24 05:45:27,797 - meas_add_source_size: None +2026-06-24 05:45:27,797 - meas_add_detector_blur: None +2026-06-24 05:45:27,797 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:45:27,797 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:45:27,797 - meas_add_poisson_noise: None +2026-06-24 05:45:27,797 - meas_export: None +2026-06-24 05:45:27,797 - probe_permute: None +2026-06-24 05:45:27,797 - probe_z_shift: None +2026-06-24 05:45:27,797 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:45:27,797 - pos_scan_flipT: None +2026-06-24 05:45:27,797 - pos_scan_affine: None +2026-06-24 05:45:27,797 - pos_scan_rand_std: 0.15 +2026-06-24 05:45:27,797 - obj_z_crop: None +2026-06-24 05:45:27,797 - obj_z_pad: None +2026-06-24 05:45:27,797 - obj_z_resample: None +2026-06-24 05:45:27,797 - meas_source: file +2026-06-24 05:45:27,797 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000010_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:45:27,797 - probe_source: simu +2026-06-24 05:45:27,797 - probe_params: None +2026-06-24 05:45:27,797 - pos_source: simu +2026-06-24 05:45:27,797 - pos_params: None +2026-06-24 05:45:27,797 - obj_source: simu +2026-06-24 05:45:27,797 - obj_params: None +2026-06-24 05:45:27,797 - tilt_source: simu +2026-06-24 05:45:27,797 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:45:27,797 - +2026-06-24 05:45:27,797 - ### Initializing cache ### +2026-06-24 05:45:27,797 - use_cached_obj = False +2026-06-24 05:45:27,797 - use_cached_probe = False +2026-06-24 05:45:27,797 - use_cached_pos = False +2026-06-24 05:45:27,797 - +2026-06-24 05:45:27,797 - ### Initializing measurements ### +2026-06-24 05:45:27,797 - Loading measurements from source = 'file' +2026-06-24 05:45:27,798 - Detected measurement file type = '.h5' +2026-06-24 05:45:27,873 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:45:27,873 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:45:27,875 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0023) +2026-06-24 05:45:27,875 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:45:27,875 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:45:27,877 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:45:27,877 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:45:27,877 - Normalizing by max of the 2D mean pattern intensity: 0.0014165619 +2026-06-24 05:45:27,878 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:45:27,879 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0431, 1.5999) +2026-06-24 05:45:27,880 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:45:27,881 - Pattern total int. statistics (min, mean, max) = (698.0621, 706.7218, 714.7162), with min/max = 97.7% +2026-06-24 05:45:27,882 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0431, 1.5999) +2026-06-24 05:45:27,882 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:45:27,882 - +2026-06-24 05:45:27,882 - ### Setting up calibration ### +2026-06-24 05:45:27,882 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:45:27,882 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:45:27,882 - Radius of fitted bright field disk (RBF) = 14.82 px with meas_Npix = 128 +2026-06-24 05:45:27,882 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2316 +2026-06-24 05:45:27,882 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:45:27,882 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:45:28,112 - Initial guess: center=(63.62, 63.63), radius=14.82, Gaussian blur std=0.50 +2026-06-24 05:45:28,127 - Final fit: center=(63.62, 63.63), radius=14.82, Gaussian blur std=0.73 +2026-06-24 05:45:28,127 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 14.95 px with Npix = 128 +2026-06-24 05:45:28,127 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:45:28,127 - +2026-06-24 05:45:28,127 - ### Setting init_variables dict ### +2026-06-24 05:45:28,127 - Derived values given input init_params: +2026-06-24 05:45:28,127 - kv = 200.0 kV +2026-06-24 05:45:28,127 - wavelength = 0.0251 Ang +2026-06-24 05:45:28,127 - conv_angle = 14.648444175720215 mrad +2026-06-24 05:45:28,127 - Npix = 128 px +2026-06-24 05:45:28,127 - dk = 0.0391 Ang^-1 +2026-06-24 05:45:28,127 - kMax = 2.5000 Ang^-1 +2026-06-24 05:45:28,128 - da = 0.9797 mrad +2026-06-24 05:45:28,128 - angleMax = 62.6984 mrad +2026-06-24 05:45:28,128 - RBF = 14.9526 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:45:28,128 - n_alpha = 4.2802 (# conv_angle) +2026-06-24 05:45:28,128 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:45:28,128 - Rayleigh-limited resolution = 1.0444 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:45:28,128 - Real space probe extent = 25.6000 Ang +2026-06-24 05:45:28,128 - +2026-06-24 05:45:28,128 - ### Initializing probe ### +2026-06-24 05:45:28,128 - Loading probe from source = 'simu' +2026-06-24 05:45:28,128 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:45:28,128 - Start simulating STEM probe +2026-06-24 05:45:28,128 - kv = 200.0 kV +2026-06-24 05:45:28,128 - wavelength = 0.0251 Ang +2026-06-24 05:45:28,128 - conv_angle = 14.648444175720215 mrad +2026-06-24 05:45:28,128 - Npix = 128 px +2026-06-24 05:45:28,128 - dk = 0.0391 Ang^-1 +2026-06-24 05:45:28,128 - kMax = 2.5000 Ang^-1 +2026-06-24 05:45:28,128 - alpha_max = 62.6984 mrad +2026-06-24 05:45:28,128 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:45:28,128 - Rayleigh-limited resolution = 1.0444 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:45:28,128 - Real space probe extent = 25.6000 Ang +2026-06-24 05:45:28,128 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:45:28,128 - ------------------------------------------------------------------------------------- +2026-06-24 05:45:28,129 - C1,0 C1 -280.8810 - Defocus (C10 = -df) +2026-06-24 05:45:28,129 - C1,2 A1 -45.0010 251.53 2-fold astigmatism +2026-06-24 05:45:28,129 - C2,1 3*B2 -635.0930 273.77 Axial coma +2026-06-24 05:45:28,129 - C2,3 A2 -597.8860 213.68 3-fold astigmatism +2026-06-24 05:45:28,129 - C3,0 C3 -691629.8750 - Spherical aberration +2026-06-24 05:45:28,129 - C3,2 4*S3 5396.4190 30.86 Axial star aberration +2026-06-24 05:45:28,129 - C3,4 A3 10994.8630 69.62 4-fold astigmatism +2026-06-24 05:45:28,129 - C4,1 4*B4 -327631.8440 224.57 Axial coma(4th) +2026-06-24 05:45:28,129 - C4,3 4*D4 -402904.3120 198.99 3-lobe aberration +2026-06-24 05:45:28,129 - C4,5 A4 -285365.8440 268.73 5-fold astigmatism +2026-06-24 05:45:28,129 - C5,0 C5 -325864064.0000 - Spherical aberration (5th) +2026-06-24 05:45:28,129 - C5,2 6*S5 -965757.6880 152.60 Axial star aberration(5th) +2026-06-24 05:45:28,129 - C5,4 6*R5 -3862680.5000 310.34 4-lobe aberration +2026-06-24 05:45:28,129 - C5,6 A5 -14337243.0000 192.01 6-fold astigmatism +2026-06-24 05:45:28,132 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:45:28,132 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:45:28,132 - Creating 5 new probe modes from the major mode +2026-06-24 05:45:28,132 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:45:28,139 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:45:28,140 - Orthogonalizing 6 pmodes +2026-06-24 05:45:28,143 - Sorting 6 pmodes by their intensities +2026-06-24 05:45:28,143 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:45:28,144 - sum(|probe_data|**2) = 706.72, while meas_total_ints (min, mean, max) = (698.0621, 706.7218, 714.7162) +2026-06-24 05:45:28,144 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:45:28,144 - +2026-06-24 05:45:28,144 - ### Initializing probe positions ### +2026-06-24 05:45:28,144 - Loading probe positions from source = 'simu' +2026-06-24 05:45:28,144 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:45:28,145 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3628, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:45:28,145 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:45:28,147 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:45:28,147 - crop_pos 1st and last px coords (y,x) = ([15, 15], [42, 43]) +2026-06-24 05:45:28,147 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:45:28,147 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:45:28,147 - +2026-06-24 05:45:28,147 - ### Initializing object ### +2026-06-24 05:45:28,147 - Loading object from source = 'simu' +2026-06-24 05:45:28,147 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:45:28,148 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:45:28,148 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 05:45:28,149 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 05:45:28,149 - +2026-06-24 05:45:28,149 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:45:28,149 - omode_occu (omode) = float32, (1,) +2026-06-24 05:45:28,149 - +2026-06-24 05:45:28,149 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:45:28,149 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:45:28,149 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:45:28,150 - +2026-06-24 05:45:28,150 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:45:28,150 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:45:28,150 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:45:28,150 - +2026-06-24 05:45:28,150 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:45:28,150 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:45:28,150 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:45:28,150 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:45:28,150 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:45:28,150 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 05:45:28,150 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:45:28,150 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:45:28,150 - +2026-06-24 05:45:28,150 - ### Collecting reconstruction provenance ### +2026-06-24 05:45:28,150 - Reconstruction provenance is collected and initialized. +2026-06-24 05:45:28,150 - +2026-06-24 05:45:28,150 - ### Initializing loss function ### +2026-06-24 05:45:28,150 - Active loss types: +2026-06-24 05:45:28,150 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:45:28,151 - +2026-06-24 05:45:28,151 - ### Initializing constraint function ### +2026-06-24 05:45:28,151 - Active constraint types: +2026-06-24 05:45:28,151 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:45:28,151 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:45:28,151 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:45:28,151 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:45:28,151 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:45:28,151 - +2026-06-24 05:45:28,151 - ### Done initializing PtyRADSolver ### +2026-06-24 05:45:28,151 - +2026-06-24 05:45:28,275 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:45:28,275 - +2026-06-24 05:45:28,275 - ### Initializing PtychoModel model ### +2026-06-24 05:45:28,346 - ### PtychoModel optimizable variables ### +2026-06-24 05:45:28,346 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:45:28,346 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:45:28,346 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:45:28,346 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:45:28,346 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:45:28,346 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:45:28,346 - +2026-06-24 05:45:28,346 - ### Optimizable variables statitsics ### +2026-06-24 05:45:28,346 - Total measurement values : 4,194,304 +2026-06-24 05:45:28,346 - Total optimizing variables: 267,058 +2026-06-24 05:45:28,346 - Overdetermined ratio : 15.71 +2026-06-24 05:45:28,346 - +2026-06-24 05:45:28,347 - ### Model behavior ### +2026-06-24 05:45:28,347 - Tilt propagator : False +2026-06-24 05:45:28,347 - Change slice thickness : False +2026-06-24 05:45:28,347 - Detector blur : False +2026-06-24 05:45:28,347 - Preload data : True +2026-06-24 05:45:28,347 - On-the-fly meas padding : False +2026-06-24 05:45:28,347 - On-the-fly meas resample : False +2026-06-24 05:45:28,347 - On-the-fly simu match mode: None +2026-06-24 05:45:28,347 - +2026-06-24 05:45:28,387 - ### Done initializing PtychoModel model ### +2026-06-24 05:45:28,387 - +2026-06-24 05:45:28,387 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:45:28,388 - +2026-06-24 05:45:28,388 - ### Generating indices, batches, and output_path ### +2026-06-24 05:45:28,389 - d90 = 63.000 px or 12.600 Ang +2026-06-24 05:45:28,389 - Selecting indices with the 'full' mode +2026-06-24 05:45:28,845 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:45:28,917 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:45:28,917 - Original recon_dir_affixes = ['default'] +2026-06-24 05:45:28,917 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:45:28,925 - Path corrected for compatibility: +2026-06-24 05:45:28,926 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5.4e+03_phi32_30.9_C34_1.1e+04_phi34_69.6_C41_-3.28e+05_phi41_225_C43_-4.03e+05_phi43_199_C45_-2.85e+05_phi45_269_C50_-3.26e+08_C52_-9.66e+05_phi52_153_C54_-3.86e+06_phi54_310_C56_-1.43e+07_phi56_192 +2026-06-24 05:45:28,926 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192 +2026-06-24 05:45:28,927 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192' is generated! +2026-06-24 05:45:29,077 - +2026-06-24 05:45:29,078 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192/20260624_054529_ptyrad_log.txt ### +2026-06-24 05:45:29,078 - +2026-06-24 05:45:29,079 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:45:29,079 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:45:29,079 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:45:30,257 - Iter: 1, Total Loss: 0.7468, loss_single: 0.7468, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:45:30,295 - Iter: 2, Total Loss: 0.7199, loss_single: 0.7199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:45:30,330 - Iter: 3, Total Loss: 0.6966, loss_single: 0.6966, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,365 - Iter: 4, Total Loss: 0.6789, loss_single: 0.6789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,400 - Iter: 5, Total Loss: 0.6634, loss_single: 0.6634, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,436 - Iter: 6, Total Loss: 0.6471, loss_single: 0.6471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,472 - Iter: 7, Total Loss: 0.6311, loss_single: 0.6311, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,506 - Iter: 8, Total Loss: 0.6152, loss_single: 0.6152, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,542 - Iter: 9, Total Loss: 0.6002, loss_single: 0.6002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,577 - Iter: 10, Total Loss: 0.5864, loss_single: 0.5864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,612 - Iter: 11, Total Loss: 0.5739, loss_single: 0.5739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,647 - Iter: 12, Total Loss: 0.5616, loss_single: 0.5616, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,683 - Iter: 13, Total Loss: 0.5504, loss_single: 0.5504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:45:30,719 - Iter: 14, Total Loss: 0.5385, loss_single: 0.5385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,754 - Iter: 15, Total Loss: 0.5270, loss_single: 0.5270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,789 - Iter: 16, Total Loss: 0.5159, loss_single: 0.5159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:30,826 - Iter: 17, Total Loss: 0.5029, loss_single: 0.5029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:45:30,861 - Iter: 18, Total Loss: 0.4919, loss_single: 0.4919, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.3347, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:33,737 - Iter: 99, Total Loss: 0.3346, loss_single: 0.3346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:33,772 - Iter: 100, Total Loss: 0.3346, loss_single: 0.3346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:45:33,883 - Saving summary figures for iter 100 +2026-06-24 05:45:37,580 - ### Finished 100 iterations, averaged iter_t = 0.038916 with std = 0.040 ### +2026-06-24 05:45:37,580 - +2026-06-24 05:45:37,581 - ### The PtyRADSolver is finished in 9.306 sec ### +2026-06-24 05:45:37,581 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192/model_iter0100.hdf5 b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192/model_iter0100.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..0c21df113149ae3d6f45e418e8b4fd978a00f493 --- /dev/null +++ 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000010/c30_small__simulation_data2__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-281_C12_-45_phi12_252_C21_-635_phi21_274_C23_-598_phi23_214_C30_-6.92e+05_C32_5..43e+07_phi56_192/simulation_data2__sample_000010.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 14.648444175720215 + probe_aberrations: + C10: -280.8814392089844 + C12: -45.00096893310547 + C21: -635.0934448242188 + C23: -597.8859252929688 + C30: -691629.875 + C32: 5396.41943359375 + C34: 10994.86328125 + C41: -327631.84375 + C43: -402904.3125 + C45: -285365.84375 + C50: -325864064.0 + C52: -965757.6875 + C54: -3862680.5 + C56: -14337243.0 + phi12: 251.5338192809288 + phi21: 273.7725600486535 + phi23: 213.6768264475945 + phi32: 30.857848688917564 + phi34: 69.61590398322207 + phi41: 224.57452987213324 + phi43: 198.99339505292778 + phi45: 268.7343119885286 + phi52: 152.59825594572732 + phi54: 310.3436604877062 + phi56: 192.01344715517334 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3628361225128174 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000010_measurement.h5 + key: measurement + random_seed: 20261890 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8..62e+07_phi56_238/20260624_054811_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:48:10,116 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:48:10,117 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:48:10,117 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:48:10,117 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:48:10,117 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:48:10,117 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:48:10,117 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:48:10,117 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:48:10,117 - +2026-06-24 05:48:10,238 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:48:10,238 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:48:10,238 - Accelerator.num_process = 1 +2026-06-24 05:48:10,238 - Accelerator.mixed_precision = no +2026-06-24 05:48:10,249 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:48:10,249 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:48:10,249 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:48:10,249 - +2026-06-24 05:48:10,249 - ### System information ### +2026-06-24 05:48:10,249 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:48:10,249 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:48:10,249 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:48:10,249 - Machine: x86_64 +2026-06-24 05:48:10,249 - Processor: x86_64 +2026-06-24 05:48:10,249 - Available CPU cores: 8 +2026-06-24 05:48:10,249 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:48:10,249 - +2026-06-24 05:48:10,249 - ### GPU information ### +2026-06-24 05:48:10,249 - CUDA Available: True +2026-06-24 05:48:10,249 - CUDA Version: 13.0 +2026-06-24 05:48:10,250 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:48:10,250 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:48:10,250 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:48:10,250 - In addition, Triton does not directly support Windows. +2026-06-24 05:48:10,250 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:48:10,265 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:48:10,265 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:48:10,265 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:48:10,265 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:48:10,265 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:48:10,265 - +2026-06-24 05:48:10,265 - ### Python information ### +2026-06-24 05:48:10,266 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:48:10,266 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:48:10,266 - +2026-06-24 05:48:10,266 - ### Packages information ### +2026-06-24 05:48:10,267 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:48:10,268 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:48:10,268 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:48:10,269 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:48:10,269 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:48:10,269 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:48:10,269 - +2026-06-24 05:48:10,269 - ### Loading params file ### +2026-06-24 05:48:10,269 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000021.yaml +2026-06-24 05:48:10,276 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:48:10,277 - Success! Params file validated and defaults applied. +2026-06-24 05:48:10,277 - +2026-06-24 05:48:10,277 - ### Setting GPU Device ### +2026-06-24 05:48:10,277 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:48:10,277 - +2026-06-24 05:48:10,277 - Random seed: 20261901 provided by params file +2026-06-24 05:48:10,277 - ### Initializing Initializer ### +2026-06-24 05:48:10,278 - init_params are displayed below: +2026-06-24 05:48:10,278 - random_seed: 20261901 +2026-06-24 05:48:10,278 - probe_illum_type: electron +2026-06-24 05:48:10,278 - probe_kv: 120.0 +2026-06-24 05:48:10,278 - probe_conv_angle: 17.024240493774414 +2026-06-24 05:48:10,278 - probe_aberrations: {'C10': -217.377, 'C12': -17.754, 'phi12': 168.908, 'C21': -587.492, 'phi21': 213.492, 'C23': 823.638, 'phi23': 163.435, 'C30': 687178.375, 'C32': 8987.818, 'phi32': 71.164, 'C34': -2177.12, 'phi34': 150.609, 'C41': -303270.969, 'phi41': 272.923, 'C43': 60785.051, 'phi43': 19.796, 'C45': -320370.969, 'phi45': 287.358, 'C50': -278649888.0, 'C52': -12258240.0, 'phi52': 88.736, 'C54': 5225277.0, 'phi54': 206.25, 'C56': 16180719.0, 'phi56': 238.371} +2026-06-24 05:48:10,278 - beam_kev: None +2026-06-24 05:48:10,278 - probe_dRn: None +2026-06-24 05:48:10,278 - probe_Rn: None +2026-06-24 05:48:10,278 - probe_D_H: None +2026-06-24 05:48:10,278 - probe_D_FZP: None +2026-06-24 05:48:10,278 - probe_Ls: None +2026-06-24 05:48:10,278 - meas_Npix: 128 +2026-06-24 05:48:10,278 - pos_N_scans: 256 +2026-06-24 05:48:10,278 - pos_N_scan_slow: 16 +2026-06-24 05:48:10,278 - pos_N_scan_fast: 16 +2026-06-24 05:48:10,278 - pos_scan_step_size: 0.3114459216594696 +2026-06-24 05:48:10,278 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:48:10,278 - probe_pmode_max: 6 +2026-06-24 05:48:10,278 - probe_pmode_init_pows: [0.02] +2026-06-24 05:48:10,278 - obj_omode_max: 1 +2026-06-24 05:48:10,278 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:48:10,278 - obj_Nlayer: 1 +2026-06-24 05:48:10,278 - obj_slice_thickness: 20.0 +2026-06-24 05:48:10,278 - simu_Npix: None +2026-06-24 05:48:10,278 - simu_match_mode: None +2026-06-24 05:48:10,278 - meas_permute: None +2026-06-24 05:48:10,278 - meas_reshape: [256, 128, 128] +2026-06-24 05:48:10,278 - meas_flipT: [0, 0, 0] +2026-06-24 05:48:10,278 - meas_crop: None +2026-06-24 05:48:10,278 - meas_pad: None +2026-06-24 05:48:10,278 - meas_resample: None +2026-06-24 05:48:10,278 - meas_add_source_size: None +2026-06-24 05:48:10,278 - meas_add_detector_blur: None +2026-06-24 05:48:10,279 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:48:10,279 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:48:10,279 - meas_add_poisson_noise: None +2026-06-24 05:48:10,279 - meas_export: None +2026-06-24 05:48:10,279 - probe_permute: None +2026-06-24 05:48:10,279 - probe_z_shift: None +2026-06-24 05:48:10,279 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:48:10,279 - pos_scan_flipT: None +2026-06-24 05:48:10,279 - pos_scan_affine: None +2026-06-24 05:48:10,279 - pos_scan_rand_std: 0.15 +2026-06-24 05:48:10,279 - obj_z_crop: None +2026-06-24 05:48:10,279 - obj_z_pad: None +2026-06-24 05:48:10,279 - obj_z_resample: None +2026-06-24 05:48:10,279 - meas_source: file +2026-06-24 05:48:10,279 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000021_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:48:10,279 - probe_source: simu +2026-06-24 05:48:10,279 - probe_params: None +2026-06-24 05:48:10,279 - pos_source: simu +2026-06-24 05:48:10,279 - pos_params: None +2026-06-24 05:48:10,279 - obj_source: simu +2026-06-24 05:48:10,279 - obj_params: None +2026-06-24 05:48:10,279 - tilt_source: simu +2026-06-24 05:48:10,279 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:48:10,279 - +2026-06-24 05:48:10,279 - ### Initializing cache ### +2026-06-24 05:48:10,279 - use_cached_obj = False +2026-06-24 05:48:10,279 - use_cached_probe = False +2026-06-24 05:48:10,279 - use_cached_pos = False +2026-06-24 05:48:10,279 - +2026-06-24 05:48:10,279 - ### Initializing measurements ### +2026-06-24 05:48:10,279 - Loading measurements from source = 'file' +2026-06-24 05:48:10,279 - Detected measurement file type = '.h5' +2026-06-24 05:48:10,358 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:48:10,358 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:48:10,359 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0033) +2026-06-24 05:48:10,359 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:48:10,359 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:48:10,361 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:48:10,361 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:48:10,362 - Normalizing by max of the 2D mean pattern intensity: 0.0015551796 +2026-06-24 05:48:10,362 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:48:10,364 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0383, 2.1488) +2026-06-24 05:48:10,364 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:48:10,365 - Pattern total int. statistics (min, mean, max) = (601.9156, 627.3408, 637.4282), with min/max = 94.4% +2026-06-24 05:48:10,367 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0383, 2.1488) +2026-06-24 05:48:10,367 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:48:10,367 - +2026-06-24 05:48:10,367 - ### Setting up calibration ### +2026-06-24 05:48:10,367 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:48:10,367 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:48:10,367 - Radius of fitted bright field disk (RBF) = 12.96 px with meas_Npix = 128 +2026-06-24 05:48:10,367 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2026 +2026-06-24 05:48:10,367 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:48:10,367 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:48:10,599 - Initial guess: center=(63.57, 63.66), radius=12.96, Gaussian blur std=0.50 +2026-06-24 05:48:10,613 - Final fit: center=(63.57, 63.66), radius=12.96, Gaussian blur std=0.68 +2026-06-24 05:48:10,614 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.01 px with Npix = 128 +2026-06-24 05:48:10,614 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:48:10,614 - +2026-06-24 05:48:10,614 - ### Setting init_variables dict ### +2026-06-24 05:48:10,614 - Derived values given input init_params: +2026-06-24 05:48:10,614 - kv = 120.0 kV +2026-06-24 05:48:10,614 - wavelength = 0.0335 Ang +2026-06-24 05:48:10,614 - conv_angle = 17.024240493774414 mrad +2026-06-24 05:48:10,614 - Npix = 128 px +2026-06-24 05:48:10,614 - dk = 0.0391 Ang^-1 +2026-06-24 05:48:10,614 - kMax = 2.5000 Ang^-1 +2026-06-24 05:48:10,614 - da = 1.3083 mrad +2026-06-24 05:48:10,614 - angleMax = 83.7304 mrad +2026-06-24 05:48:10,614 - RBF = 13.0126 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:48:10,614 - n_alpha = 4.9183 (# conv_angle) +2026-06-24 05:48:10,614 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:48:10,614 - Rayleigh-limited resolution = 1.2001 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:48:10,614 - Real space probe extent = 25.6000 Ang +2026-06-24 05:48:10,614 - +2026-06-24 05:48:10,614 - ### Initializing probe ### +2026-06-24 05:48:10,614 - Loading probe from source = 'simu' +2026-06-24 05:48:10,614 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:48:10,614 - Start simulating STEM probe +2026-06-24 05:48:10,615 - kv = 120.0 kV +2026-06-24 05:48:10,615 - wavelength = 0.0335 Ang +2026-06-24 05:48:10,615 - conv_angle = 17.024240493774414 mrad +2026-06-24 05:48:10,615 - Npix = 128 px +2026-06-24 05:48:10,615 - dk = 0.0391 Ang^-1 +2026-06-24 05:48:10,615 - kMax = 2.5000 Ang^-1 +2026-06-24 05:48:10,615 - alpha_max = 83.7304 mrad +2026-06-24 05:48:10,615 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:48:10,615 - Rayleigh-limited resolution = 1.2001 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:48:10,615 - Real space probe extent = 25.6000 Ang +2026-06-24 05:48:10,615 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:48:10,615 - ------------------------------------------------------------------------------------- +2026-06-24 05:48:10,615 - C1,0 C1 -217.3770 - Defocus (C10 = -df) +2026-06-24 05:48:10,615 - C1,2 A1 -17.7540 168.91 2-fold astigmatism +2026-06-24 05:48:10,615 - C2,1 3*B2 -587.4920 213.49 Axial coma +2026-06-24 05:48:10,615 - C2,3 A2 823.6380 163.44 3-fold astigmatism +2026-06-24 05:48:10,615 - C3,0 C3 687178.3750 - Spherical aberration +2026-06-24 05:48:10,615 - C3,2 4*S3 8987.8180 71.16 Axial star aberration +2026-06-24 05:48:10,615 - C3,4 A3 -2177.1200 150.61 4-fold astigmatism +2026-06-24 05:48:10,615 - C4,1 4*B4 -303270.9690 272.92 Axial coma(4th) +2026-06-24 05:48:10,615 - C4,3 4*D4 60785.0510 19.80 3-lobe aberration +2026-06-24 05:48:10,615 - C4,5 A4 -320370.9690 287.36 5-fold astigmatism +2026-06-24 05:48:10,615 - C5,0 C5 -278649888.0000 - Spherical aberration (5th) +2026-06-24 05:48:10,615 - C5,2 6*S5 -12258240.0000 88.74 Axial star aberration(5th) +2026-06-24 05:48:10,615 - C5,4 6*R5 5225277.0000 206.25 4-lobe aberration +2026-06-24 05:48:10,615 - C5,6 A5 16180719.0000 238.37 6-fold astigmatism +2026-06-24 05:48:10,618 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:48:10,619 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:48:10,619 - Creating 5 new probe modes from the major mode +2026-06-24 05:48:10,619 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:48:10,721 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:48:10,723 - Orthogonalizing 6 pmodes +2026-06-24 05:48:10,726 - Sorting 6 pmodes by their intensities +2026-06-24 05:48:10,726 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:48:10,727 - sum(|probe_data|**2) = 627.34, while meas_total_ints (min, mean, max) = (601.9156, 627.3408, 637.4282) +2026-06-24 05:48:10,727 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:48:10,727 - +2026-06-24 05:48:10,727 - ### Initializing probe positions ### +2026-06-24 05:48:10,727 - Loading probe positions from source = 'simu' +2026-06-24 05:48:10,727 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:48:10,727 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3114, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:48:10,727 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:48:10,729 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:48:10,729 - crop_pos 1st and last px coords (y,x) = ([15, 15], [39, 38]) +2026-06-24 05:48:10,729 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 05:48:10,730 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:48:10,730 - +2026-06-24 05:48:10,730 - ### Initializing object ### +2026-06-24 05:48:10,730 - Loading object from source = 'simu' +2026-06-24 05:48:10,730 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:48:10,731 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:48:10,731 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 182, 183) +2026-06-24 05:48:10,731 - object extent (Z, Y, X) (Ang) = [20. 36.4 36.6] +2026-06-24 05:48:10,731 - +2026-06-24 05:48:10,731 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:48:10,731 - omode_occu (omode) = float32, (1,) +2026-06-24 05:48:10,731 - +2026-06-24 05:48:10,731 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:48:10,731 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 05:48:10,732 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:48:10,732 - +2026-06-24 05:48:10,732 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:48:10,732 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:48:10,732 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:48:10,732 - +2026-06-24 05:48:10,732 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:48:10,732 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:48:10,732 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:48:10,732 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:48:10,732 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:48:10,733 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (182, 183). +2026-06-24 05:48:10,733 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:48:10,733 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:48:10,733 - +2026-06-24 05:48:10,733 - ### Collecting reconstruction provenance ### +2026-06-24 05:48:10,733 - Reconstruction provenance is collected and initialized. +2026-06-24 05:48:10,733 - +2026-06-24 05:48:10,733 - ### Initializing loss function ### +2026-06-24 05:48:10,733 - Active loss types: +2026-06-24 05:48:10,733 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:48:10,733 - +2026-06-24 05:48:10,733 - ### Initializing constraint function ### +2026-06-24 05:48:10,733 - Active constraint types: +2026-06-24 05:48:10,733 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:48:10,733 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:48:10,733 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:48:10,733 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:48:10,733 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:48:10,733 - +2026-06-24 05:48:10,733 - ### Done initializing PtyRADSolver ### +2026-06-24 05:48:10,733 - +2026-06-24 05:48:10,859 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:48:10,859 - +2026-06-24 05:48:10,860 - ### Initializing PtychoModel model ### +2026-06-24 05:48:10,930 - ### PtychoModel optimizable variables ### +2026-06-24 05:48:10,931 - obja : torch.Size([1, 1, 182, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:10,931 - objp : torch.Size([1, 1, 182, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:10,931 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:48:10,931 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:48:10,931 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:48:10,931 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:10,931 - +2026-06-24 05:48:10,931 - ### Optimizable variables statitsics ### +2026-06-24 05:48:10,931 - Total measurement values : 4,194,304 +2026-06-24 05:48:10,931 - Total optimizing variables: 263,732 +2026-06-24 05:48:10,931 - Overdetermined ratio : 15.90 +2026-06-24 05:48:10,931 - +2026-06-24 05:48:10,931 - ### Model behavior ### +2026-06-24 05:48:10,931 - Tilt propagator : False +2026-06-24 05:48:10,931 - Change slice thickness : False +2026-06-24 05:48:10,931 - Detector blur : False +2026-06-24 05:48:10,931 - Preload data : True +2026-06-24 05:48:10,931 - On-the-fly meas padding : False +2026-06-24 05:48:10,931 - On-the-fly meas resample : False +2026-06-24 05:48:10,931 - On-the-fly simu match mode: None +2026-06-24 05:48:10,931 - +2026-06-24 05:48:10,973 - ### Done initializing PtychoModel model ### +2026-06-24 05:48:10,973 - +2026-06-24 05:48:10,973 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:48:10,973 - +2026-06-24 05:48:10,973 - ### Generating indices, batches, and output_path ### +2026-06-24 05:48:10,975 - d90 = 29.000 px or 5.800 Ang +2026-06-24 05:48:10,975 - Selecting indices with the 'full' mode +2026-06-24 05:48:11,433 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:48:11,517 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:48:11,517 - Original recon_dir_affixes = ['default'] +2026-06-24 05:48:11,517 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:48:11,524 - Path corrected for compatibility: +2026-06-24 05:48:11,524 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8.99e+03_phi32_71.2_C34_-2.18e+03_phi34_151_C41_-3.03e+05_phi41_273_C43_6.08e+04_phi43_19.8_C45_-3.2e+05_phi45_287_C50_-2.79e+08_C52_-1.23e+07_phi52_88.7_C54_5.23e+06_phi54_206_C56_1.62e+07_phi56_238 +2026-06-24 05:48:11,524 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8..62e+07_phi56_238 +2026-06-24 05:48:11,525 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8..62e+07_phi56_238' is generated! +2026-06-24 05:48:11,688 - +2026-06-24 05:48:11,689 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8..62e+07_phi56_238/20260624_054811_ptyrad_log.txt ### +2026-06-24 05:48:11,689 - +2026-06-24 05:48:11,691 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:48:11,691 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:48:11,691 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:48:12,873 - Iter: 1, Total Loss: 1.0227, loss_single: 1.0227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:48:12,910 - Iter: 2, Total Loss: 1.0037, loss_single: 1.0037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:48:12,946 - Iter: 3, Total Loss: 0.9865, loss_single: 0.9865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:12,981 - Iter: 4, Total Loss: 0.9676, loss_single: 0.9676, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,016 - Iter: 5, Total Loss: 0.9535, loss_single: 0.9535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,051 - Iter: 6, Total Loss: 0.9411, loss_single: 0.9411, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,086 - Iter: 7, Total Loss: 0.9266, loss_single: 0.9266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,121 - Iter: 8, Total Loss: 0.9127, loss_single: 0.9127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,156 - Iter: 9, Total Loss: 0.8969, loss_single: 0.8969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,191 - Iter: 10, Total Loss: 0.8829, loss_single: 0.8829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,226 - Iter: 11, Total Loss: 0.8696, loss_single: 0.8696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,262 - Iter: 12, Total Loss: 0.8538, loss_single: 0.8538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:48:13,297 - Iter: 13, Total Loss: 0.8389, loss_single: 0.8389, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,333 - Iter: 14, Total Loss: 0.8268, loss_single: 0.8268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,367 - Iter: 15, Total Loss: 0.8147, loss_single: 0.8147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,402 - Iter: 16, Total Loss: 0.8005, loss_single: 0.8005, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,438 - Iter: 17, Total Loss: 0.7861, loss_single: 0.7861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,473 - Iter: 18, Total Loss: 0.7713, loss_single: 0.7713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,508 - Iter: 19, Total Loss: 0.7574, loss_single: 0.7574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,543 - Iter: 20, Total Loss: 0.7455, loss_single: 0.7455, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,578 - Iter: 21, Total Loss: 0.7348, loss_single: 0.7348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,613 - Iter: 22, Total Loss: 0.7242, loss_single: 0.7242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,648 - Iter: 23, Total Loss: 0.7139, loss_single: 0.7139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,683 - Iter: 24, Total Loss: 0.7036, loss_single: 0.7036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,718 - Iter: 25, Total Loss: 0.6930, loss_single: 0.6930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,753 - Iter: 26, Total Loss: 0.6834, loss_single: 0.6834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,788 - Iter: 27, Total Loss: 0.6741, loss_single: 0.6741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,823 - Iter: 28, Total Loss: 0.6628, loss_single: 0.6628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,858 - Iter: 29, Total Loss: 0.6499, loss_single: 0.6499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,894 - Iter: 30, Total Loss: 0.6367, loss_single: 0.6367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:13,928 - Iter: 31, Total Loss: 0.6254, loss_single: 0.6254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,963 - Iter: 32, Total Loss: 0.6171, loss_single: 0.6171, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:13,998 - Iter: 33, Total Loss: 0.6093, loss_single: 0.6093, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,033 - Iter: 34, Total Loss: 0.6010, loss_single: 0.6010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,068 - Iter: 35, Total Loss: 0.5939, loss_single: 0.5939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,103 - Iter: 36, Total Loss: 0.5880, loss_single: 0.5880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,138 - Iter: 37, Total Loss: 0.5820, loss_single: 0.5820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,173 - Iter: 38, Total Loss: 0.5763, loss_single: 0.5763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,208 - Iter: 39, Total Loss: 0.5700, loss_single: 0.5700, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,243 - Iter: 40, Total Loss: 0.5639, loss_single: 0.5639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,280 - Iter: 41, Total Loss: 0.5582, loss_single: 0.5582, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,315 - Iter: 42, Total Loss: 0.5523, loss_single: 0.5523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,350 - Iter: 43, Total Loss: 0.5472, loss_single: 0.5472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,385 - Iter: 44, Total Loss: 0.5425, loss_single: 0.5425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,420 - Iter: 45, Total Loss: 0.5380, loss_single: 0.5380, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,456 - Iter: 46, Total Loss: 0.5335, loss_single: 0.5335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,490 - Iter: 47, Total Loss: 0.5288, loss_single: 0.5288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,526 - Iter: 48, Total Loss: 0.5240, loss_single: 0.5240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,561 - Iter: 49, Total Loss: 0.5200, loss_single: 0.5200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,596 - Iter: 50, Total Loss: 0.5174, loss_single: 0.5174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,631 - Iter: 51, Total Loss: 0.5154, loss_single: 0.5154, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,666 - Iter: 52, Total Loss: 0.5126, loss_single: 0.5126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,701 - Iter: 53, Total Loss: 0.5095, loss_single: 0.5095, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,736 - Iter: 54, Total Loss: 0.5065, loss_single: 0.5065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,771 - Iter: 55, Total Loss: 0.5041, loss_single: 0.5041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,805 - Iter: 56, Total Loss: 0.5019, loss_single: 0.5019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,840 - Iter: 57, Total Loss: 0.4995, loss_single: 0.4995, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,876 - Iter: 58, Total Loss: 0.4973, loss_single: 0.4973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,911 - Iter: 59, Total Loss: 0.4950, loss_single: 0.4950, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:14,945 - Iter: 60, Total Loss: 0.4927, loss_single: 0.4927, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:14,980 - Iter: 61, Total Loss: 0.4907, loss_single: 0.4907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,016 - Iter: 62, Total Loss: 0.4888, loss_single: 0.4888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,050 - Iter: 63, Total Loss: 0.4870, loss_single: 0.4870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:15,086 - Iter: 64, Total Loss: 0.4855, loss_single: 0.4855, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,121 - Iter: 65, Total Loss: 0.4841, loss_single: 0.4841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:15,155 - Iter: 66, Total Loss: 0.4832, loss_single: 0.4832, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:15,191 - Iter: 67, Total Loss: 0.4824, loss_single: 0.4824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,226 - Iter: 68, Total Loss: 0.4815, loss_single: 0.4815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:15,261 - Iter: 69, Total Loss: 0.4808, loss_single: 0.4808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,296 - Iter: 70, Total Loss: 0.4802, loss_single: 0.4802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,331 - Iter: 71, Total Loss: 0.4795, loss_single: 0.4795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,366 - Iter: 72, Total Loss: 0.4788, loss_single: 0.4788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,401 - Iter: 73, Total Loss: 0.4782, loss_single: 0.4782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,437 - Iter: 74, Total Loss: 0.4777, loss_single: 0.4777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:15,472 - Iter: 75, Total Loss: 0.4772, loss_single: 0.4772, loss_poissn: 0.0000, loss_pacbed: 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0.4693, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:16,315 - Iter: 99, Total Loss: 0.4691, loss_single: 0.4691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:16,350 - Iter: 100, Total Loss: 0.4689, loss_single: 0.4689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:16,461 - Saving summary figures for iter 100 +2026-06-24 05:48:20,219 - ### Finished 100 iterations, averaged iter_t = 0.038667 with std = 0.040 ### +2026-06-24 05:48:20,219 - +2026-06-24 05:48:20,220 - ### The PtyRADSolver is finished in 9.360 sec ### +2026-06-24 05:48:20,220 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000021/c30_small__simulation_data2__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-217_C12_-17.8_phi12_169_C21_-587_phi21_213_C23_824_phi23_163_C30_6.87e+05_C32_8..62e+07_phi56_238/simulation_data2__sample_000021.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 17.024240493774414 + probe_aberrations: + C10: -217.37734985351562 + C12: -17.754117965698242 + C21: -587.4920043945312 + C23: 823.638427734375 + C30: 687178.375 + C32: 8987.818359375 + C34: -2177.119873046875 + C41: -303270.96875 + C43: 60785.05078125 + C45: -320370.96875 + C50: -278649888.0 + C52: -12258240.0 + C54: 5225277.0 + C56: 16180719.0 + phi12: 168.9080100232874 + phi21: 213.49242500038247 + phi23: 163.43458329038432 + phi32: 71.16443081146902 + phi34: 150.6094687839597 + phi41: 272.92321236498407 + phi43: 19.79635732808191 + phi45: 287.3575604209987 + phi52: 88.73562520608209 + phi54: 206.24969240450096 + phi56: 238.3710065615604 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3114459216594696 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000021_measurement.h5 + key: measurement + random_seed: 20261901 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:2bd2a443cfd5a44a97039002433a4206fe4b0d3ea1667188b9025c5e7af144f3 +size 50373 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/20260624_054855_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/20260624_054855_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..34269200eba1030f7d383c5c49557f781507b420 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/20260624_054855_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:48:54,037 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:48:54,038 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:48:54,038 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:48:54,038 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:48:54,038 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:48:54,038 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:48:54,038 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:48:54,038 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:48:54,038 - +2026-06-24 05:48:54,144 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:48:54,144 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:48:54,144 - Accelerator.num_process = 1 +2026-06-24 05:48:54,144 - Accelerator.mixed_precision = no +2026-06-24 05:48:54,154 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:48:54,155 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:48:54,155 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:48:54,155 - +2026-06-24 05:48:54,155 - ### System information ### +2026-06-24 05:48:54,155 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:48:54,155 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:48:54,155 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:48:54,155 - Machine: x86_64 +2026-06-24 05:48:54,155 - Processor: x86_64 +2026-06-24 05:48:54,155 - Available CPU cores: 8 +2026-06-24 05:48:54,155 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:48:54,155 - +2026-06-24 05:48:54,155 - ### GPU information ### +2026-06-24 05:48:54,155 - CUDA Available: True +2026-06-24 05:48:54,155 - CUDA Version: 13.0 +2026-06-24 05:48:54,156 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:48:54,156 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:48:54,156 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:48:54,156 - In addition, Triton does not directly support Windows. +2026-06-24 05:48:54,156 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:48:54,171 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:48:54,171 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:48:54,171 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:48:54,171 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:48:54,171 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:48:54,171 - +2026-06-24 05:48:54,171 - ### Python information ### +2026-06-24 05:48:54,173 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:48:54,173 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:48:54,173 - +2026-06-24 05:48:54,173 - ### Packages information ### +2026-06-24 05:48:54,174 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:48:54,175 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:48:54,175 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:48:54,176 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:48:54,176 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:48:54,176 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:48:54,176 - +2026-06-24 05:48:54,177 - ### Loading params file ### +2026-06-24 05:48:54,177 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000024.yaml +2026-06-24 05:48:54,183 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:48:54,184 - Success! Params file validated and defaults applied. +2026-06-24 05:48:54,184 - +2026-06-24 05:48:54,184 - ### Setting GPU Device ### +2026-06-24 05:48:54,184 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:48:54,184 - +2026-06-24 05:48:54,184 - Random seed: 20261904 provided by params file +2026-06-24 05:48:54,185 - ### Initializing Initializer ### +2026-06-24 05:48:54,185 - init_params are displayed below: +2026-06-24 05:48:54,185 - random_seed: 20261904 +2026-06-24 05:48:54,185 - probe_illum_type: electron +2026-06-24 05:48:54,185 - probe_kv: 160.0 +2026-06-24 05:48:54,185 - probe_conv_angle: 10.219306945800781 +2026-06-24 05:48:54,185 - probe_aberrations: {'C10': -191.978, 'C12': 27.964, 'phi12': 214.566, 'C21': 104.36, 'phi21': 32.793, 'C23': -809.282, 'phi23': 222.914, 'C30': -288385.25, 'C32': -1067.755, 'phi32': 55.023, 'C34': -5927.381, 'phi34': 11.837, 'C41': 30657.521, 'phi41': 43.218, 'C43': -257512.484, 'phi43': 189.811, 'C45': 429456.906, 'phi45': 164.326, 'C50': 104213408.0, 'C52': 15232683.0, 'phi52': 137.131, 'C54': -5335755.5, 'phi54': 270.566, 'C56': -573197.375, 'phi56': 332.636} +2026-06-24 05:48:54,185 - beam_kev: None +2026-06-24 05:48:54,185 - probe_dRn: None +2026-06-24 05:48:54,185 - probe_Rn: None +2026-06-24 05:48:54,185 - probe_D_H: None +2026-06-24 05:48:54,185 - probe_D_FZP: None +2026-06-24 05:48:54,185 - probe_Ls: None +2026-06-24 05:48:54,185 - meas_Npix: 128 +2026-06-24 05:48:54,185 - pos_N_scans: 256 +2026-06-24 05:48:54,185 - pos_N_scan_slow: 16 +2026-06-24 05:48:54,185 - pos_N_scan_fast: 16 +2026-06-24 05:48:54,185 - pos_scan_step_size: 0.3086661398410797 +2026-06-24 05:48:54,185 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:48:54,185 - probe_pmode_max: 6 +2026-06-24 05:48:54,185 - probe_pmode_init_pows: [0.02] +2026-06-24 05:48:54,185 - obj_omode_max: 1 +2026-06-24 05:48:54,185 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:48:54,185 - obj_Nlayer: 1 +2026-06-24 05:48:54,185 - obj_slice_thickness: 20.0 +2026-06-24 05:48:54,185 - simu_Npix: None +2026-06-24 05:48:54,185 - simu_match_mode: None +2026-06-24 05:48:54,185 - meas_permute: None +2026-06-24 05:48:54,185 - meas_reshape: [256, 128, 128] +2026-06-24 05:48:54,185 - meas_flipT: [0, 0, 0] +2026-06-24 05:48:54,186 - meas_crop: None +2026-06-24 05:48:54,186 - meas_pad: None +2026-06-24 05:48:54,186 - meas_resample: None +2026-06-24 05:48:54,186 - meas_add_source_size: None +2026-06-24 05:48:54,186 - meas_add_detector_blur: None +2026-06-24 05:48:54,186 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:48:54,186 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:48:54,186 - meas_add_poisson_noise: None +2026-06-24 05:48:54,186 - meas_export: None +2026-06-24 05:48:54,186 - probe_permute: None +2026-06-24 05:48:54,186 - probe_z_shift: None +2026-06-24 05:48:54,186 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:48:54,186 - pos_scan_flipT: None +2026-06-24 05:48:54,186 - pos_scan_affine: None +2026-06-24 05:48:54,186 - pos_scan_rand_std: 0.15 +2026-06-24 05:48:54,186 - obj_z_crop: None +2026-06-24 05:48:54,186 - obj_z_pad: None +2026-06-24 05:48:54,186 - obj_z_resample: None +2026-06-24 05:48:54,186 - meas_source: file +2026-06-24 05:48:54,186 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000024_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:48:54,186 - probe_source: simu +2026-06-24 05:48:54,186 - probe_params: None +2026-06-24 05:48:54,186 - pos_source: simu +2026-06-24 05:48:54,186 - pos_params: None +2026-06-24 05:48:54,186 - obj_source: simu +2026-06-24 05:48:54,186 - obj_params: None +2026-06-24 05:48:54,186 - tilt_source: simu +2026-06-24 05:48:54,186 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:48:54,186 - +2026-06-24 05:48:54,186 - ### Initializing cache ### +2026-06-24 05:48:54,186 - use_cached_obj = False +2026-06-24 05:48:54,186 - use_cached_probe = False +2026-06-24 05:48:54,186 - use_cached_pos = False +2026-06-24 05:48:54,186 - +2026-06-24 05:48:54,186 - ### Initializing measurements ### +2026-06-24 05:48:54,186 - Loading measurements from source = 'file' +2026-06-24 05:48:54,186 - Detected measurement file type = '.h5' +2026-06-24 05:48:54,264 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:48:54,264 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:48:54,266 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0042) +2026-06-24 05:48:54,266 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:48:54,266 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:48:54,268 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:48:54,268 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:48:54,268 - Normalizing by max of the 2D mean pattern intensity: 0.0034439741 +2026-06-24 05:48:54,269 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:48:54,270 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.2338) +2026-06-24 05:48:54,271 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:48:54,272 - Pattern total int. statistics (min, mean, max) = (279.7454, 287.6030, 291.3616), with min/max = 96.0% +2026-06-24 05:48:54,273 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.2338) +2026-06-24 05:48:54,273 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:48:54,273 - +2026-06-24 05:48:54,273 - ### Setting up calibration ### +2026-06-24 05:48:54,273 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:48:54,273 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:48:54,273 - Radius of fitted bright field disk (RBF) = 9.08 px with meas_Npix = 128 +2026-06-24 05:48:54,273 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1419 +2026-06-24 05:48:54,273 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:48:54,273 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:48:54,492 - Initial guess: center=(63.61, 63.62), radius=9.08, Gaussian blur std=0.50 +2026-06-24 05:48:54,504 - Final fit: center=(63.61, 63.62), radius=9.08, Gaussian blur std=0.69 +2026-06-24 05:48:54,504 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.18 px with Npix = 128 +2026-06-24 05:48:54,504 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:48:54,504 - +2026-06-24 05:48:54,504 - ### Setting init_variables dict ### +2026-06-24 05:48:54,504 - Derived values given input init_params: +2026-06-24 05:48:54,504 - kv = 160.0 kV +2026-06-24 05:48:54,504 - wavelength = 0.0285 Ang +2026-06-24 05:48:54,504 - conv_angle = 10.219306945800781 mrad +2026-06-24 05:48:54,505 - Npix = 128 px +2026-06-24 05:48:54,505 - dk = 0.0391 Ang^-1 +2026-06-24 05:48:54,505 - kMax = 2.5000 Ang^-1 +2026-06-24 05:48:54,505 - da = 1.1137 mrad +2026-06-24 05:48:54,505 - angleMax = 71.2751 mrad +2026-06-24 05:48:54,505 - RBF = 9.1762 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:48:54,505 - n_alpha = 6.9746 (# conv_angle) +2026-06-24 05:48:54,505 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:48:54,505 - Rayleigh-limited resolution = 1.7018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:48:54,505 - Real space probe extent = 25.6000 Ang +2026-06-24 05:48:54,505 - +2026-06-24 05:48:54,505 - ### Initializing probe ### +2026-06-24 05:48:54,505 - Loading probe from source = 'simu' +2026-06-24 05:48:54,505 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:48:54,505 - Start simulating STEM probe +2026-06-24 05:48:54,505 - kv = 160.0 kV +2026-06-24 05:48:54,505 - wavelength = 0.0285 Ang +2026-06-24 05:48:54,505 - conv_angle = 10.219306945800781 mrad +2026-06-24 05:48:54,505 - Npix = 128 px +2026-06-24 05:48:54,505 - dk = 0.0391 Ang^-1 +2026-06-24 05:48:54,505 - kMax = 2.5000 Ang^-1 +2026-06-24 05:48:54,505 - alpha_max = 71.2751 mrad +2026-06-24 05:48:54,505 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:48:54,505 - Rayleigh-limited resolution = 1.7018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:48:54,505 - Real space probe extent = 25.6000 Ang +2026-06-24 05:48:54,506 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:48:54,506 - ------------------------------------------------------------------------------------ +2026-06-24 05:48:54,506 - C1,0 C1 -191.9780 - Defocus (C10 = -df) +2026-06-24 05:48:54,506 - C1,2 A1 27.9640 214.57 2-fold astigmatism +2026-06-24 05:48:54,506 - C2,1 3*B2 104.3600 32.79 Axial coma +2026-06-24 05:48:54,506 - C2,3 A2 -809.2820 222.91 3-fold astigmatism +2026-06-24 05:48:54,506 - C3,0 C3 -288385.2500 - Spherical aberration +2026-06-24 05:48:54,506 - C3,2 4*S3 -1067.7550 55.02 Axial star aberration +2026-06-24 05:48:54,506 - C3,4 A3 -5927.3810 11.84 4-fold astigmatism +2026-06-24 05:48:54,506 - C4,1 4*B4 30657.5210 43.22 Axial coma(4th) +2026-06-24 05:48:54,506 - C4,3 4*D4 -257512.4840 189.81 3-lobe aberration +2026-06-24 05:48:54,506 - C4,5 A4 429456.9060 164.33 5-fold astigmatism +2026-06-24 05:48:54,506 - C5,0 C5 104213408.0000 - Spherical aberration (5th) +2026-06-24 05:48:54,506 - C5,2 6*S5 15232683.0000 137.13 Axial star aberration(5th) +2026-06-24 05:48:54,506 - C5,4 6*R5 -5335755.5000 270.57 4-lobe aberration +2026-06-24 05:48:54,506 - C5,6 A5 -573197.3750 332.64 6-fold astigmatism +2026-06-24 05:48:54,509 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:48:54,509 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:48:54,509 - Creating 5 new probe modes from the major mode +2026-06-24 05:48:54,509 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:48:54,611 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:48:54,612 - Orthogonalizing 6 pmodes +2026-06-24 05:48:54,614 - Sorting 6 pmodes by their intensities +2026-06-24 05:48:54,615 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:48:54,615 - sum(|probe_data|**2) = 287.60, while meas_total_ints (min, mean, max) = (279.7454, 287.6030, 291.3616) +2026-06-24 05:48:54,615 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:48:54,616 - +2026-06-24 05:48:54,616 - ### Initializing probe positions ### +2026-06-24 05:48:54,616 - Loading probe positions from source = 'simu' +2026-06-24 05:48:54,616 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:48:54,616 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3087, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:48:54,616 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:48:54,618 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:48:54,618 - crop_pos 1st and last px coords (y,x) = ([15, 16], [39, 39]) +2026-06-24 05:48:54,618 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 05:48:54,618 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:48:54,618 - +2026-06-24 05:48:54,618 - ### Initializing object ### +2026-06-24 05:48:54,618 - Loading object from source = 'simu' +2026-06-24 05:48:54,618 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:48:54,619 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:48:54,620 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 182, 182) +2026-06-24 05:48:54,620 - object extent (Z, Y, X) (Ang) = [20. 36.4 36.4] +2026-06-24 05:48:54,620 - +2026-06-24 05:48:54,620 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:48:54,620 - omode_occu (omode) = float32, (1,) +2026-06-24 05:48:54,620 - +2026-06-24 05:48:54,620 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:48:54,620 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:48:54,621 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:48:54,621 - +2026-06-24 05:48:54,621 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:48:54,621 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:48:54,621 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:48:54,621 - +2026-06-24 05:48:54,621 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:48:54,621 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:48:54,621 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:48:54,621 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:48:54,621 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:48:54,621 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (182, 182). +2026-06-24 05:48:54,621 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:48:54,621 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:48:54,621 - +2026-06-24 05:48:54,621 - ### Collecting reconstruction provenance ### +2026-06-24 05:48:54,621 - Reconstruction provenance is collected and initialized. +2026-06-24 05:48:54,621 - +2026-06-24 05:48:54,621 - ### Initializing loss function ### +2026-06-24 05:48:54,621 - Active loss types: +2026-06-24 05:48:54,622 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:48:54,622 - +2026-06-24 05:48:54,622 - ### Initializing constraint function ### +2026-06-24 05:48:54,622 - Active constraint types: +2026-06-24 05:48:54,622 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:48:54,622 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:48:54,622 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:48:54,622 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:48:54,622 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:48:54,622 - +2026-06-24 05:48:54,622 - ### Done initializing PtyRADSolver ### +2026-06-24 05:48:54,622 - +2026-06-24 05:48:54,746 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:48:54,746 - +2026-06-24 05:48:54,746 - ### Initializing PtychoModel model ### +2026-06-24 05:48:54,816 - ### PtychoModel optimizable variables ### +2026-06-24 05:48:54,817 - obja : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:54,817 - objp : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:54,817 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:48:54,817 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:48:54,817 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:48:54,817 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:48:54,817 - +2026-06-24 05:48:54,817 - ### Optimizable variables statitsics ### +2026-06-24 05:48:54,817 - Total measurement values : 4,194,304 +2026-06-24 05:48:54,817 - Total optimizing variables: 263,368 +2026-06-24 05:48:54,817 - Overdetermined ratio : 15.93 +2026-06-24 05:48:54,817 - +2026-06-24 05:48:54,817 - ### Model behavior ### +2026-06-24 05:48:54,817 - Tilt propagator : False +2026-06-24 05:48:54,817 - Change slice thickness : False +2026-06-24 05:48:54,817 - Detector blur : False +2026-06-24 05:48:54,817 - Preload data : True +2026-06-24 05:48:54,817 - On-the-fly meas padding : False +2026-06-24 05:48:54,817 - On-the-fly meas resample : False +2026-06-24 05:48:54,817 - On-the-fly simu match mode: None +2026-06-24 05:48:54,817 - +2026-06-24 05:48:54,859 - ### Done initializing PtychoModel model ### +2026-06-24 05:48:54,859 - +2026-06-24 05:48:54,860 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:48:54,860 - +2026-06-24 05:48:54,860 - ### Generating indices, batches, and output_path ### +2026-06-24 05:48:54,861 - d90 = 39.000 px or 7.800 Ang +2026-06-24 05:48:54,861 - Selecting indices with the 'full' mode +2026-06-24 05:48:55,319 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:48:55,408 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:48:55,408 - Original recon_dir_affixes = ['default'] +2026-06-24 05:48:55,408 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:48:55,414 - Path corrected for compatibility: +2026-06-24 05:48:55,414 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1.07e+03_phi32_55_C34_-5.93e+03_phi34_11.8_C41_3.07e+04_phi41_43.2_C43_-2.58e+05_phi43_190_C45_4.29e+05_phi45_164_C50_1.04e+08_C52_1.52e+07_phi52_137_C54_-5.34e+06_phi54_271_C56_-5.73e+05_phi56_333 +2026-06-24 05:48:55,414 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333 +2026-06-24 05:48:55,415 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333' is generated! +2026-06-24 05:48:55,583 - +2026-06-24 05:48:55,583 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/20260624_054855_ptyrad_log.txt ### +2026-06-24 05:48:55,584 - +2026-06-24 05:48:55,585 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:48:55,585 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:48:55,585 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:48:56,778 - Iter: 1, Total Loss: 1.0829, loss_single: 1.0829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 05:48:56,814 - Iter: 2, Total Loss: 1.0436, loss_single: 1.0436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:48:56,850 - Iter: 3, Total Loss: 1.0103, loss_single: 1.0103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:56,885 - Iter: 4, Total Loss: 0.9794, loss_single: 0.9794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:56,921 - Iter: 5, Total Loss: 0.9480, loss_single: 0.9480, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:56,957 - Iter: 6, Total Loss: 0.9208, loss_single: 0.9208, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:48:56,992 - Iter: 7, Total Loss: 0.8954, loss_single: 0.8954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,028 - Iter: 8, Total Loss: 0.8683, loss_single: 0.8683, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,063 - Iter: 9, Total Loss: 0.8428, loss_single: 0.8428, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,099 - Iter: 10, Total Loss: 0.8163, loss_single: 0.8163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,134 - Iter: 11, Total Loss: 0.7907, loss_single: 0.7907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:57,169 - Iter: 12, Total Loss: 0.7660, loss_single: 0.7660, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,204 - Iter: 13, Total Loss: 0.7409, loss_single: 0.7409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,239 - Iter: 14, Total Loss: 0.7144, loss_single: 0.7144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:57,274 - Iter: 15, Total Loss: 0.6925, loss_single: 0.6925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,309 - Iter: 16, Total Loss: 0.6723, loss_single: 0.6723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,344 - Iter: 17, Total Loss: 0.6456, loss_single: 0.6456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,379 - Iter: 18, Total Loss: 0.6162, loss_single: 0.6162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,414 - Iter: 19, Total Loss: 0.5898, loss_single: 0.5898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,449 - Iter: 20, Total Loss: 0.5667, loss_single: 0.5667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:48:57,484 - Iter: 21, Total Loss: 0.5445, loss_single: 0.5445, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,519 - Iter: 22, Total Loss: 0.5223, loss_single: 0.5223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,555 - Iter: 23, Total Loss: 0.5011, loss_single: 0.5011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:48:57,590 - Iter: 24, Total Loss: 0.4822, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/simulation_data2__sample_000024.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/simulation_data2__sample_000024.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b4773a0b538580ab857f89af0b5d95053f5f59f6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/simulation_data2__sample_000024.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 10.219306945800781 + probe_aberrations: + C10: -191.9779510498047 + C12: 27.963590621948242 + C21: 104.35951232910156 + C23: -809.2821655273438 + C30: -288385.25 + C32: -1067.7548828125 + C34: -5927.38134765625 + C41: 30657.521484375 + C43: -257512.484375 + C45: 429456.90625 + C50: 104213408.0 + C52: 15232683.0 + C54: -5335755.5 + C56: -573197.375 + phi12: 214.5664039454753 + phi21: 32.79309058268688 + phi23: 222.91385133771468 + phi32: 55.02315701016564 + phi34: 11.836530855203568 + phi41: 43.21753019963544 + phi43: 189.8110116761677 + phi45: 164.32636010917787 + phi52: 137.1311832872067 + phi54: 270.5659228371159 + phi56: 332.63600458003714 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3086661398410797 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000024_measurement.h5 + key: measurement + random_seed: 20261904 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6e64b551db1977a0d1a823645f89f971885fa299d2d203e6c32ba6bd993a5dd6 +size 1089560 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000024/c30_small__simulation_data2__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-192_C12_28_phi12_215_C21_104_phi21_32.8_C23_-809_phi23_223_C30_-2.88e+05_C32_-1..73e+05_phi56_333/summary_scan_pos_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/20260624_055053_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:50:52,060 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:50:52,060 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:50:52,060 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:50:52,060 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:50:52,060 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:50:52,060 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:50:52,060 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:50:52,060 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:50:52,060 - +2026-06-24 05:50:52,169 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:50:52,169 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:50:52,169 - Accelerator.num_process = 1 +2026-06-24 05:50:52,169 - Accelerator.mixed_precision = no +2026-06-24 05:50:52,180 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:50:52,180 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:50:52,180 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:50:52,180 - +2026-06-24 05:50:52,180 - ### System information ### +2026-06-24 05:50:52,180 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:50:52,180 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:50:52,180 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:50:52,180 - Machine: x86_64 +2026-06-24 05:50:52,180 - Processor: x86_64 +2026-06-24 05:50:52,180 - Available CPU cores: 8 +2026-06-24 05:50:52,180 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:50:52,181 - +2026-06-24 05:50:52,181 - ### GPU information ### +2026-06-24 05:50:52,181 - CUDA Available: True +2026-06-24 05:50:52,181 - CUDA Version: 13.0 +2026-06-24 05:50:52,181 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:50:52,181 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:50:52,181 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:50:52,181 - In addition, Triton does not directly support Windows. +2026-06-24 05:50:52,181 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:50:52,196 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:50:52,196 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:50:52,196 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:50:52,196 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:50:52,196 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:50:52,196 - +2026-06-24 05:50:52,196 - ### Python information ### +2026-06-24 05:50:52,198 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:50:52,198 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:50:52,198 - +2026-06-24 05:50:52,198 - ### Packages information ### +2026-06-24 05:50:52,199 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:50:52,200 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:50:52,200 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:50:52,201 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:50:52,201 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:50:52,201 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:50:52,201 - +2026-06-24 05:50:52,201 - ### Loading params file ### +2026-06-24 05:50:52,201 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000032.yaml +2026-06-24 05:50:52,208 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:50:52,209 - Success! Params file validated and defaults applied. +2026-06-24 05:50:52,209 - +2026-06-24 05:50:52,209 - ### Setting GPU Device ### +2026-06-24 05:50:52,209 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:50:52,209 - +2026-06-24 05:50:52,209 - Random seed: 20261912 provided by params file +2026-06-24 05:50:52,209 - ### Initializing Initializer ### +2026-06-24 05:50:52,210 - init_params are displayed below: +2026-06-24 05:50:52,210 - random_seed: 20261912 +2026-06-24 05:50:52,210 - probe_illum_type: electron +2026-06-24 05:50:52,210 - probe_kv: 30.0 +2026-06-24 05:50:52,210 - probe_conv_angle: 12.94440746307373 +2026-06-24 05:50:52,210 - probe_aberrations: {'C10': -460.214, 'C12': -11.701, 'phi12': 63.871, 'C21': -130.418, 'phi21': 348.744, 'C23': -977.027, 'phi23': 161.485, 'C30': 1922825.5, 'C32': -8678.406, 'phi32': 293.385, 'C34': -10483.401, 'phi34': 264.53, 'C41': -371409.688, 'phi41': 194.076, 'C43': -130966.594, 'phi43': 43.92, 'C45': 258425.312, 'phi45': 88.792, 'C50': 207998128.0, 'C52': -15980148.0, 'phi52': 255.439, 'C54': -5412235.5, 'phi54': 126.539, 'C56': 19671308.0, 'phi56': 139.216} +2026-06-24 05:50:52,210 - beam_kev: None +2026-06-24 05:50:52,210 - probe_dRn: None +2026-06-24 05:50:52,210 - probe_Rn: None +2026-06-24 05:50:52,210 - probe_D_H: None +2026-06-24 05:50:52,210 - probe_D_FZP: None +2026-06-24 05:50:52,210 - probe_Ls: None +2026-06-24 05:50:52,210 - meas_Npix: 128 +2026-06-24 05:50:52,210 - pos_N_scans: 256 +2026-06-24 05:50:52,210 - pos_N_scan_slow: 16 +2026-06-24 05:50:52,210 - pos_N_scan_fast: 16 +2026-06-24 05:50:52,210 - pos_scan_step_size: 0.30775824189186096 +2026-06-24 05:50:52,210 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:50:52,210 - probe_pmode_max: 6 +2026-06-24 05:50:52,210 - probe_pmode_init_pows: [0.02] +2026-06-24 05:50:52,210 - obj_omode_max: 1 +2026-06-24 05:50:52,210 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:50:52,210 - obj_Nlayer: 1 +2026-06-24 05:50:52,210 - obj_slice_thickness: 20.0 +2026-06-24 05:50:52,210 - simu_Npix: None +2026-06-24 05:50:52,210 - simu_match_mode: None +2026-06-24 05:50:52,210 - meas_permute: None +2026-06-24 05:50:52,210 - meas_reshape: [256, 128, 128] +2026-06-24 05:50:52,210 - meas_flipT: [0, 0, 0] +2026-06-24 05:50:52,210 - meas_crop: None +2026-06-24 05:50:52,210 - meas_pad: None +2026-06-24 05:50:52,210 - meas_resample: None +2026-06-24 05:50:52,210 - meas_add_source_size: None +2026-06-24 05:50:52,210 - meas_add_detector_blur: None +2026-06-24 05:50:52,210 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:50:52,210 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:50:52,210 - meas_add_poisson_noise: None +2026-06-24 05:50:52,210 - meas_export: None +2026-06-24 05:50:52,211 - probe_permute: None +2026-06-24 05:50:52,211 - probe_z_shift: None +2026-06-24 05:50:52,211 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:50:52,211 - pos_scan_flipT: None +2026-06-24 05:50:52,211 - pos_scan_affine: None +2026-06-24 05:50:52,211 - pos_scan_rand_std: 0.15 +2026-06-24 05:50:52,211 - obj_z_crop: None +2026-06-24 05:50:52,211 - obj_z_pad: None +2026-06-24 05:50:52,211 - obj_z_resample: None +2026-06-24 05:50:52,211 - meas_source: file +2026-06-24 05:50:52,211 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000032_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:50:52,211 - probe_source: simu +2026-06-24 05:50:52,211 - probe_params: None +2026-06-24 05:50:52,211 - pos_source: simu +2026-06-24 05:50:52,211 - pos_params: None +2026-06-24 05:50:52,211 - obj_source: simu +2026-06-24 05:50:52,211 - obj_params: None +2026-06-24 05:50:52,211 - tilt_source: simu +2026-06-24 05:50:52,211 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:50:52,211 - +2026-06-24 05:50:52,211 - ### Initializing cache ### +2026-06-24 05:50:52,211 - use_cached_obj = False +2026-06-24 05:50:52,211 - use_cached_probe = False +2026-06-24 05:50:52,211 - use_cached_pos = False +2026-06-24 05:50:52,211 - +2026-06-24 05:50:52,211 - ### Initializing measurements ### +2026-06-24 05:50:52,211 - Loading measurements from source = 'file' +2026-06-24 05:50:52,211 - Detected measurement file type = '.h5' +2026-06-24 05:50:52,290 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:50:52,290 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:50:52,292 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0142) +2026-06-24 05:50:52,292 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:50:52,292 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:50:52,294 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:50:52,294 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:50:52,294 - Normalizing by max of the 2D mean pattern intensity: 0.012359639 +2026-06-24 05:50:52,295 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:50:52,296 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0049, 1.1482) +2026-06-24 05:50:52,297 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:50:52,298 - Pattern total int. statistics (min, mean, max) = (79.2529, 80.2519, 81.0510), with min/max = 97.8% +2026-06-24 05:50:52,301 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0049, 1.1482) +2026-06-24 05:50:52,301 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:50:52,301 - +2026-06-24 05:50:52,301 - ### Setting up calibration ### +2026-06-24 05:50:52,301 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:50:52,301 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:50:52,301 - Radius of fitted bright field disk (RBF) = 4.69 px with meas_Npix = 128 +2026-06-24 05:50:52,301 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0732 +2026-06-24 05:50:52,301 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:50:52,301 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:50:52,528 - Initial guess: center=(63.63, 63.62), radius=4.69, Gaussian blur std=0.50 +2026-06-24 05:50:52,539 - Final fit: center=(63.63, 63.62), radius=4.69, Gaussian blur std=0.60 +2026-06-24 05:50:52,539 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 4.75 px with Npix = 128 +2026-06-24 05:50:52,539 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:50:52,539 - +2026-06-24 05:50:52,539 - ### Setting init_variables dict ### +2026-06-24 05:50:52,539 - Derived values given input init_params: +2026-06-24 05:50:52,539 - kv = 30.0 kV +2026-06-24 05:50:52,539 - wavelength = 0.0698 Ang +2026-06-24 05:50:52,540 - conv_angle = 12.94440746307373 mrad +2026-06-24 05:50:52,540 - Npix = 128 px +2026-06-24 05:50:52,540 - dk = 0.0391 Ang^-1 +2026-06-24 05:50:52,540 - kMax = 2.5000 Ang^-1 +2026-06-24 05:50:52,540 - da = 2.7262 mrad +2026-06-24 05:50:52,540 - angleMax = 174.4770 mrad +2026-06-24 05:50:52,540 - RBF = 4.7481 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:50:52,540 - n_alpha = 13.4790 (# conv_angle) +2026-06-24 05:50:52,540 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:50:52,540 - Rayleigh-limited resolution = 3.2889 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:50:52,540 - Real space probe extent = 25.6000 Ang +2026-06-24 05:50:52,540 - +2026-06-24 05:50:52,540 - ### Initializing probe ### +2026-06-24 05:50:52,540 - Loading probe from source = 'simu' +2026-06-24 05:50:52,540 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:50:52,540 - Start simulating STEM probe +2026-06-24 05:50:52,540 - kv = 30.0 kV +2026-06-24 05:50:52,540 - wavelength = 0.0698 Ang +2026-06-24 05:50:52,540 - conv_angle = 12.94440746307373 mrad +2026-06-24 05:50:52,540 - Npix = 128 px +2026-06-24 05:50:52,540 - dk = 0.0391 Ang^-1 +2026-06-24 05:50:52,540 - kMax = 2.5000 Ang^-1 +2026-06-24 05:50:52,540 - alpha_max = 174.4770 mrad +2026-06-24 05:50:52,540 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:50:52,540 - Rayleigh-limited resolution = 3.2889 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:50:52,540 - Real space probe extent = 25.6000 Ang +2026-06-24 05:50:52,541 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:50:52,541 - ------------------------------------------------------------------------------------ +2026-06-24 05:50:52,541 - C1,0 C1 -460.2140 - Defocus (C10 = -df) +2026-06-24 05:50:52,541 - C1,2 A1 -11.7010 63.87 2-fold astigmatism +2026-06-24 05:50:52,541 - C2,1 3*B2 -130.4180 348.74 Axial coma +2026-06-24 05:50:52,541 - C2,3 A2 -977.0270 161.49 3-fold astigmatism +2026-06-24 05:50:52,541 - C3,0 C3 1922825.5000 - Spherical aberration +2026-06-24 05:50:52,541 - C3,2 4*S3 -8678.4060 293.38 Axial star aberration +2026-06-24 05:50:52,541 - C3,4 A3 -10483.4010 264.53 4-fold astigmatism +2026-06-24 05:50:52,541 - C4,1 4*B4 -371409.6880 194.08 Axial coma(4th) +2026-06-24 05:50:52,541 - C4,3 4*D4 -130966.5940 43.92 3-lobe aberration +2026-06-24 05:50:52,541 - C4,5 A4 258425.3120 88.79 5-fold astigmatism +2026-06-24 05:50:52,541 - C5,0 C5 207998128.0000 - Spherical aberration (5th) +2026-06-24 05:50:52,541 - C5,2 6*S5 -15980148.0000 255.44 Axial star aberration(5th) +2026-06-24 05:50:52,541 - C5,4 6*R5 -5412235.5000 126.54 4-lobe aberration +2026-06-24 05:50:52,541 - C5,6 A5 19671308.0000 139.22 6-fold astigmatism +2026-06-24 05:50:52,544 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:50:52,544 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:50:52,544 - Creating 5 new probe modes from the major mode +2026-06-24 05:50:52,544 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:50:52,737 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:50:52,739 - Orthogonalizing 6 pmodes +2026-06-24 05:50:52,751 - Sorting 6 pmodes by their intensities +2026-06-24 05:50:52,751 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:50:52,752 - sum(|probe_data|**2) = 80.25, while meas_total_ints (min, mean, max) = (79.2529, 80.2519, 81.0510) +2026-06-24 05:50:52,752 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:50:52,752 - +2026-06-24 05:50:52,752 - ### Initializing probe positions ### +2026-06-24 05:50:52,752 - Loading probe positions from source = 'simu' +2026-06-24 05:50:52,752 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:50:52,752 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3078, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:50:52,752 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:50:52,754 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:50:52,754 - crop_pos 1st and last px coords (y,x) = ([15, 16], [39, 39]) +2026-06-24 05:50:52,755 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 05:50:52,755 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:50:52,755 - +2026-06-24 05:50:52,755 - ### Initializing object ### +2026-06-24 05:50:52,755 - Loading object from source = 'simu' +2026-06-24 05:50:52,755 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:50:52,756 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:50:52,756 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 182, 182) +2026-06-24 05:50:52,756 - object extent (Z, Y, X) (Ang) = [20. 36.4 36.4] +2026-06-24 05:50:52,756 - +2026-06-24 05:50:52,756 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:50:52,756 - omode_occu (omode) = float32, (1,) +2026-06-24 05:50:52,757 - +2026-06-24 05:50:52,757 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:50:52,757 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0698 Ang +2026-06-24 05:50:52,757 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:50:52,757 - +2026-06-24 05:50:52,757 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:50:52,757 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:50:52,757 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:50:52,757 - +2026-06-24 05:50:52,757 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:50:52,757 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:50:52,758 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:50:52,758 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:50:52,758 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:50:52,758 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (182, 182). +2026-06-24 05:50:52,758 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:50:52,758 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:50:52,758 - +2026-06-24 05:50:52,758 - ### Collecting reconstruction provenance ### +2026-06-24 05:50:52,758 - Reconstruction provenance is collected and initialized. +2026-06-24 05:50:52,758 - +2026-06-24 05:50:52,758 - ### Initializing loss function ### +2026-06-24 05:50:52,758 - Active loss types: +2026-06-24 05:50:52,758 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:50:52,758 - +2026-06-24 05:50:52,758 - ### Initializing constraint function ### +2026-06-24 05:50:52,758 - Active constraint types: +2026-06-24 05:50:52,758 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:50:52,758 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:50:52,758 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:50:52,758 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:50:52,758 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:50:52,758 - +2026-06-24 05:50:52,759 - ### Done initializing PtyRADSolver ### +2026-06-24 05:50:52,759 - +2026-06-24 05:50:52,882 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:50:52,882 - +2026-06-24 05:50:52,883 - ### Initializing PtychoModel model ### +2026-06-24 05:50:52,952 - ### PtychoModel optimizable variables ### +2026-06-24 05:50:52,952 - obja : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:50:52,952 - objp : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:50:52,952 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:50:52,952 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:50:52,953 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:50:52,953 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:50:52,953 - +2026-06-24 05:50:52,953 - ### Optimizable variables statitsics ### +2026-06-24 05:50:52,953 - Total measurement values : 4,194,304 +2026-06-24 05:50:52,953 - Total optimizing variables: 263,368 +2026-06-24 05:50:52,953 - Overdetermined ratio : 15.93 +2026-06-24 05:50:52,953 - +2026-06-24 05:50:52,953 - ### Model behavior ### +2026-06-24 05:50:52,953 - Tilt propagator : False +2026-06-24 05:50:52,953 - Change slice thickness : False +2026-06-24 05:50:52,953 - Detector blur : False +2026-06-24 05:50:52,953 - Preload data : True +2026-06-24 05:50:52,953 - On-the-fly meas padding : False +2026-06-24 05:50:52,953 - On-the-fly meas resample : False +2026-06-24 05:50:52,953 - On-the-fly simu match mode: None +2026-06-24 05:50:52,953 - +2026-06-24 05:50:52,994 - ### Done initializing PtychoModel model ### +2026-06-24 05:50:52,995 - +2026-06-24 05:50:52,995 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:50:52,995 - +2026-06-24 05:50:52,995 - ### Generating indices, batches, and output_path ### +2026-06-24 05:50:52,996 - d90 = 63.000 px or 12.600 Ang +2026-06-24 05:50:52,996 - Selecting indices with the 'full' mode +2026-06-24 05:50:53,453 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:50:53,534 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:50:53,534 - Original recon_dir_affixes = ['default'] +2026-06-24 05:50:53,534 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:50:53,541 - Path corrected for compatibility: +2026-06-24 05:50:53,541 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_-8.68e+03_phi32_293_C34_-1.05e+04_phi34_265_C41_-3.71e+05_phi41_194_C43_-1.31e+05_phi43_43.9_C45_2.58e+05_phi45_88.8_C50_2.08e+08_C52_-1.6e+07_phi52_255_C54_-5.41e+06_phi54_127_C56_1.97e+07_phi56_139 +2026-06-24 05:50:53,541 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139 +2026-06-24 05:50:53,542 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139' is generated! +2026-06-24 05:50:53,701 - +2026-06-24 05:50:53,703 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/20260624_055053_ptyrad_log.txt ### +2026-06-24 05:50:53,703 - +2026-06-24 05:50:53,704 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:50:53,704 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:50:53,704 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:50:54,883 - Iter: 1, Total Loss: 1.4820, loss_single: 1.4820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 05:50:54,920 - Iter: 2, Total Loss: 1.3895, loss_single: 1.3895, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:50:54,956 - Iter: 3, Total Loss: 1.3056, loss_single: 1.3056, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:54,991 - Iter: 4, Total Loss: 1.2467, loss_single: 1.2467, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,026 - Iter: 5, Total Loss: 1.2041, loss_single: 1.2041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,062 - Iter: 6, Total Loss: 1.1518, loss_single: 1.1518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:50:55,097 - Iter: 7, Total Loss: 1.1006, loss_single: 1.1006, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:50:55,133 - Iter: 8, Total Loss: 1.0552, loss_single: 1.0552, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:50:55,169 - Iter: 9, Total Loss: 1.0027, loss_single: 1.0027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,204 - Iter: 10, Total Loss: 0.9372, loss_single: 0.9372, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,240 - Iter: 11, Total Loss: 0.8763, loss_single: 0.8763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,275 - Iter: 12, Total Loss: 0.8255, loss_single: 0.8255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,310 - Iter: 13, Total Loss: 0.7769, loss_single: 0.7769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,345 - Iter: 14, Total Loss: 0.7228, loss_single: 0.7228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,380 - Iter: 15, Total Loss: 0.6653, loss_single: 0.6653, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,416 - Iter: 16, Total Loss: 0.6135, loss_single: 0.6135, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,451 - Iter: 17, Total Loss: 0.5763, loss_single: 0.5763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,487 - Iter: 18, Total Loss: 0.5470, loss_single: 0.5470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,522 - Iter: 19, Total Loss: 0.5166, loss_single: 0.5166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,557 - Iter: 20, Total Loss: 0.4875, loss_single: 0.4875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,593 - Iter: 21, Total Loss: 0.4701, loss_single: 0.4701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,628 - Iter: 22, Total Loss: 0.4602, loss_single: 0.4602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,663 - Iter: 23, Total Loss: 0.4515, loss_single: 0.4515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,698 - Iter: 24, Total Loss: 0.4466, loss_single: 0.4466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,733 - Iter: 25, Total Loss: 0.4432, loss_single: 0.4432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,769 - Iter: 26, Total Loss: 0.4404, loss_single: 0.4404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,805 - Iter: 27, Total Loss: 0.4382, loss_single: 0.4382, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,840 - Iter: 28, Total Loss: 0.4363, loss_single: 0.4363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,875 - Iter: 29, Total Loss: 0.4346, loss_single: 0.4346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,911 - Iter: 30, Total Loss: 0.4335, loss_single: 0.4335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,946 - Iter: 31, Total Loss: 0.4326, loss_single: 0.4326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:55,981 - Iter: 32, Total Loss: 0.4319, loss_single: 0.4319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,016 - Iter: 33, Total Loss: 0.4313, loss_single: 0.4313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,051 - Iter: 34, Total Loss: 0.4308, loss_single: 0.4308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,087 - Iter: 35, Total Loss: 0.4303, loss_single: 0.4303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,122 - Iter: 36, Total Loss: 0.4299, loss_single: 0.4299, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,157 - Iter: 37, Total Loss: 0.4295, loss_single: 0.4295, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,193 - Iter: 38, Total Loss: 0.4291, loss_single: 0.4291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,228 - Iter: 39, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,263 - Iter: 40, Total Loss: 0.4287, loss_single: 0.4287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,301 - Iter: 41, Total Loss: 0.4285, loss_single: 0.4285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,337 - Iter: 42, Total Loss: 0.4283, loss_single: 0.4283, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,372 - Iter: 43, Total Loss: 0.4282, loss_single: 0.4282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,407 - Iter: 44, Total Loss: 0.4281, loss_single: 0.4281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,442 - Iter: 45, Total Loss: 0.4279, loss_single: 0.4279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,478 - Iter: 46, Total Loss: 0.4278, loss_single: 0.4278, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,513 - Iter: 47, Total Loss: 0.4276, loss_single: 0.4276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,548 - Iter: 48, Total Loss: 0.4276, loss_single: 0.4276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,596 - Iter: 49, Total Loss: 0.4275, loss_single: 0.4275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,631 - Iter: 50, Total Loss: 0.4274, loss_single: 0.4274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,667 - Iter: 51, Total Loss: 0.4273, loss_single: 0.4273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:50:56,702 - Iter: 52, Total Loss: 0.4272, loss_single: 0.4272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:50:56,737 - Iter: 53, Total Loss: 0.4272, loss_single: 0.4272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,772 - Iter: 54, Total Loss: 0.4271, loss_single: 0.4271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,807 - Iter: 55, Total Loss: 0.4271, loss_single: 0.4271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,842 - Iter: 56, Total Loss: 0.4270, loss_single: 0.4270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:50:56,878 - Iter: 57, Total Loss: 0.4270, loss_single: 0.4270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:50:56,913 - Iter: 58, Total Loss: 0.4269, loss_single: 0.4269, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/simulation_data2__sample_000032.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/simulation_data2__sample_000032.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8ffa134b3db776f1d4329b7017539ba2d4bc3dff --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/simulation_data2__sample_000032.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 30.0 + probe_conv_angle: 12.94440746307373 + probe_aberrations: + C10: -460.2137451171875 + C12: -11.701135635375977 + C21: -130.41802978515625 + C23: -977.026611328125 + C30: 1922825.5 + C32: -8678.40625 + C34: -10483.4013671875 + C41: -371409.6875 + C43: -130966.59375 + C45: 258425.3125 + C50: 207998128.0 + C52: -15980148.0 + C54: -5412235.5 + C56: 19671308.0 + phi12: 63.870792815703396 + phi21: 348.7442953978385 + phi23: 161.4850150748309 + phi32: 293.384519344618 + phi34: 264.53030323362907 + phi41: 194.07583643543703 + phi43: 43.920141514270895 + phi45: 88.79234309694988 + phi52: 255.43934876909879 + phi54: 126.53883029970257 + phi56: 139.21645370118995 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.30775824189186096 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000032_measurement.h5 + key: measurement + random_seed: 20261912 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data2__sample_000032 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000032/c30_small__simulation_data2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-460_C12_-11.7_phi12_63.9_C21_-130_phi21_349_C23_-977_phi23_161_C30_1.92e+06_C32_.97e+07_phi56_139/summary_convergence_iter0100.png new file mode 100644 index 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sha256:458456a86b430560c42f522bcbad317302ec277493c7293f80c141e9f0da5ede +size 50560 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237/20260624_055108_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237/20260624_055108_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..151612253403193f8897503fcdb6e1a6d40dcc23 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237/20260624_055108_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:51:07,193 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:51:07,193 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:51:07,193 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:51:07,193 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:51:07,193 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:51:07,193 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:51:07,193 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:51:07,193 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:51:07,193 - +2026-06-24 05:51:07,305 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:51:07,305 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:51:07,305 - Accelerator.num_process = 1 +2026-06-24 05:51:07,305 - Accelerator.mixed_precision = no +2026-06-24 05:51:07,316 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:51:07,316 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:51:07,316 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:51:07,316 - +2026-06-24 05:51:07,316 - ### System information ### +2026-06-24 05:51:07,316 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:51:07,316 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:51:07,316 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:51:07,316 - Machine: x86_64 +2026-06-24 05:51:07,316 - Processor: x86_64 +2026-06-24 05:51:07,316 - Available CPU cores: 8 +2026-06-24 05:51:07,316 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:51:07,316 - +2026-06-24 05:51:07,316 - ### GPU information ### +2026-06-24 05:51:07,316 - CUDA Available: True +2026-06-24 05:51:07,316 - CUDA Version: 13.0 +2026-06-24 05:51:07,317 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:51:07,317 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:51:07,317 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:51:07,317 - In addition, Triton does not directly support Windows. +2026-06-24 05:51:07,317 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:51:07,343 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:51:07,343 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:51:07,343 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:51:07,344 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:51:07,344 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:51:07,344 - +2026-06-24 05:51:07,344 - ### Python information ### +2026-06-24 05:51:07,345 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:51:07,345 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:51:07,345 - +2026-06-24 05:51:07,346 - ### Packages information ### +2026-06-24 05:51:07,346 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:51:07,347 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:51:07,347 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:51:07,348 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:51:07,349 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:51:07,349 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:51:07,349 - +2026-06-24 05:51:07,349 - ### Loading params file ### +2026-06-24 05:51:07,349 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000033.yaml +2026-06-24 05:51:07,355 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:51:07,356 - Success! Params file validated and defaults applied. +2026-06-24 05:51:07,356 - +2026-06-24 05:51:07,356 - ### Setting GPU Device ### +2026-06-24 05:51:07,356 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:51:07,356 - +2026-06-24 05:51:07,356 - Random seed: 20261913 provided by params file +2026-06-24 05:51:07,357 - ### Initializing Initializer ### +2026-06-24 05:51:07,357 - init_params are displayed below: +2026-06-24 05:51:07,357 - random_seed: 20261913 +2026-06-24 05:51:07,357 - probe_illum_type: electron +2026-06-24 05:51:07,357 - probe_kv: 80.0 +2026-06-24 05:51:07,357 - probe_conv_angle: 9.789743423461914 +2026-06-24 05:51:07,357 - probe_aberrations: {'C10': 46.727, 'C12': -4.53, 'phi12': 82.373, 'C21': 552.801, 'phi21': 66.625, 'C23': -458.188, 'phi23': 359.784, 'C30': 1984305.25, 'C32': -2144.946, 'phi32': 76.154, 'C34': -5479.942, 'phi34': 336.387, 'C41': -28790.539, 'phi41': 36.667, 'C43': 440.896, 'phi43': 357.462, 'C45': 414949.406, 'phi45': 283.407, 'C50': -95468080.0, 'C52': 9298095.0, 'phi52': 101.708, 'C54': 14720424.0, 'phi54': 184.976, 'C56': -10155851.0, 'phi56': 237.097} +2026-06-24 05:51:07,357 - beam_kev: None +2026-06-24 05:51:07,357 - probe_dRn: None +2026-06-24 05:51:07,357 - probe_Rn: None +2026-06-24 05:51:07,357 - probe_D_H: None +2026-06-24 05:51:07,357 - probe_D_FZP: None +2026-06-24 05:51:07,357 - probe_Ls: None +2026-06-24 05:51:07,357 - meas_Npix: 128 +2026-06-24 05:51:07,357 - pos_N_scans: 256 +2026-06-24 05:51:07,357 - pos_N_scan_slow: 16 +2026-06-24 05:51:07,357 - pos_N_scan_fast: 16 +2026-06-24 05:51:07,357 - pos_scan_step_size: 0.5069717764854431 +2026-06-24 05:51:07,357 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:51:07,357 - probe_pmode_max: 6 +2026-06-24 05:51:07,357 - probe_pmode_init_pows: [0.02] +2026-06-24 05:51:07,357 - obj_omode_max: 1 +2026-06-24 05:51:07,358 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:51:07,358 - obj_Nlayer: 1 +2026-06-24 05:51:07,358 - obj_slice_thickness: 20.0 +2026-06-24 05:51:07,358 - simu_Npix: None +2026-06-24 05:51:07,358 - simu_match_mode: None +2026-06-24 05:51:07,358 - meas_permute: None +2026-06-24 05:51:07,358 - meas_reshape: [256, 128, 128] +2026-06-24 05:51:07,358 - meas_flipT: [0, 0, 0] +2026-06-24 05:51:07,358 - meas_crop: None +2026-06-24 05:51:07,358 - meas_pad: None +2026-06-24 05:51:07,358 - meas_resample: None +2026-06-24 05:51:07,358 - meas_add_source_size: None +2026-06-24 05:51:07,358 - meas_add_detector_blur: None +2026-06-24 05:51:07,358 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:51:07,358 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:51:07,358 - meas_add_poisson_noise: None +2026-06-24 05:51:07,358 - meas_export: None +2026-06-24 05:51:07,358 - probe_permute: None +2026-06-24 05:51:07,358 - probe_z_shift: None +2026-06-24 05:51:07,358 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:51:07,358 - pos_scan_flipT: None +2026-06-24 05:51:07,358 - pos_scan_affine: None +2026-06-24 05:51:07,358 - pos_scan_rand_std: 0.15 +2026-06-24 05:51:07,358 - obj_z_crop: None +2026-06-24 05:51:07,358 - obj_z_pad: None +2026-06-24 05:51:07,358 - obj_z_resample: None +2026-06-24 05:51:07,358 - meas_source: file +2026-06-24 05:51:07,358 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000033_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:51:07,358 - probe_source: simu +2026-06-24 05:51:07,358 - probe_params: None +2026-06-24 05:51:07,358 - pos_source: simu +2026-06-24 05:51:07,358 - pos_params: None +2026-06-24 05:51:07,358 - obj_source: simu +2026-06-24 05:51:07,358 - obj_params: None +2026-06-24 05:51:07,358 - tilt_source: simu +2026-06-24 05:51:07,358 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:51:07,358 - +2026-06-24 05:51:07,358 - ### Initializing cache ### +2026-06-24 05:51:07,358 - use_cached_obj = False +2026-06-24 05:51:07,359 - use_cached_probe = False +2026-06-24 05:51:07,359 - use_cached_pos = False +2026-06-24 05:51:07,359 - +2026-06-24 05:51:07,359 - ### Initializing measurements ### +2026-06-24 05:51:07,359 - Loading measurements from source = 'file' +2026-06-24 05:51:07,359 - Detected measurement file type = '.h5' +2026-06-24 05:51:07,439 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:51:07,440 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:51:07,441 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0087) +2026-06-24 05:51:07,441 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:51:07,441 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:51:07,443 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:51:07,443 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:51:07,443 - Normalizing by max of the 2D mean pattern intensity: 0.0066295573 +2026-06-24 05:51:07,444 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:51:07,445 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0090, 1.3091) +2026-06-24 05:51:07,446 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:51:07,447 - Pattern total int. statistics (min, mean, max) = (146.0816, 147.8883, 149.4379), with min/max = 97.8% +2026-06-24 05:51:07,448 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0090, 1.3091) +2026-06-24 05:51:07,448 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:51:07,448 - +2026-06-24 05:51:07,448 - ### Setting up calibration ### +2026-06-24 05:51:07,448 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:51:07,448 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:51:07,448 - Radius of fitted bright field disk (RBF) = 6.02 px with meas_Npix = 128 +2026-06-24 05:51:07,449 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0941 +2026-06-24 05:51:07,449 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:51:07,449 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:51:07,669 - Initial guess: center=(63.55, 63.62), radius=6.02, Gaussian blur std=0.50 +2026-06-24 05:51:07,679 - Final fit: center=(63.55, 63.62), radius=6.02, Gaussian blur std=0.59 +2026-06-24 05:51:07,680 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.00 px with Npix = 128 +2026-06-24 05:51:07,680 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:51:07,680 - +2026-06-24 05:51:07,680 - ### Setting init_variables dict ### +2026-06-24 05:51:07,680 - Derived values given input init_params: +2026-06-24 05:51:07,680 - kv = 80.0 kV +2026-06-24 05:51:07,680 - wavelength = 0.0418 Ang +2026-06-24 05:51:07,680 - conv_angle = 9.789743423461914 mrad +2026-06-24 05:51:07,680 - Npix = 128 px +2026-06-24 05:51:07,680 - dk = 0.0391 Ang^-1 +2026-06-24 05:51:07,680 - kMax = 2.5000 Ang^-1 +2026-06-24 05:51:07,680 - da = 1.6311 mrad +2026-06-24 05:51:07,680 - angleMax = 104.3929 mrad +2026-06-24 05:51:07,680 - RBF = 6.0018 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:51:07,680 - n_alpha = 10.6635 (# conv_angle) +2026-06-24 05:51:07,680 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:51:07,680 - Rayleigh-limited resolution = 2.6019 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:51:07,680 - Real space probe extent = 25.6000 Ang +2026-06-24 05:51:07,680 - +2026-06-24 05:51:07,680 - ### Initializing probe ### +2026-06-24 05:51:07,680 - Loading probe from source = 'simu' +2026-06-24 05:51:07,680 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:51:07,681 - Start simulating STEM probe +2026-06-24 05:51:07,681 - kv = 80.0 kV +2026-06-24 05:51:07,681 - wavelength = 0.0418 Ang +2026-06-24 05:51:07,681 - conv_angle = 9.789743423461914 mrad +2026-06-24 05:51:07,681 - Npix = 128 px +2026-06-24 05:51:07,681 - dk = 0.0391 Ang^-1 +2026-06-24 05:51:07,681 - kMax = 2.5000 Ang^-1 +2026-06-24 05:51:07,681 - alpha_max = 104.3929 mrad +2026-06-24 05:51:07,681 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:51:07,681 - Rayleigh-limited resolution = 2.6019 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:51:07,681 - Real space probe extent = 25.6000 Ang +2026-06-24 05:51:07,681 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:51:07,681 - ------------------------------------------------------------------------------------ +2026-06-24 05:51:07,681 - C1,0 C1 46.7270 - Defocus (C10 = -df) +2026-06-24 05:51:07,681 - C1,2 A1 -4.5300 82.37 2-fold astigmatism +2026-06-24 05:51:07,681 - C2,1 3*B2 552.8010 66.62 Axial coma +2026-06-24 05:51:07,681 - C2,3 A2 -458.1880 359.78 3-fold astigmatism +2026-06-24 05:51:07,681 - C3,0 C3 1984305.2500 - Spherical aberration +2026-06-24 05:51:07,681 - C3,2 4*S3 -2144.9460 76.15 Axial star aberration +2026-06-24 05:51:07,681 - C3,4 A3 -5479.9420 336.39 4-fold astigmatism +2026-06-24 05:51:07,681 - C4,1 4*B4 -28790.5390 36.67 Axial coma(4th) +2026-06-24 05:51:07,681 - C4,3 4*D4 440.8960 357.46 3-lobe aberration +2026-06-24 05:51:07,681 - C4,5 A4 414949.4060 283.41 5-fold astigmatism +2026-06-24 05:51:07,681 - C5,0 C5 -95468080.0000 - Spherical aberration (5th) +2026-06-24 05:51:07,681 - C5,2 6*S5 9298095.0000 101.71 Axial star aberration(5th) +2026-06-24 05:51:07,681 - C5,4 6*R5 14720424.0000 184.98 4-lobe aberration +2026-06-24 05:51:07,681 - C5,6 A5 -10155851.0000 237.10 6-fold astigmatism +2026-06-24 05:51:07,684 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:51:07,684 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:51:07,685 - Creating 5 new probe modes from the major mode +2026-06-24 05:51:07,685 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:51:07,921 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:51:07,922 - Orthogonalizing 6 pmodes +2026-06-24 05:51:07,925 - Sorting 6 pmodes by their intensities +2026-06-24 05:51:07,925 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:51:07,926 - sum(|probe_data|**2) = 147.89, while meas_total_ints (min, mean, max) = (146.0816, 147.8883, 149.4379) +2026-06-24 05:51:07,926 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:51:07,926 - +2026-06-24 05:51:07,926 - ### Initializing probe positions ### +2026-06-24 05:51:07,926 - Loading probe positions from source = 'simu' +2026-06-24 05:51:07,926 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:51:07,926 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5070, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:51:07,926 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:51:07,928 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:51:07,928 - crop_pos 1st and last px coords (y,x) = ([17, 17], [55, 55]) +2026-06-24 05:51:07,928 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 05:51:07,928 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:51:07,928 - +2026-06-24 05:51:07,928 - ### Initializing object ### +2026-06-24 05:51:07,928 - Loading object from source = 'simu' +2026-06-24 05:51:07,928 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:51:07,930 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:51:07,930 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 200, 200) +2026-06-24 05:51:07,930 - object extent (Z, Y, X) (Ang) = [20. 40. 40.] +2026-06-24 05:51:07,930 - +2026-06-24 05:51:07,930 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:51:07,930 - omode_occu (omode) = float32, (1,) +2026-06-24 05:51:07,930 - +2026-06-24 05:51:07,930 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:51:07,930 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 05:51:07,931 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:51:07,931 - +2026-06-24 05:51:07,931 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:51:07,931 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:51:07,931 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:51:07,931 - +2026-06-24 05:51:07,931 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:51:07,931 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:51:07,931 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:51:07,931 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:51:07,931 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:51:07,931 - crop positions (yx_min=[17 17], yx_max=[183 183]) are well contained inside object canvas (Ny,Nx) = (200, 200). +2026-06-24 05:51:07,931 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:51:07,932 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:51:07,932 - +2026-06-24 05:51:07,932 - ### Collecting reconstruction provenance ### +2026-06-24 05:51:07,932 - Reconstruction provenance is collected and initialized. +2026-06-24 05:51:07,932 - +2026-06-24 05:51:07,932 - ### Initializing loss function ### +2026-06-24 05:51:07,932 - Active loss types: +2026-06-24 05:51:07,932 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:51:07,932 - +2026-06-24 05:51:07,932 - ### Initializing constraint function ### +2026-06-24 05:51:07,932 - Active constraint types: +2026-06-24 05:51:07,932 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:51:07,932 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:51:07,932 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:51:07,932 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:51:07,932 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:51:07,932 - +2026-06-24 05:51:07,932 - ### Done initializing PtyRADSolver ### +2026-06-24 05:51:07,932 - +2026-06-24 05:51:08,061 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:51:08,061 - +2026-06-24 05:51:08,061 - ### Initializing PtychoModel model ### +2026-06-24 05:51:08,132 - ### PtychoModel optimizable variables ### +2026-06-24 05:51:08,132 - obja : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:08,132 - objp : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:08,132 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:51:08,132 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:51:08,132 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:51:08,132 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:08,132 - +2026-06-24 05:51:08,133 - ### Optimizable variables statitsics ### +2026-06-24 05:51:08,133 - Total measurement values : 4,194,304 +2026-06-24 05:51:08,133 - Total optimizing variables: 277,120 +2026-06-24 05:51:08,133 - Overdetermined ratio : 15.14 +2026-06-24 05:51:08,133 - +2026-06-24 05:51:08,133 - ### Model behavior ### +2026-06-24 05:51:08,133 - Tilt propagator : False +2026-06-24 05:51:08,133 - Change slice thickness : False +2026-06-24 05:51:08,133 - Detector blur : False +2026-06-24 05:51:08,133 - Preload data : True +2026-06-24 05:51:08,133 - On-the-fly meas padding : False +2026-06-24 05:51:08,133 - On-the-fly meas resample : False +2026-06-24 05:51:08,133 - On-the-fly simu match mode: None +2026-06-24 05:51:08,133 - +2026-06-24 05:51:08,173 - ### Done initializing PtychoModel model ### +2026-06-24 05:51:08,174 - +2026-06-24 05:51:08,174 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:51:08,174 - +2026-06-24 05:51:08,174 - ### Generating indices, batches, and output_path ### +2026-06-24 05:51:08,175 - d90 = 51.000 px or 10.200 Ang +2026-06-24 05:51:08,175 - Selecting indices with the 'full' mode +2026-06-24 05:51:08,634 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:51:08,710 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:51:08,710 - Original recon_dir_affixes = ['default'] +2026-06-24 05:51:08,710 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:51:08,717 - Path corrected for compatibility: +2026-06-24 05:51:08,717 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_-2.14e+03_phi32_76.2_C34_-5.48e+03_phi34_336_C41_-2.88e+04_phi41_36.7_C43_441_phi43_357_C45_4.15e+05_phi45_283_C50_-9.55e+07_C52_9.3e+06_phi52_102_C54_1.47e+07_phi54_185_C56_-1.02e+07_phi56_237 +2026-06-24 05:51:08,717 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237 +2026-06-24 05:51:08,718 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237' is generated! +2026-06-24 05:51:08,872 - +2026-06-24 05:51:08,873 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237/20260624_055108_ptyrad_log.txt ### +2026-06-24 05:51:08,873 - +2026-06-24 05:51:08,874 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:51:08,874 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:51:08,874 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:51:10,057 - Iter: 1, Total Loss: 1.2758, loss_single: 1.2758, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 05:51:10,094 - Iter: 2, Total Loss: 1.2288, loss_single: 1.2288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:51:10,129 - Iter: 3, Total Loss: 1.1859, loss_single: 1.1859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,165 - Iter: 4, Total Loss: 1.1455, loss_single: 1.1455, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,200 - Iter: 5, Total Loss: 1.1073, loss_single: 1.1073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,236 - Iter: 6, Total Loss: 1.0726, loss_single: 1.0726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,271 - Iter: 7, Total Loss: 1.0402, loss_single: 1.0402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,306 - Iter: 8, Total Loss: 1.0055, loss_single: 1.0055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,343 - Iter: 9, Total Loss: 0.9707, loss_single: 0.9707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:10,378 - Iter: 10, Total Loss: 0.9309, loss_single: 0.9309, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,413 - Iter: 11, Total Loss: 0.8861, loss_single: 0.8861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,448 - Iter: 12, Total Loss: 0.8414, loss_single: 0.8414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,484 - Iter: 13, Total Loss: 0.7980, loss_single: 0.7980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,519 - Iter: 14, Total Loss: 0.7560, loss_single: 0.7560, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,554 - Iter: 15, Total Loss: 0.7160, loss_single: 0.7160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,589 - Iter: 16, Total Loss: 0.6761, loss_single: 0.6761, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,625 - Iter: 17, Total Loss: 0.6415, loss_single: 0.6415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,660 - Iter: 18, Total Loss: 0.6117, loss_single: 0.6117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,696 - Iter: 19, Total Loss: 0.5821, loss_single: 0.5821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,731 - Iter: 20, Total Loss: 0.5514, loss_single: 0.5514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,767 - Iter: 21, Total Loss: 0.5224, loss_single: 0.5224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,803 - Iter: 22, Total Loss: 0.4975, loss_single: 0.4975, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:10,837 - Iter: 23, Total Loss: 0.4745, loss_single: 0.4745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:51:10,873 - Iter: 24, Total Loss: 0.4528, loss_single: 0.4528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,911 - Iter: 25, Total Loss: 0.4332, loss_single: 0.4332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:51:10,947 - Iter: 26, Total Loss: 0.4173, loss_single: 0.4173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:10,982 - Iter: 27, Total Loss: 0.4023, loss_single: 0.4023, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,018 - Iter: 28, Total Loss: 0.3892, loss_single: 0.3892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,053 - Iter: 29, Total Loss: 0.3823, loss_single: 0.3823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,088 - Iter: 30, Total Loss: 0.3772, loss_single: 0.3772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,123 - Iter: 31, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,158 - Iter: 32, Total Loss: 0.3638, loss_single: 0.3638, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,193 - Iter: 33, Total Loss: 0.3579, loss_single: 0.3579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:51:11,228 - Iter: 34, Total Loss: 0.3534, loss_single: 0.3534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:11,264 - Iter: 35, Total Loss: 0.3505, loss_single: 0.3505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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in 0.035 sec +2026-06-24 05:51:12,502 - Iter: 70, Total Loss: 0.3359, loss_single: 0.3359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:12,537 - Iter: 71, Total Loss: 0.3358, loss_single: 0.3358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:12,572 - Iter: 72, Total Loss: 0.3357, loss_single: 0.3357, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:12,608 - Iter: 73, Total Loss: 0.3357, loss_single: 0.3357, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:12,643 - Iter: 74, Total Loss: 0.3356, loss_single: 0.3356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:12,678 - Iter: 75, Total Loss: 0.3355, loss_single: 0.3355, loss_poissn: 0.0000, loss_pacbed: 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0.3342, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:13,525 - Iter: 99, Total Loss: 0.3341, loss_single: 0.3341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:13,560 - Iter: 100, Total Loss: 0.3341, loss_single: 0.3341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:13,670 - Saving summary figures for iter 100 +2026-06-24 05:51:17,238 - ### Finished 100 iterations, averaged iter_t = 0.038916 with std = 0.040 ### +2026-06-24 05:51:17,238 - +2026-06-24 05:51:17,238 - ### The PtyRADSolver is finished in 9.177 sec ### +2026-06-24 05:51:17,238 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033/c30_small__simulation_data2__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_46.7_C12_-4.53_phi12_82.4_C21_553_phi21_66.6_C23_-458_phi23_360_C30_1.98e+06_C32_.02e+07_phi56_237/simulation_data2__sample_000033.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 9.789743423461914 + probe_aberrations: + C10: 46.72700881958008 + C12: -4.5300374031066895 + C21: 552.8010864257812 + C23: -458.1876220703125 + C30: 1984305.25 + C32: -2144.945556640625 + C34: -5479.9423828125 + C41: -28790.5390625 + C43: 440.8964538574219 + C45: 414949.40625 + C50: -95468080.0 + C52: 9298095.0 + C54: 14720424.0 + C56: -10155851.0 + phi12: 82.37290784324335 + phi21: 66.62480022113341 + phi23: 359.7842033608969 + phi32: 76.15369275486658 + phi34: 336.38714447220815 + phi41: 36.66745391767408 + phi43: 357.4618024393092 + phi45: 283.4071975711168 + phi52: 101.70833327028153 + phi54: 184.97592076271567 + phi56: 237.09660254546276 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5069717764854431 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000033_measurement.h5 + key: measurement + random_seed: 20261913 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000033 + 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sha256:1cecaeac3fa2b22b1dab33d0fb3420255bc24a17ae968689fff6703e6bf87f45 +size 48601 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/20260624_055123_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/20260624_055123_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9c2c820cb25eeded02cd536f453c87abd18a6062 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/20260624_055123_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:51:21,947 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:51:21,947 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:51:21,947 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:51:21,947 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:51:21,947 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:51:21,947 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:51:21,947 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:51:21,947 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:51:21,947 - +2026-06-24 05:51:22,055 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:51:22,055 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:51:22,055 - Accelerator.num_process = 1 +2026-06-24 05:51:22,055 - Accelerator.mixed_precision = no +2026-06-24 05:51:22,066 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:51:22,066 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:51:22,066 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:51:22,066 - +2026-06-24 05:51:22,066 - ### System information ### +2026-06-24 05:51:22,066 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:51:22,066 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:51:22,066 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:51:22,066 - Machine: x86_64 +2026-06-24 05:51:22,066 - Processor: x86_64 +2026-06-24 05:51:22,066 - Available CPU cores: 8 +2026-06-24 05:51:22,066 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:51:22,066 - +2026-06-24 05:51:22,066 - ### GPU information ### +2026-06-24 05:51:22,066 - CUDA Available: True +2026-06-24 05:51:22,066 - CUDA Version: 13.0 +2026-06-24 05:51:22,067 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:51:22,067 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:51:22,067 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:51:22,067 - In addition, Triton does not directly support Windows. +2026-06-24 05:51:22,067 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:51:22,082 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:51:22,082 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:51:22,082 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:51:22,082 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:51:22,082 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:51:22,082 - +2026-06-24 05:51:22,082 - ### Python information ### +2026-06-24 05:51:22,084 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:51:22,084 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:51:22,084 - +2026-06-24 05:51:22,084 - ### Packages information ### +2026-06-24 05:51:22,085 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:51:22,085 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:51:22,086 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:51:22,087 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:51:22,087 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:51:22,087 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:51:22,087 - +2026-06-24 05:51:22,087 - ### Loading params file ### +2026-06-24 05:51:22,087 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000034.yaml +2026-06-24 05:51:22,094 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:51:22,095 - Success! Params file validated and defaults applied. +2026-06-24 05:51:22,095 - +2026-06-24 05:51:22,095 - ### Setting GPU Device ### +2026-06-24 05:51:22,095 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:51:22,095 - +2026-06-24 05:51:22,095 - Random seed: 20261914 provided by params file +2026-06-24 05:51:22,095 - ### Initializing Initializer ### +2026-06-24 05:51:22,096 - init_params are displayed below: +2026-06-24 05:51:22,096 - random_seed: 20261914 +2026-06-24 05:51:22,096 - probe_illum_type: electron +2026-06-24 05:51:22,096 - probe_kv: 200.0 +2026-06-24 05:51:22,096 - probe_conv_angle: 9.125269889831543 +2026-06-24 05:51:22,096 - probe_aberrations: {'C10': -303.464, 'C12': 46.899, 'phi12': 286.267, 'C21': 126.575, 'phi21': 133.001, 'C23': 143.74, 'phi23': 137.632, 'C30': 2654738.25, 'C32': 5259.837, 'phi32': 8.609, 'C34': -872.712, 'phi34': 28.674, 'C41': 317267.438, 'phi41': 27.951, 'C43': 479495.312, 'phi43': 349.912, 'C45': 37504.977, 'phi45': 116.912, 'C50': -287591040.0, 'C52': 3065726.0, 'phi52': 293.105, 'C54': 4330784.5, 'phi54': 264.922, 'C56': -19385906.0, 'phi56': 63.82} +2026-06-24 05:51:22,096 - beam_kev: None +2026-06-24 05:51:22,096 - probe_dRn: None +2026-06-24 05:51:22,096 - probe_Rn: None +2026-06-24 05:51:22,096 - probe_D_H: None +2026-06-24 05:51:22,096 - probe_D_FZP: None +2026-06-24 05:51:22,096 - probe_Ls: None +2026-06-24 05:51:22,096 - meas_Npix: 128 +2026-06-24 05:51:22,096 - pos_N_scans: 256 +2026-06-24 05:51:22,096 - pos_N_scan_slow: 16 +2026-06-24 05:51:22,096 - pos_N_scan_fast: 16 +2026-06-24 05:51:22,096 - pos_scan_step_size: 0.37125450372695923 +2026-06-24 05:51:22,096 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:51:22,096 - probe_pmode_max: 6 +2026-06-24 05:51:22,096 - probe_pmode_init_pows: [0.02] +2026-06-24 05:51:22,096 - obj_omode_max: 1 +2026-06-24 05:51:22,096 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:51:22,096 - obj_Nlayer: 1 +2026-06-24 05:51:22,096 - obj_slice_thickness: 20.0 +2026-06-24 05:51:22,096 - simu_Npix: None +2026-06-24 05:51:22,096 - simu_match_mode: None +2026-06-24 05:51:22,096 - meas_permute: None +2026-06-24 05:51:22,096 - meas_reshape: [256, 128, 128] +2026-06-24 05:51:22,096 - meas_flipT: [0, 0, 0] +2026-06-24 05:51:22,096 - meas_crop: None +2026-06-24 05:51:22,096 - meas_pad: None +2026-06-24 05:51:22,096 - meas_resample: None +2026-06-24 05:51:22,096 - meas_add_source_size: None +2026-06-24 05:51:22,096 - meas_add_detector_blur: None +2026-06-24 05:51:22,096 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:51:22,097 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:51:22,097 - meas_add_poisson_noise: None +2026-06-24 05:51:22,097 - meas_export: None +2026-06-24 05:51:22,097 - probe_permute: None +2026-06-24 05:51:22,097 - probe_z_shift: None +2026-06-24 05:51:22,097 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:51:22,097 - pos_scan_flipT: None +2026-06-24 05:51:22,097 - pos_scan_affine: None +2026-06-24 05:51:22,097 - pos_scan_rand_std: 0.15 +2026-06-24 05:51:22,097 - obj_z_crop: None +2026-06-24 05:51:22,097 - obj_z_pad: None +2026-06-24 05:51:22,097 - obj_z_resample: None +2026-06-24 05:51:22,097 - meas_source: file +2026-06-24 05:51:22,097 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000034_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:51:22,097 - probe_source: simu +2026-06-24 05:51:22,097 - probe_params: None +2026-06-24 05:51:22,097 - pos_source: simu +2026-06-24 05:51:22,097 - pos_params: None +2026-06-24 05:51:22,097 - obj_source: simu +2026-06-24 05:51:22,097 - obj_params: None +2026-06-24 05:51:22,097 - tilt_source: simu +2026-06-24 05:51:22,097 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:51:22,097 - +2026-06-24 05:51:22,097 - ### Initializing cache ### +2026-06-24 05:51:22,097 - use_cached_obj = False +2026-06-24 05:51:22,097 - use_cached_probe = False +2026-06-24 05:51:22,097 - use_cached_pos = False +2026-06-24 05:51:22,097 - +2026-06-24 05:51:22,097 - ### Initializing measurements ### +2026-06-24 05:51:22,097 - Loading measurements from source = 'file' +2026-06-24 05:51:22,097 - Detected measurement file type = '.h5' +2026-06-24 05:51:22,175 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:51:22,175 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:51:22,176 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0049) +2026-06-24 05:51:22,176 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:51:22,176 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:51:22,178 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:51:22,178 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:51:22,178 - Normalizing by max of the 2D mean pattern intensity: 0.003419664 +2026-06-24 05:51:22,179 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:51:22,180 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0178, 1.4417) +2026-06-24 05:51:22,181 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:51:22,182 - Pattern total int. statistics (min, mean, max) = (287.2859, 291.4340, 294.6356), with min/max = 97.5% +2026-06-24 05:51:22,183 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0178, 1.4417) +2026-06-24 05:51:22,183 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:51:22,184 - +2026-06-24 05:51:22,184 - ### Setting up calibration ### +2026-06-24 05:51:22,184 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:51:22,184 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:51:22,184 - Radius of fitted bright field disk (RBF) = 9.15 px with meas_Npix = 128 +2026-06-24 05:51:22,184 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1430 +2026-06-24 05:51:22,184 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:51:22,184 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:51:22,404 - Initial guess: center=(63.68, 63.69), radius=9.15, Gaussian blur std=0.50 +2026-06-24 05:51:22,416 - Final fit: center=(63.68, 63.69), radius=9.15, Gaussian blur std=0.65 +2026-06-24 05:51:22,416 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.31 px with Npix = 128 +2026-06-24 05:51:22,416 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:51:22,417 - +2026-06-24 05:51:22,417 - ### Setting init_variables dict ### +2026-06-24 05:51:22,417 - Derived values given input init_params: +2026-06-24 05:51:22,417 - kv = 200.0 kV +2026-06-24 05:51:22,417 - wavelength = 0.0251 Ang +2026-06-24 05:51:22,417 - conv_angle = 9.125269889831543 mrad +2026-06-24 05:51:22,417 - Npix = 128 px +2026-06-24 05:51:22,417 - dk = 0.0391 Ang^-1 +2026-06-24 05:51:22,417 - kMax = 2.5000 Ang^-1 +2026-06-24 05:51:22,417 - da = 0.9797 mrad +2026-06-24 05:51:22,417 - angleMax = 62.6984 mrad +2026-06-24 05:51:22,417 - RBF = 9.3147 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:51:22,417 - n_alpha = 6.8708 (# conv_angle) +2026-06-24 05:51:22,417 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:51:22,417 - Rayleigh-limited resolution = 1.6765 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:51:22,417 - Real space probe extent = 25.6000 Ang +2026-06-24 05:51:22,417 - +2026-06-24 05:51:22,417 - ### Initializing probe ### +2026-06-24 05:51:22,417 - Loading probe from source = 'simu' +2026-06-24 05:51:22,417 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:51:22,417 - Start simulating STEM probe +2026-06-24 05:51:22,417 - kv = 200.0 kV +2026-06-24 05:51:22,417 - wavelength = 0.0251 Ang +2026-06-24 05:51:22,417 - conv_angle = 9.125269889831543 mrad +2026-06-24 05:51:22,418 - Npix = 128 px +2026-06-24 05:51:22,418 - dk = 0.0391 Ang^-1 +2026-06-24 05:51:22,418 - kMax = 2.5000 Ang^-1 +2026-06-24 05:51:22,418 - alpha_max = 62.6984 mrad +2026-06-24 05:51:22,418 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:51:22,418 - Rayleigh-limited resolution = 1.6765 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:51:22,418 - Real space probe extent = 25.6000 Ang +2026-06-24 05:51:22,418 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:51:22,418 - ------------------------------------------------------------------------------------- +2026-06-24 05:51:22,418 - C1,0 C1 -303.4640 - Defocus (C10 = -df) +2026-06-24 05:51:22,418 - C1,2 A1 46.8990 286.27 2-fold astigmatism +2026-06-24 05:51:22,418 - C2,1 3*B2 126.5750 133.00 Axial coma +2026-06-24 05:51:22,418 - C2,3 A2 143.7400 137.63 3-fold astigmatism +2026-06-24 05:51:22,418 - C3,0 C3 2654738.2500 - Spherical aberration +2026-06-24 05:51:22,418 - C3,2 4*S3 5259.8370 8.61 Axial star aberration +2026-06-24 05:51:22,418 - C3,4 A3 -872.7120 28.67 4-fold astigmatism +2026-06-24 05:51:22,418 - C4,1 4*B4 317267.4380 27.95 Axial coma(4th) +2026-06-24 05:51:22,418 - C4,3 4*D4 479495.3120 349.91 3-lobe aberration +2026-06-24 05:51:22,418 - C4,5 A4 37504.9770 116.91 5-fold astigmatism +2026-06-24 05:51:22,418 - C5,0 C5 -287591040.0000 - Spherical aberration (5th) +2026-06-24 05:51:22,418 - C5,2 6*S5 3065726.0000 293.11 Axial star aberration(5th) +2026-06-24 05:51:22,418 - C5,4 6*R5 4330784.5000 264.92 4-lobe aberration +2026-06-24 05:51:22,418 - C5,6 A5 -19385906.0000 63.82 6-fold astigmatism +2026-06-24 05:51:22,421 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:51:22,421 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:51:22,421 - Creating 5 new probe modes from the major mode +2026-06-24 05:51:22,421 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:51:22,637 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:51:22,638 - Orthogonalizing 6 pmodes +2026-06-24 05:51:22,640 - Sorting 6 pmodes by their intensities +2026-06-24 05:51:22,640 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:51:22,641 - sum(|probe_data|**2) = 291.43, while meas_total_ints (min, mean, max) = (287.2859, 291.4340, 294.6356) +2026-06-24 05:51:22,641 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:51:22,641 - +2026-06-24 05:51:22,641 - ### Initializing probe positions ### +2026-06-24 05:51:22,641 - Loading probe positions from source = 'simu' +2026-06-24 05:51:22,641 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:51:22,641 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3713, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:51:22,642 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:51:22,644 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:51:22,644 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 05:51:22,644 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:51:22,644 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:51:22,644 - +2026-06-24 05:51:22,644 - ### Initializing object ### +2026-06-24 05:51:22,644 - Loading object from source = 'simu' +2026-06-24 05:51:22,644 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:51:22,645 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:51:22,645 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 05:51:22,646 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 05:51:22,646 - +2026-06-24 05:51:22,646 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:51:22,646 - omode_occu (omode) = float32, (1,) +2026-06-24 05:51:22,646 - +2026-06-24 05:51:22,646 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:51:22,646 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:51:22,646 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:51:22,646 - +2026-06-24 05:51:22,647 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:51:22,647 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:51:22,647 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:51:22,647 - +2026-06-24 05:51:22,647 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:51:22,647 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:51:22,647 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:51:22,647 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:51:22,647 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:51:22,647 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 05:51:22,647 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:51:22,647 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:51:22,647 - +2026-06-24 05:51:22,647 - ### Collecting reconstruction provenance ### +2026-06-24 05:51:22,647 - Reconstruction provenance is collected and initialized. +2026-06-24 05:51:22,647 - +2026-06-24 05:51:22,647 - ### Initializing loss function ### +2026-06-24 05:51:22,647 - Active loss types: +2026-06-24 05:51:22,647 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:51:22,647 - +2026-06-24 05:51:22,648 - ### Initializing constraint function ### +2026-06-24 05:51:22,648 - Active constraint types: +2026-06-24 05:51:22,648 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:51:22,648 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:51:22,648 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:51:22,648 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:51:22,648 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:51:22,648 - +2026-06-24 05:51:22,648 - ### Done initializing PtyRADSolver ### +2026-06-24 05:51:22,648 - +2026-06-24 05:51:22,772 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:51:22,772 - +2026-06-24 05:51:22,772 - ### Initializing PtychoModel model ### +2026-06-24 05:51:22,843 - ### PtychoModel optimizable variables ### +2026-06-24 05:51:22,844 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:22,844 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:22,844 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:51:22,844 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:51:22,844 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:51:22,844 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:51:22,844 - +2026-06-24 05:51:22,844 - ### Optimizable variables statitsics ### +2026-06-24 05:51:22,844 - Total measurement values : 4,194,304 +2026-06-24 05:51:22,844 - Total optimizing variables: 267,808 +2026-06-24 05:51:22,844 - Overdetermined ratio : 15.66 +2026-06-24 05:51:22,844 - +2026-06-24 05:51:22,844 - ### Model behavior ### +2026-06-24 05:51:22,844 - Tilt propagator : False +2026-06-24 05:51:22,844 - Change slice thickness : False +2026-06-24 05:51:22,844 - Detector blur : False +2026-06-24 05:51:22,844 - Preload data : True +2026-06-24 05:51:22,844 - On-the-fly meas padding : False +2026-06-24 05:51:22,844 - On-the-fly meas resample : False +2026-06-24 05:51:22,844 - On-the-fly simu match mode: None +2026-06-24 05:51:22,844 - +2026-06-24 05:51:22,885 - ### Done initializing PtychoModel model ### +2026-06-24 05:51:22,885 - +2026-06-24 05:51:22,885 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:51:22,885 - +2026-06-24 05:51:22,885 - ### Generating indices, batches, and output_path ### +2026-06-24 05:51:22,887 - d90 = 35.000 px or 7.000 Ang +2026-06-24 05:51:22,887 - Selecting indices with the 'full' mode +2026-06-24 05:51:23,353 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:51:23,428 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:51:23,428 - Original recon_dir_affixes = ['default'] +2026-06-24 05:51:23,428 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:51:23,434 - Path corrected for compatibility: +2026-06-24 05:51:23,435 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61_C34_-873_phi34_28.7_C41_3.17e+05_phi41_28_C43_4.79e+05_phi43_350_C45_3.75e+04_phi45_117_C50_-2.88e+08_C52_3.07e+06_phi52_293_C54_4.33e+06_phi54_265_C56_-1.94e+07_phi56_63.8 +2026-06-24 05:51:23,435 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8 +2026-06-24 05:51:23,436 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8' is generated! +2026-06-24 05:51:23,581 - +2026-06-24 05:51:23,582 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/20260624_055123_ptyrad_log.txt ### +2026-06-24 05:51:23,582 - +2026-06-24 05:51:23,584 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:51:23,584 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:51:23,584 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:51:24,805 - Iter: 1, Total Loss: 1.0465, loss_single: 1.0465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.440 sec +2026-06-24 05:51:24,842 - Iter: 2, Total Loss: 1.0076, loss_single: 1.0076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:51:24,878 - Iter: 3, Total Loss: 0.9753, loss_single: 0.9753, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:24,913 - Iter: 4, Total Loss: 0.9492, loss_single: 0.9492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:24,949 - Iter: 5, Total Loss: 0.9267, loss_single: 0.9267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:24,985 - Iter: 6, Total Loss: 0.9009, loss_single: 0.9009, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,020 - Iter: 7, Total Loss: 0.8790, loss_single: 0.8790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,056 - Iter: 8, Total Loss: 0.8569, loss_single: 0.8569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:25,092 - Iter: 9, Total Loss: 0.8306, loss_single: 0.8306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,127 - Iter: 10, Total Loss: 0.8048, loss_single: 0.8048, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,163 - Iter: 11, Total Loss: 0.7769, loss_single: 0.7769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:25,198 - Iter: 12, Total Loss: 0.7507, loss_single: 0.7507, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,234 - Iter: 13, Total Loss: 0.7260, loss_single: 0.7260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,270 - Iter: 14, Total Loss: 0.7018, loss_single: 0.7018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:51:25,305 - Iter: 15, Total Loss: 0.6802, loss_single: 0.6802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,341 - Iter: 16, Total Loss: 0.6574, loss_single: 0.6574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,377 - Iter: 17, Total Loss: 0.6329, loss_single: 0.6329, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,413 - Iter: 18, Total Loss: 0.6115, loss_single: 0.6115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,448 - Iter: 19, Total Loss: 0.5968, loss_single: 0.5968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,484 - Iter: 20, Total Loss: 0.5827, loss_single: 0.5827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,520 - Iter: 21, Total Loss: 0.5641, loss_single: 0.5641, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,555 - Iter: 22, Total Loss: 0.5489, loss_single: 0.5489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,591 - Iter: 23, Total Loss: 0.5370, loss_single: 0.5370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:51:25,630 - Iter: 24, Total Loss: 0.5246, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/simulation_data2__sample_000034.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/simulation_data2__sample_000034.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f288f277b2f54a9aadd5f2b3cc032ad9fdfe9735 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/simulation_data2__sample_000034.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.125269889831543 + probe_aberrations: + C10: -303.4635925292969 + C12: 46.89908218383789 + C21: 126.57453918457031 + C23: 143.74000549316406 + C30: 2654738.25 + C32: 5259.8369140625 + C34: -872.7119750976562 + C41: 317267.4375 + C43: 479495.3125 + C45: 37504.9765625 + C50: -287591040.0 + C52: 3065726.0 + C54: 4330784.5 + C56: -19385906.0 + phi12: 286.2666152860076 + phi21: 133.00080397155995 + phi23: 137.63198641753038 + phi32: 8.60857491571908 + phi34: 28.673970833886855 + phi41: 27.95107556496375 + phi43: 349.91173865153377 + phi45: 116.91248462689165 + phi52: 293.1053831736179 + phi54: 264.9218096768542 + phi56: 63.82003084979186 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37125450372695923 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000034_measurement.h5 + key: measurement + random_seed: 20261914 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data2__sample_000034 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b53c6966b7e794b2b015da77bcee66b588dd7f9e75236b36f74a38945fdc38b +size 1064324 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..80726e959e86960cf81e96fb005f908ed09d0349 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000034/c30_small__simulation_data2__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-303_C12_46.9_phi12_286_C21_127_phi21_133_C23_144_phi23_138_C30_2.65e+06_C32_5.26e+03_phi32_8.61.8/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a1a6e963f2c596bae18595eb291fc20b0ac16bbb3eb349bf9ba05e78b94aa211 +size 47990 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/20260624_055252_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/20260624_055252_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c44995564656270d08f3250b4c33625ad8aa2c6d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/20260624_055252_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:52:50,841 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:52:50,841 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:52:50,841 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:52:50,841 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:52:50,841 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:52:50,841 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:52:50,841 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:52:50,841 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:52:50,841 - +2026-06-24 05:52:50,949 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:52:50,949 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:52:50,949 - Accelerator.num_process = 1 +2026-06-24 05:52:50,949 - Accelerator.mixed_precision = no +2026-06-24 05:52:50,959 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:52:50,960 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:52:50,960 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:52:50,960 - +2026-06-24 05:52:50,960 - ### System information ### +2026-06-24 05:52:50,960 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:52:50,960 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:52:50,960 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:52:50,960 - Machine: x86_64 +2026-06-24 05:52:50,960 - Processor: x86_64 +2026-06-24 05:52:50,960 - Available CPU cores: 8 +2026-06-24 05:52:50,960 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:52:50,960 - +2026-06-24 05:52:50,960 - ### GPU information ### +2026-06-24 05:52:50,960 - CUDA Available: True +2026-06-24 05:52:50,960 - CUDA Version: 13.0 +2026-06-24 05:52:50,961 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:52:50,961 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:52:50,961 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:52:50,961 - In addition, Triton does not directly support Windows. +2026-06-24 05:52:50,961 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:52:50,976 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:52:50,976 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:52:50,976 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:52:50,976 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:52:50,976 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:52:50,976 - +2026-06-24 05:52:50,976 - ### Python information ### +2026-06-24 05:52:50,978 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:52:50,978 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:52:50,978 - +2026-06-24 05:52:50,978 - ### Packages information ### +2026-06-24 05:52:50,979 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:52:50,980 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:52:50,980 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:52:50,981 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:52:50,981 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:52:50,982 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:52:50,982 - +2026-06-24 05:52:50,982 - ### Loading params file ### +2026-06-24 05:52:50,982 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000040.yaml +2026-06-24 05:52:50,988 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:52:50,989 - Success! Params file validated and defaults applied. +2026-06-24 05:52:50,989 - +2026-06-24 05:52:50,990 - ### Setting GPU Device ### +2026-06-24 05:52:50,990 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:52:50,990 - +2026-06-24 05:52:50,990 - Random seed: 20261920 provided by params file +2026-06-24 05:52:50,990 - ### Initializing Initializer ### +2026-06-24 05:52:50,990 - init_params are displayed below: +2026-06-24 05:52:50,990 - random_seed: 20261920 +2026-06-24 05:52:50,990 - probe_illum_type: electron +2026-06-24 05:52:50,990 - probe_kv: 200.0 +2026-06-24 05:52:50,990 - probe_conv_angle: 23.375856399536133 +2026-06-24 05:52:50,990 - probe_aberrations: {'C10': -482.266, 'C12': -12.859, 'phi12': 222.94, 'C21': 390.596, 'phi21': 164.431, 'C23': -784.796, 'phi23': 28.997, 'C30': 1339259.375, 'C32': -8240.831, 'phi32': 156.888, 'C34': 5351.021, 'phi34': 244.273, 'C41': -284113.281, 'phi41': 147.046, 'C43': -323718.75, 'phi43': 265.031, 'C45': -267401.781, 'phi45': 161.163, 'C50': 488080160.0, 'C52': -199363.547, 'phi52': 298.835, 'C54': -10626107.0, 'phi54': 97.138, 'C56': 10708407.0, 'phi56': 297.17} +2026-06-24 05:52:50,990 - beam_kev: None +2026-06-24 05:52:50,990 - probe_dRn: None +2026-06-24 05:52:50,990 - probe_Rn: None +2026-06-24 05:52:50,990 - probe_D_H: None +2026-06-24 05:52:50,990 - probe_D_FZP: None +2026-06-24 05:52:50,990 - probe_Ls: None +2026-06-24 05:52:50,991 - meas_Npix: 128 +2026-06-24 05:52:50,991 - pos_N_scans: 256 +2026-06-24 05:52:50,991 - pos_N_scan_slow: 16 +2026-06-24 05:52:50,991 - pos_N_scan_fast: 16 +2026-06-24 05:52:50,991 - pos_scan_step_size: 0.3408413231372833 +2026-06-24 05:52:50,991 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:52:50,991 - probe_pmode_max: 6 +2026-06-24 05:52:50,991 - probe_pmode_init_pows: [0.02] +2026-06-24 05:52:50,991 - obj_omode_max: 1 +2026-06-24 05:52:50,991 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:52:50,991 - obj_Nlayer: 1 +2026-06-24 05:52:50,991 - obj_slice_thickness: 20.0 +2026-06-24 05:52:50,991 - simu_Npix: None +2026-06-24 05:52:50,991 - simu_match_mode: None +2026-06-24 05:52:50,991 - meas_permute: None +2026-06-24 05:52:50,991 - meas_reshape: [256, 128, 128] +2026-06-24 05:52:50,991 - meas_flipT: [0, 0, 0] +2026-06-24 05:52:50,991 - meas_crop: None +2026-06-24 05:52:50,991 - meas_pad: None +2026-06-24 05:52:50,991 - meas_resample: None +2026-06-24 05:52:50,991 - meas_add_source_size: None +2026-06-24 05:52:50,991 - meas_add_detector_blur: None +2026-06-24 05:52:50,991 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:52:50,991 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:52:50,991 - meas_add_poisson_noise: None +2026-06-24 05:52:50,991 - meas_export: None +2026-06-24 05:52:50,991 - probe_permute: None +2026-06-24 05:52:50,991 - probe_z_shift: None +2026-06-24 05:52:50,991 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:52:50,991 - pos_scan_flipT: None +2026-06-24 05:52:50,991 - pos_scan_affine: None +2026-06-24 05:52:50,991 - pos_scan_rand_std: 0.15 +2026-06-24 05:52:50,991 - obj_z_crop: None +2026-06-24 05:52:50,991 - obj_z_pad: None +2026-06-24 05:52:50,991 - obj_z_resample: None +2026-06-24 05:52:50,991 - meas_source: file +2026-06-24 05:52:50,991 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000040_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:52:50,991 - probe_source: simu +2026-06-24 05:52:50,991 - probe_params: None +2026-06-24 05:52:50,991 - pos_source: simu +2026-06-24 05:52:50,992 - pos_params: None +2026-06-24 05:52:50,992 - obj_source: simu +2026-06-24 05:52:50,992 - obj_params: None +2026-06-24 05:52:50,992 - tilt_source: simu +2026-06-24 05:52:50,992 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:52:50,992 - +2026-06-24 05:52:50,992 - ### Initializing cache ### +2026-06-24 05:52:50,992 - use_cached_obj = False +2026-06-24 05:52:50,992 - use_cached_probe = False +2026-06-24 05:52:50,992 - use_cached_pos = False +2026-06-24 05:52:50,992 - +2026-06-24 05:52:50,992 - ### Initializing measurements ### +2026-06-24 05:52:50,992 - Loading measurements from source = 'file' +2026-06-24 05:52:50,992 - Detected measurement file type = '.h5' +2026-06-24 05:52:51,068 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:52:51,068 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:52:51,070 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0011) +2026-06-24 05:52:51,070 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:52:51,070 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:52:51,071 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:52:51,071 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:52:51,072 - Normalizing by max of the 2D mean pattern intensity: 0.00057803263 +2026-06-24 05:52:51,072 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:52:51,074 - meausrements int. statistics (min, mean, max) = (0.0000, 0.1055, 1.9088) +2026-06-24 05:52:51,074 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:52:51,076 - Pattern total int. statistics (min, mean, max) = (1704.2157, 1728.5490, 1756.9636), with min/max = 97.0% +2026-06-24 05:52:51,077 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.1055, 1.9088) +2026-06-24 05:52:51,077 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:52:51,077 - +2026-06-24 05:52:51,077 - ### Setting up calibration ### +2026-06-24 05:52:51,077 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:52:51,077 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:52:51,077 - Radius of fitted bright field disk (RBF) = 23.58 px with meas_Npix = 128 +2026-06-24 05:52:51,077 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3685 +2026-06-24 05:52:51,077 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:52:51,077 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:52:51,297 - Initial guess: center=(63.63, 63.62), radius=23.58, Gaussian blur std=0.50 +2026-06-24 05:52:51,312 - Final fit: center=(63.63, 63.62), radius=23.58, Gaussian blur std=0.76 +2026-06-24 05:52:51,312 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 23.86 px with Npix = 128 +2026-06-24 05:52:51,312 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:52:51,312 - +2026-06-24 05:52:51,312 - ### Setting init_variables dict ### +2026-06-24 05:52:51,312 - Derived values given input init_params: +2026-06-24 05:52:51,312 - kv = 200.0 kV +2026-06-24 05:52:51,312 - wavelength = 0.0251 Ang +2026-06-24 05:52:51,312 - conv_angle = 23.375856399536133 mrad +2026-06-24 05:52:51,312 - Npix = 128 px +2026-06-24 05:52:51,312 - dk = 0.0391 Ang^-1 +2026-06-24 05:52:51,312 - kMax = 2.5000 Ang^-1 +2026-06-24 05:52:51,312 - da = 0.9797 mrad +2026-06-24 05:52:51,312 - angleMax = 62.6984 mrad +2026-06-24 05:52:51,312 - RBF = 23.8612 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:52:51,312 - n_alpha = 2.6822 (# conv_angle) +2026-06-24 05:52:51,312 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:52:51,312 - Rayleigh-limited resolution = 0.6545 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:52:51,312 - Real space probe extent = 25.6000 Ang +2026-06-24 05:52:51,312 - +2026-06-24 05:52:51,312 - ### Initializing probe ### +2026-06-24 05:52:51,312 - Loading probe from source = 'simu' +2026-06-24 05:52:51,312 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:52:51,313 - Start simulating STEM probe +2026-06-24 05:52:51,313 - kv = 200.0 kV +2026-06-24 05:52:51,313 - wavelength = 0.0251 Ang +2026-06-24 05:52:51,313 - conv_angle = 23.375856399536133 mrad +2026-06-24 05:52:51,313 - Npix = 128 px +2026-06-24 05:52:51,313 - dk = 0.0391 Ang^-1 +2026-06-24 05:52:51,313 - kMax = 2.5000 Ang^-1 +2026-06-24 05:52:51,313 - alpha_max = 62.6984 mrad +2026-06-24 05:52:51,313 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:52:51,313 - Rayleigh-limited resolution = 0.6545 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:52:51,313 - Real space probe extent = 25.6000 Ang +2026-06-24 05:52:51,313 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:52:51,313 - ------------------------------------------------------------------------------------ +2026-06-24 05:52:51,313 - C1,0 C1 -482.2660 - Defocus (C10 = -df) +2026-06-24 05:52:51,313 - C1,2 A1 -12.8590 222.94 2-fold astigmatism +2026-06-24 05:52:51,313 - C2,1 3*B2 390.5960 164.43 Axial coma +2026-06-24 05:52:51,313 - C2,3 A2 -784.7960 29.00 3-fold astigmatism +2026-06-24 05:52:51,313 - C3,0 C3 1339259.3750 - Spherical aberration +2026-06-24 05:52:51,313 - C3,2 4*S3 -8240.8310 156.89 Axial star aberration +2026-06-24 05:52:51,313 - C3,4 A3 5351.0210 244.27 4-fold astigmatism +2026-06-24 05:52:51,313 - C4,1 4*B4 -284113.2810 147.05 Axial coma(4th) +2026-06-24 05:52:51,313 - C4,3 4*D4 -323718.7500 265.03 3-lobe aberration +2026-06-24 05:52:51,313 - C4,5 A4 -267401.7810 161.16 5-fold astigmatism +2026-06-24 05:52:51,313 - C5,0 C5 488080160.0000 - Spherical aberration (5th) +2026-06-24 05:52:51,313 - C5,2 6*S5 -199363.5470 298.83 Axial star aberration(5th) +2026-06-24 05:52:51,313 - C5,4 6*R5 -10626107.0000 97.14 4-lobe aberration +2026-06-24 05:52:51,313 - C5,6 A5 10708407.0000 297.17 6-fold astigmatism +2026-06-24 05:52:51,316 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:52:51,316 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:52:51,316 - Creating 5 new probe modes from the major mode +2026-06-24 05:52:51,316 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:52:51,418 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:52:51,419 - Orthogonalizing 6 pmodes +2026-06-24 05:52:51,422 - Sorting 6 pmodes by their intensities +2026-06-24 05:52:51,422 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:52:51,423 - sum(|probe_data|**2) = 1728.55, while meas_total_ints (min, mean, max) = (1704.2157, 1728.5490, 1756.9636) +2026-06-24 05:52:51,423 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:52:51,423 - +2026-06-24 05:52:51,423 - ### Initializing probe positions ### +2026-06-24 05:52:51,423 - Loading probe positions from source = 'simu' +2026-06-24 05:52:51,423 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:52:51,423 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3408, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:52:51,423 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:52:51,425 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:52:51,426 - crop_pos 1st and last px coords (y,x) = ([16, 15], [41, 41]) +2026-06-24 05:52:51,426 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 05:52:51,426 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:52:51,426 - +2026-06-24 05:52:51,426 - ### Initializing object ### +2026-06-24 05:52:51,426 - Loading object from source = 'simu' +2026-06-24 05:52:51,426 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:52:51,427 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:52:51,427 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 184, 186) +2026-06-24 05:52:51,427 - object extent (Z, Y, X) (Ang) = [20. 36.8 37.2] +2026-06-24 05:52:51,428 - +2026-06-24 05:52:51,428 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:52:51,428 - omode_occu (omode) = float32, (1,) +2026-06-24 05:52:51,428 - +2026-06-24 05:52:51,428 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:52:51,428 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:52:51,428 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:52:51,428 - +2026-06-24 05:52:51,428 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:52:51,428 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:52:51,429 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:52:51,429 - +2026-06-24 05:52:51,429 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:52:51,429 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:52:51,429 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:52:51,429 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:52:51,429 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:52:51,429 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (184, 186). +2026-06-24 05:52:51,429 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:52:51,429 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:52:51,429 - +2026-06-24 05:52:51,429 - ### Collecting reconstruction provenance ### +2026-06-24 05:52:51,429 - Reconstruction provenance is collected and initialized. +2026-06-24 05:52:51,429 - +2026-06-24 05:52:51,429 - ### Initializing loss function ### +2026-06-24 05:52:51,429 - Active loss types: +2026-06-24 05:52:51,429 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:52:51,429 - +2026-06-24 05:52:51,429 - ### Initializing constraint function ### +2026-06-24 05:52:51,429 - Active constraint types: +2026-06-24 05:52:51,429 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:52:51,430 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:52:51,430 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:52:51,430 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:52:51,430 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:52:51,430 - +2026-06-24 05:52:51,430 - ### Done initializing PtyRADSolver ### +2026-06-24 05:52:51,430 - +2026-06-24 05:52:51,556 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:52:51,556 - +2026-06-24 05:52:51,557 - ### Initializing PtychoModel model ### +2026-06-24 05:52:51,627 - ### PtychoModel optimizable variables ### +2026-06-24 05:52:51,628 - obja : torch.Size([1, 1, 184, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:52:51,628 - objp : torch.Size([1, 1, 184, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:52:51,628 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:52:51,628 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:52:51,628 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:52:51,628 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:52:51,628 - +2026-06-24 05:52:51,628 - ### Optimizable variables statitsics ### +2026-06-24 05:52:51,628 - Total measurement values : 4,194,304 +2026-06-24 05:52:51,628 - Total optimizing variables: 265,568 +2026-06-24 05:52:51,628 - Overdetermined ratio : 15.79 +2026-06-24 05:52:51,628 - +2026-06-24 05:52:51,628 - ### Model behavior ### +2026-06-24 05:52:51,628 - Tilt propagator : False +2026-06-24 05:52:51,628 - Change slice thickness : False +2026-06-24 05:52:51,628 - Detector blur : False +2026-06-24 05:52:51,628 - Preload data : True +2026-06-24 05:52:51,628 - On-the-fly meas padding : False +2026-06-24 05:52:51,628 - On-the-fly meas resample : False +2026-06-24 05:52:51,628 - On-the-fly simu match mode: None +2026-06-24 05:52:51,628 - +2026-06-24 05:52:51,670 - ### Done initializing PtychoModel model ### +2026-06-24 05:52:51,670 - +2026-06-24 05:52:51,670 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:52:51,671 - +2026-06-24 05:52:51,671 - ### Generating indices, batches, and output_path ### +2026-06-24 05:52:51,672 - d90 = 55.000 px or 11.000 Ang +2026-06-24 05:52:51,672 - Selecting indices with the 'full' mode +2026-06-24 05:52:52,136 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:52:52,209 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:52:52,209 - Original recon_dir_affixes = ['default'] +2026-06-24 05:52:52,209 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:52:52,216 - Path corrected for compatibility: +2026-06-24 05:52:52,216 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8.24e+03_phi32_157_C34_5.35e+03_phi34_244_C41_-2.84e+05_phi41_147_C43_-3.24e+05_phi43_265_C45_-2.67e+05_phi45_161_C50_4.88e+08_C52_-1.99e+05_phi52_299_C54_-1.06e+07_phi54_97.1_C56_1.07e+07_phi56_297 +2026-06-24 05:52:52,216 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297 +2026-06-24 05:52:52,217 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297' is generated! +2026-06-24 05:52:52,365 - +2026-06-24 05:52:52,366 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/20260624_055252_ptyrad_log.txt ### +2026-06-24 05:52:52,366 - +2026-06-24 05:52:52,367 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:52:52,367 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:52:52,367 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:52:53,569 - Iter: 1, Total Loss: 0.5907, loss_single: 0.5907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.441 sec +2026-06-24 05:52:53,607 - Iter: 2, Total Loss: 0.5797, loss_single: 0.5797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:52:53,643 - Iter: 3, Total Loss: 0.5709, loss_single: 0.5709, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:53,678 - Iter: 4, Total Loss: 0.5631, loss_single: 0.5631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,714 - Iter: 5, Total Loss: 0.5555, loss_single: 0.5555, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,750 - Iter: 6, Total Loss: 0.5482, loss_single: 0.5482, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,785 - Iter: 7, Total Loss: 0.5404, loss_single: 0.5404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,821 - Iter: 8, Total Loss: 0.5320, loss_single: 0.5320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,856 - Iter: 9, Total Loss: 0.5247, loss_single: 0.5247, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,892 - Iter: 10, Total Loss: 0.5173, loss_single: 0.5173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,928 - Iter: 11, Total Loss: 0.5101, loss_single: 0.5101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,963 - Iter: 12, Total Loss: 0.5040, loss_single: 0.5040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:53,999 - Iter: 13, Total Loss: 0.4986, loss_single: 0.4986, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,035 - Iter: 14, Total Loss: 0.4937, loss_single: 0.4937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,070 - Iter: 15, Total Loss: 0.4885, loss_single: 0.4885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,106 - Iter: 16, Total Loss: 0.4840, loss_single: 0.4840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,142 - Iter: 17, Total Loss: 0.4795, loss_single: 0.4795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,177 - Iter: 18, Total Loss: 0.4750, loss_single: 0.4750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,213 - Iter: 19, Total Loss: 0.4710, loss_single: 0.4710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,249 - Iter: 20, Total Loss: 0.4662, loss_single: 0.4662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,284 - Iter: 21, Total Loss: 0.4617, loss_single: 0.4617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,320 - Iter: 22, Total Loss: 0.4583, loss_single: 0.4583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,356 - Iter: 23, Total Loss: 0.4552, loss_single: 0.4552, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,391 - Iter: 24, Total Loss: 0.4517, loss_single: 0.4517, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,427 - Iter: 25, Total Loss: 0.4483, loss_single: 0.4483, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,462 - Iter: 26, Total Loss: 0.4454, loss_single: 0.4454, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,498 - Iter: 27, Total Loss: 0.4425, loss_single: 0.4425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,534 - Iter: 28, Total Loss: 0.4394, loss_single: 0.4394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,569 - Iter: 29, Total Loss: 0.4365, loss_single: 0.4365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,608 - Iter: 30, Total Loss: 0.4339, loss_single: 0.4339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:52:54,644 - Iter: 31, Total Loss: 0.4310, loss_single: 0.4310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,680 - Iter: 32, Total Loss: 0.4283, loss_single: 0.4283, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,716 - Iter: 33, Total Loss: 0.4262, loss_single: 0.4262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,752 - Iter: 34, Total Loss: 0.4243, loss_single: 0.4243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,788 - Iter: 35, Total Loss: 0.4220, loss_single: 0.4220, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,823 - Iter: 36, Total Loss: 0.4193, loss_single: 0.4193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,859 - Iter: 37, Total Loss: 0.4174, loss_single: 0.4174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,896 - Iter: 38, Total Loss: 0.4158, loss_single: 0.4158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:54,931 - Iter: 39, Total Loss: 0.4143, loss_single: 0.4143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:54,967 - Iter: 40, Total Loss: 0.4132, loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,005 - Iter: 41, Total Loss: 0.4119, loss_single: 0.4119, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,041 - Iter: 42, Total Loss: 0.4106, loss_single: 0.4106, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,077 - Iter: 43, Total Loss: 0.4094, loss_single: 0.4094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:55,112 - Iter: 44, Total Loss: 0.4085, loss_single: 0.4085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,148 - Iter: 45, Total Loss: 0.4076, loss_single: 0.4076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,184 - Iter: 46, Total Loss: 0.4065, loss_single: 0.4065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,220 - Iter: 47, Total Loss: 0.4053, loss_single: 0.4053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,256 - Iter: 48, Total Loss: 0.4040, loss_single: 0.4040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,292 - Iter: 49, Total Loss: 0.4029, loss_single: 0.4029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:55,327 - Iter: 50, Total Loss: 0.4020, loss_single: 0.4020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,362 - Iter: 51, Total Loss: 0.4014, loss_single: 0.4014, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,399 - Iter: 52, Total Loss: 0.4006, loss_single: 0.4006, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:55,434 - Iter: 53, Total Loss: 0.3998, loss_single: 0.3998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,470 - Iter: 54, Total Loss: 0.3990, loss_single: 0.3990, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:55,506 - Iter: 55, Total Loss: 0.3984, loss_single: 0.3984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:52:55,542 - Iter: 56, Total Loss: 0.3979, loss_single: 0.3979, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,577 - Iter: 57, Total Loss: 0.3972, loss_single: 0.3972, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:52:55,613 - Iter: 58, Total Loss: 0.3964, loss_single: 0.3964, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/simulation_data2__sample_000040.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/simulation_data2__sample_000040.yaml new file mode 100644 index 0000000000000000000000000000000000000000..69019ff054e8d1e65a5fa9f46403052d508cf1b3 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/simulation_data2__sample_000040.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 23.375856399536133 + probe_aberrations: + C10: -482.265869140625 + C12: -12.858790397644043 + C21: 390.5963439941406 + C23: -784.7957153320312 + C30: 1339259.375 + C32: -8240.8310546875 + C34: 5351.021484375 + C41: -284113.28125 + C43: -323718.75 + C45: -267401.78125 + C50: 488080160.0 + C52: -199363.546875 + C54: -10626107.0 + C56: 10708407.0 + phi12: 222.94009292450585 + phi21: 164.4310122676408 + phi23: 28.996782649534584 + phi32: 156.88812017849392 + phi34: 244.2731369479085 + phi41: 147.04572196185714 + phi43: 265.03144787341125 + phi45: 161.16329950454497 + phi52: 298.834600490938 + phi54: 97.13772777205992 + phi56: 297.17049320155604 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3408413231372833 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000040_measurement.h5 + key: measurement + random_seed: 20261920 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data2__sample_000040 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000040/c30_small__simulation_data2__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-482_C12_-12.9_phi12_223_C21_391_phi21_164_C23_-785_phi23_29_C30_1.34e+06_C32_-8..07e+07_phi56_297/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_.5e+06_phi56_236/20260624_055351_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:53:49,815 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:53:49,815 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:53:49,815 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:53:49,815 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:53:49,815 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:53:49,815 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:53:49,815 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:53:49,815 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:53:49,815 - +2026-06-24 05:53:49,922 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:53:49,922 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:53:49,922 - Accelerator.num_process = 1 +2026-06-24 05:53:49,922 - Accelerator.mixed_precision = no +2026-06-24 05:53:49,933 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:53:49,933 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:53:49,933 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:53:49,933 - +2026-06-24 05:53:49,933 - ### System information ### +2026-06-24 05:53:49,933 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:53:49,933 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:53:49,933 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:53:49,933 - Machine: x86_64 +2026-06-24 05:53:49,933 - Processor: x86_64 +2026-06-24 05:53:49,933 - Available CPU cores: 8 +2026-06-24 05:53:49,933 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:53:49,933 - +2026-06-24 05:53:49,933 - ### GPU information ### +2026-06-24 05:53:49,933 - CUDA Available: True +2026-06-24 05:53:49,933 - CUDA Version: 13.0 +2026-06-24 05:53:49,934 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:53:49,934 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:53:49,934 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:53:49,934 - In addition, Triton does not directly support Windows. +2026-06-24 05:53:49,934 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:53:49,962 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:53:49,962 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:53:49,962 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:53:49,962 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:53:49,962 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:53:49,962 - +2026-06-24 05:53:49,962 - ### Python information ### +2026-06-24 05:53:49,964 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:53:49,964 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:53:49,964 - +2026-06-24 05:53:49,964 - ### Packages information ### +2026-06-24 05:53:49,965 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:53:49,965 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:53:49,966 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:53:49,967 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:53:49,967 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:53:49,967 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:53:49,967 - +2026-06-24 05:53:49,967 - ### Loading params file ### +2026-06-24 05:53:49,967 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data2__sample_000044.yaml +2026-06-24 05:53:49,974 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:53:49,975 - Success! Params file validated and defaults applied. +2026-06-24 05:53:49,975 - +2026-06-24 05:53:49,975 - ### Setting GPU Device ### +2026-06-24 05:53:49,975 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:53:49,976 - +2026-06-24 05:53:49,976 - Random seed: 20261924 provided by params file +2026-06-24 05:53:49,976 - ### Initializing Initializer ### +2026-06-24 05:53:49,976 - init_params are displayed below: +2026-06-24 05:53:49,976 - random_seed: 20261924 +2026-06-24 05:53:49,976 - probe_illum_type: electron +2026-06-24 05:53:49,976 - probe_kv: 300.0 +2026-06-24 05:53:49,976 - probe_conv_angle: 19.701650619506836 +2026-06-24 05:53:49,976 - probe_aberrations: {'C10': -579.472, 'C12': -41.302, 'phi12': 96.332, 'C21': 851.037, 'phi21': 37.655, 'C23': 563.462, 'phi23': 0.171, 'C30': 1046348.312, 'C32': 6121.063, 'phi32': 49.849, 'C34': -11078.021, 'phi34': 204.597, 'C41': -296477.125, 'phi41': 95.837, 'C43': -109639.383, 'phi43': 176.93, 'C45': -291143.719, 'phi45': 33.035, 'C50': 446942592.0, 'C52': -17365050.0, 'phi52': 70.701, 'C54': 6397839.5, 'phi54': 114.262, 'C56': -6501659.5, 'phi56': 235.743} +2026-06-24 05:53:49,976 - beam_kev: None +2026-06-24 05:53:49,976 - probe_dRn: None +2026-06-24 05:53:49,976 - probe_Rn: None +2026-06-24 05:53:49,976 - probe_D_H: None +2026-06-24 05:53:49,976 - probe_D_FZP: None +2026-06-24 05:53:49,976 - probe_Ls: None +2026-06-24 05:53:49,976 - meas_Npix: 128 +2026-06-24 05:53:49,976 - pos_N_scans: 256 +2026-06-24 05:53:49,976 - pos_N_scan_slow: 16 +2026-06-24 05:53:49,976 - pos_N_scan_fast: 16 +2026-06-24 05:53:49,976 - pos_scan_step_size: 0.37243330478668213 +2026-06-24 05:53:49,977 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:53:49,977 - probe_pmode_max: 6 +2026-06-24 05:53:49,977 - probe_pmode_init_pows: [0.02] +2026-06-24 05:53:49,977 - obj_omode_max: 1 +2026-06-24 05:53:49,977 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:53:49,977 - obj_Nlayer: 1 +2026-06-24 05:53:49,977 - obj_slice_thickness: 20.0 +2026-06-24 05:53:49,977 - simu_Npix: None +2026-06-24 05:53:49,977 - simu_match_mode: None +2026-06-24 05:53:49,977 - meas_permute: None +2026-06-24 05:53:49,977 - meas_reshape: [256, 128, 128] +2026-06-24 05:53:49,977 - meas_flipT: [0, 0, 0] +2026-06-24 05:53:49,977 - meas_crop: None +2026-06-24 05:53:49,977 - meas_pad: None +2026-06-24 05:53:49,977 - meas_resample: None +2026-06-24 05:53:49,977 - meas_add_source_size: None +2026-06-24 05:53:49,977 - meas_add_detector_blur: None +2026-06-24 05:53:49,977 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:53:49,977 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:53:49,977 - meas_add_poisson_noise: None +2026-06-24 05:53:49,977 - meas_export: None +2026-06-24 05:53:49,977 - probe_permute: None +2026-06-24 05:53:49,977 - probe_z_shift: None +2026-06-24 05:53:49,977 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:53:49,977 - pos_scan_flipT: None +2026-06-24 05:53:49,977 - pos_scan_affine: None +2026-06-24 05:53:49,977 - pos_scan_rand_std: 0.15 +2026-06-24 05:53:49,977 - obj_z_crop: None +2026-06-24 05:53:49,977 - obj_z_pad: None +2026-06-24 05:53:49,977 - obj_z_resample: None +2026-06-24 05:53:49,977 - meas_source: file +2026-06-24 05:53:49,977 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000044_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:53:49,977 - probe_source: simu +2026-06-24 05:53:49,977 - probe_params: None +2026-06-24 05:53:49,977 - pos_source: simu +2026-06-24 05:53:49,977 - pos_params: None +2026-06-24 05:53:49,977 - obj_source: simu +2026-06-24 05:53:49,977 - obj_params: None +2026-06-24 05:53:49,978 - tilt_source: simu +2026-06-24 05:53:49,978 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:53:49,978 - +2026-06-24 05:53:49,978 - ### Initializing cache ### +2026-06-24 05:53:49,978 - use_cached_obj = False +2026-06-24 05:53:49,978 - use_cached_probe = False +2026-06-24 05:53:49,978 - use_cached_pos = False +2026-06-24 05:53:49,978 - +2026-06-24 05:53:49,978 - ### Initializing measurements ### +2026-06-24 05:53:49,978 - Loading measurements from source = 'file' +2026-06-24 05:53:49,978 - Detected measurement file type = '.h5' +2026-06-24 05:53:50,050 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:53:50,050 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:53:50,052 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0012) +2026-06-24 05:53:50,052 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:53:50,052 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:53:50,056 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:53:50,056 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:53:50,056 - Normalizing by max of the 2D mean pattern intensity: 0.00051076652 +2026-06-24 05:53:50,057 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:53:50,058 - meausrements int. statistics (min, mean, max) = (0.0000, 0.1205, 2.2520) +2026-06-24 05:53:50,059 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:53:50,060 - Pattern total int. statistics (min, mean, max) = (1931.5784, 1974.4243, 2010.2089), with min/max = 96.1% +2026-06-24 05:53:50,061 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.1205, 2.2520) +2026-06-24 05:53:50,061 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:53:50,061 - +2026-06-24 05:53:50,061 - ### Setting up calibration ### +2026-06-24 05:53:50,062 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:53:50,062 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:53:50,062 - Radius of fitted bright field disk (RBF) = 25.33 px with meas_Npix = 128 +2026-06-24 05:53:50,062 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3957 +2026-06-24 05:53:50,062 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:53:50,062 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:53:50,293 - Initial guess: center=(63.62, 63.63), radius=25.33, Gaussian blur std=0.50 +2026-06-24 05:53:50,310 - Final fit: center=(63.62, 63.63), radius=25.33, Gaussian blur std=0.85 +2026-06-24 05:53:50,310 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 25.62 px with Npix = 128 +2026-06-24 05:53:50,310 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:53:50,310 - +2026-06-24 05:53:50,310 - ### Setting init_variables dict ### +2026-06-24 05:53:50,310 - Derived values given input init_params: +2026-06-24 05:53:50,310 - kv = 300.0 kV +2026-06-24 05:53:50,310 - wavelength = 0.0197 Ang +2026-06-24 05:53:50,310 - conv_angle = 19.701650619506836 mrad +2026-06-24 05:53:50,310 - Npix = 128 px +2026-06-24 05:53:50,310 - dk = 0.0391 Ang^-1 +2026-06-24 05:53:50,311 - kMax = 2.5000 Ang^-1 +2026-06-24 05:53:50,311 - da = 0.7690 mrad +2026-06-24 05:53:50,311 - angleMax = 49.2187 mrad +2026-06-24 05:53:50,311 - RBF = 25.6184 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:53:50,311 - n_alpha = 2.4982 (# conv_angle) +2026-06-24 05:53:50,311 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:53:50,311 - Rayleigh-limited resolution = 0.6096 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:53:50,311 - Real space probe extent = 25.6000 Ang +2026-06-24 05:53:50,311 - +2026-06-24 05:53:50,311 - ### Initializing probe ### +2026-06-24 05:53:50,311 - Loading probe from source = 'simu' +2026-06-24 05:53:50,311 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:53:50,311 - Start simulating STEM probe +2026-06-24 05:53:50,311 - kv = 300.0 kV +2026-06-24 05:53:50,311 - wavelength = 0.0197 Ang +2026-06-24 05:53:50,311 - conv_angle = 19.701650619506836 mrad +2026-06-24 05:53:50,311 - Npix = 128 px +2026-06-24 05:53:50,311 - dk = 0.0391 Ang^-1 +2026-06-24 05:53:50,311 - kMax = 2.5000 Ang^-1 +2026-06-24 05:53:50,311 - alpha_max = 49.2187 mrad +2026-06-24 05:53:50,311 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:53:50,311 - Rayleigh-limited resolution = 0.6096 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:53:50,311 - Real space probe extent = 25.6000 Ang +2026-06-24 05:53:50,312 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:53:50,312 - ------------------------------------------------------------------------------------ +2026-06-24 05:53:50,312 - C1,0 C1 -579.4720 - Defocus (C10 = -df) +2026-06-24 05:53:50,312 - C1,2 A1 -41.3020 96.33 2-fold astigmatism +2026-06-24 05:53:50,312 - C2,1 3*B2 851.0370 37.66 Axial coma +2026-06-24 05:53:50,312 - C2,3 A2 563.4620 0.17 3-fold astigmatism +2026-06-24 05:53:50,312 - C3,0 C3 1046348.3120 - Spherical aberration +2026-06-24 05:53:50,312 - C3,2 4*S3 6121.0630 49.85 Axial star aberration +2026-06-24 05:53:50,312 - C3,4 A3 -11078.0210 204.60 4-fold astigmatism +2026-06-24 05:53:50,312 - C4,1 4*B4 -296477.1250 95.84 Axial coma(4th) +2026-06-24 05:53:50,312 - C4,3 4*D4 -109639.3830 176.93 3-lobe aberration +2026-06-24 05:53:50,312 - C4,5 A4 -291143.7190 33.03 5-fold astigmatism +2026-06-24 05:53:50,312 - C5,0 C5 446942592.0000 - Spherical aberration (5th) +2026-06-24 05:53:50,312 - C5,2 6*S5 -17365050.0000 70.70 Axial star aberration(5th) +2026-06-24 05:53:50,312 - C5,4 6*R5 6397839.5000 114.26 4-lobe aberration +2026-06-24 05:53:50,312 - C5,6 A5 -6501659.5000 235.74 6-fold astigmatism +2026-06-24 05:53:50,315 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:53:50,315 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:53:50,315 - Creating 5 new probe modes from the major mode +2026-06-24 05:53:50,315 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:53:50,628 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:53:50,630 - Orthogonalizing 6 pmodes +2026-06-24 05:53:50,632 - Sorting 6 pmodes by their intensities +2026-06-24 05:53:50,633 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:53:50,633 - sum(|probe_data|**2) = 1974.42, while meas_total_ints (min, mean, max) = (1931.5784, 1974.4243, 2010.2089) +2026-06-24 05:53:50,633 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:53:50,633 - +2026-06-24 05:53:50,633 - ### Initializing probe positions ### +2026-06-24 05:53:50,633 - Loading probe positions from source = 'simu' +2026-06-24 05:53:50,633 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:53:50,634 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3724, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:53:50,634 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:53:50,636 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:53:50,636 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 05:53:50,636 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:53:50,636 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:53:50,636 - +2026-06-24 05:53:50,636 - ### Initializing object ### +2026-06-24 05:53:50,636 - Loading object from source = 'simu' +2026-06-24 05:53:50,636 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:53:50,637 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:53:50,638 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 05:53:50,638 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 05:53:50,638 - +2026-06-24 05:53:50,638 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:53:50,638 - omode_occu (omode) = float32, (1,) +2026-06-24 05:53:50,638 - +2026-06-24 05:53:50,638 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:53:50,638 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 05:53:50,639 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:53:50,639 - +2026-06-24 05:53:50,639 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:53:50,639 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:53:50,639 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:53:50,639 - +2026-06-24 05:53:50,639 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:53:50,639 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:53:50,639 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:53:50,639 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:53:50,639 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:53:50,639 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 05:53:50,639 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:53:50,639 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:53:50,639 - +2026-06-24 05:53:50,639 - ### Collecting reconstruction provenance ### +2026-06-24 05:53:50,639 - Reconstruction provenance is collected and initialized. +2026-06-24 05:53:50,639 - +2026-06-24 05:53:50,639 - ### Initializing loss function ### +2026-06-24 05:53:50,640 - Active loss types: +2026-06-24 05:53:50,640 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:53:50,640 - +2026-06-24 05:53:50,640 - ### Initializing constraint function ### +2026-06-24 05:53:50,640 - Active constraint types: +2026-06-24 05:53:50,640 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:53:50,640 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:53:50,640 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:53:50,640 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:53:50,640 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:53:50,640 - +2026-06-24 05:53:50,640 - ### Done initializing PtyRADSolver ### +2026-06-24 05:53:50,640 - +2026-06-24 05:53:50,763 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:53:50,763 - +2026-06-24 05:53:50,763 - ### Initializing PtychoModel model ### +2026-06-24 05:53:50,834 - ### PtychoModel optimizable variables ### +2026-06-24 05:53:50,835 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:53:50,835 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:53:50,835 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:53:50,835 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:53:50,835 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:53:50,835 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:53:50,835 - +2026-06-24 05:53:50,835 - ### Optimizable variables statitsics ### +2026-06-24 05:53:50,835 - Total measurement values : 4,194,304 +2026-06-24 05:53:50,835 - Total optimizing variables: 267,808 +2026-06-24 05:53:50,835 - Overdetermined ratio : 15.66 +2026-06-24 05:53:50,835 - +2026-06-24 05:53:50,835 - ### Model behavior ### +2026-06-24 05:53:50,835 - Tilt propagator : False +2026-06-24 05:53:50,835 - Change slice thickness : False +2026-06-24 05:53:50,835 - Detector blur : False +2026-06-24 05:53:50,835 - Preload data : True +2026-06-24 05:53:50,835 - On-the-fly meas padding : False +2026-06-24 05:53:50,835 - On-the-fly meas resample : False +2026-06-24 05:53:50,835 - On-the-fly simu match mode: None +2026-06-24 05:53:50,835 - +2026-06-24 05:53:50,876 - ### Done initializing PtychoModel model ### +2026-06-24 05:53:50,876 - +2026-06-24 05:53:50,876 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:53:50,877 - +2026-06-24 05:53:50,877 - ### Generating indices, batches, and output_path ### +2026-06-24 05:53:50,878 - d90 = 55.000 px or 11.000 Ang +2026-06-24 05:53:50,878 - Selecting indices with the 'full' mode +2026-06-24 05:53:51,339 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:53:51,412 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:53:51,413 - Original recon_dir_affixes = ['default'] +2026-06-24 05:53:51,413 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:53:51,418 - Path corrected for compatibility: +2026-06-24 05:53:51,419 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_6.12e+03_phi32_49.8_C34_-1.11e+04_phi34_205_C41_-2.96e+05_phi41_95.8_C43_-1.1e+05_phi43_177_C45_-2.91e+05_phi45_33_C50_4.47e+08_C52_-1.74e+07_phi52_70.7_C54_6.4e+06_phi54_114_C56_-6.5e+06_phi56_236 +2026-06-24 05:53:51,419 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_.5e+06_phi56_236 +2026-06-24 05:53:51,420 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_.5e+06_phi56_236' is generated! +2026-06-24 05:53:51,570 - +2026-06-24 05:53:51,571 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_.5e+06_phi56_236/20260624_055351_ptyrad_log.txt ### +2026-06-24 05:53:51,571 - +2026-06-24 05:53:51,572 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:53:51,572 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:53:51,573 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:53:52,757 - Iter: 1, Total Loss: 0.4416, loss_single: 0.4416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 05:53:52,795 - Iter: 2, Total Loss: 0.4315, loss_single: 0.4315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:53:52,831 - Iter: 3, Total Loss: 0.4239, loss_single: 0.4239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:52,865 - Iter: 4, Total Loss: 0.4176, loss_single: 0.4176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:52,901 - Iter: 5, Total Loss: 0.4113, loss_single: 0.4113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:52,937 - Iter: 6, Total Loss: 0.4049, loss_single: 0.4049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:52,972 - Iter: 7, Total Loss: 0.3995, loss_single: 0.3995, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,008 - Iter: 8, Total Loss: 0.3934, loss_single: 0.3934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,044 - Iter: 9, Total Loss: 0.3872, loss_single: 0.3872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:53:53,080 - Iter: 10, Total Loss: 0.3824, loss_single: 0.3824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,115 - Iter: 11, Total Loss: 0.3778, loss_single: 0.3778, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,151 - Iter: 12, Total Loss: 0.3733, loss_single: 0.3733, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,186 - Iter: 13, Total Loss: 0.3694, loss_single: 0.3694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,222 - Iter: 14, Total Loss: 0.3655, loss_single: 0.3655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,258 - Iter: 15, Total Loss: 0.3620, loss_single: 0.3620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,293 - Iter: 16, Total Loss: 0.3588, loss_single: 0.3588, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,328 - Iter: 17, Total Loss: 0.3553, loss_single: 0.3553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,364 - Iter: 18, Total Loss: 0.3521, loss_single: 0.3521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,400 - Iter: 19, Total Loss: 0.3496, loss_single: 0.3496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:53:53,435 - Iter: 20, Total Loss: 0.3473, loss_single: 0.3473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,470 - Iter: 21, Total Loss: 0.3453, loss_single: 0.3453, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,505 - Iter: 22, Total Loss: 0.3431, loss_single: 0.3431, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,540 - Iter: 23, Total Loss: 0.3406, loss_single: 0.3406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,576 - Iter: 24, Total Loss: 0.3387, loss_single: 0.3387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,612 - Iter: 25, Total Loss: 0.3370, loss_single: 0.3370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,647 - Iter: 26, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,682 - Iter: 27, Total Loss: 0.3331, loss_single: 0.3331, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,718 - Iter: 28, Total Loss: 0.3317, loss_single: 0.3317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:53:53,754 - Iter: 29, Total Loss: 0.3305, loss_single: 0.3305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,789 - Iter: 30, Total Loss: 0.3291, loss_single: 0.3291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,825 - Iter: 31, Total Loss: 0.3279, loss_single: 0.3279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,860 - Iter: 32, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,896 - Iter: 33, Total Loss: 0.3257, loss_single: 0.3257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,932 - Iter: 34, Total Loss: 0.3246, loss_single: 0.3246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:53,967 - Iter: 35, Total Loss: 0.3238, loss_single: 0.3238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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in 0.035 sec +2026-06-24 05:53:55,210 - Iter: 70, Total Loss: 0.3128, loss_single: 0.3128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:55,245 - Iter: 71, Total Loss: 0.3128, loss_single: 0.3128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:55,281 - Iter: 72, Total Loss: 0.3127, loss_single: 0.3127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:55,316 - Iter: 73, Total Loss: 0.3127, loss_single: 0.3127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:55,351 - Iter: 74, Total Loss: 0.3126, loss_single: 0.3126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:55,386 - Iter: 75, Total Loss: 0.3126, loss_single: 0.3126, loss_poissn: 0.0000, loss_pacbed: 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0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:56,240 - Iter: 99, Total Loss: 0.3118, loss_single: 0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:56,275 - Iter: 100, Total Loss: 0.3117, loss_single: 0.3117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:53:56,387 - Saving summary figures for iter 100 +2026-06-24 05:54:00,209 - ### Finished 100 iterations, averaged iter_t = 0.039108 with std = 0.040 ### +2026-06-24 05:54:00,210 - +2026-06-24 05:54:00,210 - ### The PtyRADSolver is finished in 9.447 sec ### +2026-06-24 05:54:00,210 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044/c30_small__simulation_data2__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-579_C12_-41.3_phi12_96.3_C21_851_phi21_37.7_C23_563_phi23_0.171_C30_1.05e+06_C32_.5e+06_phi56_236/simulation_data2__sample_000044.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 19.701650619506836 + probe_aberrations: + C10: -579.4720458984375 + C12: -41.30218505859375 + C21: 851.036865234375 + C23: 563.46240234375 + C30: 1046348.3125 + C32: 6121.0634765625 + C34: -11078.0205078125 + C41: -296477.125 + C43: -109639.3828125 + C45: -291143.71875 + C50: 446942592.0 + C52: -17365050.0 + C54: 6397839.5 + C56: -6501659.5 + phi12: 96.33218209153777 + phi21: 37.65474410182109 + phi23: 0.17069456488868448 + phi32: 49.84865350628817 + phi34: 204.59721009708642 + phi41: 95.83680896160426 + phi43: 176.92972569400888 + phi45: 33.03458216607643 + phi52: 70.70130300460714 + phi54: 114.26183847417146 + phi56: 235.74255852364274 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37243330478668213 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data2__sample_000044_measurement.h5 + key: measurement + random_seed: 20261924 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data2__sample_000044 + 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sha256:76856ef64a26e9bcaaed621ac8756d6d0902e6deed22e78f77739681532a1588 +size 47426 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/20260624_055506_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/20260624_055506_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..1416084978e34e721559592a63e55ecdde45afe1 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/20260624_055506_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:55:04,499 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:55:04,499 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:55:04,499 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:55:04,499 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:55:04,499 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:55:04,499 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:55:04,499 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:55:04,499 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:55:04,500 - +2026-06-24 05:55:04,608 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:55:04,608 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:55:04,608 - Accelerator.num_process = 1 +2026-06-24 05:55:04,608 - Accelerator.mixed_precision = no +2026-06-24 05:55:04,619 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:55:04,620 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:55:04,620 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:55:04,620 - +2026-06-24 05:55:04,620 - ### System information ### +2026-06-24 05:55:04,620 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:55:04,620 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:55:04,620 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:55:04,620 - Machine: x86_64 +2026-06-24 05:55:04,620 - Processor: x86_64 +2026-06-24 05:55:04,620 - Available CPU cores: 8 +2026-06-24 05:55:04,620 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:55:04,620 - +2026-06-24 05:55:04,620 - ### GPU information ### +2026-06-24 05:55:04,620 - CUDA Available: True +2026-06-24 05:55:04,620 - CUDA Version: 13.0 +2026-06-24 05:55:04,621 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:55:04,621 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:55:04,621 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:55:04,621 - In addition, Triton does not directly support Windows. +2026-06-24 05:55:04,621 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:55:04,647 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:55:04,648 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:55:04,648 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:55:04,648 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:55:04,648 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:55:04,648 - +2026-06-24 05:55:04,648 - ### Python information ### +2026-06-24 05:55:04,649 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:55:04,650 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:55:04,650 - +2026-06-24 05:55:04,650 - ### Packages information ### +2026-06-24 05:55:04,650 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:55:04,651 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:55:04,652 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:55:04,652 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:55:04,653 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:55:04,653 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:55:04,653 - +2026-06-24 05:55:04,653 - ### Loading params file ### +2026-06-24 05:55:04,653 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000001.yaml +2026-06-24 05:55:04,659 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:55:04,660 - Success! Params file validated and defaults applied. +2026-06-24 05:55:04,661 - +2026-06-24 05:55:04,661 - ### Setting GPU Device ### +2026-06-24 05:55:04,661 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:55:04,661 - +2026-06-24 05:55:04,661 - Random seed: 20261929 provided by params file +2026-06-24 05:55:04,661 - ### Initializing Initializer ### +2026-06-24 05:55:04,661 - init_params are displayed below: +2026-06-24 05:55:04,661 - random_seed: 20261929 +2026-06-24 05:55:04,661 - probe_illum_type: electron +2026-06-24 05:55:04,661 - probe_kv: 200.0 +2026-06-24 05:55:04,661 - probe_conv_angle: 9.707653999328613 +2026-06-24 05:55:04,661 - probe_aberrations: {'C10': -481.263, 'C12': -18.648, 'phi12': 57.876, 'C21': -341.989, 'phi21': 35.955, 'C23': -829.852, 'phi23': 138.349, 'C30': 1759872.375, 'C32': 8207.024, 'phi32': 94.677, 'C34': -10451.6, 'phi34': 305.419, 'C41': -358132.844, 'phi41': 69.273, 'C43': 242303.0, 'phi43': 299.119, 'C45': -267820.469, 'phi45': 167.291, 'C50': -391048736.0, 'C52': -3449704.0, 'phi52': 357.225, 'C54': 9351598.0, 'phi54': 255.018, 'C56': -3191085.75, 'phi56': 78.595} +2026-06-24 05:55:04,661 - beam_kev: None +2026-06-24 05:55:04,662 - probe_dRn: None +2026-06-24 05:55:04,662 - probe_Rn: None +2026-06-24 05:55:04,662 - probe_D_H: None +2026-06-24 05:55:04,662 - probe_D_FZP: None +2026-06-24 05:55:04,662 - probe_Ls: None +2026-06-24 05:55:04,662 - meas_Npix: 128 +2026-06-24 05:55:04,662 - pos_N_scans: 256 +2026-06-24 05:55:04,662 - pos_N_scan_slow: 16 +2026-06-24 05:55:04,662 - pos_N_scan_fast: 16 +2026-06-24 05:55:04,662 - pos_scan_step_size: 0.3916201889514923 +2026-06-24 05:55:04,662 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:55:04,662 - probe_pmode_max: 6 +2026-06-24 05:55:04,662 - probe_pmode_init_pows: [0.02] +2026-06-24 05:55:04,662 - obj_omode_max: 1 +2026-06-24 05:55:04,662 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:55:04,662 - obj_Nlayer: 1 +2026-06-24 05:55:04,662 - obj_slice_thickness: 20.0 +2026-06-24 05:55:04,662 - simu_Npix: None +2026-06-24 05:55:04,662 - simu_match_mode: None +2026-06-24 05:55:04,662 - meas_permute: None +2026-06-24 05:55:04,662 - meas_reshape: [256, 128, 128] +2026-06-24 05:55:04,662 - meas_flipT: [0, 0, 0] +2026-06-24 05:55:04,662 - meas_crop: None +2026-06-24 05:55:04,662 - meas_pad: None +2026-06-24 05:55:04,662 - meas_resample: None +2026-06-24 05:55:04,662 - meas_add_source_size: None +2026-06-24 05:55:04,662 - meas_add_detector_blur: None +2026-06-24 05:55:04,662 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:55:04,662 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:55:04,662 - meas_add_poisson_noise: None +2026-06-24 05:55:04,662 - meas_export: None +2026-06-24 05:55:04,662 - probe_permute: None +2026-06-24 05:55:04,662 - probe_z_shift: None +2026-06-24 05:55:04,662 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:55:04,662 - pos_scan_flipT: None +2026-06-24 05:55:04,662 - pos_scan_affine: None +2026-06-24 05:55:04,662 - pos_scan_rand_std: 0.15 +2026-06-24 05:55:04,662 - obj_z_crop: None +2026-06-24 05:55:04,662 - obj_z_pad: None +2026-06-24 05:55:04,662 - obj_z_resample: None +2026-06-24 05:55:04,663 - meas_source: file +2026-06-24 05:55:04,663 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000001_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:55:04,663 - probe_source: simu +2026-06-24 05:55:04,663 - probe_params: None +2026-06-24 05:55:04,663 - pos_source: simu +2026-06-24 05:55:04,663 - pos_params: None +2026-06-24 05:55:04,663 - obj_source: simu +2026-06-24 05:55:04,663 - obj_params: None +2026-06-24 05:55:04,663 - tilt_source: simu +2026-06-24 05:55:04,663 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:55:04,663 - +2026-06-24 05:55:04,663 - ### Initializing cache ### +2026-06-24 05:55:04,663 - use_cached_obj = False +2026-06-24 05:55:04,663 - use_cached_probe = False +2026-06-24 05:55:04,663 - use_cached_pos = False +2026-06-24 05:55:04,663 - +2026-06-24 05:55:04,663 - ### Initializing measurements ### +2026-06-24 05:55:04,663 - Loading measurements from source = 'file' +2026-06-24 05:55:04,663 - Detected measurement file type = '.h5' +2026-06-24 05:55:04,741 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:55:04,741 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:55:04,743 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0043) +2026-06-24 05:55:04,743 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:55:04,743 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:55:04,744 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:55:04,744 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:55:04,745 - Normalizing by max of the 2D mean pattern intensity: 0.002810573 +2026-06-24 05:55:04,746 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:55:04,747 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0217, 1.5226) +2026-06-24 05:55:04,747 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:55:04,749 - Pattern total int. statistics (min, mean, max) = (352.2060, 354.9632, 358.0891), with min/max = 98.4% +2026-06-24 05:55:04,750 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0217, 1.5226) +2026-06-24 05:55:04,750 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:55:04,750 - +2026-06-24 05:55:04,750 - ### Setting up calibration ### +2026-06-24 05:55:04,750 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:55:04,750 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:55:04,750 - Radius of fitted bright field disk (RBF) = 9.87 px with meas_Npix = 128 +2026-06-24 05:55:04,750 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1542 +2026-06-24 05:55:04,750 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:55:04,750 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:55:04,974 - Initial guess: center=(63.64, 63.61), radius=9.87, Gaussian blur std=0.50 +2026-06-24 05:55:04,989 - Final fit: center=(63.64, 63.61), radius=9.87, Gaussian blur std=0.76 +2026-06-24 05:55:04,989 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.91 px with Npix = 128 +2026-06-24 05:55:04,989 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:55:04,989 - +2026-06-24 05:55:04,989 - ### Setting init_variables dict ### +2026-06-24 05:55:04,989 - Derived values given input init_params: +2026-06-24 05:55:04,989 - kv = 200.0 kV +2026-06-24 05:55:04,990 - wavelength = 0.0251 Ang +2026-06-24 05:55:04,990 - conv_angle = 9.707653999328613 mrad +2026-06-24 05:55:04,990 - Npix = 128 px +2026-06-24 05:55:04,990 - dk = 0.0391 Ang^-1 +2026-06-24 05:55:04,990 - kMax = 2.5000 Ang^-1 +2026-06-24 05:55:04,990 - da = 0.9797 mrad +2026-06-24 05:55:04,990 - angleMax = 62.6984 mrad +2026-06-24 05:55:04,990 - RBF = 9.9092 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:55:04,990 - n_alpha = 6.4587 (# conv_angle) +2026-06-24 05:55:04,990 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:55:04,990 - Rayleigh-limited resolution = 1.5759 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:55:04,990 - Real space probe extent = 25.6000 Ang +2026-06-24 05:55:04,990 - +2026-06-24 05:55:04,990 - ### Initializing probe ### +2026-06-24 05:55:04,990 - Loading probe from source = 'simu' +2026-06-24 05:55:04,990 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:55:04,990 - Start simulating STEM probe +2026-06-24 05:55:04,990 - kv = 200.0 kV +2026-06-24 05:55:04,990 - wavelength = 0.0251 Ang +2026-06-24 05:55:04,991 - conv_angle = 9.707653999328613 mrad +2026-06-24 05:55:04,991 - Npix = 128 px +2026-06-24 05:55:04,991 - dk = 0.0391 Ang^-1 +2026-06-24 05:55:04,991 - kMax = 2.5000 Ang^-1 +2026-06-24 05:55:04,991 - alpha_max = 62.6984 mrad +2026-06-24 05:55:04,991 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:55:04,991 - Rayleigh-limited resolution = 1.5759 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:55:04,991 - Real space probe extent = 25.6000 Ang +2026-06-24 05:55:04,991 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:55:04,991 - ------------------------------------------------------------------------------------- +2026-06-24 05:55:04,991 - C1,0 C1 -481.2630 - Defocus (C10 = -df) +2026-06-24 05:55:04,991 - C1,2 A1 -18.6480 57.88 2-fold astigmatism +2026-06-24 05:55:04,991 - C2,1 3*B2 -341.9890 35.95 Axial coma +2026-06-24 05:55:04,991 - C2,3 A2 -829.8520 138.35 3-fold astigmatism +2026-06-24 05:55:04,991 - C3,0 C3 1759872.3750 - Spherical aberration +2026-06-24 05:55:04,991 - C3,2 4*S3 8207.0240 94.68 Axial star aberration +2026-06-24 05:55:04,991 - C3,4 A3 -10451.6000 305.42 4-fold astigmatism +2026-06-24 05:55:04,991 - C4,1 4*B4 -358132.8440 69.27 Axial coma(4th) +2026-06-24 05:55:04,991 - C4,3 4*D4 242303.0000 299.12 3-lobe aberration +2026-06-24 05:55:04,991 - C4,5 A4 -267820.4690 167.29 5-fold astigmatism +2026-06-24 05:55:04,991 - C5,0 C5 -391048736.0000 - Spherical aberration (5th) +2026-06-24 05:55:04,991 - C5,2 6*S5 -3449704.0000 357.23 Axial star aberration(5th) +2026-06-24 05:55:04,991 - C5,4 6*R5 9351598.0000 255.02 4-lobe aberration +2026-06-24 05:55:04,991 - C5,6 A5 -3191085.7500 78.59 6-fold astigmatism +2026-06-24 05:55:04,994 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:55:04,994 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:55:04,994 - Creating 5 new probe modes from the major mode +2026-06-24 05:55:04,994 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:55:05,210 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:55:05,211 - Orthogonalizing 6 pmodes +2026-06-24 05:55:05,214 - Sorting 6 pmodes by their intensities +2026-06-24 05:55:05,214 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:55:05,215 - sum(|probe_data|**2) = 354.96, while meas_total_ints (min, mean, max) = (352.2060, 354.9632, 358.0891) +2026-06-24 05:55:05,215 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:55:05,215 - +2026-06-24 05:55:05,215 - ### Initializing probe positions ### +2026-06-24 05:55:05,215 - Loading probe positions from source = 'simu' +2026-06-24 05:55:05,215 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:55:05,215 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3916, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:55:05,216 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:55:05,218 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:55:05,218 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 44]) +2026-06-24 05:55:05,218 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 05:55:05,218 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:55:05,218 - +2026-06-24 05:55:05,218 - ### Initializing object ### +2026-06-24 05:55:05,218 - Loading object from source = 'simu' +2026-06-24 05:55:05,218 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:55:05,219 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:55:05,219 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 189, 189) +2026-06-24 05:55:05,220 - object extent (Z, Y, X) (Ang) = [20. 37.8 37.8] +2026-06-24 05:55:05,220 - +2026-06-24 05:55:05,220 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:55:05,220 - omode_occu (omode) = float32, (1,) +2026-06-24 05:55:05,220 - +2026-06-24 05:55:05,220 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:55:05,220 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:55:05,220 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:55:05,220 - +2026-06-24 05:55:05,220 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:55:05,221 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:55:05,221 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:55:05,221 - +2026-06-24 05:55:05,221 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:55:05,221 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:55:05,221 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:55:05,221 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:55:05,221 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:55:05,221 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (189, 189). +2026-06-24 05:55:05,221 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:55:05,221 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:55:05,221 - +2026-06-24 05:55:05,221 - ### Collecting reconstruction provenance ### +2026-06-24 05:55:05,221 - Reconstruction provenance is collected and initialized. +2026-06-24 05:55:05,221 - +2026-06-24 05:55:05,221 - ### Initializing loss function ### +2026-06-24 05:55:05,221 - Active loss types: +2026-06-24 05:55:05,221 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:55:05,221 - +2026-06-24 05:55:05,221 - ### Initializing constraint function ### +2026-06-24 05:55:05,221 - Active constraint types: +2026-06-24 05:55:05,222 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:55:05,222 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:55:05,222 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:55:05,222 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:55:05,222 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:55:05,222 - +2026-06-24 05:55:05,222 - ### Done initializing PtyRADSolver ### +2026-06-24 05:55:05,222 - +2026-06-24 05:55:05,346 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:55:05,346 - +2026-06-24 05:55:05,346 - ### Initializing PtychoModel model ### +2026-06-24 05:55:05,418 - ### PtychoModel optimizable variables ### +2026-06-24 05:55:05,418 - obja : torch.Size([1, 1, 189, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:55:05,418 - objp : torch.Size([1, 1, 189, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:55:05,418 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:55:05,418 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:55:05,418 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:55:05,418 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:55:05,419 - +2026-06-24 05:55:05,419 - ### Optimizable variables statitsics ### +2026-06-24 05:55:05,419 - Total measurement values : 4,194,304 +2026-06-24 05:55:05,419 - Total optimizing variables: 268,562 +2026-06-24 05:55:05,419 - Overdetermined ratio : 15.62 +2026-06-24 05:55:05,419 - +2026-06-24 05:55:05,419 - ### Model behavior ### +2026-06-24 05:55:05,419 - Tilt propagator : False +2026-06-24 05:55:05,419 - Change slice thickness : False +2026-06-24 05:55:05,419 - Detector blur : False +2026-06-24 05:55:05,419 - Preload data : True +2026-06-24 05:55:05,419 - On-the-fly meas padding : False +2026-06-24 05:55:05,419 - On-the-fly meas resample : False +2026-06-24 05:55:05,419 - On-the-fly simu match mode: None +2026-06-24 05:55:05,419 - +2026-06-24 05:55:05,460 - ### Done initializing PtychoModel model ### +2026-06-24 05:55:05,460 - +2026-06-24 05:55:05,460 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:55:05,461 - +2026-06-24 05:55:05,461 - ### Generating indices, batches, and output_path ### +2026-06-24 05:55:05,462 - d90 = 47.000 px or 9.400 Ang +2026-06-24 05:55:05,462 - Selecting indices with the 'full' mode +2026-06-24 05:55:05,928 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:55:06,001 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:55:06,001 - Original recon_dir_affixes = ['default'] +2026-06-24 05:55:06,001 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:55:06,008 - Path corrected for compatibility: +2026-06-24 05:55:06,008 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_94.7_C34_-1.05e+04_phi34_305_C41_-3.58e+05_phi41_69.3_C43_2.42e+05_phi43_299_C45_-2.68e+05_phi45_167_C50_-3.91e+08_C52_-3.45e+06_phi52_357_C54_9.35e+06_phi54_255_C56_-3.19e+06_phi56_78.6 +2026-06-24 05:55:06,008 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6 +2026-06-24 05:55:06,009 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6' is generated! +2026-06-24 05:55:06,155 - +2026-06-24 05:55:06,156 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/20260624_055506_ptyrad_log.txt ### +2026-06-24 05:55:06,156 - +2026-06-24 05:55:06,158 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:55:06,158 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:55:06,158 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:55:07,358 - Iter: 1, Total Loss: 1.1712, loss_single: 1.1712, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 05:55:07,395 - Iter: 2, Total Loss: 1.1364, loss_single: 1.1364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:55:07,431 - Iter: 3, Total Loss: 1.1082, loss_single: 1.1082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,467 - Iter: 4, Total Loss: 1.0829, loss_single: 1.0829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,502 - Iter: 5, Total Loss: 1.0590, loss_single: 1.0590, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,537 - Iter: 6, Total Loss: 1.0356, loss_single: 1.0356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,573 - Iter: 7, Total Loss: 1.0094, loss_single: 1.0094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:55:07,609 - Iter: 8, Total Loss: 0.9834, loss_single: 0.9834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,645 - Iter: 9, Total Loss: 0.9617, loss_single: 0.9617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,680 - Iter: 10, Total Loss: 0.9392, loss_single: 0.9392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,715 - Iter: 11, Total Loss: 0.9145, loss_single: 0.9145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,751 - Iter: 12, Total Loss: 0.8900, loss_single: 0.8900, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,787 - Iter: 13, Total Loss: 0.8639, loss_single: 0.8639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,822 - Iter: 14, Total Loss: 0.8381, loss_single: 0.8381, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,857 - Iter: 15, Total Loss: 0.8131, loss_single: 0.8131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,893 - Iter: 16, Total Loss: 0.7860, loss_single: 0.7860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,928 - Iter: 17, Total Loss: 0.7602, loss_single: 0.7602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:07,964 - Iter: 18, Total Loss: 0.7410, loss_single: 0.7410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,000 - Iter: 19, Total Loss: 0.7236, loss_single: 0.7236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,035 - Iter: 20, Total Loss: 0.7040, loss_single: 0.7040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,071 - Iter: 21, Total Loss: 0.6836, loss_single: 0.6836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,106 - Iter: 22, Total Loss: 0.6608, loss_single: 0.6608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,142 - Iter: 23, Total Loss: 0.6417, loss_single: 0.6417, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:55:08,177 - Iter: 24, Total Loss: 0.6241, loss_single: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/simulation_data3__sample_000001.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7d822370bc86182650e4f777fa6474aa2235351a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001/c30_small__simulation_data3__sample_000001_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-481_C12_-18.6_phi12_57.9_C21_-342_phi21_36_C23_-830_phi23_138_C30_1.76e+06_C32_8.21e+03_phi32_9.6/simulation_data3__sample_000001.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.707653999328613 + probe_aberrations: + C10: -481.2629089355469 + C12: -18.64815330505371 + C21: -341.98858642578125 + C23: -829.8519897460938 + C30: 1759872.375 + C32: 8207.0244140625 + C34: -10451.599609375 + C41: -358132.84375 + C43: 242303.0 + C45: -267820.46875 + C50: -391048736.0 + C52: -3449704.0 + C54: 9351598.0 + C56: -3191085.75 + phi12: 57.87644804537096 + phi21: 35.95461439475653 + phi23: 138.3494158275702 + phi32: 94.6769062367527 + phi34: 305.4187935678035 + phi41: 69.27319241142752 + phi43: 299.1185724358704 + phi45: 167.29074417123346 + phi52: 357.2245763090563 + phi54: 255.01787145579564 + phi56: 78.59507557179593 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3916201889514923 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000001_measurement.h5 + key: measurement + random_seed: 20261929 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000001 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000001 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000005/c30_small__simulation_data3__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_36_phi12_292_C21_-578_phi21_9.2_C23_365_phi23_146_C30_1.08e+06_C32_-1.18.86e+07_phi56_340/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:60b55e82aef9f77d56ee6235e6c90955910cadd2fb2c15b37cc0c90fbd4e3178 +size 1129862 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000005/c30_small__simulation_data3__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_36_phi12_292_C21_-578_phi21_9.2_C23_365_phi23_146_C30_1.08e+06_C32_-1.18.86e+07_phi56_340/summary_scan_pos_iter0100.png 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sha256:70cf9f6bf586efd743b8122d10374f205d3af0709c850df4431951510e535798 +size 49151 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/20260624_055634_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/20260624_055634_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..51258647bd893c8b6573bbb5755e679163d8f51a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/20260624_055634_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:56:33,223 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:56:33,223 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:56:33,223 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:56:33,223 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:56:33,223 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:56:33,223 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:56:33,223 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:56:33,223 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:56:33,223 - +2026-06-24 05:56:33,333 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:56:33,333 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:56:33,333 - Accelerator.num_process = 1 +2026-06-24 05:56:33,333 - Accelerator.mixed_precision = no +2026-06-24 05:56:33,343 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:56:33,343 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:56:33,343 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:56:33,343 - +2026-06-24 05:56:33,343 - ### System information ### +2026-06-24 05:56:33,343 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:56:33,343 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:56:33,343 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:56:33,343 - Machine: x86_64 +2026-06-24 05:56:33,343 - Processor: x86_64 +2026-06-24 05:56:33,343 - Available CPU cores: 8 +2026-06-24 05:56:33,343 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:56:33,343 - +2026-06-24 05:56:33,343 - ### GPU information ### +2026-06-24 05:56:33,344 - CUDA Available: True +2026-06-24 05:56:33,344 - CUDA Version: 13.0 +2026-06-24 05:56:33,344 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:56:33,344 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:56:33,344 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:56:33,344 - In addition, Triton does not directly support Windows. +2026-06-24 05:56:33,344 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:56:33,371 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:56:33,371 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:56:33,371 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:56:33,371 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:56:33,371 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:56:33,371 - +2026-06-24 05:56:33,371 - ### Python information ### +2026-06-24 05:56:33,373 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:56:33,373 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:56:33,373 - +2026-06-24 05:56:33,373 - ### Packages information ### +2026-06-24 05:56:33,374 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:56:33,375 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:56:33,375 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:56:33,376 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:56:33,377 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:56:33,377 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:56:33,377 - +2026-06-24 05:56:33,377 - ### Loading params file ### +2026-06-24 05:56:33,377 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000007.yaml +2026-06-24 05:56:33,383 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:56:33,384 - Success! Params file validated and defaults applied. +2026-06-24 05:56:33,384 - +2026-06-24 05:56:33,384 - ### Setting GPU Device ### +2026-06-24 05:56:33,384 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:56:33,384 - +2026-06-24 05:56:33,384 - Random seed: 20261935 provided by params file +2026-06-24 05:56:33,385 - ### Initializing Initializer ### +2026-06-24 05:56:33,385 - init_params are displayed below: +2026-06-24 05:56:33,385 - random_seed: 20261935 +2026-06-24 05:56:33,385 - probe_illum_type: electron +2026-06-24 05:56:33,385 - probe_kv: 160.0 +2026-06-24 05:56:33,385 - probe_conv_angle: 14.522917747497559 +2026-06-24 05:56:33,385 - probe_aberrations: {'C10': -234.988, 'C12': -32.697, 'phi12': 24.074, 'C21': 554.182, 'phi21': 351.395, 'C23': 545.467, 'phi23': 268.155, 'C30': 2564086.5, 'C32': 3878.129, 'phi32': 184.898, 'C34': -7615.0, 'phi34': 106.21, 'C41': 65970.133, 'phi41': 55.864, 'C43': 153583.188, 'phi43': 359.774, 'C45': -338596.188, 'phi45': 40.609, 'C50': -440730912.0, 'C52': -11856964.0, 'phi52': 228.231, 'C54': 16450422.0, 'phi54': 147.867, 'C56': 6760985.5, 'phi56': 245.637} +2026-06-24 05:56:33,385 - beam_kev: None +2026-06-24 05:56:33,385 - probe_dRn: None +2026-06-24 05:56:33,385 - probe_Rn: None +2026-06-24 05:56:33,385 - probe_D_H: None +2026-06-24 05:56:33,385 - probe_D_FZP: None +2026-06-24 05:56:33,385 - probe_Ls: None +2026-06-24 05:56:33,385 - meas_Npix: 128 +2026-06-24 05:56:33,385 - pos_N_scans: 256 +2026-06-24 05:56:33,385 - pos_N_scan_slow: 16 +2026-06-24 05:56:33,385 - pos_N_scan_fast: 16 +2026-06-24 05:56:33,385 - pos_scan_step_size: 0.4370545744895935 +2026-06-24 05:56:33,385 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:56:33,385 - probe_pmode_max: 6 +2026-06-24 05:56:33,385 - probe_pmode_init_pows: [0.02] +2026-06-24 05:56:33,386 - obj_omode_max: 1 +2026-06-24 05:56:33,386 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:56:33,386 - obj_Nlayer: 1 +2026-06-24 05:56:33,386 - obj_slice_thickness: 20.0 +2026-06-24 05:56:33,386 - simu_Npix: None +2026-06-24 05:56:33,386 - simu_match_mode: None +2026-06-24 05:56:33,386 - meas_permute: None +2026-06-24 05:56:33,386 - meas_reshape: [256, 128, 128] +2026-06-24 05:56:33,386 - meas_flipT: [0, 0, 0] +2026-06-24 05:56:33,386 - meas_crop: None +2026-06-24 05:56:33,386 - meas_pad: None +2026-06-24 05:56:33,386 - meas_resample: None +2026-06-24 05:56:33,386 - meas_add_source_size: None +2026-06-24 05:56:33,386 - meas_add_detector_blur: None +2026-06-24 05:56:33,386 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:56:33,386 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:56:33,386 - meas_add_poisson_noise: None +2026-06-24 05:56:33,386 - meas_export: None +2026-06-24 05:56:33,386 - probe_permute: None +2026-06-24 05:56:33,386 - probe_z_shift: None +2026-06-24 05:56:33,386 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:56:33,386 - pos_scan_flipT: None +2026-06-24 05:56:33,386 - pos_scan_affine: None +2026-06-24 05:56:33,386 - pos_scan_rand_std: 0.15 +2026-06-24 05:56:33,386 - obj_z_crop: None +2026-06-24 05:56:33,386 - obj_z_pad: None +2026-06-24 05:56:33,386 - obj_z_resample: None +2026-06-24 05:56:33,386 - meas_source: file +2026-06-24 05:56:33,386 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000007_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:56:33,386 - probe_source: simu +2026-06-24 05:56:33,386 - probe_params: None +2026-06-24 05:56:33,386 - pos_source: simu +2026-06-24 05:56:33,386 - pos_params: None +2026-06-24 05:56:33,386 - obj_source: simu +2026-06-24 05:56:33,386 - obj_params: None +2026-06-24 05:56:33,386 - tilt_source: simu +2026-06-24 05:56:33,386 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:56:33,386 - +2026-06-24 05:56:33,386 - ### Initializing cache ### +2026-06-24 05:56:33,386 - use_cached_obj = False +2026-06-24 05:56:33,387 - use_cached_probe = False +2026-06-24 05:56:33,387 - use_cached_pos = False +2026-06-24 05:56:33,387 - +2026-06-24 05:56:33,387 - ### Initializing measurements ### +2026-06-24 05:56:33,387 - Loading measurements from source = 'file' +2026-06-24 05:56:33,387 - Detected measurement file type = '.h5' +2026-06-24 05:56:33,464 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:56:33,464 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:56:33,466 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0034) +2026-06-24 05:56:33,466 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:56:33,466 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:56:33,467 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:56:33,467 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:56:33,468 - Normalizing by max of the 2D mean pattern intensity: 0.0017981209 +2026-06-24 05:56:33,468 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:56:33,469 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0339, 1.8759) +2026-06-24 05:56:33,470 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:56:33,471 - Pattern total int. statistics (min, mean, max) = (551.9724, 555.4008, 558.2913), with min/max = 98.9% +2026-06-24 05:56:33,472 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0339, 1.8759) +2026-06-24 05:56:33,473 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:56:33,473 - +2026-06-24 05:56:33,473 - ### Setting up calibration ### +2026-06-24 05:56:33,473 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:56:33,473 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:56:33,473 - Radius of fitted bright field disk (RBF) = 12.98 px with meas_Npix = 128 +2026-06-24 05:56:33,473 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2028 +2026-06-24 05:56:33,473 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:56:33,473 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:56:33,694 - Initial guess: center=(63.62, 63.61), radius=12.98, Gaussian blur std=0.50 +2026-06-24 05:56:33,706 - Final fit: center=(63.62, 63.61), radius=12.98, Gaussian blur std=0.61 +2026-06-24 05:56:33,706 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.04 px with Npix = 128 +2026-06-24 05:56:33,707 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:56:33,707 - +2026-06-24 05:56:33,707 - ### Setting init_variables dict ### +2026-06-24 05:56:33,707 - Derived values given input init_params: +2026-06-24 05:56:33,707 - kv = 160.0 kV +2026-06-24 05:56:33,707 - wavelength = 0.0285 Ang +2026-06-24 05:56:33,707 - conv_angle = 14.522917747497559 mrad +2026-06-24 05:56:33,707 - Npix = 128 px +2026-06-24 05:56:33,707 - dk = 0.0391 Ang^-1 +2026-06-24 05:56:33,707 - kMax = 2.5000 Ang^-1 +2026-06-24 05:56:33,707 - da = 1.1137 mrad +2026-06-24 05:56:33,707 - angleMax = 71.2751 mrad +2026-06-24 05:56:33,707 - RBF = 13.0405 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:56:33,707 - n_alpha = 4.9078 (# conv_angle) +2026-06-24 05:56:33,707 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:56:33,707 - Rayleigh-limited resolution = 1.1975 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:56:33,707 - Real space probe extent = 25.6000 Ang +2026-06-24 05:56:33,707 - +2026-06-24 05:56:33,707 - ### Initializing probe ### +2026-06-24 05:56:33,707 - Loading probe from source = 'simu' +2026-06-24 05:56:33,707 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:56:33,707 - Start simulating STEM probe +2026-06-24 05:56:33,707 - kv = 160.0 kV +2026-06-24 05:56:33,707 - wavelength = 0.0285 Ang +2026-06-24 05:56:33,707 - conv_angle = 14.522917747497559 mrad +2026-06-24 05:56:33,708 - Npix = 128 px +2026-06-24 05:56:33,708 - dk = 0.0391 Ang^-1 +2026-06-24 05:56:33,708 - kMax = 2.5000 Ang^-1 +2026-06-24 05:56:33,708 - alpha_max = 71.2751 mrad +2026-06-24 05:56:33,708 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:56:33,708 - Rayleigh-limited resolution = 1.1975 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:56:33,708 - Real space probe extent = 25.6000 Ang +2026-06-24 05:56:33,708 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:56:33,708 - ------------------------------------------------------------------------------------- +2026-06-24 05:56:33,708 - C1,0 C1 -234.9880 - Defocus (C10 = -df) +2026-06-24 05:56:33,708 - C1,2 A1 -32.6970 24.07 2-fold astigmatism +2026-06-24 05:56:33,708 - C2,1 3*B2 554.1820 351.39 Axial coma +2026-06-24 05:56:33,708 - C2,3 A2 545.4670 268.15 3-fold astigmatism +2026-06-24 05:56:33,708 - C3,0 C3 2564086.5000 - Spherical aberration +2026-06-24 05:56:33,708 - C3,2 4*S3 3878.1290 184.90 Axial star aberration +2026-06-24 05:56:33,708 - C3,4 A3 -7615.0000 106.21 4-fold astigmatism +2026-06-24 05:56:33,708 - C4,1 4*B4 65970.1330 55.86 Axial coma(4th) +2026-06-24 05:56:33,708 - C4,3 4*D4 153583.1880 359.77 3-lobe aberration +2026-06-24 05:56:33,708 - C4,5 A4 -338596.1880 40.61 5-fold astigmatism +2026-06-24 05:56:33,708 - C5,0 C5 -440730912.0000 - Spherical aberration (5th) +2026-06-24 05:56:33,708 - C5,2 6*S5 -11856964.0000 228.23 Axial star aberration(5th) +2026-06-24 05:56:33,708 - C5,4 6*R5 16450422.0000 147.87 4-lobe aberration +2026-06-24 05:56:33,708 - C5,6 A5 6760985.5000 245.64 6-fold astigmatism +2026-06-24 05:56:33,711 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:56:33,711 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:56:33,711 - Creating 5 new probe modes from the major mode +2026-06-24 05:56:33,711 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:56:33,814 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:56:33,815 - Orthogonalizing 6 pmodes +2026-06-24 05:56:33,817 - Sorting 6 pmodes by their intensities +2026-06-24 05:56:33,818 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:56:33,818 - sum(|probe_data|**2) = 555.40, while meas_total_ints (min, mean, max) = (551.9724, 555.4008, 558.2913) +2026-06-24 05:56:33,818 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:56:33,818 - +2026-06-24 05:56:33,818 - ### Initializing probe positions ### +2026-06-24 05:56:33,818 - Loading probe positions from source = 'simu' +2026-06-24 05:56:33,818 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:56:33,818 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4371, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:56:33,819 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:56:33,821 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:56:33,821 - crop_pos 1st and last px coords (y,x) = ([16, 15], [48, 48]) +2026-06-24 05:56:33,821 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 05:56:33,821 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:56:33,821 - +2026-06-24 05:56:33,821 - ### Initializing object ### +2026-06-24 05:56:33,821 - Loading object from source = 'simu' +2026-06-24 05:56:33,821 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:56:33,822 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:56:33,822 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 05:56:33,823 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 05:56:33,823 - +2026-06-24 05:56:33,823 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:56:33,823 - omode_occu (omode) = float32, (1,) +2026-06-24 05:56:33,823 - +2026-06-24 05:56:33,823 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:56:33,823 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:56:33,823 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:56:33,824 - +2026-06-24 05:56:33,824 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:56:33,824 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:56:33,824 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:56:33,824 - +2026-06-24 05:56:33,824 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:56:33,824 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:56:33,824 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:56:33,824 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:56:33,824 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:56:33,824 - crop positions (yx_min=[15 15], yx_max=[177 177]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 05:56:33,824 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:56:33,824 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:56:33,824 - +2026-06-24 05:56:33,824 - ### Collecting reconstruction provenance ### +2026-06-24 05:56:33,824 - Reconstruction provenance is collected and initialized. +2026-06-24 05:56:33,824 - +2026-06-24 05:56:33,824 - ### Initializing loss function ### +2026-06-24 05:56:33,824 - Active loss types: +2026-06-24 05:56:33,824 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:56:33,824 - +2026-06-24 05:56:33,825 - ### Initializing constraint function ### +2026-06-24 05:56:33,825 - Active constraint types: +2026-06-24 05:56:33,825 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:56:33,825 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:56:33,825 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:56:33,825 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:56:33,825 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:56:33,825 - +2026-06-24 05:56:33,825 - ### Done initializing PtyRADSolver ### +2026-06-24 05:56:33,825 - +2026-06-24 05:56:33,952 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:56:33,952 - +2026-06-24 05:56:33,952 - ### Initializing PtychoModel model ### +2026-06-24 05:56:34,024 - ### PtychoModel optimizable variables ### +2026-06-24 05:56:34,024 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:34,024 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:34,024 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:56:34,024 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:56:34,024 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:56:34,024 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:34,024 - +2026-06-24 05:56:34,024 - ### Optimizable variables statitsics ### +2026-06-24 05:56:34,024 - Total measurement values : 4,194,304 +2026-06-24 05:56:34,024 - Total optimizing variables: 272,392 +2026-06-24 05:56:34,024 - Overdetermined ratio : 15.40 +2026-06-24 05:56:34,024 - +2026-06-24 05:56:34,024 - ### Model behavior ### +2026-06-24 05:56:34,025 - Tilt propagator : False +2026-06-24 05:56:34,025 - Change slice thickness : False +2026-06-24 05:56:34,025 - Detector blur : False +2026-06-24 05:56:34,025 - Preload data : True +2026-06-24 05:56:34,025 - On-the-fly meas padding : False +2026-06-24 05:56:34,025 - On-the-fly meas resample : False +2026-06-24 05:56:34,025 - On-the-fly simu match mode: None +2026-06-24 05:56:34,025 - +2026-06-24 05:56:34,066 - ### Done initializing PtychoModel model ### +2026-06-24 05:56:34,066 - +2026-06-24 05:56:34,066 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:56:34,067 - +2026-06-24 05:56:34,067 - ### Generating indices, batches, and output_path ### +2026-06-24 05:56:34,068 - d90 = 37.000 px or 7.400 Ang +2026-06-24 05:56:34,068 - Selecting indices with the 'full' mode +2026-06-24 05:56:34,530 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:56:34,605 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:56:34,605 - Original recon_dir_affixes = ['default'] +2026-06-24 05:56:34,605 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:56:34,611 - Path corrected for compatibility: +2026-06-24 05:56:34,611 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3.88e+03_phi32_185_C34_-7.62e+03_phi34_106_C41_6.6e+04_phi41_55.9_C43_1.54e+05_phi43_360_C45_-3.39e+05_phi45_40.6_C50_-4.41e+08_C52_-1.19e+07_phi52_228_C54_1.65e+07_phi54_148_C56_6.76e+06_phi56_246 +2026-06-24 05:56:34,611 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246 +2026-06-24 05:56:34,612 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246' is generated! +2026-06-24 05:56:34,759 - +2026-06-24 05:56:34,760 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/20260624_055634_ptyrad_log.txt ### +2026-06-24 05:56:34,760 - +2026-06-24 05:56:34,761 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:56:34,762 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:56:34,762 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:56:35,957 - Iter: 1, Total Loss: 0.9181, loss_single: 0.9181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 05:56:35,994 - Iter: 2, Total Loss: 0.8919, loss_single: 0.8919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:56:36,030 - Iter: 3, Total Loss: 0.8722, loss_single: 0.8722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,065 - Iter: 4, Total Loss: 0.8532, loss_single: 0.8532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,101 - Iter: 5, Total Loss: 0.8344, loss_single: 0.8344, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,136 - Iter: 6, Total Loss: 0.8149, loss_single: 0.8149, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,172 - Iter: 7, Total Loss: 0.7950, loss_single: 0.7950, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,207 - Iter: 8, Total Loss: 0.7747, loss_single: 0.7747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,242 - Iter: 9, Total Loss: 0.7520, loss_single: 0.7520, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,277 - Iter: 10, Total Loss: 0.7294, loss_single: 0.7294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,313 - Iter: 11, Total Loss: 0.7076, loss_single: 0.7076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,348 - Iter: 12, Total Loss: 0.6866, loss_single: 0.6866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,383 - Iter: 13, Total Loss: 0.6684, loss_single: 0.6684, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:36,418 - Iter: 14, Total Loss: 0.6514, loss_single: 0.6514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,454 - Iter: 15, Total Loss: 0.6339, loss_single: 0.6339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,489 - Iter: 16, Total Loss: 0.6161, loss_single: 0.6161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,525 - Iter: 17, Total Loss: 0.5981, loss_single: 0.5981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,560 - Iter: 18, Total Loss: 0.5825, loss_single: 0.5825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,596 - Iter: 19, Total Loss: 0.5692, loss_single: 0.5692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,631 - Iter: 20, Total Loss: 0.5563, loss_single: 0.5563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,667 - Iter: 21, Total Loss: 0.5444, loss_single: 0.5444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,702 - Iter: 22, Total Loss: 0.5335, loss_single: 0.5335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,738 - Iter: 23, Total Loss: 0.5227, loss_single: 0.5227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,774 - Iter: 24, Total Loss: 0.5126, loss_single: 0.5126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,809 - Iter: 25, Total Loss: 0.5036, loss_single: 0.5036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,845 - Iter: 26, Total Loss: 0.4952, loss_single: 0.4952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:56:36,904 - Iter: 27, Total Loss: 0.4869, loss_single: 0.4869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,939 - Iter: 28, Total Loss: 0.4787, loss_single: 0.4787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:36,978 - Iter: 29, Total Loss: 0.4725, loss_single: 0.4725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:56:37,014 - Iter: 30, Total Loss: 0.4675, loss_single: 0.4675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,049 - Iter: 31, Total Loss: 0.4627, loss_single: 0.4627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,085 - Iter: 32, Total Loss: 0.4584, loss_single: 0.4584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,120 - Iter: 33, Total Loss: 0.4538, loss_single: 0.4538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,156 - Iter: 34, Total Loss: 0.4495, loss_single: 0.4495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,191 - Iter: 35, Total Loss: 0.4460, loss_single: 0.4460, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,227 - Iter: 36, Total Loss: 0.4429, loss_single: 0.4429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,262 - Iter: 37, Total Loss: 0.4397, loss_single: 0.4397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,297 - Iter: 38, Total Loss: 0.4370, loss_single: 0.4370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,333 - Iter: 39, Total Loss: 0.4353, loss_single: 0.4353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:56:37,369 - Iter: 40, Total Loss: 0.4337, loss_single: 0.4337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,405 - Iter: 41, Total Loss: 0.4319, loss_single: 0.4319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,440 - Iter: 42, Total Loss: 0.4300, loss_single: 0.4300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,476 - Iter: 43, Total Loss: 0.4285, loss_single: 0.4285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,511 - Iter: 44, Total Loss: 0.4272, loss_single: 0.4272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,546 - Iter: 45, Total Loss: 0.4260, loss_single: 0.4260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:37,581 - Iter: 46, Total Loss: 0.4248, loss_single: 0.4248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,617 - Iter: 47, Total Loss: 0.4234, loss_single: 0.4234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,652 - Iter: 48, Total Loss: 0.4223, loss_single: 0.4223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,687 - Iter: 49, Total Loss: 0.4212, loss_single: 0.4212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,722 - Iter: 50, Total Loss: 0.4201, loss_single: 0.4201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,758 - Iter: 51, Total Loss: 0.4190, loss_single: 0.4190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,793 - Iter: 52, Total Loss: 0.4179, loss_single: 0.4179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,828 - Iter: 53, Total Loss: 0.4169, loss_single: 0.4169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,863 - Iter: 54, Total Loss: 0.4159, loss_single: 0.4159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,898 - Iter: 55, Total Loss: 0.4148, loss_single: 0.4148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:37,934 - Iter: 56, Total Loss: 0.4138, loss_single: 0.4138, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:37,969 - Iter: 57, Total Loss: 0.4128, loss_single: 0.4128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:38,005 - Iter: 58, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/simulation_data3__sample_000007.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/simulation_data3__sample_000007.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8bf032a85e35ef613ce62e69eac107e9b0d97269 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/simulation_data3__sample_000007.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 14.522917747497559 + probe_aberrations: + C10: -234.98805236816406 + C12: -32.69744873046875 + C21: 554.1824340820312 + C23: 545.4667358398438 + C30: 2564086.5 + C32: 3878.128662109375 + C34: -7614.99951171875 + C41: 65970.1328125 + C43: 153583.1875 + C45: -338596.1875 + C50: -440730912.0 + C52: -11856964.0 + C54: 16450422.0 + C56: 6760985.5 + phi12: 24.073705239194453 + phi21: 351.3952830600172 + phi23: 268.1545655317779 + phi32: 184.8975375118006 + phi34: 106.20967382013006 + phi41: 55.86373131584619 + phi43: 359.7742312847087 + phi45: 40.60930635185018 + phi52: 228.23074379521938 + phi54: 147.8671614925779 + phi56: 245.6369071591066 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4370545744895935 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000007_measurement.h5 + key: measurement + random_seed: 20261935 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000007 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000007/c30_small__simulation_data3__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-235_C12_-32.7_phi12_24.1_C21_554_phi21_351_C23_545_phi23_268_C30_2.56e+06_C32_3..76e+06_phi56_246/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6..85e+07_phi56_101/20260624_055649_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:56:47,944 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:56:47,944 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:56:47,944 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:56:47,944 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:56:47,944 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:56:47,944 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:56:47,944 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:56:47,944 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:56:47,944 - +2026-06-24 05:56:48,051 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:56:48,051 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:56:48,051 - Accelerator.num_process = 1 +2026-06-24 05:56:48,051 - Accelerator.mixed_precision = no +2026-06-24 05:56:48,061 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:56:48,061 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:56:48,061 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:56:48,061 - +2026-06-24 05:56:48,061 - ### System information ### +2026-06-24 05:56:48,061 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:56:48,061 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:56:48,061 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:56:48,061 - Machine: x86_64 +2026-06-24 05:56:48,061 - Processor: x86_64 +2026-06-24 05:56:48,061 - Available CPU cores: 8 +2026-06-24 05:56:48,061 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:56:48,061 - +2026-06-24 05:56:48,062 - ### GPU information ### +2026-06-24 05:56:48,062 - CUDA Available: True +2026-06-24 05:56:48,062 - CUDA Version: 13.0 +2026-06-24 05:56:48,062 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:56:48,062 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:56:48,062 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:56:48,062 - In addition, Triton does not directly support Windows. +2026-06-24 05:56:48,062 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:56:48,077 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:56:48,077 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:56:48,077 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:56:48,077 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:56:48,077 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:56:48,077 - +2026-06-24 05:56:48,077 - ### Python information ### +2026-06-24 05:56:48,079 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:56:48,079 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:56:48,079 - +2026-06-24 05:56:48,079 - ### Packages information ### +2026-06-24 05:56:48,080 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:56:48,081 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:56:48,081 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:56:48,082 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:56:48,083 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:56:48,083 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:56:48,083 - +2026-06-24 05:56:48,083 - ### Loading params file ### +2026-06-24 05:56:48,083 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000008.yaml +2026-06-24 05:56:48,089 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:56:48,090 - Success! Params file validated and defaults applied. +2026-06-24 05:56:48,090 - +2026-06-24 05:56:48,090 - ### Setting GPU Device ### +2026-06-24 05:56:48,090 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:56:48,090 - +2026-06-24 05:56:48,091 - Random seed: 20261936 provided by params file +2026-06-24 05:56:48,091 - ### Initializing Initializer ### +2026-06-24 05:56:48,091 - init_params are displayed below: +2026-06-24 05:56:48,091 - random_seed: 20261936 +2026-06-24 05:56:48,091 - probe_illum_type: electron +2026-06-24 05:56:48,091 - probe_kv: 100.0 +2026-06-24 05:56:48,091 - probe_conv_angle: 14.141242027282715 +2026-06-24 05:56:48,091 - probe_aberrations: {'C10': -637.162, 'C12': 9.733, 'phi12': 230.043, 'C21': -952.223, 'phi21': 115.507, 'C23': -929.798, 'phi23': 350.096, 'C30': 2355650.75, 'C32': 6101.677, 'phi32': 214.931, 'C34': 9755.707, 'phi34': 119.919, 'C41': -4957.013, 'phi41': 277.364, 'C43': 292366.344, 'phi43': 84.253, 'C45': 147837.031, 'phi45': 204.795, 'C50': 347087744.0, 'C52': -16670435.0, 'phi52': 330.229, 'C54': -14415081.0, 'phi54': 331.897, 'C56': 18459352.0, 'phi56': 101.413} +2026-06-24 05:56:48,091 - beam_kev: None +2026-06-24 05:56:48,091 - probe_dRn: None +2026-06-24 05:56:48,091 - probe_Rn: None +2026-06-24 05:56:48,091 - probe_D_H: None +2026-06-24 05:56:48,091 - probe_D_FZP: None +2026-06-24 05:56:48,091 - probe_Ls: None +2026-06-24 05:56:48,091 - meas_Npix: 128 +2026-06-24 05:56:48,091 - pos_N_scans: 256 +2026-06-24 05:56:48,091 - pos_N_scan_slow: 16 +2026-06-24 05:56:48,091 - pos_N_scan_fast: 16 +2026-06-24 05:56:48,091 - pos_scan_step_size: 0.44783034920692444 +2026-06-24 05:56:48,091 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:56:48,092 - probe_pmode_max: 6 +2026-06-24 05:56:48,092 - probe_pmode_init_pows: [0.02] +2026-06-24 05:56:48,092 - obj_omode_max: 1 +2026-06-24 05:56:48,092 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:56:48,092 - obj_Nlayer: 1 +2026-06-24 05:56:48,092 - obj_slice_thickness: 20.0 +2026-06-24 05:56:48,092 - simu_Npix: None +2026-06-24 05:56:48,092 - simu_match_mode: None +2026-06-24 05:56:48,092 - meas_permute: None +2026-06-24 05:56:48,092 - meas_reshape: [256, 128, 128] +2026-06-24 05:56:48,092 - meas_flipT: [0, 0, 0] +2026-06-24 05:56:48,092 - meas_crop: None +2026-06-24 05:56:48,092 - meas_pad: None +2026-06-24 05:56:48,092 - meas_resample: None +2026-06-24 05:56:48,092 - meas_add_source_size: None +2026-06-24 05:56:48,092 - meas_add_detector_blur: None +2026-06-24 05:56:48,092 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:56:48,092 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:56:48,092 - meas_add_poisson_noise: None +2026-06-24 05:56:48,092 - meas_export: None +2026-06-24 05:56:48,092 - probe_permute: None +2026-06-24 05:56:48,092 - probe_z_shift: None +2026-06-24 05:56:48,092 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:56:48,092 - pos_scan_flipT: None +2026-06-24 05:56:48,092 - pos_scan_affine: None +2026-06-24 05:56:48,092 - pos_scan_rand_std: 0.15 +2026-06-24 05:56:48,092 - obj_z_crop: None +2026-06-24 05:56:48,092 - obj_z_pad: None +2026-06-24 05:56:48,092 - obj_z_resample: None +2026-06-24 05:56:48,092 - meas_source: file +2026-06-24 05:56:48,092 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000008_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:56:48,092 - probe_source: simu +2026-06-24 05:56:48,092 - probe_params: None +2026-06-24 05:56:48,092 - pos_source: simu +2026-06-24 05:56:48,092 - pos_params: None +2026-06-24 05:56:48,092 - obj_source: simu +2026-06-24 05:56:48,092 - obj_params: None +2026-06-24 05:56:48,092 - tilt_source: simu +2026-06-24 05:56:48,093 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:56:48,093 - +2026-06-24 05:56:48,093 - ### Initializing cache ### +2026-06-24 05:56:48,093 - use_cached_obj = False +2026-06-24 05:56:48,093 - use_cached_probe = False +2026-06-24 05:56:48,093 - use_cached_pos = False +2026-06-24 05:56:48,093 - +2026-06-24 05:56:48,093 - ### Initializing measurements ### +2026-06-24 05:56:48,093 - Loading measurements from source = 'file' +2026-06-24 05:56:48,093 - Detected measurement file type = '.h5' +2026-06-24 05:56:48,170 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:56:48,171 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:56:48,172 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0043) +2026-06-24 05:56:48,172 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:56:48,172 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:56:48,174 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:56:48,174 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:56:48,174 - Normalizing by max of the 2D mean pattern intensity: 0.0031869712 +2026-06-24 05:56:48,175 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:56:48,176 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0191, 1.3351) +2026-06-24 05:56:48,176 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:56:48,178 - Pattern total int. statistics (min, mean, max) = (311.0131, 313.0052, 314.6995), with min/max = 98.8% +2026-06-24 05:56:48,179 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0191, 1.3351) +2026-06-24 05:56:48,179 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:56:48,179 - +2026-06-24 05:56:48,179 - ### Setting up calibration ### +2026-06-24 05:56:48,179 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:56:48,179 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:56:48,179 - Radius of fitted bright field disk (RBF) = 9.71 px with meas_Npix = 128 +2026-06-24 05:56:48,179 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1517 +2026-06-24 05:56:48,179 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:56:48,179 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:56:48,400 - Initial guess: center=(63.62, 63.63), radius=9.71, Gaussian blur std=0.50 +2026-06-24 05:56:48,412 - Final fit: center=(63.62, 63.63), radius=9.71, Gaussian blur std=0.66 +2026-06-24 05:56:48,412 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.78 px with Npix = 128 +2026-06-24 05:56:48,412 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:56:48,412 - +2026-06-24 05:56:48,413 - ### Setting init_variables dict ### +2026-06-24 05:56:48,413 - Derived values given input init_params: +2026-06-24 05:56:48,413 - kv = 100.0 kV +2026-06-24 05:56:48,413 - wavelength = 0.0370 Ang +2026-06-24 05:56:48,413 - conv_angle = 14.141242027282715 mrad +2026-06-24 05:56:48,413 - Npix = 128 px +2026-06-24 05:56:48,413 - dk = 0.0391 Ang^-1 +2026-06-24 05:56:48,413 - kMax = 2.5000 Ang^-1 +2026-06-24 05:56:48,413 - da = 1.4459 mrad +2026-06-24 05:56:48,413 - angleMax = 92.5359 mrad +2026-06-24 05:56:48,413 - RBF = 9.7804 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:56:48,413 - n_alpha = 6.5437 (# conv_angle) +2026-06-24 05:56:48,413 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:56:48,413 - Rayleigh-limited resolution = 1.5967 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:56:48,413 - Real space probe extent = 25.6000 Ang +2026-06-24 05:56:48,413 - +2026-06-24 05:56:48,413 - ### Initializing probe ### +2026-06-24 05:56:48,413 - Loading probe from source = 'simu' +2026-06-24 05:56:48,413 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:56:48,413 - Start simulating STEM probe +2026-06-24 05:56:48,413 - kv = 100.0 kV +2026-06-24 05:56:48,413 - wavelength = 0.0370 Ang +2026-06-24 05:56:48,413 - conv_angle = 14.141242027282715 mrad +2026-06-24 05:56:48,413 - Npix = 128 px +2026-06-24 05:56:48,413 - dk = 0.0391 Ang^-1 +2026-06-24 05:56:48,414 - kMax = 2.5000 Ang^-1 +2026-06-24 05:56:48,414 - alpha_max = 92.5359 mrad +2026-06-24 05:56:48,414 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:56:48,414 - Rayleigh-limited resolution = 1.5967 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:56:48,414 - Real space probe extent = 25.6000 Ang +2026-06-24 05:56:48,414 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:56:48,414 - ------------------------------------------------------------------------------------ +2026-06-24 05:56:48,414 - C1,0 C1 -637.1620 - Defocus (C10 = -df) +2026-06-24 05:56:48,414 - C1,2 A1 9.7330 230.04 2-fold astigmatism +2026-06-24 05:56:48,414 - C2,1 3*B2 -952.2230 115.51 Axial coma +2026-06-24 05:56:48,414 - C2,3 A2 -929.7980 350.10 3-fold astigmatism +2026-06-24 05:56:48,414 - C3,0 C3 2355650.7500 - Spherical aberration +2026-06-24 05:56:48,414 - C3,2 4*S3 6101.6770 214.93 Axial star aberration +2026-06-24 05:56:48,414 - C3,4 A3 9755.7070 119.92 4-fold astigmatism +2026-06-24 05:56:48,414 - C4,1 4*B4 -4957.0130 277.36 Axial coma(4th) +2026-06-24 05:56:48,414 - C4,3 4*D4 292366.3440 84.25 3-lobe aberration +2026-06-24 05:56:48,414 - C4,5 A4 147837.0310 204.79 5-fold astigmatism +2026-06-24 05:56:48,414 - C5,0 C5 347087744.0000 - Spherical aberration (5th) +2026-06-24 05:56:48,414 - C5,2 6*S5 -16670435.0000 330.23 Axial star aberration(5th) +2026-06-24 05:56:48,414 - C5,4 6*R5 -14415081.0000 331.90 4-lobe aberration +2026-06-24 05:56:48,414 - C5,6 A5 18459352.0000 101.41 6-fold astigmatism +2026-06-24 05:56:48,417 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:56:48,417 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:56:48,417 - Creating 5 new probe modes from the major mode +2026-06-24 05:56:48,417 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:56:48,520 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:56:48,521 - Orthogonalizing 6 pmodes +2026-06-24 05:56:48,524 - Sorting 6 pmodes by their intensities +2026-06-24 05:56:48,524 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:56:48,525 - sum(|probe_data|**2) = 313.01, while meas_total_ints (min, mean, max) = (311.0131, 313.0052, 314.6995) +2026-06-24 05:56:48,525 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:56:48,525 - +2026-06-24 05:56:48,525 - ### Initializing probe positions ### +2026-06-24 05:56:48,525 - Loading probe positions from source = 'simu' +2026-06-24 05:56:48,525 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:56:48,525 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4478, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:56:48,526 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:56:48,528 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:56:48,528 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 50]) +2026-06-24 05:56:48,528 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 05:56:48,528 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:56:48,528 - +2026-06-24 05:56:48,528 - ### Initializing object ### +2026-06-24 05:56:48,528 - Loading object from source = 'simu' +2026-06-24 05:56:48,528 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:56:48,529 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:56:48,530 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 195, 195) +2026-06-24 05:56:48,530 - object extent (Z, Y, X) (Ang) = [20. 39. 39.] +2026-06-24 05:56:48,530 - +2026-06-24 05:56:48,530 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:56:48,530 - omode_occu (omode) = float32, (1,) +2026-06-24 05:56:48,530 - +2026-06-24 05:56:48,530 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:56:48,530 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 05:56:48,531 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:56:48,531 - +2026-06-24 05:56:48,531 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:56:48,531 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:56:48,531 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:56:48,531 - +2026-06-24 05:56:48,531 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:56:48,531 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:56:48,531 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:56:48,531 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:56:48,531 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:56:48,531 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (195, 195). +2026-06-24 05:56:48,531 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:56:48,531 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:56:48,531 - +2026-06-24 05:56:48,531 - ### Collecting reconstruction provenance ### +2026-06-24 05:56:48,531 - Reconstruction provenance is collected and initialized. +2026-06-24 05:56:48,531 - +2026-06-24 05:56:48,531 - ### Initializing loss function ### +2026-06-24 05:56:48,531 - Active loss types: +2026-06-24 05:56:48,532 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:56:48,532 - +2026-06-24 05:56:48,532 - ### Initializing constraint function ### +2026-06-24 05:56:48,532 - Active constraint types: +2026-06-24 05:56:48,532 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:56:48,532 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:56:48,532 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:56:48,532 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:56:48,532 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:56:48,532 - +2026-06-24 05:56:48,532 - ### Done initializing PtyRADSolver ### +2026-06-24 05:56:48,532 - +2026-06-24 05:56:48,657 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:56:48,657 - +2026-06-24 05:56:48,657 - ### Initializing PtychoModel model ### +2026-06-24 05:56:48,729 - ### PtychoModel optimizable variables ### +2026-06-24 05:56:48,729 - obja : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:48,729 - objp : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:48,729 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:56:48,729 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:56:48,729 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:56:48,729 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:56:48,729 - +2026-06-24 05:56:48,729 - ### Optimizable variables statitsics ### +2026-06-24 05:56:48,729 - Total measurement values : 4,194,304 +2026-06-24 05:56:48,729 - Total optimizing variables: 273,170 +2026-06-24 05:56:48,729 - Overdetermined ratio : 15.35 +2026-06-24 05:56:48,729 - +2026-06-24 05:56:48,729 - ### Model behavior ### +2026-06-24 05:56:48,730 - Tilt propagator : False +2026-06-24 05:56:48,730 - Change slice thickness : False +2026-06-24 05:56:48,730 - Detector blur : False +2026-06-24 05:56:48,730 - Preload data : True +2026-06-24 05:56:48,730 - On-the-fly meas padding : False +2026-06-24 05:56:48,730 - On-the-fly meas resample : False +2026-06-24 05:56:48,730 - On-the-fly simu match mode: None +2026-06-24 05:56:48,730 - +2026-06-24 05:56:48,771 - ### Done initializing PtychoModel model ### +2026-06-24 05:56:48,771 - +2026-06-24 05:56:48,772 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:56:48,772 - +2026-06-24 05:56:48,772 - ### Generating indices, batches, and output_path ### +2026-06-24 05:56:48,773 - d90 = 53.000 px or 10.600 Ang +2026-06-24 05:56:48,773 - Selecting indices with the 'full' mode +2026-06-24 05:56:49,238 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:56:49,313 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:56:49,313 - Original recon_dir_affixes = ['default'] +2026-06-24 05:56:49,313 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:56:49,320 - Path corrected for compatibility: +2026-06-24 05:56:49,320 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6.1e+03_phi32_215_C34_9.76e+03_phi34_120_C41_-4.96e+03_phi41_277_C43_2.92e+05_phi43_84.3_C45_1.48e+05_phi45_205_C50_3.47e+08_C52_-1.67e+07_phi52_330_C54_-1.44e+07_phi54_332_C56_1.85e+07_phi56_101 +2026-06-24 05:56:49,320 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6..85e+07_phi56_101 +2026-06-24 05:56:49,321 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6..85e+07_phi56_101' is generated! +2026-06-24 05:56:49,471 - +2026-06-24 05:56:49,472 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6..85e+07_phi56_101/20260624_055649_ptyrad_log.txt ### +2026-06-24 05:56:49,472 - +2026-06-24 05:56:49,474 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:56:49,474 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:56:49,474 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:56:50,672 - Iter: 1, Total Loss: 1.0297, loss_single: 1.0297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:56:50,709 - Iter: 2, Total Loss: 0.9826, loss_single: 0.9826, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:56:50,744 - Iter: 3, Total Loss: 0.9505, loss_single: 0.9505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,780 - Iter: 4, Total Loss: 0.9223, loss_single: 0.9223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,815 - Iter: 5, Total Loss: 0.8953, loss_single: 0.8953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,850 - Iter: 6, Total Loss: 0.8693, loss_single: 0.8693, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,886 - Iter: 7, Total Loss: 0.8385, loss_single: 0.8385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,921 - Iter: 8, Total Loss: 0.8116, loss_single: 0.8116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,956 - Iter: 9, Total Loss: 0.7847, loss_single: 0.7847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:50,991 - Iter: 10, Total Loss: 0.7525, loss_single: 0.7525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,026 - Iter: 11, Total Loss: 0.7226, loss_single: 0.7226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,062 - Iter: 12, Total Loss: 0.6926, loss_single: 0.6926, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,097 - Iter: 13, Total Loss: 0.6630, loss_single: 0.6630, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,132 - Iter: 14, Total Loss: 0.6330, loss_single: 0.6330, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,167 - Iter: 15, Total Loss: 0.6065, loss_single: 0.6065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,202 - Iter: 16, Total Loss: 0.5851, loss_single: 0.5851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,238 - Iter: 17, Total Loss: 0.5621, loss_single: 0.5621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,274 - Iter: 18, Total Loss: 0.5411, loss_single: 0.5411, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,309 - Iter: 19, Total Loss: 0.5222, loss_single: 0.5222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,344 - Iter: 20, Total Loss: 0.5015, loss_single: 0.5015, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,380 - Iter: 21, Total Loss: 0.4793, loss_single: 0.4793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,415 - Iter: 22, Total Loss: 0.4590, loss_single: 0.4590, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,450 - Iter: 23, Total Loss: 0.4400, loss_single: 0.4400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,486 - Iter: 24, Total Loss: 0.4203, loss_single: 0.4203, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,521 - Iter: 25, Total Loss: 0.4054, loss_single: 0.4054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,556 - Iter: 26, Total Loss: 0.3934, loss_single: 0.3934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,592 - Iter: 27, Total Loss: 0.3820, loss_single: 0.3820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,627 - Iter: 28, Total Loss: 0.3711, loss_single: 0.3711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,662 - Iter: 29, Total Loss: 0.3630, loss_single: 0.3630, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:51,697 - Iter: 30, Total Loss: 0.3543, loss_single: 0.3543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,732 - Iter: 31, Total Loss: 0.3438, loss_single: 0.3438, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,770 - Iter: 32, Total Loss: 0.3351, loss_single: 0.3351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:56:51,805 - Iter: 33, Total Loss: 0.3276, loss_single: 0.3276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,841 - Iter: 34, Total Loss: 0.3217, loss_single: 0.3217, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:56:51,876 - Iter: 35, Total Loss: 0.3170, loss_single: 0.3170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,911 - Iter: 36, Total Loss: 0.3132, loss_single: 0.3132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,947 - Iter: 37, Total Loss: 0.3103, loss_single: 0.3103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:51,982 - Iter: 38, Total Loss: 0.3076, loss_single: 0.3076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,016 - Iter: 39, Total Loss: 0.3048, loss_single: 0.3048, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:52,051 - Iter: 40, Total Loss: 0.3027, loss_single: 0.3027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,089 - Iter: 41, Total Loss: 0.3011, loss_single: 0.3011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,124 - Iter: 42, Total Loss: 0.2995, loss_single: 0.2995, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,158 - Iter: 43, Total Loss: 0.2981, loss_single: 0.2981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:52,193 - Iter: 44, Total Loss: 0.2971, loss_single: 0.2971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:52,229 - Iter: 45, Total Loss: 0.2961, loss_single: 0.2961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,264 - Iter: 46, Total Loss: 0.2952, loss_single: 0.2952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,299 - Iter: 47, Total Loss: 0.2945, loss_single: 0.2945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:52,334 - Iter: 48, Total Loss: 0.2939, loss_single: 0.2939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,369 - Iter: 49, Total Loss: 0.2934, loss_single: 0.2934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:52,404 - Iter: 50, Total Loss: 0.2929, loss_single: 0.2929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,439 - Iter: 51, Total Loss: 0.2926, loss_single: 0.2926, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:52,474 - Iter: 52, Total Loss: 0.2922, loss_single: 0.2922, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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in 0.034 sec +2026-06-24 05:56:53,105 - Iter: 70, Total Loss: 0.2885, loss_single: 0.2885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:53,141 - Iter: 71, Total Loss: 0.2884, loss_single: 0.2884, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,176 - Iter: 72, Total Loss: 0.2883, loss_single: 0.2883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,211 - Iter: 73, Total Loss: 0.2881, loss_single: 0.2881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,246 - Iter: 74, Total Loss: 0.2880, loss_single: 0.2880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,281 - Iter: 75, Total Loss: 0.2879, loss_single: 0.2879, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.2871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,526 - Iter: 82, Total Loss: 0.2869, loss_single: 0.2869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,561 - Iter: 83, Total Loss: 0.2868, loss_single: 0.2868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,596 - Iter: 84, Total Loss: 0.2867, loss_single: 0.2867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,632 - Iter: 85, Total Loss: 0.2866, loss_single: 0.2866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:53,667 - Iter: 86, Total Loss: 0.2864, loss_single: 0.2864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec 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0.2849, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:56:54,125 - Iter: 99, Total Loss: 0.2848, loss_single: 0.2848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:54,160 - Iter: 100, Total Loss: 0.2847, loss_single: 0.2847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:56:54,270 - Saving summary figures for iter 100 +2026-06-24 05:56:57,992 - ### Finished 100 iterations, averaged iter_t = 0.038811 with std = 0.040 ### +2026-06-24 05:56:57,992 - +2026-06-24 05:56:57,992 - ### The PtyRADSolver is finished in 9.335 sec ### +2026-06-24 05:56:57,992 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008/c30_small__simulation_data3__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-637_C12_9.73_phi12_230_C21_-952_phi21_116_C23_-930_phi23_350_C30_2.36e+06_C32_6..85e+07_phi56_101/simulation_data3__sample_000008.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 14.141242027282715 + probe_aberrations: + C10: -637.1619873046875 + C12: 9.733260154724121 + C21: -952.2233276367188 + C23: -929.7982177734375 + C30: 2355650.75 + C32: 6101.67724609375 + C34: 9755.70703125 + C41: -4957.0126953125 + C43: 292366.34375 + C45: 147837.03125 + C50: 347087744.0 + C52: -16670435.0 + C54: -14415081.0 + C56: 18459352.0 + phi12: 230.04298422732055 + phi21: 115.50713222402652 + phi23: 350.0955253817205 + phi32: 214.93140925472076 + phi34: 119.91875140893775 + phi41: 277.36368226894945 + phi43: 84.2527056764251 + phi45: 204.7945342622081 + phi52: 330.22945572787484 + phi54: 331.8973059609219 + phi56: 101.41291392830014 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.44783034920692444 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000008_measurement.h5 + key: measurement + random_seed: 20261936 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000008 + 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sha256:740af297d466d39d468c0d50e3e5c38c116b0a385742df8a511bf1777dcd72ff +size 48123 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/20260624_055704_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/20260624_055704_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..526c2cda31fa0cae6c6b2fb9806f6813c16abdc2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/20260624_055704_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:57:02,578 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:57:02,578 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:57:02,578 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:57:02,578 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:57:02,578 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:57:02,579 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:57:02,579 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:57:02,579 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:57:02,579 - +2026-06-24 05:57:02,701 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:57:02,702 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:57:02,702 - Accelerator.num_process = 1 +2026-06-24 05:57:02,702 - Accelerator.mixed_precision = no +2026-06-24 05:57:02,712 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:57:02,712 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:57:02,713 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:57:02,713 - +2026-06-24 05:57:02,713 - ### System information ### +2026-06-24 05:57:02,713 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:57:02,713 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:57:02,713 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:57:02,713 - Machine: x86_64 +2026-06-24 05:57:02,713 - Processor: x86_64 +2026-06-24 05:57:02,713 - Available CPU cores: 8 +2026-06-24 05:57:02,713 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:57:02,713 - +2026-06-24 05:57:02,713 - ### GPU information ### +2026-06-24 05:57:02,713 - CUDA Available: True +2026-06-24 05:57:02,713 - CUDA Version: 13.0 +2026-06-24 05:57:02,714 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:57:02,714 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:57:02,714 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:57:02,714 - In addition, Triton does not directly support Windows. +2026-06-24 05:57:02,714 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:57:02,740 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:57:02,740 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:57:02,740 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:57:02,740 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:57:02,740 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:57:02,740 - +2026-06-24 05:57:02,740 - ### Python information ### +2026-06-24 05:57:02,743 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:57:02,743 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:57:02,743 - +2026-06-24 05:57:02,743 - ### Packages information ### +2026-06-24 05:57:02,743 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:57:02,744 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:57:02,745 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:57:02,745 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:57:02,746 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:57:02,746 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:57:02,746 - +2026-06-24 05:57:02,746 - ### Loading params file ### +2026-06-24 05:57:02,746 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000009.yaml +2026-06-24 05:57:02,753 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:57:02,754 - Success! Params file validated and defaults applied. +2026-06-24 05:57:02,754 - +2026-06-24 05:57:02,754 - ### Setting GPU Device ### +2026-06-24 05:57:02,754 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:57:02,754 - +2026-06-24 05:57:02,754 - Random seed: 20261937 provided by params file +2026-06-24 05:57:02,754 - ### Initializing Initializer ### +2026-06-24 05:57:02,755 - init_params are displayed below: +2026-06-24 05:57:02,755 - random_seed: 20261937 +2026-06-24 05:57:02,755 - probe_illum_type: electron +2026-06-24 05:57:02,755 - probe_kv: 60.0 +2026-06-24 05:57:02,755 - probe_conv_angle: 19.036527633666992 +2026-06-24 05:57:02,755 - probe_aberrations: {'C10': -165.929, 'C12': 30.026, 'phi12': 343.036, 'C21': -451.82, 'phi21': 165.082, 'C23': -219.287, 'phi23': 176.892, 'C30': 1023644.0, 'C32': 8987.66, 'phi32': 66.053, 'C34': -6503.131, 'phi34': 239.831, 'C41': 42947.18, 'phi41': 107.444, 'C43': 98041.211, 'phi43': 19.309, 'C45': -24610.703, 'phi45': 215.776, 'C50': -95412880.0, 'C52': 5920013.0, 'phi52': 39.392, 'C54': -12339353.0, 'phi54': 233.977, 'C56': -12510871.0, 'phi56': 54.892} +2026-06-24 05:57:02,755 - beam_kev: None +2026-06-24 05:57:02,755 - probe_dRn: None +2026-06-24 05:57:02,755 - probe_Rn: None +2026-06-24 05:57:02,755 - probe_D_H: None +2026-06-24 05:57:02,755 - probe_D_FZP: None +2026-06-24 05:57:02,755 - probe_Ls: None +2026-06-24 05:57:02,755 - meas_Npix: 128 +2026-06-24 05:57:02,755 - pos_N_scans: 256 +2026-06-24 05:57:02,755 - pos_N_scan_slow: 16 +2026-06-24 05:57:02,755 - pos_N_scan_fast: 16 +2026-06-24 05:57:02,755 - pos_scan_step_size: 0.4955219328403473 +2026-06-24 05:57:02,755 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:57:02,755 - probe_pmode_max: 6 +2026-06-24 05:57:02,755 - probe_pmode_init_pows: [0.02] +2026-06-24 05:57:02,755 - obj_omode_max: 1 +2026-06-24 05:57:02,755 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:57:02,755 - obj_Nlayer: 1 +2026-06-24 05:57:02,755 - obj_slice_thickness: 20.0 +2026-06-24 05:57:02,755 - simu_Npix: None +2026-06-24 05:57:02,755 - simu_match_mode: None +2026-06-24 05:57:02,755 - meas_permute: None +2026-06-24 05:57:02,755 - meas_reshape: [256, 128, 128] +2026-06-24 05:57:02,755 - meas_flipT: [0, 0, 0] +2026-06-24 05:57:02,755 - meas_crop: None +2026-06-24 05:57:02,755 - meas_pad: None +2026-06-24 05:57:02,755 - meas_resample: None +2026-06-24 05:57:02,755 - meas_add_source_size: None +2026-06-24 05:57:02,755 - meas_add_detector_blur: None +2026-06-24 05:57:02,756 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:57:02,756 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:57:02,756 - meas_add_poisson_noise: None +2026-06-24 05:57:02,756 - meas_export: None +2026-06-24 05:57:02,756 - probe_permute: None +2026-06-24 05:57:02,756 - probe_z_shift: None +2026-06-24 05:57:02,756 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:57:02,756 - pos_scan_flipT: None +2026-06-24 05:57:02,756 - pos_scan_affine: None +2026-06-24 05:57:02,756 - pos_scan_rand_std: 0.15 +2026-06-24 05:57:02,756 - obj_z_crop: None +2026-06-24 05:57:02,756 - obj_z_pad: None +2026-06-24 05:57:02,756 - obj_z_resample: None +2026-06-24 05:57:02,756 - meas_source: file +2026-06-24 05:57:02,756 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000009_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:57:02,756 - probe_source: simu +2026-06-24 05:57:02,756 - probe_params: None +2026-06-24 05:57:02,756 - pos_source: simu +2026-06-24 05:57:02,756 - pos_params: None +2026-06-24 05:57:02,756 - obj_source: simu +2026-06-24 05:57:02,756 - obj_params: None +2026-06-24 05:57:02,756 - tilt_source: simu +2026-06-24 05:57:02,756 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:57:02,756 - +2026-06-24 05:57:02,756 - ### Initializing cache ### +2026-06-24 05:57:02,756 - use_cached_obj = False +2026-06-24 05:57:02,756 - use_cached_probe = False +2026-06-24 05:57:02,756 - use_cached_pos = False +2026-06-24 05:57:02,756 - +2026-06-24 05:57:02,756 - ### Initializing measurements ### +2026-06-24 05:57:02,756 - Loading measurements from source = 'file' +2026-06-24 05:57:02,756 - Detected measurement file type = '.h5' +2026-06-24 05:57:02,834 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:57:02,835 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:57:02,836 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0041) +2026-06-24 05:57:02,836 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:57:02,836 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:57:02,838 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:57:02,838 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:57:02,838 - Normalizing by max of the 2D mean pattern intensity: 0.0030096895 +2026-06-24 05:57:02,839 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:57:02,842 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.3615) +2026-06-24 05:57:02,843 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:57:02,844 - Pattern total int. statistics (min, mean, max) = (327.9608, 330.6971, 333.3995), with min/max = 98.4% +2026-06-24 05:57:02,845 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.3615) +2026-06-24 05:57:02,845 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:57:02,845 - +2026-06-24 05:57:02,845 - ### Setting up calibration ### +2026-06-24 05:57:02,845 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:57:02,846 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:57:02,846 - Radius of fitted bright field disk (RBF) = 9.87 px with meas_Npix = 128 +2026-06-24 05:57:02,846 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1542 +2026-06-24 05:57:02,846 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:57:02,846 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:57:03,078 - Initial guess: center=(63.61, 63.63), radius=9.87, Gaussian blur std=0.50 +2026-06-24 05:57:03,088 - Final fit: center=(63.61, 63.63), radius=9.87, Gaussian blur std=0.60 +2026-06-24 05:57:03,088 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.01 px with Npix = 128 +2026-06-24 05:57:03,088 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:57:03,089 - +2026-06-24 05:57:03,089 - ### Setting init_variables dict ### +2026-06-24 05:57:03,089 - Derived values given input init_params: +2026-06-24 05:57:03,089 - kv = 60.0 kV +2026-06-24 05:57:03,089 - wavelength = 0.0487 Ang +2026-06-24 05:57:03,089 - conv_angle = 19.036527633666992 mrad +2026-06-24 05:57:03,089 - Npix = 128 px +2026-06-24 05:57:03,089 - dk = 0.0391 Ang^-1 +2026-06-24 05:57:03,089 - kMax = 2.5000 Ang^-1 +2026-06-24 05:57:03,089 - da = 1.9008 mrad +2026-06-24 05:57:03,089 - angleMax = 121.6515 mrad +2026-06-24 05:57:03,089 - RBF = 10.0150 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:57:03,089 - n_alpha = 6.3904 (# conv_angle) +2026-06-24 05:57:03,089 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:57:03,089 - Rayleigh-limited resolution = 1.5593 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:57:03,089 - Real space probe extent = 25.6000 Ang +2026-06-24 05:57:03,089 - +2026-06-24 05:57:03,089 - ### Initializing probe ### +2026-06-24 05:57:03,089 - Loading probe from source = 'simu' +2026-06-24 05:57:03,089 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:57:03,089 - Start simulating STEM probe +2026-06-24 05:57:03,089 - kv = 60.0 kV +2026-06-24 05:57:03,089 - wavelength = 0.0487 Ang +2026-06-24 05:57:03,089 - conv_angle = 19.036527633666992 mrad +2026-06-24 05:57:03,090 - Npix = 128 px +2026-06-24 05:57:03,090 - dk = 0.0391 Ang^-1 +2026-06-24 05:57:03,090 - kMax = 2.5000 Ang^-1 +2026-06-24 05:57:03,090 - alpha_max = 121.6515 mrad +2026-06-24 05:57:03,090 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:57:03,090 - Rayleigh-limited resolution = 1.5593 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:57:03,090 - Real space probe extent = 25.6000 Ang +2026-06-24 05:57:03,090 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:57:03,090 - ------------------------------------------------------------------------------------ +2026-06-24 05:57:03,090 - C1,0 C1 -165.9290 - Defocus (C10 = -df) +2026-06-24 05:57:03,090 - C1,2 A1 30.0260 343.04 2-fold astigmatism +2026-06-24 05:57:03,090 - C2,1 3*B2 -451.8200 165.08 Axial coma +2026-06-24 05:57:03,090 - C2,3 A2 -219.2870 176.89 3-fold astigmatism +2026-06-24 05:57:03,090 - C3,0 C3 1023644.0000 - Spherical aberration +2026-06-24 05:57:03,090 - C3,2 4*S3 8987.6600 66.05 Axial star aberration +2026-06-24 05:57:03,090 - C3,4 A3 -6503.1310 239.83 4-fold astigmatism +2026-06-24 05:57:03,090 - C4,1 4*B4 42947.1800 107.44 Axial coma(4th) +2026-06-24 05:57:03,090 - C4,3 4*D4 98041.2110 19.31 3-lobe aberration +2026-06-24 05:57:03,090 - C4,5 A4 -24610.7030 215.78 5-fold astigmatism +2026-06-24 05:57:03,090 - C5,0 C5 -95412880.0000 - Spherical aberration (5th) +2026-06-24 05:57:03,090 - C5,2 6*S5 5920013.0000 39.39 Axial star aberration(5th) +2026-06-24 05:57:03,090 - C5,4 6*R5 -12339353.0000 233.98 4-lobe aberration +2026-06-24 05:57:03,090 - C5,6 A5 -12510871.0000 54.89 6-fold astigmatism +2026-06-24 05:57:03,093 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:57:03,093 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:57:03,093 - Creating 5 new probe modes from the major mode +2026-06-24 05:57:03,093 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:57:03,197 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:57:03,198 - Orthogonalizing 6 pmodes +2026-06-24 05:57:03,201 - Sorting 6 pmodes by their intensities +2026-06-24 05:57:03,201 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:57:03,202 - sum(|probe_data|**2) = 330.70, while meas_total_ints (min, mean, max) = (327.9608, 330.6971, 333.3995) +2026-06-24 05:57:03,202 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:57:03,202 - +2026-06-24 05:57:03,202 - ### Initializing probe positions ### +2026-06-24 05:57:03,202 - Loading probe positions from source = 'simu' +2026-06-24 05:57:03,202 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:57:03,202 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4955, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:57:03,202 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:57:03,204 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:57:03,204 - crop_pos 1st and last px coords (y,x) = ([16, 16], [54, 54]) +2026-06-24 05:57:03,205 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 05:57:03,205 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:57:03,205 - +2026-06-24 05:57:03,205 - ### Initializing object ### +2026-06-24 05:57:03,205 - Loading object from source = 'simu' +2026-06-24 05:57:03,205 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:57:03,207 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:57:03,207 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 05:57:03,207 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 05:57:03,207 - +2026-06-24 05:57:03,207 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:57:03,207 - omode_occu (omode) = float32, (1,) +2026-06-24 05:57:03,207 - +2026-06-24 05:57:03,207 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:57:03,207 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 05:57:03,208 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:57:03,208 - +2026-06-24 05:57:03,208 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:57:03,208 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:57:03,208 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:57:03,208 - +2026-06-24 05:57:03,208 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:57:03,208 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:57:03,208 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:57:03,208 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:57:03,208 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:57:03,208 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 05:57:03,208 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:57:03,208 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:57:03,208 - +2026-06-24 05:57:03,208 - ### Collecting reconstruction provenance ### +2026-06-24 05:57:03,209 - Reconstruction provenance is collected and initialized. +2026-06-24 05:57:03,209 - +2026-06-24 05:57:03,209 - ### Initializing loss function ### +2026-06-24 05:57:03,209 - Active loss types: +2026-06-24 05:57:03,209 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:57:03,209 - +2026-06-24 05:57:03,209 - ### Initializing constraint function ### +2026-06-24 05:57:03,209 - Active constraint types: +2026-06-24 05:57:03,209 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:57:03,209 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:57:03,209 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:57:03,209 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:57:03,209 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:57:03,209 - +2026-06-24 05:57:03,209 - ### Done initializing PtyRADSolver ### +2026-06-24 05:57:03,209 - +2026-06-24 05:57:03,337 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:57:03,337 - +2026-06-24 05:57:03,337 - ### Initializing PtychoModel model ### +2026-06-24 05:57:03,408 - ### PtychoModel optimizable variables ### +2026-06-24 05:57:03,408 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:03,408 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:03,408 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:57:03,408 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:57:03,408 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:57:03,408 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:03,408 - +2026-06-24 05:57:03,408 - ### Optimizable variables statitsics ### +2026-06-24 05:57:03,408 - Total measurement values : 4,194,304 +2026-06-24 05:57:03,408 - Total optimizing variables: 276,322 +2026-06-24 05:57:03,408 - Overdetermined ratio : 15.18 +2026-06-24 05:57:03,408 - +2026-06-24 05:57:03,409 - ### Model behavior ### +2026-06-24 05:57:03,409 - Tilt propagator : False +2026-06-24 05:57:03,409 - Change slice thickness : False +2026-06-24 05:57:03,409 - Detector blur : False +2026-06-24 05:57:03,409 - Preload data : True +2026-06-24 05:57:03,409 - On-the-fly meas padding : False +2026-06-24 05:57:03,409 - On-the-fly meas resample : False +2026-06-24 05:57:03,409 - On-the-fly simu match mode: None +2026-06-24 05:57:03,409 - +2026-06-24 05:57:03,450 - ### Done initializing PtychoModel model ### +2026-06-24 05:57:03,450 - +2026-06-24 05:57:03,451 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:57:03,451 - +2026-06-24 05:57:03,451 - ### Generating indices, batches, and output_path ### +2026-06-24 05:57:03,452 - d90 = 39.000 px or 7.800 Ang +2026-06-24 05:57:03,452 - Selecting indices with the 'full' mode +2026-06-24 05:57:03,911 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:57:03,989 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:57:03,989 - Original recon_dir_affixes = ['default'] +2026-06-24 05:57:03,989 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:57:03,995 - Path corrected for compatibility: +2026-06-24 05:57:03,995 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1_C34_-6.5e+03_phi34_240_C41_4.29e+04_phi41_107_C43_9.8e+04_phi43_19.3_C45_-2.46e+04_phi45_216_C50_-9.54e+07_C52_5.92e+06_phi52_39.4_C54_-1.23e+07_phi54_234_C56_-1.25e+07_phi56_54.9 +2026-06-24 05:57:03,996 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9 +2026-06-24 05:57:03,997 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9' is generated! +2026-06-24 05:57:04,150 - +2026-06-24 05:57:04,151 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/20260624_055704_ptyrad_log.txt ### +2026-06-24 05:57:04,151 - +2026-06-24 05:57:04,152 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:57:04,152 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:57:04,152 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:57:05,339 - Iter: 1, Total Loss: 0.9894, loss_single: 0.9894, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 05:57:05,377 - Iter: 2, Total Loss: 0.9481, loss_single: 0.9481, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:57:05,413 - Iter: 3, Total Loss: 0.9146, loss_single: 0.9146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,450 - Iter: 4, Total Loss: 0.8865, loss_single: 0.8865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,485 - Iter: 5, Total Loss: 0.8647, loss_single: 0.8647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,522 - Iter: 6, Total Loss: 0.8425, loss_single: 0.8425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,558 - Iter: 7, Total Loss: 0.8148, loss_single: 0.8148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,594 - Iter: 8, Total Loss: 0.7882, loss_single: 0.7882, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,630 - Iter: 9, Total Loss: 0.7606, loss_single: 0.7606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,665 - Iter: 10, Total Loss: 0.7331, loss_single: 0.7331, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,702 - Iter: 11, Total Loss: 0.7099, loss_single: 0.7099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:57:05,737 - Iter: 12, Total Loss: 0.6885, loss_single: 0.6885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,773 - Iter: 13, Total Loss: 0.6672, loss_single: 0.6672, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,808 - Iter: 14, Total Loss: 0.6470, loss_single: 0.6470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,844 - Iter: 15, Total Loss: 0.6264, loss_single: 0.6264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,879 - Iter: 16, Total Loss: 0.6000, loss_single: 0.6000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,915 - Iter: 17, Total Loss: 0.5747, loss_single: 0.5747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:05,951 - Iter: 18, Total Loss: 0.5528, loss_single: 0.5528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:05,986 - Iter: 19, Total Loss: 0.5284, loss_single: 0.5284, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:06,022 - Iter: 20, Total Loss: 0.5013, loss_single: 0.5013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:06,058 - Iter: 21, Total Loss: 0.4772, loss_single: 0.4772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:06,093 - Iter: 22, Total Loss: 0.4565, loss_single: 0.4565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:06,129 - Iter: 23, Total Loss: 0.4386, loss_single: 0.4386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:06,164 - Iter: 24, Total Loss: 0.4264, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/simulation_data3__sample_000009.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/simulation_data3__sample_000009.yaml new file mode 100644 index 0000000000000000000000000000000000000000..887bb26c15c1d35ef0fc42a9ca8c1de0aacaef58 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/simulation_data3__sample_000009.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 19.036527633666992 + probe_aberrations: + C10: -165.92869567871094 + C12: 30.025632858276367 + C21: -451.8203430175781 + C23: -219.28729248046875 + C30: 1023644.0 + C32: 8987.66015625 + C34: -6503.130859375 + C41: 42947.1796875 + C43: 98041.2109375 + C45: -24610.703125 + C50: -95412880.0 + C52: 5920013.0 + C54: -12339353.0 + C56: -12510871.0 + phi12: 343.0362243461888 + phi21: 165.0820249181914 + phi23: 176.8915039554135 + phi32: 66.05310655741417 + phi34: 239.8307819117322 + phi41: 107.44370458804377 + phi43: 19.30928117044267 + phi45: 215.77637195694305 + phi52: 39.39219737760517 + phi54: 233.9773917553013 + phi56: 54.89170318939957 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4955219328403473 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000009_measurement.h5 + key: measurement + random_seed: 20261937 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000009 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:52a677fb19dc1d0cc86b2b6a2a4e246b34a48fa07ed35af157846805e6417016 +size 1062594 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000009/c30_small__simulation_data3__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_30_phi12_343_C21_-452_phi21_165_C23_-219_phi23_177_C30_1.02e+06_C32_8.99e+03_phi32_66.1.9/summary_scan_pos_iter0100.png 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sha256:25f298a01073a22f7ee07cf14ff50a133ed772a5e68bc9ac54f7b4d9df4fb8d6 +size 48369 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/20260624_055748_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/20260624_055748_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..19b952eca02801c24ea0f57681359854fd5857ac --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/20260624_055748_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:57:47,146 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:57:47,147 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:57:47,147 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:57:47,147 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:57:47,147 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:57:47,147 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:57:47,147 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:57:47,147 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:57:47,147 - +2026-06-24 05:57:47,255 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:57:47,255 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:57:47,255 - Accelerator.num_process = 1 +2026-06-24 05:57:47,255 - Accelerator.mixed_precision = no +2026-06-24 05:57:47,266 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:57:47,266 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:57:47,266 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:57:47,266 - +2026-06-24 05:57:47,266 - ### System information ### +2026-06-24 05:57:47,266 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:57:47,266 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:57:47,266 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:57:47,266 - Machine: x86_64 +2026-06-24 05:57:47,266 - Processor: x86_64 +2026-06-24 05:57:47,266 - Available CPU cores: 8 +2026-06-24 05:57:47,266 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:57:47,266 - +2026-06-24 05:57:47,266 - ### GPU information ### +2026-06-24 05:57:47,266 - CUDA Available: True +2026-06-24 05:57:47,266 - CUDA Version: 13.0 +2026-06-24 05:57:47,267 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:57:47,267 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:57:47,267 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:57:47,267 - In addition, Triton does not directly support Windows. +2026-06-24 05:57:47,267 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:57:47,283 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:57:47,283 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:57:47,283 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:57:47,283 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:57:47,283 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:57:47,283 - +2026-06-24 05:57:47,283 - ### Python information ### +2026-06-24 05:57:47,284 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:57:47,284 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:57:47,284 - +2026-06-24 05:57:47,284 - ### Packages information ### +2026-06-24 05:57:47,285 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:57:47,286 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:57:47,286 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:57:47,287 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:57:47,287 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:57:47,287 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:57:47,288 - +2026-06-24 05:57:47,288 - ### Loading params file ### +2026-06-24 05:57:47,288 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000012.yaml +2026-06-24 05:57:47,294 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:57:47,295 - Success! Params file validated and defaults applied. +2026-06-24 05:57:47,295 - +2026-06-24 05:57:47,295 - ### Setting GPU Device ### +2026-06-24 05:57:47,295 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:57:47,295 - +2026-06-24 05:57:47,295 - Random seed: 20261940 provided by params file +2026-06-24 05:57:47,296 - ### Initializing Initializer ### +2026-06-24 05:57:47,296 - init_params are displayed below: +2026-06-24 05:57:47,296 - random_seed: 20261940 +2026-06-24 05:57:47,296 - probe_illum_type: electron +2026-06-24 05:57:47,296 - probe_kv: 160.0 +2026-06-24 05:57:47,296 - probe_conv_angle: 28.509687423706055 +2026-06-24 05:57:47,296 - probe_aberrations: {'C10': 26.684, 'C12': -19.53, 'phi12': 305.799, 'C21': 690.456, 'phi21': 356.308, 'C23': 60.338, 'phi23': 222.493, 'C30': 56705.93, 'C32': -7221.257, 'phi32': 141.632, 'C34': 7660.616, 'phi34': 77.25, 'C41': -208663.344, 'phi41': 286.957, 'C43': 390834.938, 'phi43': 160.95, 'C45': 134100.0, 'phi45': 104.643, 'C50': 179485072.0, 'C52': 9193875.0, 'phi52': 258.639, 'C54': -19467058.0, 'phi54': 149.76, 'C56': -10610066.0, 'phi56': 184.289} +2026-06-24 05:57:47,296 - beam_kev: None +2026-06-24 05:57:47,296 - probe_dRn: None +2026-06-24 05:57:47,296 - probe_Rn: None +2026-06-24 05:57:47,296 - probe_D_H: None +2026-06-24 05:57:47,296 - probe_D_FZP: None +2026-06-24 05:57:47,296 - probe_Ls: None +2026-06-24 05:57:47,296 - meas_Npix: 128 +2026-06-24 05:57:47,296 - pos_N_scans: 256 +2026-06-24 05:57:47,296 - pos_N_scan_slow: 16 +2026-06-24 05:57:47,296 - pos_N_scan_fast: 16 +2026-06-24 05:57:47,296 - pos_scan_step_size: 0.44282132387161255 +2026-06-24 05:57:47,296 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:57:47,296 - probe_pmode_max: 6 +2026-06-24 05:57:47,296 - probe_pmode_init_pows: [0.02] +2026-06-24 05:57:47,296 - obj_omode_max: 1 +2026-06-24 05:57:47,296 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:57:47,296 - obj_Nlayer: 1 +2026-06-24 05:57:47,296 - obj_slice_thickness: 20.0 +2026-06-24 05:57:47,296 - simu_Npix: None +2026-06-24 05:57:47,296 - simu_match_mode: None +2026-06-24 05:57:47,296 - meas_permute: None +2026-06-24 05:57:47,296 - meas_reshape: [256, 128, 128] +2026-06-24 05:57:47,296 - meas_flipT: [0, 0, 0] +2026-06-24 05:57:47,297 - meas_crop: None +2026-06-24 05:57:47,297 - meas_pad: None +2026-06-24 05:57:47,297 - meas_resample: None +2026-06-24 05:57:47,297 - meas_add_source_size: None +2026-06-24 05:57:47,297 - meas_add_detector_blur: None +2026-06-24 05:57:47,297 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:57:47,297 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:57:47,297 - meas_add_poisson_noise: None +2026-06-24 05:57:47,297 - meas_export: None +2026-06-24 05:57:47,297 - probe_permute: None +2026-06-24 05:57:47,297 - probe_z_shift: None +2026-06-24 05:57:47,297 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:57:47,297 - pos_scan_flipT: None +2026-06-24 05:57:47,297 - pos_scan_affine: None +2026-06-24 05:57:47,297 - pos_scan_rand_std: 0.15 +2026-06-24 05:57:47,297 - obj_z_crop: None +2026-06-24 05:57:47,297 - obj_z_pad: None +2026-06-24 05:57:47,297 - obj_z_resample: None +2026-06-24 05:57:47,297 - meas_source: file +2026-06-24 05:57:47,297 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000012_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:57:47,297 - probe_source: simu +2026-06-24 05:57:47,297 - probe_params: None +2026-06-24 05:57:47,297 - pos_source: simu +2026-06-24 05:57:47,297 - pos_params: None +2026-06-24 05:57:47,297 - obj_source: simu +2026-06-24 05:57:47,297 - obj_params: None +2026-06-24 05:57:47,297 - tilt_source: simu +2026-06-24 05:57:47,297 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:57:47,297 - +2026-06-24 05:57:47,297 - ### Initializing cache ### +2026-06-24 05:57:47,297 - use_cached_obj = False +2026-06-24 05:57:47,297 - use_cached_probe = False +2026-06-24 05:57:47,297 - use_cached_pos = False +2026-06-24 05:57:47,297 - +2026-06-24 05:57:47,297 - ### Initializing measurements ### +2026-06-24 05:57:47,297 - Loading measurements from source = 'file' +2026-06-24 05:57:47,297 - Detected measurement file type = '.h5' +2026-06-24 05:57:47,377 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:57:47,377 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:57:47,379 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0010) +2026-06-24 05:57:47,379 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:57:47,379 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:57:47,381 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:57:47,381 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:57:47,382 - Normalizing by max of the 2D mean pattern intensity: 0.00049543055 +2026-06-24 05:57:47,382 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:57:47,384 - meausrements int. statistics (min, mean, max) = (0.0000, 0.1229, 1.9182) +2026-06-24 05:57:47,384 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:57:47,385 - Pattern total int. statistics (min, mean, max) = (2002.2153, 2014.3641, 2028.3286), with min/max = 98.7% +2026-06-24 05:57:47,387 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.1229, 1.9182) +2026-06-24 05:57:47,387 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:57:47,387 - +2026-06-24 05:57:47,387 - ### Setting up calibration ### +2026-06-24 05:57:47,387 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:57:47,387 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:57:47,387 - Radius of fitted bright field disk (RBF) = 25.35 px with meas_Npix = 128 +2026-06-24 05:57:47,387 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3961 +2026-06-24 05:57:47,387 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:57:47,387 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:57:47,620 - Initial guess: center=(63.62, 63.63), radius=25.35, Gaussian blur std=0.50 +2026-06-24 05:57:47,630 - Final fit: center=(63.62, 63.63), radius=25.35, Gaussian blur std=0.57 +2026-06-24 05:57:47,630 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 25.60 px with Npix = 128 +2026-06-24 05:57:47,630 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:57:47,630 - +2026-06-24 05:57:47,630 - ### Setting init_variables dict ### +2026-06-24 05:57:47,630 - Derived values given input init_params: +2026-06-24 05:57:47,630 - kv = 160.0 kV +2026-06-24 05:57:47,630 - wavelength = 0.0285 Ang +2026-06-24 05:57:47,630 - conv_angle = 28.509687423706055 mrad +2026-06-24 05:57:47,630 - Npix = 128 px +2026-06-24 05:57:47,630 - dk = 0.0391 Ang^-1 +2026-06-24 05:57:47,630 - kMax = 2.5000 Ang^-1 +2026-06-24 05:57:47,630 - da = 1.1137 mrad +2026-06-24 05:57:47,630 - angleMax = 71.2751 mrad +2026-06-24 05:57:47,630 - RBF = 25.5997 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:57:47,630 - n_alpha = 2.5000 (# conv_angle) +2026-06-24 05:57:47,630 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:57:47,630 - Rayleigh-limited resolution = 0.6100 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:57:47,631 - Real space probe extent = 25.6000 Ang +2026-06-24 05:57:47,631 - +2026-06-24 05:57:47,631 - ### Initializing probe ### +2026-06-24 05:57:47,631 - Loading probe from source = 'simu' +2026-06-24 05:57:47,631 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:57:47,631 - Start simulating STEM probe +2026-06-24 05:57:47,631 - kv = 160.0 kV +2026-06-24 05:57:47,631 - wavelength = 0.0285 Ang +2026-06-24 05:57:47,631 - conv_angle = 28.509687423706055 mrad +2026-06-24 05:57:47,631 - Npix = 128 px +2026-06-24 05:57:47,631 - dk = 0.0391 Ang^-1 +2026-06-24 05:57:47,631 - kMax = 2.5000 Ang^-1 +2026-06-24 05:57:47,631 - alpha_max = 71.2751 mrad +2026-06-24 05:57:47,631 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:57:47,631 - Rayleigh-limited resolution = 0.6100 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:57:47,631 - Real space probe extent = 25.6000 Ang +2026-06-24 05:57:47,631 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:57:47,631 - ------------------------------------------------------------------------------------ +2026-06-24 05:57:47,631 - C1,0 C1 26.6840 - Defocus (C10 = -df) +2026-06-24 05:57:47,631 - C1,2 A1 -19.5300 305.80 2-fold astigmatism +2026-06-24 05:57:47,631 - C2,1 3*B2 690.4560 356.31 Axial coma +2026-06-24 05:57:47,631 - C2,3 A2 60.3380 222.49 3-fold astigmatism +2026-06-24 05:57:47,631 - C3,0 C3 56705.9300 - Spherical aberration +2026-06-24 05:57:47,631 - C3,2 4*S3 -7221.2570 141.63 Axial star aberration +2026-06-24 05:57:47,632 - C3,4 A3 7660.6160 77.25 4-fold astigmatism +2026-06-24 05:57:47,632 - C4,1 4*B4 -208663.3440 286.96 Axial coma(4th) +2026-06-24 05:57:47,632 - C4,3 4*D4 390834.9380 160.95 3-lobe aberration +2026-06-24 05:57:47,632 - C4,5 A4 134100.0000 104.64 5-fold astigmatism +2026-06-24 05:57:47,632 - C5,0 C5 179485072.0000 - Spherical aberration (5th) +2026-06-24 05:57:47,632 - C5,2 6*S5 9193875.0000 258.64 Axial star aberration(5th) +2026-06-24 05:57:47,632 - C5,4 6*R5 -19467058.0000 149.76 4-lobe aberration +2026-06-24 05:57:47,632 - C5,6 A5 -10610066.0000 184.29 6-fold astigmatism +2026-06-24 05:57:47,635 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:57:47,635 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:57:47,635 - Creating 5 new probe modes from the major mode +2026-06-24 05:57:47,635 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:57:47,778 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:57:47,779 - Orthogonalizing 6 pmodes +2026-06-24 05:57:47,782 - Sorting 6 pmodes by their intensities +2026-06-24 05:57:47,783 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:57:47,783 - sum(|probe_data|**2) = 2014.36, while meas_total_ints (min, mean, max) = (2002.2153, 2014.3641, 2028.3286) +2026-06-24 05:57:47,783 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:57:47,783 - +2026-06-24 05:57:47,783 - ### Initializing probe positions ### +2026-06-24 05:57:47,783 - Loading probe positions from source = 'simu' +2026-06-24 05:57:47,783 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:57:47,783 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4428, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:57:47,784 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:57:47,786 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:57:47,786 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 49]) +2026-06-24 05:57:47,786 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 05:57:47,786 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:57:47,786 - +2026-06-24 05:57:47,786 - ### Initializing object ### +2026-06-24 05:57:47,786 - Loading object from source = 'simu' +2026-06-24 05:57:47,786 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:57:47,787 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:57:47,788 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 05:57:47,788 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 05:57:47,788 - +2026-06-24 05:57:47,788 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:57:47,788 - omode_occu (omode) = float32, (1,) +2026-06-24 05:57:47,788 - +2026-06-24 05:57:47,788 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:57:47,788 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:57:47,789 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:57:47,789 - +2026-06-24 05:57:47,789 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:57:47,789 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:57:47,789 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:57:47,789 - +2026-06-24 05:57:47,789 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:57:47,789 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:57:47,789 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:57:47,789 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:57:47,789 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:57:47,789 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 05:57:47,789 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:57:47,789 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:57:47,789 - +2026-06-24 05:57:47,789 - ### Collecting reconstruction provenance ### +2026-06-24 05:57:47,789 - Reconstruction provenance is collected and initialized. +2026-06-24 05:57:47,789 - +2026-06-24 05:57:47,789 - ### Initializing loss function ### +2026-06-24 05:57:47,789 - Active loss types: +2026-06-24 05:57:47,790 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:57:47,790 - +2026-06-24 05:57:47,790 - ### Initializing constraint function ### +2026-06-24 05:57:47,790 - Active constraint types: +2026-06-24 05:57:47,790 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:57:47,790 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:57:47,790 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:57:47,790 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:57:47,790 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:57:47,790 - +2026-06-24 05:57:47,790 - ### Done initializing PtyRADSolver ### +2026-06-24 05:57:47,790 - +2026-06-24 05:57:47,921 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:57:47,921 - +2026-06-24 05:57:47,921 - ### Initializing PtychoModel model ### +2026-06-24 05:57:47,991 - ### PtychoModel optimizable variables ### +2026-06-24 05:57:47,991 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:47,991 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:47,991 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:57:47,991 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:57:47,991 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:57:47,991 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:57:47,991 - +2026-06-24 05:57:47,991 - ### Optimizable variables statitsics ### +2026-06-24 05:57:47,991 - Total measurement values : 4,194,304 +2026-06-24 05:57:47,991 - Total optimizing variables: 272,392 +2026-06-24 05:57:47,991 - Overdetermined ratio : 15.40 +2026-06-24 05:57:47,991 - +2026-06-24 05:57:47,991 - ### Model behavior ### +2026-06-24 05:57:47,991 - Tilt propagator : False +2026-06-24 05:57:47,991 - Change slice thickness : False +2026-06-24 05:57:47,991 - Detector blur : False +2026-06-24 05:57:47,991 - Preload data : True +2026-06-24 05:57:47,991 - On-the-fly meas padding : False +2026-06-24 05:57:47,992 - On-the-fly meas resample : False +2026-06-24 05:57:47,992 - On-the-fly simu match mode: None +2026-06-24 05:57:47,992 - +2026-06-24 05:57:48,032 - ### Done initializing PtychoModel model ### +2026-06-24 05:57:48,033 - +2026-06-24 05:57:48,033 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:57:48,033 - +2026-06-24 05:57:48,033 - ### Generating indices, batches, and output_path ### +2026-06-24 05:57:48,034 - d90 = 43.000 px or 8.600 Ang +2026-06-24 05:57:48,034 - Selecting indices with the 'full' mode +2026-06-24 05:57:48,493 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:57:48,565 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:57:48,566 - Original recon_dir_affixes = ['default'] +2026-06-24 05:57:48,566 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:57:48,572 - Path corrected for compatibility: +2026-06-24 05:57:48,572 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.22e+03_phi32_142_C34_7.66e+03_phi34_77.2_C41_-2.09e+05_phi41_287_C43_3.91e+05_phi43_161_C45_1.34e+05_phi45_105_C50_1.79e+08_C52_9.19e+06_phi52_259_C54_-1.95e+07_phi54_150_C56_-1.06e+07_phi56_184 +2026-06-24 05:57:48,572 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184 +2026-06-24 05:57:48,573 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184' is generated! +2026-06-24 05:57:48,719 - +2026-06-24 05:57:48,731 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/20260624_055748_ptyrad_log.txt ### +2026-06-24 05:57:48,731 - +2026-06-24 05:57:48,733 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:57:48,733 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:57:48,733 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:57:49,907 - Iter: 1, Total Loss: 0.4566, loss_single: 0.4566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:57:49,944 - Iter: 2, Total Loss: 0.4456, loss_single: 0.4456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:57:49,979 - Iter: 3, Total Loss: 0.4355, loss_single: 0.4355, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,014 - Iter: 4, Total Loss: 0.4251, loss_single: 0.4251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,049 - Iter: 5, Total Loss: 0.4146, loss_single: 0.4146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,084 - Iter: 6, Total Loss: 0.4054, loss_single: 0.4054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,119 - Iter: 7, Total Loss: 0.3973, loss_single: 0.3973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,155 - Iter: 8, Total Loss: 0.3892, loss_single: 0.3892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,190 - Iter: 9, Total Loss: 0.3815, loss_single: 0.3815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,224 - Iter: 10, Total Loss: 0.3736, loss_single: 0.3736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,259 - Iter: 11, Total Loss: 0.3647, loss_single: 0.3647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,297 - Iter: 12, Total Loss: 0.3566, loss_single: 0.3566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:57:50,332 - Iter: 13, Total Loss: 0.3495, loss_single: 0.3495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,367 - Iter: 14, Total Loss: 0.3423, loss_single: 0.3423, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,402 - Iter: 15, Total Loss: 0.3358, loss_single: 0.3358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,437 - Iter: 16, Total Loss: 0.3296, loss_single: 0.3296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,472 - Iter: 17, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,507 - Iter: 18, Total Loss: 0.3178, loss_single: 0.3178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,542 - Iter: 19, Total Loss: 0.3122, loss_single: 0.3122, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,577 - Iter: 20, Total Loss: 0.3068, loss_single: 0.3068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,612 - Iter: 21, Total Loss: 0.3018, loss_single: 0.3018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,647 - Iter: 22, Total Loss: 0.2970, loss_single: 0.2970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,682 - Iter: 23, Total Loss: 0.2927, loss_single: 0.2927, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,717 - Iter: 24, Total Loss: 0.2897, loss_single: 0.2897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,753 - Iter: 25, Total Loss: 0.2872, loss_single: 0.2872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,787 - Iter: 26, Total Loss: 0.2845, loss_single: 0.2845, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,822 - Iter: 27, Total Loss: 0.2824, loss_single: 0.2824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:50,857 - Iter: 28, Total Loss: 0.2800, loss_single: 0.2800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,892 - Iter: 29, Total Loss: 0.2774, loss_single: 0.2774, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,928 - Iter: 30, Total Loss: 0.2749, loss_single: 0.2749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:50,962 - Iter: 31, Total Loss: 0.2723, loss_single: 0.2723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,000 - Iter: 32, Total Loss: 0.2700, loss_single: 0.2700, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:57:51,035 - Iter: 33, Total Loss: 0.2681, loss_single: 0.2681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,070 - Iter: 34, Total Loss: 0.2662, loss_single: 0.2662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,105 - Iter: 35, Total Loss: 0.2645, loss_single: 0.2645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,141 - Iter: 36, Total Loss: 0.2629, loss_single: 0.2629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,176 - Iter: 37, Total Loss: 0.2618, loss_single: 0.2618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,210 - Iter: 38, Total Loss: 0.2609, loss_single: 0.2609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,246 - Iter: 39, Total Loss: 0.2600, loss_single: 0.2600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,280 - Iter: 40, Total Loss: 0.2591, loss_single: 0.2591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,318 - Iter: 41, Total Loss: 0.2581, loss_single: 0.2581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,353 - Iter: 42, Total Loss: 0.2572, loss_single: 0.2572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,388 - Iter: 43, Total Loss: 0.2565, loss_single: 0.2565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,423 - Iter: 44, Total Loss: 0.2556, loss_single: 0.2556, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,458 - Iter: 45, Total Loss: 0.2548, loss_single: 0.2548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,493 - Iter: 46, Total Loss: 0.2541, loss_single: 0.2541, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,528 - Iter: 47, Total Loss: 0.2534, loss_single: 0.2534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,563 - Iter: 48, Total Loss: 0.2528, loss_single: 0.2528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,598 - Iter: 49, Total Loss: 0.2522, loss_single: 0.2522, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:57:51,633 - Iter: 50, Total Loss: 0.2518, loss_single: 0.2518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,668 - Iter: 51, Total Loss: 0.2514, loss_single: 0.2514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,703 - Iter: 52, Total Loss: 0.2509, loss_single: 0.2509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,742 - Iter: 53, Total Loss: 0.2504, loss_single: 0.2504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:57:51,777 - Iter: 54, Total Loss: 0.2499, loss_single: 0.2499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,812 - Iter: 55, Total Loss: 0.2494, loss_single: 0.2494, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,848 - Iter: 56, Total Loss: 0.2490, loss_single: 0.2490, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,883 - Iter: 57, Total Loss: 0.2486, loss_single: 0.2486, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:57:51,918 - Iter: 58, Total Loss: 0.2482, loss_single: 0.2482, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/simulation_data3__sample_000012.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/simulation_data3__sample_000012.yaml new file mode 100644 index 0000000000000000000000000000000000000000..be1ab00d28a8efa967222209315ba95059212742 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/simulation_data3__sample_000012.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 28.509687423706055 + probe_aberrations: + C10: 26.683876037597656 + C12: -19.53023338317871 + C21: 690.4555053710938 + C23: 60.33770751953125 + C30: 56705.9296875 + C32: -7221.25732421875 + C34: 7660.6162109375 + C41: -208663.34375 + C43: 390834.9375 + C45: 134100.0 + C50: 179485072.0 + C52: 9193875.0 + C54: -19467058.0 + C56: -10610066.0 + phi12: 305.79909850078985 + phi21: 356.3084293753042 + phi23: 222.492674552735 + phi32: 141.6315812709498 + phi34: 77.24999958835616 + phi41: 286.9572840148793 + phi43: 160.94954190428024 + phi45: 104.64339533023025 + phi52: 258.63918311222307 + phi54: 149.75988887385847 + phi56: 184.2894184492377 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.44282132387161255 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000012_measurement.h5 + key: measurement + random_seed: 20261940 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000012 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000012/c30_small__simulation_data3__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_26.7_C12_-19.5_phi12_306_C21_690_phi21_356_C23_60.3_phi23_222_C30_5.67e+04_C32_-7.06e+07_phi56_184/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/20260624_055818_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:58:16,758 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:58:16,758 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:58:16,758 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:58:16,758 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:58:16,758 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:58:16,758 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:58:16,758 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:58:16,758 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:58:16,758 - +2026-06-24 05:58:16,867 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:58:16,867 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:58:16,867 - Accelerator.num_process = 1 +2026-06-24 05:58:16,867 - Accelerator.mixed_precision = no +2026-06-24 05:58:16,889 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:58:16,889 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:58:16,889 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:58:16,889 - +2026-06-24 05:58:16,889 - ### System information ### +2026-06-24 05:58:16,889 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:58:16,889 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:58:16,889 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:58:16,889 - Machine: x86_64 +2026-06-24 05:58:16,889 - Processor: x86_64 +2026-06-24 05:58:16,889 - Available CPU cores: 8 +2026-06-24 05:58:16,889 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:58:16,889 - +2026-06-24 05:58:16,889 - ### GPU information ### +2026-06-24 05:58:16,889 - CUDA Available: True +2026-06-24 05:58:16,889 - CUDA Version: 13.0 +2026-06-24 05:58:16,890 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:58:16,890 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:58:16,890 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:58:16,890 - In addition, Triton does not directly support Windows. +2026-06-24 05:58:16,890 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:58:16,905 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:58:16,905 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:58:16,905 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:58:16,905 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:58:16,905 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:58:16,905 - +2026-06-24 05:58:16,905 - ### Python information ### +2026-06-24 05:58:16,907 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:58:16,907 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:58:16,907 - +2026-06-24 05:58:16,907 - ### Packages information ### +2026-06-24 05:58:16,908 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:58:16,909 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:58:16,909 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:58:16,910 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:58:16,910 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:58:16,910 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:58:16,910 - +2026-06-24 05:58:16,911 - ### Loading params file ### +2026-06-24 05:58:16,911 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000014.yaml +2026-06-24 05:58:16,917 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:58:16,918 - Success! Params file validated and defaults applied. +2026-06-24 05:58:16,918 - +2026-06-24 05:58:16,918 - ### Setting GPU Device ### +2026-06-24 05:58:16,918 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:58:16,918 - +2026-06-24 05:58:16,918 - Random seed: 20261942 provided by params file +2026-06-24 05:58:16,918 - ### Initializing Initializer ### +2026-06-24 05:58:16,919 - init_params are displayed below: +2026-06-24 05:58:16,919 - random_seed: 20261942 +2026-06-24 05:58:16,919 - probe_illum_type: electron +2026-06-24 05:58:16,919 - probe_kv: 30.0 +2026-06-24 05:58:16,919 - probe_conv_angle: 15.594320297241211 +2026-06-24 05:58:16,919 - probe_aberrations: {'C10': -448.102, 'C12': 25.775, 'phi12': 77.818, 'C21': 634.609, 'phi21': 102.305, 'C23': -403.503, 'phi23': 155.027, 'C30': 4005126.25, 'C32': -9116.148, 'phi32': 109.776, 'C34': -11275.234, 'phi34': 17.632, 'C41': 391634.625, 'phi41': 45.147, 'C43': -295829.344, 'phi43': 128.062, 'C45': 422199.531, 'phi45': 181.214, 'C50': -238394544.0, 'C52': -3324134.5, 'phi52': 90.671, 'C54': 4495996.0, 'phi54': 51.305, 'C56': 6198037.0, 'phi56': 248.82} +2026-06-24 05:58:16,919 - beam_kev: None +2026-06-24 05:58:16,919 - probe_dRn: None +2026-06-24 05:58:16,919 - probe_Rn: None +2026-06-24 05:58:16,919 - probe_D_H: None +2026-06-24 05:58:16,919 - probe_D_FZP: None +2026-06-24 05:58:16,919 - probe_Ls: None +2026-06-24 05:58:16,919 - meas_Npix: 128 +2026-06-24 05:58:16,919 - pos_N_scans: 256 +2026-06-24 05:58:16,919 - pos_N_scan_slow: 16 +2026-06-24 05:58:16,919 - pos_N_scan_fast: 16 +2026-06-24 05:58:16,919 - pos_scan_step_size: 0.4895961284637451 +2026-06-24 05:58:16,919 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:58:16,919 - probe_pmode_max: 6 +2026-06-24 05:58:16,919 - probe_pmode_init_pows: [0.02] +2026-06-24 05:58:16,919 - obj_omode_max: 1 +2026-06-24 05:58:16,919 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:58:16,919 - obj_Nlayer: 1 +2026-06-24 05:58:16,919 - obj_slice_thickness: 20.0 +2026-06-24 05:58:16,919 - simu_Npix: None +2026-06-24 05:58:16,919 - simu_match_mode: None +2026-06-24 05:58:16,919 - meas_permute: None +2026-06-24 05:58:16,919 - meas_reshape: [256, 128, 128] +2026-06-24 05:58:16,919 - meas_flipT: [0, 0, 0] +2026-06-24 05:58:16,919 - meas_crop: None +2026-06-24 05:58:16,919 - meas_pad: None +2026-06-24 05:58:16,919 - meas_resample: None +2026-06-24 05:58:16,919 - meas_add_source_size: None +2026-06-24 05:58:16,919 - meas_add_detector_blur: None +2026-06-24 05:58:16,919 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:58:16,919 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:58:16,919 - meas_add_poisson_noise: None +2026-06-24 05:58:16,920 - meas_export: None +2026-06-24 05:58:16,920 - probe_permute: None +2026-06-24 05:58:16,920 - probe_z_shift: None +2026-06-24 05:58:16,920 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:58:16,920 - pos_scan_flipT: None +2026-06-24 05:58:16,920 - pos_scan_affine: None +2026-06-24 05:58:16,920 - pos_scan_rand_std: 0.15 +2026-06-24 05:58:16,920 - obj_z_crop: None +2026-06-24 05:58:16,920 - obj_z_pad: None +2026-06-24 05:58:16,920 - obj_z_resample: None +2026-06-24 05:58:16,920 - meas_source: file +2026-06-24 05:58:16,920 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000014_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:58:16,920 - probe_source: simu +2026-06-24 05:58:16,920 - probe_params: None +2026-06-24 05:58:16,920 - pos_source: simu +2026-06-24 05:58:16,920 - pos_params: None +2026-06-24 05:58:16,920 - obj_source: simu +2026-06-24 05:58:16,920 - obj_params: None +2026-06-24 05:58:16,920 - tilt_source: simu +2026-06-24 05:58:16,920 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:58:16,920 - +2026-06-24 05:58:16,920 - ### Initializing cache ### +2026-06-24 05:58:16,920 - use_cached_obj = False +2026-06-24 05:58:16,920 - use_cached_probe = False +2026-06-24 05:58:16,920 - use_cached_pos = False +2026-06-24 05:58:16,920 - +2026-06-24 05:58:16,920 - ### Initializing measurements ### +2026-06-24 05:58:16,920 - Loading measurements from source = 'file' +2026-06-24 05:58:16,920 - Detected measurement file type = '.h5' +2026-06-24 05:58:17,002 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:58:17,002 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:58:17,004 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0094) +2026-06-24 05:58:17,004 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:58:17,004 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:58:17,006 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:58:17,006 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:58:17,006 - Normalizing by max of the 2D mean pattern intensity: 0.0083224084 +2026-06-24 05:58:17,007 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:58:17,008 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0073, 1.1260) +2026-06-24 05:58:17,009 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:58:17,010 - Pattern total int. statistics (min, mean, max) = (119.0432, 119.7669, 120.5485), with min/max = 98.8% +2026-06-24 05:58:17,011 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0073, 1.1260) +2026-06-24 05:58:17,011 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:58:17,011 - +2026-06-24 05:58:17,011 - ### Setting up calibration ### +2026-06-24 05:58:17,011 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:58:17,011 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:58:17,011 - Radius of fitted bright field disk (RBF) = 5.67 px with meas_Npix = 128 +2026-06-24 05:58:17,011 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0886 +2026-06-24 05:58:17,011 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:58:17,012 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:58:17,241 - Initial guess: center=(63.62, 63.63), radius=5.67, Gaussian blur std=0.50 +2026-06-24 05:58:17,253 - Final fit: center=(63.62, 63.63), radius=5.67, Gaussian blur std=0.70 +2026-06-24 05:58:17,253 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 5.72 px with Npix = 128 +2026-06-24 05:58:17,253 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:58:17,253 - +2026-06-24 05:58:17,253 - ### Setting init_variables dict ### +2026-06-24 05:58:17,253 - Derived values given input init_params: +2026-06-24 05:58:17,253 - kv = 30.0 kV +2026-06-24 05:58:17,253 - wavelength = 0.0698 Ang +2026-06-24 05:58:17,253 - conv_angle = 15.594320297241211 mrad +2026-06-24 05:58:17,253 - Npix = 128 px +2026-06-24 05:58:17,253 - dk = 0.0391 Ang^-1 +2026-06-24 05:58:17,253 - kMax = 2.5000 Ang^-1 +2026-06-24 05:58:17,253 - da = 2.7262 mrad +2026-06-24 05:58:17,253 - angleMax = 174.4770 mrad +2026-06-24 05:58:17,253 - RBF = 5.7202 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:58:17,253 - n_alpha = 11.1885 (# conv_angle) +2026-06-24 05:58:17,253 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:58:17,253 - Rayleigh-limited resolution = 2.7300 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:58:17,253 - Real space probe extent = 25.6000 Ang +2026-06-24 05:58:17,254 - +2026-06-24 05:58:17,254 - ### Initializing probe ### +2026-06-24 05:58:17,254 - Loading probe from source = 'simu' +2026-06-24 05:58:17,254 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:58:17,254 - Start simulating STEM probe +2026-06-24 05:58:17,254 - kv = 30.0 kV +2026-06-24 05:58:17,254 - wavelength = 0.0698 Ang +2026-06-24 05:58:17,254 - conv_angle = 15.594320297241211 mrad +2026-06-24 05:58:17,254 - Npix = 128 px +2026-06-24 05:58:17,254 - dk = 0.0391 Ang^-1 +2026-06-24 05:58:17,254 - kMax = 2.5000 Ang^-1 +2026-06-24 05:58:17,254 - alpha_max = 174.4770 mrad +2026-06-24 05:58:17,254 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:58:17,254 - Rayleigh-limited resolution = 2.7300 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:58:17,254 - Real space probe extent = 25.6000 Ang +2026-06-24 05:58:17,254 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:58:17,254 - ------------------------------------------------------------------------------------- +2026-06-24 05:58:17,254 - C1,0 C1 -448.1020 - Defocus (C10 = -df) +2026-06-24 05:58:17,254 - C1,2 A1 25.7750 77.82 2-fold astigmatism +2026-06-24 05:58:17,254 - C2,1 3*B2 634.6090 102.31 Axial coma +2026-06-24 05:58:17,254 - C2,3 A2 -403.5030 155.03 3-fold astigmatism +2026-06-24 05:58:17,254 - C3,0 C3 4005126.2500 - Spherical aberration +2026-06-24 05:58:17,254 - C3,2 4*S3 -9116.1480 109.78 Axial star aberration +2026-06-24 05:58:17,254 - C3,4 A3 -11275.2340 17.63 4-fold astigmatism +2026-06-24 05:58:17,254 - C4,1 4*B4 391634.6250 45.15 Axial coma(4th) +2026-06-24 05:58:17,255 - C4,3 4*D4 -295829.3440 128.06 3-lobe aberration +2026-06-24 05:58:17,255 - C4,5 A4 422199.5310 181.21 5-fold astigmatism +2026-06-24 05:58:17,255 - C5,0 C5 -238394544.0000 - Spherical aberration (5th) +2026-06-24 05:58:17,255 - C5,2 6*S5 -3324134.5000 90.67 Axial star aberration(5th) +2026-06-24 05:58:17,255 - C5,4 6*R5 4495996.0000 51.30 4-lobe aberration +2026-06-24 05:58:17,255 - C5,6 A5 6198037.0000 248.82 6-fold astigmatism +2026-06-24 05:58:17,258 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:58:17,258 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:58:17,258 - Creating 5 new probe modes from the major mode +2026-06-24 05:58:17,258 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:58:17,360 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:58:17,361 - Orthogonalizing 6 pmodes +2026-06-24 05:58:17,363 - Sorting 6 pmodes by their intensities +2026-06-24 05:58:17,363 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:58:17,364 - sum(|probe_data|**2) = 119.77, while meas_total_ints (min, mean, max) = (119.0432, 119.7669, 120.5485) +2026-06-24 05:58:17,364 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:58:17,364 - +2026-06-24 05:58:17,364 - ### Initializing probe positions ### +2026-06-24 05:58:17,364 - Loading probe positions from source = 'simu' +2026-06-24 05:58:17,364 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:58:17,364 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4896, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:58:17,364 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:58:17,366 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:58:17,366 - crop_pos 1st and last px coords (y,x) = ([17, 17], [53, 53]) +2026-06-24 05:58:17,367 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 05:58:17,367 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:58:17,367 - +2026-06-24 05:58:17,367 - ### Initializing object ### +2026-06-24 05:58:17,367 - Loading object from source = 'simu' +2026-06-24 05:58:17,367 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:58:17,368 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:58:17,368 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 05:58:17,368 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 05:58:17,368 - +2026-06-24 05:58:17,369 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:58:17,369 - omode_occu (omode) = float32, (1,) +2026-06-24 05:58:17,369 - +2026-06-24 05:58:17,369 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:58:17,369 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0698 Ang +2026-06-24 05:58:17,369 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:58:17,369 - +2026-06-24 05:58:17,369 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:58:17,369 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:58:17,370 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:58:17,370 - +2026-06-24 05:58:17,370 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:58:17,370 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:58:17,370 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:58:17,370 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:58:17,370 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:58:17,370 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 05:58:17,370 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:58:17,370 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:58:17,370 - +2026-06-24 05:58:17,370 - ### Collecting reconstruction provenance ### +2026-06-24 05:58:17,370 - Reconstruction provenance is collected and initialized. +2026-06-24 05:58:17,370 - +2026-06-24 05:58:17,370 - ### Initializing loss function ### +2026-06-24 05:58:17,370 - Active loss types: +2026-06-24 05:58:17,370 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:58:17,370 - +2026-06-24 05:58:17,370 - ### Initializing constraint function ### +2026-06-24 05:58:17,370 - Active constraint types: +2026-06-24 05:58:17,370 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:58:17,370 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:58:17,371 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:58:17,371 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:58:17,371 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:58:17,371 - +2026-06-24 05:58:17,371 - ### Done initializing PtyRADSolver ### +2026-06-24 05:58:17,371 - +2026-06-24 05:58:17,497 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:58:17,497 - +2026-06-24 05:58:17,497 - ### Initializing PtychoModel model ### +2026-06-24 05:58:17,567 - ### PtychoModel optimizable variables ### +2026-06-24 05:58:17,567 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:17,567 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:17,567 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:58:17,567 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:58:17,568 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:58:17,568 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:17,568 - +2026-06-24 05:58:17,568 - ### Optimizable variables statitsics ### +2026-06-24 05:58:17,568 - Total measurement values : 4,194,304 +2026-06-24 05:58:17,568 - Total optimizing variables: 276,322 +2026-06-24 05:58:17,568 - Overdetermined ratio : 15.18 +2026-06-24 05:58:17,568 - +2026-06-24 05:58:17,568 - ### Model behavior ### +2026-06-24 05:58:17,568 - Tilt propagator : False +2026-06-24 05:58:17,568 - Change slice thickness : False +2026-06-24 05:58:17,568 - Detector blur : False +2026-06-24 05:58:17,568 - Preload data : True +2026-06-24 05:58:17,568 - On-the-fly meas padding : False +2026-06-24 05:58:17,568 - On-the-fly meas resample : False +2026-06-24 05:58:17,568 - On-the-fly simu match mode: None +2026-06-24 05:58:17,568 - +2026-06-24 05:58:17,609 - ### Done initializing PtychoModel model ### +2026-06-24 05:58:17,609 - +2026-06-24 05:58:17,610 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:58:17,610 - +2026-06-24 05:58:17,610 - ### Generating indices, batches, and output_path ### +2026-06-24 05:58:17,611 - d90 = 63.000 px or 12.600 Ang +2026-06-24 05:58:17,611 - Selecting indices with the 'full' mode +2026-06-24 05:58:18,068 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:58:18,143 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:58:18,143 - Original recon_dir_affixes = ['default'] +2026-06-24 05:58:18,143 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:58:18,149 - Path corrected for compatibility: +2026-06-24 05:58:18,149 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9.12e+03_phi32_110_C34_-1.13e+04_phi34_17.6_C41_3.92e+05_phi41_45.1_C43_-2.96e+05_phi43_128_C45_4.22e+05_phi45_181_C50_-2.38e+08_C52_-3.32e+06_phi52_90.7_C54_4.5e+06_phi54_51.3_C56_6.2e+06_phi56_249 +2026-06-24 05:58:18,149 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249 +2026-06-24 05:58:18,150 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249' is generated! +2026-06-24 05:58:18,306 - +2026-06-24 05:58:18,307 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/20260624_055818_ptyrad_log.txt ### +2026-06-24 05:58:18,307 - +2026-06-24 05:58:18,308 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:58:18,308 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:58:18,308 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:58:19,490 - Iter: 1, Total Loss: 1.5343, loss_single: 1.5343, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:58:19,527 - Iter: 2, Total Loss: 1.4543, loss_single: 1.4543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:19,563 - Iter: 3, Total Loss: 1.3952, loss_single: 1.3952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,597 - Iter: 4, Total Loss: 1.3360, loss_single: 1.3360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:19,632 - Iter: 5, Total Loss: 1.2764, loss_single: 1.2764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,668 - Iter: 6, Total Loss: 1.2242, loss_single: 1.2242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,703 - Iter: 7, Total Loss: 1.1772, loss_single: 1.1772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,738 - Iter: 8, Total Loss: 1.1306, loss_single: 1.1306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,773 - Iter: 9, Total Loss: 1.0732, loss_single: 1.0732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,808 - Iter: 10, Total Loss: 1.0209, loss_single: 1.0209, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,843 - Iter: 11, Total Loss: 0.9765, loss_single: 0.9765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,878 - Iter: 12, Total Loss: 0.9263, loss_single: 0.9263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,913 - Iter: 13, Total Loss: 0.8696, loss_single: 0.8696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:19,948 - Iter: 14, Total Loss: 0.8160, loss_single: 0.8160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:19,983 - Iter: 15, Total Loss: 0.7627, loss_single: 0.7627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,018 - Iter: 16, Total Loss: 0.7109, loss_single: 0.7109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,053 - Iter: 17, Total Loss: 0.6585, loss_single: 0.6585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,088 - Iter: 18, Total Loss: 0.6123, loss_single: 0.6123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,124 - Iter: 19, Total Loss: 0.5726, loss_single: 0.5726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,159 - Iter: 20, Total Loss: 0.5328, loss_single: 0.5328, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,193 - Iter: 21, Total Loss: 0.4943, loss_single: 0.4943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,230 - Iter: 22, Total Loss: 0.4605, loss_single: 0.4605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:20,264 - Iter: 23, Total Loss: 0.4369, loss_single: 0.4369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,299 - Iter: 24, Total Loss: 0.4177, loss_single: 0.4177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,334 - Iter: 25, Total Loss: 0.4022, loss_single: 0.4022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,370 - Iter: 26, Total Loss: 0.3871, loss_single: 0.3871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,405 - Iter: 27, Total Loss: 0.3714, loss_single: 0.3714, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,440 - Iter: 28, Total Loss: 0.3599, loss_single: 0.3599, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,475 - Iter: 29, Total Loss: 0.3506, loss_single: 0.3506, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,510 - Iter: 30, Total Loss: 0.3440, loss_single: 0.3440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,545 - Iter: 31, Total Loss: 0.3388, loss_single: 0.3388, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,580 - Iter: 32, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,615 - Iter: 33, Total Loss: 0.3313, loss_single: 0.3313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,651 - Iter: 34, Total Loss: 0.3285, loss_single: 0.3285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,685 - Iter: 35, Total Loss: 0.3268, loss_single: 0.3268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,721 - Iter: 36, Total Loss: 0.3254, loss_single: 0.3254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:20,756 - Iter: 37, Total Loss: 0.3242, loss_single: 0.3242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,791 - Iter: 38, Total Loss: 0.3231, loss_single: 0.3231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,827 - Iter: 39, Total Loss: 0.3221, loss_single: 0.3221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,862 - Iter: 40, Total Loss: 0.3216, loss_single: 0.3216, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,899 - Iter: 41, Total Loss: 0.3212, loss_single: 0.3212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:20,934 - Iter: 42, Total Loss: 0.3208, loss_single: 0.3208, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:20,969 - Iter: 43, Total Loss: 0.3206, loss_single: 0.3206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,004 - Iter: 44, Total Loss: 0.3203, loss_single: 0.3203, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,039 - Iter: 45, Total Loss: 0.3201, loss_single: 0.3201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,074 - Iter: 46, Total Loss: 0.3199, loss_single: 0.3199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,109 - Iter: 47, Total Loss: 0.3197, loss_single: 0.3197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,144 - Iter: 48, Total Loss: 0.3196, loss_single: 0.3196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,179 - Iter: 49, Total Loss: 0.3194, loss_single: 0.3194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,214 - Iter: 50, Total Loss: 0.3193, loss_single: 0.3193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,249 - Iter: 51, Total Loss: 0.3192, loss_single: 0.3192, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,284 - Iter: 52, Total Loss: 0.3191, loss_single: 0.3191, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,320 - Iter: 53, Total Loss: 0.3190, loss_single: 0.3190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,355 - Iter: 54, Total Loss: 0.3189, loss_single: 0.3189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,390 - Iter: 55, Total Loss: 0.3189, loss_single: 0.3189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,425 - Iter: 56, Total Loss: 0.3188, loss_single: 0.3188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,460 - Iter: 57, Total Loss: 0.3187, loss_single: 0.3187, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,495 - Iter: 58, Total Loss: 0.3186, loss_single: 0.3186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,530 - Iter: 59, Total Loss: 0.3186, loss_single: 0.3186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,565 - Iter: 60, Total Loss: 0.3185, loss_single: 0.3185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,600 - Iter: 61, Total Loss: 0.3184, loss_single: 0.3184, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,635 - Iter: 62, Total Loss: 0.3184, loss_single: 0.3184, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,670 - Iter: 63, Total Loss: 0.3184, loss_single: 0.3184, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,705 - Iter: 64, Total Loss: 0.3183, loss_single: 0.3183, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:21,740 - Iter: 65, Total Loss: 0.3183, loss_single: 0.3183, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,775 - Iter: 66, Total Loss: 0.3182, loss_single: 0.3182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,810 - Iter: 67, Total Loss: 0.3182, loss_single: 0.3182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,845 - Iter: 68, Total Loss: 0.3181, loss_single: 0.3181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,882 - Iter: 69, Total Loss: 0.3181, loss_single: 0.3181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:21,917 - Iter: 70, Total Loss: 0.3180, loss_single: 0.3180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,952 - Iter: 71, Total Loss: 0.3180, loss_single: 0.3180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:21,987 - Iter: 72, Total Loss: 0.3180, loss_single: 0.3180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,022 - Iter: 73, Total Loss: 0.3179, loss_single: 0.3179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,057 - Iter: 74, Total Loss: 0.3179, loss_single: 0.3179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,092 - Iter: 75, Total Loss: 0.3178, loss_single: 0.3178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,127 - Iter: 76, Total Loss: 0.3178, loss_single: 0.3178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,162 - Iter: 77, Total Loss: 0.3177, loss_single: 0.3177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,197 - Iter: 78, Total Loss: 0.3177, loss_single: 0.3177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,232 - Iter: 79, Total Loss: 0.3176, loss_single: 0.3176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,267 - Iter: 80, Total Loss: 0.3176, loss_single: 0.3176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,303 - Iter: 81, Total Loss: 0.3176, loss_single: 0.3176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,338 - Iter: 82, Total Loss: 0.3175, loss_single: 0.3175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,373 - Iter: 83, Total Loss: 0.3175, loss_single: 0.3175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,408 - Iter: 84, Total Loss: 0.3175, loss_single: 0.3175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,443 - Iter: 85, Total Loss: 0.3174, loss_single: 0.3174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,478 - Iter: 86, Total Loss: 0.3174, loss_single: 0.3174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,513 - Iter: 87, Total Loss: 0.3173, loss_single: 0.3173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,548 - Iter: 88, Total Loss: 0.3173, loss_single: 0.3173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,583 - Iter: 89, Total Loss: 0.3172, loss_single: 0.3172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,618 - Iter: 90, Total Loss: 0.3172, loss_single: 0.3172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,653 - Iter: 91, Total Loss: 0.3171, loss_single: 0.3171, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,688 - Iter: 92, Total Loss: 0.3171, loss_single: 0.3171, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,723 - Iter: 93, Total Loss: 0.3170, loss_single: 0.3170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,758 - Iter: 94, Total Loss: 0.3170, loss_single: 0.3170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,794 - Iter: 95, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,828 - Iter: 96, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,863 - Iter: 97, Total Loss: 0.3168, loss_single: 0.3168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:58:22,898 - Iter: 98, Total Loss: 0.3168, loss_single: 0.3168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,933 - Iter: 99, Total Loss: 0.3167, loss_single: 0.3167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:22,968 - Iter: 100, Total Loss: 0.3167, loss_single: 0.3167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:23,081 - Saving summary figures for iter 100 +2026-06-24 05:58:26,630 - ### Finished 100 iterations, averaged iter_t = 0.038701 with std = 0.040 ### +2026-06-24 05:58:26,630 - +2026-06-24 05:58:26,631 - ### The PtyRADSolver is finished in 9.134 sec ### +2026-06-24 05:58:26,631 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..20611eeeee97600809dbc8e27caf2efee5a81a1e Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/simulation_data3__sample_000014.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/simulation_data3__sample_000014.yaml new file mode 100644 index 0000000000000000000000000000000000000000..17b8c113862fc3d4bc452aec0ae8bae7a0ab8e7e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014/c30_small__simulation_data3__sample_000014_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_25.8_phi12_77.8_C21_635_phi21_102_C23_-404_phi23_155_C30_4.01e+06_C32_-9..2e+06_phi56_249/simulation_data3__sample_000014.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 30.0 + probe_conv_angle: 15.594320297241211 + probe_aberrations: + C10: -448.1016540527344 + C12: 25.77499771118164 + C21: 634.6089477539062 + C23: -403.5030822753906 + C30: 4005126.25 + C32: -9116.1484375 + C34: -11275.234375 + C41: 391634.625 + C43: -295829.34375 + C45: 422199.53125 + C50: -238394544.0 + C52: -3324134.5 + C54: 4495996.0 + C56: 6198037.0 + phi12: 77.81786834614019 + phi21: 102.30473855841788 + phi23: 155.0272214787456 + phi32: 109.77618686884645 + phi34: 17.632124804651454 + phi41: 45.147140602434085 + phi43: 128.06174391856197 + phi45: 181.2138389074943 + phi52: 90.67142376026877 + phi54: 51.305068403388326 + phi56: 248.82002119914267 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4895961284637451 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000014_measurement.h5 + key: measurement + random_seed: 20261942 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000014 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000014 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/20260624_055847_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/20260624_055847_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..4d6d8b4ced477d3f279128a44b9b116bb25baa22 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/20260624_055847_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:58:46,206 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:58:46,206 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:58:46,207 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:58:46,207 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:58:46,207 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:58:46,207 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:58:46,207 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:58:46,207 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:58:46,207 - +2026-06-24 05:58:46,315 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:58:46,315 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:58:46,315 - Accelerator.num_process = 1 +2026-06-24 05:58:46,315 - Accelerator.mixed_precision = no +2026-06-24 05:58:46,326 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:58:46,326 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:58:46,326 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:58:46,326 - +2026-06-24 05:58:46,326 - ### System information ### +2026-06-24 05:58:46,326 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:58:46,326 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:58:46,326 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:58:46,326 - Machine: x86_64 +2026-06-24 05:58:46,326 - Processor: x86_64 +2026-06-24 05:58:46,326 - Available CPU cores: 8 +2026-06-24 05:58:46,326 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:58:46,326 - +2026-06-24 05:58:46,326 - ### GPU information ### +2026-06-24 05:58:46,326 - CUDA Available: True +2026-06-24 05:58:46,326 - CUDA Version: 13.0 +2026-06-24 05:58:46,327 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:58:46,327 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:58:46,327 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:58:46,327 - In addition, Triton does not directly support Windows. +2026-06-24 05:58:46,327 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:58:46,356 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:58:46,356 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:58:46,356 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:58:46,356 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:58:46,356 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:58:46,356 - +2026-06-24 05:58:46,356 - ### Python information ### +2026-06-24 05:58:46,358 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:58:46,358 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:58:46,358 - +2026-06-24 05:58:46,358 - ### Packages information ### +2026-06-24 05:58:46,359 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:58:46,359 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:58:46,360 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:58:46,361 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:58:46,361 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:58:46,361 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:58:46,361 - +2026-06-24 05:58:46,361 - ### Loading params file ### +2026-06-24 05:58:46,361 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000016.yaml +2026-06-24 05:58:46,368 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:58:46,369 - Success! Params file validated and defaults applied. +2026-06-24 05:58:46,369 - +2026-06-24 05:58:46,369 - ### Setting GPU Device ### +2026-06-24 05:58:46,369 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:58:46,369 - +2026-06-24 05:58:46,369 - Random seed: 20261944 provided by params file +2026-06-24 05:58:46,370 - ### Initializing Initializer ### +2026-06-24 05:58:46,370 - init_params are displayed below: +2026-06-24 05:58:46,370 - random_seed: 20261944 +2026-06-24 05:58:46,370 - probe_illum_type: electron +2026-06-24 05:58:46,370 - probe_kv: 160.0 +2026-06-24 05:58:46,370 - probe_conv_angle: 13.29338550567627 +2026-06-24 05:58:46,370 - probe_aberrations: {'C10': -162.874, 'C12': 39.286, 'phi12': 167.585, 'C21': 641.014, 'phi21': 83.952, 'C23': -747.915, 'phi23': 83.115, 'C30': 4187895.75, 'C32': 352.732, 'phi32': 337.96, 'C34': 3252.515, 'phi34': 186.828, 'C41': 99947.594, 'phi41': 355.936, 'C43': 285025.781, 'phi43': 83.376, 'C45': 243358.547, 'phi45': 348.253, 'C50': -317487264.0, 'C52': 15214170.0, 'phi52': 279.95, 'C54': -16656594.0, 'phi54': 68.32, 'C56': -5696292.5, 'phi56': 234.978} +2026-06-24 05:58:46,370 - beam_kev: None +2026-06-24 05:58:46,370 - probe_dRn: None +2026-06-24 05:58:46,370 - probe_Rn: None +2026-06-24 05:58:46,370 - probe_D_H: None +2026-06-24 05:58:46,370 - probe_D_FZP: None +2026-06-24 05:58:46,370 - probe_Ls: None +2026-06-24 05:58:46,370 - meas_Npix: 128 +2026-06-24 05:58:46,370 - pos_N_scans: 256 +2026-06-24 05:58:46,370 - pos_N_scan_slow: 16 +2026-06-24 05:58:46,370 - pos_N_scan_fast: 16 +2026-06-24 05:58:46,370 - pos_scan_step_size: 0.5252974629402161 +2026-06-24 05:58:46,370 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:58:46,370 - probe_pmode_max: 6 +2026-06-24 05:58:46,370 - probe_pmode_init_pows: [0.02] +2026-06-24 05:58:46,370 - obj_omode_max: 1 +2026-06-24 05:58:46,370 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:58:46,370 - obj_Nlayer: 1 +2026-06-24 05:58:46,370 - obj_slice_thickness: 20.0 +2026-06-24 05:58:46,370 - simu_Npix: None +2026-06-24 05:58:46,370 - simu_match_mode: None +2026-06-24 05:58:46,370 - meas_permute: None +2026-06-24 05:58:46,370 - meas_reshape: [256, 128, 128] +2026-06-24 05:58:46,370 - meas_flipT: [0, 0, 0] +2026-06-24 05:58:46,370 - meas_crop: None +2026-06-24 05:58:46,370 - meas_pad: None +2026-06-24 05:58:46,371 - meas_resample: None +2026-06-24 05:58:46,371 - meas_add_source_size: None +2026-06-24 05:58:46,371 - meas_add_detector_blur: None +2026-06-24 05:58:46,371 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:58:46,371 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:58:46,371 - meas_add_poisson_noise: None +2026-06-24 05:58:46,371 - meas_export: None +2026-06-24 05:58:46,371 - probe_permute: None +2026-06-24 05:58:46,371 - probe_z_shift: None +2026-06-24 05:58:46,371 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:58:46,371 - pos_scan_flipT: None +2026-06-24 05:58:46,371 - pos_scan_affine: None +2026-06-24 05:58:46,371 - pos_scan_rand_std: 0.15 +2026-06-24 05:58:46,371 - obj_z_crop: None +2026-06-24 05:58:46,371 - obj_z_pad: None +2026-06-24 05:58:46,371 - obj_z_resample: None +2026-06-24 05:58:46,371 - meas_source: file +2026-06-24 05:58:46,371 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000016_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:58:46,371 - probe_source: simu +2026-06-24 05:58:46,371 - probe_params: None +2026-06-24 05:58:46,371 - pos_source: simu +2026-06-24 05:58:46,371 - pos_params: None +2026-06-24 05:58:46,371 - obj_source: simu +2026-06-24 05:58:46,371 - obj_params: None +2026-06-24 05:58:46,371 - tilt_source: simu +2026-06-24 05:58:46,371 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:58:46,371 - +2026-06-24 05:58:46,371 - ### Initializing cache ### +2026-06-24 05:58:46,371 - use_cached_obj = False +2026-06-24 05:58:46,371 - use_cached_probe = False +2026-06-24 05:58:46,371 - use_cached_pos = False +2026-06-24 05:58:46,371 - +2026-06-24 05:58:46,371 - ### Initializing measurements ### +2026-06-24 05:58:46,371 - Loading measurements from source = 'file' +2026-06-24 05:58:46,371 - Detected measurement file type = '.h5' +2026-06-24 05:58:46,452 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:58:46,453 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:58:46,454 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0049) +2026-06-24 05:58:46,454 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:58:46,454 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:58:46,456 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:58:46,456 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:58:46,456 - Normalizing by max of the 2D mean pattern intensity: 0.0020172831 +2026-06-24 05:58:46,457 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:58:46,458 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0300, 2.4169) +2026-06-24 05:58:46,459 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:58:46,460 - Pattern total int. statistics (min, mean, max) = (484.5091, 490.7606, 495.8093), with min/max = 97.7% +2026-06-24 05:58:46,461 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0300, 2.4169) +2026-06-24 05:58:46,462 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:58:46,462 - +2026-06-24 05:58:46,462 - ### Setting up calibration ### +2026-06-24 05:58:46,462 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:58:46,462 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:58:46,462 - Radius of fitted bright field disk (RBF) = 11.83 px with meas_Npix = 128 +2026-06-24 05:58:46,462 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1849 +2026-06-24 05:58:46,462 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:58:46,462 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:58:46,685 - Initial guess: center=(63.63, 63.62), radius=11.83, Gaussian blur std=0.50 +2026-06-24 05:58:46,698 - Final fit: center=(63.63, 63.62), radius=11.83, Gaussian blur std=0.60 +2026-06-24 05:58:46,698 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.94 px with Npix = 128 +2026-06-24 05:58:46,698 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:58:46,698 - +2026-06-24 05:58:46,698 - ### Setting init_variables dict ### +2026-06-24 05:58:46,698 - Derived values given input init_params: +2026-06-24 05:58:46,698 - kv = 160.0 kV +2026-06-24 05:58:46,698 - wavelength = 0.0285 Ang +2026-06-24 05:58:46,698 - conv_angle = 13.29338550567627 mrad +2026-06-24 05:58:46,698 - Npix = 128 px +2026-06-24 05:58:46,698 - dk = 0.0391 Ang^-1 +2026-06-24 05:58:46,699 - kMax = 2.5000 Ang^-1 +2026-06-24 05:58:46,699 - da = 1.1137 mrad +2026-06-24 05:58:46,699 - angleMax = 71.2751 mrad +2026-06-24 05:58:46,699 - RBF = 11.9365 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:58:46,699 - n_alpha = 5.3617 (# conv_angle) +2026-06-24 05:58:46,699 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:58:46,699 - Rayleigh-limited resolution = 1.3083 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:58:46,699 - Real space probe extent = 25.6000 Ang +2026-06-24 05:58:46,699 - +2026-06-24 05:58:46,699 - ### Initializing probe ### +2026-06-24 05:58:46,699 - Loading probe from source = 'simu' +2026-06-24 05:58:46,699 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:58:46,699 - Start simulating STEM probe +2026-06-24 05:58:46,699 - kv = 160.0 kV +2026-06-24 05:58:46,699 - wavelength = 0.0285 Ang +2026-06-24 05:58:46,699 - conv_angle = 13.29338550567627 mrad +2026-06-24 05:58:46,699 - Npix = 128 px +2026-06-24 05:58:46,699 - dk = 0.0391 Ang^-1 +2026-06-24 05:58:46,699 - kMax = 2.5000 Ang^-1 +2026-06-24 05:58:46,699 - alpha_max = 71.2751 mrad +2026-06-24 05:58:46,699 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:58:46,699 - Rayleigh-limited resolution = 1.3083 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:58:46,699 - Real space probe extent = 25.6000 Ang +2026-06-24 05:58:46,699 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:58:46,700 - ------------------------------------------------------------------------------------- +2026-06-24 05:58:46,700 - C1,0 C1 -162.8740 - Defocus (C10 = -df) +2026-06-24 05:58:46,700 - C1,2 A1 39.2860 167.59 2-fold astigmatism +2026-06-24 05:58:46,700 - C2,1 3*B2 641.0140 83.95 Axial coma +2026-06-24 05:58:46,700 - C2,3 A2 -747.9150 83.11 3-fold astigmatism +2026-06-24 05:58:46,700 - C3,0 C3 4187895.7500 - Spherical aberration +2026-06-24 05:58:46,700 - C3,2 4*S3 352.7320 337.96 Axial star aberration +2026-06-24 05:58:46,700 - C3,4 A3 3252.5150 186.83 4-fold astigmatism +2026-06-24 05:58:46,700 - C4,1 4*B4 99947.5940 355.94 Axial coma(4th) +2026-06-24 05:58:46,700 - C4,3 4*D4 285025.7810 83.38 3-lobe aberration +2026-06-24 05:58:46,700 - C4,5 A4 243358.5470 348.25 5-fold astigmatism +2026-06-24 05:58:46,700 - C5,0 C5 -317487264.0000 - Spherical aberration (5th) +2026-06-24 05:58:46,700 - C5,2 6*S5 15214170.0000 279.95 Axial star aberration(5th) +2026-06-24 05:58:46,700 - C5,4 6*R5 -16656594.0000 68.32 4-lobe aberration +2026-06-24 05:58:46,700 - C5,6 A5 -5696292.5000 234.98 6-fold astigmatism +2026-06-24 05:58:46,703 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:58:46,703 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:58:46,703 - Creating 5 new probe modes from the major mode +2026-06-24 05:58:46,703 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:58:46,899 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:58:46,900 - Orthogonalizing 6 pmodes +2026-06-24 05:58:46,913 - Sorting 6 pmodes by their intensities +2026-06-24 05:58:46,913 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:58:46,914 - sum(|probe_data|**2) = 490.76, while meas_total_ints (min, mean, max) = (484.5091, 490.7606, 495.8093) +2026-06-24 05:58:46,914 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:58:46,914 - +2026-06-24 05:58:46,914 - ### Initializing probe positions ### +2026-06-24 05:58:46,914 - Loading probe positions from source = 'simu' +2026-06-24 05:58:46,914 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:58:46,914 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5253, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:58:46,914 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:58:46,916 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:58:46,916 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:58:46,917 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:58:46,917 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:58:46,917 - +2026-06-24 05:58:46,917 - ### Initializing object ### +2026-06-24 05:58:46,917 - Loading object from source = 'simu' +2026-06-24 05:58:46,917 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:58:46,918 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:58:46,918 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 201, 201) +2026-06-24 05:58:46,919 - object extent (Z, Y, X) (Ang) = [20. 40.2 40.2] +2026-06-24 05:58:46,919 - +2026-06-24 05:58:46,919 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:58:46,919 - omode_occu (omode) = float32, (1,) +2026-06-24 05:58:46,919 - +2026-06-24 05:58:46,919 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:58:46,919 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 05:58:46,919 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:58:46,919 - +2026-06-24 05:58:46,920 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:58:46,920 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:58:46,920 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:58:46,920 - +2026-06-24 05:58:46,920 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:58:46,920 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:58:46,920 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:58:46,920 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:58:46,920 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:58:46,920 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (201, 201). +2026-06-24 05:58:46,920 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:58:46,920 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:58:46,920 - +2026-06-24 05:58:46,920 - ### Collecting reconstruction provenance ### +2026-06-24 05:58:46,920 - Reconstruction provenance is collected and initialized. +2026-06-24 05:58:46,920 - +2026-06-24 05:58:46,920 - ### Initializing loss function ### +2026-06-24 05:58:46,920 - Active loss types: +2026-06-24 05:58:46,920 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:58:46,920 - +2026-06-24 05:58:46,921 - ### Initializing constraint function ### +2026-06-24 05:58:46,921 - Active constraint types: +2026-06-24 05:58:46,921 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:58:46,921 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:58:46,921 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:58:46,921 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:58:46,921 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:58:46,921 - +2026-06-24 05:58:46,921 - ### Done initializing PtyRADSolver ### +2026-06-24 05:58:46,921 - +2026-06-24 05:58:47,047 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:58:47,047 - +2026-06-24 05:58:47,047 - ### Initializing PtychoModel model ### +2026-06-24 05:58:47,118 - ### PtychoModel optimizable variables ### +2026-06-24 05:58:47,118 - obja : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:47,118 - objp : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:47,118 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:58:47,118 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:58:47,118 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:58:47,119 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:58:47,119 - +2026-06-24 05:58:47,119 - ### Optimizable variables statitsics ### +2026-06-24 05:58:47,119 - Total measurement values : 4,194,304 +2026-06-24 05:58:47,119 - Total optimizing variables: 277,922 +2026-06-24 05:58:47,119 - Overdetermined ratio : 15.09 +2026-06-24 05:58:47,119 - +2026-06-24 05:58:47,119 - ### Model behavior ### +2026-06-24 05:58:47,119 - Tilt propagator : False +2026-06-24 05:58:47,119 - Change slice thickness : False +2026-06-24 05:58:47,119 - Detector blur : False +2026-06-24 05:58:47,119 - Preload data : True +2026-06-24 05:58:47,119 - On-the-fly meas padding : False +2026-06-24 05:58:47,119 - On-the-fly meas resample : False +2026-06-24 05:58:47,119 - On-the-fly simu match mode: None +2026-06-24 05:58:47,119 - +2026-06-24 05:58:47,161 - ### Done initializing PtychoModel model ### +2026-06-24 05:58:47,161 - +2026-06-24 05:58:47,161 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:58:47,161 - +2026-06-24 05:58:47,161 - ### Generating indices, batches, and output_path ### +2026-06-24 05:58:47,162 - d90 = 59.000 px or 11.800 Ang +2026-06-24 05:58:47,162 - Selecting indices with the 'full' mode +2026-06-24 05:58:47,626 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:58:47,704 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:58:47,704 - Original recon_dir_affixes = ['default'] +2026-06-24 05:58:47,704 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:58:47,710 - Path corrected for compatibility: +2026-06-24 05:58:47,710 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_phi32_338_C34_3.25e+03_phi34_187_C41_9.99e+04_phi41_356_C43_2.85e+05_phi43_83.4_C45_2.43e+05_phi45_348_C50_-3.17e+08_C52_1.52e+07_phi52_280_C54_-1.67e+07_phi54_68.3_C56_-5.7e+06_phi56_235 +2026-06-24 05:58:47,710 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235 +2026-06-24 05:58:47,711 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235' is generated! +2026-06-24 05:58:47,865 - +2026-06-24 05:58:47,866 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/20260624_055847_ptyrad_log.txt ### +2026-06-24 05:58:47,866 - +2026-06-24 05:58:47,868 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:58:47,868 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:58:47,868 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:58:49,060 - Iter: 1, Total Loss: 1.1082, loss_single: 1.1082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:58:49,096 - Iter: 2, Total Loss: 1.0833, loss_single: 1.0833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:49,132 - Iter: 3, Total Loss: 1.0640, loss_single: 1.0640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,168 - Iter: 4, Total Loss: 1.0458, loss_single: 1.0458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,203 - Iter: 5, Total Loss: 1.0290, loss_single: 1.0290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,238 - Iter: 6, Total Loss: 1.0123, loss_single: 1.0123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,274 - Iter: 7, Total Loss: 0.9954, loss_single: 0.9954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,310 - Iter: 8, Total Loss: 0.9791, loss_single: 0.9791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,345 - Iter: 9, Total Loss: 0.9605, loss_single: 0.9605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,380 - Iter: 10, Total Loss: 0.9418, loss_single: 0.9418, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,416 - Iter: 11, Total Loss: 0.9257, loss_single: 0.9257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,451 - Iter: 12, Total Loss: 0.9110, loss_single: 0.9110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,486 - Iter: 13, Total Loss: 0.8937, loss_single: 0.8937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,522 - Iter: 14, Total Loss: 0.8767, loss_single: 0.8767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,557 - Iter: 15, Total Loss: 0.8630, loss_single: 0.8630, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,593 - Iter: 16, Total Loss: 0.8501, loss_single: 0.8501, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,628 - Iter: 17, Total Loss: 0.8363, loss_single: 0.8363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,664 - Iter: 18, Total Loss: 0.8215, loss_single: 0.8215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,700 - Iter: 19, Total Loss: 0.8098, loss_single: 0.8098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,735 - Iter: 20, Total Loss: 0.7987, loss_single: 0.7987, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,771 - Iter: 21, Total Loss: 0.7871, loss_single: 0.7871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,806 - Iter: 22, Total Loss: 0.7764, loss_single: 0.7764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,842 - Iter: 23, Total Loss: 0.7633, loss_single: 0.7633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,881 - Iter: 24, Total Loss: 0.7510, loss_single: 0.7510, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:58:49,916 - Iter: 25, Total Loss: 0.7394, loss_single: 0.7394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,951 - Iter: 26, Total Loss: 0.7280, loss_single: 0.7280, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:49,986 - Iter: 27, Total Loss: 0.7194, loss_single: 0.7194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,022 - Iter: 28, Total Loss: 0.7105, loss_single: 0.7105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:50,058 - Iter: 29, Total Loss: 0.7003, loss_single: 0.7003, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,093 - Iter: 30, Total Loss: 0.6917, loss_single: 0.6917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,129 - Iter: 31, Total Loss: 0.6827, loss_single: 0.6827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,165 - Iter: 32, Total Loss: 0.6735, loss_single: 0.6735, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,200 - Iter: 33, Total Loss: 0.6653, loss_single: 0.6653, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,236 - Iter: 34, Total Loss: 0.6578, loss_single: 0.6578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,272 - Iter: 35, Total Loss: 0.6505, loss_single: 0.6505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,307 - Iter: 36, Total Loss: 0.6423, loss_single: 0.6423, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,342 - Iter: 37, Total Loss: 0.6359, loss_single: 0.6359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,377 - Iter: 38, Total Loss: 0.6298, loss_single: 0.6298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,412 - Iter: 39, Total Loss: 0.6224, loss_single: 0.6224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,448 - Iter: 40, Total Loss: 0.6171, loss_single: 0.6171, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,485 - Iter: 41, Total Loss: 0.6125, loss_single: 0.6125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,520 - Iter: 42, Total Loss: 0.6078, loss_single: 0.6078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,556 - Iter: 43, Total Loss: 0.6030, loss_single: 0.6030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,591 - Iter: 44, Total Loss: 0.5975, loss_single: 0.5975, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,627 - Iter: 45, Total Loss: 0.5921, loss_single: 0.5921, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,663 - Iter: 46, Total Loss: 0.5870, loss_single: 0.5870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:58:50,698 - Iter: 47, Total Loss: 0.5819, loss_single: 0.5819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,734 - Iter: 48, Total Loss: 0.5772, loss_single: 0.5772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,770 - Iter: 49, Total Loss: 0.5732, loss_single: 0.5732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,805 - Iter: 50, Total Loss: 0.5693, loss_single: 0.5693, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,841 - Iter: 51, Total Loss: 0.5667, loss_single: 0.5667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,877 - Iter: 52, Total Loss: 0.5648, loss_single: 0.5648, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,912 - Iter: 53, Total Loss: 0.5624, loss_single: 0.5624, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,947 - Iter: 54, Total Loss: 0.5598, loss_single: 0.5598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:50,983 - Iter: 55, Total Loss: 0.5575, loss_single: 0.5575, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:51,018 - Iter: 56, Total Loss: 0.5559, loss_single: 0.5559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:51,054 - Iter: 57, Total Loss: 0.5542, loss_single: 0.5542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:51,089 - Iter: 58, Total Loss: 0.5528, loss_single: 0.5528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:58:51,124 - 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Saving summary figures for iter 100 +2026-06-24 05:58:56,376 - ### Finished 100 iterations, averaged iter_t = 0.039087 with std = 0.040 ### +2026-06-24 05:58:56,376 - +2026-06-24 05:58:56,377 - ### The PtyRADSolver is finished in 9.330 sec ### +2026-06-24 05:58:56,377 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..57a5bee4f4acda7cbc63c4b63c08eb0920c19486 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/simulation_data3__sample_000016.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/simulation_data3__sample_000016.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d79094e7b374e9419fa17e9ed4aa4399047f41b6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016/c30_small__simulation_data3__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_39.3_phi12_168_C21_641_phi21_84_C23_-748_phi23_83.1_C30_4.19e+06_C32_353_.7e+06_phi56_235/simulation_data3__sample_000016.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 13.29338550567627 + probe_aberrations: + C10: -162.87384033203125 + C12: 39.28644943237305 + C21: 641.013671875 + C23: -747.9152221679688 + C30: 4187895.75 + C32: 352.73199462890625 + C34: 3252.5146484375 + C41: 99947.59375 + C43: 285025.78125 + C45: 243358.546875 + C50: -317487264.0 + C52: 15214170.0 + C54: -16656594.0 + C56: -5696292.5 + phi12: 167.58461989046242 + phi21: 83.9521363718095 + phi23: 83.11511034940278 + phi32: 337.9596999059552 + phi34: 186.8277079901112 + phi41: 355.9363753108352 + phi43: 83.37609187758898 + phi45: 348.2525490983543 + phi52: 279.94970117174296 + phi54: 68.31952724856448 + phi56: 234.978287676275 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5252974629402161 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000016_measurement.h5 + key: measurement + random_seed: 20261944 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000016 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000016 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/20260624_055931_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/20260624_055931_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..10efda364a03f009a0aa6e71985ee1868996224b --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/20260624_055931_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:59:30,328 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:59:30,328 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:59:30,328 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:59:30,328 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:59:30,328 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:59:30,328 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:59:30,328 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:59:30,328 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:59:30,328 - +2026-06-24 05:59:30,434 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:59:30,434 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:59:30,434 - Accelerator.num_process = 1 +2026-06-24 05:59:30,435 - Accelerator.mixed_precision = no +2026-06-24 05:59:30,445 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:59:30,445 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:59:30,445 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:59:30,445 - +2026-06-24 05:59:30,445 - ### System information ### +2026-06-24 05:59:30,445 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:59:30,445 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:59:30,445 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:59:30,446 - Machine: x86_64 +2026-06-24 05:59:30,446 - Processor: x86_64 +2026-06-24 05:59:30,446 - Available CPU cores: 8 +2026-06-24 05:59:30,446 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:59:30,446 - +2026-06-24 05:59:30,446 - ### GPU information ### +2026-06-24 05:59:30,446 - CUDA Available: True +2026-06-24 05:59:30,446 - CUDA Version: 13.0 +2026-06-24 05:59:30,446 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:59:30,446 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:59:30,446 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:59:30,446 - In addition, Triton does not directly support Windows. +2026-06-24 05:59:30,446 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:59:30,462 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:59:30,462 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:59:30,462 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:59:30,462 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:59:30,462 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:59:30,462 - +2026-06-24 05:59:30,462 - ### Python information ### +2026-06-24 05:59:30,464 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:59:30,464 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:59:30,464 - +2026-06-24 05:59:30,464 - ### Packages information ### +2026-06-24 05:59:30,464 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:59:30,465 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:59:30,466 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:59:30,466 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:59:30,467 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:59:30,467 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:59:30,467 - +2026-06-24 05:59:30,467 - ### Loading params file ### +2026-06-24 05:59:30,467 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000019.yaml +2026-06-24 05:59:30,474 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:59:30,475 - Success! Params file validated and defaults applied. +2026-06-24 05:59:30,475 - +2026-06-24 05:59:30,475 - ### Setting GPU Device ### +2026-06-24 05:59:30,475 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:59:30,475 - +2026-06-24 05:59:30,475 - Random seed: 20261947 provided by params file +2026-06-24 05:59:30,475 - ### Initializing Initializer ### +2026-06-24 05:59:30,475 - init_params are displayed below: +2026-06-24 05:59:30,475 - random_seed: 20261947 +2026-06-24 05:59:30,475 - probe_illum_type: electron +2026-06-24 05:59:30,475 - probe_kv: 300.0 +2026-06-24 05:59:30,476 - probe_conv_angle: 14.86167049407959 +2026-06-24 05:59:30,476 - probe_aberrations: {'C10': -350.041, 'C12': -3.26, 'phi12': 254.351, 'C21': 710.487, 'phi21': 60.366, 'C23': 210.02, 'phi23': 66.329, 'C30': 4093271.75, 'C32': 10107.136, 'phi32': 268.906, 'C34': -10451.633, 'phi34': 326.607, 'C41': 485571.469, 'phi41': 244.407, 'C43': -51909.57, 'phi43': 252.265, 'C45': 348397.0, 'phi45': 145.942, 'C50': 166396400.0, 'C52': 10922700.0, 'phi52': 265.639, 'C54': 11885179.0, 'phi54': 277.121, 'C56': 8711447.0, 'phi56': 185.074} +2026-06-24 05:59:30,476 - beam_kev: None +2026-06-24 05:59:30,476 - probe_dRn: None +2026-06-24 05:59:30,476 - probe_Rn: None +2026-06-24 05:59:30,476 - probe_D_H: None +2026-06-24 05:59:30,476 - probe_D_FZP: None +2026-06-24 05:59:30,476 - probe_Ls: None +2026-06-24 05:59:30,476 - meas_Npix: 128 +2026-06-24 05:59:30,476 - pos_N_scans: 256 +2026-06-24 05:59:30,476 - pos_N_scan_slow: 16 +2026-06-24 05:59:30,476 - pos_N_scan_fast: 16 +2026-06-24 05:59:30,476 - pos_scan_step_size: 0.3740711212158203 +2026-06-24 05:59:30,476 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:59:30,476 - probe_pmode_max: 6 +2026-06-24 05:59:30,476 - probe_pmode_init_pows: [0.02] +2026-06-24 05:59:30,476 - obj_omode_max: 1 +2026-06-24 05:59:30,476 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:59:30,476 - obj_Nlayer: 1 +2026-06-24 05:59:30,476 - obj_slice_thickness: 20.0 +2026-06-24 05:59:30,476 - simu_Npix: None +2026-06-24 05:59:30,476 - simu_match_mode: None +2026-06-24 05:59:30,476 - meas_permute: None +2026-06-24 05:59:30,476 - meas_reshape: [256, 128, 128] +2026-06-24 05:59:30,476 - meas_flipT: [0, 0, 0] +2026-06-24 05:59:30,476 - meas_crop: None +2026-06-24 05:59:30,476 - meas_pad: None +2026-06-24 05:59:30,476 - meas_resample: None +2026-06-24 05:59:30,476 - meas_add_source_size: None +2026-06-24 05:59:30,476 - meas_add_detector_blur: None +2026-06-24 05:59:30,476 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:59:30,476 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:59:30,476 - meas_add_poisson_noise: None +2026-06-24 05:59:30,476 - meas_export: None +2026-06-24 05:59:30,476 - probe_permute: None +2026-06-24 05:59:30,476 - probe_z_shift: None +2026-06-24 05:59:30,476 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:59:30,476 - pos_scan_flipT: None +2026-06-24 05:59:30,476 - pos_scan_affine: None +2026-06-24 05:59:30,477 - pos_scan_rand_std: 0.15 +2026-06-24 05:59:30,477 - obj_z_crop: None +2026-06-24 05:59:30,477 - obj_z_pad: None +2026-06-24 05:59:30,477 - obj_z_resample: None +2026-06-24 05:59:30,477 - meas_source: file +2026-06-24 05:59:30,477 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000019_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:59:30,477 - probe_source: simu +2026-06-24 05:59:30,477 - probe_params: None +2026-06-24 05:59:30,477 - pos_source: simu +2026-06-24 05:59:30,477 - pos_params: None +2026-06-24 05:59:30,477 - obj_source: simu +2026-06-24 05:59:30,477 - obj_params: None +2026-06-24 05:59:30,477 - tilt_source: simu +2026-06-24 05:59:30,477 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:59:30,477 - +2026-06-24 05:59:30,477 - ### Initializing cache ### +2026-06-24 05:59:30,477 - use_cached_obj = False +2026-06-24 05:59:30,477 - use_cached_probe = False +2026-06-24 05:59:30,477 - use_cached_pos = False +2026-06-24 05:59:30,477 - +2026-06-24 05:59:30,477 - ### Initializing measurements ### +2026-06-24 05:59:30,477 - Loading measurements from source = 'file' +2026-06-24 05:59:30,477 - Detected measurement file type = '.h5' +2026-06-24 05:59:30,556 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:59:30,556 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:59:30,558 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0015) +2026-06-24 05:59:30,558 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:59:30,558 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:59:30,560 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:30,560 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:59:30,560 - Normalizing by max of the 2D mean pattern intensity: 0.00084800128 +2026-06-24 05:59:30,561 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:59:30,562 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0718, 1.7316) +2026-06-24 05:59:30,563 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:30,564 - Pattern total int. statistics (min, mean, max) = (1166.8337, 1176.0952, 1189.5402), with min/max = 98.1% +2026-06-24 05:59:30,565 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0718, 1.7316) +2026-06-24 05:59:30,565 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:59:30,565 - +2026-06-24 05:59:30,565 - ### Setting up calibration ### +2026-06-24 05:59:30,565 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:59:30,565 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:59:30,565 - Radius of fitted bright field disk (RBF) = 19.16 px with meas_Npix = 128 +2026-06-24 05:59:30,565 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2993 +2026-06-24 05:59:30,565 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:59:30,565 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:59:30,795 - Initial guess: center=(63.61, 63.62), radius=19.16, Gaussian blur std=0.50 +2026-06-24 05:59:30,812 - Final fit: center=(63.61, 63.62), radius=19.16, Gaussian blur std=0.82 +2026-06-24 05:59:30,812 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 19.32 px with Npix = 128 +2026-06-24 05:59:30,812 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:59:30,812 - +2026-06-24 05:59:30,812 - ### Setting init_variables dict ### +2026-06-24 05:59:30,812 - Derived values given input init_params: +2026-06-24 05:59:30,812 - kv = 300.0 kV +2026-06-24 05:59:30,812 - wavelength = 0.0197 Ang +2026-06-24 05:59:30,812 - conv_angle = 14.86167049407959 mrad +2026-06-24 05:59:30,812 - Npix = 128 px +2026-06-24 05:59:30,812 - dk = 0.0391 Ang^-1 +2026-06-24 05:59:30,812 - kMax = 2.5000 Ang^-1 +2026-06-24 05:59:30,812 - da = 0.7690 mrad +2026-06-24 05:59:30,812 - angleMax = 49.2187 mrad +2026-06-24 05:59:30,812 - RBF = 19.3249 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:59:30,812 - n_alpha = 3.3118 (# conv_angle) +2026-06-24 05:59:30,813 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:59:30,813 - Rayleigh-limited resolution = 0.8081 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:59:30,813 - Real space probe extent = 25.6000 Ang +2026-06-24 05:59:30,813 - +2026-06-24 05:59:30,813 - ### Initializing probe ### +2026-06-24 05:59:30,813 - Loading probe from source = 'simu' +2026-06-24 05:59:30,813 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:59:30,813 - Start simulating STEM probe +2026-06-24 05:59:30,813 - kv = 300.0 kV +2026-06-24 05:59:30,813 - wavelength = 0.0197 Ang +2026-06-24 05:59:30,813 - conv_angle = 14.86167049407959 mrad +2026-06-24 05:59:30,813 - Npix = 128 px +2026-06-24 05:59:30,813 - dk = 0.0391 Ang^-1 +2026-06-24 05:59:30,813 - kMax = 2.5000 Ang^-1 +2026-06-24 05:59:30,813 - alpha_max = 49.2187 mrad +2026-06-24 05:59:30,813 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:59:30,813 - Rayleigh-limited resolution = 0.8081 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:59:30,813 - Real space probe extent = 25.6000 Ang +2026-06-24 05:59:30,813 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:59:30,813 - ------------------------------------------------------------------------------------ +2026-06-24 05:59:30,813 - C1,0 C1 -350.0410 - Defocus (C10 = -df) +2026-06-24 05:59:30,813 - C1,2 A1 -3.2600 254.35 2-fold astigmatism +2026-06-24 05:59:30,813 - C2,1 3*B2 710.4870 60.37 Axial coma +2026-06-24 05:59:30,813 - C2,3 A2 210.0200 66.33 3-fold astigmatism +2026-06-24 05:59:30,814 - C3,0 C3 4093271.7500 - Spherical aberration +2026-06-24 05:59:30,814 - C3,2 4*S3 10107.1360 268.91 Axial star aberration +2026-06-24 05:59:30,814 - C3,4 A3 -10451.6330 326.61 4-fold astigmatism +2026-06-24 05:59:30,814 - C4,1 4*B4 485571.4690 244.41 Axial coma(4th) +2026-06-24 05:59:30,814 - C4,3 4*D4 -51909.5700 252.26 3-lobe aberration +2026-06-24 05:59:30,814 - C4,5 A4 348397.0000 145.94 5-fold astigmatism +2026-06-24 05:59:30,814 - C5,0 C5 166396400.0000 - Spherical aberration (5th) +2026-06-24 05:59:30,814 - C5,2 6*S5 10922700.0000 265.64 Axial star aberration(5th) +2026-06-24 05:59:30,814 - C5,4 6*R5 11885179.0000 277.12 4-lobe aberration +2026-06-24 05:59:30,814 - C5,6 A5 8711447.0000 185.07 6-fold astigmatism +2026-06-24 05:59:30,817 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:59:30,817 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:59:30,817 - Creating 5 new probe modes from the major mode +2026-06-24 05:59:30,817 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:59:30,923 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:59:30,924 - Orthogonalizing 6 pmodes +2026-06-24 05:59:30,927 - Sorting 6 pmodes by their intensities +2026-06-24 05:59:30,927 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:59:30,928 - sum(|probe_data|**2) = 1176.10, while meas_total_ints (min, mean, max) = (1166.8337, 1176.0952, 1189.5402) +2026-06-24 05:59:30,928 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:59:30,928 - +2026-06-24 05:59:30,928 - ### Initializing probe positions ### +2026-06-24 05:59:30,928 - Loading probe positions from source = 'simu' +2026-06-24 05:59:30,928 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:59:30,928 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3741, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:59:30,929 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:59:30,931 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:59:30,931 - crop_pos 1st and last px coords (y,x) = ([16, 16], [44, 44]) +2026-06-24 05:59:30,931 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 05:59:30,931 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:59:30,931 - +2026-06-24 05:59:30,931 - ### Initializing object ### +2026-06-24 05:59:30,931 - Loading object from source = 'simu' +2026-06-24 05:59:30,931 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:59:30,932 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:59:30,933 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 05:59:30,933 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 05:59:30,933 - +2026-06-24 05:59:30,933 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:59:30,933 - omode_occu (omode) = float32, (1,) +2026-06-24 05:59:30,933 - +2026-06-24 05:59:30,933 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:59:30,933 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 05:59:30,934 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:59:30,934 - +2026-06-24 05:59:30,934 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:59:30,934 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:59:30,934 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:59:30,934 - +2026-06-24 05:59:30,934 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:59:30,934 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:59:30,934 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:59:30,934 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:59:30,934 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:59:30,934 - crop positions (yx_min=[16 16], yx_max=[172 172]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 05:59:30,934 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:59:30,934 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:59:30,934 - +2026-06-24 05:59:30,934 - ### Collecting reconstruction provenance ### +2026-06-24 05:59:30,934 - Reconstruction provenance is collected and initialized. +2026-06-24 05:59:30,934 - +2026-06-24 05:59:30,934 - ### Initializing loss function ### +2026-06-24 05:59:30,934 - Active loss types: +2026-06-24 05:59:30,934 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:59:30,935 - +2026-06-24 05:59:30,935 - ### Initializing constraint function ### +2026-06-24 05:59:30,935 - Active constraint types: +2026-06-24 05:59:30,935 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:59:30,935 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:59:30,935 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:59:30,935 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:59:30,935 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:59:30,935 - +2026-06-24 05:59:30,935 - ### Done initializing PtyRADSolver ### +2026-06-24 05:59:30,935 - +2026-06-24 05:59:31,058 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:59:31,058 - +2026-06-24 05:59:31,058 - ### Initializing PtychoModel model ### +2026-06-24 05:59:31,130 - ### PtychoModel optimizable variables ### +2026-06-24 05:59:31,130 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:31,130 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:31,130 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:59:31,130 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:59:31,130 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:59:31,130 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:31,130 - +2026-06-24 05:59:31,130 - ### Optimizable variables statitsics ### +2026-06-24 05:59:31,130 - Total measurement values : 4,194,304 +2026-06-24 05:59:31,130 - Total optimizing variables: 267,808 +2026-06-24 05:59:31,130 - Overdetermined ratio : 15.66 +2026-06-24 05:59:31,130 - +2026-06-24 05:59:31,130 - ### Model behavior ### +2026-06-24 05:59:31,130 - Tilt propagator : False +2026-06-24 05:59:31,130 - Change slice thickness : False +2026-06-24 05:59:31,130 - Detector blur : False +2026-06-24 05:59:31,131 - Preload data : True +2026-06-24 05:59:31,131 - On-the-fly meas padding : False +2026-06-24 05:59:31,131 - On-the-fly meas resample : False +2026-06-24 05:59:31,131 - On-the-fly simu match mode: None +2026-06-24 05:59:31,131 - +2026-06-24 05:59:31,172 - ### Done initializing PtychoModel model ### +2026-06-24 05:59:31,172 - +2026-06-24 05:59:31,172 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:59:31,172 - +2026-06-24 05:59:31,172 - ### Generating indices, batches, and output_path ### +2026-06-24 05:59:31,173 - d90 = 61.000 px or 12.200 Ang +2026-06-24 05:59:31,173 - Selecting indices with the 'full' mode +2026-06-24 05:59:31,630 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:59:31,701 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:59:31,701 - Original recon_dir_affixes = ['default'] +2026-06-24 05:59:31,701 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:59:31,707 - Path corrected for compatibility: +2026-06-24 05:59:31,708 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.01e+04_phi32_269_C34_-1.05e+04_phi34_327_C41_4.86e+05_phi41_244_C43_-5.19e+04_phi43_252_C45_3.48e+05_phi45_146_C50_1.66e+08_C52_1.09e+07_phi52_266_C54_1.19e+07_phi54_277_C56_8.71e+06_phi56_185 +2026-06-24 05:59:31,708 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185 +2026-06-24 05:59:31,709 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185' is generated! +2026-06-24 05:59:31,853 - +2026-06-24 05:59:31,854 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/20260624_055931_ptyrad_log.txt ### +2026-06-24 05:59:31,854 - +2026-06-24 05:59:31,856 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:59:31,856 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:59:31,856 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:59:33,039 - Iter: 1, Total Loss: 0.6896, loss_single: 0.6896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:59:33,076 - Iter: 2, Total Loss: 0.6728, loss_single: 0.6728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:33,112 - Iter: 3, Total Loss: 0.6576, loss_single: 0.6576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,147 - Iter: 4, Total Loss: 0.6461, loss_single: 0.6461, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,183 - Iter: 5, Total Loss: 0.6356, loss_single: 0.6356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:33,218 - Iter: 6, Total Loss: 0.6224, loss_single: 0.6224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,254 - Iter: 7, Total Loss: 0.6101, loss_single: 0.6101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,289 - Iter: 8, Total Loss: 0.5987, loss_single: 0.5987, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,325 - Iter: 9, Total Loss: 0.5869, loss_single: 0.5869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:33,361 - Iter: 10, Total Loss: 0.5757, loss_single: 0.5757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,396 - Iter: 11, Total Loss: 0.5654, loss_single: 0.5654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,431 - Iter: 12, Total Loss: 0.5540, loss_single: 0.5540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,466 - Iter: 13, Total Loss: 0.5424, loss_single: 0.5424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,502 - Iter: 14, Total Loss: 0.5321, loss_single: 0.5321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,538 - Iter: 15, Total Loss: 0.5227, loss_single: 0.5227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:33,574 - Iter: 16, Total Loss: 0.5134, loss_single: 0.5134, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,609 - Iter: 17, Total Loss: 0.5036, loss_single: 0.5036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,644 - Iter: 18, Total Loss: 0.4940, loss_single: 0.4940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,680 - Iter: 19, Total Loss: 0.4825, loss_single: 0.4825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,715 - Iter: 20, Total Loss: 0.4690, loss_single: 0.4690, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:59:33,750 - Iter: 21, Total Loss: 0.4548, loss_single: 0.4548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,786 - Iter: 22, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,821 - Iter: 23, Total Loss: 0.4276, loss_single: 0.4276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,856 - Iter: 24, Total Loss: 0.4161, loss_single: 0.4161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,892 - Iter: 25, Total Loss: 0.4040, loss_single: 0.4040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,927 - Iter: 26, Total Loss: 0.3945, loss_single: 0.3945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,962 - Iter: 27, Total Loss: 0.3861, loss_single: 0.3861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:33,997 - Iter: 28, Total Loss: 0.3773, loss_single: 0.3773, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,032 - Iter: 29, Total Loss: 0.3686, loss_single: 0.3686, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,068 - Iter: 30, Total Loss: 0.3592, loss_single: 0.3592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,103 - Iter: 31, Total Loss: 0.3490, loss_single: 0.3490, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,139 - Iter: 32, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,174 - Iter: 33, Total Loss: 0.3330, loss_single: 0.3330, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,209 - Iter: 34, Total Loss: 0.3263, loss_single: 0.3263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,244 - Iter: 35, Total Loss: 0.3198, loss_single: 0.3198, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,279 - Iter: 36, Total Loss: 0.3136, loss_single: 0.3136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,314 - Iter: 37, Total Loss: 0.3077, loss_single: 0.3077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,349 - Iter: 38, Total Loss: 0.3018, loss_single: 0.3018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,385 - Iter: 39, Total Loss: 0.2963, loss_single: 0.2963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,420 - Iter: 40, Total Loss: 0.2915, loss_single: 0.2915, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,480 - Iter: 41, Total Loss: 0.2868, loss_single: 0.2868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,516 - Iter: 42, Total Loss: 0.2828, loss_single: 0.2828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,550 - Iter: 43, Total Loss: 0.2791, loss_single: 0.2791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:59:34,585 - Iter: 44, Total Loss: 0.2757, loss_single: 0.2757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,621 - Iter: 45, Total Loss: 0.2726, loss_single: 0.2726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,657 - Iter: 46, Total Loss: 0.2696, loss_single: 0.2696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:34,692 - Iter: 47, Total Loss: 0.2668, loss_single: 0.2668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:59:34,727 - Iter: 48, Total Loss: 0.2642, loss_single: 0.2642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,762 - Iter: 49, Total Loss: 0.2619, loss_single: 0.2619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,798 - Iter: 50, Total Loss: 0.2598, loss_single: 0.2598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,833 - Iter: 51, Total Loss: 0.2580, loss_single: 0.2580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,868 - Iter: 52, Total Loss: 0.2564, loss_single: 0.2564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:34,903 - 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Saving summary figures for iter 100 +2026-06-24 05:59:40,380 - ### Finished 100 iterations, averaged iter_t = 0.038921 with std = 0.040 ### +2026-06-24 05:59:40,380 - +2026-06-24 05:59:40,380 - ### The PtyRADSolver is finished in 9.322 sec ### +2026-06-24 05:59:40,380 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..76ecf98ec27500797888ce87354c8209b6878073 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/simulation_data3__sample_000019.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/simulation_data3__sample_000019.yaml new file mode 100644 index 0000000000000000000000000000000000000000..21a8b249441332672f2521ab8aa01ddddf570b75 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019/c30_small__simulation_data3__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-350_C12_-3.26_phi12_254_C21_710_phi21_60.4_C23_210_phi23_66.3_C30_4.09e+06_C32_1.71e+06_phi56_185/simulation_data3__sample_000019.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 14.86167049407959 + probe_aberrations: + C10: -350.0412902832031 + C12: -3.260378122329712 + C21: 710.4866333007812 + C23: 210.02047729492188 + C30: 4093271.75 + C32: 10107.1357421875 + C34: -10451.6328125 + C41: 485571.46875 + C43: -51909.5703125 + C45: 348397.0 + C50: 166396400.0 + C52: 10922700.0 + C54: 11885179.0 + C56: 8711447.0 + phi12: 254.35143623809915 + phi21: 60.36639350729911 + phi23: 66.32903936969352 + phi32: 268.905913661236 + phi34: 326.60735176950374 + phi41: 244.4066808065606 + phi43: 252.26484076741693 + phi45: 145.94249614673836 + phi52: 265.63941667181246 + phi54: 277.1208553835771 + phi56: 185.07407058108876 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3740711212158203 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000019_measurement.h5 + key: measurement + random_seed: 20261947 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000019 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000019 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/20260624_055946_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/20260624_055946_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f5b81ee12269d760efc12a3002d1aadef34f9861 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/20260624_055946_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:59:44,938 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:59:44,938 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:59:44,938 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:59:44,938 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:59:44,938 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:59:44,939 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:59:44,939 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:59:44,939 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:59:44,939 - +2026-06-24 05:59:45,050 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:59:45,050 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:59:45,050 - Accelerator.num_process = 1 +2026-06-24 05:59:45,050 - Accelerator.mixed_precision = no +2026-06-24 05:59:45,061 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:59:45,061 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:59:45,061 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:59:45,062 - +2026-06-24 05:59:45,062 - ### System information ### +2026-06-24 05:59:45,062 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:59:45,062 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:59:45,062 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:59:45,062 - Machine: x86_64 +2026-06-24 05:59:45,062 - Processor: x86_64 +2026-06-24 05:59:45,062 - Available CPU cores: 8 +2026-06-24 05:59:45,062 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:59:45,062 - +2026-06-24 05:59:45,062 - ### GPU information ### +2026-06-24 05:59:45,062 - CUDA Available: True +2026-06-24 05:59:45,062 - CUDA Version: 13.0 +2026-06-24 05:59:45,062 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:59:45,063 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:59:45,063 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:59:45,063 - In addition, Triton does not directly support Windows. +2026-06-24 05:59:45,063 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:59:45,090 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:59:45,090 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:59:45,090 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:59:45,090 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:59:45,090 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:59:45,090 - +2026-06-24 05:59:45,090 - ### Python information ### +2026-06-24 05:59:45,092 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:59:45,092 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:59:45,092 - +2026-06-24 05:59:45,092 - ### Packages information ### +2026-06-24 05:59:45,093 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:59:45,093 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:59:45,094 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:59:45,094 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:59:45,095 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:59:45,095 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:59:45,095 - +2026-06-24 05:59:45,095 - ### Loading params file ### +2026-06-24 05:59:45,095 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000020.yaml +2026-06-24 05:59:45,102 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:59:45,103 - Success! Params file validated and defaults applied. +2026-06-24 05:59:45,103 - +2026-06-24 05:59:45,103 - ### Setting GPU Device ### +2026-06-24 05:59:45,103 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:59:45,103 - +2026-06-24 05:59:45,103 - Random seed: 20261948 provided by params file +2026-06-24 05:59:45,104 - ### Initializing Initializer ### +2026-06-24 05:59:45,104 - init_params are displayed below: +2026-06-24 05:59:45,104 - random_seed: 20261948 +2026-06-24 05:59:45,104 - probe_illum_type: electron +2026-06-24 05:59:45,104 - probe_kv: 80.0 +2026-06-24 05:59:45,104 - probe_conv_angle: 11.231908798217773 +2026-06-24 05:59:45,104 - probe_aberrations: {'C10': -498.661, 'C12': -34.239, 'phi12': 62.094, 'C21': -431.984, 'phi21': 63.463, 'C23': -39.249, 'phi23': 128.446, 'C30': 1318682.5, 'C32': 10612.789, 'phi32': 259.889, 'C34': 2188.166, 'phi34': 86.053, 'C41': -240729.609, 'phi41': 258.75, 'C43': -453905.969, 'phi43': 281.068, 'C45': 96865.562, 'phi45': 347.445, 'C50': -247494288.0, 'C52': 8998041.0, 'phi52': 283.131, 'C54': 743044.875, 'phi54': 228.221, 'C56': 6377071.0, 'phi56': 337.231} +2026-06-24 05:59:45,104 - beam_kev: None +2026-06-24 05:59:45,104 - probe_dRn: None +2026-06-24 05:59:45,104 - probe_Rn: None +2026-06-24 05:59:45,104 - probe_D_H: None +2026-06-24 05:59:45,104 - probe_D_FZP: None +2026-06-24 05:59:45,104 - probe_Ls: None +2026-06-24 05:59:45,104 - meas_Npix: 128 +2026-06-24 05:59:45,104 - pos_N_scans: 256 +2026-06-24 05:59:45,104 - pos_N_scan_slow: 16 +2026-06-24 05:59:45,104 - pos_N_scan_fast: 16 +2026-06-24 05:59:45,104 - pos_scan_step_size: 0.39237770438194275 +2026-06-24 05:59:45,104 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:59:45,104 - probe_pmode_max: 6 +2026-06-24 05:59:45,104 - probe_pmode_init_pows: [0.02] +2026-06-24 05:59:45,104 - obj_omode_max: 1 +2026-06-24 05:59:45,104 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:59:45,104 - obj_Nlayer: 1 +2026-06-24 05:59:45,104 - obj_slice_thickness: 20.0 +2026-06-24 05:59:45,104 - simu_Npix: None +2026-06-24 05:59:45,104 - simu_match_mode: None +2026-06-24 05:59:45,104 - meas_permute: None +2026-06-24 05:59:45,104 - meas_reshape: [256, 128, 128] +2026-06-24 05:59:45,104 - meas_flipT: [0, 0, 0] +2026-06-24 05:59:45,104 - meas_crop: None +2026-06-24 05:59:45,104 - meas_pad: None +2026-06-24 05:59:45,105 - meas_resample: None +2026-06-24 05:59:45,105 - meas_add_source_size: None +2026-06-24 05:59:45,105 - meas_add_detector_blur: None +2026-06-24 05:59:45,105 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:59:45,105 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:59:45,105 - meas_add_poisson_noise: None +2026-06-24 05:59:45,105 - meas_export: None +2026-06-24 05:59:45,105 - probe_permute: None +2026-06-24 05:59:45,105 - probe_z_shift: None +2026-06-24 05:59:45,105 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:59:45,105 - pos_scan_flipT: None +2026-06-24 05:59:45,105 - pos_scan_affine: None +2026-06-24 05:59:45,105 - pos_scan_rand_std: 0.15 +2026-06-24 05:59:45,105 - obj_z_crop: None +2026-06-24 05:59:45,105 - obj_z_pad: None +2026-06-24 05:59:45,105 - obj_z_resample: None +2026-06-24 05:59:45,105 - meas_source: file +2026-06-24 05:59:45,105 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000020_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:59:45,105 - probe_source: simu +2026-06-24 05:59:45,105 - probe_params: None +2026-06-24 05:59:45,105 - pos_source: simu +2026-06-24 05:59:45,105 - pos_params: None +2026-06-24 05:59:45,105 - obj_source: simu +2026-06-24 05:59:45,105 - obj_params: None +2026-06-24 05:59:45,105 - tilt_source: simu +2026-06-24 05:59:45,105 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:59:45,105 - +2026-06-24 05:59:45,105 - ### Initializing cache ### +2026-06-24 05:59:45,105 - use_cached_obj = False +2026-06-24 05:59:45,105 - use_cached_probe = False +2026-06-24 05:59:45,105 - use_cached_pos = False +2026-06-24 05:59:45,105 - +2026-06-24 05:59:45,105 - ### Initializing measurements ### +2026-06-24 05:59:45,105 - Loading measurements from source = 'file' +2026-06-24 05:59:45,105 - Detected measurement file type = '.h5' +2026-06-24 05:59:45,181 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:59:45,181 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:59:45,183 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0083) +2026-06-24 05:59:45,183 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:59:45,183 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:59:45,184 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:45,184 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:59:45,185 - Normalizing by max of the 2D mean pattern intensity: 0.0068246876 +2026-06-24 05:59:45,186 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:59:45,187 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0090, 1.2202) +2026-06-24 05:59:45,187 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:45,189 - Pattern total int. statistics (min, mean, max) = (144.6814, 146.9051, 148.5657), with min/max = 97.4% +2026-06-24 05:59:45,190 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0090, 1.2202) +2026-06-24 05:59:45,190 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:59:45,190 - +2026-06-24 05:59:45,190 - ### Setting up calibration ### +2026-06-24 05:59:45,190 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:59:45,190 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:59:45,190 - Radius of fitted bright field disk (RBF) = 6.82 px with meas_Npix = 128 +2026-06-24 05:59:45,190 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1065 +2026-06-24 05:59:45,190 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:59:45,190 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:59:45,418 - Initial guess: center=(63.62, 63.62), radius=6.82, Gaussian blur std=0.50 +2026-06-24 05:59:45,426 - Final fit: center=(63.62, 63.62), radius=6.82, Gaussian blur std=0.55 +2026-06-24 05:59:45,427 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.89 px with Npix = 128 +2026-06-24 05:59:45,427 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:59:45,427 - +2026-06-24 05:59:45,427 - ### Setting init_variables dict ### +2026-06-24 05:59:45,427 - Derived values given input init_params: +2026-06-24 05:59:45,427 - kv = 80.0 kV +2026-06-24 05:59:45,427 - wavelength = 0.0418 Ang +2026-06-24 05:59:45,427 - conv_angle = 11.231908798217773 mrad +2026-06-24 05:59:45,427 - Npix = 128 px +2026-06-24 05:59:45,427 - dk = 0.0391 Ang^-1 +2026-06-24 05:59:45,427 - kMax = 2.5000 Ang^-1 +2026-06-24 05:59:45,427 - da = 1.6311 mrad +2026-06-24 05:59:45,427 - angleMax = 104.3929 mrad +2026-06-24 05:59:45,427 - RBF = 6.8859 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:59:45,427 - n_alpha = 9.2943 (# conv_angle) +2026-06-24 05:59:45,427 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:59:45,427 - Rayleigh-limited resolution = 2.2678 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:59:45,427 - Real space probe extent = 25.6000 Ang +2026-06-24 05:59:45,427 - +2026-06-24 05:59:45,427 - ### Initializing probe ### +2026-06-24 05:59:45,427 - Loading probe from source = 'simu' +2026-06-24 05:59:45,427 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:59:45,427 - Start simulating STEM probe +2026-06-24 05:59:45,428 - kv = 80.0 kV +2026-06-24 05:59:45,428 - wavelength = 0.0418 Ang +2026-06-24 05:59:45,428 - conv_angle = 11.231908798217773 mrad +2026-06-24 05:59:45,428 - Npix = 128 px +2026-06-24 05:59:45,428 - dk = 0.0391 Ang^-1 +2026-06-24 05:59:45,428 - kMax = 2.5000 Ang^-1 +2026-06-24 05:59:45,428 - alpha_max = 104.3929 mrad +2026-06-24 05:59:45,428 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:59:45,428 - Rayleigh-limited resolution = 2.2678 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:59:45,428 - Real space probe extent = 25.6000 Ang +2026-06-24 05:59:45,428 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:59:45,428 - ------------------------------------------------------------------------------------- +2026-06-24 05:59:45,428 - C1,0 C1 -498.6610 - Defocus (C10 = -df) +2026-06-24 05:59:45,428 - C1,2 A1 -34.2390 62.09 2-fold astigmatism +2026-06-24 05:59:45,428 - C2,1 3*B2 -431.9840 63.46 Axial coma +2026-06-24 05:59:45,428 - C2,3 A2 -39.2490 128.45 3-fold astigmatism +2026-06-24 05:59:45,428 - C3,0 C3 1318682.5000 - Spherical aberration +2026-06-24 05:59:45,428 - C3,2 4*S3 10612.7890 259.89 Axial star aberration +2026-06-24 05:59:45,428 - C3,4 A3 2188.1660 86.05 4-fold astigmatism +2026-06-24 05:59:45,428 - C4,1 4*B4 -240729.6090 258.75 Axial coma(4th) +2026-06-24 05:59:45,428 - C4,3 4*D4 -453905.9690 281.07 3-lobe aberration +2026-06-24 05:59:45,428 - C4,5 A4 96865.5620 347.44 5-fold astigmatism +2026-06-24 05:59:45,428 - C5,0 C5 -247494288.0000 - Spherical aberration (5th) +2026-06-24 05:59:45,428 - C5,2 6*S5 8998041.0000 283.13 Axial star aberration(5th) +2026-06-24 05:59:45,428 - C5,4 6*R5 743044.8750 228.22 4-lobe aberration +2026-06-24 05:59:45,428 - C5,6 A5 6377071.0000 337.23 6-fold astigmatism +2026-06-24 05:59:45,431 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:59:45,431 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:59:45,431 - Creating 5 new probe modes from the major mode +2026-06-24 05:59:45,432 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:59:45,599 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:59:45,600 - Orthogonalizing 6 pmodes +2026-06-24 05:59:45,603 - Sorting 6 pmodes by their intensities +2026-06-24 05:59:45,604 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:59:45,604 - sum(|probe_data|**2) = 146.91, while meas_total_ints (min, mean, max) = (144.6814, 146.9051, 148.5657) +2026-06-24 05:59:45,604 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:59:45,604 - +2026-06-24 05:59:45,604 - ### Initializing probe positions ### +2026-06-24 05:59:45,604 - Loading probe positions from source = 'simu' +2026-06-24 05:59:45,605 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:59:45,605 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3924, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:59:45,605 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:59:45,607 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:59:45,607 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 45]) +2026-06-24 05:59:45,607 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 05:59:45,607 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:59:45,607 - +2026-06-24 05:59:45,607 - ### Initializing object ### +2026-06-24 05:59:45,607 - Loading object from source = 'simu' +2026-06-24 05:59:45,607 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:59:45,608 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:59:45,609 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 189) +2026-06-24 05:59:45,609 - object extent (Z, Y, X) (Ang) = [20. 38. 37.8] +2026-06-24 05:59:45,609 - +2026-06-24 05:59:45,609 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:59:45,609 - omode_occu (omode) = float32, (1,) +2026-06-24 05:59:45,609 - +2026-06-24 05:59:45,609 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:59:45,609 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 05:59:45,610 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:59:45,610 - +2026-06-24 05:59:45,610 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:59:45,610 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:59:45,610 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:59:45,610 - +2026-06-24 05:59:45,610 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:59:45,610 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:59:45,610 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:59:45,610 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:59:45,610 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:59:45,610 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (190, 189). +2026-06-24 05:59:45,610 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:59:45,610 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:59:45,610 - +2026-06-24 05:59:45,610 - ### Collecting reconstruction provenance ### +2026-06-24 05:59:45,610 - Reconstruction provenance is collected and initialized. +2026-06-24 05:59:45,610 - +2026-06-24 05:59:45,610 - ### Initializing loss function ### +2026-06-24 05:59:45,611 - Active loss types: +2026-06-24 05:59:45,611 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:59:45,611 - +2026-06-24 05:59:45,611 - ### Initializing constraint function ### +2026-06-24 05:59:45,611 - Active constraint types: +2026-06-24 05:59:45,611 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:59:45,611 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:59:45,611 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:59:45,611 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:59:45,611 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:59:45,611 - +2026-06-24 05:59:45,611 - ### Done initializing PtyRADSolver ### +2026-06-24 05:59:45,611 - +2026-06-24 05:59:45,741 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:59:45,741 - +2026-06-24 05:59:45,741 - ### Initializing PtychoModel model ### +2026-06-24 05:59:45,812 - ### PtychoModel optimizable variables ### +2026-06-24 05:59:45,813 - obja : torch.Size([1, 1, 190, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:45,813 - objp : torch.Size([1, 1, 190, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:45,813 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:59:45,813 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:59:45,813 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:59:45,813 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:59:45,813 - +2026-06-24 05:59:45,813 - ### Optimizable variables statitsics ### +2026-06-24 05:59:45,813 - Total measurement values : 4,194,304 +2026-06-24 05:59:45,813 - Total optimizing variables: 268,940 +2026-06-24 05:59:45,813 - Overdetermined ratio : 15.60 +2026-06-24 05:59:45,813 - +2026-06-24 05:59:45,813 - ### Model behavior ### +2026-06-24 05:59:45,813 - Tilt propagator : False +2026-06-24 05:59:45,813 - Change slice thickness : False +2026-06-24 05:59:45,813 - Detector blur : False +2026-06-24 05:59:45,813 - Preload data : True +2026-06-24 05:59:45,813 - On-the-fly meas padding : False +2026-06-24 05:59:45,813 - On-the-fly meas resample : False +2026-06-24 05:59:45,813 - On-the-fly simu match mode: None +2026-06-24 05:59:45,813 - +2026-06-24 05:59:45,855 - ### Done initializing PtychoModel model ### +2026-06-24 05:59:45,855 - +2026-06-24 05:59:45,855 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:59:45,855 - +2026-06-24 05:59:45,855 - ### Generating indices, batches, and output_path ### +2026-06-24 05:59:45,857 - d90 = 59.000 px or 11.800 Ang +2026-06-24 05:59:45,857 - Selecting indices with the 'full' mode +2026-06-24 05:59:46,318 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:59:46,393 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:59:46,393 - Original recon_dir_affixes = ['default'] +2026-06-24 05:59:46,393 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:59:46,399 - Path corrected for compatibility: +2026-06-24 05:59:46,399 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C32_1.06e+04_phi32_260_C34_2.19e+03_phi34_86.1_C41_-2.41e+05_phi41_259_C43_-4.54e+05_phi43_281_C45_9.69e+04_phi45_347_C50_-2.47e+08_C52_9e+06_phi52_283_C54_7.43e+05_phi54_228_C56_6.38e+06_phi56_337 +2026-06-24 05:59:46,399 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337 +2026-06-24 05:59:46,400 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337' is generated! +2026-06-24 05:59:46,550 - +2026-06-24 05:59:46,551 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/20260624_055946_ptyrad_log.txt ### +2026-06-24 05:59:46,551 - +2026-06-24 05:59:46,553 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:59:46,553 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:59:46,553 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:59:47,742 - Iter: 1, Total Loss: 1.4054, loss_single: 1.4054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.439 sec +2026-06-24 05:59:47,780 - Iter: 2, Total Loss: 1.3057, loss_single: 1.3057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:59:47,816 - Iter: 3, Total Loss: 1.2373, loss_single: 1.2373, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:47,852 - Iter: 4, Total Loss: 1.1729, loss_single: 1.1729, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:47,888 - Iter: 5, Total Loss: 1.1111, loss_single: 1.1111, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:47,924 - Iter: 6, Total Loss: 1.0622, loss_single: 1.0622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:47,959 - Iter: 7, Total Loss: 1.0210, loss_single: 1.0210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:47,994 - Iter: 8, Total Loss: 0.9775, loss_single: 0.9775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,030 - Iter: 9, Total Loss: 0.9358, loss_single: 0.9358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,067 - Iter: 10, Total Loss: 0.9065, loss_single: 0.9065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:48,102 - Iter: 11, Total Loss: 0.8795, loss_single: 0.8795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,137 - Iter: 12, Total Loss: 0.8475, loss_single: 0.8475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,173 - Iter: 13, Total Loss: 0.8191, loss_single: 0.8191, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,209 - Iter: 14, Total Loss: 0.7923, loss_single: 0.7923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,244 - Iter: 15, Total Loss: 0.7619, loss_single: 0.7619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,280 - Iter: 16, Total Loss: 0.7391, loss_single: 0.7391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,316 - Iter: 17, Total Loss: 0.7208, loss_single: 0.7208, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:48,351 - Iter: 18, Total Loss: 0.7002, loss_single: 0.7002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,387 - Iter: 19, Total Loss: 0.6789, loss_single: 0.6789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:48,423 - Iter: 20, Total Loss: 0.6617, loss_single: 0.6617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,458 - Iter: 21, Total Loss: 0.6506, loss_single: 0.6506, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,494 - Iter: 22, Total Loss: 0.6415, loss_single: 0.6415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,529 - Iter: 23, Total Loss: 0.6325, loss_single: 0.6325, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,565 - Iter: 24, Total Loss: 0.6245, loss_single: 0.6245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,600 - Iter: 25, Total Loss: 0.6181, loss_single: 0.6181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,635 - Iter: 26, Total Loss: 0.6137, loss_single: 0.6137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,671 - Iter: 27, Total Loss: 0.6114, loss_single: 0.6114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,706 - Iter: 28, Total Loss: 0.6105, loss_single: 0.6105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,742 - Iter: 29, Total Loss: 0.6099, loss_single: 0.6099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,778 - Iter: 30, Total Loss: 0.6094, loss_single: 0.6094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,813 - Iter: 31, Total Loss: 0.6088, loss_single: 0.6088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,849 - Iter: 32, Total Loss: 0.6084, loss_single: 0.6084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,885 - Iter: 33, Total Loss: 0.6081, loss_single: 0.6081, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:48,920 - Iter: 34, Total Loss: 0.6079, loss_single: 0.6079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:48,956 - Iter: 35, Total Loss: 0.6076, loss_single: 0.6076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:48,991 - Iter: 36, Total Loss: 0.6074, loss_single: 0.6074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,027 - Iter: 37, Total Loss: 0.6072, loss_single: 0.6072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,062 - Iter: 38, Total Loss: 0.6070, loss_single: 0.6070, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,098 - Iter: 39, Total Loss: 0.6068, loss_single: 0.6068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,133 - Iter: 40, Total Loss: 0.6066, loss_single: 0.6066, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,171 - Iter: 41, Total Loss: 0.6065, loss_single: 0.6065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,207 - Iter: 42, Total Loss: 0.6063, loss_single: 0.6063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,242 - Iter: 43, Total Loss: 0.6063, loss_single: 0.6063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,278 - Iter: 44, Total Loss: 0.6062, loss_single: 0.6062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,314 - Iter: 45, Total Loss: 0.6060, loss_single: 0.6060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:59:49,350 - Iter: 46, Total Loss: 0.6060, loss_single: 0.6060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:59:49,385 - 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/simulation_data3__sample_000020.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 11.231908798217773 + probe_aberrations: + C10: -498.66058349609375 + C12: -34.23941421508789 + C21: -431.984130859375 + C23: -39.24949645996094 + C30: 1318682.5 + C32: 10612.7890625 + C34: 2188.16552734375 + C41: -240729.609375 + C43: -453905.96875 + C45: 96865.5625 + C50: -247494288.0 + C52: 8998041.0 + C54: 743044.875 + C56: 6377071.0 + phi12: 62.09359125404442 + phi21: 63.463160295847864 + phi23: 128.44613330467195 + phi32: 259.88929897563213 + phi34: 86.05297961710036 + phi41: 258.7501600258574 + phi43: 281.06758457282064 + phi45: 347.4453027007288 + phi52: 283.13106668335155 + phi54: 228.2212225115164 + phi56: 337.23119192908166 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.39237770438194275 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000020_measurement.h5 + key: measurement + random_seed: 20261948 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000020 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000020/c30_small__simulation_data3__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-499_C12_-34.2_phi12_62.1_C21_-432_phi21_63.5_C23_-39.2_phi23_128_C30_1.32e+06_C3.38e+06_phi56_337/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/20260624_060001_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:59:59,600 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:59:59,600 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:59:59,600 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:59:59,600 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:59:59,600 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:59:59,600 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:59:59,600 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:59:59,600 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:59:59,600 - +2026-06-24 05:59:59,724 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:59:59,724 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:59:59,724 - Accelerator.num_process = 1 +2026-06-24 05:59:59,724 - Accelerator.mixed_precision = no +2026-06-24 05:59:59,735 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:59:59,735 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:59:59,735 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:59:59,735 - +2026-06-24 05:59:59,735 - ### System information ### +2026-06-24 05:59:59,735 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:59:59,735 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:59:59,735 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:59:59,735 - Machine: x86_64 +2026-06-24 05:59:59,735 - Processor: x86_64 +2026-06-24 05:59:59,735 - Available CPU cores: 8 +2026-06-24 05:59:59,735 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:59:59,735 - +2026-06-24 05:59:59,735 - ### GPU information ### +2026-06-24 05:59:59,735 - CUDA Available: True +2026-06-24 05:59:59,736 - CUDA Version: 13.0 +2026-06-24 05:59:59,736 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:59:59,736 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:59:59,736 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:59:59,736 - In addition, Triton does not directly support Windows. +2026-06-24 05:59:59,736 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:59:59,752 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:59:59,752 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:59:59,752 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:59:59,752 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:59:59,752 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:59:59,752 - +2026-06-24 05:59:59,752 - ### Python information ### +2026-06-24 05:59:59,753 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:59:59,753 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:59:59,753 - +2026-06-24 05:59:59,753 - ### Packages information ### +2026-06-24 05:59:59,754 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:59:59,755 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:59:59,755 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:59:59,756 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:59:59,756 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:59:59,756 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:59:59,756 - +2026-06-24 05:59:59,757 - ### Loading params file ### +2026-06-24 05:59:59,757 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000021.yaml +2026-06-24 05:59:59,763 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:59:59,764 - Success! Params file validated and defaults applied. +2026-06-24 05:59:59,764 - +2026-06-24 05:59:59,764 - ### Setting GPU Device ### +2026-06-24 05:59:59,764 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:59:59,764 - +2026-06-24 05:59:59,764 - Random seed: 20261949 provided by params file +2026-06-24 05:59:59,765 - ### Initializing Initializer ### +2026-06-24 05:59:59,765 - init_params are displayed below: +2026-06-24 05:59:59,765 - random_seed: 20261949 +2026-06-24 05:59:59,765 - probe_illum_type: electron +2026-06-24 05:59:59,765 - probe_kv: 200.0 +2026-06-24 05:59:59,765 - probe_conv_angle: 11.25532341003418 +2026-06-24 05:59:59,765 - probe_aberrations: {'C10': -172.547, 'C12': 42.134, 'phi12': 130.341, 'C21': 975.725, 'phi21': 343.695, 'C23': -649.958, 'phi23': 78.243, 'C30': 2620627.0, 'C32': 2578.448, 'phi32': 135.553, 'C34': -10973.277, 'phi34': 15.656, 'C41': -171448.25, 'phi41': 291.902, 'C43': 360343.344, 'phi43': 202.031, 'C45': 455336.719, 'phi45': 45.578, 'C50': -106429304.0, 'C52': 8035212.0, 'phi52': 145.39, 'C54': 1519307.25, 'phi54': 148.722, 'C56': -18684532.0, 'phi56': 195.113} +2026-06-24 05:59:59,765 - beam_kev: None +2026-06-24 05:59:59,765 - probe_dRn: None +2026-06-24 05:59:59,765 - probe_Rn: None +2026-06-24 05:59:59,765 - probe_D_H: None +2026-06-24 05:59:59,765 - probe_D_FZP: None +2026-06-24 05:59:59,765 - probe_Ls: None +2026-06-24 05:59:59,765 - meas_Npix: 128 +2026-06-24 05:59:59,765 - pos_N_scans: 256 +2026-06-24 05:59:59,765 - pos_N_scan_slow: 16 +2026-06-24 05:59:59,765 - pos_N_scan_fast: 16 +2026-06-24 05:59:59,765 - pos_scan_step_size: 0.37316733598709106 +2026-06-24 05:59:59,765 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:59:59,765 - probe_pmode_max: 6 +2026-06-24 05:59:59,765 - probe_pmode_init_pows: [0.02] +2026-06-24 05:59:59,765 - obj_omode_max: 1 +2026-06-24 05:59:59,765 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:59:59,765 - obj_Nlayer: 1 +2026-06-24 05:59:59,765 - obj_slice_thickness: 20.0 +2026-06-24 05:59:59,765 - simu_Npix: None +2026-06-24 05:59:59,765 - simu_match_mode: None +2026-06-24 05:59:59,765 - meas_permute: None +2026-06-24 05:59:59,765 - meas_reshape: [256, 128, 128] +2026-06-24 05:59:59,766 - meas_flipT: [0, 0, 0] +2026-06-24 05:59:59,766 - meas_crop: None +2026-06-24 05:59:59,766 - meas_pad: None +2026-06-24 05:59:59,766 - meas_resample: None +2026-06-24 05:59:59,766 - meas_add_source_size: None +2026-06-24 05:59:59,766 - meas_add_detector_blur: None +2026-06-24 05:59:59,766 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:59:59,766 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:59:59,766 - meas_add_poisson_noise: None +2026-06-24 05:59:59,766 - meas_export: None +2026-06-24 05:59:59,766 - probe_permute: None +2026-06-24 05:59:59,766 - probe_z_shift: None +2026-06-24 05:59:59,766 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:59:59,766 - pos_scan_flipT: None +2026-06-24 05:59:59,766 - pos_scan_affine: None +2026-06-24 05:59:59,766 - pos_scan_rand_std: 0.15 +2026-06-24 05:59:59,766 - obj_z_crop: None +2026-06-24 05:59:59,766 - obj_z_pad: None +2026-06-24 05:59:59,766 - obj_z_resample: None +2026-06-24 05:59:59,766 - meas_source: file +2026-06-24 05:59:59,766 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000021_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:59:59,766 - probe_source: simu +2026-06-24 05:59:59,766 - probe_params: None +2026-06-24 05:59:59,766 - pos_source: simu +2026-06-24 05:59:59,766 - pos_params: None +2026-06-24 05:59:59,766 - obj_source: simu +2026-06-24 05:59:59,766 - obj_params: None +2026-06-24 05:59:59,766 - tilt_source: simu +2026-06-24 05:59:59,766 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:59:59,766 - +2026-06-24 05:59:59,766 - ### Initializing cache ### +2026-06-24 05:59:59,766 - use_cached_obj = False +2026-06-24 05:59:59,766 - use_cached_probe = False +2026-06-24 05:59:59,766 - use_cached_pos = False +2026-06-24 05:59:59,766 - +2026-06-24 05:59:59,766 - ### Initializing measurements ### +2026-06-24 05:59:59,766 - Loading measurements from source = 'file' +2026-06-24 05:59:59,766 - Detected measurement file type = '.h5' +2026-06-24 05:59:59,841 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:59:59,841 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:59:59,843 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0030) +2026-06-24 05:59:59,843 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:59:59,843 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:59:59,844 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:59,844 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:59:59,845 - Normalizing by max of the 2D mean pattern intensity: 0.0024608276 +2026-06-24 05:59:59,845 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:59:59,847 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0249, 1.2333) +2026-06-24 05:59:59,847 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:59:59,848 - Pattern total int. statistics (min, mean, max) = (403.6101, 407.5735, 411.3375), with min/max = 98.1% +2026-06-24 05:59:59,849 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0249, 1.2333) +2026-06-24 05:59:59,850 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:59:59,850 - +2026-06-24 05:59:59,850 - ### Setting up calibration ### +2026-06-24 05:59:59,850 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:59:59,850 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:59:59,850 - Radius of fitted bright field disk (RBF) = 11.35 px with meas_Npix = 128 +2026-06-24 05:59:59,850 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1774 +2026-06-24 05:59:59,850 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:59:59,850 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:00:00,077 - Initial guess: center=(63.64, 63.63), radius=11.35, Gaussian blur std=0.50 +2026-06-24 06:00:00,089 - Final fit: center=(63.64, 63.63), radius=11.35, Gaussian blur std=0.61 +2026-06-24 06:00:00,089 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.49 px with Npix = 128 +2026-06-24 06:00:00,089 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:00:00,089 - +2026-06-24 06:00:00,089 - ### Setting init_variables dict ### +2026-06-24 06:00:00,089 - Derived values given input init_params: +2026-06-24 06:00:00,089 - kv = 200.0 kV +2026-06-24 06:00:00,089 - wavelength = 0.0251 Ang +2026-06-24 06:00:00,089 - conv_angle = 11.25532341003418 mrad +2026-06-24 06:00:00,089 - Npix = 128 px +2026-06-24 06:00:00,089 - dk = 0.0391 Ang^-1 +2026-06-24 06:00:00,089 - kMax = 2.5000 Ang^-1 +2026-06-24 06:00:00,089 - da = 0.9797 mrad +2026-06-24 06:00:00,089 - angleMax = 62.6984 mrad +2026-06-24 06:00:00,089 - RBF = 11.4890 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:00:00,090 - n_alpha = 5.5706 (# conv_angle) +2026-06-24 06:00:00,090 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:00:00,090 - Rayleigh-limited resolution = 1.3592 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:00:00,090 - Real space probe extent = 25.6000 Ang +2026-06-24 06:00:00,090 - +2026-06-24 06:00:00,090 - ### Initializing probe ### +2026-06-24 06:00:00,090 - Loading probe from source = 'simu' +2026-06-24 06:00:00,090 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:00:00,090 - Start simulating STEM probe +2026-06-24 06:00:00,090 - kv = 200.0 kV +2026-06-24 06:00:00,090 - wavelength = 0.0251 Ang +2026-06-24 06:00:00,090 - conv_angle = 11.25532341003418 mrad +2026-06-24 06:00:00,090 - Npix = 128 px +2026-06-24 06:00:00,090 - dk = 0.0391 Ang^-1 +2026-06-24 06:00:00,090 - kMax = 2.5000 Ang^-1 +2026-06-24 06:00:00,090 - alpha_max = 62.6984 mrad +2026-06-24 06:00:00,090 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:00:00,090 - Rayleigh-limited resolution = 1.3592 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:00:00,090 - Real space probe extent = 25.6000 Ang +2026-06-24 06:00:00,091 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:00:00,091 - ------------------------------------------------------------------------------------- +2026-06-24 06:00:00,091 - C1,0 C1 -172.5470 - Defocus (C10 = -df) +2026-06-24 06:00:00,091 - C1,2 A1 42.1340 130.34 2-fold astigmatism +2026-06-24 06:00:00,091 - C2,1 3*B2 975.7250 343.69 Axial coma +2026-06-24 06:00:00,091 - C2,3 A2 -649.9580 78.24 3-fold astigmatism +2026-06-24 06:00:00,091 - C3,0 C3 2620627.0000 - Spherical aberration +2026-06-24 06:00:00,091 - C3,2 4*S3 2578.4480 135.55 Axial star aberration +2026-06-24 06:00:00,091 - C3,4 A3 -10973.2770 15.66 4-fold astigmatism +2026-06-24 06:00:00,091 - C4,1 4*B4 -171448.2500 291.90 Axial coma(4th) +2026-06-24 06:00:00,091 - C4,3 4*D4 360343.3440 202.03 3-lobe aberration +2026-06-24 06:00:00,091 - C4,5 A4 455336.7190 45.58 5-fold astigmatism +2026-06-24 06:00:00,091 - C5,0 C5 -106429304.0000 - Spherical aberration (5th) +2026-06-24 06:00:00,091 - C5,2 6*S5 8035212.0000 145.39 Axial star aberration(5th) +2026-06-24 06:00:00,091 - C5,4 6*R5 1519307.2500 148.72 4-lobe aberration +2026-06-24 06:00:00,091 - C5,6 A5 -18684532.0000 195.11 6-fold astigmatism +2026-06-24 06:00:00,094 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:00:00,094 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:00:00,094 - Creating 5 new probe modes from the major mode +2026-06-24 06:00:00,094 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:00:00,318 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:00:00,319 - Orthogonalizing 6 pmodes +2026-06-24 06:00:00,332 - Sorting 6 pmodes by their intensities +2026-06-24 06:00:00,332 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:00:00,333 - sum(|probe_data|**2) = 407.57, while meas_total_ints (min, mean, max) = (403.6101, 407.5735, 411.3375) +2026-06-24 06:00:00,333 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:00:00,333 - +2026-06-24 06:00:00,333 - ### Initializing probe positions ### +2026-06-24 06:00:00,333 - Loading probe positions from source = 'simu' +2026-06-24 06:00:00,333 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:00:00,333 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3732, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:00:00,333 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:00:00,336 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:00:00,336 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 06:00:00,336 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:00:00,336 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:00:00,336 - +2026-06-24 06:00:00,336 - ### Initializing object ### +2026-06-24 06:00:00,336 - Loading object from source = 'simu' +2026-06-24 06:00:00,336 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:00:00,337 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:00:00,337 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:00:00,337 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:00:00,338 - +2026-06-24 06:00:00,338 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:00:00,338 - omode_occu (omode) = float32, (1,) +2026-06-24 06:00:00,338 - +2026-06-24 06:00:00,338 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:00:00,338 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:00:00,338 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:00:00,338 - +2026-06-24 06:00:00,338 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:00:00,338 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:00:00,339 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:00:00,339 - +2026-06-24 06:00:00,339 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:00:00,339 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:00:00,339 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:00:00,339 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:00:00,339 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:00:00,339 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:00:00,339 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:00:00,339 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:00:00,339 - +2026-06-24 06:00:00,339 - ### Collecting reconstruction provenance ### +2026-06-24 06:00:00,339 - Reconstruction provenance is collected and initialized. +2026-06-24 06:00:00,339 - +2026-06-24 06:00:00,339 - ### Initializing loss function ### +2026-06-24 06:00:00,339 - Active loss types: +2026-06-24 06:00:00,339 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:00:00,339 - +2026-06-24 06:00:00,339 - ### Initializing constraint function ### +2026-06-24 06:00:00,339 - Active constraint types: +2026-06-24 06:00:00,339 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:00:00,340 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:00:00,340 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:00:00,340 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:00:00,340 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:00:00,340 - +2026-06-24 06:00:00,340 - ### Done initializing PtyRADSolver ### +2026-06-24 06:00:00,340 - +2026-06-24 06:00:00,464 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:00:00,464 - +2026-06-24 06:00:00,465 - ### Initializing PtychoModel model ### +2026-06-24 06:00:00,535 - ### PtychoModel optimizable variables ### +2026-06-24 06:00:00,536 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:00,536 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:00,536 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:00:00,536 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:00:00,536 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:00:00,536 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:00,536 - +2026-06-24 06:00:00,536 - ### Optimizable variables statitsics ### +2026-06-24 06:00:00,536 - Total measurement values : 4,194,304 +2026-06-24 06:00:00,536 - Total optimizing variables: 267,808 +2026-06-24 06:00:00,536 - Overdetermined ratio : 15.66 +2026-06-24 06:00:00,536 - +2026-06-24 06:00:00,536 - ### Model behavior ### +2026-06-24 06:00:00,536 - Tilt propagator : False +2026-06-24 06:00:00,536 - Change slice thickness : False +2026-06-24 06:00:00,536 - Detector blur : False +2026-06-24 06:00:00,536 - Preload data : True +2026-06-24 06:00:00,536 - On-the-fly meas padding : False +2026-06-24 06:00:00,536 - On-the-fly meas resample : False +2026-06-24 06:00:00,536 - On-the-fly simu match mode: None +2026-06-24 06:00:00,536 - +2026-06-24 06:00:00,578 - ### Done initializing PtychoModel model ### +2026-06-24 06:00:00,578 - +2026-06-24 06:00:00,578 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:00:00,578 - +2026-06-24 06:00:00,578 - ### Generating indices, batches, and output_path ### +2026-06-24 06:00:00,580 - d90 = 27.000 px or 5.400 Ang +2026-06-24 06:00:00,580 - Selecting indices with the 'full' mode +2026-06-24 06:00:01,040 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:00:01,117 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:00:01,117 - Original recon_dir_affixes = ['default'] +2026-06-24 06:00:01,117 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:00:01,123 - Path corrected for compatibility: +2026-06-24 06:00:01,124 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2.58e+03_phi32_136_C34_-1.1e+04_phi34_15.7_C41_-1.71e+05_phi41_292_C43_3.6e+05_phi43_202_C45_4.55e+05_phi45_45.6_C50_-1.06e+08_C52_8.04e+06_phi52_145_C54_1.52e+06_phi54_149_C56_-1.87e+07_phi56_195 +2026-06-24 06:00:01,124 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195 +2026-06-24 06:00:01,124 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195' is generated! +2026-06-24 06:00:01,272 - +2026-06-24 06:00:01,273 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/20260624_060001_ptyrad_log.txt ### +2026-06-24 06:00:01,273 - +2026-06-24 06:00:01,274 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:00:01,275 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:00:01,275 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:00:02,469 - Iter: 1, Total Loss: 0.9890, loss_single: 0.9890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:00:02,506 - Iter: 2, Total Loss: 0.9470, loss_single: 0.9470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:00:02,542 - Iter: 3, Total Loss: 0.9172, loss_single: 0.9172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,577 - Iter: 4, Total Loss: 0.8890, loss_single: 0.8890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,612 - Iter: 5, Total Loss: 0.8598, loss_single: 0.8598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,648 - Iter: 6, Total Loss: 0.8350, loss_single: 0.8350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,682 - Iter: 7, Total Loss: 0.8140, loss_single: 0.8140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:02,717 - Iter: 8, Total Loss: 0.7924, loss_single: 0.7924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,753 - Iter: 9, Total Loss: 0.7708, loss_single: 0.7708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,788 - Iter: 10, Total Loss: 0.7537, loss_single: 0.7537, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,824 - Iter: 11, Total Loss: 0.7397, loss_single: 0.7397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,859 - Iter: 12, Total Loss: 0.7227, loss_single: 0.7227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,894 - Iter: 13, Total Loss: 0.7038, loss_single: 0.7038, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,929 - Iter: 14, Total Loss: 0.6893, loss_single: 0.6893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,964 - Iter: 15, Total Loss: 0.6785, loss_single: 0.6785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:02,999 - Iter: 16, Total Loss: 0.6674, loss_single: 0.6674, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,034 - Iter: 17, Total Loss: 0.6551, loss_single: 0.6551, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,069 - Iter: 18, Total Loss: 0.6429, loss_single: 0.6429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,104 - Iter: 19, Total Loss: 0.6336, loss_single: 0.6336, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,139 - Iter: 20, Total Loss: 0.6239, loss_single: 0.6239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,174 - Iter: 21, Total Loss: 0.6133, loss_single: 0.6133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,210 - Iter: 22, Total Loss: 0.6052, loss_single: 0.6052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,245 - Iter: 23, Total Loss: 0.5988, loss_single: 0.5988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,280 - Iter: 24, Total Loss: 0.5917, loss_single: 0.5917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,315 - Iter: 25, Total Loss: 0.5841, loss_single: 0.5841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,350 - Iter: 26, Total Loss: 0.5760, loss_single: 0.5760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,385 - Iter: 27, Total Loss: 0.5677, loss_single: 0.5677, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,420 - Iter: 28, Total Loss: 0.5606, loss_single: 0.5606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,455 - Iter: 29, Total Loss: 0.5532, loss_single: 0.5532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,490 - Iter: 30, Total Loss: 0.5473, loss_single: 0.5473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,525 - Iter: 31, Total Loss: 0.5422, loss_single: 0.5422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,560 - Iter: 32, Total Loss: 0.5360, loss_single: 0.5360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,595 - Iter: 33, Total Loss: 0.5308, loss_single: 0.5308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,631 - Iter: 34, Total Loss: 0.5269, loss_single: 0.5269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,666 - Iter: 35, Total Loss: 0.5229, loss_single: 0.5229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,701 - Iter: 36, Total Loss: 0.5188, loss_single: 0.5188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,736 - Iter: 37, Total Loss: 0.5143, loss_single: 0.5143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,772 - Iter: 38, Total Loss: 0.5104, loss_single: 0.5104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,806 - Iter: 39, Total Loss: 0.5073, loss_single: 0.5073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:03,842 - Iter: 40, Total Loss: 0.5025, loss_single: 0.5025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,880 - Iter: 41, Total Loss: 0.4961, loss_single: 0.4961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,915 - Iter: 42, Total Loss: 0.4919, loss_single: 0.4919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,950 - Iter: 43, Total Loss: 0.4875, loss_single: 0.4875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:03,985 - Iter: 44, Total Loss: 0.4819, loss_single: 0.4819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,020 - Iter: 45, Total Loss: 0.4781, loss_single: 0.4781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,055 - Iter: 46, Total Loss: 0.4741, loss_single: 0.4741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,090 - Iter: 47, Total Loss: 0.4700, loss_single: 0.4700, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,126 - Iter: 48, Total Loss: 0.4654, loss_single: 0.4654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,160 - Iter: 49, Total Loss: 0.4614, loss_single: 0.4614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,196 - Iter: 50, Total Loss: 0.4591, loss_single: 0.4591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,231 - Iter: 51, Total Loss: 0.4561, loss_single: 0.4561, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,266 - Iter: 52, Total Loss: 0.4534, loss_single: 0.4534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,301 - Iter: 53, Total Loss: 0.4507, loss_single: 0.4507, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,336 - Iter: 54, Total Loss: 0.4470, loss_single: 0.4470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,371 - Iter: 55, Total Loss: 0.4419, loss_single: 0.4419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,406 - Iter: 56, Total Loss: 0.4368, loss_single: 0.4368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,441 - Iter: 57, Total Loss: 0.4334, loss_single: 0.4334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,476 - Iter: 58, Total Loss: 0.4317, loss_single: 0.4317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,511 - Iter: 59, Total Loss: 0.4298, loss_single: 0.4298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,546 - Iter: 60, Total Loss: 0.4267, loss_single: 0.4267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:04,581 - Iter: 61, Total Loss: 0.4243, loss_single: 0.4243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,616 - Iter: 62, Total Loss: 0.4223, loss_single: 0.4223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:04,653 - Iter: 63, Total Loss: 0.4199, loss_single: 0.4199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:00:04,688 - Iter: 64, 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0.3466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:05,912 - Iter: 99, Total Loss: 0.3457, loss_single: 0.3457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:05,947 - Iter: 100, Total Loss: 0.3447, loss_single: 0.3447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:06,058 - Saving summary figures for iter 100 +2026-06-24 06:00:09,573 - ### Finished 100 iterations, averaged iter_t = 0.038679 with std = 0.040 ### +2026-06-24 06:00:09,574 - +2026-06-24 06:00:09,574 - ### The PtyRADSolver is finished in 9.109 sec ### +2026-06-24 06:00:09,574 - diff --git 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/simulation_data3__sample_000021.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/simulation_data3__sample_000021.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e4b6ef0e9c1e6c041caec7f63a3b338e85bdf3dd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/simulation_data3__sample_000021.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 11.25532341003418 + probe_aberrations: + C10: -172.5470733642578 + C12: 42.13441848754883 + C21: 975.7246704101562 + C23: -649.9581298828125 + C30: 2620627.0 + C32: 2578.4482421875 + C34: -10973.27734375 + C41: -171448.25 + C43: 360343.34375 + C45: 455336.71875 + C50: -106429304.0 + C52: 8035212.0 + C54: 1519307.25 + C56: -18684532.0 + phi12: 130.34129223329705 + phi21: 343.695173676555 + phi23: 78.24310226348683 + phi32: 135.5530134379619 + phi34: 15.656241577773267 + phi41: 291.9019311626183 + phi43: 202.03084847872415 + phi45: 45.57776012394129 + phi52: 145.38953769191247 + phi54: 148.7224651012036 + phi56: 195.11302798166014 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37316733598709106 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000021_measurement.h5 + key: measurement + random_seed: 20261949 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000021 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000021/c30_small__simulation_data3__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_42.1_phi12_130_C21_976_phi21_344_C23_-650_phi23_78.2_C30_2.62e+06_C32_2..87e+07_phi56_195/summary_convergence_iter0100.png new file mode 100644 index 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sha256:21d50d86def7b460d869ab0418cefa15940890d02b4a4fde18cc1b9399098e3a +size 48319 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/20260624_060045_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/20260624_060045_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..dac51d3ea1309d4150cc9c619d3313a6fda98749 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/20260624_060045_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:00:43,699 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:00:43,699 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:00:43,699 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:00:43,699 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:00:43,700 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:00:43,700 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:00:43,700 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:00:43,700 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:00:43,700 - +2026-06-24 06:00:43,807 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:00:43,807 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:00:43,807 - Accelerator.num_process = 1 +2026-06-24 06:00:43,807 - Accelerator.mixed_precision = no +2026-06-24 06:00:43,817 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:00:43,817 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:00:43,817 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:00:43,817 - +2026-06-24 06:00:43,817 - ### System information ### +2026-06-24 06:00:43,817 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:00:43,818 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:00:43,818 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:00:43,818 - Machine: x86_64 +2026-06-24 06:00:43,818 - Processor: x86_64 +2026-06-24 06:00:43,818 - Available CPU cores: 8 +2026-06-24 06:00:43,818 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:00:43,818 - +2026-06-24 06:00:43,818 - ### GPU information ### +2026-06-24 06:00:43,818 - CUDA Available: True +2026-06-24 06:00:43,818 - CUDA Version: 13.0 +2026-06-24 06:00:43,818 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:00:43,818 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:00:43,818 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:00:43,818 - In addition, Triton does not directly support Windows. +2026-06-24 06:00:43,819 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:00:43,834 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:00:43,834 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:00:43,835 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:00:43,835 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:00:43,835 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:00:43,835 - +2026-06-24 06:00:43,835 - ### Python information ### +2026-06-24 06:00:43,837 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:00:43,837 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:00:43,837 - +2026-06-24 06:00:43,837 - ### Packages information ### +2026-06-24 06:00:43,838 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:00:43,838 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:00:43,839 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:00:43,840 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:00:43,840 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:00:43,840 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:00:43,840 - +2026-06-24 06:00:43,840 - ### Loading params file ### +2026-06-24 06:00:43,840 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000024.yaml +2026-06-24 06:00:43,847 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:00:43,848 - Success! Params file validated and defaults applied. +2026-06-24 06:00:43,848 - +2026-06-24 06:00:43,848 - ### Setting GPU Device ### +2026-06-24 06:00:43,848 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:00:43,848 - +2026-06-24 06:00:43,848 - Random seed: 20261952 provided by params file +2026-06-24 06:00:43,848 - ### Initializing Initializer ### +2026-06-24 06:00:43,848 - init_params are displayed below: +2026-06-24 06:00:43,848 - random_seed: 20261952 +2026-06-24 06:00:43,849 - probe_illum_type: electron +2026-06-24 06:00:43,849 - probe_kv: 80.0 +2026-06-24 06:00:43,849 - probe_conv_angle: 11.798361778259277 +2026-06-24 06:00:43,849 - probe_aberrations: {'C10': -179.586, 'C12': -27.209, 'phi12': 195.503, 'C21': 652.601, 'phi21': 139.024, 'C23': -840.59, 'phi23': 10.029, 'C30': 4919342.5, 'C32': -2221.543, 'phi32': 256.921, 'C34': -3709.869, 'phi34': 32.232, 'C41': 460935.969, 'phi41': 94.47, 'C43': -348589.562, 'phi43': 44.011, 'C45': 89982.609, 'phi45': 317.604, 'C50': 35151548.0, 'C52': 10237128.0, 'phi52': 254.703, 'C54': 7789527.0, 'phi54': 275.018, 'C56': -15559670.0, 'phi56': 70.792} +2026-06-24 06:00:43,849 - beam_kev: None +2026-06-24 06:00:43,849 - probe_dRn: None +2026-06-24 06:00:43,849 - probe_Rn: None +2026-06-24 06:00:43,849 - probe_D_H: None +2026-06-24 06:00:43,849 - probe_D_FZP: None +2026-06-24 06:00:43,849 - probe_Ls: None +2026-06-24 06:00:43,849 - meas_Npix: 128 +2026-06-24 06:00:43,849 - pos_N_scans: 256 +2026-06-24 06:00:43,849 - pos_N_scan_slow: 16 +2026-06-24 06:00:43,849 - pos_N_scan_fast: 16 +2026-06-24 06:00:43,849 - pos_scan_step_size: 0.35756543278694153 +2026-06-24 06:00:43,849 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:00:43,849 - probe_pmode_max: 6 +2026-06-24 06:00:43,849 - probe_pmode_init_pows: [0.02] +2026-06-24 06:00:43,849 - obj_omode_max: 1 +2026-06-24 06:00:43,849 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:00:43,849 - obj_Nlayer: 1 +2026-06-24 06:00:43,849 - obj_slice_thickness: 20.0 +2026-06-24 06:00:43,849 - simu_Npix: None +2026-06-24 06:00:43,849 - simu_match_mode: None +2026-06-24 06:00:43,849 - meas_permute: None +2026-06-24 06:00:43,849 - meas_reshape: [256, 128, 128] +2026-06-24 06:00:43,849 - meas_flipT: [0, 0, 0] +2026-06-24 06:00:43,849 - meas_crop: None +2026-06-24 06:00:43,849 - meas_pad: None +2026-06-24 06:00:43,849 - meas_resample: None +2026-06-24 06:00:43,849 - meas_add_source_size: None +2026-06-24 06:00:43,849 - meas_add_detector_blur: None +2026-06-24 06:00:43,849 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:00:43,849 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:00:43,849 - meas_add_poisson_noise: None +2026-06-24 06:00:43,849 - meas_export: None +2026-06-24 06:00:43,849 - probe_permute: None +2026-06-24 06:00:43,849 - probe_z_shift: None +2026-06-24 06:00:43,849 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:00:43,850 - pos_scan_flipT: None +2026-06-24 06:00:43,850 - pos_scan_affine: None +2026-06-24 06:00:43,850 - pos_scan_rand_std: 0.15 +2026-06-24 06:00:43,850 - obj_z_crop: None +2026-06-24 06:00:43,850 - obj_z_pad: None +2026-06-24 06:00:43,850 - obj_z_resample: None +2026-06-24 06:00:43,850 - meas_source: file +2026-06-24 06:00:43,850 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000024_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:00:43,850 - probe_source: simu +2026-06-24 06:00:43,850 - probe_params: None +2026-06-24 06:00:43,850 - pos_source: simu +2026-06-24 06:00:43,850 - pos_params: None +2026-06-24 06:00:43,850 - obj_source: simu +2026-06-24 06:00:43,850 - obj_params: None +2026-06-24 06:00:43,850 - tilt_source: simu +2026-06-24 06:00:43,850 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:00:43,850 - +2026-06-24 06:00:43,850 - ### Initializing cache ### +2026-06-24 06:00:43,850 - use_cached_obj = False +2026-06-24 06:00:43,850 - use_cached_probe = False +2026-06-24 06:00:43,850 - use_cached_pos = False +2026-06-24 06:00:43,850 - +2026-06-24 06:00:43,850 - ### Initializing measurements ### +2026-06-24 06:00:43,850 - Loading measurements from source = 'file' +2026-06-24 06:00:43,850 - Detected measurement file type = '.h5' +2026-06-24 06:00:43,927 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:00:43,927 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:00:43,929 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0073) +2026-06-24 06:00:43,929 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:00:43,929 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:00:43,931 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:00:43,931 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:00:43,932 - Normalizing by max of the 2D mean pattern intensity: 0.006078817 +2026-06-24 06:00:43,932 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:00:43,935 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0100, 1.2019) +2026-06-24 06:00:43,936 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:00:43,937 - Pattern total int. statistics (min, mean, max) = (163.4113, 164.6093, 165.7439), with min/max = 98.6% +2026-06-24 06:00:43,938 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0100, 1.2019) +2026-06-24 06:00:43,938 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:00:43,939 - +2026-06-24 06:00:43,939 - ### Setting up calibration ### +2026-06-24 06:00:43,939 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:00:43,939 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:00:43,939 - Radius of fitted bright field disk (RBF) = 7.18 px with meas_Npix = 128 +2026-06-24 06:00:43,939 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1122 +2026-06-24 06:00:43,939 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:00:43,939 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:00:44,167 - Initial guess: center=(63.63, 63.62), radius=7.18, Gaussian blur std=0.50 +2026-06-24 06:00:44,175 - Final fit: center=(63.63, 63.62), radius=7.18, Gaussian blur std=0.54 +2026-06-24 06:00:44,175 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 7.23 px with Npix = 128 +2026-06-24 06:00:44,175 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:00:44,175 - +2026-06-24 06:00:44,175 - ### Setting init_variables dict ### +2026-06-24 06:00:44,176 - Derived values given input init_params: +2026-06-24 06:00:44,176 - kv = 80.0 kV +2026-06-24 06:00:44,176 - wavelength = 0.0418 Ang +2026-06-24 06:00:44,176 - conv_angle = 11.798361778259277 mrad +2026-06-24 06:00:44,176 - Npix = 128 px +2026-06-24 06:00:44,176 - dk = 0.0391 Ang^-1 +2026-06-24 06:00:44,176 - kMax = 2.5000 Ang^-1 +2026-06-24 06:00:44,176 - da = 1.6311 mrad +2026-06-24 06:00:44,176 - angleMax = 104.3929 mrad +2026-06-24 06:00:44,176 - RBF = 7.2332 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:00:44,176 - n_alpha = 8.8481 (# conv_angle) +2026-06-24 06:00:44,176 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:00:44,176 - Rayleigh-limited resolution = 2.1589 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:00:44,176 - Real space probe extent = 25.6000 Ang +2026-06-24 06:00:44,176 - +2026-06-24 06:00:44,176 - ### Initializing probe ### +2026-06-24 06:00:44,176 - Loading probe from source = 'simu' +2026-06-24 06:00:44,176 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:00:44,176 - Start simulating STEM probe +2026-06-24 06:00:44,176 - kv = 80.0 kV +2026-06-24 06:00:44,176 - wavelength = 0.0418 Ang +2026-06-24 06:00:44,176 - conv_angle = 11.798361778259277 mrad +2026-06-24 06:00:44,176 - Npix = 128 px +2026-06-24 06:00:44,176 - dk = 0.0391 Ang^-1 +2026-06-24 06:00:44,176 - kMax = 2.5000 Ang^-1 +2026-06-24 06:00:44,177 - alpha_max = 104.3929 mrad +2026-06-24 06:00:44,177 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:00:44,177 - Rayleigh-limited resolution = 2.1589 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:00:44,177 - Real space probe extent = 25.6000 Ang +2026-06-24 06:00:44,177 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:00:44,177 - ------------------------------------------------------------------------------------ +2026-06-24 06:00:44,177 - C1,0 C1 -179.5860 - Defocus (C10 = -df) +2026-06-24 06:00:44,177 - C1,2 A1 -27.2090 195.50 2-fold astigmatism +2026-06-24 06:00:44,177 - C2,1 3*B2 652.6010 139.02 Axial coma +2026-06-24 06:00:44,177 - C2,3 A2 -840.5900 10.03 3-fold astigmatism +2026-06-24 06:00:44,177 - C3,0 C3 4919342.5000 - Spherical aberration +2026-06-24 06:00:44,177 - C3,2 4*S3 -2221.5430 256.92 Axial star aberration +2026-06-24 06:00:44,177 - C3,4 A3 -3709.8690 32.23 4-fold astigmatism +2026-06-24 06:00:44,177 - C4,1 4*B4 460935.9690 94.47 Axial coma(4th) +2026-06-24 06:00:44,177 - C4,3 4*D4 -348589.5620 44.01 3-lobe aberration +2026-06-24 06:00:44,177 - C4,5 A4 89982.6090 317.60 5-fold astigmatism +2026-06-24 06:00:44,177 - C5,0 C5 35151548.0000 - Spherical aberration (5th) +2026-06-24 06:00:44,177 - C5,2 6*S5 10237128.0000 254.70 Axial star aberration(5th) +2026-06-24 06:00:44,177 - C5,4 6*R5 7789527.0000 275.02 4-lobe aberration +2026-06-24 06:00:44,177 - C5,6 A5 -15559670.0000 70.79 6-fold astigmatism +2026-06-24 06:00:44,180 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:00:44,180 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:00:44,180 - Creating 5 new probe modes from the major mode +2026-06-24 06:00:44,180 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:00:44,286 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:00:44,288 - Orthogonalizing 6 pmodes +2026-06-24 06:00:44,291 - Sorting 6 pmodes by their intensities +2026-06-24 06:00:44,291 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:00:44,292 - sum(|probe_data|**2) = 164.61, while meas_total_ints (min, mean, max) = (163.4113, 164.6093, 165.7439) +2026-06-24 06:00:44,292 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:00:44,292 - +2026-06-24 06:00:44,292 - ### Initializing probe positions ### +2026-06-24 06:00:44,292 - Loading probe positions from source = 'simu' +2026-06-24 06:00:44,292 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:00:44,292 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3576, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:00:44,293 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:00:44,295 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:00:44,295 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 06:00:44,295 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:00:44,295 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:00:44,295 - +2026-06-24 06:00:44,295 - ### Initializing object ### +2026-06-24 06:00:44,295 - Loading object from source = 'simu' +2026-06-24 06:00:44,295 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:00:44,297 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:00:44,297 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 06:00:44,297 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 06:00:44,297 - +2026-06-24 06:00:44,297 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:00:44,297 - omode_occu (omode) = float32, (1,) +2026-06-24 06:00:44,297 - +2026-06-24 06:00:44,297 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:00:44,297 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:00:44,298 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:00:44,298 - +2026-06-24 06:00:44,298 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:00:44,298 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:00:44,298 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:00:44,298 - +2026-06-24 06:00:44,298 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:00:44,298 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:00:44,298 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:00:44,298 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:00:44,298 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:00:44,298 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 06:00:44,298 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:00:44,298 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:00:44,298 - +2026-06-24 06:00:44,298 - ### Collecting reconstruction provenance ### +2026-06-24 06:00:44,299 - Reconstruction provenance is collected and initialized. +2026-06-24 06:00:44,299 - +2026-06-24 06:00:44,299 - ### Initializing loss function ### +2026-06-24 06:00:44,299 - Active loss types: +2026-06-24 06:00:44,299 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:00:44,299 - +2026-06-24 06:00:44,299 - ### Initializing constraint function ### +2026-06-24 06:00:44,299 - Active constraint types: +2026-06-24 06:00:44,299 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:00:44,299 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:00:44,299 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:00:44,299 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:00:44,299 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:00:44,299 - +2026-06-24 06:00:44,299 - ### Done initializing PtyRADSolver ### +2026-06-24 06:00:44,299 - +2026-06-24 06:00:44,424 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:00:44,425 - +2026-06-24 06:00:44,425 - ### Initializing PtychoModel model ### +2026-06-24 06:00:44,508 - ### PtychoModel optimizable variables ### +2026-06-24 06:00:44,508 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:44,508 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:44,508 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:00:44,508 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:00:44,508 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:00:44,509 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:00:44,509 - +2026-06-24 06:00:44,509 - ### Optimizable variables statitsics ### +2026-06-24 06:00:44,509 - Total measurement values : 4,194,304 +2026-06-24 06:00:44,509 - Total optimizing variables: 267,058 +2026-06-24 06:00:44,509 - Overdetermined ratio : 15.71 +2026-06-24 06:00:44,509 - +2026-06-24 06:00:44,509 - ### Model behavior ### +2026-06-24 06:00:44,509 - Tilt propagator : False +2026-06-24 06:00:44,509 - Change slice thickness : False +2026-06-24 06:00:44,509 - Detector blur : False +2026-06-24 06:00:44,509 - Preload data : True +2026-06-24 06:00:44,509 - On-the-fly meas padding : False +2026-06-24 06:00:44,509 - On-the-fly meas resample : False +2026-06-24 06:00:44,509 - On-the-fly simu match mode: None +2026-06-24 06:00:44,509 - +2026-06-24 06:00:44,550 - ### Done initializing PtychoModel model ### +2026-06-24 06:00:44,550 - +2026-06-24 06:00:44,550 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:00:44,551 - +2026-06-24 06:00:44,551 - ### Generating indices, batches, and output_path ### +2026-06-24 06:00:44,552 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:00:44,552 - Selecting indices with the 'full' mode +2026-06-24 06:00:45,008 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:00:45,082 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:00:45,082 - Original recon_dir_affixes = ['default'] +2026-06-24 06:00:45,082 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:00:45,088 - Path corrected for compatibility: +2026-06-24 06:00:45,088 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_257_C34_-3.71e+03_phi34_32.2_C41_4.61e+05_phi41_94.5_C43_-3.49e+05_phi43_44_C45_9e+04_phi45_318_C50_3.52e+07_C52_1.02e+07_phi52_255_C54_7.79e+06_phi54_275_C56_-1.56e+07_phi56_70.8 +2026-06-24 06:00:45,088 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8 +2026-06-24 06:00:45,089 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8' is generated! +2026-06-24 06:00:45,239 - +2026-06-24 06:00:45,240 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/20260624_060045_ptyrad_log.txt ### +2026-06-24 06:00:45,240 - +2026-06-24 06:00:45,241 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:00:45,241 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:00:45,241 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:00:46,421 - Iter: 1, Total Loss: 1.3787, loss_single: 1.3787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:00:46,460 - Iter: 2, Total Loss: 1.2757, loss_single: 1.2757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:00:46,495 - Iter: 3, Total Loss: 1.1958, loss_single: 1.1958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,531 - Iter: 4, Total Loss: 1.1148, loss_single: 1.1148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,567 - Iter: 5, Total Loss: 1.0315, loss_single: 1.0315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:00:46,602 - Iter: 6, Total Loss: 0.9503, loss_single: 0.9503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,637 - Iter: 7, Total Loss: 0.8780, loss_single: 0.8780, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,672 - Iter: 8, Total Loss: 0.8301, loss_single: 0.8301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:46,707 - Iter: 9, Total Loss: 0.7879, loss_single: 0.7879, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,742 - Iter: 10, Total Loss: 0.7418, loss_single: 0.7418, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,777 - Iter: 11, Total Loss: 0.6957, loss_single: 0.6957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,812 - Iter: 12, Total Loss: 0.6444, loss_single: 0.6444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,847 - Iter: 13, Total Loss: 0.6027, loss_single: 0.6027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,882 - Iter: 14, Total Loss: 0.5628, loss_single: 0.5628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,917 - Iter: 15, Total Loss: 0.5302, loss_single: 0.5302, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,952 - Iter: 16, Total Loss: 0.5043, loss_single: 0.5043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:46,990 - Iter: 17, Total Loss: 0.4795, loss_single: 0.4795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:00:47,025 - Iter: 18, Total Loss: 0.4622, loss_single: 0.4622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,061 - Iter: 19, Total Loss: 0.4463, loss_single: 0.4463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,096 - Iter: 20, Total Loss: 0.4335, loss_single: 0.4335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,132 - Iter: 21, Total Loss: 0.4222, loss_single: 0.4222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,199 - Iter: 22, Total Loss: 0.4132, loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,234 - Iter: 23, Total Loss: 0.4060, loss_single: 0.4060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,269 - Iter: 24, Total Loss: 0.3992, loss_single: 0.3992, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,305 - Iter: 25, Total Loss: 0.3940, loss_single: 0.3940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,340 - Iter: 26, Total Loss: 0.3886, loss_single: 0.3886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,375 - Iter: 27, Total Loss: 0.3843, loss_single: 0.3843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,410 - Iter: 28, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,445 - Iter: 29, Total Loss: 0.3787, loss_single: 0.3787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:47,480 - Iter: 30, Total Loss: 0.3769, loss_single: 0.3769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,518 - Iter: 31, Total Loss: 0.3750, loss_single: 0.3750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:00:47,554 - Iter: 32, Total Loss: 0.3729, loss_single: 0.3729, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,589 - Iter: 33, Total Loss: 0.3715, loss_single: 0.3715, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,624 - Iter: 34, Total Loss: 0.3702, loss_single: 0.3702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,659 - Iter: 35, Total Loss: 0.3692, loss_single: 0.3692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,694 - Iter: 36, Total Loss: 0.3685, loss_single: 0.3685, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,730 - Iter: 37, Total Loss: 0.3680, loss_single: 0.3680, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,765 - Iter: 38, Total Loss: 0.3676, loss_single: 0.3676, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,800 - Iter: 39, Total Loss: 0.3669, loss_single: 0.3669, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,835 - Iter: 40, Total Loss: 0.3664, loss_single: 0.3664, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,872 - Iter: 41, Total Loss: 0.3659, loss_single: 0.3659, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,907 - Iter: 42, Total Loss: 0.3655, loss_single: 0.3655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,942 - Iter: 43, Total Loss: 0.3652, loss_single: 0.3652, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:47,978 - Iter: 44, Total Loss: 0.3649, loss_single: 0.3649, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,013 - Iter: 45, Total Loss: 0.3646, loss_single: 0.3646, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,048 - Iter: 46, Total Loss: 0.3643, loss_single: 0.3643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,087 - Iter: 47, Total Loss: 0.3641, loss_single: 0.3641, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:00:48,123 - Iter: 48, Total Loss: 0.3639, loss_single: 0.3639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:00:48,158 - Iter: 49, Total Loss: 0.3637, loss_single: 0.3637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,193 - Iter: 50, Total Loss: 0.3635, loss_single: 0.3635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,228 - Iter: 51, Total Loss: 0.3634, loss_single: 0.3634, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,264 - Iter: 52, Total Loss: 0.3633, loss_single: 0.3633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,299 - Iter: 53, Total Loss: 0.3631, loss_single: 0.3631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,335 - Iter: 54, Total Loss: 0.3630, loss_single: 0.3630, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,370 - Iter: 55, Total Loss: 0.3629, loss_single: 0.3629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,405 - Iter: 56, Total Loss: 0.3627, loss_single: 0.3627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,440 - Iter: 57, Total Loss: 0.3626, loss_single: 0.3626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,475 - Iter: 58, Total Loss: 0.3625, loss_single: 0.3625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,510 - Iter: 59, Total Loss: 0.3623, loss_single: 0.3623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,546 - Iter: 60, Total Loss: 0.3622, loss_single: 0.3622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,581 - Iter: 61, Total Loss: 0.3621, loss_single: 0.3621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,619 - Iter: 62, Total Loss: 0.3620, loss_single: 0.3620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:00:48,654 - Iter: 63, Total Loss: 0.3618, loss_single: 0.3618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,690 - Iter: 64, Total Loss: 0.3617, loss_single: 0.3617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,725 - Iter: 65, Total Loss: 0.3616, loss_single: 0.3616, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,760 - Iter: 66, Total Loss: 0.3615, loss_single: 0.3615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,796 - Iter: 67, Total Loss: 0.3614, loss_single: 0.3614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,831 - Iter: 68, Total Loss: 0.3612, loss_single: 0.3612, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,867 - Iter: 69, Total Loss: 0.3611, loss_single: 0.3611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,902 - Iter: 70, Total Loss: 0.3610, loss_single: 0.3610, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,937 - Iter: 71, Total Loss: 0.3609, loss_single: 0.3609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:48,972 - Iter: 72, Total Loss: 0.3608, loss_single: 0.3608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,007 - Iter: 73, Total Loss: 0.3607, loss_single: 0.3607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,043 - Iter: 74, Total Loss: 0.3606, loss_single: 0.3606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,078 - Iter: 75, Total Loss: 0.3605, loss_single: 0.3605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,114 - Iter: 76, Total Loss: 0.3603, loss_single: 0.3603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,149 - Iter: 77, Total Loss: 0.3602, loss_single: 0.3602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,187 - Iter: 78, Total Loss: 0.3601, loss_single: 0.3601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:00:49,222 - Iter: 79, Total Loss: 0.3600, loss_single: 0.3600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,258 - Iter: 80, Total Loss: 0.3599, loss_single: 0.3599, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,293 - Iter: 81, Total Loss: 0.3598, loss_single: 0.3598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,328 - Iter: 82, Total Loss: 0.3597, loss_single: 0.3597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,363 - Iter: 83, Total Loss: 0.3596, loss_single: 0.3596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:49,398 - Iter: 84, Total Loss: 0.3595, loss_single: 0.3595, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:49,433 - Iter: 85, Total Loss: 0.3594, loss_single: 0.3594, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,468 - Iter: 86, Total Loss: 0.3593, loss_single: 0.3593, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,504 - Iter: 87, Total Loss: 0.3591, loss_single: 0.3591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,539 - Iter: 88, Total Loss: 0.3590, loss_single: 0.3590, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,574 - Iter: 89, Total Loss: 0.3589, loss_single: 0.3589, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,609 - Iter: 90, Total Loss: 0.3588, loss_single: 0.3588, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,644 - Iter: 91, Total Loss: 0.3587, loss_single: 0.3587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,680 - Iter: 92, Total Loss: 0.3586, loss_single: 0.3586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:00:49,716 - Iter: 93, Total Loss: 0.3585, loss_single: 0.3585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,751 - Iter: 94, Total Loss: 0.3584, loss_single: 0.3584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,786 - Iter: 95, Total Loss: 0.3583, loss_single: 0.3583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,821 - Iter: 96, Total Loss: 0.3582, loss_single: 0.3582, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,856 - Iter: 97, Total Loss: 0.3581, loss_single: 0.3581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:49,891 - Iter: 98, Total Loss: 0.3580, loss_single: 0.3580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:00:49,926 - Iter: 99, Total Loss: 0.3578, loss_single: 0.3578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:49,961 - Iter: 100, Total Loss: 0.3577, loss_single: 0.3577, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:00:50,074 - Saving summary figures for iter 100 +2026-06-24 06:00:53,628 - ### Finished 100 iterations, averaged iter_t = 0.039006 with std = 0.040 ### +2026-06-24 06:00:53,628 - +2026-06-24 06:00:53,629 - ### The PtyRADSolver is finished in 9.204 sec ### +2026-06-24 06:00:53,629 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..41678975d140766fc632007df53db10c6be11cef Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/simulation_data3__sample_000024.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/simulation_data3__sample_000024.yaml new file mode 100644 index 0000000000000000000000000000000000000000..548598d581d2b9cfdcc91a4d2a16e121d340a726 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024/c30_small__simulation_data3__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_-27.2_phi12_196_C21_653_phi21_139_C23_-841_phi23_10_C30_4.92e+06_C32_-2.22e+03_phi32_25.8/simulation_data3__sample_000024.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 11.798361778259277 + probe_aberrations: + C10: -179.58599853515625 + C12: -27.20867347717285 + C21: 652.6014404296875 + C23: -840.5895385742188 + C30: 4919342.5 + C32: -2221.54345703125 + C34: -3709.86865234375 + C41: 460935.96875 + C43: -348589.5625 + C45: 89982.609375 + C50: 35151548.0 + C52: 10237128.0 + C54: 7789527.0 + C56: -15559670.0 + phi12: 195.5029771417545 + phi21: 139.02422485718913 + phi23: 10.029399404601595 + phi32: 256.9210080453713 + phi34: 32.23241742919346 + phi41: 94.4697056180912 + phi43: 44.010692747192344 + phi45: 317.6042608584565 + phi52: 254.7034915086783 + phi54: 275.0178674588869 + phi56: 70.79170738846143 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.35756543278694153 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000024_measurement.h5 + key: measurement + random_seed: 20261952 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000024 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000024 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/20260624_060144_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/20260624_060144_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..942efdeb3a905fef6b213bf71ce288241512e4ec --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/20260624_060144_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:01:42,543 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:01:42,543 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:01:42,543 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:01:42,543 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:01:42,543 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:01:42,543 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:01:42,543 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:01:42,543 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:01:42,543 - +2026-06-24 06:01:42,649 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:01:42,649 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:01:42,649 - Accelerator.num_process = 1 +2026-06-24 06:01:42,649 - Accelerator.mixed_precision = no +2026-06-24 06:01:42,672 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:01:42,672 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:01:42,672 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:01:42,672 - +2026-06-24 06:01:42,672 - ### System information ### +2026-06-24 06:01:42,672 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:01:42,672 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:01:42,672 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:01:42,672 - Machine: x86_64 +2026-06-24 06:01:42,672 - Processor: x86_64 +2026-06-24 06:01:42,672 - Available CPU cores: 8 +2026-06-24 06:01:42,672 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:01:42,673 - +2026-06-24 06:01:42,673 - ### GPU information ### +2026-06-24 06:01:42,673 - CUDA Available: True +2026-06-24 06:01:42,673 - CUDA Version: 13.0 +2026-06-24 06:01:42,673 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:01:42,673 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:01:42,673 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:01:42,673 - In addition, Triton does not directly support Windows. +2026-06-24 06:01:42,673 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:01:42,689 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:01:42,689 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:01:42,689 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:01:42,689 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:01:42,689 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:01:42,689 - +2026-06-24 06:01:42,689 - ### Python information ### +2026-06-24 06:01:42,691 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:01:42,691 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:01:42,691 - +2026-06-24 06:01:42,691 - ### Packages information ### +2026-06-24 06:01:42,691 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:01:42,692 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:01:42,693 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:01:42,693 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:01:42,694 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:01:42,694 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:01:42,694 - +2026-06-24 06:01:42,694 - ### Loading params file ### +2026-06-24 06:01:42,694 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000028.yaml +2026-06-24 06:01:42,700 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:01:42,701 - Success! Params file validated and defaults applied. +2026-06-24 06:01:42,701 - +2026-06-24 06:01:42,702 - ### Setting GPU Device ### +2026-06-24 06:01:42,702 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:01:42,702 - +2026-06-24 06:01:42,702 - Random seed: 20261956 provided by params file +2026-06-24 06:01:42,702 - ### Initializing Initializer ### +2026-06-24 06:01:42,702 - init_params are displayed below: +2026-06-24 06:01:42,702 - random_seed: 20261956 +2026-06-24 06:01:42,702 - probe_illum_type: electron +2026-06-24 06:01:42,702 - probe_kv: 100.0 +2026-06-24 06:01:42,702 - probe_conv_angle: 26.744834899902344 +2026-06-24 06:01:42,702 - probe_aberrations: {'C10': -429.517, 'C12': 47.328, 'phi12': 226.337, 'C21': 898.524, 'phi21': 86.621, 'C23': -715.563, 'phi23': 179.788, 'C30': 1176544.625, 'C32': 6834.764, 'phi32': 90.66, 'C34': 1699.099, 'phi34': 131.419, 'C41': -272778.531, 'phi41': 97.725, 'C43': -438022.688, 'phi43': 268.987, 'C45': -1752.137, 'phi45': 181.371, 'C50': -188327728.0, 'C52': -6071836.5, 'phi52': 182.233, 'C54': 7936817.5, 'phi54': 205.886, 'C56': 18532228.0, 'phi56': 139.275} +2026-06-24 06:01:42,702 - beam_kev: None +2026-06-24 06:01:42,702 - probe_dRn: None +2026-06-24 06:01:42,702 - probe_Rn: None +2026-06-24 06:01:42,702 - probe_D_H: None +2026-06-24 06:01:42,702 - probe_D_FZP: None +2026-06-24 06:01:42,702 - probe_Ls: None +2026-06-24 06:01:42,703 - meas_Npix: 128 +2026-06-24 06:01:42,703 - pos_N_scans: 256 +2026-06-24 06:01:42,703 - pos_N_scan_slow: 16 +2026-06-24 06:01:42,703 - pos_N_scan_fast: 16 +2026-06-24 06:01:42,703 - pos_scan_step_size: 0.3874207139015198 +2026-06-24 06:01:42,703 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:01:42,703 - probe_pmode_max: 6 +2026-06-24 06:01:42,703 - probe_pmode_init_pows: [0.02] +2026-06-24 06:01:42,703 - obj_omode_max: 1 +2026-06-24 06:01:42,703 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:01:42,703 - obj_Nlayer: 1 +2026-06-24 06:01:42,703 - obj_slice_thickness: 20.0 +2026-06-24 06:01:42,703 - simu_Npix: None +2026-06-24 06:01:42,703 - simu_match_mode: None +2026-06-24 06:01:42,703 - meas_permute: None +2026-06-24 06:01:42,703 - meas_reshape: [256, 128, 128] +2026-06-24 06:01:42,703 - meas_flipT: [0, 0, 0] +2026-06-24 06:01:42,703 - meas_crop: None +2026-06-24 06:01:42,703 - meas_pad: None +2026-06-24 06:01:42,703 - meas_resample: None +2026-06-24 06:01:42,703 - meas_add_source_size: None +2026-06-24 06:01:42,703 - meas_add_detector_blur: None +2026-06-24 06:01:42,703 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:01:42,703 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:01:42,703 - meas_add_poisson_noise: None +2026-06-24 06:01:42,703 - meas_export: None +2026-06-24 06:01:42,703 - probe_permute: None +2026-06-24 06:01:42,703 - probe_z_shift: None +2026-06-24 06:01:42,703 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:01:42,703 - pos_scan_flipT: None +2026-06-24 06:01:42,703 - pos_scan_affine: None +2026-06-24 06:01:42,703 - pos_scan_rand_std: 0.15 +2026-06-24 06:01:42,703 - obj_z_crop: None +2026-06-24 06:01:42,703 - obj_z_pad: None +2026-06-24 06:01:42,703 - obj_z_resample: None +2026-06-24 06:01:42,703 - meas_source: file +2026-06-24 06:01:42,703 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000028_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:01:42,703 - probe_source: simu +2026-06-24 06:01:42,703 - probe_params: None +2026-06-24 06:01:42,703 - pos_source: simu +2026-06-24 06:01:42,703 - pos_params: None +2026-06-24 06:01:42,704 - obj_source: simu +2026-06-24 06:01:42,704 - obj_params: None +2026-06-24 06:01:42,704 - tilt_source: simu +2026-06-24 06:01:42,704 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:01:42,704 - +2026-06-24 06:01:42,704 - ### Initializing cache ### +2026-06-24 06:01:42,704 - use_cached_obj = False +2026-06-24 06:01:42,704 - use_cached_probe = False +2026-06-24 06:01:42,704 - use_cached_pos = False +2026-06-24 06:01:42,704 - +2026-06-24 06:01:42,704 - ### Initializing measurements ### +2026-06-24 06:01:42,704 - Loading measurements from source = 'file' +2026-06-24 06:01:42,704 - Detected measurement file type = '.h5' +2026-06-24 06:01:42,776 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:01:42,776 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:01:42,778 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0016) +2026-06-24 06:01:42,778 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:01:42,778 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:01:42,780 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:01:42,780 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:01:42,780 - Normalizing by max of the 2D mean pattern intensity: 0.00096400909 +2026-06-24 06:01:42,781 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:01:42,782 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0638, 1.6575) +2026-06-24 06:01:42,783 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:01:42,784 - Pattern total int. statistics (min, mean, max) = (1030.0771, 1045.1864, 1059.8518), with min/max = 97.2% +2026-06-24 06:01:42,785 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0638, 1.6575) +2026-06-24 06:01:42,785 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:01:42,785 - +2026-06-24 06:01:42,785 - ### Setting up calibration ### +2026-06-24 06:01:42,785 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:01:42,785 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:01:42,786 - Radius of fitted bright field disk (RBF) = 18.23 px with meas_Npix = 128 +2026-06-24 06:01:42,786 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2848 +2026-06-24 06:01:42,786 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:01:42,786 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:01:43,013 - Initial guess: center=(63.62, 63.62), radius=18.23, Gaussian blur std=0.50 +2026-06-24 06:01:43,026 - Final fit: center=(63.62, 63.62), radius=18.23, Gaussian blur std=0.65 +2026-06-24 06:01:43,026 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 18.50 px with Npix = 128 +2026-06-24 06:01:43,026 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:01:43,026 - +2026-06-24 06:01:43,026 - ### Setting init_variables dict ### +2026-06-24 06:01:43,026 - Derived values given input init_params: +2026-06-24 06:01:43,026 - kv = 100.0 kV +2026-06-24 06:01:43,026 - wavelength = 0.0370 Ang +2026-06-24 06:01:43,026 - conv_angle = 26.744834899902344 mrad +2026-06-24 06:01:43,026 - Npix = 128 px +2026-06-24 06:01:43,026 - dk = 0.0391 Ang^-1 +2026-06-24 06:01:43,026 - kMax = 2.5000 Ang^-1 +2026-06-24 06:01:43,026 - da = 1.4459 mrad +2026-06-24 06:01:43,026 - angleMax = 92.5359 mrad +2026-06-24 06:01:43,026 - RBF = 18.4974 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:01:43,026 - n_alpha = 3.4600 (# conv_angle) +2026-06-24 06:01:43,026 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:01:43,026 - Rayleigh-limited resolution = 0.8442 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:01:43,026 - Real space probe extent = 25.6000 Ang +2026-06-24 06:01:43,026 - +2026-06-24 06:01:43,026 - ### Initializing probe ### +2026-06-24 06:01:43,026 - Loading probe from source = 'simu' +2026-06-24 06:01:43,026 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:01:43,027 - Start simulating STEM probe +2026-06-24 06:01:43,027 - kv = 100.0 kV +2026-06-24 06:01:43,027 - wavelength = 0.0370 Ang +2026-06-24 06:01:43,027 - conv_angle = 26.744834899902344 mrad +2026-06-24 06:01:43,027 - Npix = 128 px +2026-06-24 06:01:43,027 - dk = 0.0391 Ang^-1 +2026-06-24 06:01:43,027 - kMax = 2.5000 Ang^-1 +2026-06-24 06:01:43,027 - alpha_max = 92.5359 mrad +2026-06-24 06:01:43,027 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:01:43,027 - Rayleigh-limited resolution = 0.8442 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:01:43,027 - Real space probe extent = 25.6000 Ang +2026-06-24 06:01:43,027 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:01:43,027 - ------------------------------------------------------------------------------------- +2026-06-24 06:01:43,027 - C1,0 C1 -429.5170 - Defocus (C10 = -df) +2026-06-24 06:01:43,027 - C1,2 A1 47.3280 226.34 2-fold astigmatism +2026-06-24 06:01:43,027 - C2,1 3*B2 898.5240 86.62 Axial coma +2026-06-24 06:01:43,027 - C2,3 A2 -715.5630 179.79 3-fold astigmatism +2026-06-24 06:01:43,027 - C3,0 C3 1176544.6250 - Spherical aberration +2026-06-24 06:01:43,027 - C3,2 4*S3 6834.7640 90.66 Axial star aberration +2026-06-24 06:01:43,027 - C3,4 A3 1699.0990 131.42 4-fold astigmatism +2026-06-24 06:01:43,027 - C4,1 4*B4 -272778.5310 97.72 Axial coma(4th) +2026-06-24 06:01:43,027 - C4,3 4*D4 -438022.6880 268.99 3-lobe aberration +2026-06-24 06:01:43,027 - C4,5 A4 -1752.1370 181.37 5-fold astigmatism +2026-06-24 06:01:43,027 - C5,0 C5 -188327728.0000 - Spherical aberration (5th) +2026-06-24 06:01:43,027 - C5,2 6*S5 -6071836.5000 182.23 Axial star aberration(5th) +2026-06-24 06:01:43,027 - C5,4 6*R5 7936817.5000 205.89 4-lobe aberration +2026-06-24 06:01:43,027 - C5,6 A5 18532228.0000 139.28 6-fold astigmatism +2026-06-24 06:01:43,031 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:01:43,031 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:01:43,031 - Creating 5 new probe modes from the major mode +2026-06-24 06:01:43,031 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:01:43,198 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:01:43,200 - Orthogonalizing 6 pmodes +2026-06-24 06:01:43,203 - Sorting 6 pmodes by their intensities +2026-06-24 06:01:43,203 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:01:43,204 - sum(|probe_data|**2) = 1045.19, while meas_total_ints (min, mean, max) = (1030.0771, 1045.1864, 1059.8518) +2026-06-24 06:01:43,204 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:01:43,204 - +2026-06-24 06:01:43,204 - ### Initializing probe positions ### +2026-06-24 06:01:43,204 - Loading probe positions from source = 'simu' +2026-06-24 06:01:43,204 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:01:43,204 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3874, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:01:43,204 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:01:43,206 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:01:43,206 - crop_pos 1st and last px coords (y,x) = ([16, 16], [45, 44]) +2026-06-24 06:01:43,206 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 06:01:43,206 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:01:43,206 - +2026-06-24 06:01:43,206 - ### Initializing object ### +2026-06-24 06:01:43,206 - Loading object from source = 'simu' +2026-06-24 06:01:43,207 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:01:43,208 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:01:43,208 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 189, 189) +2026-06-24 06:01:43,208 - object extent (Z, Y, X) (Ang) = [20. 37.8 37.8] +2026-06-24 06:01:43,208 - +2026-06-24 06:01:43,208 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:01:43,208 - omode_occu (omode) = float32, (1,) +2026-06-24 06:01:43,208 - +2026-06-24 06:01:43,208 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:01:43,208 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:01:43,209 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:01:43,209 - +2026-06-24 06:01:43,209 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:01:43,209 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:01:43,209 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:01:43,209 - +2026-06-24 06:01:43,209 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:01:43,209 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:01:43,209 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:01:43,209 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:01:43,209 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:01:43,209 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (189, 189). +2026-06-24 06:01:43,210 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:01:43,210 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:01:43,210 - +2026-06-24 06:01:43,210 - ### Collecting reconstruction provenance ### +2026-06-24 06:01:43,210 - Reconstruction provenance is collected and initialized. +2026-06-24 06:01:43,210 - +2026-06-24 06:01:43,210 - ### Initializing loss function ### +2026-06-24 06:01:43,210 - Active loss types: +2026-06-24 06:01:43,210 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:01:43,210 - +2026-06-24 06:01:43,210 - ### Initializing constraint function ### +2026-06-24 06:01:43,210 - Active constraint types: +2026-06-24 06:01:43,210 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:01:43,210 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:01:43,210 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:01:43,210 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:01:43,210 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:01:43,210 - +2026-06-24 06:01:43,210 - ### Done initializing PtyRADSolver ### +2026-06-24 06:01:43,210 - +2026-06-24 06:01:43,333 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:01:43,333 - +2026-06-24 06:01:43,334 - ### Initializing PtychoModel model ### +2026-06-24 06:01:43,405 - ### PtychoModel optimizable variables ### +2026-06-24 06:01:43,405 - obja : torch.Size([1, 1, 189, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:43,405 - objp : torch.Size([1, 1, 189, 189]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:43,405 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:01:43,405 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:01:43,405 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:01:43,405 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:43,405 - +2026-06-24 06:01:43,405 - ### Optimizable variables statitsics ### +2026-06-24 06:01:43,405 - Total measurement values : 4,194,304 +2026-06-24 06:01:43,405 - Total optimizing variables: 268,562 +2026-06-24 06:01:43,406 - Overdetermined ratio : 15.62 +2026-06-24 06:01:43,406 - +2026-06-24 06:01:43,406 - ### Model behavior ### +2026-06-24 06:01:43,406 - Tilt propagator : False +2026-06-24 06:01:43,406 - Change slice thickness : False +2026-06-24 06:01:43,406 - Detector blur : False +2026-06-24 06:01:43,406 - Preload data : True +2026-06-24 06:01:43,406 - On-the-fly meas padding : False +2026-06-24 06:01:43,406 - On-the-fly meas resample : False +2026-06-24 06:01:43,406 - On-the-fly simu match mode: None +2026-06-24 06:01:43,406 - +2026-06-24 06:01:43,447 - ### Done initializing PtychoModel model ### +2026-06-24 06:01:43,447 - +2026-06-24 06:01:43,447 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:01:43,447 - +2026-06-24 06:01:43,447 - ### Generating indices, batches, and output_path ### +2026-06-24 06:01:43,449 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:01:43,449 - Selecting indices with the 'full' mode +2026-06-24 06:01:43,906 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:01:43,979 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:01:43,979 - Original recon_dir_affixes = ['default'] +2026-06-24 06:01:43,979 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:01:43,985 - Path corrected for compatibility: +2026-06-24 06:01:43,985 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6.83e+03_phi32_90.7_C34_1.7e+03_phi34_131_C41_-2.73e+05_phi41_97.7_C43_-4.38e+05_phi43_269_C45_-1.75e+03_phi45_181_C50_-1.88e+08_C52_-6.07e+06_phi52_182_C54_7.94e+06_phi54_206_C56_1.85e+07_phi56_139 +2026-06-24 06:01:43,985 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139 +2026-06-24 06:01:43,986 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139' is generated! +2026-06-24 06:01:44,128 - +2026-06-24 06:01:44,129 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/20260624_060144_ptyrad_log.txt ### +2026-06-24 06:01:44,129 - +2026-06-24 06:01:44,130 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:01:44,130 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:01:44,130 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:01:45,312 - Iter: 1, Total Loss: 0.5763, loss_single: 0.5763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:01:45,349 - Iter: 2, Total Loss: 0.5572, loss_single: 0.5572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:01:45,384 - Iter: 3, Total Loss: 0.5410, loss_single: 0.5410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,419 - Iter: 4, Total Loss: 0.5274, loss_single: 0.5274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,454 - Iter: 5, Total Loss: 0.5149, loss_single: 0.5149, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,489 - Iter: 6, Total Loss: 0.5020, loss_single: 0.5020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:45,524 - Iter: 7, Total Loss: 0.4896, loss_single: 0.4896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:45,559 - Iter: 8, Total Loss: 0.4776, loss_single: 0.4776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:45,594 - Iter: 9, Total Loss: 0.4666, loss_single: 0.4666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,629 - Iter: 10, Total Loss: 0.4564, loss_single: 0.4564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,665 - Iter: 11, Total Loss: 0.4465, loss_single: 0.4465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:01:45,701 - Iter: 12, Total Loss: 0.4385, loss_single: 0.4385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,736 - Iter: 13, Total Loss: 0.4332, loss_single: 0.4332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,771 - Iter: 14, Total Loss: 0.4282, loss_single: 0.4282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:45,806 - Iter: 15, Total Loss: 0.4234, loss_single: 0.4234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,841 - Iter: 16, Total Loss: 0.4192, loss_single: 0.4192, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,876 - Iter: 17, Total Loss: 0.4145, loss_single: 0.4145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,911 - Iter: 18, Total Loss: 0.4100, loss_single: 0.4100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:45,946 - Iter: 19, Total Loss: 0.4064, loss_single: 0.4064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:45,981 - Iter: 20, Total Loss: 0.4031, loss_single: 0.4031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,016 - Iter: 21, Total Loss: 0.3996, loss_single: 0.3996, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,051 - Iter: 22, Total Loss: 0.3967, loss_single: 0.3967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,086 - Iter: 23, Total Loss: 0.3943, loss_single: 0.3943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,121 - Iter: 24, Total Loss: 0.3914, loss_single: 0.3914, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,156 - Iter: 25, Total Loss: 0.3887, loss_single: 0.3887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,191 - Iter: 26, Total Loss: 0.3866, loss_single: 0.3866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,226 - Iter: 27, Total Loss: 0.3848, loss_single: 0.3848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,261 - Iter: 28, Total Loss: 0.3829, loss_single: 0.3829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,296 - Iter: 29, Total Loss: 0.3814, loss_single: 0.3814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,332 - Iter: 30, Total Loss: 0.3803, loss_single: 0.3803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,367 - Iter: 31, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,402 - Iter: 32, Total Loss: 0.3781, loss_single: 0.3781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,437 - Iter: 33, Total Loss: 0.3774, loss_single: 0.3774, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,472 - Iter: 34, Total Loss: 0.3768, loss_single: 0.3768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,507 - Iter: 35, Total Loss: 0.3763, loss_single: 0.3763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,542 - Iter: 36, Total Loss: 0.3759, loss_single: 0.3759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,577 - Iter: 37, Total Loss: 0.3755, loss_single: 0.3755, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,612 - Iter: 38, Total Loss: 0.3752, loss_single: 0.3752, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,647 - Iter: 39, Total Loss: 0.3748, loss_single: 0.3748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,682 - Iter: 40, Total Loss: 0.3745, loss_single: 0.3745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,719 - Iter: 41, Total Loss: 0.3741, loss_single: 0.3741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,754 - Iter: 42, Total Loss: 0.3737, loss_single: 0.3737, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,788 - Iter: 43, Total Loss: 0.3734, loss_single: 0.3734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:46,824 - Iter: 44, Total Loss: 0.3731, loss_single: 0.3731, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,859 - Iter: 45, Total Loss: 0.3729, loss_single: 0.3729, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,894 - Iter: 46, Total Loss: 0.3727, loss_single: 0.3727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,929 - Iter: 47, Total Loss: 0.3724, loss_single: 0.3724, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,964 - Iter: 48, Total Loss: 0.3722, loss_single: 0.3722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:46,999 - Iter: 49, Total Loss: 0.3721, loss_single: 0.3721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,034 - Iter: 50, Total Loss: 0.3719, loss_single: 0.3719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,069 - Iter: 51, Total Loss: 0.3718, loss_single: 0.3718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,104 - Iter: 52, Total Loss: 0.3716, loss_single: 0.3716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,139 - Iter: 53, Total Loss: 0.3715, loss_single: 0.3715, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,174 - Iter: 54, Total Loss: 0.3714, loss_single: 0.3714, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,209 - Iter: 55, Total Loss: 0.3713, loss_single: 0.3713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:47,251 - Iter: 56, Total Loss: 0.3712, loss_single: 0.3712, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,285 - Iter: 57, Total Loss: 0.3711, loss_single: 0.3711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:47,320 - Iter: 58, Total Loss: 0.3711, loss_single: 0.3711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,355 - Iter: 59, Total Loss: 0.3710, loss_single: 0.3710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,390 - Iter: 60, Total Loss: 0.3710, loss_single: 0.3710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,426 - Iter: 61, Total Loss: 0.3709, loss_single: 0.3709, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,461 - Iter: 62, Total Loss: 0.3709, loss_single: 0.3709, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,496 - Iter: 63, Total Loss: 0.3708, loss_single: 0.3708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,531 - Iter: 64, Total Loss: 0.3708, loss_single: 0.3708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,566 - Iter: 65, Total Loss: 0.3707, loss_single: 0.3707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:47,601 - Iter: 66, Total Loss: 0.3707, loss_single: 0.3707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,636 - Iter: 67, Total Loss: 0.3707, loss_single: 0.3707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:47,671 - Iter: 68, Total Loss: 0.3706, loss_single: 0.3706, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,706 - Iter: 69, Total Loss: 0.3706, loss_single: 0.3706, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,741 - Iter: 70, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,777 - Iter: 71, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,811 - Iter: 72, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:47,846 - Iter: 73, Total Loss: 0.3704, loss_single: 0.3704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,882 - Iter: 74, Total Loss: 0.3704, loss_single: 0.3704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:47,916 - Iter: 75, Total Loss: 0.3703, loss_single: 0.3703, loss_poissn: 0.0000, loss_pacbed: 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0.3695, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:48,760 - Iter: 99, Total Loss: 0.3695, loss_single: 0.3695, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:48,795 - Iter: 100, Total Loss: 0.3695, loss_single: 0.3695, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:01:48,904 - Saving summary figures for iter 100 +2026-06-24 06:01:52,605 - ### Finished 100 iterations, averaged iter_t = 0.038685 with std = 0.040 ### +2026-06-24 06:01:52,606 - +2026-06-24 06:01:52,606 - ### The PtyRADSolver is finished in 9.273 sec ### +2026-06-24 06:01:52,606 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/simulation_data3__sample_000028.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 26.744834899902344 + probe_aberrations: + C10: -429.5165710449219 + C12: 47.32832336425781 + C21: 898.5243530273438 + C23: -715.5634765625 + C30: 1176544.625 + C32: 6834.763671875 + C34: 1699.099365234375 + C41: -272778.53125 + C43: -438022.6875 + C45: -1752.13671875 + C50: -188327728.0 + C52: -6071836.5 + C54: 7936817.5 + C56: 18532228.0 + phi12: 226.33652743269977 + phi21: 86.6209166767761 + phi23: 179.78758612576894 + phi32: 90.66035202362417 + phi34: 131.41928732962182 + phi41: 97.72455030479072 + phi43: 268.98722023311586 + phi45: 181.37078299424286 + phi52: 182.23271188636346 + phi54: 205.88587554817107 + phi56: 139.27470155443183 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3874207139015198 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000028_measurement.h5 + key: measurement + random_seed: 20261956 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000028 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000028/c30_small__simulation_data3__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-430_C12_47.3_phi12_226_C21_899_phi21_86.6_C23_-716_phi23_180_C30_1.18e+06_C32_6..85e+07_phi56_139/summary_convergence_iter0100.png new file mode 100644 index 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sha256:af47d42b7e45a28c3ddf4d62777aa51f38645f77d76b192c4f22796cacc876ec +size 45946 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/20260624_060158_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/20260624_060158_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..65f8f1597b7f101e38362d4133505823f4204846 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/20260624_060158_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:01:57,158 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:01:57,158 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:01:57,158 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:01:57,158 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:01:57,158 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:01:57,158 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:01:57,158 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:01:57,158 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:01:57,158 - +2026-06-24 06:01:57,264 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:01:57,264 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:01:57,264 - Accelerator.num_process = 1 +2026-06-24 06:01:57,264 - Accelerator.mixed_precision = no +2026-06-24 06:01:57,275 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:01:57,275 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:01:57,275 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:01:57,275 - +2026-06-24 06:01:57,275 - ### System information ### +2026-06-24 06:01:57,275 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:01:57,275 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:01:57,275 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:01:57,275 - Machine: x86_64 +2026-06-24 06:01:57,275 - Processor: x86_64 +2026-06-24 06:01:57,275 - Available CPU cores: 8 +2026-06-24 06:01:57,275 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:01:57,275 - +2026-06-24 06:01:57,275 - ### GPU information ### +2026-06-24 06:01:57,275 - CUDA Available: True +2026-06-24 06:01:57,275 - CUDA Version: 13.0 +2026-06-24 06:01:57,276 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:01:57,276 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:01:57,276 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:01:57,276 - In addition, Triton does not directly support Windows. +2026-06-24 06:01:57,276 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:01:57,291 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:01:57,291 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:01:57,291 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:01:57,291 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:01:57,291 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:01:57,291 - +2026-06-24 06:01:57,291 - ### Python information ### +2026-06-24 06:01:57,293 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:01:57,293 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:01:57,293 - +2026-06-24 06:01:57,293 - ### Packages information ### +2026-06-24 06:01:57,294 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:01:57,295 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:01:57,295 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:01:57,296 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:01:57,296 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:01:57,297 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:01:57,297 - +2026-06-24 06:01:57,297 - ### Loading params file ### +2026-06-24 06:01:57,297 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000029.yaml +2026-06-24 06:01:57,303 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:01:57,304 - Success! Params file validated and defaults applied. +2026-06-24 06:01:57,304 - +2026-06-24 06:01:57,304 - ### Setting GPU Device ### +2026-06-24 06:01:57,304 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:01:57,304 - +2026-06-24 06:01:57,304 - Random seed: 20261957 provided by params file +2026-06-24 06:01:57,305 - ### Initializing Initializer ### +2026-06-24 06:01:57,305 - init_params are displayed below: +2026-06-24 06:01:57,305 - random_seed: 20261957 +2026-06-24 06:01:57,305 - probe_illum_type: electron +2026-06-24 06:01:57,305 - probe_kv: 120.0 +2026-06-24 06:01:57,305 - probe_conv_angle: 13.020979881286621 +2026-06-24 06:01:57,305 - probe_aberrations: {'C10': -198.19, 'C12': -4.805, 'phi12': 305.636, 'C21': 384.14, 'phi21': 151.098, 'C23': 360.983, 'phi23': 94.092, 'C30': 4119662.75, 'C32': 8797.676, 'phi32': 3.968, 'C34': -398.148, 'phi34': 65.553, 'C41': -465696.719, 'phi41': 168.986, 'C43': 385672.375, 'phi43': 162.992, 'C45': 130449.492, 'phi45': 100.989, 'C50': 476960640.0, 'C52': -13821542.0, 'phi52': 7.503, 'C54': 7284448.0, 'phi54': 159.105, 'C56': -13540188.0, 'phi56': 171.053} +2026-06-24 06:01:57,305 - beam_kev: None +2026-06-24 06:01:57,305 - probe_dRn: None +2026-06-24 06:01:57,305 - probe_Rn: None +2026-06-24 06:01:57,305 - probe_D_H: None +2026-06-24 06:01:57,305 - probe_D_FZP: None +2026-06-24 06:01:57,305 - probe_Ls: None +2026-06-24 06:01:57,305 - meas_Npix: 128 +2026-06-24 06:01:57,305 - pos_N_scans: 256 +2026-06-24 06:01:57,305 - pos_N_scan_slow: 16 +2026-06-24 06:01:57,305 - pos_N_scan_fast: 16 +2026-06-24 06:01:57,305 - pos_scan_step_size: 0.3369060456752777 +2026-06-24 06:01:57,305 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:01:57,305 - probe_pmode_max: 6 +2026-06-24 06:01:57,305 - probe_pmode_init_pows: [0.02] +2026-06-24 06:01:57,305 - obj_omode_max: 1 +2026-06-24 06:01:57,305 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:01:57,306 - obj_Nlayer: 1 +2026-06-24 06:01:57,306 - obj_slice_thickness: 20.0 +2026-06-24 06:01:57,306 - simu_Npix: None +2026-06-24 06:01:57,306 - simu_match_mode: None +2026-06-24 06:01:57,306 - meas_permute: None +2026-06-24 06:01:57,306 - meas_reshape: [256, 128, 128] +2026-06-24 06:01:57,306 - meas_flipT: [0, 0, 0] +2026-06-24 06:01:57,306 - meas_crop: None +2026-06-24 06:01:57,306 - meas_pad: None +2026-06-24 06:01:57,306 - meas_resample: None +2026-06-24 06:01:57,306 - meas_add_source_size: None +2026-06-24 06:01:57,306 - meas_add_detector_blur: None +2026-06-24 06:01:57,306 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:01:57,306 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:01:57,306 - meas_add_poisson_noise: None +2026-06-24 06:01:57,306 - meas_export: None +2026-06-24 06:01:57,306 - probe_permute: None +2026-06-24 06:01:57,306 - probe_z_shift: None +2026-06-24 06:01:57,306 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:01:57,306 - pos_scan_flipT: None +2026-06-24 06:01:57,306 - pos_scan_affine: None +2026-06-24 06:01:57,306 - pos_scan_rand_std: 0.15 +2026-06-24 06:01:57,306 - obj_z_crop: None +2026-06-24 06:01:57,306 - obj_z_pad: None +2026-06-24 06:01:57,306 - obj_z_resample: None +2026-06-24 06:01:57,306 - meas_source: file +2026-06-24 06:01:57,306 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000029_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:01:57,306 - probe_source: simu +2026-06-24 06:01:57,306 - probe_params: None +2026-06-24 06:01:57,306 - pos_source: simu +2026-06-24 06:01:57,306 - pos_params: None +2026-06-24 06:01:57,306 - obj_source: simu +2026-06-24 06:01:57,306 - obj_params: None +2026-06-24 06:01:57,306 - tilt_source: simu +2026-06-24 06:01:57,306 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:01:57,306 - +2026-06-24 06:01:57,306 - ### Initializing cache ### +2026-06-24 06:01:57,306 - use_cached_obj = False +2026-06-24 06:01:57,306 - use_cached_probe = False +2026-06-24 06:01:57,307 - use_cached_pos = False +2026-06-24 06:01:57,307 - +2026-06-24 06:01:57,307 - ### Initializing measurements ### +2026-06-24 06:01:57,307 - Loading measurements from source = 'file' +2026-06-24 06:01:57,307 - Detected measurement file type = '.h5' +2026-06-24 06:01:57,376 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:01:57,376 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:01:57,378 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0049) +2026-06-24 06:01:57,378 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:01:57,378 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:01:57,380 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:01:57,380 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:01:57,380 - Normalizing by max of the 2D mean pattern intensity: 0.0032402643 +2026-06-24 06:01:57,381 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:01:57,382 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0189, 1.5134) +2026-06-24 06:01:57,382 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:01:57,384 - Pattern total int. statistics (min, mean, max) = (304.6801, 309.2159, 313.1404), with min/max = 97.3% +2026-06-24 06:01:57,385 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0189, 1.5134) +2026-06-24 06:01:57,385 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:01:57,385 - +2026-06-24 06:01:57,385 - ### Setting up calibration ### +2026-06-24 06:01:57,385 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:01:57,385 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:01:57,385 - Radius of fitted bright field disk (RBF) = 9.87 px with meas_Npix = 128 +2026-06-24 06:01:57,385 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1542 +2026-06-24 06:01:57,385 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:01:57,385 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:01:57,616 - Initial guess: center=(63.63, 63.62), radius=9.87, Gaussian blur std=0.50 +2026-06-24 06:01:57,624 - Final fit: center=(63.63, 63.62), radius=9.87, Gaussian blur std=0.54 +2026-06-24 06:01:57,624 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.95 px with Npix = 128 +2026-06-24 06:01:57,624 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:01:57,624 - +2026-06-24 06:01:57,624 - ### Setting init_variables dict ### +2026-06-24 06:01:57,624 - Derived values given input init_params: +2026-06-24 06:01:57,624 - kv = 120.0 kV +2026-06-24 06:01:57,624 - wavelength = 0.0335 Ang +2026-06-24 06:01:57,624 - conv_angle = 13.020979881286621 mrad +2026-06-24 06:01:57,624 - Npix = 128 px +2026-06-24 06:01:57,624 - dk = 0.0391 Ang^-1 +2026-06-24 06:01:57,624 - kMax = 2.5000 Ang^-1 +2026-06-24 06:01:57,624 - da = 1.3083 mrad +2026-06-24 06:01:57,624 - angleMax = 83.7304 mrad +2026-06-24 06:01:57,624 - RBF = 9.9527 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:01:57,624 - n_alpha = 6.4304 (# conv_angle) +2026-06-24 06:01:57,624 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:01:57,624 - Rayleigh-limited resolution = 1.5690 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:01:57,624 - Real space probe extent = 25.6000 Ang +2026-06-24 06:01:57,624 - +2026-06-24 06:01:57,625 - ### Initializing probe ### +2026-06-24 06:01:57,625 - Loading probe from source = 'simu' +2026-06-24 06:01:57,625 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:01:57,625 - Start simulating STEM probe +2026-06-24 06:01:57,625 - kv = 120.0 kV +2026-06-24 06:01:57,625 - wavelength = 0.0335 Ang +2026-06-24 06:01:57,625 - conv_angle = 13.020979881286621 mrad +2026-06-24 06:01:57,625 - Npix = 128 px +2026-06-24 06:01:57,625 - dk = 0.0391 Ang^-1 +2026-06-24 06:01:57,625 - kMax = 2.5000 Ang^-1 +2026-06-24 06:01:57,625 - alpha_max = 83.7304 mrad +2026-06-24 06:01:57,625 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:01:57,625 - Rayleigh-limited resolution = 1.5690 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:01:57,625 - Real space probe extent = 25.6000 Ang +2026-06-24 06:01:57,625 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:01:57,625 - ------------------------------------------------------------------------------------ +2026-06-24 06:01:57,625 - C1,0 C1 -198.1900 - Defocus (C10 = -df) +2026-06-24 06:01:57,625 - C1,2 A1 -4.8050 305.64 2-fold astigmatism +2026-06-24 06:01:57,625 - C2,1 3*B2 384.1400 151.10 Axial coma +2026-06-24 06:01:57,625 - C2,3 A2 360.9830 94.09 3-fold astigmatism +2026-06-24 06:01:57,625 - C3,0 C3 4119662.7500 - Spherical aberration +2026-06-24 06:01:57,625 - C3,2 4*S3 8797.6760 3.97 Axial star aberration +2026-06-24 06:01:57,625 - C3,4 A3 -398.1480 65.55 4-fold astigmatism +2026-06-24 06:01:57,625 - C4,1 4*B4 -465696.7190 168.99 Axial coma(4th) +2026-06-24 06:01:57,625 - C4,3 4*D4 385672.3750 162.99 3-lobe aberration +2026-06-24 06:01:57,625 - C4,5 A4 130449.4920 100.99 5-fold astigmatism +2026-06-24 06:01:57,626 - C5,0 C5 476960640.0000 - Spherical aberration (5th) +2026-06-24 06:01:57,626 - C5,2 6*S5 -13821542.0000 7.50 Axial star aberration(5th) +2026-06-24 06:01:57,626 - C5,4 6*R5 7284448.0000 159.10 4-lobe aberration +2026-06-24 06:01:57,626 - C5,6 A5 -13540188.0000 171.05 6-fold astigmatism +2026-06-24 06:01:57,629 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:01:57,629 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:01:57,629 - Creating 5 new probe modes from the major mode +2026-06-24 06:01:57,629 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:01:57,757 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:01:57,759 - Orthogonalizing 6 pmodes +2026-06-24 06:01:57,762 - Sorting 6 pmodes by their intensities +2026-06-24 06:01:57,762 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:01:57,763 - sum(|probe_data|**2) = 309.22, while meas_total_ints (min, mean, max) = (304.6801, 309.2159, 313.1404) +2026-06-24 06:01:57,763 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:01:57,763 - +2026-06-24 06:01:57,763 - ### Initializing probe positions ### +2026-06-24 06:01:57,763 - Loading probe positions from source = 'simu' +2026-06-24 06:01:57,763 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:01:57,763 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3369, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:01:57,763 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:01:57,765 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:01:57,765 - crop_pos 1st and last px coords (y,x) = ([15, 15], [41, 40]) +2026-06-24 06:01:57,766 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:01:57,766 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:01:57,766 - +2026-06-24 06:01:57,766 - ### Initializing object ### +2026-06-24 06:01:57,766 - Loading object from source = 'simu' +2026-06-24 06:01:57,766 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:01:57,767 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:01:57,767 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 184, 184) +2026-06-24 06:01:57,767 - object extent (Z, Y, X) (Ang) = [20. 36.8 36.8] +2026-06-24 06:01:57,767 - +2026-06-24 06:01:57,767 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:01:57,768 - omode_occu (omode) = float32, (1,) +2026-06-24 06:01:57,768 - +2026-06-24 06:01:57,768 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:01:57,768 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:01:57,768 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:01:57,768 - +2026-06-24 06:01:57,768 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:01:57,768 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:01:57,768 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:01:57,768 - +2026-06-24 06:01:57,769 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:01:57,769 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:01:57,769 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:01:57,769 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:01:57,769 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:01:57,769 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (184, 184). +2026-06-24 06:01:57,769 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:01:57,769 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:01:57,769 - +2026-06-24 06:01:57,769 - ### Collecting reconstruction provenance ### +2026-06-24 06:01:57,769 - Reconstruction provenance is collected and initialized. +2026-06-24 06:01:57,769 - +2026-06-24 06:01:57,769 - ### Initializing loss function ### +2026-06-24 06:01:57,769 - Active loss types: +2026-06-24 06:01:57,769 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:01:57,769 - +2026-06-24 06:01:57,769 - ### Initializing constraint function ### +2026-06-24 06:01:57,769 - Active constraint types: +2026-06-24 06:01:57,769 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:01:57,769 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:01:57,769 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:01:57,770 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:01:57,770 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:01:57,770 - +2026-06-24 06:01:57,770 - ### Done initializing PtyRADSolver ### +2026-06-24 06:01:57,770 - +2026-06-24 06:01:57,893 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:01:57,893 - +2026-06-24 06:01:57,893 - ### Initializing PtychoModel model ### +2026-06-24 06:01:57,978 - ### PtychoModel optimizable variables ### +2026-06-24 06:01:57,978 - obja : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:57,978 - objp : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:57,978 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:01:57,978 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:01:57,978 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:01:57,979 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:01:57,979 - +2026-06-24 06:01:57,979 - ### Optimizable variables statitsics ### +2026-06-24 06:01:57,979 - Total measurement values : 4,194,304 +2026-06-24 06:01:57,979 - Total optimizing variables: 264,832 +2026-06-24 06:01:57,979 - Overdetermined ratio : 15.84 +2026-06-24 06:01:57,979 - +2026-06-24 06:01:57,979 - ### Model behavior ### +2026-06-24 06:01:57,979 - Tilt propagator : False +2026-06-24 06:01:57,979 - Change slice thickness : False +2026-06-24 06:01:57,979 - Detector blur : False +2026-06-24 06:01:57,979 - Preload data : True +2026-06-24 06:01:57,979 - On-the-fly meas padding : False +2026-06-24 06:01:57,979 - On-the-fly meas resample : False +2026-06-24 06:01:57,979 - On-the-fly simu match mode: None +2026-06-24 06:01:57,979 - +2026-06-24 06:01:58,020 - ### Done initializing PtychoModel model ### +2026-06-24 06:01:58,020 - +2026-06-24 06:01:58,020 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:01:58,020 - +2026-06-24 06:01:58,020 - ### Generating indices, batches, and output_path ### +2026-06-24 06:01:58,022 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:01:58,022 - Selecting indices with the 'full' mode +2026-06-24 06:01:58,479 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:01:58,552 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:01:58,552 - Original recon_dir_affixes = ['default'] +2026-06-24 06:01:58,552 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:01:58,558 - Path corrected for compatibility: +2026-06-24 06:01:58,558 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8e+03_phi32_3.97_C34_-398_phi34_65.6_C41_-4.66e+05_phi41_169_C43_3.86e+05_phi43_163_C45_1.3e+05_phi45_101_C50_4.77e+08_C52_-1.38e+07_phi52_7.5_C54_7.28e+06_phi54_159_C56_-1.35e+07_phi56_171 +2026-06-24 06:01:58,558 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171 +2026-06-24 06:01:58,559 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171' is generated! +2026-06-24 06:01:58,708 - +2026-06-24 06:01:58,709 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/20260624_060158_ptyrad_log.txt ### +2026-06-24 06:01:58,710 - +2026-06-24 06:01:58,711 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:01:58,711 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:01:58,711 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:01:59,890 - Iter: 1, Total Loss: 1.0721, loss_single: 1.0721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:01:59,927 - Iter: 2, Total Loss: 1.0180, loss_single: 1.0180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:01:59,962 - Iter: 3, Total Loss: 0.9775, loss_single: 0.9775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:01:59,997 - Iter: 4, Total Loss: 0.9339, loss_single: 0.9339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,033 - Iter: 5, Total Loss: 0.8891, loss_single: 0.8891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,068 - Iter: 6, Total Loss: 0.8451, loss_single: 0.8451, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,102 - Iter: 7, Total Loss: 0.8146, loss_single: 0.8146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,138 - Iter: 8, Total Loss: 0.7954, loss_single: 0.7954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,173 - Iter: 9, Total Loss: 0.7718, loss_single: 0.7718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,208 - Iter: 10, Total Loss: 0.7448, loss_single: 0.7448, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,243 - Iter: 11, Total Loss: 0.7254, loss_single: 0.7254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,278 - Iter: 12, Total Loss: 0.7136, loss_single: 0.7136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,313 - Iter: 13, Total Loss: 0.7002, loss_single: 0.7002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,348 - Iter: 14, Total Loss: 0.6887, loss_single: 0.6887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,385 - Iter: 15, Total Loss: 0.6773, loss_single: 0.6773, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:02:00,419 - Iter: 16, Total Loss: 0.6640, loss_single: 0.6640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:00,454 - Iter: 17, Total Loss: 0.6503, loss_single: 0.6503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:00,489 - Iter: 18, Total Loss: 0.6372, loss_single: 0.6372, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.5060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:03,355 - Iter: 99, Total Loss: 0.5058, loss_single: 0.5058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:03,390 - Iter: 100, Total Loss: 0.5056, loss_single: 0.5056, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:03,503 - Saving summary figures for iter 100 +2026-06-24 06:02:07,074 - ### Finished 100 iterations, averaged iter_t = 0.038631 with std = 0.040 ### +2026-06-24 06:02:07,075 - +2026-06-24 06:02:07,075 - ### The PtyRADSolver is finished in 9.182 sec ### +2026-06-24 06:02:07,075 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/model_iter0100.hdf5 b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/model_iter0100.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..e160d459edba83ef82e8a1c4bce7cbc4c2161d85 --- /dev/null +++ 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/simulation_data3__sample_000029.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/simulation_data3__sample_000029.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2bbb4ecc6ef7ac57e0fd894582c74378778aca7e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/simulation_data3__sample_000029.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 13.020979881286621 + probe_aberrations: + C10: -198.1902618408203 + C12: -4.805131912231445 + C21: 384.13958740234375 + C23: 360.9826965332031 + C30: 4119662.75 + C32: 8797.67578125 + C34: -398.1482849121094 + C41: -465696.71875 + C43: 385672.375 + C45: 130449.4921875 + C50: 476960640.0 + C52: -13821542.0 + C54: 7284448.0 + C56: -13540188.0 + phi12: 305.63558377205976 + phi21: 151.09754044167045 + phi23: 94.09207811925953 + phi32: 3.968321124757191 + phi34: 65.55284984222409 + phi41: 168.98603810436563 + phi43: 162.99213729632925 + phi45: 100.98881382235571 + phi52: 7.502834737212069 + phi54: 159.10451656416305 + phi56: 171.0528943283465 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3369060456752777 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000029_measurement.h5 + key: measurement + random_seed: 20261957 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000029 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ae2057e668f6e3340dcae797288e566ffe9c63ae51afe356bfa858da4598af7c +size 1002763 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..20dddaf43b64b648708e90142f6e4792e7cf5cce --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000029/c30_small__simulation_data3__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-198_C12_-4.8_phi12_306_C21_384_phi21_151_C23_361_phi23_94.1_C30_4.12e+06_C32_8.8.35e+07_phi56_171/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6c4f6fdd5d21b458634b978b00d5ffcd1f681839cf9b41e04158a7bc6da87759 +size 48495 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/20260624_060243_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/20260624_060243_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fa46ccf4192868dd9cb58d4408977d9de84934e5 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/20260624_060243_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:02:41,373 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:02:41,373 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:02:41,373 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:02:41,373 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:02:41,373 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:02:41,373 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:02:41,373 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:02:41,373 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:02:41,373 - +2026-06-24 06:02:41,480 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:02:41,480 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:02:41,480 - Accelerator.num_process = 1 +2026-06-24 06:02:41,480 - Accelerator.mixed_precision = no +2026-06-24 06:02:41,490 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:02:41,490 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:02:41,490 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:02:41,490 - +2026-06-24 06:02:41,490 - ### System information ### +2026-06-24 06:02:41,491 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:02:41,491 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:02:41,491 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:02:41,491 - Machine: x86_64 +2026-06-24 06:02:41,491 - Processor: x86_64 +2026-06-24 06:02:41,491 - Available CPU cores: 8 +2026-06-24 06:02:41,491 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:02:41,491 - +2026-06-24 06:02:41,491 - ### GPU information ### +2026-06-24 06:02:41,491 - CUDA Available: True +2026-06-24 06:02:41,491 - CUDA Version: 13.0 +2026-06-24 06:02:41,491 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:02:41,491 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:02:41,491 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:02:41,492 - In addition, Triton does not directly support Windows. +2026-06-24 06:02:41,492 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:02:41,518 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:02:41,519 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:02:41,519 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:02:41,519 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:02:41,519 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:02:41,519 - +2026-06-24 06:02:41,519 - ### Python information ### +2026-06-24 06:02:41,520 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:02:41,520 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:02:41,520 - +2026-06-24 06:02:41,520 - ### Packages information ### +2026-06-24 06:02:41,521 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:02:41,521 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:02:41,522 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:02:41,523 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:02:41,523 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:02:41,523 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:02:41,523 - +2026-06-24 06:02:41,523 - ### Loading params file ### +2026-06-24 06:02:41,523 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000032.yaml +2026-06-24 06:02:41,530 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:02:41,531 - Success! Params file validated and defaults applied. +2026-06-24 06:02:41,531 - +2026-06-24 06:02:41,531 - ### Setting GPU Device ### +2026-06-24 06:02:41,531 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:02:41,531 - +2026-06-24 06:02:41,531 - Random seed: 20261960 provided by params file +2026-06-24 06:02:41,531 - ### Initializing Initializer ### +2026-06-24 06:02:41,532 - init_params are displayed below: +2026-06-24 06:02:41,532 - random_seed: 20261960 +2026-06-24 06:02:41,532 - probe_illum_type: electron +2026-06-24 06:02:41,532 - probe_kv: 120.0 +2026-06-24 06:02:41,532 - probe_conv_angle: 15.02608871459961 +2026-06-24 06:02:41,532 - probe_aberrations: {'C10': -417.133, 'C12': 4.315, 'phi12': 30.148, 'C21': -182.607, 'phi21': 341.474, 'C23': 968.303, 'phi23': 180.83, 'C30': 199419.984, 'C32': 2319.069, 'phi32': 66.164, 'C34': -1716.133, 'phi34': 119.519, 'C41': 161246.156, 'phi41': 346.654, 'C43': -409169.719, 'phi43': 119.13, 'C45': -469365.469, 'phi45': 88.214, 'C50': 86264376.0, 'C52': 1284521.625, 'phi52': 4.236, 'C54': 17311968.0, 'phi54': 146.266, 'C56': 18882870.0, 'phi56': 301.118} +2026-06-24 06:02:41,532 - beam_kev: None +2026-06-24 06:02:41,532 - probe_dRn: None +2026-06-24 06:02:41,532 - probe_Rn: None +2026-06-24 06:02:41,532 - probe_D_H: None +2026-06-24 06:02:41,532 - probe_D_FZP: None +2026-06-24 06:02:41,532 - probe_Ls: None +2026-06-24 06:02:41,532 - meas_Npix: 128 +2026-06-24 06:02:41,532 - pos_N_scans: 256 +2026-06-24 06:02:41,532 - pos_N_scan_slow: 16 +2026-06-24 06:02:41,532 - pos_N_scan_fast: 16 +2026-06-24 06:02:41,532 - pos_scan_step_size: 0.39992260932922363 +2026-06-24 06:02:41,532 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:02:41,532 - probe_pmode_max: 6 +2026-06-24 06:02:41,532 - probe_pmode_init_pows: [0.02] +2026-06-24 06:02:41,532 - obj_omode_max: 1 +2026-06-24 06:02:41,532 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:02:41,532 - obj_Nlayer: 1 +2026-06-24 06:02:41,532 - obj_slice_thickness: 20.0 +2026-06-24 06:02:41,532 - simu_Npix: None +2026-06-24 06:02:41,532 - simu_match_mode: None +2026-06-24 06:02:41,532 - meas_permute: None +2026-06-24 06:02:41,532 - meas_reshape: [256, 128, 128] +2026-06-24 06:02:41,532 - meas_flipT: [0, 0, 0] +2026-06-24 06:02:41,532 - meas_crop: None +2026-06-24 06:02:41,532 - meas_pad: None +2026-06-24 06:02:41,532 - meas_resample: None +2026-06-24 06:02:41,532 - meas_add_source_size: None +2026-06-24 06:02:41,533 - meas_add_detector_blur: None +2026-06-24 06:02:41,533 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:02:41,533 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:02:41,533 - meas_add_poisson_noise: None +2026-06-24 06:02:41,533 - meas_export: None +2026-06-24 06:02:41,533 - probe_permute: None +2026-06-24 06:02:41,533 - probe_z_shift: None +2026-06-24 06:02:41,533 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:02:41,533 - pos_scan_flipT: None +2026-06-24 06:02:41,533 - pos_scan_affine: None +2026-06-24 06:02:41,533 - pos_scan_rand_std: 0.15 +2026-06-24 06:02:41,533 - obj_z_crop: None +2026-06-24 06:02:41,533 - obj_z_pad: None +2026-06-24 06:02:41,533 - obj_z_resample: None +2026-06-24 06:02:41,533 - meas_source: file +2026-06-24 06:02:41,533 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000032_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:02:41,533 - probe_source: simu +2026-06-24 06:02:41,533 - probe_params: None +2026-06-24 06:02:41,533 - pos_source: simu +2026-06-24 06:02:41,533 - pos_params: None +2026-06-24 06:02:41,533 - obj_source: simu +2026-06-24 06:02:41,533 - obj_params: None +2026-06-24 06:02:41,533 - tilt_source: simu +2026-06-24 06:02:41,533 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:02:41,533 - +2026-06-24 06:02:41,533 - ### Initializing cache ### +2026-06-24 06:02:41,533 - use_cached_obj = False +2026-06-24 06:02:41,533 - use_cached_probe = False +2026-06-24 06:02:41,533 - use_cached_pos = False +2026-06-24 06:02:41,533 - +2026-06-24 06:02:41,533 - ### Initializing measurements ### +2026-06-24 06:02:41,533 - Loading measurements from source = 'file' +2026-06-24 06:02:41,533 - Detected measurement file type = '.h5' +2026-06-24 06:02:41,615 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:02:41,615 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:02:41,616 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0034) +2026-06-24 06:02:41,616 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:02:41,616 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:02:41,619 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:02:41,619 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:02:41,619 - Normalizing by max of the 2D mean pattern intensity: 0.0023991235 +2026-06-24 06:02:41,620 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:02:41,621 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0254, 1.4238) +2026-06-24 06:02:41,622 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:02:41,623 - Pattern total int. statistics (min, mean, max) = (414.1537, 416.1452, 418.5394), with min/max = 99.0% +2026-06-24 06:02:41,624 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0254, 1.4238) +2026-06-24 06:02:41,624 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:02:41,624 - +2026-06-24 06:02:41,624 - ### Setting up calibration ### +2026-06-24 06:02:41,624 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:02:41,624 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:02:41,624 - Radius of fitted bright field disk (RBF) = 11.31 px with meas_Npix = 128 +2026-06-24 06:02:41,625 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1767 +2026-06-24 06:02:41,625 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:02:41,625 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:02:41,855 - Initial guess: center=(63.62, 63.62), radius=11.31, Gaussian blur std=0.50 +2026-06-24 06:02:41,867 - Final fit: center=(63.62, 63.62), radius=11.31, Gaussian blur std=0.69 +2026-06-24 06:02:41,867 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.49 px with Npix = 128 +2026-06-24 06:02:41,867 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:02:41,867 - +2026-06-24 06:02:41,868 - ### Setting init_variables dict ### +2026-06-24 06:02:41,868 - Derived values given input init_params: +2026-06-24 06:02:41,868 - kv = 120.0 kV +2026-06-24 06:02:41,868 - wavelength = 0.0335 Ang +2026-06-24 06:02:41,868 - conv_angle = 15.02608871459961 mrad +2026-06-24 06:02:41,868 - Npix = 128 px +2026-06-24 06:02:41,868 - dk = 0.0391 Ang^-1 +2026-06-24 06:02:41,868 - kMax = 2.5000 Ang^-1 +2026-06-24 06:02:41,868 - da = 1.3083 mrad +2026-06-24 06:02:41,868 - angleMax = 83.7304 mrad +2026-06-24 06:02:41,868 - RBF = 11.4853 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:02:41,868 - n_alpha = 5.5723 (# conv_angle) +2026-06-24 06:02:41,868 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:02:41,868 - Rayleigh-limited resolution = 1.3596 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:02:41,868 - Real space probe extent = 25.6000 Ang +2026-06-24 06:02:41,868 - +2026-06-24 06:02:41,868 - ### Initializing probe ### +2026-06-24 06:02:41,868 - Loading probe from source = 'simu' +2026-06-24 06:02:41,868 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:02:41,868 - Start simulating STEM probe +2026-06-24 06:02:41,868 - kv = 120.0 kV +2026-06-24 06:02:41,868 - wavelength = 0.0335 Ang +2026-06-24 06:02:41,868 - conv_angle = 15.02608871459961 mrad +2026-06-24 06:02:41,868 - Npix = 128 px +2026-06-24 06:02:41,868 - dk = 0.0391 Ang^-1 +2026-06-24 06:02:41,869 - kMax = 2.5000 Ang^-1 +2026-06-24 06:02:41,869 - alpha_max = 83.7304 mrad +2026-06-24 06:02:41,869 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:02:41,869 - Rayleigh-limited resolution = 1.3596 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:02:41,869 - Real space probe extent = 25.6000 Ang +2026-06-24 06:02:41,869 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:02:41,869 - ----------------------------------------------------------------------------------- +2026-06-24 06:02:41,869 - C1,0 C1 -417.1330 - Defocus (C10 = -df) +2026-06-24 06:02:41,869 - C1,2 A1 4.3150 30.15 2-fold astigmatism +2026-06-24 06:02:41,869 - C2,1 3*B2 -182.6070 341.47 Axial coma +2026-06-24 06:02:41,869 - C2,3 A2 968.3030 180.83 3-fold astigmatism +2026-06-24 06:02:41,869 - C3,0 C3 199419.9840 - Spherical aberration +2026-06-24 06:02:41,869 - C3,2 4*S3 2319.0690 66.16 Axial star aberration +2026-06-24 06:02:41,869 - C3,4 A3 -1716.1330 119.52 4-fold astigmatism +2026-06-24 06:02:41,869 - C4,1 4*B4 161246.1560 346.65 Axial coma(4th) +2026-06-24 06:02:41,869 - C4,3 4*D4 -409169.7190 119.13 3-lobe aberration +2026-06-24 06:02:41,869 - C4,5 A4 -469365.4690 88.21 5-fold astigmatism +2026-06-24 06:02:41,869 - C5,0 C5 86264376.0000 - Spherical aberration (5th) +2026-06-24 06:02:41,869 - C5,2 6*S5 1284521.6250 4.24 Axial star aberration(5th) +2026-06-24 06:02:41,869 - C5,4 6*R5 17311968.0000 146.27 4-lobe aberration +2026-06-24 06:02:41,869 - C5,6 A5 18882870.0000 301.12 6-fold astigmatism +2026-06-24 06:02:41,872 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:02:41,872 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:02:41,872 - Creating 5 new probe modes from the major mode +2026-06-24 06:02:41,872 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:02:42,069 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:02:42,070 - Orthogonalizing 6 pmodes +2026-06-24 06:02:42,083 - Sorting 6 pmodes by their intensities +2026-06-24 06:02:42,083 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:02:42,084 - sum(|probe_data|**2) = 416.15, while meas_total_ints (min, mean, max) = (414.1537, 416.1452, 418.5394) +2026-06-24 06:02:42,084 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:02:42,084 - +2026-06-24 06:02:42,084 - ### Initializing probe positions ### +2026-06-24 06:02:42,084 - Loading probe positions from source = 'simu' +2026-06-24 06:02:42,084 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:02:42,084 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3999, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:02:42,084 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:02:42,086 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:02:42,086 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 45]) +2026-06-24 06:02:42,086 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 06:02:42,086 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:02:42,086 - +2026-06-24 06:02:42,086 - ### Initializing object ### +2026-06-24 06:02:42,087 - Loading object from source = 'simu' +2026-06-24 06:02:42,087 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:02:42,088 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:02:42,088 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-24 06:02:42,088 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-24 06:02:42,088 - +2026-06-24 06:02:42,088 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:02:42,088 - omode_occu (omode) = float32, (1,) +2026-06-24 06:02:42,088 - +2026-06-24 06:02:42,088 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:02:42,088 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:02:42,089 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:02:42,089 - +2026-06-24 06:02:42,089 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:02:42,089 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:02:42,089 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:02:42,089 - +2026-06-24 06:02:42,089 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:02:42,089 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:02:42,089 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:02:42,089 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:02:42,089 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:02:42,090 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-24 06:02:42,090 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:02:42,090 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:02:42,090 - +2026-06-24 06:02:42,090 - ### Collecting reconstruction provenance ### +2026-06-24 06:02:42,090 - Reconstruction provenance is collected and initialized. +2026-06-24 06:02:42,090 - +2026-06-24 06:02:42,090 - ### Initializing loss function ### +2026-06-24 06:02:42,090 - Active loss types: +2026-06-24 06:02:42,090 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:02:42,090 - +2026-06-24 06:02:42,090 - ### Initializing constraint function ### +2026-06-24 06:02:42,090 - Active constraint types: +2026-06-24 06:02:42,090 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:02:42,090 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:02:42,090 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:02:42,090 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:02:42,090 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:02:42,090 - +2026-06-24 06:02:42,090 - ### Done initializing PtyRADSolver ### +2026-06-24 06:02:42,090 - +2026-06-24 06:02:42,213 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:02:42,214 - +2026-06-24 06:02:42,214 - ### Initializing PtychoModel model ### +2026-06-24 06:02:42,287 - ### PtychoModel optimizable variables ### +2026-06-24 06:02:42,287 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:42,287 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:42,287 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:02:42,287 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:02:42,287 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:02:42,287 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:42,287 - +2026-06-24 06:02:42,287 - ### Optimizable variables statitsics ### +2026-06-24 06:02:42,287 - Total measurement values : 4,194,304 +2026-06-24 06:02:42,287 - Total optimizing variables: 269,320 +2026-06-24 06:02:42,287 - Overdetermined ratio : 15.57 +2026-06-24 06:02:42,287 - +2026-06-24 06:02:42,287 - ### Model behavior ### +2026-06-24 06:02:42,287 - Tilt propagator : False +2026-06-24 06:02:42,287 - Change slice thickness : False +2026-06-24 06:02:42,288 - Detector blur : False +2026-06-24 06:02:42,288 - Preload data : True +2026-06-24 06:02:42,288 - On-the-fly meas padding : False +2026-06-24 06:02:42,288 - On-the-fly meas resample : False +2026-06-24 06:02:42,288 - On-the-fly simu match mode: None +2026-06-24 06:02:42,288 - +2026-06-24 06:02:42,329 - ### Done initializing PtychoModel model ### +2026-06-24 06:02:42,329 - +2026-06-24 06:02:42,329 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:02:42,329 - +2026-06-24 06:02:42,329 - ### Generating indices, batches, and output_path ### +2026-06-24 06:02:42,330 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:02:42,330 - Selecting indices with the 'full' mode +2026-06-24 06:02:42,788 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:02:42,862 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:02:42,862 - Original recon_dir_affixes = ['default'] +2026-06-24 06:02:42,862 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:02:42,868 - Path corrected for compatibility: +2026-06-24 06:02:42,868 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2.32e+03_phi32_66.2_C34_-1.72e+03_phi34_120_C41_1.61e+05_phi41_347_C43_-4.09e+05_phi43_119_C45_-4.69e+05_phi45_88.2_C50_8.63e+07_C52_1.28e+06_phi52_4.24_C54_1.73e+07_phi54_146_C56_1.89e+07_phi56_301 +2026-06-24 06:02:42,868 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301 +2026-06-24 06:02:42,869 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301' is generated! +2026-06-24 06:02:43,014 - +2026-06-24 06:02:43,015 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/20260624_060243_ptyrad_log.txt ### +2026-06-24 06:02:43,015 - +2026-06-24 06:02:43,016 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:02:43,017 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:02:43,017 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:02:44,193 - Iter: 1, Total Loss: 0.9133, loss_single: 0.9133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:02:44,230 - Iter: 2, Total Loss: 0.8720, loss_single: 0.8720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:02:44,265 - Iter: 3, Total Loss: 0.8406, loss_single: 0.8406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,301 - Iter: 4, Total Loss: 0.8143, loss_single: 0.8143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,335 - Iter: 5, Total Loss: 0.7867, loss_single: 0.7867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,370 - Iter: 6, Total Loss: 0.7578, loss_single: 0.7578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,406 - Iter: 7, Total Loss: 0.7292, loss_single: 0.7292, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,441 - Iter: 8, Total Loss: 0.7043, loss_single: 0.7043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,475 - Iter: 9, Total Loss: 0.6804, loss_single: 0.6804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,510 - Iter: 10, Total Loss: 0.6548, loss_single: 0.6548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,546 - Iter: 11, Total Loss: 0.6306, loss_single: 0.6306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:02:44,581 - Iter: 12, Total Loss: 0.6045, loss_single: 0.6045, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,616 - Iter: 13, Total Loss: 0.5801, loss_single: 0.5801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,651 - Iter: 14, Total Loss: 0.5573, loss_single: 0.5573, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,686 - Iter: 15, Total Loss: 0.5377, loss_single: 0.5377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,721 - Iter: 16, Total Loss: 0.5194, loss_single: 0.5194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,756 - Iter: 17, Total Loss: 0.4983, loss_single: 0.4983, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,791 - Iter: 18, Total Loss: 0.4786, loss_single: 0.4786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,826 - Iter: 19, Total Loss: 0.4632, loss_single: 0.4632, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,860 - Iter: 20, Total Loss: 0.4477, loss_single: 0.4477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:44,895 - Iter: 21, Total Loss: 0.4305, loss_single: 0.4305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,931 - Iter: 22, Total Loss: 0.4168, loss_single: 0.4168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:44,965 - Iter: 23, Total Loss: 0.4062, loss_single: 0.4062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,000 - Iter: 24, Total Loss: 0.3940, loss_single: 0.3940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,036 - Iter: 25, Total Loss: 0.3829, loss_single: 0.3829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,071 - Iter: 26, Total Loss: 0.3743, loss_single: 0.3743, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,106 - Iter: 27, Total Loss: 0.3644, loss_single: 0.3644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,140 - Iter: 28, Total Loss: 0.3549, loss_single: 0.3549, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,175 - Iter: 29, Total Loss: 0.3469, loss_single: 0.3469, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,210 - Iter: 30, Total Loss: 0.3397, loss_single: 0.3397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,245 - Iter: 31, Total Loss: 0.3340, loss_single: 0.3340, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,280 - Iter: 32, Total Loss: 0.3301, loss_single: 0.3301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,315 - Iter: 33, Total Loss: 0.3269, loss_single: 0.3269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,350 - Iter: 34, Total Loss: 0.3241, loss_single: 0.3241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,385 - Iter: 35, Total Loss: 0.3212, loss_single: 0.3212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,420 - Iter: 36, Total Loss: 0.3184, loss_single: 0.3184, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,455 - Iter: 37, Total Loss: 0.3162, loss_single: 0.3162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,490 - Iter: 38, Total Loss: 0.3147, loss_single: 0.3147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,528 - Iter: 39, Total Loss: 0.3133, loss_single: 0.3133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:02:45,563 - Iter: 40, Total Loss: 0.3118, loss_single: 0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,601 - Iter: 41, Total Loss: 0.3103, loss_single: 0.3103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,636 - Iter: 42, Total Loss: 0.3090, loss_single: 0.3090, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,671 - Iter: 43, Total Loss: 0.3076, loss_single: 0.3076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,706 - Iter: 44, Total Loss: 0.3064, loss_single: 0.3064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,741 - Iter: 45, Total Loss: 0.3053, loss_single: 0.3053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:02:45,776 - Iter: 46, Total Loss: 0.3043, loss_single: 0.3043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:45,811 - 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/simulation_data3__sample_000032.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/simulation_data3__sample_000032.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2b0c6043c40255a55f188eb6c271e8e87f452a24 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000032/c30_small__simulation_data3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-417_C12_4.32_phi12_30.1_C21_-183_phi21_341_C23_968_phi23_181_C30_1.99e+05_C32_2..89e+07_phi56_301/simulation_data3__sample_000032.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 15.02608871459961 + probe_aberrations: + C10: -417.1329345703125 + C12: 4.314841270446777 + C21: -182.60720825195312 + C23: 968.3033447265625 + C30: 199419.984375 + C32: 2319.069091796875 + C34: -1716.13330078125 + C41: 161246.15625 + C43: -409169.71875 + C45: -469365.46875 + C50: 86264376.0 + C52: 1284521.625 + C54: 17311968.0 + C56: 18882870.0 + phi12: 30.14751243033082 + phi21: 341.4740507999802 + phi23: 180.8297090685728 + phi32: 66.16374879177921 + phi34: 119.51874821038513 + phi41: 346.65379305895107 + phi43: 119.12980991828792 + phi45: 88.21409245162742 + phi52: 4.23600989870833 + phi54: 146.2657416793984 + phi56: 301.11828790031007 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.39992260932922363 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000032_measurement.h5 + key: measurement + random_seed: 20261960 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/20260624_060257_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:02:56,404 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:02:56,404 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:02:56,404 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:02:56,404 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:02:56,404 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:02:56,404 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:02:56,404 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:02:56,404 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:02:56,404 - +2026-06-24 06:02:56,513 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:02:56,513 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:02:56,513 - Accelerator.num_process = 1 +2026-06-24 06:02:56,513 - Accelerator.mixed_precision = no +2026-06-24 06:02:56,535 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:02:56,535 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:02:56,535 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:02:56,536 - +2026-06-24 06:02:56,536 - ### System information ### +2026-06-24 06:02:56,536 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:02:56,536 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:02:56,536 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:02:56,536 - Machine: x86_64 +2026-06-24 06:02:56,536 - Processor: x86_64 +2026-06-24 06:02:56,536 - Available CPU cores: 8 +2026-06-24 06:02:56,536 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:02:56,536 - +2026-06-24 06:02:56,536 - ### GPU information ### +2026-06-24 06:02:56,536 - CUDA Available: True +2026-06-24 06:02:56,536 - CUDA Version: 13.0 +2026-06-24 06:02:56,536 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:02:56,537 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:02:56,537 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:02:56,537 - In addition, Triton does not directly support Windows. +2026-06-24 06:02:56,537 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:02:56,577 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:02:56,577 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:02:56,577 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:02:56,577 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:02:56,577 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:02:56,577 - +2026-06-24 06:02:56,577 - ### Python information ### +2026-06-24 06:02:56,579 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:02:56,579 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:02:56,579 - +2026-06-24 06:02:56,579 - ### Packages information ### +2026-06-24 06:02:56,580 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:02:56,580 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:02:56,581 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:02:56,582 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:02:56,582 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:02:56,582 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:02:56,582 - +2026-06-24 06:02:56,582 - ### Loading params file ### +2026-06-24 06:02:56,582 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000033.yaml +2026-06-24 06:02:56,589 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:02:56,590 - Success! Params file validated and defaults applied. +2026-06-24 06:02:56,590 - +2026-06-24 06:02:56,590 - ### Setting GPU Device ### +2026-06-24 06:02:56,590 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:02:56,590 - +2026-06-24 06:02:56,590 - Random seed: 20261961 provided by params file +2026-06-24 06:02:56,590 - ### Initializing Initializer ### +2026-06-24 06:02:56,590 - init_params are displayed below: +2026-06-24 06:02:56,591 - random_seed: 20261961 +2026-06-24 06:02:56,591 - probe_illum_type: electron +2026-06-24 06:02:56,591 - probe_kv: 80.0 +2026-06-24 06:02:56,591 - probe_conv_angle: 16.246652603149414 +2026-06-24 06:02:56,591 - probe_aberrations: {'C10': -184.925, 'C12': -10.092, 'phi12': 351.876, 'C21': -666.647, 'phi21': 323.624, 'C23': -698.412, 'phi23': 157.705, 'C30': 1140546.625, 'C32': -1678.647, 'phi32': 153.167, 'C34': -622.022, 'phi34': 12.702, 'C41': -342794.219, 'phi41': 105.749, 'C43': 448874.75, 'phi43': 356.05, 'C45': 495363.125, 'phi45': 81.921, 'C50': -473188608.0, 'C52': 12154104.0, 'phi52': 13.537, 'C54': -14568536.0, 'phi54': 83.117, 'C56': -5317734.0, 'phi56': 160.742} +2026-06-24 06:02:56,591 - beam_kev: None +2026-06-24 06:02:56,591 - probe_dRn: None +2026-06-24 06:02:56,591 - probe_Rn: None +2026-06-24 06:02:56,591 - probe_D_H: None +2026-06-24 06:02:56,591 - probe_D_FZP: None +2026-06-24 06:02:56,591 - probe_Ls: None +2026-06-24 06:02:56,591 - meas_Npix: 128 +2026-06-24 06:02:56,591 - pos_N_scans: 256 +2026-06-24 06:02:56,591 - pos_N_scan_slow: 16 +2026-06-24 06:02:56,591 - pos_N_scan_fast: 16 +2026-06-24 06:02:56,591 - pos_scan_step_size: 0.34307581186294556 +2026-06-24 06:02:56,591 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:02:56,591 - probe_pmode_max: 6 +2026-06-24 06:02:56,591 - probe_pmode_init_pows: [0.02] +2026-06-24 06:02:56,591 - obj_omode_max: 1 +2026-06-24 06:02:56,591 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:02:56,591 - obj_Nlayer: 1 +2026-06-24 06:02:56,591 - obj_slice_thickness: 20.0 +2026-06-24 06:02:56,591 - simu_Npix: None +2026-06-24 06:02:56,591 - simu_match_mode: None +2026-06-24 06:02:56,591 - meas_permute: None +2026-06-24 06:02:56,591 - meas_reshape: [256, 128, 128] +2026-06-24 06:02:56,591 - meas_flipT: [0, 0, 0] +2026-06-24 06:02:56,591 - meas_crop: None +2026-06-24 06:02:56,591 - meas_pad: None +2026-06-24 06:02:56,591 - meas_resample: None +2026-06-24 06:02:56,591 - meas_add_source_size: None +2026-06-24 06:02:56,591 - meas_add_detector_blur: None +2026-06-24 06:02:56,591 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:02:56,591 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:02:56,591 - meas_add_poisson_noise: None +2026-06-24 06:02:56,591 - meas_export: None +2026-06-24 06:02:56,591 - probe_permute: None +2026-06-24 06:02:56,592 - probe_z_shift: None +2026-06-24 06:02:56,592 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:02:56,592 - pos_scan_flipT: None +2026-06-24 06:02:56,592 - pos_scan_affine: None +2026-06-24 06:02:56,592 - pos_scan_rand_std: 0.15 +2026-06-24 06:02:56,592 - obj_z_crop: None +2026-06-24 06:02:56,592 - obj_z_pad: None +2026-06-24 06:02:56,592 - obj_z_resample: None +2026-06-24 06:02:56,592 - meas_source: file +2026-06-24 06:02:56,592 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000033_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:02:56,592 - probe_source: simu +2026-06-24 06:02:56,592 - probe_params: None +2026-06-24 06:02:56,592 - pos_source: simu +2026-06-24 06:02:56,592 - pos_params: None +2026-06-24 06:02:56,592 - obj_source: simu +2026-06-24 06:02:56,592 - obj_params: None +2026-06-24 06:02:56,592 - tilt_source: simu +2026-06-24 06:02:56,592 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:02:56,592 - +2026-06-24 06:02:56,592 - ### Initializing cache ### +2026-06-24 06:02:56,592 - use_cached_obj = False +2026-06-24 06:02:56,592 - use_cached_probe = False +2026-06-24 06:02:56,592 - use_cached_pos = False +2026-06-24 06:02:56,592 - +2026-06-24 06:02:56,592 - ### Initializing measurements ### +2026-06-24 06:02:56,592 - Loading measurements from source = 'file' +2026-06-24 06:02:56,592 - Detected measurement file type = '.h5' +2026-06-24 06:02:56,673 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:02:56,673 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:02:56,675 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0049) +2026-06-24 06:02:56,675 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:02:56,675 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:02:56,677 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:02:56,677 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:02:56,677 - Normalizing by max of the 2D mean pattern intensity: 0.0030192609 +2026-06-24 06:02:56,678 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:02:56,679 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0201, 1.6123) +2026-06-24 06:02:56,679 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:02:56,681 - Pattern total int. statistics (min, mean, max) = (326.9661, 330.1248, 332.5717), with min/max = 98.3% +2026-06-24 06:02:56,682 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0201, 1.6123) +2026-06-24 06:02:56,682 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:02:56,682 - +2026-06-24 06:02:56,682 - ### Setting up calibration ### +2026-06-24 06:02:56,682 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:02:56,682 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:02:56,682 - Radius of fitted bright field disk (RBF) = 9.87 px with meas_Npix = 128 +2026-06-24 06:02:56,682 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1542 +2026-06-24 06:02:56,682 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:02:56,682 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:02:56,913 - Initial guess: center=(63.55, 63.61), radius=9.87, Gaussian blur std=0.50 +2026-06-24 06:02:56,923 - Final fit: center=(63.55, 63.61), radius=9.87, Gaussian blur std=0.60 +2026-06-24 06:02:56,924 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.96 px with Npix = 128 +2026-06-24 06:02:56,924 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:02:56,924 - +2026-06-24 06:02:56,924 - ### Setting init_variables dict ### +2026-06-24 06:02:56,924 - Derived values given input init_params: +2026-06-24 06:02:56,924 - kv = 80.0 kV +2026-06-24 06:02:56,924 - wavelength = 0.0418 Ang +2026-06-24 06:02:56,924 - conv_angle = 16.246652603149414 mrad +2026-06-24 06:02:56,924 - Npix = 128 px +2026-06-24 06:02:56,924 - dk = 0.0391 Ang^-1 +2026-06-24 06:02:56,924 - kMax = 2.5000 Ang^-1 +2026-06-24 06:02:56,924 - da = 1.6311 mrad +2026-06-24 06:02:56,924 - angleMax = 104.3929 mrad +2026-06-24 06:02:56,924 - RBF = 9.9603 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:02:56,924 - n_alpha = 6.4255 (# conv_angle) +2026-06-24 06:02:56,924 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:02:56,924 - Rayleigh-limited resolution = 1.5678 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:02:56,924 - Real space probe extent = 25.6000 Ang +2026-06-24 06:02:56,924 - +2026-06-24 06:02:56,924 - ### Initializing probe ### +2026-06-24 06:02:56,924 - Loading probe from source = 'simu' +2026-06-24 06:02:56,924 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:02:56,924 - Start simulating STEM probe +2026-06-24 06:02:56,925 - kv = 80.0 kV +2026-06-24 06:02:56,925 - wavelength = 0.0418 Ang +2026-06-24 06:02:56,925 - conv_angle = 16.246652603149414 mrad +2026-06-24 06:02:56,925 - Npix = 128 px +2026-06-24 06:02:56,925 - dk = 0.0391 Ang^-1 +2026-06-24 06:02:56,925 - kMax = 2.5000 Ang^-1 +2026-06-24 06:02:56,925 - alpha_max = 104.3929 mrad +2026-06-24 06:02:56,925 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:02:56,925 - Rayleigh-limited resolution = 1.5678 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:02:56,925 - Real space probe extent = 25.6000 Ang +2026-06-24 06:02:56,925 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:02:56,925 - ------------------------------------------------------------------------------------- +2026-06-24 06:02:56,925 - C1,0 C1 -184.9250 - Defocus (C10 = -df) +2026-06-24 06:02:56,925 - C1,2 A1 -10.0920 351.88 2-fold astigmatism +2026-06-24 06:02:56,925 - C2,1 3*B2 -666.6470 323.62 Axial coma +2026-06-24 06:02:56,925 - C2,3 A2 -698.4120 157.71 3-fold astigmatism +2026-06-24 06:02:56,925 - C3,0 C3 1140546.6250 - Spherical aberration +2026-06-24 06:02:56,925 - C3,2 4*S3 -1678.6470 153.17 Axial star aberration +2026-06-24 06:02:56,925 - C3,4 A3 -622.0220 12.70 4-fold astigmatism +2026-06-24 06:02:56,925 - C4,1 4*B4 -342794.2190 105.75 Axial coma(4th) +2026-06-24 06:02:56,925 - C4,3 4*D4 448874.7500 356.05 3-lobe aberration +2026-06-24 06:02:56,925 - C4,5 A4 495363.1250 81.92 5-fold astigmatism +2026-06-24 06:02:56,925 - C5,0 C5 -473188608.0000 - Spherical aberration (5th) +2026-06-24 06:02:56,925 - C5,2 6*S5 12154104.0000 13.54 Axial star aberration(5th) +2026-06-24 06:02:56,925 - C5,4 6*R5 -14568536.0000 83.12 4-lobe aberration +2026-06-24 06:02:56,925 - C5,6 A5 -5317734.0000 160.74 6-fold astigmatism +2026-06-24 06:02:56,928 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:02:56,928 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:02:56,928 - Creating 5 new probe modes from the major mode +2026-06-24 06:02:56,928 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:02:57,031 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:02:57,033 - Orthogonalizing 6 pmodes +2026-06-24 06:02:57,035 - Sorting 6 pmodes by their intensities +2026-06-24 06:02:57,035 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:02:57,036 - sum(|probe_data|**2) = 330.12, while meas_total_ints (min, mean, max) = (326.9661, 330.1248, 332.5717) +2026-06-24 06:02:57,036 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:02:57,036 - +2026-06-24 06:02:57,036 - ### Initializing probe positions ### +2026-06-24 06:02:57,036 - Loading probe positions from source = 'simu' +2026-06-24 06:02:57,036 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:02:57,036 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3431, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:02:57,036 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:02:57,038 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:02:57,038 - crop_pos 1st and last px coords (y,x) = ([15, 15], [41, 41]) +2026-06-24 06:02:57,038 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:02:57,038 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:02:57,038 - +2026-06-24 06:02:57,039 - ### Initializing object ### +2026-06-24 06:02:57,039 - Loading object from source = 'simu' +2026-06-24 06:02:57,039 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:02:57,040 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:02:57,040 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 186) +2026-06-24 06:02:57,040 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.2] +2026-06-24 06:02:57,040 - +2026-06-24 06:02:57,040 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:02:57,040 - omode_occu (omode) = float32, (1,) +2026-06-24 06:02:57,040 - +2026-06-24 06:02:57,040 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:02:57,040 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:02:57,041 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:02:57,041 - +2026-06-24 06:02:57,041 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:02:57,041 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:02:57,041 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:02:57,041 - +2026-06-24 06:02:57,041 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:02:57,041 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:02:57,041 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:02:57,041 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:02:57,041 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:02:57,042 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (186, 186). +2026-06-24 06:02:57,042 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:02:57,042 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:02:57,042 - +2026-06-24 06:02:57,042 - ### Collecting reconstruction provenance ### +2026-06-24 06:02:57,042 - Reconstruction provenance is collected and initialized. +2026-06-24 06:02:57,042 - +2026-06-24 06:02:57,042 - ### Initializing loss function ### +2026-06-24 06:02:57,042 - Active loss types: +2026-06-24 06:02:57,042 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:02:57,042 - +2026-06-24 06:02:57,042 - ### Initializing constraint function ### +2026-06-24 06:02:57,042 - Active constraint types: +2026-06-24 06:02:57,042 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:02:57,042 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:02:57,042 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:02:57,042 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:02:57,042 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:02:57,042 - +2026-06-24 06:02:57,042 - ### Done initializing PtyRADSolver ### +2026-06-24 06:02:57,042 - +2026-06-24 06:02:57,170 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:02:57,170 - +2026-06-24 06:02:57,170 - ### Initializing PtychoModel model ### +2026-06-24 06:02:57,241 - ### PtychoModel optimizable variables ### +2026-06-24 06:02:57,242 - obja : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:57,242 - objp : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:57,242 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:02:57,242 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:02:57,242 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:02:57,242 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:02:57,242 - +2026-06-24 06:02:57,242 - ### Optimizable variables statitsics ### +2026-06-24 06:02:57,242 - Total measurement values : 4,194,304 +2026-06-24 06:02:57,242 - Total optimizing variables: 266,312 +2026-06-24 06:02:57,242 - Overdetermined ratio : 15.75 +2026-06-24 06:02:57,242 - +2026-06-24 06:02:57,242 - ### Model behavior ### +2026-06-24 06:02:57,242 - Tilt propagator : False +2026-06-24 06:02:57,242 - Change slice thickness : False +2026-06-24 06:02:57,242 - Detector blur : False +2026-06-24 06:02:57,242 - Preload data : True +2026-06-24 06:02:57,242 - On-the-fly meas padding : False +2026-06-24 06:02:57,242 - On-the-fly meas resample : False +2026-06-24 06:02:57,242 - On-the-fly simu match mode: None +2026-06-24 06:02:57,242 - +2026-06-24 06:02:57,284 - ### Done initializing PtychoModel model ### +2026-06-24 06:02:57,284 - +2026-06-24 06:02:57,284 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:02:57,284 - +2026-06-24 06:02:57,284 - ### Generating indices, batches, and output_path ### +2026-06-24 06:02:57,285 - d90 = 27.000 px or 5.400 Ang +2026-06-24 06:02:57,285 - Selecting indices with the 'full' mode +2026-06-24 06:02:57,744 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:02:57,819 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:02:57,819 - Original recon_dir_affixes = ['default'] +2026-06-24 06:02:57,819 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:02:57,825 - Path corrected for compatibility: +2026-06-24 06:02:57,825 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-1.68e+03_phi32_153_C34_-622_phi34_12.7_C41_-3.43e+05_phi41_106_C43_4.49e+05_phi43_356_C45_4.95e+05_phi45_81.9_C50_-4.73e+08_C52_1.22e+07_phi52_13.5_C54_-1.46e+07_phi54_83.1_C56_-5.32e+06_phi56_161 +2026-06-24 06:02:57,825 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161 +2026-06-24 06:02:57,826 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161' is generated! +2026-06-24 06:02:57,973 - +2026-06-24 06:02:57,974 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/20260624_060257_ptyrad_log.txt ### +2026-06-24 06:02:57,974 - +2026-06-24 06:02:57,975 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:02:57,975 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:02:57,975 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:02:59,159 - Iter: 1, Total Loss: 1.0347, loss_single: 1.0347, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:02:59,196 - Iter: 2, Total Loss: 0.9959, loss_single: 0.9959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:02:59,232 - Iter: 3, Total Loss: 0.9649, loss_single: 0.9649, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,268 - Iter: 4, Total Loss: 0.9342, loss_single: 0.9342, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:02:59,303 - Iter: 5, Total Loss: 0.9018, loss_single: 0.9018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,339 - Iter: 6, Total Loss: 0.8711, loss_single: 0.8711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,374 - Iter: 7, Total Loss: 0.8437, loss_single: 0.8437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,409 - Iter: 8, Total Loss: 0.8193, loss_single: 0.8193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,445 - Iter: 9, Total Loss: 0.7947, loss_single: 0.7947, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,480 - Iter: 10, Total Loss: 0.7659, loss_single: 0.7659, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,515 - Iter: 11, Total Loss: 0.7392, loss_single: 0.7392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,551 - Iter: 12, Total Loss: 0.7132, loss_single: 0.7132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,586 - Iter: 13, Total Loss: 0.6856, loss_single: 0.6856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,622 - Iter: 14, Total Loss: 0.6610, loss_single: 0.6610, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,660 - Iter: 15, Total Loss: 0.6391, loss_single: 0.6391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:02:59,695 - Iter: 16, Total Loss: 0.6200, loss_single: 0.6200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,731 - Iter: 17, Total Loss: 0.5990, loss_single: 0.5990, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,766 - Iter: 18, Total Loss: 0.5788, loss_single: 0.5788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,801 - Iter: 19, Total Loss: 0.5617, loss_single: 0.5617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,837 - Iter: 20, Total Loss: 0.5471, loss_single: 0.5471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,872 - Iter: 21, Total Loss: 0.5327, loss_single: 0.5327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,908 - Iter: 22, Total Loss: 0.5168, loss_single: 0.5168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,943 - Iter: 23, Total Loss: 0.5025, loss_single: 0.5025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:02:59,978 - Iter: 24, Total Loss: 0.4924, loss_single: 0.4924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,014 - Iter: 25, Total Loss: 0.4836, loss_single: 0.4836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,050 - Iter: 26, Total Loss: 0.4733, loss_single: 0.4733, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,084 - Iter: 27, Total Loss: 0.4623, loss_single: 0.4623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,120 - Iter: 28, Total Loss: 0.4548, loss_single: 0.4548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,155 - Iter: 29, Total Loss: 0.4495, loss_single: 0.4495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,191 - Iter: 30, Total Loss: 0.4436, loss_single: 0.4436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,226 - Iter: 31, Total Loss: 0.4392, loss_single: 0.4392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,262 - Iter: 32, Total Loss: 0.4344, loss_single: 0.4344, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,297 - Iter: 33, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,333 - Iter: 34, Total Loss: 0.4249, loss_single: 0.4249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:00,371 - Iter: 35, Total Loss: 0.4215, loss_single: 0.4215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:03:00,407 - Iter: 36, Total Loss: 0.4187, loss_single: 0.4187, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,443 - Iter: 37, Total Loss: 0.4163, loss_single: 0.4163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,478 - Iter: 38, Total Loss: 0.4141, loss_single: 0.4141, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,514 - Iter: 39, Total Loss: 0.4123, loss_single: 0.4123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,550 - Iter: 40, Total Loss: 0.4104, loss_single: 0.4104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,587 - Iter: 41, Total Loss: 0.4090, loss_single: 0.4090, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,622 - Iter: 42, Total Loss: 0.4078, loss_single: 0.4078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,658 - Iter: 43, Total Loss: 0.4063, loss_single: 0.4063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,693 - Iter: 44, Total Loss: 0.4049, loss_single: 0.4049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,729 - Iter: 45, Total Loss: 0.4039, loss_single: 0.4039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,764 - Iter: 46, Total Loss: 0.4031, loss_single: 0.4031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,800 - Iter: 47, Total Loss: 0.4023, loss_single: 0.4023, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:00,835 - Iter: 48, Total Loss: 0.4014, loss_single: 0.4014, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,870 - Iter: 49, Total Loss: 0.4005, loss_single: 0.4005, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,905 - Iter: 50, Total Loss: 0.3996, loss_single: 0.3996, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,941 - Iter: 51, Total Loss: 0.3989, loss_single: 0.3989, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:00,977 - Iter: 52, Total Loss: 0.3982, loss_single: 0.3982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,012 - Iter: 53, Total Loss: 0.3974, loss_single: 0.3974, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,047 - Iter: 54, Total Loss: 0.3967, loss_single: 0.3967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,086 - Iter: 55, Total Loss: 0.3960, loss_single: 0.3960, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:03:01,121 - Iter: 56, Total Loss: 0.3954, loss_single: 0.3954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,156 - Iter: 57, Total Loss: 0.3948, loss_single: 0.3948, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,192 - Iter: 58, Total Loss: 0.3942, loss_single: 0.3942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,228 - Iter: 59, Total Loss: 0.3936, loss_single: 0.3936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,263 - Iter: 60, Total Loss: 0.3931, loss_single: 0.3931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,298 - Iter: 61, Total Loss: 0.3925, loss_single: 0.3925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,334 - Iter: 62, Total Loss: 0.3919, loss_single: 0.3919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,369 - Iter: 63, Total Loss: 0.3914, loss_single: 0.3914, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:01,404 - Iter: 64, 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0.3710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:02,653 - Iter: 99, Total Loss: 0.3704, loss_single: 0.3704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:02,689 - Iter: 100, Total Loss: 0.3698, loss_single: 0.3698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:02,802 - Saving summary figures for iter 100 +2026-06-24 06:03:06,468 - ### Finished 100 iterations, averaged iter_t = 0.039167 with std = 0.040 ### +2026-06-24 06:03:06,468 - +2026-06-24 06:03:06,468 - ### The PtyRADSolver is finished in 9.298 sec ### +2026-06-24 06:03:06,468 - diff --git 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/simulation_data3__sample_000033.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/simulation_data3__sample_000033.yaml new file mode 100644 index 0000000000000000000000000000000000000000..22b10cc86825f3c2253c58992c180645ba3c1fb4 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/simulation_data3__sample_000033.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 16.246652603149414 + probe_aberrations: + C10: -184.9245147705078 + C12: -10.09196949005127 + C21: -666.6468505859375 + C23: -698.41162109375 + C30: 1140546.625 + C32: -1678.6466064453125 + C34: -622.021728515625 + C41: -342794.21875 + C43: 448874.75 + C45: 495363.125 + C50: -473188608.0 + C52: 12154104.0 + C54: -14568536.0 + C56: -5317734.0 + phi12: 351.8757732077493 + phi21: 323.6237612155021 + phi23: 157.70518838814584 + phi32: 153.16688285450923 + phi34: 12.702152318344195 + phi41: 105.7486565417217 + phi43: 356.049537885004 + phi45: 81.92114547116036 + phi52: 13.537188194381505 + phi54: 83.11659933064185 + phi56: 160.74215004032197 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.34307581186294556 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000033_measurement.h5 + key: measurement + random_seed: 20261961 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000033 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000033/c30_small__simulation_data3__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-185_C12_-10.1_phi12_352_C21_-667_phi21_324_C23_-698_phi23_158_C30_1.14e+06_C32_-.32e+06_phi56_161/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+0.5_C56_2e+07_phi56_342/20260624_060312_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:03:11,022 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:03:11,022 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:03:11,022 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:03:11,022 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:03:11,022 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:03:11,022 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:03:11,022 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:03:11,022 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:03:11,022 - +2026-06-24 06:03:11,133 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:03:11,133 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:03:11,133 - Accelerator.num_process = 1 +2026-06-24 06:03:11,133 - Accelerator.mixed_precision = no +2026-06-24 06:03:11,143 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:03:11,144 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:03:11,144 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:03:11,144 - +2026-06-24 06:03:11,144 - ### System information ### +2026-06-24 06:03:11,144 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:03:11,144 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:03:11,144 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:03:11,144 - Machine: x86_64 +2026-06-24 06:03:11,144 - Processor: x86_64 +2026-06-24 06:03:11,144 - Available CPU cores: 8 +2026-06-24 06:03:11,144 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:03:11,144 - +2026-06-24 06:03:11,144 - ### GPU information ### +2026-06-24 06:03:11,144 - CUDA Available: True +2026-06-24 06:03:11,144 - CUDA Version: 13.0 +2026-06-24 06:03:11,145 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:03:11,145 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:03:11,145 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:03:11,145 - In addition, Triton does not directly support Windows. +2026-06-24 06:03:11,145 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:03:11,159 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:03:11,160 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:03:11,160 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:03:11,160 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:03:11,160 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:03:11,160 - +2026-06-24 06:03:11,160 - ### Python information ### +2026-06-24 06:03:11,161 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:03:11,161 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:03:11,161 - +2026-06-24 06:03:11,161 - ### Packages information ### +2026-06-24 06:03:11,162 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:03:11,162 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:03:11,163 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:03:11,164 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:03:11,164 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:03:11,164 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:03:11,164 - +2026-06-24 06:03:11,164 - ### Loading params file ### +2026-06-24 06:03:11,164 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000034.yaml +2026-06-24 06:03:11,171 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:03:11,172 - Success! Params file validated and defaults applied. +2026-06-24 06:03:11,172 - +2026-06-24 06:03:11,172 - ### Setting GPU Device ### +2026-06-24 06:03:11,172 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:03:11,172 - +2026-06-24 06:03:11,172 - Random seed: 20261962 provided by params file +2026-06-24 06:03:11,172 - ### Initializing Initializer ### +2026-06-24 06:03:11,172 - init_params are displayed below: +2026-06-24 06:03:11,172 - random_seed: 20261962 +2026-06-24 06:03:11,172 - probe_illum_type: electron +2026-06-24 06:03:11,173 - probe_kv: 200.0 +2026-06-24 06:03:11,173 - probe_conv_angle: 9.154783248901367 +2026-06-24 06:03:11,173 - probe_aberrations: {'C10': -38.287, 'C12': 37.819, 'phi12': 222.209, 'C21': -394.379, 'phi21': 261.426, 'C23': -390.165, 'phi23': 28.342, 'C30': -831967.125, 'C32': 436.701, 'phi32': 284.744, 'C34': -3612.519, 'phi34': 164.22, 'C41': -175738.781, 'phi41': 214.636, 'C43': -330340.969, 'phi43': 174.756, 'C45': -234747.484, 'phi45': 41.345, 'C50': 434172256.0, 'C52': 6429254.5, 'phi52': 90.46, 'C54': -8384286.0, 'phi54': 58.455, 'C56': 19966670.0, 'phi56': 342.099} +2026-06-24 06:03:11,173 - beam_kev: None +2026-06-24 06:03:11,173 - probe_dRn: None +2026-06-24 06:03:11,173 - probe_Rn: None +2026-06-24 06:03:11,173 - probe_D_H: None +2026-06-24 06:03:11,173 - probe_D_FZP: None +2026-06-24 06:03:11,173 - probe_Ls: None +2026-06-24 06:03:11,173 - meas_Npix: 128 +2026-06-24 06:03:11,173 - pos_N_scans: 256 +2026-06-24 06:03:11,173 - pos_N_scan_slow: 16 +2026-06-24 06:03:11,173 - pos_N_scan_fast: 16 +2026-06-24 06:03:11,173 - pos_scan_step_size: 0.34335169196128845 +2026-06-24 06:03:11,173 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:03:11,173 - probe_pmode_max: 6 +2026-06-24 06:03:11,173 - probe_pmode_init_pows: [0.02] +2026-06-24 06:03:11,173 - obj_omode_max: 1 +2026-06-24 06:03:11,173 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:03:11,173 - obj_Nlayer: 1 +2026-06-24 06:03:11,173 - obj_slice_thickness: 20.0 +2026-06-24 06:03:11,173 - simu_Npix: None +2026-06-24 06:03:11,173 - simu_match_mode: None +2026-06-24 06:03:11,173 - meas_permute: None +2026-06-24 06:03:11,173 - meas_reshape: [256, 128, 128] +2026-06-24 06:03:11,173 - meas_flipT: [0, 0, 0] +2026-06-24 06:03:11,173 - meas_crop: None +2026-06-24 06:03:11,173 - meas_pad: None +2026-06-24 06:03:11,173 - meas_resample: None +2026-06-24 06:03:11,173 - meas_add_source_size: None +2026-06-24 06:03:11,173 - meas_add_detector_blur: None +2026-06-24 06:03:11,173 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:03:11,173 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:03:11,173 - meas_add_poisson_noise: None +2026-06-24 06:03:11,173 - meas_export: None +2026-06-24 06:03:11,173 - probe_permute: None +2026-06-24 06:03:11,173 - probe_z_shift: None +2026-06-24 06:03:11,173 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:03:11,173 - pos_scan_flipT: None +2026-06-24 06:03:11,173 - pos_scan_affine: None +2026-06-24 06:03:11,174 - pos_scan_rand_std: 0.15 +2026-06-24 06:03:11,174 - obj_z_crop: None +2026-06-24 06:03:11,174 - obj_z_pad: None +2026-06-24 06:03:11,174 - obj_z_resample: None +2026-06-24 06:03:11,174 - meas_source: file +2026-06-24 06:03:11,174 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000034_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:03:11,174 - probe_source: simu +2026-06-24 06:03:11,174 - probe_params: None +2026-06-24 06:03:11,174 - pos_source: simu +2026-06-24 06:03:11,174 - pos_params: None +2026-06-24 06:03:11,174 - obj_source: simu +2026-06-24 06:03:11,174 - obj_params: None +2026-06-24 06:03:11,174 - tilt_source: simu +2026-06-24 06:03:11,174 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:03:11,174 - +2026-06-24 06:03:11,174 - ### Initializing cache ### +2026-06-24 06:03:11,174 - use_cached_obj = False +2026-06-24 06:03:11,174 - use_cached_probe = False +2026-06-24 06:03:11,174 - use_cached_pos = False +2026-06-24 06:03:11,174 - +2026-06-24 06:03:11,174 - ### Initializing measurements ### +2026-06-24 06:03:11,174 - Loading measurements from source = 'file' +2026-06-24 06:03:11,174 - Detected measurement file type = '.h5' +2026-06-24 06:03:11,246 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:03:11,246 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:03:11,247 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0054) +2026-06-24 06:03:11,248 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:03:11,248 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:03:11,248 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:03:11,249 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:03:11,249 - Normalizing by max of the 2D mean pattern intensity: 0.0036469509 +2026-06-24 06:03:11,250 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:03:11,251 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0169, 1.4921) +2026-06-24 06:03:11,251 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:03:11,253 - Pattern total int. statistics (min, mean, max) = (268.6157, 276.4652, 280.5697), with min/max = 95.7% +2026-06-24 06:03:11,254 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0169, 1.4921) +2026-06-24 06:03:11,254 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:03:11,254 - +2026-06-24 06:03:11,254 - ### Setting up calibration ### +2026-06-24 06:03:11,254 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:03:11,254 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:03:11,254 - Radius of fitted bright field disk (RBF) = 9.18 px with meas_Npix = 128 +2026-06-24 06:03:11,254 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1435 +2026-06-24 06:03:11,254 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:03:11,254 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:03:11,473 - Initial guess: center=(63.64, 63.61), radius=9.18, Gaussian blur std=0.50 +2026-06-24 06:03:11,481 - Final fit: center=(63.64, 63.61), radius=9.18, Gaussian blur std=0.52 +2026-06-24 06:03:11,481 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.34 px with Npix = 128 +2026-06-24 06:03:11,481 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:03:11,481 - +2026-06-24 06:03:11,481 - ### Setting init_variables dict ### +2026-06-24 06:03:11,482 - Derived values given input init_params: +2026-06-24 06:03:11,482 - kv = 200.0 kV +2026-06-24 06:03:11,482 - wavelength = 0.0251 Ang +2026-06-24 06:03:11,482 - conv_angle = 9.154783248901367 mrad +2026-06-24 06:03:11,482 - Npix = 128 px +2026-06-24 06:03:11,482 - dk = 0.0391 Ang^-1 +2026-06-24 06:03:11,482 - kMax = 2.5000 Ang^-1 +2026-06-24 06:03:11,482 - da = 0.9797 mrad +2026-06-24 06:03:11,482 - angleMax = 62.6984 mrad +2026-06-24 06:03:11,482 - RBF = 9.3448 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:03:11,482 - n_alpha = 6.8487 (# conv_angle) +2026-06-24 06:03:11,482 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:03:11,482 - Rayleigh-limited resolution = 1.6711 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:03:11,482 - Real space probe extent = 25.6000 Ang +2026-06-24 06:03:11,482 - +2026-06-24 06:03:11,482 - ### Initializing probe ### +2026-06-24 06:03:11,482 - Loading probe from source = 'simu' +2026-06-24 06:03:11,482 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:03:11,482 - Start simulating STEM probe +2026-06-24 06:03:11,482 - kv = 200.0 kV +2026-06-24 06:03:11,482 - wavelength = 0.0251 Ang +2026-06-24 06:03:11,482 - conv_angle = 9.154783248901367 mrad +2026-06-24 06:03:11,482 - Npix = 128 px +2026-06-24 06:03:11,482 - dk = 0.0391 Ang^-1 +2026-06-24 06:03:11,482 - kMax = 2.5000 Ang^-1 +2026-06-24 06:03:11,483 - alpha_max = 62.6984 mrad +2026-06-24 06:03:11,483 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:03:11,483 - Rayleigh-limited resolution = 1.6711 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:03:11,483 - Real space probe extent = 25.6000 Ang +2026-06-24 06:03:11,483 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:03:11,483 - ------------------------------------------------------------------------------------ +2026-06-24 06:03:11,483 - C1,0 C1 -38.2870 - Defocus (C10 = -df) +2026-06-24 06:03:11,483 - C1,2 A1 37.8190 222.21 2-fold astigmatism +2026-06-24 06:03:11,483 - C2,1 3*B2 -394.3790 261.43 Axial coma +2026-06-24 06:03:11,483 - C2,3 A2 -390.1650 28.34 3-fold astigmatism +2026-06-24 06:03:11,483 - C3,0 C3 -831967.1250 - Spherical aberration +2026-06-24 06:03:11,483 - C3,2 4*S3 436.7010 284.74 Axial star aberration +2026-06-24 06:03:11,483 - C3,4 A3 -3612.5190 164.22 4-fold astigmatism +2026-06-24 06:03:11,483 - C4,1 4*B4 -175738.7810 214.64 Axial coma(4th) +2026-06-24 06:03:11,483 - C4,3 4*D4 -330340.9690 174.76 3-lobe aberration +2026-06-24 06:03:11,483 - C4,5 A4 -234747.4840 41.34 5-fold astigmatism +2026-06-24 06:03:11,483 - C5,0 C5 434172256.0000 - Spherical aberration (5th) +2026-06-24 06:03:11,483 - C5,2 6*S5 6429254.5000 90.46 Axial star aberration(5th) +2026-06-24 06:03:11,483 - C5,4 6*R5 -8384286.0000 58.45 4-lobe aberration +2026-06-24 06:03:11,483 - C5,6 A5 19966670.0000 342.10 6-fold astigmatism +2026-06-24 06:03:11,486 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:03:11,486 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:03:11,486 - Creating 5 new probe modes from the major mode +2026-06-24 06:03:11,486 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:03:11,589 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:03:11,590 - Orthogonalizing 6 pmodes +2026-06-24 06:03:11,593 - Sorting 6 pmodes by their intensities +2026-06-24 06:03:11,593 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:03:11,594 - sum(|probe_data|**2) = 276.47, while meas_total_ints (min, mean, max) = (268.6157, 276.4652, 280.5697) +2026-06-24 06:03:11,594 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:03:11,594 - +2026-06-24 06:03:11,594 - ### Initializing probe positions ### +2026-06-24 06:03:11,594 - Loading probe positions from source = 'simu' +2026-06-24 06:03:11,594 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:03:11,594 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3434, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:03:11,595 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:03:11,596 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:03:11,597 - crop_pos 1st and last px coords (y,x) = ([15, 15], [41, 41]) +2026-06-24 06:03:11,597 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:03:11,597 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:03:11,597 - +2026-06-24 06:03:11,597 - ### Initializing object ### +2026-06-24 06:03:11,597 - Loading object from source = 'simu' +2026-06-24 06:03:11,597 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:03:11,598 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:03:11,598 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 186) +2026-06-24 06:03:11,598 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.2] +2026-06-24 06:03:11,598 - +2026-06-24 06:03:11,599 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:03:11,599 - omode_occu (omode) = float32, (1,) +2026-06-24 06:03:11,599 - +2026-06-24 06:03:11,599 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:03:11,599 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:03:11,599 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:03:11,599 - +2026-06-24 06:03:11,599 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:03:11,599 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:03:11,599 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:03:11,600 - +2026-06-24 06:03:11,600 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:03:11,600 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:03:11,600 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:03:11,600 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:03:11,600 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:03:11,600 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (186, 186). +2026-06-24 06:03:11,600 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:03:11,600 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:03:11,600 - +2026-06-24 06:03:11,600 - ### Collecting reconstruction provenance ### +2026-06-24 06:03:11,600 - Reconstruction provenance is collected and initialized. +2026-06-24 06:03:11,600 - +2026-06-24 06:03:11,600 - ### Initializing loss function ### +2026-06-24 06:03:11,600 - Active loss types: +2026-06-24 06:03:11,600 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:03:11,600 - +2026-06-24 06:03:11,600 - ### Initializing constraint function ### +2026-06-24 06:03:11,600 - Active constraint types: +2026-06-24 06:03:11,600 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:03:11,600 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:03:11,601 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:03:11,601 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:03:11,601 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:03:11,601 - +2026-06-24 06:03:11,601 - ### Done initializing PtyRADSolver ### +2026-06-24 06:03:11,601 - +2026-06-24 06:03:11,727 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:03:11,727 - +2026-06-24 06:03:11,727 - ### Initializing PtychoModel model ### +2026-06-24 06:03:11,796 - ### PtychoModel optimizable variables ### +2026-06-24 06:03:11,797 - obja : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:11,797 - objp : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:11,797 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:03:11,797 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:03:11,797 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:03:11,797 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:11,797 - +2026-06-24 06:03:11,797 - ### Optimizable variables statitsics ### +2026-06-24 06:03:11,797 - Total measurement values : 4,194,304 +2026-06-24 06:03:11,797 - Total optimizing variables: 266,312 +2026-06-24 06:03:11,797 - Overdetermined ratio : 15.75 +2026-06-24 06:03:11,797 - +2026-06-24 06:03:11,797 - ### Model behavior ### +2026-06-24 06:03:11,797 - Tilt propagator : False +2026-06-24 06:03:11,797 - Change slice thickness : False +2026-06-24 06:03:11,797 - Detector blur : False +2026-06-24 06:03:11,797 - Preload data : True +2026-06-24 06:03:11,797 - On-the-fly meas padding : False +2026-06-24 06:03:11,797 - On-the-fly meas resample : False +2026-06-24 06:03:11,797 - On-the-fly simu match mode: None +2026-06-24 06:03:11,797 - +2026-06-24 06:03:11,839 - ### Done initializing PtychoModel model ### +2026-06-24 06:03:11,840 - +2026-06-24 06:03:11,840 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:03:11,840 - +2026-06-24 06:03:11,840 - ### Generating indices, batches, and output_path ### +2026-06-24 06:03:11,841 - d90 = 31.000 px or 6.200 Ang +2026-06-24 06:03:11,841 - Selecting indices with the 'full' mode +2026-06-24 06:03:12,307 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:03:12,382 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:03:12,382 - Original recon_dir_affixes = ['default'] +2026-06-24 06:03:12,382 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:03:12,389 - Path corrected for compatibility: +2026-06-24 06:03:12,389 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+05_C32_437_phi32_285_C34_-3.61e+03_phi34_164_C41_-1.76e+05_phi41_215_C43_-3.3e+05_phi43_175_C45_-2.35e+05_phi45_41.3_C50_4.34e+08_C52_6.43e+06_phi52_90.5_C54_-8.38e+06_phi54_58.5_C56_2e+07_phi56_342 +2026-06-24 06:03:12,389 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+0.5_C56_2e+07_phi56_342 +2026-06-24 06:03:12,390 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+0.5_C56_2e+07_phi56_342' is generated! +2026-06-24 06:03:12,539 - +2026-06-24 06:03:12,540 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+0.5_C56_2e+07_phi56_342/20260624_060312_ptyrad_log.txt ### +2026-06-24 06:03:12,540 - +2026-06-24 06:03:12,542 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:03:12,542 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:03:12,542 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:03:13,737 - Iter: 1, Total Loss: 1.1803, loss_single: 1.1803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:03:13,774 - Iter: 2, Total Loss: 1.1321, loss_single: 1.1321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:13,809 - Iter: 3, Total Loss: 1.0886, loss_single: 1.0886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:13,845 - Iter: 4, Total Loss: 1.0464, loss_single: 1.0464, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:13,880 - Iter: 5, Total Loss: 1.0094, loss_single: 1.0094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:13,915 - Iter: 6, Total Loss: 0.9768, loss_single: 0.9768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:13,951 - Iter: 7, Total Loss: 0.9467, loss_single: 0.9467, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:13,986 - Iter: 8, Total Loss: 0.9195, loss_single: 0.9195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,021 - Iter: 9, Total Loss: 0.9007, loss_single: 0.9007, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,056 - Iter: 10, Total Loss: 0.8833, loss_single: 0.8833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,091 - Iter: 11, Total Loss: 0.8624, loss_single: 0.8624, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,126 - Iter: 12, Total Loss: 0.8472, loss_single: 0.8472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,161 - Iter: 13, Total Loss: 0.8333, loss_single: 0.8333, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,196 - Iter: 14, Total Loss: 0.8201, loss_single: 0.8201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:14,231 - Iter: 15, Total Loss: 0.8104, loss_single: 0.8104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,266 - Iter: 16, Total Loss: 0.7968, loss_single: 0.7968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,301 - Iter: 17, Total Loss: 0.7814, loss_single: 0.7814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,337 - Iter: 18, Total Loss: 0.7683, loss_single: 0.7683, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,372 - Iter: 19, Total Loss: 0.7579, loss_single: 0.7579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:14,407 - Iter: 20, Total Loss: 0.7502, loss_single: 0.7502, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,442 - Iter: 21, Total Loss: 0.7428, loss_single: 0.7428, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,478 - Iter: 22, Total Loss: 0.7354, loss_single: 0.7354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,513 - Iter: 23, Total Loss: 0.7280, loss_single: 0.7280, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,548 - Iter: 24, Total Loss: 0.7202, loss_single: 0.7202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,584 - Iter: 25, Total Loss: 0.7136, loss_single: 0.7136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,619 - Iter: 26, Total Loss: 0.7084, loss_single: 0.7084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,654 - Iter: 27, Total Loss: 0.7037, loss_single: 0.7037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,689 - Iter: 28, Total Loss: 0.6997, loss_single: 0.6997, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,724 - Iter: 29, Total Loss: 0.6961, loss_single: 0.6961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,759 - Iter: 30, Total Loss: 0.6923, loss_single: 0.6923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:14,798 - Iter: 31, Total Loss: 0.6876, loss_single: 0.6876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:03:14,834 - Iter: 32, Total Loss: 0.6836, loss_single: 0.6836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,869 - Iter: 33, Total Loss: 0.6808, loss_single: 0.6808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,904 - Iter: 34, Total Loss: 0.6789, loss_single: 0.6789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:14,939 - Iter: 35, Total Loss: 0.6770, loss_single: 0.6770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:14,974 - Iter: 36, Total Loss: 0.6744, loss_single: 0.6744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,009 - Iter: 37, Total Loss: 0.6718, loss_single: 0.6718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,045 - Iter: 38, Total Loss: 0.6694, loss_single: 0.6694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:15,080 - Iter: 39, Total Loss: 0.6672, loss_single: 0.6672, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,116 - Iter: 40, Total Loss: 0.6645, loss_single: 0.6645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,153 - Iter: 41, Total Loss: 0.6619, loss_single: 0.6619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,188 - Iter: 42, Total Loss: 0.6598, loss_single: 0.6598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,223 - Iter: 43, Total Loss: 0.6579, loss_single: 0.6579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:15,258 - Iter: 44, Total Loss: 0.6559, loss_single: 0.6559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,293 - Iter: 45, Total Loss: 0.6540, loss_single: 0.6540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,328 - Iter: 46, Total Loss: 0.6523, loss_single: 0.6523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,365 - Iter: 47, Total Loss: 0.6505, loss_single: 0.6505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:15,400 - Iter: 48, Total Loss: 0.6489, loss_single: 0.6489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,435 - Iter: 49, Total Loss: 0.6473, loss_single: 0.6473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,470 - Iter: 50, Total Loss: 0.6465, loss_single: 0.6465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,506 - Iter: 51, Total Loss: 0.6458, loss_single: 0.6458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:15,541 - Iter: 52, Total Loss: 0.6449, loss_single: 0.6449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,576 - Iter: 53, Total Loss: 0.6442, loss_single: 0.6442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,611 - Iter: 54, Total Loss: 0.6433, loss_single: 0.6433, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,646 - Iter: 55, Total Loss: 0.6424, loss_single: 0.6424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,681 - Iter: 56, Total Loss: 0.6414, loss_single: 0.6414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,717 - Iter: 57, Total Loss: 0.6406, loss_single: 0.6406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,752 - Iter: 58, Total Loss: 0.6401, loss_single: 0.6401, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,787 - Iter: 59, Total Loss: 0.6396, loss_single: 0.6396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,823 - Iter: 60, Total Loss: 0.6391, loss_single: 0.6391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:15,858 - Iter: 61, Total Loss: 0.6385, loss_single: 0.6385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,893 - Iter: 62, Total Loss: 0.6379, loss_single: 0.6379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,929 - Iter: 63, Total Loss: 0.6374, loss_single: 0.6374, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:15,964 - Iter: 64, 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in 0.035 sec +2026-06-24 06:03:16,175 - Iter: 70, Total Loss: 0.6334, loss_single: 0.6334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,211 - Iter: 71, Total Loss: 0.6330, loss_single: 0.6330, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,246 - Iter: 72, Total Loss: 0.6325, loss_single: 0.6325, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,281 - Iter: 73, Total Loss: 0.6318, loss_single: 0.6318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,317 - Iter: 74, Total Loss: 0.6313, loss_single: 0.6313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:16,352 - Iter: 75, Total Loss: 0.6310, loss_single: 0.6310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,387 - Iter: 76, Total Loss: 0.6306, loss_single: 0.6306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:16,422 - Iter: 77, Total Loss: 0.6303, loss_single: 0.6303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,458 - Iter: 78, Total Loss: 0.6299, loss_single: 0.6299, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,493 - Iter: 79, Total Loss: 0.6296, loss_single: 0.6296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:16,528 - Iter: 80, Total Loss: 0.6292, loss_single: 0.6292, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,563 - Iter: 81, Total Loss: 0.6287, loss_single: 0.6287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,599 - Iter: 82, Total Loss: 0.6282, loss_single: 0.6282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,634 - Iter: 83, Total Loss: 0.6277, loss_single: 0.6277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,669 - Iter: 84, Total Loss: 0.6271, loss_single: 0.6271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,704 - Iter: 85, Total Loss: 0.6265, loss_single: 0.6265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,740 - Iter: 86, Total Loss: 0.6260, loss_single: 0.6260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,775 - Iter: 87, Total Loss: 0.6256, loss_single: 0.6256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,810 - Iter: 88, Total Loss: 0.6253, loss_single: 0.6253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,845 - Iter: 89, Total Loss: 0.6249, loss_single: 0.6249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,881 - Iter: 90, Total Loss: 0.6246, loss_single: 0.6246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,916 - Iter: 91, Total Loss: 0.6242, loss_single: 0.6242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:16,953 - Iter: 92, Total Loss: 0.6239, loss_single: 0.6239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:03:16,988 - Iter: 93, Total Loss: 0.6237, loss_single: 0.6237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,024 - Iter: 94, Total Loss: 0.6235, loss_single: 0.6235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,059 - Iter: 95, Total Loss: 0.6233, loss_single: 0.6233, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,095 - Iter: 96, Total Loss: 0.6230, loss_single: 0.6230, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,130 - Iter: 97, Total Loss: 0.6226, loss_single: 0.6226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,165 - Iter: 98, Total Loss: 0.6222, loss_single: 0.6222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,200 - Iter: 99, Total Loss: 0.6221, loss_single: 0.6221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:03:17,235 - Iter: 100, Total Loss: 0.6218, loss_single: 0.6218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:17,346 - Saving summary figures for iter 100 +2026-06-24 06:03:20,939 - ### Finished 100 iterations, averaged iter_t = 0.03888 with std = 0.040 ### +2026-06-24 06:03:20,939 - +2026-06-24 06:03:20,939 - ### The PtyRADSolver is finished in 9.212 sec ### +2026-06-24 06:03:20,939 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034/c30_small__simulation_data3__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-38.3_C12_37.8_phi12_222_C21_-394_phi21_261_C23_-390_phi23_28.3_C30_-8.32e+0.5_C56_2e+07_phi56_342/simulation_data3__sample_000034.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.154783248901367 + probe_aberrations: + C10: -38.28733825683594 + C12: 37.81923294067383 + C21: -394.37921142578125 + C23: -390.16455078125 + C30: -831967.125 + C32: 436.7008972167969 + C34: -3612.5185546875 + C41: -175738.78125 + C43: -330340.96875 + C45: -234747.484375 + C50: 434172256.0 + C52: 6429254.5 + C54: -8384286.0 + C56: 19966670.0 + phi12: 222.20853868326247 + phi21: 261.4255724445081 + phi23: 28.342373687419197 + phi32: 284.7437289879049 + phi34: 164.22045119590766 + phi41: 214.63551179949746 + phi43: 174.75589504724726 + phi45: 41.34489381979846 + phi52: 90.46014551867276 + phi54: 58.454671369936726 + phi56: 342.0992863166032 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.34335169196128845 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000034_measurement.h5 + key: measurement + random_seed: 20261962 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000034 + 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sha256:71c9061fd690fcfcbd32f215d4853324c2290ce0875d0709d34cf9e46abc8c4c +size 47432 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/20260624_060326_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/20260624_060326_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6780df88cd0b42d4da647cc4cd847e06e0c87f5 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/20260624_060326_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:03:25,526 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:03:25,526 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:03:25,526 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:03:25,526 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:03:25,526 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:03:25,526 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:03:25,526 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:03:25,526 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:03:25,526 - +2026-06-24 06:03:25,634 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:03:25,634 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:03:25,635 - Accelerator.num_process = 1 +2026-06-24 06:03:25,635 - Accelerator.mixed_precision = no +2026-06-24 06:03:25,645 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:03:25,645 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:03:25,645 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:03:25,645 - +2026-06-24 06:03:25,645 - ### System information ### +2026-06-24 06:03:25,645 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:03:25,645 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:03:25,645 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:03:25,646 - Machine: x86_64 +2026-06-24 06:03:25,646 - Processor: x86_64 +2026-06-24 06:03:25,646 - Available CPU cores: 8 +2026-06-24 06:03:25,646 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:03:25,646 - +2026-06-24 06:03:25,646 - ### GPU information ### +2026-06-24 06:03:25,646 - CUDA Available: True +2026-06-24 06:03:25,646 - CUDA Version: 13.0 +2026-06-24 06:03:25,646 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:03:25,646 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:03:25,646 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:03:25,646 - In addition, Triton does not directly support Windows. +2026-06-24 06:03:25,646 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:03:25,675 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:03:25,675 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:03:25,675 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:03:25,675 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:03:25,675 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:03:25,675 - +2026-06-24 06:03:25,675 - ### Python information ### +2026-06-24 06:03:25,677 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:03:25,677 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:03:25,677 - +2026-06-24 06:03:25,677 - ### Packages information ### +2026-06-24 06:03:25,677 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:03:25,678 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:03:25,679 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:03:25,679 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:03:25,680 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:03:25,680 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:03:25,680 - +2026-06-24 06:03:25,680 - ### Loading params file ### +2026-06-24 06:03:25,680 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000035.yaml +2026-06-24 06:03:25,687 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:03:25,688 - Success! Params file validated and defaults applied. +2026-06-24 06:03:25,688 - +2026-06-24 06:03:25,688 - ### Setting GPU Device ### +2026-06-24 06:03:25,688 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:03:25,688 - +2026-06-24 06:03:25,688 - Random seed: 20261963 provided by params file +2026-06-24 06:03:25,688 - ### Initializing Initializer ### +2026-06-24 06:03:25,689 - init_params are displayed below: +2026-06-24 06:03:25,689 - random_seed: 20261963 +2026-06-24 06:03:25,689 - probe_illum_type: electron +2026-06-24 06:03:25,689 - probe_kv: 60.0 +2026-06-24 06:03:25,689 - probe_conv_angle: 9.306949615478516 +2026-06-24 06:03:25,689 - probe_aberrations: {'C10': -22.042, 'C12': 9.407, 'phi12': 230.585, 'C21': 312.756, 'phi21': 77.792, 'C23': -891.294, 'phi23': 10.574, 'C30': 2448782.75, 'C32': -3585.894, 'phi32': 115.004, 'C34': -2926.945, 'phi34': 48.126, 'C41': -227575.812, 'phi41': 313.002, 'C43': -137200.562, 'phi43': 87.845, 'C45': -257039.172, 'phi45': 4.195, 'C50': 497470176.0, 'C52': -14528546.0, 'phi52': 14.159, 'C54': 19948208.0, 'phi54': 324.774, 'C56': 12221815.0, 'phi56': 248.646} +2026-06-24 06:03:25,689 - beam_kev: None +2026-06-24 06:03:25,689 - probe_dRn: None +2026-06-24 06:03:25,689 - probe_Rn: None +2026-06-24 06:03:25,689 - probe_D_H: None +2026-06-24 06:03:25,689 - probe_D_FZP: None +2026-06-24 06:03:25,689 - probe_Ls: None +2026-06-24 06:03:25,689 - meas_Npix: 128 +2026-06-24 06:03:25,689 - pos_N_scans: 256 +2026-06-24 06:03:25,689 - pos_N_scan_slow: 16 +2026-06-24 06:03:25,689 - pos_N_scan_fast: 16 +2026-06-24 06:03:25,689 - pos_scan_step_size: 0.5022904872894287 +2026-06-24 06:03:25,689 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:03:25,689 - probe_pmode_max: 6 +2026-06-24 06:03:25,689 - probe_pmode_init_pows: [0.02] +2026-06-24 06:03:25,689 - obj_omode_max: 1 +2026-06-24 06:03:25,689 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:03:25,689 - obj_Nlayer: 1 +2026-06-24 06:03:25,689 - obj_slice_thickness: 20.0 +2026-06-24 06:03:25,689 - simu_Npix: None +2026-06-24 06:03:25,689 - simu_match_mode: None +2026-06-24 06:03:25,689 - meas_permute: None +2026-06-24 06:03:25,689 - meas_reshape: [256, 128, 128] +2026-06-24 06:03:25,689 - meas_flipT: [0, 0, 0] +2026-06-24 06:03:25,689 - meas_crop: None +2026-06-24 06:03:25,689 - meas_pad: None +2026-06-24 06:03:25,689 - meas_resample: None +2026-06-24 06:03:25,689 - meas_add_source_size: None +2026-06-24 06:03:25,689 - meas_add_detector_blur: None +2026-06-24 06:03:25,689 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:03:25,689 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:03:25,689 - meas_add_poisson_noise: None +2026-06-24 06:03:25,689 - meas_export: None +2026-06-24 06:03:25,690 - probe_permute: None +2026-06-24 06:03:25,690 - probe_z_shift: None +2026-06-24 06:03:25,690 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:03:25,690 - pos_scan_flipT: None +2026-06-24 06:03:25,690 - pos_scan_affine: None +2026-06-24 06:03:25,690 - pos_scan_rand_std: 0.15 +2026-06-24 06:03:25,690 - obj_z_crop: None +2026-06-24 06:03:25,690 - obj_z_pad: None +2026-06-24 06:03:25,690 - obj_z_resample: None +2026-06-24 06:03:25,690 - meas_source: file +2026-06-24 06:03:25,690 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000035_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:03:25,690 - probe_source: simu +2026-06-24 06:03:25,690 - probe_params: None +2026-06-24 06:03:25,690 - pos_source: simu +2026-06-24 06:03:25,690 - pos_params: None +2026-06-24 06:03:25,690 - obj_source: simu +2026-06-24 06:03:25,690 - obj_params: None +2026-06-24 06:03:25,690 - tilt_source: simu +2026-06-24 06:03:25,690 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:03:25,690 - +2026-06-24 06:03:25,690 - ### Initializing cache ### +2026-06-24 06:03:25,690 - use_cached_obj = False +2026-06-24 06:03:25,690 - use_cached_probe = False +2026-06-24 06:03:25,690 - use_cached_pos = False +2026-06-24 06:03:25,690 - +2026-06-24 06:03:25,690 - ### Initializing measurements ### +2026-06-24 06:03:25,690 - Loading measurements from source = 'file' +2026-06-24 06:03:25,690 - Detected measurement file type = '.h5' +2026-06-24 06:03:25,763 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:03:25,763 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:03:25,765 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0146) +2026-06-24 06:03:25,765 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:03:25,765 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:03:25,767 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:03:25,767 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:03:25,767 - Normalizing by max of the 2D mean pattern intensity: 0.013429407 +2026-06-24 06:03:25,768 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:03:25,769 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0046, 1.0905) +2026-06-24 06:03:25,770 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:03:25,771 - Pattern total int. statistics (min, mean, max) = (73.7097, 74.6678, 75.4500), with min/max = 97.7% +2026-06-24 06:03:25,772 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0046, 1.0905) +2026-06-24 06:03:25,772 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:03:25,772 - +2026-06-24 06:03:25,772 - ### Setting up calibration ### +2026-06-24 06:03:25,772 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:03:25,772 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:03:25,772 - Radius of fitted bright field disk (RBF) = 4.82 px with meas_Npix = 128 +2026-06-24 06:03:25,773 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0753 +2026-06-24 06:03:25,773 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:03:25,773 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:03:25,992 - Initial guess: center=(63.62, 63.62), radius=4.82, Gaussian blur std=0.50 +2026-06-24 06:03:26,002 - Final fit: center=(63.62, 63.62), radius=4.82, Gaussian blur std=0.62 +2026-06-24 06:03:26,002 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 4.90 px with Npix = 128 +2026-06-24 06:03:26,002 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:03:26,002 - +2026-06-24 06:03:26,002 - ### Setting init_variables dict ### +2026-06-24 06:03:26,003 - Derived values given input init_params: +2026-06-24 06:03:26,003 - kv = 60.0 kV +2026-06-24 06:03:26,003 - wavelength = 0.0487 Ang +2026-06-24 06:03:26,003 - conv_angle = 9.306949615478516 mrad +2026-06-24 06:03:26,003 - Npix = 128 px +2026-06-24 06:03:26,003 - dk = 0.0391 Ang^-1 +2026-06-24 06:03:26,003 - kMax = 2.5000 Ang^-1 +2026-06-24 06:03:26,003 - da = 1.9008 mrad +2026-06-24 06:03:26,003 - angleMax = 121.6515 mrad +2026-06-24 06:03:26,003 - RBF = 4.8963 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:03:26,003 - n_alpha = 13.0710 (# conv_angle) +2026-06-24 06:03:26,003 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:03:26,003 - Rayleigh-limited resolution = 3.1893 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:03:26,003 - Real space probe extent = 25.6000 Ang +2026-06-24 06:03:26,003 - +2026-06-24 06:03:26,003 - ### Initializing probe ### +2026-06-24 06:03:26,003 - Loading probe from source = 'simu' +2026-06-24 06:03:26,003 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:03:26,003 - Start simulating STEM probe +2026-06-24 06:03:26,003 - kv = 60.0 kV +2026-06-24 06:03:26,003 - wavelength = 0.0487 Ang +2026-06-24 06:03:26,003 - conv_angle = 9.306949615478516 mrad +2026-06-24 06:03:26,003 - Npix = 128 px +2026-06-24 06:03:26,003 - dk = 0.0391 Ang^-1 +2026-06-24 06:03:26,003 - kMax = 2.5000 Ang^-1 +2026-06-24 06:03:26,003 - alpha_max = 121.6515 mrad +2026-06-24 06:03:26,004 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:03:26,004 - Rayleigh-limited resolution = 3.1893 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:03:26,004 - Real space probe extent = 25.6000 Ang +2026-06-24 06:03:26,004 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:03:26,004 - ------------------------------------------------------------------------------------ +2026-06-24 06:03:26,004 - C1,0 C1 -22.0420 - Defocus (C10 = -df) +2026-06-24 06:03:26,004 - C1,2 A1 9.4070 230.59 2-fold astigmatism +2026-06-24 06:03:26,004 - C2,1 3*B2 312.7560 77.79 Axial coma +2026-06-24 06:03:26,004 - C2,3 A2 -891.2940 10.57 3-fold astigmatism +2026-06-24 06:03:26,004 - C3,0 C3 2448782.7500 - Spherical aberration +2026-06-24 06:03:26,004 - C3,2 4*S3 -3585.8940 115.00 Axial star aberration +2026-06-24 06:03:26,004 - C3,4 A3 -2926.9450 48.13 4-fold astigmatism +2026-06-24 06:03:26,004 - C4,1 4*B4 -227575.8120 313.00 Axial coma(4th) +2026-06-24 06:03:26,004 - C4,3 4*D4 -137200.5620 87.84 3-lobe aberration +2026-06-24 06:03:26,004 - C4,5 A4 -257039.1720 4.20 5-fold astigmatism +2026-06-24 06:03:26,004 - C5,0 C5 497470176.0000 - Spherical aberration (5th) +2026-06-24 06:03:26,004 - C5,2 6*S5 -14528546.0000 14.16 Axial star aberration(5th) +2026-06-24 06:03:26,004 - C5,4 6*R5 19948208.0000 324.77 4-lobe aberration +2026-06-24 06:03:26,004 - C5,6 A5 12221815.0000 248.65 6-fold astigmatism +2026-06-24 06:03:26,007 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:03:26,007 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:03:26,007 - Creating 5 new probe modes from the major mode +2026-06-24 06:03:26,007 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:03:26,013 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:03:26,014 - Orthogonalizing 6 pmodes +2026-06-24 06:03:26,017 - Sorting 6 pmodes by their intensities +2026-06-24 06:03:26,017 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:03:26,018 - sum(|probe_data|**2) = 74.67, while meas_total_ints (min, mean, max) = (73.7097, 74.6678, 75.4500) +2026-06-24 06:03:26,018 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:03:26,018 - +2026-06-24 06:03:26,018 - ### Initializing probe positions ### +2026-06-24 06:03:26,018 - Loading probe positions from source = 'simu' +2026-06-24 06:03:26,018 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:03:26,018 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5023, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:03:26,018 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:03:26,020 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:03:26,020 - crop_pos 1st and last px coords (y,x) = ([16, 16], [54, 54]) +2026-06-24 06:03:26,021 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:03:26,021 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:03:26,021 - +2026-06-24 06:03:26,021 - ### Initializing object ### +2026-06-24 06:03:26,021 - Loading object from source = 'simu' +2026-06-24 06:03:26,021 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:03:26,022 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:03:26,022 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 200, 200) +2026-06-24 06:03:26,022 - object extent (Z, Y, X) (Ang) = [20. 40. 40.] +2026-06-24 06:03:26,022 - +2026-06-24 06:03:26,023 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:03:26,023 - omode_occu (omode) = float32, (1,) +2026-06-24 06:03:26,023 - +2026-06-24 06:03:26,023 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:03:26,023 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 06:03:26,023 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:03:26,023 - +2026-06-24 06:03:26,023 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:03:26,023 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:03:26,023 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:03:26,024 - +2026-06-24 06:03:26,024 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:03:26,024 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:03:26,024 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:03:26,024 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:03:26,024 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:03:26,024 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (200, 200). +2026-06-24 06:03:26,024 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:03:26,024 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:03:26,024 - +2026-06-24 06:03:26,024 - ### Collecting reconstruction provenance ### +2026-06-24 06:03:26,024 - Reconstruction provenance is collected and initialized. +2026-06-24 06:03:26,024 - +2026-06-24 06:03:26,024 - ### Initializing loss function ### +2026-06-24 06:03:26,024 - Active loss types: +2026-06-24 06:03:26,024 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:03:26,024 - +2026-06-24 06:03:26,024 - ### Initializing constraint function ### +2026-06-24 06:03:26,024 - Active constraint types: +2026-06-24 06:03:26,024 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:03:26,024 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:03:26,024 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:03:26,025 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:03:26,025 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:03:26,025 - +2026-06-24 06:03:26,025 - ### Done initializing PtyRADSolver ### +2026-06-24 06:03:26,025 - +2026-06-24 06:03:26,153 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:03:26,153 - +2026-06-24 06:03:26,153 - ### Initializing PtychoModel model ### +2026-06-24 06:03:26,224 - ### PtychoModel optimizable variables ### +2026-06-24 06:03:26,224 - obja : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:26,225 - objp : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:26,225 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:03:26,225 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:03:26,225 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:03:26,225 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:03:26,225 - +2026-06-24 06:03:26,225 - ### Optimizable variables statitsics ### +2026-06-24 06:03:26,225 - Total measurement values : 4,194,304 +2026-06-24 06:03:26,225 - Total optimizing variables: 277,120 +2026-06-24 06:03:26,225 - Overdetermined ratio : 15.14 +2026-06-24 06:03:26,225 - +2026-06-24 06:03:26,225 - ### Model behavior ### +2026-06-24 06:03:26,225 - Tilt propagator : False +2026-06-24 06:03:26,225 - Change slice thickness : False +2026-06-24 06:03:26,225 - Detector blur : False +2026-06-24 06:03:26,225 - Preload data : True +2026-06-24 06:03:26,225 - On-the-fly meas padding : False +2026-06-24 06:03:26,225 - On-the-fly meas resample : False +2026-06-24 06:03:26,225 - On-the-fly simu match mode: None +2026-06-24 06:03:26,225 - +2026-06-24 06:03:26,266 - ### Done initializing PtychoModel model ### +2026-06-24 06:03:26,267 - +2026-06-24 06:03:26,267 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:03:26,267 - +2026-06-24 06:03:26,267 - ### Generating indices, batches, and output_path ### +2026-06-24 06:03:26,268 - d90 = 51.000 px or 10.200 Ang +2026-06-24 06:03:26,268 - Selecting indices with the 'full' mode +2026-06-24 06:03:26,727 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:03:26,807 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:03:26,807 - Original recon_dir_affixes = ['default'] +2026-06-24 06:03:26,807 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:03:26,814 - Path corrected for compatibility: +2026-06-24 06:03:26,814 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.59e+03_phi32_115_C34_-2.93e+03_phi34_48.1_C41_-2.28e+05_phi41_313_C43_-1.37e+05_phi43_87.8_C45_-2.57e+05_phi45_4.2_C50_4.97e+08_C52_-1.45e+07_phi52_14.2_C54_1.99e+07_phi54_325_C56_1.22e+07_phi56_249 +2026-06-24 06:03:26,814 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249 +2026-06-24 06:03:26,816 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249' is generated! +2026-06-24 06:03:26,971 - +2026-06-24 06:03:26,972 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/20260624_060326_ptyrad_log.txt ### +2026-06-24 06:03:26,972 - +2026-06-24 06:03:26,973 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:03:26,973 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:03:26,973 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:03:28,171 - Iter: 1, Total Loss: 2.0284, loss_single: 2.0284, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:03:28,208 - Iter: 2, Total Loss: 1.8608, loss_single: 1.8608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:03:28,245 - Iter: 3, Total Loss: 1.7399, loss_single: 1.7399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,281 - Iter: 4, Total Loss: 1.6348, loss_single: 1.6348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,316 - Iter: 5, Total Loss: 1.5379, loss_single: 1.5379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,352 - Iter: 6, Total Loss: 1.4359, loss_single: 1.4359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,388 - Iter: 7, Total Loss: 1.3449, loss_single: 1.3449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,423 - Iter: 8, Total Loss: 1.2747, loss_single: 1.2747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,459 - Iter: 9, Total Loss: 1.1988, loss_single: 1.1988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,495 - Iter: 10, Total Loss: 1.1196, loss_single: 1.1196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,532 - Iter: 11, Total Loss: 1.0548, loss_single: 1.0548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,568 - Iter: 12, Total Loss: 0.9926, loss_single: 0.9926, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,604 - Iter: 13, Total Loss: 0.9139, loss_single: 0.9139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,640 - Iter: 14, Total Loss: 0.8287, loss_single: 0.8287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,676 - Iter: 15, Total Loss: 0.7562, loss_single: 0.7562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,712 - Iter: 16, Total Loss: 0.6991, loss_single: 0.6991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,748 - Iter: 17, Total Loss: 0.6732, loss_single: 0.6732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,784 - Iter: 18, Total Loss: 0.6598, loss_single: 0.6598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,820 - Iter: 19, Total Loss: 0.6404, loss_single: 0.6404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,856 - Iter: 20, Total Loss: 0.6262, loss_single: 0.6262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,892 - Iter: 21, Total Loss: 0.6130, loss_single: 0.6130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,928 - Iter: 22, Total Loss: 0.6020, loss_single: 0.6020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:28,964 - Iter: 23, Total Loss: 0.5901, loss_single: 0.5901, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:28,999 - Iter: 24, Total Loss: 0.5747, loss_single: 0.5747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:29,035 - Iter: 25, Total Loss: 0.5671, loss_single: 0.5671, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:29,071 - Iter: 26, Total Loss: 0.5637, loss_single: 0.5637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:29,107 - Iter: 27, Total Loss: 0.5603, loss_single: 0.5603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:03:29,143 - Iter: 28, Total Loss: 0.5555, loss_single: 0.5555, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:03:29,178 - Iter: 29, Total Loss: 0.5491, loss_single: 0.5491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/simulation_data3__sample_000035.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/simulation_data3__sample_000035.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0b9f30760829904fed5295becc90fd22d762724f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/simulation_data3__sample_000035.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 9.306949615478516 + probe_aberrations: + C10: -22.042377471923828 + C12: 9.406610488891602 + C21: 312.7564697265625 + C23: -891.2936401367188 + C30: 2448782.75 + C32: -3585.89404296875 + C34: -2926.9453125 + C41: -227575.8125 + C43: -137200.5625 + C45: -257039.171875 + C50: 497470176.0 + C52: -14528546.0 + C54: 19948208.0 + C56: 12221815.0 + phi12: 230.5849733983394 + phi21: 77.79170189142987 + phi23: 10.573725354090238 + phi32: 115.00393852749333 + phi34: 48.12553679757194 + phi41: 313.00156030132496 + phi43: 87.84484559490737 + phi45: 4.19523580379747 + phi52: 14.159336465499628 + phi54: 324.77407435475897 + phi56: 248.64647975271097 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5022904872894287 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000035_measurement.h5 + key: measurement + random_seed: 20261963 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000035 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:00ca7da7c4282783538f4c070fa748a7c0523878b037e30e4695b6c5b5cf9933 +size 1081173 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..b57a15dd112014e09a60e34b6121b355ac68f6ac --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000035/c30_small__simulation_data3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_9.41_phi12_231_C21_313_phi21_77.8_C23_-891_phi23_10.6_C30_2.45e+06_C32_-3.22e+07_phi56_249/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b8748d10cb97b04bcdc33c6c504a9e5519defa845935ec4501f4ff5f82b8f4ad +size 49615 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/20260624_060554_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/20260624_060554_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..4cfc5dbf7de4ea42db14f708db0376180276f1a8 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/20260624_060554_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:05:52,627 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:05:52,627 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:05:52,627 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:05:52,627 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:05:52,627 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:05:52,627 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:05:52,627 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:05:52,627 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:05:52,627 - +2026-06-24 06:05:52,735 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:05:52,735 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:05:52,735 - Accelerator.num_process = 1 +2026-06-24 06:05:52,735 - Accelerator.mixed_precision = no +2026-06-24 06:05:52,745 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:05:52,746 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:05:52,746 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:05:52,746 - +2026-06-24 06:05:52,746 - ### System information ### +2026-06-24 06:05:52,746 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:05:52,746 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:05:52,746 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:05:52,746 - Machine: x86_64 +2026-06-24 06:05:52,746 - Processor: x86_64 +2026-06-24 06:05:52,746 - Available CPU cores: 8 +2026-06-24 06:05:52,746 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:05:52,746 - +2026-06-24 06:05:52,746 - ### GPU information ### +2026-06-24 06:05:52,746 - CUDA Available: True +2026-06-24 06:05:52,746 - CUDA Version: 13.0 +2026-06-24 06:05:52,747 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:05:52,747 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:05:52,747 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:05:52,747 - In addition, Triton does not directly support Windows. +2026-06-24 06:05:52,747 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:05:52,762 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:05:52,762 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:05:52,762 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:05:52,762 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:05:52,762 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:05:52,762 - +2026-06-24 06:05:52,762 - ### Python information ### +2026-06-24 06:05:52,764 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:05:52,764 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:05:52,764 - +2026-06-24 06:05:52,764 - ### Packages information ### +2026-06-24 06:05:52,764 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:05:52,765 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:05:52,766 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:05:52,766 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:05:52,767 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:05:52,767 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:05:52,767 - +2026-06-24 06:05:52,767 - ### Loading params file ### +2026-06-24 06:05:52,767 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data3__sample_000045.yaml +2026-06-24 06:05:52,774 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:05:52,775 - Success! Params file validated and defaults applied. +2026-06-24 06:05:52,775 - +2026-06-24 06:05:52,775 - ### Setting GPU Device ### +2026-06-24 06:05:52,775 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:05:52,775 - +2026-06-24 06:05:52,775 - Random seed: 20261973 provided by params file +2026-06-24 06:05:52,775 - ### Initializing Initializer ### +2026-06-24 06:05:52,775 - init_params are displayed below: +2026-06-24 06:05:52,775 - random_seed: 20261973 +2026-06-24 06:05:52,775 - probe_illum_type: electron +2026-06-24 06:05:52,775 - probe_kv: 160.0 +2026-06-24 06:05:52,775 - probe_conv_angle: 14.142257690429688 +2026-06-24 06:05:52,775 - probe_aberrations: {'C10': -347.294, 'C12': 27.606, 'phi12': 165.97, 'C21': -227.645, 'phi21': 39.717, 'C23': 882.355, 'phi23': 149.152, 'C30': 4251283.5, 'C32': 5753.911, 'phi32': 155.145, 'C34': -6022.483, 'phi34': 276.835, 'C41': 383904.094, 'phi41': 107.329, 'C43': -254520.281, 'phi43': 59.896, 'C45': 260293.594, 'phi45': 190.748, 'C50': -270716960.0, 'C52': -12610341.0, 'phi52': 72.587, 'C54': -18151722.0, 'phi54': 254.346, 'C56': -8993279.0, 'phi56': 243.671} +2026-06-24 06:05:52,776 - beam_kev: None +2026-06-24 06:05:52,776 - probe_dRn: None +2026-06-24 06:05:52,776 - probe_Rn: None +2026-06-24 06:05:52,776 - probe_D_H: None +2026-06-24 06:05:52,776 - probe_D_FZP: None +2026-06-24 06:05:52,776 - probe_Ls: None +2026-06-24 06:05:52,776 - meas_Npix: 128 +2026-06-24 06:05:52,776 - pos_N_scans: 256 +2026-06-24 06:05:52,776 - pos_N_scan_slow: 16 +2026-06-24 06:05:52,776 - pos_N_scan_fast: 16 +2026-06-24 06:05:52,776 - pos_scan_step_size: 0.49196022748947144 +2026-06-24 06:05:52,776 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:05:52,776 - probe_pmode_max: 6 +2026-06-24 06:05:52,776 - probe_pmode_init_pows: [0.02] +2026-06-24 06:05:52,776 - obj_omode_max: 1 +2026-06-24 06:05:52,776 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:05:52,776 - obj_Nlayer: 1 +2026-06-24 06:05:52,776 - obj_slice_thickness: 20.0 +2026-06-24 06:05:52,776 - simu_Npix: None +2026-06-24 06:05:52,776 - simu_match_mode: None +2026-06-24 06:05:52,776 - meas_permute: None +2026-06-24 06:05:52,776 - meas_reshape: [256, 128, 128] +2026-06-24 06:05:52,776 - meas_flipT: [0, 0, 0] +2026-06-24 06:05:52,776 - meas_crop: None +2026-06-24 06:05:52,776 - meas_pad: None +2026-06-24 06:05:52,776 - meas_resample: None +2026-06-24 06:05:52,776 - meas_add_source_size: None +2026-06-24 06:05:52,776 - meas_add_detector_blur: None +2026-06-24 06:05:52,776 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:05:52,776 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:05:52,776 - meas_add_poisson_noise: None +2026-06-24 06:05:52,776 - meas_export: None +2026-06-24 06:05:52,776 - probe_permute: None +2026-06-24 06:05:52,776 - probe_z_shift: None +2026-06-24 06:05:52,776 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:05:52,776 - pos_scan_flipT: None +2026-06-24 06:05:52,776 - pos_scan_affine: None +2026-06-24 06:05:52,776 - pos_scan_rand_std: 0.15 +2026-06-24 06:05:52,776 - obj_z_crop: None +2026-06-24 06:05:52,776 - obj_z_pad: None +2026-06-24 06:05:52,777 - obj_z_resample: None +2026-06-24 06:05:52,777 - meas_source: file +2026-06-24 06:05:52,777 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000045_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:05:52,777 - probe_source: simu +2026-06-24 06:05:52,777 - probe_params: None +2026-06-24 06:05:52,777 - pos_source: simu +2026-06-24 06:05:52,777 - pos_params: None +2026-06-24 06:05:52,777 - obj_source: simu +2026-06-24 06:05:52,777 - obj_params: None +2026-06-24 06:05:52,777 - tilt_source: simu +2026-06-24 06:05:52,777 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:05:52,777 - +2026-06-24 06:05:52,777 - ### Initializing cache ### +2026-06-24 06:05:52,777 - use_cached_obj = False +2026-06-24 06:05:52,777 - use_cached_probe = False +2026-06-24 06:05:52,777 - use_cached_pos = False +2026-06-24 06:05:52,777 - +2026-06-24 06:05:52,777 - ### Initializing measurements ### +2026-06-24 06:05:52,777 - Loading measurements from source = 'file' +2026-06-24 06:05:52,777 - Detected measurement file type = '.h5' +2026-06-24 06:05:52,848 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:05:52,849 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:05:52,850 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0032) +2026-06-24 06:05:52,850 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:05:52,850 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:05:52,852 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:05:52,852 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:05:52,853 - Normalizing by max of the 2D mean pattern intensity: 0.0020312194 +2026-06-24 06:05:52,853 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:05:52,855 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0303, 1.5888) +2026-06-24 06:05:52,855 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:05:52,857 - Pattern total int. statistics (min, mean, max) = (487.9175, 496.1851, 504.8072), with min/max = 96.7% +2026-06-24 06:05:52,858 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0303, 1.5888) +2026-06-24 06:05:52,858 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:05:52,858 - +2026-06-24 06:05:52,858 - ### Setting up calibration ### +2026-06-24 06:05:52,858 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:05:52,858 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:05:52,858 - Radius of fitted bright field disk (RBF) = 12.51 px with meas_Npix = 128 +2026-06-24 06:05:52,858 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1955 +2026-06-24 06:05:52,858 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:05:52,858 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:05:53,079 - Initial guess: center=(63.63, 63.63), radius=12.51, Gaussian blur std=0.50 +2026-06-24 06:05:53,090 - Final fit: center=(63.63, 63.63), radius=12.51, Gaussian blur std=0.55 +2026-06-24 06:05:53,090 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.70 px with Npix = 128 +2026-06-24 06:05:53,090 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:05:53,090 - +2026-06-24 06:05:53,090 - ### Setting init_variables dict ### +2026-06-24 06:05:53,090 - Derived values given input init_params: +2026-06-24 06:05:53,090 - kv = 160.0 kV +2026-06-24 06:05:53,090 - wavelength = 0.0285 Ang +2026-06-24 06:05:53,090 - conv_angle = 14.142257690429688 mrad +2026-06-24 06:05:53,090 - Npix = 128 px +2026-06-24 06:05:53,090 - dk = 0.0391 Ang^-1 +2026-06-24 06:05:53,090 - kMax = 2.5000 Ang^-1 +2026-06-24 06:05:53,090 - da = 1.1137 mrad +2026-06-24 06:05:53,090 - angleMax = 71.2751 mrad +2026-06-24 06:05:53,090 - RBF = 12.6987 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:05:53,090 - n_alpha = 5.0399 (# conv_angle) +2026-06-24 06:05:53,090 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:05:53,090 - Rayleigh-limited resolution = 1.2297 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:05:53,090 - Real space probe extent = 25.6000 Ang +2026-06-24 06:05:53,090 - +2026-06-24 06:05:53,090 - ### Initializing probe ### +2026-06-24 06:05:53,090 - Loading probe from source = 'simu' +2026-06-24 06:05:53,090 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:05:53,091 - Start simulating STEM probe +2026-06-24 06:05:53,091 - kv = 160.0 kV +2026-06-24 06:05:53,091 - wavelength = 0.0285 Ang +2026-06-24 06:05:53,091 - conv_angle = 14.142257690429688 mrad +2026-06-24 06:05:53,091 - Npix = 128 px +2026-06-24 06:05:53,091 - dk = 0.0391 Ang^-1 +2026-06-24 06:05:53,091 - kMax = 2.5000 Ang^-1 +2026-06-24 06:05:53,091 - alpha_max = 71.2751 mrad +2026-06-24 06:05:53,091 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:05:53,091 - Rayleigh-limited resolution = 1.2297 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:05:53,091 - Real space probe extent = 25.6000 Ang +2026-06-24 06:05:53,091 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:05:53,091 - ------------------------------------------------------------------------------------- +2026-06-24 06:05:53,091 - C1,0 C1 -347.2940 - Defocus (C10 = -df) +2026-06-24 06:05:53,091 - C1,2 A1 27.6060 165.97 2-fold astigmatism +2026-06-24 06:05:53,091 - C2,1 3*B2 -227.6450 39.72 Axial coma +2026-06-24 06:05:53,091 - C2,3 A2 882.3550 149.15 3-fold astigmatism +2026-06-24 06:05:53,091 - C3,0 C3 4251283.5000 - Spherical aberration +2026-06-24 06:05:53,091 - C3,2 4*S3 5753.9110 155.15 Axial star aberration +2026-06-24 06:05:53,091 - C3,4 A3 -6022.4830 276.83 4-fold astigmatism +2026-06-24 06:05:53,091 - C4,1 4*B4 383904.0940 107.33 Axial coma(4th) +2026-06-24 06:05:53,091 - C4,3 4*D4 -254520.2810 59.90 3-lobe aberration +2026-06-24 06:05:53,091 - C4,5 A4 260293.5940 190.75 5-fold astigmatism +2026-06-24 06:05:53,091 - C5,0 C5 -270716960.0000 - Spherical aberration (5th) +2026-06-24 06:05:53,091 - C5,2 6*S5 -12610341.0000 72.59 Axial star aberration(5th) +2026-06-24 06:05:53,091 - C5,4 6*R5 -18151722.0000 254.35 4-lobe aberration +2026-06-24 06:05:53,091 - C5,6 A5 -8993279.0000 243.67 6-fold astigmatism +2026-06-24 06:05:53,094 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:05:53,094 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:05:53,094 - Creating 5 new probe modes from the major mode +2026-06-24 06:05:53,094 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:05:53,264 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:05:53,265 - Orthogonalizing 6 pmodes +2026-06-24 06:05:53,269 - Sorting 6 pmodes by their intensities +2026-06-24 06:05:53,269 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:05:53,270 - sum(|probe_data|**2) = 496.19, while meas_total_ints (min, mean, max) = (487.9175, 496.1851, 504.8072) +2026-06-24 06:05:53,270 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:05:53,270 - +2026-06-24 06:05:53,270 - ### Initializing probe positions ### +2026-06-24 06:05:53,270 - Loading probe positions from source = 'simu' +2026-06-24 06:05:53,270 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:05:53,270 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4920, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:05:53,270 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:05:53,272 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:05:53,272 - crop_pos 1st and last px coords (y,x) = ([16, 16], [53, 54]) +2026-06-24 06:05:53,272 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:05:53,273 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:05:53,273 - +2026-06-24 06:05:53,273 - ### Initializing object ### +2026-06-24 06:05:53,273 - Loading object from source = 'simu' +2026-06-24 06:05:53,273 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:05:53,274 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:05:53,274 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 06:05:53,274 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 06:05:53,274 - +2026-06-24 06:05:53,274 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:05:53,274 - omode_occu (omode) = float32, (1,) +2026-06-24 06:05:53,274 - +2026-06-24 06:05:53,275 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:05:53,275 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:05:53,275 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:05:53,275 - +2026-06-24 06:05:53,275 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:05:53,275 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:05:53,275 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:05:53,275 - +2026-06-24 06:05:53,275 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:05:53,275 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:05:53,276 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:05:53,276 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:05:53,276 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:05:53,276 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 06:05:53,276 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:05:53,276 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:05:53,276 - +2026-06-24 06:05:53,276 - ### Collecting reconstruction provenance ### +2026-06-24 06:05:53,276 - Reconstruction provenance is collected and initialized. +2026-06-24 06:05:53,276 - +2026-06-24 06:05:53,276 - ### Initializing loss function ### +2026-06-24 06:05:53,276 - Active loss types: +2026-06-24 06:05:53,276 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:05:53,276 - +2026-06-24 06:05:53,276 - ### Initializing constraint function ### +2026-06-24 06:05:53,276 - Active constraint types: +2026-06-24 06:05:53,276 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:05:53,276 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:05:53,276 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:05:53,276 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:05:53,276 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:05:53,277 - +2026-06-24 06:05:53,277 - ### Done initializing PtyRADSolver ### +2026-06-24 06:05:53,277 - +2026-06-24 06:05:53,402 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:05:53,402 - +2026-06-24 06:05:53,402 - ### Initializing PtychoModel model ### +2026-06-24 06:05:53,471 - ### PtychoModel optimizable variables ### +2026-06-24 06:05:53,471 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:05:53,472 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:05:53,472 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:05:53,472 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:05:53,472 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:05:53,472 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:05:53,472 - +2026-06-24 06:05:53,472 - ### Optimizable variables statitsics ### +2026-06-24 06:05:53,472 - Total measurement values : 4,194,304 +2026-06-24 06:05:53,472 - Total optimizing variables: 276,322 +2026-06-24 06:05:53,472 - Overdetermined ratio : 15.18 +2026-06-24 06:05:53,472 - +2026-06-24 06:05:53,472 - ### Model behavior ### +2026-06-24 06:05:53,472 - Tilt propagator : False +2026-06-24 06:05:53,472 - Change slice thickness : False +2026-06-24 06:05:53,472 - Detector blur : False +2026-06-24 06:05:53,472 - Preload data : True +2026-06-24 06:05:53,472 - On-the-fly meas padding : False +2026-06-24 06:05:53,472 - On-the-fly meas resample : False +2026-06-24 06:05:53,472 - On-the-fly simu match mode: None +2026-06-24 06:05:53,472 - +2026-06-24 06:05:53,514 - ### Done initializing PtychoModel model ### +2026-06-24 06:05:53,514 - +2026-06-24 06:05:53,514 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:05:53,514 - +2026-06-24 06:05:53,514 - ### Generating indices, batches, and output_path ### +2026-06-24 06:05:53,515 - d90 = 53.000 px or 10.600 Ang +2026-06-24 06:05:53,515 - Selecting indices with the 'full' mode +2026-06-24 06:05:53,981 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:05:54,058 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:05:54,058 - Original recon_dir_affixes = ['default'] +2026-06-24 06:05:54,058 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:05:54,064 - Path corrected for compatibility: +2026-06-24 06:05:54,064 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5.75e+03_phi32_155_C34_-6.02e+03_phi34_277_C41_3.84e+05_phi41_107_C43_-2.55e+05_phi43_59.9_C45_2.6e+05_phi45_191_C50_-2.71e+08_C52_-1.26e+07_phi52_72.6_C54_-1.82e+07_phi54_254_C56_-8.99e+06_phi56_244 +2026-06-24 06:05:54,064 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244 +2026-06-24 06:05:54,065 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244' is generated! +2026-06-24 06:05:54,220 - +2026-06-24 06:05:54,222 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/20260624_060554_ptyrad_log.txt ### +2026-06-24 06:05:54,222 - +2026-06-24 06:05:54,223 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:05:54,223 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:05:54,223 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:05:55,422 - Iter: 1, Total Loss: 0.8366, loss_single: 0.8366, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:05:55,459 - Iter: 2, Total Loss: 0.8029, loss_single: 0.8029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:05:55,495 - Iter: 3, Total Loss: 0.7742, loss_single: 0.7742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,531 - Iter: 4, Total Loss: 0.7470, loss_single: 0.7470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,566 - Iter: 5, Total Loss: 0.7224, loss_single: 0.7224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,602 - Iter: 6, Total Loss: 0.7002, loss_single: 0.7002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,637 - Iter: 7, Total Loss: 0.6851, loss_single: 0.6851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,672 - Iter: 8, Total Loss: 0.6725, loss_single: 0.6725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,708 - Iter: 9, Total Loss: 0.6579, loss_single: 0.6579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,743 - Iter: 10, Total Loss: 0.6454, loss_single: 0.6454, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,778 - Iter: 11, Total Loss: 0.6332, loss_single: 0.6332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,814 - Iter: 12, Total Loss: 0.6218, loss_single: 0.6218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,849 - Iter: 13, Total Loss: 0.6126, loss_single: 0.6126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,884 - Iter: 14, Total Loss: 0.6033, loss_single: 0.6033, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,920 - Iter: 15, Total Loss: 0.5954, loss_single: 0.5954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,955 - Iter: 16, Total Loss: 0.5885, loss_single: 0.5885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:55,990 - Iter: 17, Total Loss: 0.5825, loss_single: 0.5825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,025 - Iter: 18, Total Loss: 0.5776, loss_single: 0.5776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,060 - Iter: 19, Total Loss: 0.5732, loss_single: 0.5732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,096 - Iter: 20, Total Loss: 0.5686, loss_single: 0.5686, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,131 - Iter: 21, Total Loss: 0.5638, loss_single: 0.5638, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,166 - Iter: 22, Total Loss: 0.5607, loss_single: 0.5607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,201 - Iter: 23, Total Loss: 0.5580, loss_single: 0.5580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,236 - Iter: 24, Total Loss: 0.5549, loss_single: 0.5549, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,272 - Iter: 25, Total Loss: 0.5526, loss_single: 0.5526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,310 - Iter: 26, Total Loss: 0.5505, loss_single: 0.5505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:05:56,346 - Iter: 27, Total Loss: 0.5480, loss_single: 0.5480, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,381 - Iter: 28, Total Loss: 0.5461, loss_single: 0.5461, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,417 - Iter: 29, Total Loss: 0.5443, loss_single: 0.5443, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,452 - Iter: 30, Total Loss: 0.5425, loss_single: 0.5425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,487 - Iter: 31, Total Loss: 0.5408, loss_single: 0.5408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,523 - Iter: 32, Total Loss: 0.5396, loss_single: 0.5396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,558 - Iter: 33, Total Loss: 0.5387, loss_single: 0.5387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,593 - Iter: 34, Total Loss: 0.5373, loss_single: 0.5373, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,629 - Iter: 35, Total Loss: 0.5357, loss_single: 0.5357, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,664 - Iter: 36, Total Loss: 0.5346, loss_single: 0.5346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,699 - Iter: 37, Total Loss: 0.5339, loss_single: 0.5339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,734 - Iter: 38, Total Loss: 0.5332, loss_single: 0.5332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,769 - Iter: 39, Total Loss: 0.5324, loss_single: 0.5324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,804 - Iter: 40, Total Loss: 0.5317, loss_single: 0.5317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,841 - Iter: 41, Total Loss: 0.5311, loss_single: 0.5311, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,876 - Iter: 42, Total Loss: 0.5306, loss_single: 0.5306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,912 - Iter: 43, Total Loss: 0.5303, loss_single: 0.5303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,947 - Iter: 44, Total Loss: 0.5300, loss_single: 0.5300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:56,983 - Iter: 45, Total Loss: 0.5297, loss_single: 0.5297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,018 - Iter: 46, Total Loss: 0.5293, loss_single: 0.5293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,053 - Iter: 47, Total Loss: 0.5290, loss_single: 0.5290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,088 - Iter: 48, Total Loss: 0.5288, loss_single: 0.5288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,124 - Iter: 49, Total Loss: 0.5285, loss_single: 0.5285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,159 - Iter: 50, Total Loss: 0.5283, loss_single: 0.5283, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,194 - Iter: 51, Total Loss: 0.5279, loss_single: 0.5279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,230 - Iter: 52, Total Loss: 0.5275, loss_single: 0.5275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:05:57,265 - 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Saving summary figures for iter 100 +2026-06-24 06:06:02,696 - ### Finished 100 iterations, averaged iter_t = 0.038977 with std = 0.040 ### +2026-06-24 06:06:02,696 - +2026-06-24 06:06:02,697 - ### The PtyRADSolver is finished in 9.295 sec ### +2026-06-24 06:06:02,697 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..a69cf423d2bff1fde7e93deb0dc8b12ef4a27a9c Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/simulation_data3__sample_000045.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/simulation_data3__sample_000045.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a0b05a87a8e2c1ac1d7e7486e3527fc1a2460262 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045/c30_small__simulation_data3__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-347_C12_27.6_phi12_166_C21_-228_phi21_39.7_C23_882_phi23_149_C30_4.25e+06_C32_5..99e+06_phi56_244/simulation_data3__sample_000045.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 14.142257690429688 + probe_aberrations: + C10: -347.29437255859375 + C12: 27.60617446899414 + C21: -227.64541625976562 + C23: 882.3550415039062 + C30: 4251283.5 + C32: 5753.9111328125 + C34: -6022.4833984375 + C41: 383904.09375 + C43: -254520.28125 + C45: 260293.59375 + C50: -270716960.0 + C52: -12610341.0 + C54: -18151722.0 + C56: -8993279.0 + phi12: 165.9700587933198 + phi21: 39.71710264623351 + phi23: 149.15237086794252 + phi32: 155.14516518533338 + phi34: 276.835490080054 + phi41: 107.32940137228361 + phi43: 59.89646966221306 + phi45: 190.74818193218516 + phi52: 72.58709091369099 + phi54: 254.34556227541296 + phi56: 243.6709601499235 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.49196022748947144 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data3__sample_000045_measurement.h5 + key: measurement + random_seed: 20261973 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data3__sample_000045 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data3__sample_000045 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/20260624_060638_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/20260624_060638_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..eab5b4508eb4657d0f739a826d84084d161965f4 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/20260624_060638_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:06:37,125 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:06:37,125 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:06:37,125 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:06:37,125 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:06:37,125 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:06:37,125 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:06:37,125 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:06:37,125 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:06:37,125 - +2026-06-24 06:06:37,235 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:06:37,235 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:06:37,235 - Accelerator.num_process = 1 +2026-06-24 06:06:37,235 - Accelerator.mixed_precision = no +2026-06-24 06:06:37,245 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:06:37,245 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:06:37,245 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:06:37,245 - +2026-06-24 06:06:37,245 - ### System information ### +2026-06-24 06:06:37,245 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:06:37,245 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:06:37,245 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:06:37,245 - Machine: x86_64 +2026-06-24 06:06:37,245 - Processor: x86_64 +2026-06-24 06:06:37,245 - Available CPU cores: 8 +2026-06-24 06:06:37,245 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:06:37,245 - +2026-06-24 06:06:37,245 - ### GPU information ### +2026-06-24 06:06:37,246 - CUDA Available: True +2026-06-24 06:06:37,246 - CUDA Version: 13.0 +2026-06-24 06:06:37,246 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:06:37,246 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:06:37,246 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:06:37,246 - In addition, Triton does not directly support Windows. +2026-06-24 06:06:37,246 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:06:37,261 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:06:37,261 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:06:37,261 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:06:37,261 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:06:37,261 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:06:37,261 - +2026-06-24 06:06:37,261 - ### Python information ### +2026-06-24 06:06:37,263 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:06:37,263 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:06:37,263 - +2026-06-24 06:06:37,263 - ### Packages information ### +2026-06-24 06:06:37,264 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:06:37,265 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:06:37,265 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:06:37,266 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:06:37,267 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:06:37,267 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:06:37,267 - +2026-06-24 06:06:37,267 - ### Loading params file ### +2026-06-24 06:06:37,267 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000000.yaml +2026-06-24 06:06:37,273 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:06:37,274 - Success! Params file validated and defaults applied. +2026-06-24 06:06:37,274 - +2026-06-24 06:06:37,274 - ### Setting GPU Device ### +2026-06-24 06:06:37,274 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:06:37,274 - +2026-06-24 06:06:37,274 - Random seed: 20261976 provided by params file +2026-06-24 06:06:37,275 - ### Initializing Initializer ### +2026-06-24 06:06:37,275 - init_params are displayed below: +2026-06-24 06:06:37,275 - random_seed: 20261976 +2026-06-24 06:06:37,275 - probe_illum_type: electron +2026-06-24 06:06:37,275 - probe_kv: 200.0 +2026-06-24 06:06:37,275 - probe_conv_angle: 10.578505516052246 +2026-06-24 06:06:37,275 - probe_aberrations: {'C10': -610.402, 'C12': 21.408, 'phi12': 12.671, 'C21': -933.126, 'phi21': 98.887, 'C23': -94.49, 'phi23': 244.118, 'C30': 3950256.75, 'C32': -5196.527, 'phi32': 111.835, 'C34': -9306.237, 'phi34': 118.626, 'C41': -482562.906, 'phi41': 206.683, 'C43': -221040.781, 'phi43': 278.575, 'C45': 477320.156, 'phi45': 261.411, 'C50': 463473568.0, 'C52': -6229440.5, 'phi52': 48.269, 'C54': 14473225.0, 'phi54': 275.627, 'C56': -10395729.0, 'phi56': 77.873} +2026-06-24 06:06:37,275 - beam_kev: None +2026-06-24 06:06:37,275 - probe_dRn: None +2026-06-24 06:06:37,275 - probe_Rn: None +2026-06-24 06:06:37,275 - probe_D_H: None +2026-06-24 06:06:37,275 - probe_D_FZP: None +2026-06-24 06:06:37,275 - probe_Ls: None +2026-06-24 06:06:37,275 - meas_Npix: 128 +2026-06-24 06:06:37,275 - pos_N_scans: 256 +2026-06-24 06:06:37,275 - pos_N_scan_slow: 16 +2026-06-24 06:06:37,275 - pos_N_scan_fast: 16 +2026-06-24 06:06:37,275 - pos_scan_step_size: 0.32114824652671814 +2026-06-24 06:06:37,275 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:06:37,275 - probe_pmode_max: 6 +2026-06-24 06:06:37,276 - probe_pmode_init_pows: [0.02] +2026-06-24 06:06:37,276 - obj_omode_max: 1 +2026-06-24 06:06:37,276 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:06:37,277 - obj_Nlayer: 1 +2026-06-24 06:06:37,277 - obj_slice_thickness: 20.0 +2026-06-24 06:06:37,277 - simu_Npix: None +2026-06-24 06:06:37,277 - simu_match_mode: None +2026-06-24 06:06:37,277 - meas_permute: None +2026-06-24 06:06:37,277 - meas_reshape: [256, 128, 128] +2026-06-24 06:06:37,277 - meas_flipT: [0, 0, 0] +2026-06-24 06:06:37,277 - meas_crop: None +2026-06-24 06:06:37,277 - meas_pad: None +2026-06-24 06:06:37,277 - meas_resample: None +2026-06-24 06:06:37,277 - meas_add_source_size: None +2026-06-24 06:06:37,277 - meas_add_detector_blur: None +2026-06-24 06:06:37,277 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:06:37,277 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:06:37,277 - meas_add_poisson_noise: None +2026-06-24 06:06:37,277 - meas_export: None +2026-06-24 06:06:37,277 - probe_permute: None +2026-06-24 06:06:37,277 - probe_z_shift: None +2026-06-24 06:06:37,277 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:06:37,277 - pos_scan_flipT: None +2026-06-24 06:06:37,277 - pos_scan_affine: None +2026-06-24 06:06:37,277 - pos_scan_rand_std: 0.15 +2026-06-24 06:06:37,277 - obj_z_crop: None +2026-06-24 06:06:37,277 - obj_z_pad: None +2026-06-24 06:06:37,277 - obj_z_resample: None +2026-06-24 06:06:37,277 - meas_source: file +2026-06-24 06:06:37,277 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000000_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:06:37,277 - probe_source: simu +2026-06-24 06:06:37,277 - probe_params: None +2026-06-24 06:06:37,277 - pos_source: simu +2026-06-24 06:06:37,277 - pos_params: None +2026-06-24 06:06:37,277 - obj_source: simu +2026-06-24 06:06:37,277 - obj_params: None +2026-06-24 06:06:37,277 - tilt_source: simu +2026-06-24 06:06:37,277 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:06:37,278 - +2026-06-24 06:06:37,278 - ### Initializing cache ### +2026-06-24 06:06:37,278 - use_cached_obj = False +2026-06-24 06:06:37,278 - use_cached_probe = False +2026-06-24 06:06:37,278 - use_cached_pos = False +2026-06-24 06:06:37,278 - +2026-06-24 06:06:37,278 - ### Initializing measurements ### +2026-06-24 06:06:37,278 - Loading measurements from source = 'file' +2026-06-24 06:06:37,278 - Detected measurement file type = '.h5' +2026-06-24 06:06:37,356 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:06:37,356 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:06:37,357 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0050) +2026-06-24 06:06:37,358 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:06:37,358 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:06:37,359 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:06:37,359 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:06:37,359 - Normalizing by max of the 2D mean pattern intensity: 0.0025518339 +2026-06-24 06:06:37,360 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:06:37,361 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0238, 1.9571) +2026-06-24 06:06:37,362 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:06:37,363 - Pattern total int. statistics (min, mean, max) = (386.8685, 390.2112, 392.8016), with min/max = 98.5% +2026-06-24 06:06:37,364 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0238, 1.9571) +2026-06-24 06:06:37,365 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:06:37,365 - +2026-06-24 06:06:37,365 - ### Setting up calibration ### +2026-06-24 06:06:37,365 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:06:37,365 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:06:37,365 - Radius of fitted bright field disk (RBF) = 10.72 px with meas_Npix = 128 +2026-06-24 06:06:37,365 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1675 +2026-06-24 06:06:37,365 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:06:37,365 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:06:37,594 - Initial guess: center=(63.58, 63.64), radius=10.72, Gaussian blur std=0.50 +2026-06-24 06:06:37,606 - Final fit: center=(63.58, 63.64), radius=10.72, Gaussian blur std=0.67 +2026-06-24 06:06:37,606 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.80 px with Npix = 128 +2026-06-24 06:06:37,607 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:06:37,607 - +2026-06-24 06:06:37,607 - ### Setting init_variables dict ### +2026-06-24 06:06:37,607 - Derived values given input init_params: +2026-06-24 06:06:37,607 - kv = 200.0 kV +2026-06-24 06:06:37,607 - wavelength = 0.0251 Ang +2026-06-24 06:06:37,607 - conv_angle = 10.578505516052246 mrad +2026-06-24 06:06:37,607 - Npix = 128 px +2026-06-24 06:06:37,607 - dk = 0.0391 Ang^-1 +2026-06-24 06:06:37,607 - kMax = 2.5000 Ang^-1 +2026-06-24 06:06:37,607 - da = 0.9797 mrad +2026-06-24 06:06:37,607 - angleMax = 62.6984 mrad +2026-06-24 06:06:37,607 - RBF = 10.7981 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:06:37,607 - n_alpha = 5.9270 (# conv_angle) +2026-06-24 06:06:37,607 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:06:37,607 - Rayleigh-limited resolution = 1.4462 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:06:37,607 - Real space probe extent = 25.6000 Ang +2026-06-24 06:06:37,607 - +2026-06-24 06:06:37,607 - ### Initializing probe ### +2026-06-24 06:06:37,607 - Loading probe from source = 'simu' +2026-06-24 06:06:37,607 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:06:37,607 - Start simulating STEM probe +2026-06-24 06:06:37,607 - kv = 200.0 kV +2026-06-24 06:06:37,607 - wavelength = 0.0251 Ang +2026-06-24 06:06:37,608 - conv_angle = 10.578505516052246 mrad +2026-06-24 06:06:37,608 - Npix = 128 px +2026-06-24 06:06:37,608 - dk = 0.0391 Ang^-1 +2026-06-24 06:06:37,608 - kMax = 2.5000 Ang^-1 +2026-06-24 06:06:37,608 - alpha_max = 62.6984 mrad +2026-06-24 06:06:37,608 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:06:37,608 - Rayleigh-limited resolution = 1.4462 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:06:37,608 - Real space probe extent = 25.6000 Ang +2026-06-24 06:06:37,608 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:06:37,608 - ------------------------------------------------------------------------------------ +2026-06-24 06:06:37,608 - C1,0 C1 -610.4020 - Defocus (C10 = -df) +2026-06-24 06:06:37,608 - C1,2 A1 21.4080 12.67 2-fold astigmatism +2026-06-24 06:06:37,608 - C2,1 3*B2 -933.1260 98.89 Axial coma +2026-06-24 06:06:37,608 - C2,3 A2 -94.4900 244.12 3-fold astigmatism +2026-06-24 06:06:37,608 - C3,0 C3 3950256.7500 - Spherical aberration +2026-06-24 06:06:37,608 - C3,2 4*S3 -5196.5270 111.83 Axial star aberration +2026-06-24 06:06:37,608 - C3,4 A3 -9306.2370 118.63 4-fold astigmatism +2026-06-24 06:06:37,608 - C4,1 4*B4 -482562.9060 206.68 Axial coma(4th) +2026-06-24 06:06:37,608 - C4,3 4*D4 -221040.7810 278.57 3-lobe aberration +2026-06-24 06:06:37,608 - C4,5 A4 477320.1560 261.41 5-fold astigmatism +2026-06-24 06:06:37,608 - C5,0 C5 463473568.0000 - Spherical aberration (5th) +2026-06-24 06:06:37,608 - C5,2 6*S5 -6229440.5000 48.27 Axial star aberration(5th) +2026-06-24 06:06:37,608 - C5,4 6*R5 14473225.0000 275.63 4-lobe aberration +2026-06-24 06:06:37,608 - C5,6 A5 -10395729.0000 77.87 6-fold astigmatism +2026-06-24 06:06:37,611 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:06:37,611 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:06:37,611 - Creating 5 new probe modes from the major mode +2026-06-24 06:06:37,611 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:06:37,715 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:06:37,716 - Orthogonalizing 6 pmodes +2026-06-24 06:06:37,720 - Sorting 6 pmodes by their intensities +2026-06-24 06:06:37,720 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:06:37,721 - sum(|probe_data|**2) = 390.21, while meas_total_ints (min, mean, max) = (386.8685, 390.2112, 392.8016) +2026-06-24 06:06:37,721 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:06:37,721 - +2026-06-24 06:06:37,721 - ### Initializing probe positions ### +2026-06-24 06:06:37,721 - Loading probe positions from source = 'simu' +2026-06-24 06:06:37,721 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:06:37,721 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3211, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:06:37,721 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:06:37,723 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:06:37,723 - crop_pos 1st and last px coords (y,x) = ([15, 15], [39, 39]) +2026-06-24 06:06:37,723 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 06:06:37,723 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:06:37,723 - +2026-06-24 06:06:37,723 - ### Initializing object ### +2026-06-24 06:06:37,723 - Loading object from source = 'simu' +2026-06-24 06:06:37,724 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:06:37,725 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:06:37,725 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 183, 183) +2026-06-24 06:06:37,725 - object extent (Z, Y, X) (Ang) = [20. 36.6 36.6] +2026-06-24 06:06:37,725 - +2026-06-24 06:06:37,725 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:06:37,725 - omode_occu (omode) = float32, (1,) +2026-06-24 06:06:37,725 - +2026-06-24 06:06:37,725 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:06:37,725 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:06:37,726 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:06:37,726 - +2026-06-24 06:06:37,726 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:06:37,726 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:06:37,726 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:06:37,726 - +2026-06-24 06:06:37,726 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:06:37,726 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:06:37,726 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:06:37,726 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:06:37,726 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:06:37,726 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (183, 183). +2026-06-24 06:06:37,727 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:06:37,727 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:06:37,727 - +2026-06-24 06:06:37,727 - ### Collecting reconstruction provenance ### +2026-06-24 06:06:37,727 - Reconstruction provenance is collected and initialized. +2026-06-24 06:06:37,727 - +2026-06-24 06:06:37,727 - ### Initializing loss function ### +2026-06-24 06:06:37,727 - Active loss types: +2026-06-24 06:06:37,727 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:06:37,727 - +2026-06-24 06:06:37,727 - ### Initializing constraint function ### +2026-06-24 06:06:37,727 - Active constraint types: +2026-06-24 06:06:37,727 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:06:37,727 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:06:37,727 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:06:37,727 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:06:37,727 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:06:37,727 - +2026-06-24 06:06:37,727 - ### Done initializing PtyRADSolver ### +2026-06-24 06:06:37,727 - +2026-06-24 06:06:37,851 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:06:37,851 - +2026-06-24 06:06:37,851 - ### Initializing PtychoModel model ### +2026-06-24 06:06:37,923 - ### PtychoModel optimizable variables ### +2026-06-24 06:06:37,923 - obja : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:06:37,923 - objp : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:06:37,923 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:06:37,923 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:06:37,924 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:06:37,924 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:06:37,924 - +2026-06-24 06:06:37,924 - ### Optimizable variables statitsics ### +2026-06-24 06:06:37,924 - Total measurement values : 4,194,304 +2026-06-24 06:06:37,924 - Total optimizing variables: 264,098 +2026-06-24 06:06:37,924 - Overdetermined ratio : 15.88 +2026-06-24 06:06:37,924 - +2026-06-24 06:06:37,924 - ### Model behavior ### +2026-06-24 06:06:37,924 - Tilt propagator : False +2026-06-24 06:06:37,924 - Change slice thickness : False +2026-06-24 06:06:37,924 - Detector blur : False +2026-06-24 06:06:37,924 - Preload data : True +2026-06-24 06:06:37,924 - On-the-fly meas padding : False +2026-06-24 06:06:37,924 - On-the-fly meas resample : False +2026-06-24 06:06:37,924 - On-the-fly simu match mode: None +2026-06-24 06:06:37,924 - +2026-06-24 06:06:37,965 - ### Done initializing PtychoModel model ### +2026-06-24 06:06:37,966 - +2026-06-24 06:06:37,966 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:06:37,966 - +2026-06-24 06:06:37,966 - ### Generating indices, batches, and output_path ### +2026-06-24 06:06:37,967 - d90 = 43.000 px or 8.600 Ang +2026-06-24 06:06:37,967 - Selecting indices with the 'full' mode +2026-06-24 06:06:38,429 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:06:38,516 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:06:38,516 - Original recon_dir_affixes = ['default'] +2026-06-24 06:06:38,516 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:06:38,522 - Path corrected for compatibility: +2026-06-24 06:06:38,522 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32_112_C34_-9.31e+03_phi34_119_C41_-4.83e+05_phi41_207_C43_-2.21e+05_phi43_279_C45_4.77e+05_phi45_261_C50_4.63e+08_C52_-6.23e+06_phi52_48.3_C54_1.45e+07_phi54_276_C56_-1.04e+07_phi56_77.9 +2026-06-24 06:06:38,523 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9 +2026-06-24 06:06:38,524 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9' is generated! +2026-06-24 06:06:38,691 - +2026-06-24 06:06:38,692 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/20260624_060638_ptyrad_log.txt ### +2026-06-24 06:06:38,692 - +2026-06-24 06:06:38,693 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:06:38,693 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:06:38,694 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:06:39,883 - Iter: 1, Total Loss: 1.0595, loss_single: 1.0595, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.439 sec +2026-06-24 06:06:39,921 - Iter: 2, Total Loss: 1.0260, loss_single: 1.0260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:06:39,956 - Iter: 3, Total Loss: 1.0010, loss_single: 1.0010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:39,991 - Iter: 4, Total Loss: 0.9782, loss_single: 0.9782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,026 - Iter: 5, Total Loss: 0.9533, loss_single: 0.9533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,061 - Iter: 6, Total Loss: 0.9297, loss_single: 0.9297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,096 - Iter: 7, Total Loss: 0.9065, loss_single: 0.9065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,131 - Iter: 8, Total Loss: 0.8835, loss_single: 0.8835, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,167 - Iter: 9, Total Loss: 0.8614, loss_single: 0.8614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,202 - Iter: 10, Total Loss: 0.8376, loss_single: 0.8376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,237 - Iter: 11, Total Loss: 0.8142, loss_single: 0.8142, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,272 - Iter: 12, Total Loss: 0.7930, loss_single: 0.7930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,307 - Iter: 13, Total Loss: 0.7731, loss_single: 0.7731, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,342 - Iter: 14, Total Loss: 0.7529, loss_single: 0.7529, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,377 - Iter: 15, Total Loss: 0.7327, loss_single: 0.7327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,418 - Iter: 16, Total Loss: 0.7120, loss_single: 0.7120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.041 sec +2026-06-24 06:06:40,454 - Iter: 17, Total Loss: 0.6896, loss_single: 0.6896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:06:40,490 - Iter: 18, Total Loss: 0.6694, loss_single: 0.6694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,525 - Iter: 19, Total Loss: 0.6529, loss_single: 0.6529, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,560 - Iter: 20, Total Loss: 0.6362, loss_single: 0.6362, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,594 - Iter: 21, Total Loss: 0.6170, loss_single: 0.6170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,630 - Iter: 22, Total Loss: 0.5973, loss_single: 0.5973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,665 - Iter: 23, Total Loss: 0.5797, loss_single: 0.5797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,700 - Iter: 24, Total Loss: 0.5620, loss_single: 0.5620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,735 - Iter: 25, Total Loss: 0.5477, loss_single: 0.5477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,770 - Iter: 26, Total Loss: 0.5369, loss_single: 0.5369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,805 - Iter: 27, Total Loss: 0.5254, loss_single: 0.5254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:40,840 - Iter: 28, Total Loss: 0.5136, loss_single: 0.5136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,875 - Iter: 29, Total Loss: 0.5026, loss_single: 0.5026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,910 - Iter: 30, Total Loss: 0.4911, loss_single: 0.4911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:40,951 - Iter: 31, Total Loss: 0.4790, loss_single: 0.4790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.041 sec +2026-06-24 06:06:40,990 - Iter: 32, Total Loss: 0.4692, loss_single: 0.4692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:06:41,025 - Iter: 33, Total Loss: 0.4610, loss_single: 0.4610, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:41,060 - Iter: 34, Total Loss: 0.4543, loss_single: 0.4543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,095 - Iter: 35, Total Loss: 0.4491, loss_single: 0.4491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:41,130 - Iter: 36, Total Loss: 0.4431, loss_single: 0.4431, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,165 - Iter: 37, Total Loss: 0.4364, loss_single: 0.4364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,200 - Iter: 38, Total Loss: 0.4290, loss_single: 0.4290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,235 - Iter: 39, Total Loss: 0.4223, loss_single: 0.4223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,270 - Iter: 40, Total Loss: 0.4186, loss_single: 0.4186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,306 - Iter: 41, Total Loss: 0.4156, loss_single: 0.4156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:41,341 - Iter: 42, Total Loss: 0.4115, loss_single: 0.4115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:41,376 - Iter: 43, Total Loss: 0.4079, loss_single: 0.4079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,411 - Iter: 44, Total Loss: 0.4047, loss_single: 0.4047, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,447 - Iter: 45, Total Loss: 0.4022, loss_single: 0.4022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:06:41,481 - Iter: 46, Total Loss: 0.4001, loss_single: 0.4001, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:06:41,524 - 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/simulation_data4__sample_000000.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/simulation_data4__sample_000000.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7f1f8be31c48465607307e6f8fadc3a06c487871 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000000/c30_small__simulation_data4__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-610_C12_21.4_phi12_12.7_C21_-933_phi21_98.9_C23_-94.5_phi23_244_C30_3.95e+06_C32_-5.2e+03_phi32.9/simulation_data4__sample_000000.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 10.578505516052246 + probe_aberrations: + C10: -610.4020385742188 + C12: 21.40838623046875 + C21: -933.1261596679688 + C23: -94.4898910522461 + C30: 3950256.75 + C32: -5196.52685546875 + C34: -9306.2373046875 + C41: -482562.90625 + C43: -221040.78125 + C45: 477320.15625 + C50: 463473568.0 + C52: -6229440.5 + C54: 14473225.0 + C56: -10395729.0 + phi12: 12.670528542487036 + phi21: 98.88675480339259 + phi23: 244.11773648391238 + phi32: 111.83466928090489 + phi34: 118.62647961797134 + phi41: 206.68254881296136 + phi43: 278.57533050695304 + phi45: 261.4108738774142 + phi52: 48.268981015425965 + phi54: 275.6271476536087 + phi56: 77.8734865765516 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.32114824652671814 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000000_measurement.h5 + key: measurement + random_seed: 20261976 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/20260624_060723_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:07:22,257 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:07:22,258 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:07:22,258 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:07:22,258 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:07:22,258 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:07:22,258 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:07:22,258 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:07:22,258 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:07:22,258 - +2026-06-24 06:07:22,366 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:07:22,366 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:07:22,366 - Accelerator.num_process = 1 +2026-06-24 06:07:22,366 - Accelerator.mixed_precision = no +2026-06-24 06:07:22,390 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:07:22,390 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:07:22,390 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:07:22,390 - +2026-06-24 06:07:22,390 - ### System information ### +2026-06-24 06:07:22,391 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:07:22,391 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:07:22,391 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:07:22,391 - Machine: x86_64 +2026-06-24 06:07:22,391 - Processor: x86_64 +2026-06-24 06:07:22,391 - Available CPU cores: 8 +2026-06-24 06:07:22,391 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:07:22,391 - +2026-06-24 06:07:22,391 - ### GPU information ### +2026-06-24 06:07:22,391 - CUDA Available: True +2026-06-24 06:07:22,391 - CUDA Version: 13.0 +2026-06-24 06:07:22,391 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:07:22,391 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:07:22,392 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:07:22,392 - In addition, Triton does not directly support Windows. +2026-06-24 06:07:22,392 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:07:22,407 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:07:22,407 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:07:22,407 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:07:22,407 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:07:22,407 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:07:22,407 - +2026-06-24 06:07:22,407 - ### Python information ### +2026-06-24 06:07:22,409 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:07:22,409 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:07:22,409 - +2026-06-24 06:07:22,409 - ### Packages information ### +2026-06-24 06:07:22,410 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:07:22,410 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:07:22,411 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:07:22,412 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:07:22,412 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:07:22,412 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:07:22,412 - +2026-06-24 06:07:22,412 - ### Loading params file ### +2026-06-24 06:07:22,412 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000003.yaml +2026-06-24 06:07:22,419 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:07:22,420 - Success! Params file validated and defaults applied. +2026-06-24 06:07:22,420 - +2026-06-24 06:07:22,420 - ### Setting GPU Device ### +2026-06-24 06:07:22,420 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:07:22,420 - +2026-06-24 06:07:22,420 - Random seed: 20261979 provided by params file +2026-06-24 06:07:22,420 - ### Initializing Initializer ### +2026-06-24 06:07:22,421 - init_params are displayed below: +2026-06-24 06:07:22,421 - random_seed: 20261979 +2026-06-24 06:07:22,421 - probe_illum_type: electron +2026-06-24 06:07:22,421 - probe_kv: 300.0 +2026-06-24 06:07:22,421 - probe_conv_angle: 12.811492919921875 +2026-06-24 06:07:22,421 - probe_aberrations: {'C10': -15.604, 'C12': 20.308, 'phi12': 315.933, 'C21': -829.77, 'phi21': 217.035, 'C23': 387.632, 'phi23': 177.608, 'C30': 3674324.25, 'C32': -10177.279, 'phi32': 12.104, 'C34': 4064.233, 'phi34': 16.36, 'C41': -430273.562, 'phi41': 325.378, 'C43': 262010.156, 'phi43': 345.586, 'C45': -478581.719, 'phi45': 120.478, 'C50': -457566976.0, 'C52': 12183036.0, 'phi52': 154.097, 'C54': -2417857.75, 'phi54': 230.667, 'C56': 13191576.0, 'phi56': 83.501} +2026-06-24 06:07:22,421 - beam_kev: None +2026-06-24 06:07:22,421 - probe_dRn: None +2026-06-24 06:07:22,421 - probe_Rn: None +2026-06-24 06:07:22,421 - probe_D_H: None +2026-06-24 06:07:22,421 - probe_D_FZP: None +2026-06-24 06:07:22,421 - probe_Ls: None +2026-06-24 06:07:22,421 - meas_Npix: 128 +2026-06-24 06:07:22,421 - pos_N_scans: 256 +2026-06-24 06:07:22,421 - pos_N_scan_slow: 16 +2026-06-24 06:07:22,421 - pos_N_scan_fast: 16 +2026-06-24 06:07:22,421 - pos_scan_step_size: 0.4390125572681427 +2026-06-24 06:07:22,421 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:07:22,421 - probe_pmode_max: 6 +2026-06-24 06:07:22,421 - probe_pmode_init_pows: [0.02] +2026-06-24 06:07:22,421 - obj_omode_max: 1 +2026-06-24 06:07:22,421 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:07:22,421 - obj_Nlayer: 1 +2026-06-24 06:07:22,421 - obj_slice_thickness: 20.0 +2026-06-24 06:07:22,421 - simu_Npix: None +2026-06-24 06:07:22,421 - simu_match_mode: None +2026-06-24 06:07:22,421 - meas_permute: None +2026-06-24 06:07:22,421 - meas_reshape: [256, 128, 128] +2026-06-24 06:07:22,421 - meas_flipT: [0, 0, 0] +2026-06-24 06:07:22,421 - meas_crop: None +2026-06-24 06:07:22,421 - meas_pad: None +2026-06-24 06:07:22,421 - meas_resample: None +2026-06-24 06:07:22,421 - meas_add_source_size: None +2026-06-24 06:07:22,421 - meas_add_detector_blur: None +2026-06-24 06:07:22,421 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:07:22,421 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:07:22,422 - meas_add_poisson_noise: None +2026-06-24 06:07:22,422 - meas_export: None +2026-06-24 06:07:22,422 - probe_permute: None +2026-06-24 06:07:22,422 - probe_z_shift: None +2026-06-24 06:07:22,422 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:07:22,422 - pos_scan_flipT: None +2026-06-24 06:07:22,422 - pos_scan_affine: None +2026-06-24 06:07:22,422 - pos_scan_rand_std: 0.15 +2026-06-24 06:07:22,422 - obj_z_crop: None +2026-06-24 06:07:22,422 - obj_z_pad: None +2026-06-24 06:07:22,422 - obj_z_resample: None +2026-06-24 06:07:22,422 - meas_source: file +2026-06-24 06:07:22,422 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000003_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:07:22,422 - probe_source: simu +2026-06-24 06:07:22,422 - probe_params: None +2026-06-24 06:07:22,422 - pos_source: simu +2026-06-24 06:07:22,422 - pos_params: None +2026-06-24 06:07:22,422 - obj_source: simu +2026-06-24 06:07:22,422 - obj_params: None +2026-06-24 06:07:22,422 - tilt_source: simu +2026-06-24 06:07:22,422 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:07:22,422 - +2026-06-24 06:07:22,422 - ### Initializing cache ### +2026-06-24 06:07:22,422 - use_cached_obj = False +2026-06-24 06:07:22,422 - use_cached_probe = False +2026-06-24 06:07:22,422 - use_cached_pos = False +2026-06-24 06:07:22,422 - +2026-06-24 06:07:22,422 - ### Initializing measurements ### +2026-06-24 06:07:22,422 - Loading measurements from source = 'file' +2026-06-24 06:07:22,422 - Detected measurement file type = '.h5' +2026-06-24 06:07:22,498 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:07:22,498 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:07:22,499 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0020) +2026-06-24 06:07:22,499 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:07:22,499 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:07:22,500 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:07:22,500 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:07:22,501 - Normalizing by max of the 2D mean pattern intensity: 0.0011292771 +2026-06-24 06:07:22,501 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:07:22,503 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0541, 1.7796) +2026-06-24 06:07:22,503 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:07:22,504 - Pattern total int. statistics (min, mean, max) = (879.2245, 886.8871, 896.1784), with min/max = 98.1% +2026-06-24 06:07:22,506 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0541, 1.7796) +2026-06-24 06:07:22,506 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:07:22,506 - +2026-06-24 06:07:22,506 - ### Setting up calibration ### +2026-06-24 06:07:22,506 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:07:22,506 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:07:22,506 - Radius of fitted bright field disk (RBF) = 16.51 px with meas_Npix = 128 +2026-06-24 06:07:22,506 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2579 +2026-06-24 06:07:22,506 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:07:22,506 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:07:22,728 - Initial guess: center=(63.62, 63.62), radius=16.51, Gaussian blur std=0.50 +2026-06-24 06:07:22,740 - Final fit: center=(63.62, 63.62), radius=16.51, Gaussian blur std=0.63 +2026-06-24 06:07:22,740 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 16.66 px with Npix = 128 +2026-06-24 06:07:22,740 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:07:22,741 - +2026-06-24 06:07:22,741 - ### Setting init_variables dict ### +2026-06-24 06:07:22,741 - Derived values given input init_params: +2026-06-24 06:07:22,741 - kv = 300.0 kV +2026-06-24 06:07:22,741 - wavelength = 0.0197 Ang +2026-06-24 06:07:22,741 - conv_angle = 12.811492919921875 mrad +2026-06-24 06:07:22,741 - Npix = 128 px +2026-06-24 06:07:22,741 - dk = 0.0391 Ang^-1 +2026-06-24 06:07:22,741 - kMax = 2.5000 Ang^-1 +2026-06-24 06:07:22,741 - da = 0.7690 mrad +2026-06-24 06:07:22,741 - angleMax = 49.2187 mrad +2026-06-24 06:07:22,741 - RBF = 16.6590 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:07:22,741 - n_alpha = 3.8418 (# conv_angle) +2026-06-24 06:07:22,741 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:07:22,741 - Rayleigh-limited resolution = 0.9374 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:07:22,741 - Real space probe extent = 25.6000 Ang +2026-06-24 06:07:22,741 - +2026-06-24 06:07:22,741 - ### Initializing probe ### +2026-06-24 06:07:22,741 - Loading probe from source = 'simu' +2026-06-24 06:07:22,741 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:07:22,741 - Start simulating STEM probe +2026-06-24 06:07:22,741 - kv = 300.0 kV +2026-06-24 06:07:22,741 - wavelength = 0.0197 Ang +2026-06-24 06:07:22,741 - conv_angle = 12.811492919921875 mrad +2026-06-24 06:07:22,742 - Npix = 128 px +2026-06-24 06:07:22,742 - dk = 0.0391 Ang^-1 +2026-06-24 06:07:22,742 - kMax = 2.5000 Ang^-1 +2026-06-24 06:07:22,742 - alpha_max = 49.2187 mrad +2026-06-24 06:07:22,742 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:07:22,742 - Rayleigh-limited resolution = 0.9374 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:07:22,742 - Real space probe extent = 25.6000 Ang +2026-06-24 06:07:22,742 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:07:22,742 - ------------------------------------------------------------------------------------- +2026-06-24 06:07:22,742 - C1,0 C1 -15.6040 - Defocus (C10 = -df) +2026-06-24 06:07:22,742 - C1,2 A1 20.3080 315.93 2-fold astigmatism +2026-06-24 06:07:22,742 - C2,1 3*B2 -829.7700 217.03 Axial coma +2026-06-24 06:07:22,742 - C2,3 A2 387.6320 177.61 3-fold astigmatism +2026-06-24 06:07:22,742 - C3,0 C3 3674324.2500 - Spherical aberration +2026-06-24 06:07:22,742 - C3,2 4*S3 -10177.2790 12.10 Axial star aberration +2026-06-24 06:07:22,742 - C3,4 A3 4064.2330 16.36 4-fold astigmatism +2026-06-24 06:07:22,742 - C4,1 4*B4 -430273.5620 325.38 Axial coma(4th) +2026-06-24 06:07:22,742 - C4,3 4*D4 262010.1560 345.59 3-lobe aberration +2026-06-24 06:07:22,742 - C4,5 A4 -478581.7190 120.48 5-fold astigmatism +2026-06-24 06:07:22,742 - C5,0 C5 -457566976.0000 - Spherical aberration (5th) +2026-06-24 06:07:22,742 - C5,2 6*S5 12183036.0000 154.10 Axial star aberration(5th) +2026-06-24 06:07:22,742 - C5,4 6*R5 -2417857.7500 230.67 4-lobe aberration +2026-06-24 06:07:22,742 - C5,6 A5 13191576.0000 83.50 6-fold astigmatism +2026-06-24 06:07:22,745 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:07:22,745 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:07:22,745 - Creating 5 new probe modes from the major mode +2026-06-24 06:07:22,745 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:07:22,845 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:07:22,846 - Orthogonalizing 6 pmodes +2026-06-24 06:07:22,849 - Sorting 6 pmodes by their intensities +2026-06-24 06:07:22,850 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:07:22,850 - sum(|probe_data|**2) = 886.89, while meas_total_ints (min, mean, max) = (879.2245, 886.8871, 896.1784) +2026-06-24 06:07:22,850 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:07:22,850 - +2026-06-24 06:07:22,851 - ### Initializing probe positions ### +2026-06-24 06:07:22,851 - Loading probe positions from source = 'simu' +2026-06-24 06:07:22,851 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:07:22,851 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4390, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:07:22,851 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:07:22,853 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:07:22,853 - crop_pos 1st and last px coords (y,x) = ([16, 15], [48, 48]) +2026-06-24 06:07:22,853 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 06:07:22,853 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:07:22,853 - +2026-06-24 06:07:22,853 - ### Initializing object ### +2026-06-24 06:07:22,853 - Loading object from source = 'simu' +2026-06-24 06:07:22,853 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:07:22,855 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:07:22,855 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 06:07:22,855 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 06:07:22,855 - +2026-06-24 06:07:22,855 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:07:22,855 - omode_occu (omode) = float32, (1,) +2026-06-24 06:07:22,855 - +2026-06-24 06:07:22,855 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:07:22,855 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:07:22,856 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:07:22,856 - +2026-06-24 06:07:22,856 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:07:22,856 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:07:22,856 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:07:22,856 - +2026-06-24 06:07:22,856 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:07:22,856 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:07:22,856 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:07:22,856 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:07:22,856 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:07:22,856 - crop positions (yx_min=[15 15], yx_max=[177 177]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 06:07:22,857 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:07:22,857 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:07:22,857 - +2026-06-24 06:07:22,857 - ### Collecting reconstruction provenance ### +2026-06-24 06:07:22,857 - Reconstruction provenance is collected and initialized. +2026-06-24 06:07:22,857 - +2026-06-24 06:07:22,857 - ### Initializing loss function ### +2026-06-24 06:07:22,857 - Active loss types: +2026-06-24 06:07:22,857 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:07:22,857 - +2026-06-24 06:07:22,857 - ### Initializing constraint function ### +2026-06-24 06:07:22,857 - Active constraint types: +2026-06-24 06:07:22,857 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:07:22,857 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:07:22,857 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:07:22,857 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:07:22,857 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:07:22,857 - +2026-06-24 06:07:22,857 - ### Done initializing PtyRADSolver ### +2026-06-24 06:07:22,857 - +2026-06-24 06:07:22,985 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:07:22,985 - +2026-06-24 06:07:22,985 - ### Initializing PtychoModel model ### +2026-06-24 06:07:23,057 - ### PtychoModel optimizable variables ### +2026-06-24 06:07:23,057 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:23,057 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:23,057 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:07:23,057 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:07:23,058 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:07:23,058 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:23,058 - +2026-06-24 06:07:23,058 - ### Optimizable variables statitsics ### +2026-06-24 06:07:23,058 - Total measurement values : 4,194,304 +2026-06-24 06:07:23,058 - Total optimizing variables: 272,392 +2026-06-24 06:07:23,058 - Overdetermined ratio : 15.40 +2026-06-24 06:07:23,058 - +2026-06-24 06:07:23,058 - ### Model behavior ### +2026-06-24 06:07:23,058 - Tilt propagator : False +2026-06-24 06:07:23,058 - Change slice thickness : False +2026-06-24 06:07:23,058 - Detector blur : False +2026-06-24 06:07:23,058 - Preload data : True +2026-06-24 06:07:23,058 - On-the-fly meas padding : False +2026-06-24 06:07:23,058 - On-the-fly meas resample : False +2026-06-24 06:07:23,058 - On-the-fly simu match mode: None +2026-06-24 06:07:23,058 - +2026-06-24 06:07:23,099 - ### Done initializing PtychoModel model ### +2026-06-24 06:07:23,099 - +2026-06-24 06:07:23,099 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:07:23,099 - +2026-06-24 06:07:23,099 - ### Generating indices, batches, and output_path ### +2026-06-24 06:07:23,100 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:07:23,100 - Selecting indices with the 'full' mode +2026-06-24 06:07:23,560 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:07:23,638 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:07:23,638 - Original recon_dir_affixes = ['default'] +2026-06-24 06:07:23,638 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:07:23,645 - Path corrected for compatibility: +2026-06-24 06:07:23,645 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_12.1_C34_4.06e+03_phi34_16.4_C41_-4.3e+05_phi41_325_C43_2.62e+05_phi43_346_C45_-4.79e+05_phi45_120_C50_-4.58e+08_C52_1.22e+07_phi52_154_C54_-2.42e+06_phi54_231_C56_1.32e+07_phi56_83.5 +2026-06-24 06:07:23,645 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5 +2026-06-24 06:07:23,646 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5' is generated! +2026-06-24 06:07:23,796 - +2026-06-24 06:07:23,797 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/20260624_060723_ptyrad_log.txt ### +2026-06-24 06:07:23,797 - +2026-06-24 06:07:23,798 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:07:23,798 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:07:23,799 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:07:24,999 - Iter: 1, Total Loss: 0.7326, loss_single: 0.7326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:07:25,036 - Iter: 2, Total Loss: 0.7105, loss_single: 0.7105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:07:25,072 - Iter: 3, Total Loss: 0.6905, loss_single: 0.6905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,108 - Iter: 4, Total Loss: 0.6700, loss_single: 0.6700, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:07:25,144 - Iter: 5, Total Loss: 0.6547, loss_single: 0.6547, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,179 - Iter: 6, Total Loss: 0.6424, loss_single: 0.6424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:25,214 - Iter: 7, Total Loss: 0.6282, loss_single: 0.6282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,250 - Iter: 8, Total Loss: 0.6128, loss_single: 0.6128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,285 - Iter: 9, Total Loss: 0.5983, loss_single: 0.5983, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,320 - Iter: 10, Total Loss: 0.5842, loss_single: 0.5842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,355 - Iter: 11, Total Loss: 0.5701, loss_single: 0.5701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,391 - Iter: 12, Total Loss: 0.5592, loss_single: 0.5592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,426 - Iter: 13, Total Loss: 0.5499, loss_single: 0.5499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,461 - Iter: 14, Total Loss: 0.5397, loss_single: 0.5397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,497 - Iter: 15, Total Loss: 0.5276, loss_single: 0.5276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,532 - Iter: 16, Total Loss: 0.5152, loss_single: 0.5152, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,567 - Iter: 17, Total Loss: 0.5042, loss_single: 0.5042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,603 - Iter: 18, Total Loss: 0.4959, loss_single: 0.4959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,638 - Iter: 19, Total Loss: 0.4874, loss_single: 0.4874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,673 - Iter: 20, Total Loss: 0.4776, loss_single: 0.4776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,709 - Iter: 21, Total Loss: 0.4691, loss_single: 0.4691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,744 - Iter: 22, Total Loss: 0.4604, loss_single: 0.4604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,780 - Iter: 23, Total Loss: 0.4505, loss_single: 0.4505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,815 - Iter: 24, Total Loss: 0.4429, loss_single: 0.4429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,852 - Iter: 25, Total Loss: 0.4360, loss_single: 0.4360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:07:25,887 - Iter: 26, Total Loss: 0.4282, loss_single: 0.4282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,922 - Iter: 27, Total Loss: 0.4214, loss_single: 0.4214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,958 - Iter: 28, Total Loss: 0.4155, loss_single: 0.4155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:25,993 - Iter: 29, Total Loss: 0.4092, loss_single: 0.4092, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,029 - Iter: 30, Total Loss: 0.4030, loss_single: 0.4030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,064 - Iter: 31, Total Loss: 0.3976, loss_single: 0.3976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,099 - Iter: 32, Total Loss: 0.3925, loss_single: 0.3925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,138 - Iter: 33, Total Loss: 0.3874, loss_single: 0.3874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:07:26,173 - Iter: 34, Total Loss: 0.3830, loss_single: 0.3830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,209 - Iter: 35, Total Loss: 0.3790, loss_single: 0.3790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,244 - Iter: 36, Total Loss: 0.3750, loss_single: 0.3750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,279 - Iter: 37, Total Loss: 0.3708, loss_single: 0.3708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,315 - Iter: 38, Total Loss: 0.3673, loss_single: 0.3673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,350 - Iter: 39, Total Loss: 0.3640, loss_single: 0.3640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,385 - Iter: 40, Total Loss: 0.3613, loss_single: 0.3613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,423 - Iter: 41, Total Loss: 0.3591, loss_single: 0.3591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,458 - Iter: 42, Total Loss: 0.3562, loss_single: 0.3562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,494 - Iter: 43, Total Loss: 0.3535, loss_single: 0.3535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,529 - Iter: 44, Total Loss: 0.3513, loss_single: 0.3513, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,564 - Iter: 45, Total Loss: 0.3495, loss_single: 0.3495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,599 - Iter: 46, Total Loss: 0.3477, loss_single: 0.3477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,634 - Iter: 47, Total Loss: 0.3461, loss_single: 0.3461, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,669 - Iter: 48, Total Loss: 0.3447, loss_single: 0.3447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,704 - Iter: 49, Total Loss: 0.3436, loss_single: 0.3436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,739 - Iter: 50, Total Loss: 0.3426, loss_single: 0.3426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:26,774 - Iter: 51, Total Loss: 0.3416, loss_single: 0.3416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,810 - Iter: 52, Total Loss: 0.3406, loss_single: 0.3406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,845 - Iter: 53, Total Loss: 0.3395, loss_single: 0.3395, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,880 - Iter: 54, Total Loss: 0.3384, loss_single: 0.3384, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,915 - Iter: 55, Total Loss: 0.3374, loss_single: 0.3374, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,950 - Iter: 56, Total Loss: 0.3365, loss_single: 0.3365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:26,985 - Iter: 57, Total Loss: 0.3356, loss_single: 0.3356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,020 - Iter: 58, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,055 - Iter: 59, Total Loss: 0.3341, loss_single: 0.3341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,091 - Iter: 60, Total Loss: 0.3334, loss_single: 0.3334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,126 - Iter: 61, Total Loss: 0.3326, loss_single: 0.3326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,161 - Iter: 62, Total Loss: 0.3318, loss_single: 0.3318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,197 - Iter: 63, Total Loss: 0.3310, loss_single: 0.3310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:27,232 - Iter: 64, 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/simulation_data4__sample_000003.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/simulation_data4__sample_000003.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7a153848f81b463e21dc4b710e068875c38db095 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/simulation_data4__sample_000003.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 12.811492919921875 + probe_aberrations: + C10: -15.60432243347168 + C12: 20.307687759399414 + C21: -829.7703857421875 + C23: 387.6322021484375 + C30: 3674324.25 + C32: -10177.279296875 + C34: 4064.23291015625 + C41: -430273.5625 + C43: 262010.15625 + C45: -478581.71875 + C50: -457566976.0 + C52: 12183036.0 + C54: -2417857.75 + C56: 13191576.0 + phi12: 315.93280428552765 + phi21: 217.03450646243772 + phi23: 177.60779955405107 + phi32: 12.104323789539551 + phi34: 16.36007037362828 + phi41: 325.37827288873825 + phi43: 345.5858246803279 + phi45: 120.47767944909823 + phi52: 154.0971682798433 + phi54: 230.66723619670302 + phi56: 83.50070184880668 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4390125572681427 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000003_measurement.h5 + key: measurement + random_seed: 20261979 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000003 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000003/c30_small__simulation_data4__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-15.6_C12_20.3_phi12_316_C21_-830_phi21_217_C23_388_phi23_178_C30_3.67e+06_C32_-1.02e+04_phi32_1.5/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_.94e+05_phi56_204/20260624_060753_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:07:51,601 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:07:51,601 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:07:51,602 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:07:51,602 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:07:51,602 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:07:51,602 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:07:51,602 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:07:51,602 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:07:51,602 - +2026-06-24 06:07:51,710 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:07:51,710 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:07:51,710 - Accelerator.num_process = 1 +2026-06-24 06:07:51,710 - Accelerator.mixed_precision = no +2026-06-24 06:07:51,720 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:07:51,721 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:07:51,721 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:07:51,721 - +2026-06-24 06:07:51,721 - ### System information ### +2026-06-24 06:07:51,721 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:07:51,721 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:07:51,721 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:07:51,721 - Machine: x86_64 +2026-06-24 06:07:51,721 - Processor: x86_64 +2026-06-24 06:07:51,721 - Available CPU cores: 8 +2026-06-24 06:07:51,721 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:07:51,721 - +2026-06-24 06:07:51,721 - ### GPU information ### +2026-06-24 06:07:51,721 - CUDA Available: True +2026-06-24 06:07:51,721 - CUDA Version: 13.0 +2026-06-24 06:07:51,722 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:07:51,722 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:07:51,722 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:07:51,722 - In addition, Triton does not directly support Windows. +2026-06-24 06:07:51,722 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:07:51,749 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:07:51,749 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:07:51,749 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:07:51,749 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:07:51,749 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:07:51,749 - +2026-06-24 06:07:51,750 - ### Python information ### +2026-06-24 06:07:51,751 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:07:51,751 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:07:51,751 - +2026-06-24 06:07:51,751 - ### Packages information ### +2026-06-24 06:07:51,752 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:07:51,753 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:07:51,753 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:07:51,754 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:07:51,754 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:07:51,755 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:07:51,755 - +2026-06-24 06:07:51,755 - ### Loading params file ### +2026-06-24 06:07:51,755 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000005.yaml +2026-06-24 06:07:51,761 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:07:51,762 - Success! Params file validated and defaults applied. +2026-06-24 06:07:51,762 - +2026-06-24 06:07:51,762 - ### Setting GPU Device ### +2026-06-24 06:07:51,762 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:07:51,762 - +2026-06-24 06:07:51,762 - Random seed: 20261981 provided by params file +2026-06-24 06:07:51,763 - ### Initializing Initializer ### +2026-06-24 06:07:51,763 - init_params are displayed below: +2026-06-24 06:07:51,763 - random_seed: 20261981 +2026-06-24 06:07:51,763 - probe_illum_type: electron +2026-06-24 06:07:51,763 - probe_kv: 120.0 +2026-06-24 06:07:51,763 - probe_conv_angle: 10.68708324432373 +2026-06-24 06:07:51,763 - probe_aberrations: {'C10': -413.281, 'C12': -9.575, 'phi12': 11.263, 'C21': 378.824, 'phi21': 16.617, 'C23': 161.493, 'phi23': 287.11, 'C30': -896373.375, 'C32': 2709.798, 'phi32': 358.435, 'C34': -3648.29, 'phi34': 296.553, 'C41': -360835.375, 'phi41': 134.496, 'C43': 334841.531, 'phi43': 308.387, 'C45': 182629.141, 'phi45': 183.948, 'C50': -365274176.0, 'C52': -3431413.75, 'phi52': 133.042, 'C54': -15206738.0, 'phi54': 173.352, 'C56': -894155.562, 'phi56': 204.259} +2026-06-24 06:07:51,763 - beam_kev: None +2026-06-24 06:07:51,763 - probe_dRn: None +2026-06-24 06:07:51,763 - probe_Rn: None +2026-06-24 06:07:51,763 - probe_D_H: None +2026-06-24 06:07:51,763 - probe_D_FZP: None +2026-06-24 06:07:51,763 - probe_Ls: None +2026-06-24 06:07:51,763 - meas_Npix: 128 +2026-06-24 06:07:51,763 - pos_N_scans: 256 +2026-06-24 06:07:51,763 - pos_N_scan_slow: 16 +2026-06-24 06:07:51,763 - pos_N_scan_fast: 16 +2026-06-24 06:07:51,763 - pos_scan_step_size: 0.4925555884838104 +2026-06-24 06:07:51,763 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:07:51,763 - probe_pmode_max: 6 +2026-06-24 06:07:51,763 - probe_pmode_init_pows: [0.02] +2026-06-24 06:07:51,763 - obj_omode_max: 1 +2026-06-24 06:07:51,763 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:07:51,763 - obj_Nlayer: 1 +2026-06-24 06:07:51,764 - obj_slice_thickness: 20.0 +2026-06-24 06:07:51,764 - simu_Npix: None +2026-06-24 06:07:51,764 - simu_match_mode: None +2026-06-24 06:07:51,764 - meas_permute: None +2026-06-24 06:07:51,764 - meas_reshape: [256, 128, 128] +2026-06-24 06:07:51,764 - meas_flipT: [0, 0, 0] +2026-06-24 06:07:51,764 - meas_crop: None +2026-06-24 06:07:51,764 - meas_pad: None +2026-06-24 06:07:51,764 - meas_resample: None +2026-06-24 06:07:51,764 - meas_add_source_size: None +2026-06-24 06:07:51,764 - meas_add_detector_blur: None +2026-06-24 06:07:51,764 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:07:51,764 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:07:51,764 - meas_add_poisson_noise: None +2026-06-24 06:07:51,764 - meas_export: None +2026-06-24 06:07:51,764 - probe_permute: None +2026-06-24 06:07:51,764 - probe_z_shift: None +2026-06-24 06:07:51,764 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:07:51,764 - pos_scan_flipT: None +2026-06-24 06:07:51,764 - pos_scan_affine: None +2026-06-24 06:07:51,764 - pos_scan_rand_std: 0.15 +2026-06-24 06:07:51,764 - obj_z_crop: None +2026-06-24 06:07:51,764 - obj_z_pad: None +2026-06-24 06:07:51,764 - obj_z_resample: None +2026-06-24 06:07:51,764 - meas_source: file +2026-06-24 06:07:51,764 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000005_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:07:51,764 - probe_source: simu +2026-06-24 06:07:51,764 - probe_params: None +2026-06-24 06:07:51,764 - pos_source: simu +2026-06-24 06:07:51,764 - pos_params: None +2026-06-24 06:07:51,764 - obj_source: simu +2026-06-24 06:07:51,764 - obj_params: None +2026-06-24 06:07:51,764 - tilt_source: simu +2026-06-24 06:07:51,764 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:07:51,764 - +2026-06-24 06:07:51,764 - ### Initializing cache ### +2026-06-24 06:07:51,764 - use_cached_obj = False +2026-06-24 06:07:51,764 - use_cached_probe = False +2026-06-24 06:07:51,765 - use_cached_pos = False +2026-06-24 06:07:51,765 - +2026-06-24 06:07:51,765 - ### Initializing measurements ### +2026-06-24 06:07:51,765 - Loading measurements from source = 'file' +2026-06-24 06:07:51,765 - Detected measurement file type = '.h5' +2026-06-24 06:07:51,843 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:07:51,843 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:07:51,845 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0055) +2026-06-24 06:07:51,845 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:07:51,845 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:07:51,847 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:07:51,847 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:07:51,847 - Normalizing by max of the 2D mean pattern intensity: 0.0046219314 +2026-06-24 06:07:51,848 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:07:51,849 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0132, 1.1978) +2026-06-24 06:07:51,850 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:07:51,851 - Pattern total int. statistics (min, mean, max) = (214.0719, 216.0548, 218.1823), with min/max = 98.1% +2026-06-24 06:07:51,852 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0132, 1.1978) +2026-06-24 06:07:51,852 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:07:51,852 - +2026-06-24 06:07:51,853 - ### Setting up calibration ### +2026-06-24 06:07:51,853 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:07:51,853 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:07:51,853 - Radius of fitted bright field disk (RBF) = 8.06 px with meas_Npix = 128 +2026-06-24 06:07:51,853 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1259 +2026-06-24 06:07:51,853 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:07:51,853 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:07:52,076 - Initial guess: center=(63.62, 63.62), radius=8.06, Gaussian blur std=0.50 +2026-06-24 06:07:52,089 - Final fit: center=(63.62, 63.62), radius=8.06, Gaussian blur std=0.66 +2026-06-24 06:07:52,089 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.17 px with Npix = 128 +2026-06-24 06:07:52,089 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:07:52,089 - +2026-06-24 06:07:52,089 - ### Setting init_variables dict ### +2026-06-24 06:07:52,089 - Derived values given input init_params: +2026-06-24 06:07:52,089 - kv = 120.0 kV +2026-06-24 06:07:52,089 - wavelength = 0.0335 Ang +2026-06-24 06:07:52,089 - conv_angle = 10.68708324432373 mrad +2026-06-24 06:07:52,089 - Npix = 128 px +2026-06-24 06:07:52,089 - dk = 0.0391 Ang^-1 +2026-06-24 06:07:52,089 - kMax = 2.5000 Ang^-1 +2026-06-24 06:07:52,089 - da = 1.3083 mrad +2026-06-24 06:07:52,089 - angleMax = 83.7304 mrad +2026-06-24 06:07:52,089 - RBF = 8.1688 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:07:52,089 - n_alpha = 7.8347 (# conv_angle) +2026-06-24 06:07:52,089 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:07:52,089 - Rayleigh-limited resolution = 1.9117 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:07:52,090 - Real space probe extent = 25.6000 Ang +2026-06-24 06:07:52,090 - +2026-06-24 06:07:52,090 - ### Initializing probe ### +2026-06-24 06:07:52,090 - Loading probe from source = 'simu' +2026-06-24 06:07:52,090 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:07:52,090 - Start simulating STEM probe +2026-06-24 06:07:52,090 - kv = 120.0 kV +2026-06-24 06:07:52,090 - wavelength = 0.0335 Ang +2026-06-24 06:07:52,090 - conv_angle = 10.68708324432373 mrad +2026-06-24 06:07:52,090 - Npix = 128 px +2026-06-24 06:07:52,090 - dk = 0.0391 Ang^-1 +2026-06-24 06:07:52,090 - kMax = 2.5000 Ang^-1 +2026-06-24 06:07:52,090 - alpha_max = 83.7304 mrad +2026-06-24 06:07:52,090 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:07:52,090 - Rayleigh-limited resolution = 1.9117 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:07:52,090 - Real space probe extent = 25.6000 Ang +2026-06-24 06:07:52,090 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:07:52,090 - ------------------------------------------------------------------------------------- +2026-06-24 06:07:52,090 - C1,0 C1 -413.2810 - Defocus (C10 = -df) +2026-06-24 06:07:52,090 - C1,2 A1 -9.5750 11.26 2-fold astigmatism +2026-06-24 06:07:52,090 - C2,1 3*B2 378.8240 16.62 Axial coma +2026-06-24 06:07:52,090 - C2,3 A2 161.4930 287.11 3-fold astigmatism +2026-06-24 06:07:52,090 - C3,0 C3 -896373.3750 - Spherical aberration +2026-06-24 06:07:52,090 - C3,2 4*S3 2709.7980 358.44 Axial star aberration +2026-06-24 06:07:52,091 - C3,4 A3 -3648.2900 296.55 4-fold astigmatism +2026-06-24 06:07:52,091 - C4,1 4*B4 -360835.3750 134.50 Axial coma(4th) +2026-06-24 06:07:52,091 - C4,3 4*D4 334841.5310 308.39 3-lobe aberration +2026-06-24 06:07:52,091 - C4,5 A4 182629.1410 183.95 5-fold astigmatism +2026-06-24 06:07:52,091 - C5,0 C5 -365274176.0000 - Spherical aberration (5th) +2026-06-24 06:07:52,091 - C5,2 6*S5 -3431413.7500 133.04 Axial star aberration(5th) +2026-06-24 06:07:52,091 - C5,4 6*R5 -15206738.0000 173.35 4-lobe aberration +2026-06-24 06:07:52,091 - C5,6 A5 -894155.5620 204.26 6-fold astigmatism +2026-06-24 06:07:52,093 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:07:52,094 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:07:52,094 - Creating 5 new probe modes from the major mode +2026-06-24 06:07:52,094 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:07:52,190 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:07:52,191 - Orthogonalizing 6 pmodes +2026-06-24 06:07:52,193 - Sorting 6 pmodes by their intensities +2026-06-24 06:07:52,193 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:07:52,194 - sum(|probe_data|**2) = 216.05, while meas_total_ints (min, mean, max) = (214.0719, 216.0548, 218.1823) +2026-06-24 06:07:52,194 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:07:52,194 - +2026-06-24 06:07:52,194 - ### Initializing probe positions ### +2026-06-24 06:07:52,194 - Loading probe positions from source = 'simu' +2026-06-24 06:07:52,194 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:07:52,194 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4926, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:07:52,194 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:07:52,196 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:07:52,196 - crop_pos 1st and last px coords (y,x) = ([16, 17], [54, 54]) +2026-06-24 06:07:52,196 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:07:52,197 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:07:52,197 - +2026-06-24 06:07:52,197 - ### Initializing object ### +2026-06-24 06:07:52,197 - Loading object from source = 'simu' +2026-06-24 06:07:52,197 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:07:52,198 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:07:52,198 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 06:07:52,198 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 06:07:52,198 - +2026-06-24 06:07:52,198 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:07:52,198 - omode_occu (omode) = float32, (1,) +2026-06-24 06:07:52,199 - +2026-06-24 06:07:52,199 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:07:52,199 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:07:52,199 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:07:52,199 - +2026-06-24 06:07:52,199 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:07:52,199 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:07:52,199 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:07:52,199 - +2026-06-24 06:07:52,199 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:07:52,199 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:07:52,200 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:07:52,200 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:07:52,200 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:07:52,200 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 06:07:52,200 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:07:52,200 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:07:52,200 - +2026-06-24 06:07:52,200 - ### Collecting reconstruction provenance ### +2026-06-24 06:07:52,200 - Reconstruction provenance is collected and initialized. +2026-06-24 06:07:52,200 - +2026-06-24 06:07:52,200 - ### Initializing loss function ### +2026-06-24 06:07:52,200 - Active loss types: +2026-06-24 06:07:52,200 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:07:52,200 - +2026-06-24 06:07:52,200 - ### Initializing constraint function ### +2026-06-24 06:07:52,200 - Active constraint types: +2026-06-24 06:07:52,200 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:07:52,200 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:07:52,200 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:07:52,200 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:07:52,200 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:07:52,201 - +2026-06-24 06:07:52,201 - ### Done initializing PtyRADSolver ### +2026-06-24 06:07:52,201 - +2026-06-24 06:07:52,326 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:07:52,327 - +2026-06-24 06:07:52,327 - ### Initializing PtychoModel model ### +2026-06-24 06:07:52,397 - ### PtychoModel optimizable variables ### +2026-06-24 06:07:52,397 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:52,397 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:52,397 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:07:52,397 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:07:52,397 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:07:52,397 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:07:52,397 - +2026-06-24 06:07:52,397 - ### Optimizable variables statitsics ### +2026-06-24 06:07:52,397 - Total measurement values : 4,194,304 +2026-06-24 06:07:52,397 - Total optimizing variables: 276,322 +2026-06-24 06:07:52,397 - Overdetermined ratio : 15.18 +2026-06-24 06:07:52,398 - +2026-06-24 06:07:52,398 - ### Model behavior ### +2026-06-24 06:07:52,398 - Tilt propagator : False +2026-06-24 06:07:52,398 - Change slice thickness : False +2026-06-24 06:07:52,398 - Detector blur : False +2026-06-24 06:07:52,398 - Preload data : True +2026-06-24 06:07:52,398 - On-the-fly meas padding : False +2026-06-24 06:07:52,398 - On-the-fly meas resample : False +2026-06-24 06:07:52,398 - On-the-fly simu match mode: None +2026-06-24 06:07:52,398 - +2026-06-24 06:07:52,439 - ### Done initializing PtychoModel model ### +2026-06-24 06:07:52,439 - +2026-06-24 06:07:52,439 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:07:52,439 - +2026-06-24 06:07:52,439 - ### Generating indices, batches, and output_path ### +2026-06-24 06:07:52,441 - d90 = 65.000 px or 13.000 Ang +2026-06-24 06:07:52,441 - Selecting indices with the 'full' mode +2026-06-24 06:07:52,905 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:07:52,981 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:07:52,981 - Original recon_dir_affixes = ['default'] +2026-06-24 06:07:52,981 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:07:52,988 - Path corrected for compatibility: +2026-06-24 06:07:52,988 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_2.71e+03_phi32_358_C34_-3.65e+03_phi34_297_C41_-3.61e+05_phi41_134_C43_3.35e+05_phi43_308_C45_1.83e+05_phi45_184_C50_-3.65e+08_C52_-3.43e+06_phi52_133_C54_-1.52e+07_phi54_173_C56_-8.94e+05_phi56_204 +2026-06-24 06:07:52,988 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_.94e+05_phi56_204 +2026-06-24 06:07:52,989 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_.94e+05_phi56_204' is generated! +2026-06-24 06:07:53,142 - +2026-06-24 06:07:53,143 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_.94e+05_phi56_204/20260624_060753_ptyrad_log.txt ### +2026-06-24 06:07:53,143 - +2026-06-24 06:07:53,145 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:07:53,145 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:07:53,145 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:07:54,345 - Iter: 1, Total Loss: 1.0946, loss_single: 1.0946, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:07:54,382 - Iter: 2, Total Loss: 1.0307, loss_single: 1.0307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:07:54,418 - Iter: 3, Total Loss: 0.9777, loss_single: 0.9777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,453 - Iter: 4, Total Loss: 0.9296, loss_single: 0.9296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,489 - Iter: 5, Total Loss: 0.8910, loss_single: 0.8910, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:07:54,524 - Iter: 6, Total Loss: 0.8528, loss_single: 0.8528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,560 - Iter: 7, Total Loss: 0.8090, loss_single: 0.8090, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,595 - Iter: 8, Total Loss: 0.7720, loss_single: 0.7720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,631 - Iter: 9, Total Loss: 0.7350, loss_single: 0.7350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:07:54,666 - Iter: 10, Total Loss: 0.6951, loss_single: 0.6951, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,701 - Iter: 11, Total Loss: 0.6542, loss_single: 0.6542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,737 - Iter: 12, Total Loss: 0.6117, loss_single: 0.6117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,773 - Iter: 13, Total Loss: 0.5768, loss_single: 0.5768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,808 - Iter: 14, Total Loss: 0.5486, loss_single: 0.5486, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,844 - Iter: 15, Total Loss: 0.5248, loss_single: 0.5248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,879 - Iter: 16, Total Loss: 0.5019, loss_single: 0.5019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,915 - Iter: 17, Total Loss: 0.4793, loss_single: 0.4793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,950 - Iter: 18, Total Loss: 0.4558, loss_single: 0.4558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:54,986 - Iter: 19, Total Loss: 0.4317, loss_single: 0.4317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,021 - Iter: 20, Total Loss: 0.4120, loss_single: 0.4120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,057 - Iter: 21, Total Loss: 0.3941, loss_single: 0.3941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,093 - Iter: 22, Total Loss: 0.3779, loss_single: 0.3779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,128 - Iter: 23, Total Loss: 0.3655, loss_single: 0.3655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,164 - Iter: 24, Total Loss: 0.3567, loss_single: 0.3567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,199 - Iter: 25, Total Loss: 0.3496, loss_single: 0.3496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,235 - Iter: 26, Total Loss: 0.3458, loss_single: 0.3458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,270 - Iter: 27, Total Loss: 0.3434, loss_single: 0.3434, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,305 - Iter: 28, Total Loss: 0.3405, loss_single: 0.3405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,341 - Iter: 29, Total Loss: 0.3384, loss_single: 0.3384, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,379 - Iter: 30, Total Loss: 0.3369, loss_single: 0.3369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:07:55,415 - Iter: 31, Total Loss: 0.3353, loss_single: 0.3353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,450 - Iter: 32, Total Loss: 0.3339, loss_single: 0.3339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,485 - Iter: 33, Total Loss: 0.3327, loss_single: 0.3327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,521 - Iter: 34, Total Loss: 0.3319, loss_single: 0.3319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,556 - Iter: 35, Total Loss: 0.3313, loss_single: 0.3313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,591 - Iter: 36, Total Loss: 0.3308, loss_single: 0.3308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,627 - Iter: 37, Total Loss: 0.3303, loss_single: 0.3303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,662 - Iter: 38, Total Loss: 0.3300, loss_single: 0.3300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,698 - Iter: 39, Total Loss: 0.3297, loss_single: 0.3297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,733 - Iter: 40, Total Loss: 0.3294, loss_single: 0.3294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,770 - Iter: 41, Total Loss: 0.3291, loss_single: 0.3291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,806 - Iter: 42, Total Loss: 0.3289, loss_single: 0.3289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,841 - Iter: 43, Total Loss: 0.3287, loss_single: 0.3287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,876 - Iter: 44, Total Loss: 0.3285, loss_single: 0.3285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:55,911 - Iter: 45, Total Loss: 0.3283, loss_single: 0.3283, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:55,946 - Iter: 46, Total Loss: 0.3281, loss_single: 0.3281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:55,981 - Iter: 47, Total Loss: 0.3279, loss_single: 0.3279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,016 - Iter: 48, Total Loss: 0.3278, loss_single: 0.3278, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,051 - Iter: 49, Total Loss: 0.3277, loss_single: 0.3277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,086 - Iter: 50, Total Loss: 0.3275, loss_single: 0.3275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,121 - Iter: 51, Total Loss: 0.3274, loss_single: 0.3274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,157 - Iter: 52, Total Loss: 0.3273, loss_single: 0.3273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,192 - Iter: 53, Total Loss: 0.3272, loss_single: 0.3272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,228 - Iter: 54, Total Loss: 0.3271, loss_single: 0.3271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,263 - Iter: 55, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,299 - Iter: 56, Total Loss: 0.3269, loss_single: 0.3269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,333 - Iter: 57, Total Loss: 0.3268, loss_single: 0.3268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:56,368 - Iter: 58, Total Loss: 0.3267, loss_single: 0.3267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,404 - Iter: 59, Total Loss: 0.3266, loss_single: 0.3266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,440 - Iter: 60, Total Loss: 0.3265, loss_single: 0.3265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,475 - Iter: 61, Total Loss: 0.3264, loss_single: 0.3264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,510 - Iter: 62, Total Loss: 0.3263, loss_single: 0.3263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:56,545 - Iter: 63, Total Loss: 0.3262, loss_single: 0.3262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,580 - Iter: 64, 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in 0.035 sec +2026-06-24 06:07:56,791 - Iter: 70, Total Loss: 0.3258, loss_single: 0.3258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,826 - Iter: 71, Total Loss: 0.3257, loss_single: 0.3257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,862 - Iter: 72, Total Loss: 0.3256, loss_single: 0.3256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,897 - Iter: 73, Total Loss: 0.3256, loss_single: 0.3256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,932 - Iter: 74, Total Loss: 0.3255, loss_single: 0.3255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:56,967 - Iter: 75, Total Loss: 0.3254, loss_single: 0.3254, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.3250, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,214 - Iter: 82, Total Loss: 0.3249, loss_single: 0.3249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,255 - Iter: 83, Total Loss: 0.3249, loss_single: 0.3249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 06:07:57,294 - Iter: 84, Total Loss: 0.3248, loss_single: 0.3248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:07:57,329 - Iter: 85, Total Loss: 0.3247, loss_single: 0.3247, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,365 - Iter: 86, Total Loss: 0.3246, loss_single: 0.3246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,401 - Iter: 87, Total Loss: 0.3246, loss_single: 0.3246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,435 - Iter: 88, Total Loss: 0.3245, loss_single: 0.3245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:07:57,470 - Iter: 89, Total Loss: 0.3244, loss_single: 0.3244, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,506 - Iter: 90, Total Loss: 0.3243, loss_single: 0.3243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,541 - Iter: 91, Total Loss: 0.3242, loss_single: 0.3242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,579 - Iter: 92, Total Loss: 0.3242, loss_single: 0.3242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:07:57,614 - Iter: 93, Total Loss: 0.3241, loss_single: 0.3241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,649 - Iter: 94, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,684 - Iter: 95, Total Loss: 0.3239, loss_single: 0.3239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,720 - Iter: 96, Total Loss: 0.3239, loss_single: 0.3239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,755 - Iter: 97, Total Loss: 0.3238, loss_single: 0.3238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,790 - Iter: 98, Total Loss: 0.3237, loss_single: 0.3237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,825 - Iter: 99, Total Loss: 0.3236, loss_single: 0.3236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:07:57,867 - Iter: 100, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.041 sec +2026-06-24 06:07:57,977 - Saving summary figures for iter 100 +2026-06-24 06:08:01,624 - ### Finished 100 iterations, averaged iter_t = 0.039159 with std = 0.040 ### +2026-06-24 06:08:01,624 - +2026-06-24 06:08:01,624 - ### The PtyRADSolver is finished in 9.297 sec ### +2026-06-24 06:08:01,624 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000005/c30_small__simulation_data4__sample_000005_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-413_C12_-9.57_phi12_11.3_C21_379_phi21_16.6_C23_161_phi23_287_C30_-8.96e+05_C32_.94e+05_phi56_204/simulation_data4__sample_000005.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 10.68708324432373 + probe_aberrations: + C10: -413.2811279296875 + C12: -9.57466983795166 + C21: 378.8238220214844 + C23: 161.49258422851562 + C30: -896373.375 + C32: 2709.79833984375 + C34: -3648.28955078125 + C41: -360835.375 + C43: 334841.53125 + C45: 182629.140625 + C50: -365274176.0 + C52: -3431413.75 + C54: -15206738.0 + C56: -894155.5625 + phi12: 11.262836799831163 + phi21: 16.617360184568074 + phi23: 287.1101709692609 + phi32: 358.4352409998194 + phi34: 296.55326266664036 + phi41: 134.49608264503746 + phi43: 308.38664736595746 + phi45: 183.94845540587067 + phi52: 133.0422222386869 + phi54: 173.3522775124313 + phi56: 204.25899278976573 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4925555884838104 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000005_measurement.h5 + key: measurement + random_seed: 20261981 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:f914977fac83a70791c2590e529cbb5d7f6d2b632c43c6c5ea877516ef38381b +size 48596 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/20260624_060807_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/20260624_060807_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..01135a980b069e8218fddcadf0d9a823ac1a5263 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/20260624_060807_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:08:06,126 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:08:06,126 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:08:06,126 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:08:06,126 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:08:06,126 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:08:06,126 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:08:06,126 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:08:06,126 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:08:06,126 - +2026-06-24 06:08:06,235 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:08:06,235 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:08:06,235 - Accelerator.num_process = 1 +2026-06-24 06:08:06,235 - Accelerator.mixed_precision = no +2026-06-24 06:08:06,246 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:08:06,246 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:08:06,246 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:08:06,246 - +2026-06-24 06:08:06,246 - ### System information ### +2026-06-24 06:08:06,246 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:08:06,246 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:08:06,246 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:08:06,246 - Machine: x86_64 +2026-06-24 06:08:06,246 - Processor: x86_64 +2026-06-24 06:08:06,246 - Available CPU cores: 8 +2026-06-24 06:08:06,246 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:08:06,246 - +2026-06-24 06:08:06,246 - ### GPU information ### +2026-06-24 06:08:06,246 - CUDA Available: True +2026-06-24 06:08:06,246 - CUDA Version: 13.0 +2026-06-24 06:08:06,247 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:08:06,247 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:08:06,247 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:08:06,247 - In addition, Triton does not directly support Windows. +2026-06-24 06:08:06,247 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:08:06,262 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:08:06,262 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:08:06,262 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:08:06,262 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:08:06,262 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:08:06,262 - +2026-06-24 06:08:06,263 - ### Python information ### +2026-06-24 06:08:06,264 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:08:06,264 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:08:06,264 - +2026-06-24 06:08:06,264 - ### Packages information ### +2026-06-24 06:08:06,265 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:08:06,266 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:08:06,266 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:08:06,267 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:08:06,267 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:08:06,268 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:08:06,268 - +2026-06-24 06:08:06,268 - ### Loading params file ### +2026-06-24 06:08:06,268 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000006.yaml +2026-06-24 06:08:06,275 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:08:06,276 - Success! Params file validated and defaults applied. +2026-06-24 06:08:06,276 - +2026-06-24 06:08:06,276 - ### Setting GPU Device ### +2026-06-24 06:08:06,276 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:08:06,276 - +2026-06-24 06:08:06,276 - Random seed: 20261982 provided by params file +2026-06-24 06:08:06,276 - ### Initializing Initializer ### +2026-06-24 06:08:06,276 - init_params are displayed below: +2026-06-24 06:08:06,276 - random_seed: 20261982 +2026-06-24 06:08:06,276 - probe_illum_type: electron +2026-06-24 06:08:06,276 - probe_kv: 100.0 +2026-06-24 06:08:06,276 - probe_conv_angle: 17.585540771484375 +2026-06-24 06:08:06,276 - probe_aberrations: {'C10': -237.601, 'C12': -41.409, 'phi12': 93.295, 'C21': 980.989, 'phi21': 77.523, 'C23': 132.0, 'phi23': 111.071, 'C30': -17005.092, 'C32': 2283.062, 'phi32': 20.353, 'C34': -5925.74, 'phi34': 71.661, 'C41': 435723.938, 'phi41': 309.391, 'C43': 162406.156, 'phi43': 345.874, 'C45': 370306.719, 'phi45': 193.361, 'C50': 440309888.0, 'C52': -7033548.5, 'phi52': 81.353, 'C54': -753318.438, 'phi54': 106.24, 'C56': -1329729.75, 'phi56': 221.465} +2026-06-24 06:08:06,276 - beam_kev: None +2026-06-24 06:08:06,277 - probe_dRn: None +2026-06-24 06:08:06,277 - probe_Rn: None +2026-06-24 06:08:06,277 - probe_D_H: None +2026-06-24 06:08:06,277 - probe_D_FZP: None +2026-06-24 06:08:06,277 - probe_Ls: None +2026-06-24 06:08:06,277 - meas_Npix: 128 +2026-06-24 06:08:06,277 - pos_N_scans: 256 +2026-06-24 06:08:06,277 - pos_N_scan_slow: 16 +2026-06-24 06:08:06,277 - pos_N_scan_fast: 16 +2026-06-24 06:08:06,277 - pos_scan_step_size: 0.5161117911338806 +2026-06-24 06:08:06,277 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:08:06,277 - probe_pmode_max: 6 +2026-06-24 06:08:06,277 - probe_pmode_init_pows: [0.02] +2026-06-24 06:08:06,277 - obj_omode_max: 1 +2026-06-24 06:08:06,277 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:08:06,277 - obj_Nlayer: 1 +2026-06-24 06:08:06,277 - obj_slice_thickness: 20.0 +2026-06-24 06:08:06,277 - simu_Npix: None +2026-06-24 06:08:06,277 - simu_match_mode: None +2026-06-24 06:08:06,277 - meas_permute: None +2026-06-24 06:08:06,277 - meas_reshape: [256, 128, 128] +2026-06-24 06:08:06,277 - meas_flipT: [0, 0, 0] +2026-06-24 06:08:06,277 - meas_crop: None +2026-06-24 06:08:06,277 - meas_pad: None +2026-06-24 06:08:06,277 - meas_resample: None +2026-06-24 06:08:06,277 - meas_add_source_size: None +2026-06-24 06:08:06,277 - meas_add_detector_blur: None +2026-06-24 06:08:06,277 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:08:06,277 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:08:06,277 - meas_add_poisson_noise: None +2026-06-24 06:08:06,277 - meas_export: None +2026-06-24 06:08:06,277 - probe_permute: None +2026-06-24 06:08:06,277 - probe_z_shift: None +2026-06-24 06:08:06,277 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:08:06,277 - pos_scan_flipT: None +2026-06-24 06:08:06,277 - pos_scan_affine: None +2026-06-24 06:08:06,277 - pos_scan_rand_std: 0.15 +2026-06-24 06:08:06,277 - obj_z_crop: None +2026-06-24 06:08:06,277 - obj_z_pad: None +2026-06-24 06:08:06,277 - obj_z_resample: None +2026-06-24 06:08:06,277 - meas_source: file +2026-06-24 06:08:06,278 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000006_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:08:06,278 - probe_source: simu +2026-06-24 06:08:06,278 - probe_params: None +2026-06-24 06:08:06,278 - pos_source: simu +2026-06-24 06:08:06,278 - pos_params: None +2026-06-24 06:08:06,278 - obj_source: simu +2026-06-24 06:08:06,278 - obj_params: None +2026-06-24 06:08:06,278 - tilt_source: simu +2026-06-24 06:08:06,278 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:08:06,278 - +2026-06-24 06:08:06,278 - ### Initializing cache ### +2026-06-24 06:08:06,278 - use_cached_obj = False +2026-06-24 06:08:06,278 - use_cached_probe = False +2026-06-24 06:08:06,278 - use_cached_pos = False +2026-06-24 06:08:06,278 - +2026-06-24 06:08:06,278 - ### Initializing measurements ### +2026-06-24 06:08:06,278 - Loading measurements from source = 'file' +2026-06-24 06:08:06,278 - Detected measurement file type = '.h5' +2026-06-24 06:08:06,352 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:08:06,353 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:08:06,354 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0029) +2026-06-24 06:08:06,354 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:08:06,354 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:08:06,356 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:08:06,356 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:08:06,357 - Normalizing by max of the 2D mean pattern intensity: 0.0021921801 +2026-06-24 06:08:06,357 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:08:06,358 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0279, 1.3235) +2026-06-24 06:08:06,359 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:08:06,360 - Pattern total int. statistics (min, mean, max) = (451.6024, 456.4509, 459.7826), with min/max = 98.2% +2026-06-24 06:08:06,361 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0279, 1.3235) +2026-06-24 06:08:06,362 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:08:06,362 - +2026-06-24 06:08:06,362 - ### Setting up calibration ### +2026-06-24 06:08:06,362 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:08:06,362 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:08:06,362 - Radius of fitted bright field disk (RBF) = 12.06 px with meas_Npix = 128 +2026-06-24 06:08:06,362 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1885 +2026-06-24 06:08:06,362 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:08:06,362 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:08:06,579 - Initial guess: center=(63.63, 63.63), radius=12.06, Gaussian blur std=0.50 +2026-06-24 06:08:06,591 - Final fit: center=(63.63, 63.63), radius=12.06, Gaussian blur std=0.66 +2026-06-24 06:08:06,591 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.16 px with Npix = 128 +2026-06-24 06:08:06,591 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:08:06,591 - +2026-06-24 06:08:06,592 - ### Setting init_variables dict ### +2026-06-24 06:08:06,592 - Derived values given input init_params: +2026-06-24 06:08:06,592 - kv = 100.0 kV +2026-06-24 06:08:06,592 - wavelength = 0.0370 Ang +2026-06-24 06:08:06,592 - conv_angle = 17.585540771484375 mrad +2026-06-24 06:08:06,592 - Npix = 128 px +2026-06-24 06:08:06,592 - dk = 0.0391 Ang^-1 +2026-06-24 06:08:06,592 - kMax = 2.5000 Ang^-1 +2026-06-24 06:08:06,592 - da = 1.4459 mrad +2026-06-24 06:08:06,592 - angleMax = 92.5359 mrad +2026-06-24 06:08:06,592 - RBF = 12.1626 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:08:06,592 - n_alpha = 5.2620 (# conv_angle) +2026-06-24 06:08:06,592 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:08:06,592 - Rayleigh-limited resolution = 1.2839 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:08:06,592 - Real space probe extent = 25.6000 Ang +2026-06-24 06:08:06,592 - +2026-06-24 06:08:06,592 - ### Initializing probe ### +2026-06-24 06:08:06,592 - Loading probe from source = 'simu' +2026-06-24 06:08:06,592 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:08:06,592 - Start simulating STEM probe +2026-06-24 06:08:06,592 - kv = 100.0 kV +2026-06-24 06:08:06,592 - wavelength = 0.0370 Ang +2026-06-24 06:08:06,592 - conv_angle = 17.585540771484375 mrad +2026-06-24 06:08:06,592 - Npix = 128 px +2026-06-24 06:08:06,592 - dk = 0.0391 Ang^-1 +2026-06-24 06:08:06,593 - kMax = 2.5000 Ang^-1 +2026-06-24 06:08:06,593 - alpha_max = 92.5359 mrad +2026-06-24 06:08:06,593 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:08:06,593 - Rayleigh-limited resolution = 1.2839 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:08:06,593 - Real space probe extent = 25.6000 Ang +2026-06-24 06:08:06,593 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:08:06,593 - ------------------------------------------------------------------------------------ +2026-06-24 06:08:06,593 - C1,0 C1 -237.6010 - Defocus (C10 = -df) +2026-06-24 06:08:06,593 - C1,2 A1 -41.4090 93.30 2-fold astigmatism +2026-06-24 06:08:06,593 - C2,1 3*B2 980.9890 77.52 Axial coma +2026-06-24 06:08:06,593 - C2,3 A2 132.0000 111.07 3-fold astigmatism +2026-06-24 06:08:06,593 - C3,0 C3 -17005.0920 - Spherical aberration +2026-06-24 06:08:06,593 - C3,2 4*S3 2283.0620 20.35 Axial star aberration +2026-06-24 06:08:06,593 - C3,4 A3 -5925.7400 71.66 4-fold astigmatism +2026-06-24 06:08:06,593 - C4,1 4*B4 435723.9380 309.39 Axial coma(4th) +2026-06-24 06:08:06,593 - C4,3 4*D4 162406.1560 345.87 3-lobe aberration +2026-06-24 06:08:06,593 - C4,5 A4 370306.7190 193.36 5-fold astigmatism +2026-06-24 06:08:06,593 - C5,0 C5 440309888.0000 - Spherical aberration (5th) +2026-06-24 06:08:06,593 - C5,2 6*S5 -7033548.5000 81.35 Axial star aberration(5th) +2026-06-24 06:08:06,593 - C5,4 6*R5 -753318.4380 106.24 4-lobe aberration +2026-06-24 06:08:06,593 - C5,6 A5 -1329729.7500 221.47 6-fold astigmatism +2026-06-24 06:08:06,596 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:08:06,596 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:08:06,596 - Creating 5 new probe modes from the major mode +2026-06-24 06:08:06,596 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:08:06,788 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:08:06,789 - Orthogonalizing 6 pmodes +2026-06-24 06:08:06,792 - Sorting 6 pmodes by their intensities +2026-06-24 06:08:06,792 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:08:06,793 - sum(|probe_data|**2) = 456.45, while meas_total_ints (min, mean, max) = (451.6024, 456.4509, 459.7826) +2026-06-24 06:08:06,793 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:08:06,793 - +2026-06-24 06:08:06,793 - ### Initializing probe positions ### +2026-06-24 06:08:06,793 - Loading probe positions from source = 'simu' +2026-06-24 06:08:06,793 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:08:06,793 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5161, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:08:06,793 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:08:06,795 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:08:06,795 - crop_pos 1st and last px coords (y,x) = ([17, 17], [55, 55]) +2026-06-24 06:08:06,796 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 06:08:06,796 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:08:06,796 - +2026-06-24 06:08:06,796 - ### Initializing object ### +2026-06-24 06:08:06,796 - Loading object from source = 'simu' +2026-06-24 06:08:06,796 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:08:06,797 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:08:06,797 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 201, 201) +2026-06-24 06:08:06,797 - object extent (Z, Y, X) (Ang) = [20. 40.2 40.2] +2026-06-24 06:08:06,798 - +2026-06-24 06:08:06,798 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:08:06,798 - omode_occu (omode) = float32, (1,) +2026-06-24 06:08:06,798 - +2026-06-24 06:08:06,798 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:08:06,798 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:08:06,798 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:08:06,798 - +2026-06-24 06:08:06,798 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:08:06,798 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:08:06,798 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:08:06,799 - +2026-06-24 06:08:06,799 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:08:06,799 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:08:06,799 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:08:06,799 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:08:06,799 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:08:06,799 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (201, 201). +2026-06-24 06:08:06,799 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:08:06,799 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:08:06,799 - +2026-06-24 06:08:06,799 - ### Collecting reconstruction provenance ### +2026-06-24 06:08:06,799 - Reconstruction provenance is collected and initialized. +2026-06-24 06:08:06,799 - +2026-06-24 06:08:06,799 - ### Initializing loss function ### +2026-06-24 06:08:06,799 - Active loss types: +2026-06-24 06:08:06,799 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:08:06,799 - +2026-06-24 06:08:06,799 - ### Initializing constraint function ### +2026-06-24 06:08:06,799 - Active constraint types: +2026-06-24 06:08:06,799 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:08:06,799 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:08:06,800 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:08:06,800 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:08:06,800 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:08:06,800 - +2026-06-24 06:08:06,800 - ### Done initializing PtyRADSolver ### +2026-06-24 06:08:06,800 - +2026-06-24 06:08:06,923 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:08:06,923 - +2026-06-24 06:08:06,923 - ### Initializing PtychoModel model ### +2026-06-24 06:08:06,994 - ### PtychoModel optimizable variables ### +2026-06-24 06:08:06,994 - obja : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:06,994 - objp : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:06,994 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:08:06,994 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:08:06,994 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:08:06,994 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:06,994 - +2026-06-24 06:08:06,994 - ### Optimizable variables statitsics ### +2026-06-24 06:08:06,994 - Total measurement values : 4,194,304 +2026-06-24 06:08:06,994 - Total optimizing variables: 277,922 +2026-06-24 06:08:06,994 - Overdetermined ratio : 15.09 +2026-06-24 06:08:06,994 - +2026-06-24 06:08:06,994 - ### Model behavior ### +2026-06-24 06:08:06,994 - Tilt propagator : False +2026-06-24 06:08:06,994 - Change slice thickness : False +2026-06-24 06:08:06,994 - Detector blur : False +2026-06-24 06:08:06,994 - Preload data : True +2026-06-24 06:08:06,994 - On-the-fly meas padding : False +2026-06-24 06:08:06,994 - On-the-fly meas resample : False +2026-06-24 06:08:06,994 - On-the-fly simu match mode: None +2026-06-24 06:08:06,994 - +2026-06-24 06:08:07,036 - ### Done initializing PtychoModel model ### +2026-06-24 06:08:07,036 - +2026-06-24 06:08:07,037 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:08:07,037 - +2026-06-24 06:08:07,037 - ### Generating indices, batches, and output_path ### +2026-06-24 06:08:07,038 - d90 = 49.000 px or 9.800 Ang +2026-06-24 06:08:07,038 - Selecting indices with the 'full' mode +2026-06-24 06:08:07,502 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:08:07,579 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:08:07,615 - Original recon_dir_affixes = ['default'] +2026-06-24 06:08:07,615 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:08:07,622 - Path corrected for compatibility: +2026-06-24 06:08:07,622 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.28e+03_phi32_20.4_C34_-5.93e+03_phi34_71.7_C41_4.36e+05_phi41_309_C43_1.62e+05_phi43_346_C45_3.7e+05_phi45_193_C50_4.4e+08_C52_-7.03e+06_phi52_81.4_C54_-7.53e+05_phi54_106_C56_-1.33e+06_phi56_221 +2026-06-24 06:08:07,622 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221 +2026-06-24 06:08:07,623 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221' is generated! +2026-06-24 06:08:07,775 - +2026-06-24 06:08:07,776 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/20260624_060807_ptyrad_log.txt ### +2026-06-24 06:08:07,776 - +2026-06-24 06:08:07,778 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:08:07,778 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:08:07,778 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:08:08,973 - Iter: 1, Total Loss: 0.7971, loss_single: 0.7971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:08:09,009 - Iter: 2, Total Loss: 0.7543, loss_single: 0.7543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:08:09,045 - Iter: 3, Total Loss: 0.7196, loss_single: 0.7196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,080 - Iter: 4, Total Loss: 0.6876, loss_single: 0.6876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,115 - Iter: 5, Total Loss: 0.6613, loss_single: 0.6613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,150 - Iter: 6, Total Loss: 0.6339, loss_single: 0.6339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,186 - Iter: 7, Total Loss: 0.6063, loss_single: 0.6063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,225 - Iter: 8, Total Loss: 0.5816, loss_single: 0.5816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:08:09,265 - Iter: 9, Total Loss: 0.5614, loss_single: 0.5614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:08:09,300 - Iter: 10, Total Loss: 0.5427, loss_single: 0.5427, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,335 - Iter: 11, Total Loss: 0.5236, loss_single: 0.5236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,370 - Iter: 12, Total Loss: 0.5074, loss_single: 0.5074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,405 - Iter: 13, Total Loss: 0.4940, loss_single: 0.4940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,440 - Iter: 14, Total Loss: 0.4803, loss_single: 0.4803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,475 - Iter: 15, Total Loss: 0.4619, loss_single: 0.4619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,511 - Iter: 16, Total Loss: 0.4471, loss_single: 0.4471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,546 - Iter: 17, Total Loss: 0.4362, loss_single: 0.4362, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,581 - Iter: 18, Total Loss: 0.4230, loss_single: 0.4230, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,617 - Iter: 19, Total Loss: 0.4086, loss_single: 0.4086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,652 - Iter: 20, Total Loss: 0.3981, loss_single: 0.3981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,687 - Iter: 21, Total Loss: 0.3887, loss_single: 0.3887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,723 - Iter: 22, Total Loss: 0.3786, loss_single: 0.3786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:08:09,759 - Iter: 23, Total Loss: 0.3689, loss_single: 0.3689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,795 - Iter: 24, Total Loss: 0.3599, loss_single: 0.3599, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,830 - Iter: 25, Total Loss: 0.3526, loss_single: 0.3526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,870 - Iter: 26, Total Loss: 0.3463, loss_single: 0.3463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 06:08:09,913 - Iter: 27, Total Loss: 0.3415, loss_single: 0.3415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.042 sec +2026-06-24 06:08:09,948 - Iter: 28, Total Loss: 0.3376, loss_single: 0.3376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:09,983 - 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Iter: 89, Total Loss: 0.3089, loss_single: 0.3089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,164 - Iter: 90, Total Loss: 0.3089, loss_single: 0.3089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,199 - Iter: 91, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,236 - Iter: 92, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:08:12,271 - Iter: 93, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,307 - Iter: 94, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,342 - Iter: 95, Total Loss: 0.3087, loss_single: 0.3087, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,377 - Iter: 96, Total Loss: 0.3087, loss_single: 0.3087, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,412 - Iter: 97, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,447 - Iter: 98, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,482 - Iter: 99, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,517 - Iter: 100, Total Loss: 0.3085, loss_single: 0.3085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:12,627 - Saving summary figures for iter 100 +2026-06-24 06:08:16,237 - ### Finished 100 iterations, averaged iter_t = 0.039334 with std = 0.040 ### +2026-06-24 06:08:16,237 - +2026-06-24 06:08:16,237 - ### The PtyRADSolver is finished in 9.314 sec ### +2026-06-24 06:08:16,237 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..afffe26099a736876149264d4b5d543ee095ff29 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/simulation_data4__sample_000006.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/simulation_data4__sample_000006.yaml new file mode 100644 index 0000000000000000000000000000000000000000..029b841b731051c0569a8796f9659fad47447e03 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006/c30_small__simulation_data4__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_-41.4_phi12_93.3_C21_981_phi21_77.5_C23_132_phi23_111_C30_-1.7e+04_C32_2.33e+06_phi56_221/simulation_data4__sample_000006.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 17.585540771484375 + probe_aberrations: + C10: -237.60096740722656 + C12: -41.40922927856445 + C21: 980.9886474609375 + C23: 131.9999237060547 + C30: -17005.091796875 + C32: 2283.0625 + C34: -5925.740234375 + C41: 435723.9375 + C43: 162406.15625 + C45: 370306.71875 + C50: 440309888.0 + C52: -7033548.5 + C54: -753318.4375 + C56: -1329729.75 + phi12: 93.29496772236236 + phi21: 77.5229476079682 + phi23: 111.07066481091478 + phi32: 20.35259427370941 + phi34: 71.66135439434413 + phi41: 309.39114962681293 + phi43: 345.8743045501125 + phi45: 193.36081125198507 + phi52: 81.35338599640305 + phi54: 106.24026623742255 + phi56: 221.46537312043006 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5161117911338806 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000006_measurement.h5 + key: measurement + random_seed: 20261982 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000006 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000006 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4/20260624_060851_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4/20260624_060851_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c14695ade1d2b8fe1468bc660bfb6382866e108c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4/20260624_060851_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:08:50,424 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:08:50,424 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:08:50,424 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:08:50,424 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:08:50,424 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:08:50,425 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:08:50,425 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:08:50,425 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:08:50,425 - +2026-06-24 06:08:50,530 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:08:50,531 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:08:50,531 - Accelerator.num_process = 1 +2026-06-24 06:08:50,531 - Accelerator.mixed_precision = no +2026-06-24 06:08:50,541 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:08:50,541 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:08:50,541 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:08:50,541 - +2026-06-24 06:08:50,541 - ### System information ### +2026-06-24 06:08:50,541 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:08:50,541 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:08:50,541 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:08:50,541 - Machine: x86_64 +2026-06-24 06:08:50,541 - Processor: x86_64 +2026-06-24 06:08:50,541 - Available CPU cores: 8 +2026-06-24 06:08:50,541 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:08:50,541 - +2026-06-24 06:08:50,541 - ### GPU information ### +2026-06-24 06:08:50,541 - CUDA Available: True +2026-06-24 06:08:50,541 - CUDA Version: 13.0 +2026-06-24 06:08:50,542 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:08:50,542 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:08:50,542 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:08:50,542 - In addition, Triton does not directly support Windows. +2026-06-24 06:08:50,542 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:08:50,557 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:08:50,557 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:08:50,557 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:08:50,557 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:08:50,557 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:08:50,557 - +2026-06-24 06:08:50,557 - ### Python information ### +2026-06-24 06:08:50,559 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:08:50,559 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:08:50,559 - +2026-06-24 06:08:50,559 - ### Packages information ### +2026-06-24 06:08:50,561 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:08:50,562 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:08:50,563 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:08:50,563 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:08:50,564 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:08:50,564 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:08:50,564 - +2026-06-24 06:08:50,564 - ### Loading params file ### +2026-06-24 06:08:50,564 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000009.yaml +2026-06-24 06:08:50,571 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:08:50,572 - Success! Params file validated and defaults applied. +2026-06-24 06:08:50,572 - +2026-06-24 06:08:50,572 - ### Setting GPU Device ### +2026-06-24 06:08:50,572 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:08:50,572 - +2026-06-24 06:08:50,572 - Random seed: 20261985 provided by params file +2026-06-24 06:08:50,572 - ### Initializing Initializer ### +2026-06-24 06:08:50,573 - init_params are displayed below: +2026-06-24 06:08:50,573 - random_seed: 20261985 +2026-06-24 06:08:50,573 - probe_illum_type: electron +2026-06-24 06:08:50,573 - probe_kv: 100.0 +2026-06-24 06:08:50,573 - probe_conv_angle: 14.095917701721191 +2026-06-24 06:08:50,573 - probe_aberrations: {'C10': -448.29, 'C12': 2.957, 'phi12': 278.285, 'C21': -670.96, 'phi21': 188.777, 'C23': 788.786, 'phi23': 265.65, 'C30': 4805550.0, 'C32': 7478.16, 'phi32': 317.331, 'C34': 2905.055, 'phi34': 309.207, 'C41': 188178.75, 'phi41': 195.053, 'C43': 390002.188, 'phi43': 200.843, 'C45': -87393.359, 'phi45': 102.902, 'C50': 498016608.0, 'C52': -16733446.0, 'phi52': 241.793, 'C54': -6771817.5, 'phi54': 201.772, 'C56': 13407280.0, 'phi56': 97.39} +2026-06-24 06:08:50,573 - beam_kev: None +2026-06-24 06:08:50,573 - probe_dRn: None +2026-06-24 06:08:50,573 - probe_Rn: None +2026-06-24 06:08:50,573 - probe_D_H: None +2026-06-24 06:08:50,573 - probe_D_FZP: None +2026-06-24 06:08:50,573 - probe_Ls: None +2026-06-24 06:08:50,573 - meas_Npix: 128 +2026-06-24 06:08:50,573 - pos_N_scans: 256 +2026-06-24 06:08:50,573 - pos_N_scan_slow: 16 +2026-06-24 06:08:50,573 - pos_N_scan_fast: 16 +2026-06-24 06:08:50,573 - pos_scan_step_size: 0.4856165945529938 +2026-06-24 06:08:50,573 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:08:50,573 - probe_pmode_max: 6 +2026-06-24 06:08:50,573 - probe_pmode_init_pows: [0.02] +2026-06-24 06:08:50,573 - obj_omode_max: 1 +2026-06-24 06:08:50,573 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:08:50,573 - obj_Nlayer: 1 +2026-06-24 06:08:50,573 - obj_slice_thickness: 20.0 +2026-06-24 06:08:50,573 - simu_Npix: None +2026-06-24 06:08:50,573 - simu_match_mode: None +2026-06-24 06:08:50,573 - meas_permute: None +2026-06-24 06:08:50,573 - meas_reshape: [256, 128, 128] +2026-06-24 06:08:50,573 - meas_flipT: [0, 0, 0] +2026-06-24 06:08:50,573 - meas_crop: None +2026-06-24 06:08:50,573 - meas_pad: None +2026-06-24 06:08:50,573 - meas_resample: None +2026-06-24 06:08:50,573 - meas_add_source_size: None +2026-06-24 06:08:50,573 - meas_add_detector_blur: None +2026-06-24 06:08:50,573 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:08:50,573 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:08:50,573 - meas_add_poisson_noise: None +2026-06-24 06:08:50,573 - meas_export: None +2026-06-24 06:08:50,574 - probe_permute: None +2026-06-24 06:08:50,574 - probe_z_shift: None +2026-06-24 06:08:50,574 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:08:50,574 - pos_scan_flipT: None +2026-06-24 06:08:50,574 - pos_scan_affine: None +2026-06-24 06:08:50,574 - pos_scan_rand_std: 0.15 +2026-06-24 06:08:50,574 - obj_z_crop: None +2026-06-24 06:08:50,574 - obj_z_pad: None +2026-06-24 06:08:50,574 - obj_z_resample: None +2026-06-24 06:08:50,574 - meas_source: file +2026-06-24 06:08:50,574 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000009_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:08:50,574 - probe_source: simu +2026-06-24 06:08:50,574 - probe_params: None +2026-06-24 06:08:50,574 - pos_source: simu +2026-06-24 06:08:50,574 - pos_params: None +2026-06-24 06:08:50,574 - obj_source: simu +2026-06-24 06:08:50,574 - obj_params: None +2026-06-24 06:08:50,574 - tilt_source: simu +2026-06-24 06:08:50,574 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:08:50,574 - +2026-06-24 06:08:50,574 - ### Initializing cache ### +2026-06-24 06:08:50,574 - use_cached_obj = False +2026-06-24 06:08:50,574 - use_cached_probe = False +2026-06-24 06:08:50,574 - use_cached_pos = False +2026-06-24 06:08:50,574 - +2026-06-24 06:08:50,574 - ### Initializing measurements ### +2026-06-24 06:08:50,574 - Loading measurements from source = 'file' +2026-06-24 06:08:50,574 - Detected measurement file type = '.h5' +2026-06-24 06:08:50,655 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:08:50,655 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:08:50,656 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0051) +2026-06-24 06:08:50,656 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:08:50,656 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:08:50,658 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:08:50,658 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:08:50,659 - Normalizing by max of the 2D mean pattern intensity: 0.0030341453 +2026-06-24 06:08:50,660 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:08:50,661 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0200, 1.6688) +2026-06-24 06:08:50,661 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:08:50,663 - Pattern total int. statistics (min, mean, max) = (323.3408, 327.6560, 331.3812), with min/max = 97.6% +2026-06-24 06:08:50,664 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0200, 1.6688) +2026-06-24 06:08:50,664 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:08:50,664 - +2026-06-24 06:08:50,664 - ### Setting up calibration ### +2026-06-24 06:08:50,664 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:08:50,664 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:08:50,664 - Radius of fitted bright field disk (RBF) = 9.57 px with meas_Npix = 128 +2026-06-24 06:08:50,664 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1496 +2026-06-24 06:08:50,664 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:08:50,664 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:08:50,888 - Initial guess: center=(63.63, 63.70), radius=9.57, Gaussian blur std=0.50 +2026-06-24 06:08:50,903 - Final fit: center=(63.63, 63.70), radius=9.57, Gaussian blur std=0.76 +2026-06-24 06:08:50,903 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.75 px with Npix = 128 +2026-06-24 06:08:50,903 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:08:50,903 - +2026-06-24 06:08:50,903 - ### Setting init_variables dict ### +2026-06-24 06:08:50,903 - Derived values given input init_params: +2026-06-24 06:08:50,903 - kv = 100.0 kV +2026-06-24 06:08:50,903 - wavelength = 0.0370 Ang +2026-06-24 06:08:50,903 - conv_angle = 14.095917701721191 mrad +2026-06-24 06:08:50,903 - Npix = 128 px +2026-06-24 06:08:50,903 - dk = 0.0391 Ang^-1 +2026-06-24 06:08:50,903 - kMax = 2.5000 Ang^-1 +2026-06-24 06:08:50,903 - da = 1.4459 mrad +2026-06-24 06:08:50,903 - angleMax = 92.5359 mrad +2026-06-24 06:08:50,903 - RBF = 9.7491 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:08:50,904 - n_alpha = 6.5647 (# conv_angle) +2026-06-24 06:08:50,904 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:08:50,904 - Rayleigh-limited resolution = 1.6018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:08:50,904 - Real space probe extent = 25.6000 Ang +2026-06-24 06:08:50,904 - +2026-06-24 06:08:50,904 - ### Initializing probe ### +2026-06-24 06:08:50,904 - Loading probe from source = 'simu' +2026-06-24 06:08:50,904 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:08:50,904 - Start simulating STEM probe +2026-06-24 06:08:50,904 - kv = 100.0 kV +2026-06-24 06:08:50,904 - wavelength = 0.0370 Ang +2026-06-24 06:08:50,904 - conv_angle = 14.095917701721191 mrad +2026-06-24 06:08:50,904 - Npix = 128 px +2026-06-24 06:08:50,904 - dk = 0.0391 Ang^-1 +2026-06-24 06:08:50,904 - kMax = 2.5000 Ang^-1 +2026-06-24 06:08:50,904 - alpha_max = 92.5359 mrad +2026-06-24 06:08:50,904 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:08:50,904 - Rayleigh-limited resolution = 1.6018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:08:50,904 - Real space probe extent = 25.6000 Ang +2026-06-24 06:08:50,904 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:08:50,904 - ------------------------------------------------------------------------------------ +2026-06-24 06:08:50,904 - C1,0 C1 -448.2900 - Defocus (C10 = -df) +2026-06-24 06:08:50,904 - C1,2 A1 2.9570 278.29 2-fold astigmatism +2026-06-24 06:08:50,904 - C2,1 3*B2 -670.9600 188.78 Axial coma +2026-06-24 06:08:50,904 - C2,3 A2 788.7860 265.65 3-fold astigmatism +2026-06-24 06:08:50,905 - C3,0 C3 4805550.0000 - Spherical aberration +2026-06-24 06:08:50,905 - C3,2 4*S3 7478.1600 317.33 Axial star aberration +2026-06-24 06:08:50,905 - C3,4 A3 2905.0550 309.21 4-fold astigmatism +2026-06-24 06:08:50,905 - C4,1 4*B4 188178.7500 195.05 Axial coma(4th) +2026-06-24 06:08:50,905 - C4,3 4*D4 390002.1880 200.84 3-lobe aberration +2026-06-24 06:08:50,905 - C4,5 A4 -87393.3590 102.90 5-fold astigmatism +2026-06-24 06:08:50,905 - C5,0 C5 498016608.0000 - Spherical aberration (5th) +2026-06-24 06:08:50,905 - C5,2 6*S5 -16733446.0000 241.79 Axial star aberration(5th) +2026-06-24 06:08:50,905 - C5,4 6*R5 -6771817.5000 201.77 4-lobe aberration +2026-06-24 06:08:50,905 - C5,6 A5 13407280.0000 97.39 6-fold astigmatism +2026-06-24 06:08:50,908 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:08:50,908 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:08:50,908 - Creating 5 new probe modes from the major mode +2026-06-24 06:08:50,908 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:08:51,011 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:08:51,012 - Orthogonalizing 6 pmodes +2026-06-24 06:08:51,014 - Sorting 6 pmodes by their intensities +2026-06-24 06:08:51,015 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:08:51,015 - sum(|probe_data|**2) = 327.66, while meas_total_ints (min, mean, max) = (323.3408, 327.6560, 331.3812) +2026-06-24 06:08:51,016 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:08:51,016 - +2026-06-24 06:08:51,016 - ### Initializing probe positions ### +2026-06-24 06:08:51,016 - Loading probe positions from source = 'simu' +2026-06-24 06:08:51,016 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:08:51,016 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4856, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:08:51,016 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:08:51,018 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:08:51,018 - crop_pos 1st and last px coords (y,x) = ([17, 17], [53, 53]) +2026-06-24 06:08:51,018 - crop_pos extent (Ang) = [7.4 7.6] +2026-06-24 06:08:51,018 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:08:51,018 - +2026-06-24 06:08:51,018 - ### Initializing object ### +2026-06-24 06:08:51,018 - Loading object from source = 'simu' +2026-06-24 06:08:51,018 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:08:51,020 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:08:51,020 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 198, 199) +2026-06-24 06:08:51,020 - object extent (Z, Y, X) (Ang) = [20. 39.6 39.8] +2026-06-24 06:08:51,020 - +2026-06-24 06:08:51,020 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:08:51,020 - omode_occu (omode) = float32, (1,) +2026-06-24 06:08:51,020 - +2026-06-24 06:08:51,020 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:08:51,020 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:08:51,021 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:08:51,021 - +2026-06-24 06:08:51,021 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:08:51,021 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:08:51,021 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:08:51,021 - +2026-06-24 06:08:51,021 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:08:51,021 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:08:51,021 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:08:51,021 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:08:51,021 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:08:51,021 - crop positions (yx_min=[16 16], yx_max=[181 182]) are well contained inside object canvas (Ny,Nx) = (198, 199). +2026-06-24 06:08:51,021 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:08:51,021 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:08:51,022 - +2026-06-24 06:08:51,022 - ### Collecting reconstruction provenance ### +2026-06-24 06:08:51,022 - Reconstruction provenance is collected and initialized. +2026-06-24 06:08:51,022 - +2026-06-24 06:08:51,022 - ### Initializing loss function ### +2026-06-24 06:08:51,022 - Active loss types: +2026-06-24 06:08:51,022 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:08:51,022 - +2026-06-24 06:08:51,022 - ### Initializing constraint function ### +2026-06-24 06:08:51,022 - Active constraint types: +2026-06-24 06:08:51,022 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:08:51,022 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:08:51,022 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:08:51,022 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:08:51,022 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:08:51,022 - +2026-06-24 06:08:51,022 - ### Done initializing PtyRADSolver ### +2026-06-24 06:08:51,022 - +2026-06-24 06:08:51,146 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:08:51,146 - +2026-06-24 06:08:51,146 - ### Initializing PtychoModel model ### +2026-06-24 06:08:51,219 - ### PtychoModel optimizable variables ### +2026-06-24 06:08:51,220 - obja : torch.Size([1, 1, 198, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:51,220 - objp : torch.Size([1, 1, 198, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:51,220 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:08:51,220 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:08:51,220 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:08:51,220 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:08:51,220 - +2026-06-24 06:08:51,220 - ### Optimizable variables statitsics ### +2026-06-24 06:08:51,220 - Total measurement values : 4,194,304 +2026-06-24 06:08:51,220 - Total optimizing variables: 275,924 +2026-06-24 06:08:51,220 - Overdetermined ratio : 15.20 +2026-06-24 06:08:51,220 - +2026-06-24 06:08:51,220 - ### Model behavior ### +2026-06-24 06:08:51,220 - Tilt propagator : False +2026-06-24 06:08:51,220 - Change slice thickness : False +2026-06-24 06:08:51,220 - Detector blur : False +2026-06-24 06:08:51,220 - Preload data : True +2026-06-24 06:08:51,220 - On-the-fly meas padding : False +2026-06-24 06:08:51,220 - On-the-fly meas resample : False +2026-06-24 06:08:51,220 - On-the-fly simu match mode: None +2026-06-24 06:08:51,220 - +2026-06-24 06:08:51,262 - ### Done initializing PtychoModel model ### +2026-06-24 06:08:51,262 - +2026-06-24 06:08:51,262 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:08:51,262 - +2026-06-24 06:08:51,262 - ### Generating indices, batches, and output_path ### +2026-06-24 06:08:51,263 - d90 = 51.000 px or 10.200 Ang +2026-06-24 06:08:51,263 - Selecting indices with the 'full' mode +2026-06-24 06:08:51,725 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:08:51,802 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:08:51,802 - Original recon_dir_affixes = ['default'] +2026-06-24 06:08:51,802 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:08:51,809 - Path corrected for compatibility: +2026-06-24 06:08:51,809 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317_C34_2.91e+03_phi34_309_C41_1.88e+05_phi41_195_C43_3.9e+05_phi43_201_C45_-8.74e+04_phi45_103_C50_4.98e+08_C52_-1.67e+07_phi52_242_C54_-6.77e+06_phi54_202_C56_1.34e+07_phi56_97.4 +2026-06-24 06:08:51,809 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4 +2026-06-24 06:08:51,810 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4' is generated! +2026-06-24 06:08:51,965 - +2026-06-24 06:08:51,967 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009/c30_small__simulation_data4__sample_000009_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-448_C12_2.96_phi12_278_C21_-671_phi21_189_C23_789_phi23_266_C30_4.81e+06_C32_7.48e+03_phi32_317.4/20260624_060851_ptyrad_log.txt ### +2026-06-24 06:08:51,967 - +2026-06-24 06:08:51,968 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:08:51,968 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:08:51,968 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:08:53,172 - Iter: 1, Total Loss: 1.1076, loss_single: 1.1076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.444 sec +2026-06-24 06:08:53,210 - Iter: 2, Total Loss: 1.0730, loss_single: 1.0730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:08:53,245 - Iter: 3, Total Loss: 1.0473, loss_single: 1.0473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,281 - Iter: 4, Total Loss: 1.0234, loss_single: 1.0234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:08:53,316 - Iter: 5, Total Loss: 0.9958, loss_single: 0.9958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:53,351 - Iter: 6, Total Loss: 0.9639, loss_single: 0.9639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,386 - Iter: 7, Total Loss: 0.9404, loss_single: 0.9404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,422 - Iter: 8, Total Loss: 0.9241, loss_single: 0.9241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,459 - Iter: 9, Total Loss: 0.9030, loss_single: 0.9030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:08:53,494 - Iter: 10, Total Loss: 0.8797, loss_single: 0.8797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,529 - Iter: 11, Total Loss: 0.8555, loss_single: 0.8555, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:53,564 - Iter: 12, Total Loss: 0.8301, loss_single: 0.8301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,599 - Iter: 13, Total Loss: 0.8094, loss_single: 0.8094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,634 - Iter: 14, Total Loss: 0.7891, loss_single: 0.7891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:53,669 - Iter: 15, Total Loss: 0.7644, loss_single: 0.7644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,705 - Iter: 16, Total Loss: 0.7397, loss_single: 0.7397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,740 - Iter: 17, Total Loss: 0.7190, loss_single: 0.7190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,775 - Iter: 18, Total Loss: 0.7000, loss_single: 0.7000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,810 - Iter: 19, Total Loss: 0.6798, loss_single: 0.6798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,846 - Iter: 20, Total Loss: 0.6618, loss_single: 0.6618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,881 - Iter: 21, Total Loss: 0.6442, loss_single: 0.6442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,916 - Iter: 22, Total Loss: 0.6268, loss_single: 0.6268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,951 - Iter: 23, Total Loss: 0.6101, loss_single: 0.6101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:53,986 - Iter: 24, Total Loss: 0.5940, loss_single: 0.5940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,022 - Iter: 25, Total Loss: 0.5806, loss_single: 0.5806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,057 - Iter: 26, Total Loss: 0.5666, loss_single: 0.5666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,092 - Iter: 27, Total Loss: 0.5528, loss_single: 0.5528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,127 - Iter: 28, Total Loss: 0.5387, loss_single: 0.5387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,163 - Iter: 29, Total Loss: 0.5240, loss_single: 0.5240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,198 - Iter: 30, Total Loss: 0.5114, loss_single: 0.5114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,233 - Iter: 31, Total Loss: 0.4986, loss_single: 0.4986, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,267 - Iter: 32, Total Loss: 0.4882, loss_single: 0.4882, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,302 - Iter: 33, Total Loss: 0.4801, loss_single: 0.4801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,337 - Iter: 34, Total Loss: 0.4719, loss_single: 0.4719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,372 - Iter: 35, Total Loss: 0.4641, loss_single: 0.4641, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,407 - Iter: 36, Total Loss: 0.4573, loss_single: 0.4573, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,442 - Iter: 37, Total Loss: 0.4520, loss_single: 0.4520, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,477 - Iter: 38, Total Loss: 0.4471, loss_single: 0.4471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,512 - Iter: 39, Total Loss: 0.4431, loss_single: 0.4431, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,547 - Iter: 40, Total Loss: 0.4394, loss_single: 0.4394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,585 - Iter: 41, Total Loss: 0.4358, loss_single: 0.4358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,620 - Iter: 42, Total Loss: 0.4324, loss_single: 0.4324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,655 - Iter: 43, Total Loss: 0.4294, loss_single: 0.4294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,691 - Iter: 44, Total Loss: 0.4271, loss_single: 0.4271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,725 - Iter: 45, Total Loss: 0.4254, loss_single: 0.4254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,760 - Iter: 46, Total Loss: 0.4237, loss_single: 0.4237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:54,796 - Iter: 47, Total Loss: 0.4217, loss_single: 0.4217, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,831 - Iter: 48, Total Loss: 0.4200, loss_single: 0.4200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,866 - Iter: 49, Total Loss: 0.4186, loss_single: 0.4186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,901 - Iter: 50, Total Loss: 0.4173, loss_single: 0.4173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,937 - Iter: 51, Total Loss: 0.4161, loss_single: 0.4161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:54,972 - Iter: 52, Total Loss: 0.4150, loss_single: 0.4150, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,007 - Iter: 53, Total Loss: 0.4140, loss_single: 0.4140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,042 - Iter: 54, Total Loss: 0.4132, loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,077 - Iter: 55, Total Loss: 0.4125, loss_single: 0.4125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,112 - Iter: 56, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,148 - Iter: 57, Total Loss: 0.4111, loss_single: 0.4111, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,183 - Iter: 58, Total Loss: 0.4105, loss_single: 0.4105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,217 - Iter: 59, Total Loss: 0.4100, loss_single: 0.4100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,253 - Iter: 60, Total Loss: 0.4094, loss_single: 0.4094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,288 - Iter: 61, Total Loss: 0.4089, loss_single: 0.4089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,323 - Iter: 62, Total Loss: 0.4083, loss_single: 0.4083, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,358 - Iter: 63, Total Loss: 0.4078, loss_single: 0.4078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,393 - Iter: 64, 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in 0.035 sec +2026-06-24 06:08:55,604 - Iter: 70, Total Loss: 0.4044, loss_single: 0.4044, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,639 - Iter: 71, Total Loss: 0.4039, loss_single: 0.4039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,673 - Iter: 72, Total Loss: 0.4035, loss_single: 0.4035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,708 - Iter: 73, Total Loss: 0.4030, loss_single: 0.4030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,743 - Iter: 74, Total Loss: 0.4025, loss_single: 0.4025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,779 - Iter: 75, Total Loss: 0.4021, loss_single: 0.4021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,814 - Iter: 76, Total Loss: 0.4016, loss_single: 0.4016, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:55,849 - Iter: 77, Total Loss: 0.4011, loss_single: 0.4011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,884 - Iter: 78, Total Loss: 0.4007, loss_single: 0.4007, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,919 - Iter: 79, Total Loss: 0.4002, loss_single: 0.4002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,954 - Iter: 80, Total Loss: 0.3997, loss_single: 0.3997, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:55,989 - Iter: 81, Total Loss: 0.3992, loss_single: 0.3992, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,024 - Iter: 82, Total Loss: 0.3987, loss_single: 0.3987, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:56,059 - Iter: 83, Total Loss: 0.3983, loss_single: 0.3983, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,094 - Iter: 84, Total Loss: 0.3979, loss_single: 0.3979, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:56,129 - Iter: 85, Total Loss: 0.3974, loss_single: 0.3974, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,165 - Iter: 86, Total Loss: 0.3969, loss_single: 0.3969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,199 - Iter: 87, Total Loss: 0.3965, loss_single: 0.3965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:56,234 - Iter: 88, Total Loss: 0.3960, loss_single: 0.3960, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,270 - Iter: 89, Total Loss: 0.3956, loss_single: 0.3956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,305 - Iter: 90, Total Loss: 0.3952, loss_single: 0.3952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,340 - Iter: 91, Total Loss: 0.3948, loss_single: 0.3948, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:56,377 - Iter: 92, Total Loss: 0.3943, loss_single: 0.3943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:08:56,412 - Iter: 93, Total Loss: 0.3939, loss_single: 0.3939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,447 - Iter: 94, Total Loss: 0.3934, loss_single: 0.3934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,482 - Iter: 95, Total Loss: 0.3929, loss_single: 0.3929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,517 - Iter: 96, Total Loss: 0.3924, loss_single: 0.3924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,553 - Iter: 97, Total Loss: 0.3919, loss_single: 0.3919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,587 - Iter: 98, Total Loss: 0.3915, loss_single: 0.3915, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:08:56,622 - Iter: 99, Total Loss: 0.3910, loss_single: 0.3910, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,657 - Iter: 100, Total Loss: 0.3906, loss_single: 0.3906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:08:56,768 - Saving summary figures for iter 100 +2026-06-24 06:09:00,421 - ### Finished 100 iterations, averaged iter_t = 0.038857 with std = 0.041 ### +2026-06-24 06:09:00,421 - +2026-06-24 06:09:00,421 - ### The PtyRADSolver is finished in 9.275 sec ### +2026-06-24 06:09:00,422 - diff --git 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+ probe_aberrations: + C10: -448.2904052734375 + C12: 2.956887722015381 + C21: -670.9601440429688 + C23: 788.786376953125 + C30: 4805550.0 + C32: 7478.15966796875 + C34: 2905.055419921875 + C41: 188178.75 + C43: 390002.1875 + C45: -87393.359375 + C50: 498016608.0 + C52: -16733446.0 + C54: -6771817.5 + C56: 13407280.0 + phi12: 278.2852660332809 + phi21: 188.77660684712595 + phi23: 265.65045425751117 + phi32: 317.33053419727906 + phi34: 309.20654327392583 + phi41: 195.05264910939724 + phi43: 200.84335178962576 + phi45: 102.90183369566039 + phi52: 241.7930679395202 + phi54: 201.771997969559 + phi56: 97.38951586562327 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4856165945529938 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000009_measurement.h5 + key: measurement + random_seed: 20261985 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000009 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000009 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git 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sha256:2e5857de76a7903d32ea39cac60f1e221904de3b11874565099c729449856217 +size 48184 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/20260624_061119_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/20260624_061119_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ad2b153a4ae0be351599e8f179d8eac3488e72ab --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/20260624_061119_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:11:18,169 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:11:18,169 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:11:18,170 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:11:18,170 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:11:18,170 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:11:18,170 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:11:18,170 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:11:18,170 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:11:18,170 - +2026-06-24 06:11:18,278 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:11:18,278 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:11:18,278 - Accelerator.num_process = 1 +2026-06-24 06:11:18,278 - Accelerator.mixed_precision = no +2026-06-24 06:11:18,289 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:11:18,289 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:11:18,289 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:11:18,289 - +2026-06-24 06:11:18,289 - ### System information ### +2026-06-24 06:11:18,289 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:11:18,289 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:11:18,289 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:11:18,289 - Machine: x86_64 +2026-06-24 06:11:18,289 - Processor: x86_64 +2026-06-24 06:11:18,289 - Available CPU cores: 8 +2026-06-24 06:11:18,289 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:11:18,289 - +2026-06-24 06:11:18,289 - ### GPU information ### +2026-06-24 06:11:18,289 - CUDA Available: True +2026-06-24 06:11:18,289 - CUDA Version: 13.0 +2026-06-24 06:11:18,290 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:11:18,290 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:11:18,290 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:11:18,290 - In addition, Triton does not directly support Windows. +2026-06-24 06:11:18,290 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:11:18,305 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:11:18,305 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:11:18,305 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:11:18,305 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:11:18,305 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:11:18,305 - +2026-06-24 06:11:18,305 - ### Python information ### +2026-06-24 06:11:18,306 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:11:18,306 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:11:18,306 - +2026-06-24 06:11:18,306 - ### Packages information ### +2026-06-24 06:11:18,307 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:11:18,308 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:11:18,308 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:11:18,309 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:11:18,309 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:11:18,309 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:11:18,309 - +2026-06-24 06:11:18,310 - ### Loading params file ### +2026-06-24 06:11:18,310 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000019.yaml +2026-06-24 06:11:18,316 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:11:18,317 - Success! Params file validated and defaults applied. +2026-06-24 06:11:18,317 - +2026-06-24 06:11:18,317 - ### Setting GPU Device ### +2026-06-24 06:11:18,317 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:11:18,318 - +2026-06-24 06:11:18,318 - Random seed: 20261995 provided by params file +2026-06-24 06:11:18,318 - ### Initializing Initializer ### +2026-06-24 06:11:18,318 - init_params are displayed below: +2026-06-24 06:11:18,318 - random_seed: 20261995 +2026-06-24 06:11:18,318 - probe_illum_type: electron +2026-06-24 06:11:18,318 - probe_kv: 80.0 +2026-06-24 06:11:18,318 - probe_conv_angle: 9.277036666870117 +2026-06-24 06:11:18,318 - probe_aberrations: {'C10': -22.048, 'C12': 27.645, 'phi12': 96.642, 'C21': -714.01, 'phi21': 349.445, 'C23': -858.327, 'phi23': 296.136, 'C30': 365686.5, 'C32': 1928.388, 'phi32': 294.646, 'C34': -2381.438, 'phi34': 202.038, 'C41': 209309.0, 'phi41': 207.94, 'C43': 321878.5, 'phi43': 34.786, 'C45': -437818.5, 'phi45': 23.477, 'C50': -75271808.0, 'C52': 12476817.0, 'phi52': 265.504, 'C54': -11271489.0, 'phi54': 164.954, 'C56': 15499739.0, 'phi56': 28.032} +2026-06-24 06:11:18,318 - beam_kev: None +2026-06-24 06:11:18,318 - probe_dRn: None +2026-06-24 06:11:18,318 - probe_Rn: None +2026-06-24 06:11:18,318 - probe_D_H: None +2026-06-24 06:11:18,318 - probe_D_FZP: None +2026-06-24 06:11:18,318 - probe_Ls: None +2026-06-24 06:11:18,318 - meas_Npix: 128 +2026-06-24 06:11:18,318 - pos_N_scans: 256 +2026-06-24 06:11:18,318 - pos_N_scan_slow: 16 +2026-06-24 06:11:18,318 - pos_N_scan_fast: 16 +2026-06-24 06:11:18,319 - pos_scan_step_size: 0.4213043749332428 +2026-06-24 06:11:18,319 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:11:18,319 - probe_pmode_max: 6 +2026-06-24 06:11:18,319 - probe_pmode_init_pows: [0.02] +2026-06-24 06:11:18,319 - obj_omode_max: 1 +2026-06-24 06:11:18,319 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:11:18,319 - obj_Nlayer: 1 +2026-06-24 06:11:18,319 - obj_slice_thickness: 20.0 +2026-06-24 06:11:18,319 - simu_Npix: None +2026-06-24 06:11:18,319 - simu_match_mode: None +2026-06-24 06:11:18,319 - meas_permute: None +2026-06-24 06:11:18,319 - meas_reshape: [256, 128, 128] +2026-06-24 06:11:18,319 - meas_flipT: [0, 0, 0] +2026-06-24 06:11:18,319 - meas_crop: None +2026-06-24 06:11:18,319 - meas_pad: None +2026-06-24 06:11:18,319 - meas_resample: None +2026-06-24 06:11:18,319 - meas_add_source_size: None +2026-06-24 06:11:18,319 - meas_add_detector_blur: None +2026-06-24 06:11:18,319 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:11:18,319 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:11:18,319 - meas_add_poisson_noise: None +2026-06-24 06:11:18,319 - meas_export: None +2026-06-24 06:11:18,319 - probe_permute: None +2026-06-24 06:11:18,319 - probe_z_shift: None +2026-06-24 06:11:18,319 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:11:18,319 - pos_scan_flipT: None +2026-06-24 06:11:18,319 - pos_scan_affine: None +2026-06-24 06:11:18,319 - pos_scan_rand_std: 0.15 +2026-06-24 06:11:18,319 - obj_z_crop: None +2026-06-24 06:11:18,319 - obj_z_pad: None +2026-06-24 06:11:18,319 - obj_z_resample: None +2026-06-24 06:11:18,319 - meas_source: file +2026-06-24 06:11:18,319 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000019_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:11:18,319 - probe_source: simu +2026-06-24 06:11:18,319 - probe_params: None +2026-06-24 06:11:18,319 - pos_source: simu +2026-06-24 06:11:18,319 - pos_params: None +2026-06-24 06:11:18,319 - obj_source: simu +2026-06-24 06:11:18,319 - obj_params: None +2026-06-24 06:11:18,320 - tilt_source: simu +2026-06-24 06:11:18,320 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:11:18,320 - +2026-06-24 06:11:18,320 - ### Initializing cache ### +2026-06-24 06:11:18,320 - use_cached_obj = False +2026-06-24 06:11:18,320 - use_cached_probe = False +2026-06-24 06:11:18,320 - use_cached_pos = False +2026-06-24 06:11:18,320 - +2026-06-24 06:11:18,320 - ### Initializing measurements ### +2026-06-24 06:11:18,320 - Loading measurements from source = 'file' +2026-06-24 06:11:18,320 - Detected measurement file type = '.h5' +2026-06-24 06:11:18,398 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:11:18,398 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:11:18,400 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0097) +2026-06-24 06:11:18,400 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:11:18,400 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:11:18,401 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:11:18,401 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:11:18,402 - Normalizing by max of the 2D mean pattern intensity: 0.0086743291 +2026-06-24 06:11:18,402 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:11:18,403 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0070, 1.1168) +2026-06-24 06:11:18,404 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:11:18,405 - Pattern total int. statistics (min, mean, max) = (113.1285, 114.4087, 115.9823), with min/max = 97.5% +2026-06-24 06:11:18,406 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0070, 1.1168) +2026-06-24 06:11:18,406 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:11:18,406 - +2026-06-24 06:11:18,407 - ### Setting up calibration ### +2026-06-24 06:11:18,407 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:11:18,407 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:11:18,407 - Radius of fitted bright field disk (RBF) = 5.53 px with meas_Npix = 128 +2026-06-24 06:11:18,407 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0864 +2026-06-24 06:11:18,407 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:11:18,407 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:11:18,629 - Initial guess: center=(63.63, 63.62), radius=5.53, Gaussian blur std=0.50 +2026-06-24 06:11:18,642 - Final fit: center=(63.63, 63.62), radius=5.53, Gaussian blur std=0.70 +2026-06-24 06:11:18,642 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 5.69 px with Npix = 128 +2026-06-24 06:11:18,642 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:11:18,642 - +2026-06-24 06:11:18,642 - ### Setting init_variables dict ### +2026-06-24 06:11:18,642 - Derived values given input init_params: +2026-06-24 06:11:18,642 - kv = 80.0 kV +2026-06-24 06:11:18,642 - wavelength = 0.0418 Ang +2026-06-24 06:11:18,642 - conv_angle = 9.277036666870117 mrad +2026-06-24 06:11:18,642 - Npix = 128 px +2026-06-24 06:11:18,642 - dk = 0.0391 Ang^-1 +2026-06-24 06:11:18,642 - kMax = 2.5000 Ang^-1 +2026-06-24 06:11:18,642 - da = 1.6311 mrad +2026-06-24 06:11:18,642 - angleMax = 104.3929 mrad +2026-06-24 06:11:18,642 - RBF = 5.6875 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:11:18,643 - n_alpha = 11.2528 (# conv_angle) +2026-06-24 06:11:18,643 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:11:18,643 - Rayleigh-limited resolution = 2.7457 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:11:18,643 - Real space probe extent = 25.6000 Ang +2026-06-24 06:11:18,643 - +2026-06-24 06:11:18,643 - ### Initializing probe ### +2026-06-24 06:11:18,643 - Loading probe from source = 'simu' +2026-06-24 06:11:18,643 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:11:18,643 - Start simulating STEM probe +2026-06-24 06:11:18,643 - kv = 80.0 kV +2026-06-24 06:11:18,643 - wavelength = 0.0418 Ang +2026-06-24 06:11:18,643 - conv_angle = 9.277036666870117 mrad +2026-06-24 06:11:18,643 - Npix = 128 px +2026-06-24 06:11:18,643 - dk = 0.0391 Ang^-1 +2026-06-24 06:11:18,643 - kMax = 2.5000 Ang^-1 +2026-06-24 06:11:18,643 - alpha_max = 104.3929 mrad +2026-06-24 06:11:18,643 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:11:18,643 - Rayleigh-limited resolution = 2.7457 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:11:18,643 - Real space probe extent = 25.6000 Ang +2026-06-24 06:11:18,643 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:11:18,643 - ------------------------------------------------------------------------------------ +2026-06-24 06:11:18,643 - C1,0 C1 -22.0480 - Defocus (C10 = -df) +2026-06-24 06:11:18,643 - C1,2 A1 27.6450 96.64 2-fold astigmatism +2026-06-24 06:11:18,643 - C2,1 3*B2 -714.0100 349.44 Axial coma +2026-06-24 06:11:18,644 - C2,3 A2 -858.3270 296.14 3-fold astigmatism +2026-06-24 06:11:18,644 - C3,0 C3 365686.5000 - Spherical aberration +2026-06-24 06:11:18,644 - C3,2 4*S3 1928.3880 294.65 Axial star aberration +2026-06-24 06:11:18,644 - C3,4 A3 -2381.4380 202.04 4-fold astigmatism +2026-06-24 06:11:18,644 - C4,1 4*B4 209309.0000 207.94 Axial coma(4th) +2026-06-24 06:11:18,644 - C4,3 4*D4 321878.5000 34.79 3-lobe aberration +2026-06-24 06:11:18,644 - C4,5 A4 -437818.5000 23.48 5-fold astigmatism +2026-06-24 06:11:18,644 - C5,0 C5 -75271808.0000 - Spherical aberration (5th) +2026-06-24 06:11:18,644 - C5,2 6*S5 12476817.0000 265.50 Axial star aberration(5th) +2026-06-24 06:11:18,644 - C5,4 6*R5 -11271489.0000 164.95 4-lobe aberration +2026-06-24 06:11:18,644 - C5,6 A5 15499739.0000 28.03 6-fold astigmatism +2026-06-24 06:11:18,647 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:11:18,647 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:11:18,647 - Creating 5 new probe modes from the major mode +2026-06-24 06:11:18,647 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:11:18,862 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:11:18,863 - Orthogonalizing 6 pmodes +2026-06-24 06:11:18,865 - Sorting 6 pmodes by their intensities +2026-06-24 06:11:18,865 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:11:18,866 - sum(|probe_data|**2) = 114.41, while meas_total_ints (min, mean, max) = (113.1285, 114.4087, 115.9823) +2026-06-24 06:11:18,866 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:11:18,866 - +2026-06-24 06:11:18,866 - ### Initializing probe positions ### +2026-06-24 06:11:18,866 - Loading probe positions from source = 'simu' +2026-06-24 06:11:18,866 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:11:18,866 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4213, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:11:18,867 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:11:18,869 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:11:18,869 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 06:11:18,869 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:11:18,869 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:11:18,869 - +2026-06-24 06:11:18,869 - ### Initializing object ### +2026-06-24 06:11:18,869 - Loading object from source = 'simu' +2026-06-24 06:11:18,869 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:11:18,870 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:11:18,870 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 192, 193) +2026-06-24 06:11:18,871 - object extent (Z, Y, X) (Ang) = [20. 38.4 38.6] +2026-06-24 06:11:18,871 - +2026-06-24 06:11:18,871 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:11:18,871 - omode_occu (omode) = float32, (1,) +2026-06-24 06:11:18,871 - +2026-06-24 06:11:18,871 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:11:18,871 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:11:18,871 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:11:18,871 - +2026-06-24 06:11:18,872 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:11:18,872 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:11:18,872 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:11:18,872 - +2026-06-24 06:11:18,872 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:11:18,872 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:11:18,872 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:11:18,872 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:11:18,872 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:11:18,872 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (192, 193). +2026-06-24 06:11:18,872 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:11:18,872 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:11:18,872 - +2026-06-24 06:11:18,872 - ### Collecting reconstruction provenance ### +2026-06-24 06:11:18,872 - Reconstruction provenance is collected and initialized. +2026-06-24 06:11:18,872 - +2026-06-24 06:11:18,872 - ### Initializing loss function ### +2026-06-24 06:11:18,872 - Active loss types: +2026-06-24 06:11:18,872 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:11:18,872 - +2026-06-24 06:11:18,873 - ### Initializing constraint function ### +2026-06-24 06:11:18,873 - Active constraint types: +2026-06-24 06:11:18,873 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:11:18,873 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:11:18,873 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:11:18,873 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:11:18,873 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:11:18,873 - +2026-06-24 06:11:18,873 - ### Done initializing PtyRADSolver ### +2026-06-24 06:11:18,873 - +2026-06-24 06:11:19,000 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:11:19,000 - +2026-06-24 06:11:19,000 - ### Initializing PtychoModel model ### +2026-06-24 06:11:19,072 - ### PtychoModel optimizable variables ### +2026-06-24 06:11:19,072 - obja : torch.Size([1, 1, 192, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:19,072 - objp : torch.Size([1, 1, 192, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:19,072 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:11:19,072 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:11:19,072 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:11:19,072 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:19,072 - +2026-06-24 06:11:19,072 - ### Optimizable variables statitsics ### +2026-06-24 06:11:19,072 - Total measurement values : 4,194,304 +2026-06-24 06:11:19,072 - Total optimizing variables: 271,232 +2026-06-24 06:11:19,072 - Overdetermined ratio : 15.46 +2026-06-24 06:11:19,072 - +2026-06-24 06:11:19,072 - ### Model behavior ### +2026-06-24 06:11:19,073 - Tilt propagator : False +2026-06-24 06:11:19,073 - Change slice thickness : False +2026-06-24 06:11:19,073 - Detector blur : False +2026-06-24 06:11:19,073 - Preload data : True +2026-06-24 06:11:19,073 - On-the-fly meas padding : False +2026-06-24 06:11:19,073 - On-the-fly meas resample : False +2026-06-24 06:11:19,073 - On-the-fly simu match mode: None +2026-06-24 06:11:19,073 - +2026-06-24 06:11:19,114 - ### Done initializing PtychoModel model ### +2026-06-24 06:11:19,114 - +2026-06-24 06:11:19,114 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:11:19,114 - +2026-06-24 06:11:19,114 - ### Generating indices, batches, and output_path ### +2026-06-24 06:11:19,116 - d90 = 41.000 px or 8.200 Ang +2026-06-24 06:11:19,116 - Selecting indices with the 'full' mode +2026-06-24 06:11:19,582 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:11:19,655 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:11:19,655 - Original recon_dir_affixes = ['default'] +2026-06-24 06:11:19,655 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:11:19,662 - Path corrected for compatibility: +2026-06-24 06:11:19,662 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.93e+03_phi32_295_C34_-2.38e+03_phi34_202_C41_2.09e+05_phi41_208_C43_3.22e+05_phi43_34.8_C45_-4.38e+05_phi45_23.5_C50_-7.53e+07_C52_1.25e+07_phi52_266_C54_-1.13e+07_phi54_165_C56_1.55e+07_phi56_28 +2026-06-24 06:11:19,662 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28 +2026-06-24 06:11:19,663 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28' is generated! +2026-06-24 06:11:19,810 - +2026-06-24 06:11:19,811 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/20260624_061119_ptyrad_log.txt ### +2026-06-24 06:11:19,812 - +2026-06-24 06:11:19,813 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:11:19,813 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:11:19,813 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:11:21,009 - Iter: 1, Total Loss: 1.2962, loss_single: 1.2962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:11:21,047 - Iter: 2, Total Loss: 1.2245, loss_single: 1.2245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:11:21,083 - Iter: 3, Total Loss: 1.1673, loss_single: 1.1673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,118 - Iter: 4, Total Loss: 1.1113, loss_single: 1.1113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,154 - Iter: 5, Total Loss: 1.0645, loss_single: 1.0645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:11:21,190 - Iter: 6, Total Loss: 1.0229, loss_single: 1.0229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,225 - Iter: 7, Total Loss: 0.9844, loss_single: 0.9844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,261 - Iter: 8, Total Loss: 0.9499, loss_single: 0.9499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,296 - Iter: 9, Total Loss: 0.9107, loss_single: 0.9107, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,331 - Iter: 10, Total Loss: 0.8658, loss_single: 0.8658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,367 - Iter: 11, Total Loss: 0.8186, loss_single: 0.8186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,402 - Iter: 12, Total Loss: 0.7716, loss_single: 0.7716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,438 - Iter: 13, Total Loss: 0.7219, loss_single: 0.7219, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,473 - Iter: 14, Total Loss: 0.6777, loss_single: 0.6777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,508 - Iter: 15, Total Loss: 0.6422, loss_single: 0.6422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,543 - Iter: 16, Total Loss: 0.6123, loss_single: 0.6123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,579 - Iter: 17, Total Loss: 0.5823, loss_single: 0.5823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,614 - Iter: 18, Total Loss: 0.5507, loss_single: 0.5507, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,649 - Iter: 19, Total Loss: 0.5236, loss_single: 0.5236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,685 - Iter: 20, Total Loss: 0.5010, loss_single: 0.5010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:11:21,720 - Iter: 21, Total Loss: 0.4779, loss_single: 0.4779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,755 - Iter: 22, Total Loss: 0.4617, loss_single: 0.4617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,791 - Iter: 23, Total Loss: 0.4505, loss_single: 0.4505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,826 - Iter: 24, Total Loss: 0.4367, loss_single: 0.4367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,864 - Iter: 25, Total Loss: 0.4255, loss_single: 0.4255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:11:21,900 - Iter: 26, Total Loss: 0.4188, loss_single: 0.4188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,935 - Iter: 27, Total Loss: 0.4130, loss_single: 0.4130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:21,970 - Iter: 28, Total Loss: 0.4080, loss_single: 0.4080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:22,006 - Iter: 29, Total Loss: 0.4042, loss_single: 0.4042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/simulation_data4__sample_000019.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/simulation_data4__sample_000019.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7a067745971c2589d10a44020830e5bf778503ef --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/simulation_data4__sample_000019.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 9.277036666870117 + probe_aberrations: + C10: -22.048381805419922 + C12: 27.64488410949707 + C21: -714.0100708007812 + C23: -858.3267822265625 + C30: 365686.5 + C32: 1928.3876953125 + C34: -2381.4384765625 + C41: 209309.0 + C43: 321878.5 + C45: -437818.5 + C50: -75271808.0 + C52: 12476817.0 + C54: -11271489.0 + C56: 15499739.0 + phi12: 96.64232732136972 + phi21: 349.445400655762 + phi23: 296.1362932781894 + phi32: 294.6458367182659 + phi34: 202.0384299887029 + phi41: 207.93969977121554 + phi43: 34.786354933455456 + phi45: 23.477299951058107 + phi52: 265.50352322808584 + phi54: 164.95416377692877 + phi56: 28.032033797195915 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4213043749332428 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000019_measurement.h5 + key: measurement + random_seed: 20261995 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000019 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eb84d1e2dd9aba30784a627cf506aad2d12cdf6eed50447889cec55467c3c6ac +size 1100203 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..e35c1b5168df197d4572a490c36831779a41fe98 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000019/c30_small__simulation_data4__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-22_C12_27.6_phi12_96.6_C21_-714_phi21_349_C23_-858_phi23_296_C30_3.66e+05_C32_1.9.55e+07_phi56_28/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:19f226f72fb7865857cbf67109ad6838446bbe07b1e0ac9c4eb9f0e57f545cf8 +size 48701 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/20260624_061149_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/20260624_061149_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9368d48a8d4654a7d599608e5963e279fae39cfa --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/20260624_061149_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:11:48,329 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:11:48,329 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:11:48,329 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:11:48,329 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:11:48,329 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:11:48,329 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:11:48,329 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:11:48,329 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:11:48,329 - +2026-06-24 06:11:48,435 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:11:48,435 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:11:48,435 - Accelerator.num_process = 1 +2026-06-24 06:11:48,435 - Accelerator.mixed_precision = no +2026-06-24 06:11:48,446 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:11:48,446 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:11:48,446 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:11:48,446 - +2026-06-24 06:11:48,446 - ### System information ### +2026-06-24 06:11:48,446 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:11:48,446 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:11:48,446 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:11:48,446 - Machine: x86_64 +2026-06-24 06:11:48,446 - Processor: x86_64 +2026-06-24 06:11:48,446 - Available CPU cores: 8 +2026-06-24 06:11:48,446 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:11:48,446 - +2026-06-24 06:11:48,446 - ### GPU information ### +2026-06-24 06:11:48,446 - CUDA Available: True +2026-06-24 06:11:48,446 - CUDA Version: 13.0 +2026-06-24 06:11:48,447 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:11:48,447 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:11:48,447 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:11:48,447 - In addition, Triton does not directly support Windows. +2026-06-24 06:11:48,447 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:11:48,461 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:11:48,462 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:11:48,462 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:11:48,462 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:11:48,462 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:11:48,462 - +2026-06-24 06:11:48,462 - ### Python information ### +2026-06-24 06:11:48,463 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:11:48,464 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:11:48,464 - +2026-06-24 06:11:48,464 - ### Packages information ### +2026-06-24 06:11:48,464 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:11:48,465 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:11:48,466 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:11:48,466 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:11:48,467 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:11:48,467 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:11:48,467 - +2026-06-24 06:11:48,467 - ### Loading params file ### +2026-06-24 06:11:48,467 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000021.yaml +2026-06-24 06:11:48,474 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:11:48,475 - Success! Params file validated and defaults applied. +2026-06-24 06:11:48,475 - +2026-06-24 06:11:48,475 - ### Setting GPU Device ### +2026-06-24 06:11:48,475 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:11:48,475 - +2026-06-24 06:11:48,475 - Random seed: 20261997 provided by params file +2026-06-24 06:11:48,475 - ### Initializing Initializer ### +2026-06-24 06:11:48,475 - init_params are displayed below: +2026-06-24 06:11:48,475 - random_seed: 20261997 +2026-06-24 06:11:48,475 - probe_illum_type: electron +2026-06-24 06:11:48,475 - probe_kv: 200.0 +2026-06-24 06:11:48,476 - probe_conv_angle: 20.734708786010742 +2026-06-24 06:11:48,476 - probe_aberrations: {'C10': 93.012, 'C12': 4.669, 'phi12': 75.127, 'C21': 174.889, 'phi21': 221.674, 'C23': -579.018, 'phi23': 343.281, 'C30': -829411.938, 'C32': 7512.883, 'phi32': 145.785, 'C34': 5044.625, 'phi34': 24.28, 'C41': -76757.227, 'phi41': 50.331, 'C43': 325149.875, 'phi43': 327.654, 'C45': -118067.773, 'phi45': 300.031, 'C50': -480933440.0, 'C52': -7526734.0, 'phi52': 135.578, 'C54': 4404934.0, 'phi54': 301.994, 'C56': 13315362.0, 'phi56': 357.389} +2026-06-24 06:11:48,476 - beam_kev: None +2026-06-24 06:11:48,476 - probe_dRn: None +2026-06-24 06:11:48,476 - probe_Rn: None +2026-06-24 06:11:48,476 - probe_D_H: None +2026-06-24 06:11:48,476 - probe_D_FZP: None +2026-06-24 06:11:48,476 - probe_Ls: None +2026-06-24 06:11:48,476 - meas_Npix: 128 +2026-06-24 06:11:48,476 - pos_N_scans: 256 +2026-06-24 06:11:48,476 - pos_N_scan_slow: 16 +2026-06-24 06:11:48,476 - pos_N_scan_fast: 16 +2026-06-24 06:11:48,476 - pos_scan_step_size: 0.4116571545600891 +2026-06-24 06:11:48,476 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:11:48,476 - probe_pmode_max: 6 +2026-06-24 06:11:48,476 - probe_pmode_init_pows: [0.02] +2026-06-24 06:11:48,476 - obj_omode_max: 1 +2026-06-24 06:11:48,476 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:11:48,476 - obj_Nlayer: 1 +2026-06-24 06:11:48,476 - obj_slice_thickness: 20.0 +2026-06-24 06:11:48,476 - simu_Npix: None +2026-06-24 06:11:48,476 - simu_match_mode: None +2026-06-24 06:11:48,476 - meas_permute: None +2026-06-24 06:11:48,476 - meas_reshape: [256, 128, 128] +2026-06-24 06:11:48,476 - meas_flipT: [0, 0, 0] +2026-06-24 06:11:48,476 - meas_crop: None +2026-06-24 06:11:48,476 - meas_pad: None +2026-06-24 06:11:48,476 - meas_resample: None +2026-06-24 06:11:48,476 - meas_add_source_size: None +2026-06-24 06:11:48,476 - meas_add_detector_blur: None +2026-06-24 06:11:48,476 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:11:48,476 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:11:48,476 - meas_add_poisson_noise: None +2026-06-24 06:11:48,476 - meas_export: None +2026-06-24 06:11:48,476 - probe_permute: None +2026-06-24 06:11:48,476 - probe_z_shift: None +2026-06-24 06:11:48,476 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:11:48,476 - pos_scan_flipT: None +2026-06-24 06:11:48,476 - pos_scan_affine: None +2026-06-24 06:11:48,477 - pos_scan_rand_std: 0.15 +2026-06-24 06:11:48,477 - obj_z_crop: None +2026-06-24 06:11:48,477 - obj_z_pad: None +2026-06-24 06:11:48,477 - obj_z_resample: None +2026-06-24 06:11:48,477 - meas_source: file +2026-06-24 06:11:48,477 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000021_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:11:48,477 - probe_source: simu +2026-06-24 06:11:48,477 - probe_params: None +2026-06-24 06:11:48,477 - pos_source: simu +2026-06-24 06:11:48,477 - pos_params: None +2026-06-24 06:11:48,477 - obj_source: simu +2026-06-24 06:11:48,477 - obj_params: None +2026-06-24 06:11:48,477 - tilt_source: simu +2026-06-24 06:11:48,477 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:11:48,477 - +2026-06-24 06:11:48,477 - ### Initializing cache ### +2026-06-24 06:11:48,477 - use_cached_obj = False +2026-06-24 06:11:48,477 - use_cached_probe = False +2026-06-24 06:11:48,477 - use_cached_pos = False +2026-06-24 06:11:48,477 - +2026-06-24 06:11:48,477 - ### Initializing measurements ### +2026-06-24 06:11:48,477 - Loading measurements from source = 'file' +2026-06-24 06:11:48,477 - Detected measurement file type = '.h5' +2026-06-24 06:11:48,556 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:11:48,556 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:11:48,557 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0020) +2026-06-24 06:11:48,557 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:11:48,557 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:11:48,559 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:11:48,559 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:11:48,559 - Normalizing by max of the 2D mean pattern intensity: 0.0006983027 +2026-06-24 06:11:48,560 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:11:48,561 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0876, 2.8746) +2026-06-24 06:11:48,562 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:11:48,563 - Pattern total int. statistics (min, mean, max) = (1401.8081, 1434.7170, 1464.5562), with min/max = 95.7% +2026-06-24 06:11:48,564 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0876, 2.8746) +2026-06-24 06:11:48,564 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:11:48,565 - +2026-06-24 06:11:48,565 - ### Setting up calibration ### +2026-06-24 06:11:48,565 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:11:48,565 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:11:48,565 - Radius of fitted bright field disk (RBF) = 20.98 px with meas_Npix = 128 +2026-06-24 06:11:48,565 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3278 +2026-06-24 06:11:48,565 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:11:48,565 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:11:48,793 - Initial guess: center=(63.58, 63.61), radius=20.98, Gaussian blur std=0.50 +2026-06-24 06:11:48,809 - Final fit: center=(63.58, 63.61), radius=20.98, Gaussian blur std=0.80 +2026-06-24 06:11:48,809 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 21.17 px with Npix = 128 +2026-06-24 06:11:48,809 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:11:48,810 - +2026-06-24 06:11:48,810 - ### Setting init_variables dict ### +2026-06-24 06:11:48,810 - Derived values given input init_params: +2026-06-24 06:11:48,810 - kv = 200.0 kV +2026-06-24 06:11:48,810 - wavelength = 0.0251 Ang +2026-06-24 06:11:48,810 - conv_angle = 20.734708786010742 mrad +2026-06-24 06:11:48,810 - Npix = 128 px +2026-06-24 06:11:48,810 - dk = 0.0391 Ang^-1 +2026-06-24 06:11:48,810 - kMax = 2.5000 Ang^-1 +2026-06-24 06:11:48,810 - da = 0.9797 mrad +2026-06-24 06:11:48,810 - angleMax = 62.6984 mrad +2026-06-24 06:11:48,810 - RBF = 21.1652 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:11:48,810 - n_alpha = 3.0238 (# conv_angle) +2026-06-24 06:11:48,810 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:11:48,810 - Rayleigh-limited resolution = 0.7378 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:11:48,810 - Real space probe extent = 25.6000 Ang +2026-06-24 06:11:48,810 - +2026-06-24 06:11:48,810 - ### Initializing probe ### +2026-06-24 06:11:48,810 - Loading probe from source = 'simu' +2026-06-24 06:11:48,810 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:11:48,810 - Start simulating STEM probe +2026-06-24 06:11:48,810 - kv = 200.0 kV +2026-06-24 06:11:48,810 - wavelength = 0.0251 Ang +2026-06-24 06:11:48,810 - conv_angle = 20.734708786010742 mrad +2026-06-24 06:11:48,811 - Npix = 128 px +2026-06-24 06:11:48,811 - dk = 0.0391 Ang^-1 +2026-06-24 06:11:48,811 - kMax = 2.5000 Ang^-1 +2026-06-24 06:11:48,811 - alpha_max = 62.6984 mrad +2026-06-24 06:11:48,811 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:11:48,811 - Rayleigh-limited resolution = 0.7378 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:11:48,811 - Real space probe extent = 25.6000 Ang +2026-06-24 06:11:48,811 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:11:48,811 - ------------------------------------------------------------------------------------- +2026-06-24 06:11:48,811 - C1,0 C1 93.0120 - Defocus (C10 = -df) +2026-06-24 06:11:48,811 - C1,2 A1 4.6690 75.13 2-fold astigmatism +2026-06-24 06:11:48,811 - C2,1 3*B2 174.8890 221.67 Axial coma +2026-06-24 06:11:48,811 - C2,3 A2 -579.0180 343.28 3-fold astigmatism +2026-06-24 06:11:48,811 - C3,0 C3 -829411.9380 - Spherical aberration +2026-06-24 06:11:48,811 - C3,2 4*S3 7512.8830 145.78 Axial star aberration +2026-06-24 06:11:48,811 - C3,4 A3 5044.6250 24.28 4-fold astigmatism +2026-06-24 06:11:48,811 - C4,1 4*B4 -76757.2270 50.33 Axial coma(4th) +2026-06-24 06:11:48,811 - C4,3 4*D4 325149.8750 327.65 3-lobe aberration +2026-06-24 06:11:48,811 - C4,5 A4 -118067.7730 300.03 5-fold astigmatism +2026-06-24 06:11:48,811 - C5,0 C5 -480933440.0000 - Spherical aberration (5th) +2026-06-24 06:11:48,811 - C5,2 6*S5 -7526734.0000 135.58 Axial star aberration(5th) +2026-06-24 06:11:48,811 - C5,4 6*R5 4404934.0000 301.99 4-lobe aberration +2026-06-24 06:11:48,811 - C5,6 A5 13315362.0000 357.39 6-fold astigmatism +2026-06-24 06:11:48,814 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:11:48,814 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:11:48,814 - Creating 5 new probe modes from the major mode +2026-06-24 06:11:48,814 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:11:49,055 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:11:49,056 - Orthogonalizing 6 pmodes +2026-06-24 06:11:49,058 - Sorting 6 pmodes by their intensities +2026-06-24 06:11:49,058 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:11:49,059 - sum(|probe_data|**2) = 1434.72, while meas_total_ints (min, mean, max) = (1401.8081, 1434.7170, 1464.5562) +2026-06-24 06:11:49,059 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:11:49,059 - +2026-06-24 06:11:49,059 - ### Initializing probe positions ### +2026-06-24 06:11:49,059 - Loading probe positions from source = 'simu' +2026-06-24 06:11:49,059 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:11:49,059 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4117, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:11:49,059 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:11:49,061 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:11:49,061 - crop_pos 1st and last px coords (y,x) = ([16, 15], [47, 47]) +2026-06-24 06:11:49,061 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:11:49,061 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:11:49,061 - +2026-06-24 06:11:49,061 - ### Initializing object ### +2026-06-24 06:11:49,062 - Loading object from source = 'simu' +2026-06-24 06:11:49,062 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:11:49,063 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:11:49,063 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 192, 192) +2026-06-24 06:11:49,063 - object extent (Z, Y, X) (Ang) = [20. 38.4 38.4] +2026-06-24 06:11:49,063 - +2026-06-24 06:11:49,063 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:11:49,063 - omode_occu (omode) = float32, (1,) +2026-06-24 06:11:49,063 - +2026-06-24 06:11:49,063 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:11:49,063 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:11:49,064 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:11:49,064 - +2026-06-24 06:11:49,064 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:11:49,064 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:11:49,064 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:11:49,064 - +2026-06-24 06:11:49,064 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:11:49,064 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:11:49,064 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:11:49,064 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:11:49,064 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:11:49,065 - crop positions (yx_min=[15 15], yx_max=[175 175]) are well contained inside object canvas (Ny,Nx) = (192, 192). +2026-06-24 06:11:49,065 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:11:49,065 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:11:49,065 - +2026-06-24 06:11:49,065 - ### Collecting reconstruction provenance ### +2026-06-24 06:11:49,065 - Reconstruction provenance is collected and initialized. +2026-06-24 06:11:49,065 - +2026-06-24 06:11:49,065 - ### Initializing loss function ### +2026-06-24 06:11:49,065 - Active loss types: +2026-06-24 06:11:49,065 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:11:49,065 - +2026-06-24 06:11:49,065 - ### Initializing constraint function ### +2026-06-24 06:11:49,065 - Active constraint types: +2026-06-24 06:11:49,065 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:11:49,065 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:11:49,065 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:11:49,065 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:11:49,065 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:11:49,065 - +2026-06-24 06:11:49,065 - ### Done initializing PtyRADSolver ### +2026-06-24 06:11:49,065 - +2026-06-24 06:11:49,190 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:11:49,191 - +2026-06-24 06:11:49,191 - ### Initializing PtychoModel model ### +2026-06-24 06:11:49,262 - ### PtychoModel optimizable variables ### +2026-06-24 06:11:49,263 - obja : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:49,263 - objp : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:49,263 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:11:49,263 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:11:49,263 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:11:49,263 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:11:49,263 - +2026-06-24 06:11:49,263 - ### Optimizable variables statitsics ### +2026-06-24 06:11:49,263 - Total measurement values : 4,194,304 +2026-06-24 06:11:49,263 - Total optimizing variables: 270,848 +2026-06-24 06:11:49,263 - Overdetermined ratio : 15.49 +2026-06-24 06:11:49,263 - +2026-06-24 06:11:49,263 - ### Model behavior ### +2026-06-24 06:11:49,263 - Tilt propagator : False +2026-06-24 06:11:49,263 - Change slice thickness : False +2026-06-24 06:11:49,263 - Detector blur : False +2026-06-24 06:11:49,263 - Preload data : True +2026-06-24 06:11:49,263 - On-the-fly meas padding : False +2026-06-24 06:11:49,263 - On-the-fly meas resample : False +2026-06-24 06:11:49,263 - On-the-fly simu match mode: None +2026-06-24 06:11:49,263 - +2026-06-24 06:11:49,304 - ### Done initializing PtychoModel model ### +2026-06-24 06:11:49,304 - +2026-06-24 06:11:49,304 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:11:49,304 - +2026-06-24 06:11:49,305 - ### Generating indices, batches, and output_path ### +2026-06-24 06:11:49,306 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:11:49,306 - Selecting indices with the 'full' mode +2026-06-24 06:11:49,764 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:11:49,836 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:11:49,836 - Original recon_dir_affixes = ['default'] +2026-06-24 06:11:49,836 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:11:49,841 - Path corrected for compatibility: +2026-06-24 06:11:49,841 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.51e+03_phi32_146_C34_5.04e+03_phi34_24.3_C41_-7.68e+04_phi41_50.3_C43_3.25e+05_phi43_328_C45_-1.18e+05_phi45_300_C50_-4.81e+08_C52_-7.53e+06_phi52_136_C54_4.4e+06_phi54_302_C56_1.33e+07_phi56_357 +2026-06-24 06:11:49,841 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357 +2026-06-24 06:11:49,842 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357' is generated! +2026-06-24 06:11:49,990 - +2026-06-24 06:11:49,991 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/20260624_061149_ptyrad_log.txt ### +2026-06-24 06:11:49,991 - +2026-06-24 06:11:49,992 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:11:49,992 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:11:49,992 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:11:51,180 - Iter: 1, Total Loss: 0.8294, loss_single: 0.8294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:11:51,217 - Iter: 2, Total Loss: 0.8177, loss_single: 0.8177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:11:51,252 - Iter: 3, Total Loss: 0.8075, loss_single: 0.8075, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,288 - Iter: 4, Total Loss: 0.7981, loss_single: 0.7981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,324 - Iter: 5, Total Loss: 0.7894, loss_single: 0.7894, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:11:51,360 - Iter: 6, Total Loss: 0.7807, loss_single: 0.7807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,394 - Iter: 7, Total Loss: 0.7724, loss_single: 0.7724, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:11:51,430 - Iter: 8, Total Loss: 0.7643, loss_single: 0.7643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,465 - Iter: 9, Total Loss: 0.7559, loss_single: 0.7559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,500 - Iter: 10, Total Loss: 0.7476, loss_single: 0.7476, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,535 - Iter: 11, Total Loss: 0.7394, loss_single: 0.7394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,571 - Iter: 12, Total Loss: 0.7321, loss_single: 0.7321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,606 - Iter: 13, Total Loss: 0.7254, loss_single: 0.7254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,641 - Iter: 14, Total Loss: 0.7193, loss_single: 0.7193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,676 - Iter: 15, Total Loss: 0.7130, loss_single: 0.7130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,711 - Iter: 16, Total Loss: 0.7064, loss_single: 0.7064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,746 - Iter: 17, Total Loss: 0.7000, loss_single: 0.7000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,781 - Iter: 18, Total Loss: 0.6937, loss_single: 0.6937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,816 - Iter: 19, Total Loss: 0.6878, loss_single: 0.6878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,852 - Iter: 20, Total Loss: 0.6819, loss_single: 0.6819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,887 - Iter: 21, Total Loss: 0.6758, loss_single: 0.6758, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,922 - Iter: 22, Total Loss: 0.6692, loss_single: 0.6692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,957 - Iter: 23, Total Loss: 0.6623, loss_single: 0.6623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:51,992 - Iter: 24, Total Loss: 0.6559, loss_single: 0.6559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,028 - Iter: 25, Total Loss: 0.6498, loss_single: 0.6498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,063 - Iter: 26, Total Loss: 0.6437, loss_single: 0.6437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,099 - Iter: 27, Total Loss: 0.6378, loss_single: 0.6378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,134 - Iter: 28, Total Loss: 0.6318, loss_single: 0.6318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,169 - Iter: 29, Total Loss: 0.6258, loss_single: 0.6258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,204 - Iter: 30, Total Loss: 0.6198, loss_single: 0.6198, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,239 - Iter: 31, Total Loss: 0.6140, loss_single: 0.6140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,274 - Iter: 32, Total Loss: 0.6084, loss_single: 0.6084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,310 - Iter: 33, Total Loss: 0.6031, loss_single: 0.6031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,345 - Iter: 34, Total Loss: 0.5988, loss_single: 0.5988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,380 - Iter: 35, Total Loss: 0.5954, loss_single: 0.5954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,416 - Iter: 36, Total Loss: 0.5922, loss_single: 0.5922, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,450 - Iter: 37, Total Loss: 0.5888, loss_single: 0.5888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:11:52,486 - Iter: 38, Total Loss: 0.5861, loss_single: 0.5861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,522 - Iter: 39, Total Loss: 0.5843, loss_single: 0.5843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,557 - Iter: 40, Total Loss: 0.5825, loss_single: 0.5825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,594 - Iter: 41, Total Loss: 0.5806, loss_single: 0.5806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,629 - Iter: 42, Total Loss: 0.5785, loss_single: 0.5785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,664 - Iter: 43, Total Loss: 0.5767, loss_single: 0.5767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,699 - Iter: 44, Total Loss: 0.5753, loss_single: 0.5753, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,734 - Iter: 45, Total Loss: 0.5736, loss_single: 0.5736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,771 - Iter: 46, Total Loss: 0.5722, loss_single: 0.5722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,806 - Iter: 47, Total Loss: 0.5708, loss_single: 0.5708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,841 - Iter: 48, Total Loss: 0.5692, loss_single: 0.5692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,876 - Iter: 49, Total Loss: 0.5674, loss_single: 0.5674, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:11:52,911 - Iter: 50, Total Loss: 0.5657, loss_single: 0.5657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,946 - Iter: 51, Total Loss: 0.5643, loss_single: 0.5643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:52,982 - Iter: 52, Total Loss: 0.5628, loss_single: 0.5628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,017 - Iter: 53, Total Loss: 0.5617, loss_single: 0.5617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,052 - Iter: 54, Total Loss: 0.5607, loss_single: 0.5607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,087 - Iter: 55, Total Loss: 0.5596, loss_single: 0.5596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,123 - Iter: 56, Total Loss: 0.5583, loss_single: 0.5583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,158 - Iter: 57, Total Loss: 0.5569, loss_single: 0.5569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:11:53,193 - Iter: 58, Total Loss: 0.5559, loss_single: 0.5559, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/simulation_data4__sample_000021.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/simulation_data4__sample_000021.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2efb6523de205867b5f8020aa44dd5a6dbf82651 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/simulation_data4__sample_000021.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 20.734708786010742 + probe_aberrations: + C10: 93.01203155517578 + C12: 4.6694207191467285 + C21: 174.8887939453125 + C23: -579.01806640625 + C30: -829411.9375 + C32: 7512.8828125 + C34: 5044.62451171875 + C41: -76757.2265625 + C43: 325149.875 + C45: -118067.7734375 + C50: -480933440.0 + C52: -7526734.0 + C54: 4404934.0 + C56: 13315362.0 + phi12: 75.1269718886411 + phi21: 221.67406272033062 + phi23: 343.28093636377207 + phi32: 145.78489636182948 + phi34: 24.27980790494688 + phi41: 50.33111074850119 + phi43: 327.65362746732296 + phi45: 300.0305666146072 + phi52: 135.57836710016102 + phi54: 301.99421868022915 + phi56: 357.38885601897346 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4116571545600891 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000021_measurement.h5 + key: measurement + random_seed: 20261997 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000021 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000021/c30_small__simulation_data4__sample_000021_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_93_C12_4.67_phi12_75.1_C21_175_phi21_222_C23_-579_phi23_343_C30_-8.29e+05_C32_7.5.33e+07_phi56_357/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32.79e+07_phi56_165/20260624_061234_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:12:32,792 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:12:32,792 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:12:32,793 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:12:32,793 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:12:32,793 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:12:32,793 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:12:32,793 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:12:32,793 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:12:32,793 - +2026-06-24 06:12:32,899 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:12:32,899 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:12:32,899 - Accelerator.num_process = 1 +2026-06-24 06:12:32,899 - Accelerator.mixed_precision = no +2026-06-24 06:12:32,910 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:12:32,910 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:12:32,910 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:12:32,910 - +2026-06-24 06:12:32,910 - ### System information ### +2026-06-24 06:12:32,910 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:12:32,910 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:12:32,910 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:12:32,910 - Machine: x86_64 +2026-06-24 06:12:32,910 - Processor: x86_64 +2026-06-24 06:12:32,911 - Available CPU cores: 8 +2026-06-24 06:12:32,911 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:12:32,911 - +2026-06-24 06:12:32,911 - ### GPU information ### +2026-06-24 06:12:32,911 - CUDA Available: True +2026-06-24 06:12:32,911 - CUDA Version: 13.0 +2026-06-24 06:12:32,911 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:12:32,911 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:12:32,911 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:12:32,911 - In addition, Triton does not directly support Windows. +2026-06-24 06:12:32,911 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:12:32,926 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:12:32,926 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:12:32,926 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:12:32,926 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:12:32,926 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:12:32,926 - +2026-06-24 06:12:32,926 - ### Python information ### +2026-06-24 06:12:32,928 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:12:32,928 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:12:32,928 - +2026-06-24 06:12:32,928 - ### Packages information ### +2026-06-24 06:12:32,929 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:12:32,930 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:12:32,930 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:12:32,931 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:12:32,931 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:12:32,931 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:12:32,931 - +2026-06-24 06:12:32,931 - ### Loading params file ### +2026-06-24 06:12:32,931 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000024.yaml +2026-06-24 06:12:32,938 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:12:32,939 - Success! Params file validated and defaults applied. +2026-06-24 06:12:32,939 - +2026-06-24 06:12:32,939 - ### Setting GPU Device ### +2026-06-24 06:12:32,939 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:12:32,939 - +2026-06-24 06:12:32,939 - Random seed: 20262000 provided by params file +2026-06-24 06:12:32,939 - ### Initializing Initializer ### +2026-06-24 06:12:32,940 - init_params are displayed below: +2026-06-24 06:12:32,940 - random_seed: 20262000 +2026-06-24 06:12:32,940 - probe_illum_type: electron +2026-06-24 06:12:32,940 - probe_kv: 200.0 +2026-06-24 06:12:32,940 - probe_conv_angle: 21.56110191345215 +2026-06-24 06:12:32,940 - probe_aberrations: {'C10': -3.752, 'C12': 27.582, 'phi12': 25.581, 'C21': -779.33, 'phi21': 359.093, 'C23': -670.597, 'phi23': 122.15, 'C30': -376188.531, 'C32': -2610.32, 'phi32': 219.478, 'C34': -38.214, 'phi34': 89.388, 'C41': 446954.469, 'phi41': 20.167, 'C43': -275919.875, 'phi43': 73.198, 'C45': 22994.676, 'phi45': 231.823, 'C50': 453757152.0, 'C52': 11530836.0, 'phi52': 175.147, 'C54': 12589776.0, 'phi54': 152.365, 'C56': 17896664.0, 'phi56': 165.445} +2026-06-24 06:12:32,940 - beam_kev: None +2026-06-24 06:12:32,940 - probe_dRn: None +2026-06-24 06:12:32,940 - probe_Rn: None +2026-06-24 06:12:32,940 - probe_D_H: None +2026-06-24 06:12:32,940 - probe_D_FZP: None +2026-06-24 06:12:32,940 - probe_Ls: None +2026-06-24 06:12:32,940 - meas_Npix: 128 +2026-06-24 06:12:32,940 - pos_N_scans: 256 +2026-06-24 06:12:32,940 - pos_N_scan_slow: 16 +2026-06-24 06:12:32,940 - pos_N_scan_fast: 16 +2026-06-24 06:12:32,940 - pos_scan_step_size: 0.3573286235332489 +2026-06-24 06:12:32,940 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:12:32,940 - probe_pmode_max: 6 +2026-06-24 06:12:32,940 - probe_pmode_init_pows: [0.02] +2026-06-24 06:12:32,940 - obj_omode_max: 1 +2026-06-24 06:12:32,940 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:12:32,940 - obj_Nlayer: 1 +2026-06-24 06:12:32,940 - obj_slice_thickness: 20.0 +2026-06-24 06:12:32,940 - simu_Npix: None +2026-06-24 06:12:32,940 - simu_match_mode: None +2026-06-24 06:12:32,940 - meas_permute: None +2026-06-24 06:12:32,940 - meas_reshape: [256, 128, 128] +2026-06-24 06:12:32,940 - meas_flipT: [0, 0, 0] +2026-06-24 06:12:32,940 - meas_crop: None +2026-06-24 06:12:32,940 - meas_pad: None +2026-06-24 06:12:32,940 - meas_resample: None +2026-06-24 06:12:32,940 - meas_add_source_size: None +2026-06-24 06:12:32,941 - meas_add_detector_blur: None +2026-06-24 06:12:32,941 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:12:32,941 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:12:32,941 - meas_add_poisson_noise: None +2026-06-24 06:12:32,941 - meas_export: None +2026-06-24 06:12:32,941 - probe_permute: None +2026-06-24 06:12:32,941 - probe_z_shift: None +2026-06-24 06:12:32,941 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:12:32,941 - pos_scan_flipT: None +2026-06-24 06:12:32,941 - pos_scan_affine: None +2026-06-24 06:12:32,941 - pos_scan_rand_std: 0.15 +2026-06-24 06:12:32,941 - obj_z_crop: None +2026-06-24 06:12:32,941 - obj_z_pad: None +2026-06-24 06:12:32,941 - obj_z_resample: None +2026-06-24 06:12:32,941 - meas_source: file +2026-06-24 06:12:32,941 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000024_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:12:32,941 - probe_source: simu +2026-06-24 06:12:32,941 - probe_params: None +2026-06-24 06:12:32,941 - pos_source: simu +2026-06-24 06:12:32,941 - pos_params: None +2026-06-24 06:12:32,941 - obj_source: simu +2026-06-24 06:12:32,941 - obj_params: None +2026-06-24 06:12:32,941 - tilt_source: simu +2026-06-24 06:12:32,941 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:12:32,941 - +2026-06-24 06:12:32,941 - ### Initializing cache ### +2026-06-24 06:12:32,941 - use_cached_obj = False +2026-06-24 06:12:32,941 - use_cached_probe = False +2026-06-24 06:12:32,941 - use_cached_pos = False +2026-06-24 06:12:32,941 - +2026-06-24 06:12:32,941 - ### Initializing measurements ### +2026-06-24 06:12:32,941 - Loading measurements from source = 'file' +2026-06-24 06:12:32,941 - Detected measurement file type = '.h5' +2026-06-24 06:12:33,019 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:12:33,019 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:12:33,020 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0011) +2026-06-24 06:12:33,020 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:12:33,020 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:12:33,022 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:12:33,022 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:12:33,022 - Normalizing by max of the 2D mean pattern intensity: 0.00067003269 +2026-06-24 06:12:33,023 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:12:33,024 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0910, 1.6846) +2026-06-24 06:12:33,025 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:12:33,026 - Pattern total int. statistics (min, mean, max) = (1474.9059, 1490.5503, 1500.2770), with min/max = 98.3% +2026-06-24 06:12:33,027 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0910, 1.6846) +2026-06-24 06:12:33,027 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:12:33,027 - +2026-06-24 06:12:33,027 - ### Setting up calibration ### +2026-06-24 06:12:33,027 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:12:33,027 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:12:33,027 - Radius of fitted bright field disk (RBF) = 21.86 px with meas_Npix = 128 +2026-06-24 06:12:33,028 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3415 +2026-06-24 06:12:33,028 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:12:33,028 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:12:33,251 - Initial guess: center=(63.61, 63.65), radius=21.86, Gaussian blur std=0.50 +2026-06-24 06:12:33,263 - Final fit: center=(63.61, 63.65), radius=21.86, Gaussian blur std=0.62 +2026-06-24 06:12:33,264 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 22.01 px with Npix = 128 +2026-06-24 06:12:33,264 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:12:33,264 - +2026-06-24 06:12:33,264 - ### Setting init_variables dict ### +2026-06-24 06:12:33,264 - Derived values given input init_params: +2026-06-24 06:12:33,264 - kv = 200.0 kV +2026-06-24 06:12:33,264 - wavelength = 0.0251 Ang +2026-06-24 06:12:33,264 - conv_angle = 21.56110191345215 mrad +2026-06-24 06:12:33,264 - Npix = 128 px +2026-06-24 06:12:33,264 - dk = 0.0391 Ang^-1 +2026-06-24 06:12:33,264 - kMax = 2.5000 Ang^-1 +2026-06-24 06:12:33,264 - da = 0.9797 mrad +2026-06-24 06:12:33,264 - angleMax = 62.6984 mrad +2026-06-24 06:12:33,264 - RBF = 22.0087 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:12:33,264 - n_alpha = 2.9079 (# conv_angle) +2026-06-24 06:12:33,264 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:12:33,264 - Rayleigh-limited resolution = 0.7095 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:12:33,264 - Real space probe extent = 25.6000 Ang +2026-06-24 06:12:33,264 - +2026-06-24 06:12:33,264 - ### Initializing probe ### +2026-06-24 06:12:33,264 - Loading probe from source = 'simu' +2026-06-24 06:12:33,264 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:12:33,264 - Start simulating STEM probe +2026-06-24 06:12:33,265 - kv = 200.0 kV +2026-06-24 06:12:33,265 - wavelength = 0.0251 Ang +2026-06-24 06:12:33,265 - conv_angle = 21.56110191345215 mrad +2026-06-24 06:12:33,265 - Npix = 128 px +2026-06-24 06:12:33,265 - dk = 0.0391 Ang^-1 +2026-06-24 06:12:33,265 - kMax = 2.5000 Ang^-1 +2026-06-24 06:12:33,265 - alpha_max = 62.6984 mrad +2026-06-24 06:12:33,265 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:12:33,265 - Rayleigh-limited resolution = 0.7095 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:12:33,265 - Real space probe extent = 25.6000 Ang +2026-06-24 06:12:33,265 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:12:33,265 - ------------------------------------------------------------------------------------ +2026-06-24 06:12:33,265 - C1,0 C1 -3.7520 - Defocus (C10 = -df) +2026-06-24 06:12:33,265 - C1,2 A1 27.5820 25.58 2-fold astigmatism +2026-06-24 06:12:33,265 - C2,1 3*B2 -779.3300 359.09 Axial coma +2026-06-24 06:12:33,265 - C2,3 A2 -670.5970 122.15 3-fold astigmatism +2026-06-24 06:12:33,265 - C3,0 C3 -376188.5310 - Spherical aberration +2026-06-24 06:12:33,265 - C3,2 4*S3 -2610.3200 219.48 Axial star aberration +2026-06-24 06:12:33,265 - C3,4 A3 -38.2140 89.39 4-fold astigmatism +2026-06-24 06:12:33,265 - C4,1 4*B4 446954.4690 20.17 Axial coma(4th) +2026-06-24 06:12:33,265 - C4,3 4*D4 -275919.8750 73.20 3-lobe aberration +2026-06-24 06:12:33,265 - C4,5 A4 22994.6760 231.82 5-fold astigmatism +2026-06-24 06:12:33,265 - C5,0 C5 453757152.0000 - Spherical aberration (5th) +2026-06-24 06:12:33,265 - C5,2 6*S5 11530836.0000 175.15 Axial star aberration(5th) +2026-06-24 06:12:33,265 - C5,4 6*R5 12589776.0000 152.37 4-lobe aberration +2026-06-24 06:12:33,265 - C5,6 A5 17896664.0000 165.44 6-fold astigmatism +2026-06-24 06:12:33,268 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:12:33,268 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:12:33,268 - Creating 5 new probe modes from the major mode +2026-06-24 06:12:33,268 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:12:33,487 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:12:33,488 - Orthogonalizing 6 pmodes +2026-06-24 06:12:33,491 - Sorting 6 pmodes by their intensities +2026-06-24 06:12:33,492 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:12:33,492 - sum(|probe_data|**2) = 1490.55, while meas_total_ints (min, mean, max) = (1474.9059, 1490.5503, 1500.2770) +2026-06-24 06:12:33,492 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:12:33,492 - +2026-06-24 06:12:33,492 - ### Initializing probe positions ### +2026-06-24 06:12:33,492 - Loading probe positions from source = 'simu' +2026-06-24 06:12:33,492 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:12:33,492 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3573, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:12:33,493 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:12:33,495 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:12:33,495 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 06:12:33,495 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:12:33,495 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:12:33,495 - +2026-06-24 06:12:33,495 - ### Initializing object ### +2026-06-24 06:12:33,495 - Loading object from source = 'simu' +2026-06-24 06:12:33,495 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:12:33,496 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:12:33,496 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 06:12:33,497 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 06:12:33,497 - +2026-06-24 06:12:33,497 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:12:33,497 - omode_occu (omode) = float32, (1,) +2026-06-24 06:12:33,497 - +2026-06-24 06:12:33,497 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:12:33,497 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:12:33,497 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:12:33,498 - +2026-06-24 06:12:33,498 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:12:33,498 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:12:33,498 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:12:33,498 - +2026-06-24 06:12:33,498 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:12:33,498 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:12:33,498 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:12:33,498 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:12:33,498 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:12:33,498 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 06:12:33,498 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:12:33,498 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:12:33,498 - +2026-06-24 06:12:33,498 - ### Collecting reconstruction provenance ### +2026-06-24 06:12:33,498 - Reconstruction provenance is collected and initialized. +2026-06-24 06:12:33,498 - +2026-06-24 06:12:33,498 - ### Initializing loss function ### +2026-06-24 06:12:33,498 - Active loss types: +2026-06-24 06:12:33,498 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:12:33,499 - +2026-06-24 06:12:33,499 - ### Initializing constraint function ### +2026-06-24 06:12:33,499 - Active constraint types: +2026-06-24 06:12:33,499 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:12:33,499 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:12:33,499 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:12:33,499 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:12:33,499 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:12:33,499 - +2026-06-24 06:12:33,499 - ### Done initializing PtyRADSolver ### +2026-06-24 06:12:33,499 - +2026-06-24 06:12:33,623 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:12:33,623 - +2026-06-24 06:12:33,623 - ### Initializing PtychoModel model ### +2026-06-24 06:12:33,694 - ### PtychoModel optimizable variables ### +2026-06-24 06:12:33,694 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:33,694 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:33,695 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:12:33,695 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:12:33,695 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:12:33,695 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:33,695 - +2026-06-24 06:12:33,695 - ### Optimizable variables statitsics ### +2026-06-24 06:12:33,695 - Total measurement values : 4,194,304 +2026-06-24 06:12:33,695 - Total optimizing variables: 267,058 +2026-06-24 06:12:33,695 - Overdetermined ratio : 15.71 +2026-06-24 06:12:33,695 - +2026-06-24 06:12:33,695 - ### Model behavior ### +2026-06-24 06:12:33,695 - Tilt propagator : False +2026-06-24 06:12:33,695 - Change slice thickness : False +2026-06-24 06:12:33,695 - Detector blur : False +2026-06-24 06:12:33,695 - Preload data : True +2026-06-24 06:12:33,695 - On-the-fly meas padding : False +2026-06-24 06:12:33,695 - On-the-fly meas resample : False +2026-06-24 06:12:33,695 - On-the-fly simu match mode: None +2026-06-24 06:12:33,695 - +2026-06-24 06:12:33,736 - ### Done initializing PtychoModel model ### +2026-06-24 06:12:33,736 - +2026-06-24 06:12:33,737 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:12:33,737 - +2026-06-24 06:12:33,737 - ### Generating indices, batches, and output_path ### +2026-06-24 06:12:33,738 - d90 = 25.000 px or 5.000 Ang +2026-06-24 06:12:33,738 - Selecting indices with the 'full' mode +2026-06-24 06:12:34,199 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:12:34,273 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:12:34,273 - Original recon_dir_affixes = ['default'] +2026-06-24 06:12:34,273 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:12:34,279 - Path corrected for compatibility: +2026-06-24 06:12:34,279 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32_-2.61e+03_phi32_219_C34_-38.2_phi34_89.4_C41_4.47e+05_phi41_20.2_C43_-2.76e+05_phi43_73.2_C45_2.3e+04_phi45_232_C50_4.54e+08_C52_1.15e+07_phi52_175_C54_1.26e+07_phi54_152_C56_1.79e+07_phi56_165 +2026-06-24 06:12:34,279 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32.79e+07_phi56_165 +2026-06-24 06:12:34,280 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32.79e+07_phi56_165' is generated! +2026-06-24 06:12:34,426 - +2026-06-24 06:12:34,428 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32.79e+07_phi56_165/20260624_061234_ptyrad_log.txt ### +2026-06-24 06:12:34,428 - +2026-06-24 06:12:34,429 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:12:34,429 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:12:34,429 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:12:35,654 - Iter: 1, Total Loss: 0.4874, loss_single: 0.4874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.441 sec +2026-06-24 06:12:35,691 - Iter: 2, Total Loss: 0.4745, loss_single: 0.4745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:12:35,727 - Iter: 3, Total Loss: 0.4644, loss_single: 0.4644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,763 - Iter: 4, Total Loss: 0.4543, loss_single: 0.4543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,798 - Iter: 5, Total Loss: 0.4448, loss_single: 0.4448, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,833 - Iter: 6, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,869 - Iter: 7, Total Loss: 0.4265, loss_single: 0.4265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,905 - Iter: 8, Total Loss: 0.4193, loss_single: 0.4193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,940 - Iter: 9, Total Loss: 0.4113, loss_single: 0.4113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:35,975 - Iter: 10, Total Loss: 0.4041, loss_single: 0.4041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,011 - Iter: 11, Total Loss: 0.3967, loss_single: 0.3967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,046 - Iter: 12, Total Loss: 0.3882, loss_single: 0.3882, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,081 - Iter: 13, Total Loss: 0.3801, loss_single: 0.3801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,117 - Iter: 14, Total Loss: 0.3748, loss_single: 0.3748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:36,153 - Iter: 15, Total Loss: 0.3704, loss_single: 0.3704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,188 - Iter: 16, Total Loss: 0.3658, loss_single: 0.3658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,223 - Iter: 17, Total Loss: 0.3617, loss_single: 0.3617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,259 - Iter: 18, Total Loss: 0.3567, loss_single: 0.3567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:36,295 - Iter: 19, Total Loss: 0.3519, loss_single: 0.3519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,330 - Iter: 20, Total Loss: 0.3477, loss_single: 0.3477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,365 - Iter: 21, Total Loss: 0.3429, loss_single: 0.3429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,401 - Iter: 22, Total Loss: 0.3385, loss_single: 0.3385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,436 - Iter: 23, Total Loss: 0.3352, loss_single: 0.3352, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,471 - Iter: 24, Total Loss: 0.3321, loss_single: 0.3321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,510 - Iter: 25, Total Loss: 0.3287, loss_single: 0.3287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:12:36,545 - Iter: 26, Total Loss: 0.3254, loss_single: 0.3254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,581 - Iter: 27, Total Loss: 0.3223, loss_single: 0.3223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,616 - Iter: 28, Total Loss: 0.3196, loss_single: 0.3196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,651 - Iter: 29, Total Loss: 0.3172, loss_single: 0.3172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,687 - Iter: 30, Total Loss: 0.3143, loss_single: 0.3143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,722 - Iter: 31, Total Loss: 0.3123, loss_single: 0.3123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,758 - Iter: 32, Total Loss: 0.3108, loss_single: 0.3108, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,793 - Iter: 33, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,827 - Iter: 34, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:12:36,862 - Iter: 35, Total Loss: 0.3052, loss_single: 0.3052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,898 - Iter: 36, Total Loss: 0.3040, loss_single: 0.3040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,934 - Iter: 37, Total Loss: 0.3026, loss_single: 0.3026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:36,969 - Iter: 38, Total Loss: 0.3011, loss_single: 0.3011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:37,005 - Iter: 39, Total Loss: 0.2999, loss_single: 0.2999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:37,040 - Iter: 40, Total Loss: 0.2985, loss_single: 0.2985, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:37,077 - Iter: 41, Total Loss: 0.2972, loss_single: 0.2972, 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in 0.035 sec +2026-06-24 06:12:38,121 - Iter: 70, Total Loss: 0.2784, loss_single: 0.2784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,157 - Iter: 71, Total Loss: 0.2778, loss_single: 0.2778, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:38,193 - Iter: 72, Total Loss: 0.2772, loss_single: 0.2772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:38,228 - Iter: 73, Total Loss: 0.2767, loss_single: 0.2767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,264 - Iter: 74, Total Loss: 0.2762, loss_single: 0.2762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,299 - Iter: 75, Total Loss: 0.2757, loss_single: 0.2757, loss_poissn: 0.0000, loss_pacbed: 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+2026-06-24 06:12:38,724 - Iter: 87, Total Loss: 0.2721, loss_single: 0.2721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,760 - Iter: 88, Total Loss: 0.2719, loss_single: 0.2719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,795 - Iter: 89, Total Loss: 0.2716, loss_single: 0.2716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,830 - Iter: 90, Total Loss: 0.2713, loss_single: 0.2713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,866 - Iter: 91, Total Loss: 0.2711, loss_single: 0.2711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:38,904 - Iter: 92, Total Loss: 0.2709, loss_single: 0.2709, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.2699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:39,150 - Iter: 99, Total Loss: 0.2698, loss_single: 0.2698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:39,186 - Iter: 100, Total Loss: 0.2697, loss_single: 0.2697, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:39,299 - Saving summary figures for iter 100 +2026-06-24 06:12:42,844 - ### Finished 100 iterations, averaged iter_t = 0.039138 with std = 0.040 ### +2026-06-24 06:12:42,844 - +2026-06-24 06:12:42,844 - ### The PtyRADSolver is finished in 9.222 sec ### +2026-06-24 06:12:42,844 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000024/c30_small__simulation_data4__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-3.75_C12_27.6_phi12_25.6_C21_-779_phi21_359_C23_-671_phi23_122_C30_-3.76e+05_C32.79e+07_phi56_165/simulation_data4__sample_000024.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 21.56110191345215 + probe_aberrations: + C10: -3.7520840167999268 + C12: 27.582101821899414 + C21: -779.330322265625 + C23: -670.5966186523438 + C30: -376188.53125 + C32: -2610.320068359375 + C34: -38.213871002197266 + C41: 446954.46875 + C43: -275919.875 + C45: 22994.67578125 + C50: 453757152.0 + C52: 11530836.0 + C54: 12589776.0 + C56: 17896664.0 + phi12: 25.58061230973393 + phi21: 359.0925784055415 + phi23: 122.15024251267262 + phi32: 219.47833448708997 + phi34: 89.38839321524938 + phi41: 20.16746711889809 + phi43: 73.1975322405717 + phi45: 231.82334133637605 + phi52: 175.14680043382543 + phi54: 152.3653191742732 + phi56: 165.44483090652415 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3573286235332489 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000024_measurement.h5 + key: measurement + random_seed: 20262000 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:575ba3ca9ee7c671cbfac752601444fc792a64ad21c85ca55f296190f5b0f218 +size 47959 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344/20260624_061249_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344/20260624_061249_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..880603ace762d1bf8b5dec2e14adf4524722b964 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344/20260624_061249_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:12:47,484 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:12:47,484 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:12:47,484 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:12:47,484 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:12:47,484 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:12:47,484 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:12:47,484 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:12:47,484 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:12:47,484 - +2026-06-24 06:12:47,590 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:12:47,590 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:12:47,590 - Accelerator.num_process = 1 +2026-06-24 06:12:47,590 - Accelerator.mixed_precision = no +2026-06-24 06:12:47,613 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:12:47,613 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:12:47,613 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:12:47,613 - +2026-06-24 06:12:47,613 - ### System information ### +2026-06-24 06:12:47,613 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:12:47,613 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:12:47,613 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:12:47,613 - Machine: x86_64 +2026-06-24 06:12:47,613 - Processor: x86_64 +2026-06-24 06:12:47,613 - Available CPU cores: 8 +2026-06-24 06:12:47,613 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:12:47,613 - +2026-06-24 06:12:47,613 - ### GPU information ### +2026-06-24 06:12:47,613 - CUDA Available: True +2026-06-24 06:12:47,613 - CUDA Version: 13.0 +2026-06-24 06:12:47,614 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:12:47,614 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:12:47,614 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:12:47,614 - In addition, Triton does not directly support Windows. +2026-06-24 06:12:47,614 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:12:47,642 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:12:47,642 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:12:47,642 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:12:47,643 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:12:47,643 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:12:47,643 - +2026-06-24 06:12:47,643 - ### Python information ### +2026-06-24 06:12:47,644 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:12:47,645 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:12:47,645 - +2026-06-24 06:12:47,645 - ### Packages information ### +2026-06-24 06:12:47,645 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:12:47,646 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:12:47,647 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:12:47,647 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:12:47,648 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:12:47,648 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:12:47,648 - +2026-06-24 06:12:47,648 - ### Loading params file ### +2026-06-24 06:12:47,648 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000025.yaml +2026-06-24 06:12:47,654 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:12:47,655 - Success! Params file validated and defaults applied. +2026-06-24 06:12:47,655 - +2026-06-24 06:12:47,655 - ### Setting GPU Device ### +2026-06-24 06:12:47,655 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:12:47,655 - +2026-06-24 06:12:47,655 - Random seed: 20262001 provided by params file +2026-06-24 06:12:47,656 - ### Initializing Initializer ### +2026-06-24 06:12:47,656 - init_params are displayed below: +2026-06-24 06:12:47,656 - random_seed: 20262001 +2026-06-24 06:12:47,656 - probe_illum_type: electron +2026-06-24 06:12:47,656 - probe_kv: 300.0 +2026-06-24 06:12:47,656 - probe_conv_angle: 15.504130363464355 +2026-06-24 06:12:47,656 - probe_aberrations: {'C10': -685.727, 'C12': 46.57, 'phi12': 62.868, 'C21': -56.095, 'phi21': 39.935, 'C23': -490.142, 'phi23': 159.715, 'C30': 3239768.5, 'C32': 2528.323, 'phi32': 319.923, 'C34': -4439.603, 'phi34': 178.471, 'C41': 238103.797, 'phi41': 286.444, 'C43': 164436.891, 'phi43': 9.11, 'C45': 177506.172, 'phi45': 82.159, 'C50': -200105952.0, 'C52': -9447842.0, 'phi52': 316.956, 'C54': 7694001.5, 'phi54': 288.804, 'C56': -14879661.0, 'phi56': 343.527} +2026-06-24 06:12:47,656 - beam_kev: None +2026-06-24 06:12:47,656 - probe_dRn: None +2026-06-24 06:12:47,656 - probe_Rn: None +2026-06-24 06:12:47,656 - probe_D_H: None +2026-06-24 06:12:47,656 - probe_D_FZP: None +2026-06-24 06:12:47,656 - probe_Ls: None +2026-06-24 06:12:47,656 - meas_Npix: 128 +2026-06-24 06:12:47,656 - pos_N_scans: 256 +2026-06-24 06:12:47,656 - pos_N_scan_slow: 16 +2026-06-24 06:12:47,656 - pos_N_scan_fast: 16 +2026-06-24 06:12:47,656 - pos_scan_step_size: 0.4238789975643158 +2026-06-24 06:12:47,656 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:12:47,656 - probe_pmode_max: 6 +2026-06-24 06:12:47,656 - probe_pmode_init_pows: [0.02] +2026-06-24 06:12:47,656 - obj_omode_max: 1 +2026-06-24 06:12:47,657 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:12:47,657 - obj_Nlayer: 1 +2026-06-24 06:12:47,657 - obj_slice_thickness: 20.0 +2026-06-24 06:12:47,657 - simu_Npix: None +2026-06-24 06:12:47,657 - simu_match_mode: None +2026-06-24 06:12:47,657 - meas_permute: None +2026-06-24 06:12:47,657 - meas_reshape: [256, 128, 128] +2026-06-24 06:12:47,657 - meas_flipT: [0, 0, 0] +2026-06-24 06:12:47,657 - meas_crop: None +2026-06-24 06:12:47,657 - meas_pad: None +2026-06-24 06:12:47,657 - meas_resample: None +2026-06-24 06:12:47,657 - meas_add_source_size: None +2026-06-24 06:12:47,657 - meas_add_detector_blur: None +2026-06-24 06:12:47,657 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:12:47,657 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:12:47,657 - meas_add_poisson_noise: None +2026-06-24 06:12:47,657 - meas_export: None +2026-06-24 06:12:47,657 - probe_permute: None +2026-06-24 06:12:47,657 - probe_z_shift: None +2026-06-24 06:12:47,657 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:12:47,657 - pos_scan_flipT: None +2026-06-24 06:12:47,657 - pos_scan_affine: None +2026-06-24 06:12:47,657 - pos_scan_rand_std: 0.15 +2026-06-24 06:12:47,657 - obj_z_crop: None +2026-06-24 06:12:47,657 - obj_z_pad: None +2026-06-24 06:12:47,657 - obj_z_resample: None +2026-06-24 06:12:47,657 - meas_source: file +2026-06-24 06:12:47,657 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000025_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:12:47,657 - probe_source: simu +2026-06-24 06:12:47,657 - probe_params: None +2026-06-24 06:12:47,657 - pos_source: simu +2026-06-24 06:12:47,657 - pos_params: None +2026-06-24 06:12:47,657 - obj_source: simu +2026-06-24 06:12:47,657 - obj_params: None +2026-06-24 06:12:47,657 - tilt_source: simu +2026-06-24 06:12:47,657 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:12:47,657 - +2026-06-24 06:12:47,657 - ### Initializing cache ### +2026-06-24 06:12:47,657 - use_cached_obj = False +2026-06-24 06:12:47,657 - use_cached_probe = False +2026-06-24 06:12:47,657 - use_cached_pos = False +2026-06-24 06:12:47,657 - +2026-06-24 06:12:47,658 - ### Initializing measurements ### +2026-06-24 06:12:47,658 - Loading measurements from source = 'file' +2026-06-24 06:12:47,658 - Detected measurement file type = '.h5' +2026-06-24 06:12:47,734 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:12:47,734 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:12:47,735 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0014) +2026-06-24 06:12:47,735 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:12:47,735 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:12:47,736 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:12:47,736 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:12:47,737 - Normalizing by max of the 2D mean pattern intensity: 0.00079254183 +2026-06-24 06:12:47,737 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:12:47,739 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0769, 1.7624) +2026-06-24 06:12:47,739 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:12:47,740 - Pattern total int. statistics (min, mean, max) = (1250.4471, 1260.3228, 1271.0203), with min/max = 98.4% +2026-06-24 06:12:47,742 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0769, 1.7624) +2026-06-24 06:12:47,742 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:12:47,742 - +2026-06-24 06:12:47,742 - ### Setting up calibration ### +2026-06-24 06:12:47,742 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:12:47,742 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:12:47,742 - Radius of fitted bright field disk (RBF) = 20.03 px with meas_Npix = 128 +2026-06-24 06:12:47,742 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3129 +2026-06-24 06:12:47,742 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:12:47,742 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:12:47,969 - Initial guess: center=(63.63, 63.63), radius=20.03, Gaussian blur std=0.50 +2026-06-24 06:12:47,979 - Final fit: center=(63.63, 63.63), radius=20.03, Gaussian blur std=0.59 +2026-06-24 06:12:47,979 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 20.16 px with Npix = 128 +2026-06-24 06:12:47,980 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:12:47,980 - +2026-06-24 06:12:47,980 - ### Setting init_variables dict ### +2026-06-24 06:12:47,980 - Derived values given input init_params: +2026-06-24 06:12:47,980 - kv = 300.0 kV +2026-06-24 06:12:47,980 - wavelength = 0.0197 Ang +2026-06-24 06:12:47,980 - conv_angle = 15.504130363464355 mrad +2026-06-24 06:12:47,980 - Npix = 128 px +2026-06-24 06:12:47,980 - dk = 0.0391 Ang^-1 +2026-06-24 06:12:47,980 - kMax = 2.5000 Ang^-1 +2026-06-24 06:12:47,980 - da = 0.7690 mrad +2026-06-24 06:12:47,980 - angleMax = 49.2187 mrad +2026-06-24 06:12:47,980 - RBF = 20.1603 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:12:47,980 - n_alpha = 3.1746 (# conv_angle) +2026-06-24 06:12:47,980 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:12:47,980 - Rayleigh-limited resolution = 0.7746 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:12:47,980 - Real space probe extent = 25.6000 Ang +2026-06-24 06:12:47,980 - +2026-06-24 06:12:47,980 - ### Initializing probe ### +2026-06-24 06:12:47,980 - Loading probe from source = 'simu' +2026-06-24 06:12:47,980 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:12:47,980 - Start simulating STEM probe +2026-06-24 06:12:47,980 - kv = 300.0 kV +2026-06-24 06:12:47,980 - wavelength = 0.0197 Ang +2026-06-24 06:12:47,980 - conv_angle = 15.504130363464355 mrad +2026-06-24 06:12:47,980 - Npix = 128 px +2026-06-24 06:12:47,981 - dk = 0.0391 Ang^-1 +2026-06-24 06:12:47,981 - kMax = 2.5000 Ang^-1 +2026-06-24 06:12:47,981 - alpha_max = 49.2187 mrad +2026-06-24 06:12:47,981 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:12:47,981 - Rayleigh-limited resolution = 0.7746 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:12:47,981 - Real space probe extent = 25.6000 Ang +2026-06-24 06:12:47,981 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:12:47,981 - ------------------------------------------------------------------------------------- +2026-06-24 06:12:47,981 - C1,0 C1 -685.7270 - Defocus (C10 = -df) +2026-06-24 06:12:47,981 - C1,2 A1 46.5700 62.87 2-fold astigmatism +2026-06-24 06:12:47,981 - C2,1 3*B2 -56.0950 39.94 Axial coma +2026-06-24 06:12:47,981 - C2,3 A2 -490.1420 159.72 3-fold astigmatism +2026-06-24 06:12:47,981 - C3,0 C3 3239768.5000 - Spherical aberration +2026-06-24 06:12:47,981 - C3,2 4*S3 2528.3230 319.92 Axial star aberration +2026-06-24 06:12:47,981 - C3,4 A3 -4439.6030 178.47 4-fold astigmatism +2026-06-24 06:12:47,981 - C4,1 4*B4 238103.7970 286.44 Axial coma(4th) +2026-06-24 06:12:47,981 - C4,3 4*D4 164436.8910 9.11 3-lobe aberration +2026-06-24 06:12:47,981 - C4,5 A4 177506.1720 82.16 5-fold astigmatism +2026-06-24 06:12:47,981 - C5,0 C5 -200105952.0000 - Spherical aberration (5th) +2026-06-24 06:12:47,981 - C5,2 6*S5 -9447842.0000 316.96 Axial star aberration(5th) +2026-06-24 06:12:47,981 - C5,4 6*R5 7694001.5000 288.80 4-lobe aberration +2026-06-24 06:12:47,981 - C5,6 A5 -14879661.0000 343.53 6-fold astigmatism +2026-06-24 06:12:47,984 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:12:47,984 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:12:47,984 - Creating 5 new probe modes from the major mode +2026-06-24 06:12:47,984 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:12:48,087 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:12:48,088 - Orthogonalizing 6 pmodes +2026-06-24 06:12:48,091 - Sorting 6 pmodes by their intensities +2026-06-24 06:12:48,091 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:12:48,092 - sum(|probe_data|**2) = 1260.32, while meas_total_ints (min, mean, max) = (1250.4471, 1260.3228, 1271.0203) +2026-06-24 06:12:48,092 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:12:48,092 - +2026-06-24 06:12:48,092 - ### Initializing probe positions ### +2026-06-24 06:12:48,092 - Loading probe positions from source = 'simu' +2026-06-24 06:12:48,092 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:12:48,092 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4239, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:12:48,092 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:12:48,094 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:12:48,094 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 06:12:48,095 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:12:48,095 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:12:48,095 - +2026-06-24 06:12:48,095 - ### Initializing object ### +2026-06-24 06:12:48,095 - Loading object from source = 'simu' +2026-06-24 06:12:48,095 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:12:48,096 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:12:48,096 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 193, 193) +2026-06-24 06:12:48,096 - object extent (Z, Y, X) (Ang) = [20. 38.6 38.6] +2026-06-24 06:12:48,096 - +2026-06-24 06:12:48,097 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:12:48,097 - omode_occu (omode) = float32, (1,) +2026-06-24 06:12:48,097 - +2026-06-24 06:12:48,097 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:12:48,097 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:12:48,097 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:12:48,097 - +2026-06-24 06:12:48,097 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:12:48,097 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:12:48,097 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:12:48,098 - +2026-06-24 06:12:48,098 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:12:48,098 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:12:48,098 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:12:48,098 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:12:48,098 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:12:48,098 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (193, 193). +2026-06-24 06:12:48,098 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:12:48,098 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:12:48,098 - +2026-06-24 06:12:48,098 - ### Collecting reconstruction provenance ### +2026-06-24 06:12:48,098 - Reconstruction provenance is collected and initialized. +2026-06-24 06:12:48,098 - +2026-06-24 06:12:48,098 - ### Initializing loss function ### +2026-06-24 06:12:48,098 - Active loss types: +2026-06-24 06:12:48,098 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:12:48,098 - +2026-06-24 06:12:48,098 - ### Initializing constraint function ### +2026-06-24 06:12:48,098 - Active constraint types: +2026-06-24 06:12:48,098 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:12:48,098 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:12:48,098 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:12:48,098 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:12:48,099 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:12:48,099 - +2026-06-24 06:12:48,099 - ### Done initializing PtyRADSolver ### +2026-06-24 06:12:48,099 - +2026-06-24 06:12:48,225 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:12:48,225 - +2026-06-24 06:12:48,225 - ### Initializing PtychoModel model ### +2026-06-24 06:12:48,294 - ### PtychoModel optimizable variables ### +2026-06-24 06:12:48,295 - obja : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:48,295 - objp : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:48,295 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:12:48,295 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:12:48,295 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:12:48,295 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:12:48,295 - +2026-06-24 06:12:48,295 - ### Optimizable variables statitsics ### +2026-06-24 06:12:48,295 - Total measurement values : 4,194,304 +2026-06-24 06:12:48,295 - Total optimizing variables: 271,618 +2026-06-24 06:12:48,295 - Overdetermined ratio : 15.44 +2026-06-24 06:12:48,295 - +2026-06-24 06:12:48,295 - ### Model behavior ### +2026-06-24 06:12:48,295 - Tilt propagator : False +2026-06-24 06:12:48,295 - Change slice thickness : False +2026-06-24 06:12:48,295 - Detector blur : False +2026-06-24 06:12:48,295 - Preload data : True +2026-06-24 06:12:48,295 - On-the-fly meas padding : False +2026-06-24 06:12:48,295 - On-the-fly meas resample : False +2026-06-24 06:12:48,295 - On-the-fly simu match mode: None +2026-06-24 06:12:48,295 - +2026-06-24 06:12:48,337 - ### Done initializing PtychoModel model ### +2026-06-24 06:12:48,337 - +2026-06-24 06:12:48,337 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:12:48,337 - +2026-06-24 06:12:48,337 - ### Generating indices, batches, and output_path ### +2026-06-24 06:12:48,338 - d90 = 41.000 px or 8.200 Ang +2026-06-24 06:12:48,339 - Selecting indices with the 'full' mode +2026-06-24 06:12:48,793 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:12:48,865 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:12:48,865 - Original recon_dir_affixes = ['default'] +2026-06-24 06:12:48,865 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:12:48,870 - Path corrected for compatibility: +2026-06-24 06:12:48,870 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32_2.53e+03_phi32_320_C34_-4.44e+03_phi34_178_C41_2.38e+05_phi41_286_C43_1.64e+05_phi43_9.11_C45_1.78e+05_phi45_82.2_C50_-2e+08_C52_-9.45e+06_phi52_317_C54_7.69e+06_phi54_289_C56_-1.49e+07_phi56_344 +2026-06-24 06:12:48,870 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344 +2026-06-24 06:12:48,872 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344' is generated! +2026-06-24 06:12:49,019 - +2026-06-24 06:12:49,020 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344/20260624_061249_ptyrad_log.txt ### +2026-06-24 06:12:49,020 - +2026-06-24 06:12:49,021 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:12:49,022 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:12:49,022 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:12:50,197 - Iter: 1, Total Loss: 0.5741, loss_single: 0.5741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:12:50,234 - Iter: 2, Total Loss: 0.5580, loss_single: 0.5580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:50,270 - Iter: 3, Total Loss: 0.5447, loss_single: 0.5447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,305 - Iter: 4, Total Loss: 0.5322, loss_single: 0.5322, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:12:50,340 - Iter: 5, Total Loss: 0.5197, loss_single: 0.5197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:12:50,375 - Iter: 6, Total Loss: 0.5072, loss_single: 0.5072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,410 - Iter: 7, Total Loss: 0.4964, loss_single: 0.4964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,445 - Iter: 8, Total Loss: 0.4858, loss_single: 0.4858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,480 - Iter: 9, Total Loss: 0.4746, loss_single: 0.4746, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:12:50,515 - Iter: 10, Total Loss: 0.4654, loss_single: 0.4654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,550 - Iter: 11, Total Loss: 0.4558, loss_single: 0.4558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,585 - Iter: 12, Total Loss: 0.4470, loss_single: 0.4470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,620 - Iter: 13, Total Loss: 0.4386, loss_single: 0.4386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,657 - Iter: 14, Total Loss: 0.4303, loss_single: 0.4303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:12:50,692 - Iter: 15, Total Loss: 0.4224, loss_single: 0.4224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,727 - Iter: 16, Total Loss: 0.4139, loss_single: 0.4139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,762 - Iter: 17, Total Loss: 0.4066, loss_single: 0.4066, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,797 - Iter: 18, Total Loss: 0.4008, loss_single: 0.4008, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,832 - Iter: 19, Total Loss: 0.3952, loss_single: 0.3952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,867 - Iter: 20, Total Loss: 0.3897, loss_single: 0.3897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,902 - Iter: 21, Total Loss: 0.3824, loss_single: 0.3824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,937 - Iter: 22, Total Loss: 0.3754, loss_single: 0.3754, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:50,972 - Iter: 23, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:12:51,007 - Iter: 24, Total Loss: 0.3662, loss_single: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025/c30_small__simulation_data4__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-686_C12_46.6_phi12_62.9_C21_-56.1_phi21_39.9_C23_-490_phi23_160_C30_3.24e+06_C32.49e+07_phi56_344/simulation_data4__sample_000025.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 15.504130363464355 + probe_aberrations: + C10: -685.7272338867188 + C12: 46.570030212402344 + C21: -56.09505081176758 + C23: -490.1419677734375 + C30: 3239768.5 + C32: 2528.32275390625 + C34: -4439.60302734375 + C41: 238103.796875 + C43: 164436.890625 + C45: 177506.171875 + C50: -200105952.0 + C52: -9447842.0 + C54: 7694001.5 + C56: -14879661.0 + phi12: 62.868141536113036 + phi21: 39.935149605297 + phi23: 159.71452075893689 + phi32: 319.9232466854592 + phi34: 178.4714496538425 + phi41: 286.44381771383445 + phi43: 9.109584659265147 + phi45: 82.15937563922124 + phi52: 316.95596662319554 + phi54: 288.8038119966139 + phi56: 343.5268231738925 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4238789975643158 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000025_measurement.h5 + key: measurement + random_seed: 20262001 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000025 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/20260624_061403_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:14:02,088 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:14:02,089 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:14:02,089 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:14:02,089 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:14:02,089 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:14:02,089 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:14:02,089 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:14:02,089 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:14:02,089 - +2026-06-24 06:14:02,209 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:14:02,209 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:14:02,209 - Accelerator.num_process = 1 +2026-06-24 06:14:02,209 - Accelerator.mixed_precision = no +2026-06-24 06:14:02,220 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:14:02,220 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:14:02,220 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:14:02,220 - +2026-06-24 06:14:02,220 - ### System information ### +2026-06-24 06:14:02,220 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:14:02,220 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:14:02,220 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:14:02,220 - Machine: x86_64 +2026-06-24 06:14:02,220 - Processor: x86_64 +2026-06-24 06:14:02,220 - Available CPU cores: 8 +2026-06-24 06:14:02,220 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:14:02,220 - +2026-06-24 06:14:02,220 - ### GPU information ### +2026-06-24 06:14:02,220 - CUDA Available: True +2026-06-24 06:14:02,220 - CUDA Version: 13.0 +2026-06-24 06:14:02,221 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:14:02,221 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:14:02,221 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:14:02,221 - In addition, Triton does not directly support Windows. +2026-06-24 06:14:02,221 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:14:02,236 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:14:02,236 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:14:02,236 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:14:02,236 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:14:02,236 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:14:02,237 - +2026-06-24 06:14:02,237 - ### Python information ### +2026-06-24 06:14:02,238 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:14:02,238 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:14:02,238 - +2026-06-24 06:14:02,238 - ### Packages information ### +2026-06-24 06:14:02,239 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:14:02,240 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:14:02,240 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:14:02,241 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:14:02,242 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:14:02,242 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:14:02,242 - +2026-06-24 06:14:02,242 - ### Loading params file ### +2026-06-24 06:14:02,242 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000030.yaml +2026-06-24 06:14:02,249 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:14:02,250 - Success! Params file validated and defaults applied. +2026-06-24 06:14:02,250 - +2026-06-24 06:14:02,250 - ### Setting GPU Device ### +2026-06-24 06:14:02,250 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:14:02,250 - +2026-06-24 06:14:02,250 - Random seed: 20262006 provided by params file +2026-06-24 06:14:02,250 - ### Initializing Initializer ### +2026-06-24 06:14:02,250 - init_params are displayed below: +2026-06-24 06:14:02,250 - random_seed: 20262006 +2026-06-24 06:14:02,250 - probe_illum_type: electron +2026-06-24 06:14:02,250 - probe_kv: 200.0 +2026-06-24 06:14:02,250 - probe_conv_angle: 12.082392692565918 +2026-06-24 06:14:02,251 - probe_aberrations: {'C10': -548.824, 'C12': -11.196, 'phi12': 125.612, 'C21': -518.745, 'phi21': 224.636, 'C23': -650.286, 'phi23': 87.865, 'C30': 1244609.0, 'C32': 9197.491, 'phi32': 329.71, 'C34': -10637.715, 'phi34': 37.673, 'C41': -391198.938, 'phi41': 66.789, 'C43': -230725.828, 'phi43': 17.889, 'C45': -478411.719, 'phi45': 234.148, 'C50': -317700704.0, 'C52': -11179447.0, 'phi52': 82.735, 'C54': -10970837.0, 'phi54': 295.776, 'C56': 17874432.0, 'phi56': 349.44} +2026-06-24 06:14:02,251 - beam_kev: None +2026-06-24 06:14:02,251 - probe_dRn: None +2026-06-24 06:14:02,251 - probe_Rn: None +2026-06-24 06:14:02,251 - probe_D_H: None +2026-06-24 06:14:02,251 - probe_D_FZP: None +2026-06-24 06:14:02,251 - probe_Ls: None +2026-06-24 06:14:02,251 - meas_Npix: 128 +2026-06-24 06:14:02,251 - pos_N_scans: 256 +2026-06-24 06:14:02,251 - pos_N_scan_slow: 16 +2026-06-24 06:14:02,251 - pos_N_scan_fast: 16 +2026-06-24 06:14:02,251 - pos_scan_step_size: 0.3654874265193939 +2026-06-24 06:14:02,251 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:14:02,251 - probe_pmode_max: 6 +2026-06-24 06:14:02,251 - probe_pmode_init_pows: [0.02] +2026-06-24 06:14:02,251 - obj_omode_max: 1 +2026-06-24 06:14:02,251 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:14:02,251 - obj_Nlayer: 1 +2026-06-24 06:14:02,251 - obj_slice_thickness: 20.0 +2026-06-24 06:14:02,251 - simu_Npix: None +2026-06-24 06:14:02,251 - simu_match_mode: None +2026-06-24 06:14:02,251 - meas_permute: None +2026-06-24 06:14:02,251 - meas_reshape: [256, 128, 128] +2026-06-24 06:14:02,251 - meas_flipT: [0, 0, 0] +2026-06-24 06:14:02,251 - meas_crop: None +2026-06-24 06:14:02,251 - meas_pad: None +2026-06-24 06:14:02,251 - meas_resample: None +2026-06-24 06:14:02,251 - meas_add_source_size: None +2026-06-24 06:14:02,251 - meas_add_detector_blur: None +2026-06-24 06:14:02,251 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:14:02,251 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:14:02,251 - meas_add_poisson_noise: None +2026-06-24 06:14:02,251 - meas_export: None +2026-06-24 06:14:02,251 - probe_permute: None +2026-06-24 06:14:02,251 - probe_z_shift: None +2026-06-24 06:14:02,251 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:14:02,251 - pos_scan_flipT: None +2026-06-24 06:14:02,251 - pos_scan_affine: None +2026-06-24 06:14:02,252 - pos_scan_rand_std: 0.15 +2026-06-24 06:14:02,252 - obj_z_crop: None +2026-06-24 06:14:02,252 - obj_z_pad: None +2026-06-24 06:14:02,252 - obj_z_resample: None +2026-06-24 06:14:02,252 - meas_source: file +2026-06-24 06:14:02,252 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000030_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:14:02,252 - probe_source: simu +2026-06-24 06:14:02,252 - probe_params: None +2026-06-24 06:14:02,252 - pos_source: simu +2026-06-24 06:14:02,252 - pos_params: None +2026-06-24 06:14:02,252 - obj_source: simu +2026-06-24 06:14:02,252 - obj_params: None +2026-06-24 06:14:02,252 - tilt_source: simu +2026-06-24 06:14:02,252 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:14:02,252 - +2026-06-24 06:14:02,252 - ### Initializing cache ### +2026-06-24 06:14:02,252 - use_cached_obj = False +2026-06-24 06:14:02,252 - use_cached_probe = False +2026-06-24 06:14:02,252 - use_cached_pos = False +2026-06-24 06:14:02,252 - +2026-06-24 06:14:02,252 - ### Initializing measurements ### +2026-06-24 06:14:02,252 - Loading measurements from source = 'file' +2026-06-24 06:14:02,252 - Detected measurement file type = '.h5' +2026-06-24 06:14:02,328 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:14:02,328 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:14:02,330 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0028) +2026-06-24 06:14:02,330 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:14:02,330 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:14:02,331 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:14:02,331 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:14:02,332 - Normalizing by max of the 2D mean pattern intensity: 0.0020875363 +2026-06-24 06:14:02,332 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:14:02,334 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0292, 1.3622) +2026-06-24 06:14:02,334 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:14:02,336 - Pattern total int. statistics (min, mean, max) = (476.5571, 479.0308, 482.3030), with min/max = 98.8% +2026-06-24 06:14:02,337 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0292, 1.3622) +2026-06-24 06:14:02,337 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:14:02,337 - +2026-06-24 06:14:02,337 - ### Setting up calibration ### +2026-06-24 06:14:02,337 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:14:02,337 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:14:02,337 - Radius of fitted bright field disk (RBF) = 12.23 px with meas_Npix = 128 +2026-06-24 06:14:02,337 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1911 +2026-06-24 06:14:02,337 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:14:02,337 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:14:02,560 - Initial guess: center=(63.62, 63.62), radius=12.23, Gaussian blur std=0.50 +2026-06-24 06:14:02,571 - Final fit: center=(63.62, 63.62), radius=12.23, Gaussian blur std=0.55 +2026-06-24 06:14:02,571 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.33 px with Npix = 128 +2026-06-24 06:14:02,571 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:14:02,571 - +2026-06-24 06:14:02,571 - ### Setting init_variables dict ### +2026-06-24 06:14:02,571 - Derived values given input init_params: +2026-06-24 06:14:02,571 - kv = 200.0 kV +2026-06-24 06:14:02,571 - wavelength = 0.0251 Ang +2026-06-24 06:14:02,571 - conv_angle = 12.082392692565918 mrad +2026-06-24 06:14:02,571 - Npix = 128 px +2026-06-24 06:14:02,571 - dk = 0.0391 Ang^-1 +2026-06-24 06:14:02,572 - kMax = 2.5000 Ang^-1 +2026-06-24 06:14:02,572 - da = 0.9797 mrad +2026-06-24 06:14:02,572 - angleMax = 62.6984 mrad +2026-06-24 06:14:02,572 - RBF = 12.3332 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:14:02,572 - n_alpha = 5.1892 (# conv_angle) +2026-06-24 06:14:02,572 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:14:02,572 - Rayleigh-limited resolution = 1.2662 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:14:02,572 - Real space probe extent = 25.6000 Ang +2026-06-24 06:14:02,572 - +2026-06-24 06:14:02,572 - ### Initializing probe ### +2026-06-24 06:14:02,572 - Loading probe from source = 'simu' +2026-06-24 06:14:02,572 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:14:02,572 - Start simulating STEM probe +2026-06-24 06:14:02,572 - kv = 200.0 kV +2026-06-24 06:14:02,572 - wavelength = 0.0251 Ang +2026-06-24 06:14:02,572 - conv_angle = 12.082392692565918 mrad +2026-06-24 06:14:02,572 - Npix = 128 px +2026-06-24 06:14:02,572 - dk = 0.0391 Ang^-1 +2026-06-24 06:14:02,572 - kMax = 2.5000 Ang^-1 +2026-06-24 06:14:02,572 - alpha_max = 62.6984 mrad +2026-06-24 06:14:02,572 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:14:02,572 - Rayleigh-limited resolution = 1.2662 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:14:02,572 - Real space probe extent = 25.6000 Ang +2026-06-24 06:14:02,573 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:14:02,573 - ------------------------------------------------------------------------------------- +2026-06-24 06:14:02,573 - C1,0 C1 -548.8240 - Defocus (C10 = -df) +2026-06-24 06:14:02,573 - C1,2 A1 -11.1960 125.61 2-fold astigmatism +2026-06-24 06:14:02,573 - C2,1 3*B2 -518.7450 224.64 Axial coma +2026-06-24 06:14:02,573 - C2,3 A2 -650.2860 87.86 3-fold astigmatism +2026-06-24 06:14:02,573 - C3,0 C3 1244609.0000 - Spherical aberration +2026-06-24 06:14:02,573 - C3,2 4*S3 9197.4910 329.71 Axial star aberration +2026-06-24 06:14:02,573 - C3,4 A3 -10637.7150 37.67 4-fold astigmatism +2026-06-24 06:14:02,573 - C4,1 4*B4 -391198.9380 66.79 Axial coma(4th) +2026-06-24 06:14:02,573 - C4,3 4*D4 -230725.8280 17.89 3-lobe aberration +2026-06-24 06:14:02,573 - C4,5 A4 -478411.7190 234.15 5-fold astigmatism +2026-06-24 06:14:02,573 - C5,0 C5 -317700704.0000 - Spherical aberration (5th) +2026-06-24 06:14:02,573 - C5,2 6*S5 -11179447.0000 82.73 Axial star aberration(5th) +2026-06-24 06:14:02,573 - C5,4 6*R5 -10970837.0000 295.78 4-lobe aberration +2026-06-24 06:14:02,573 - C5,6 A5 17874432.0000 349.44 6-fold astigmatism +2026-06-24 06:14:02,576 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:14:02,576 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:14:02,576 - Creating 5 new probe modes from the major mode +2026-06-24 06:14:02,576 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:14:02,763 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:14:02,764 - Orthogonalizing 6 pmodes +2026-06-24 06:14:02,767 - Sorting 6 pmodes by their intensities +2026-06-24 06:14:02,767 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:14:02,768 - sum(|probe_data|**2) = 479.03, while meas_total_ints (min, mean, max) = (476.5571, 479.0308, 482.3030) +2026-06-24 06:14:02,768 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:14:02,768 - +2026-06-24 06:14:02,768 - ### Initializing probe positions ### +2026-06-24 06:14:02,768 - Loading probe positions from source = 'simu' +2026-06-24 06:14:02,768 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:14:02,768 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3655, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:14:02,769 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:14:02,771 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:14:02,771 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 06:14:02,771 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:14:02,771 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:14:02,771 - +2026-06-24 06:14:02,771 - ### Initializing object ### +2026-06-24 06:14:02,771 - Loading object from source = 'simu' +2026-06-24 06:14:02,771 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:14:02,772 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:14:02,773 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 187) +2026-06-24 06:14:02,773 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.4] +2026-06-24 06:14:02,773 - +2026-06-24 06:14:02,773 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:14:02,773 - omode_occu (omode) = float32, (1,) +2026-06-24 06:14:02,773 - +2026-06-24 06:14:02,773 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:14:02,773 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:14:02,774 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:14:02,774 - +2026-06-24 06:14:02,774 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:14:02,774 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:14:02,774 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:14:02,774 - +2026-06-24 06:14:02,774 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:14:02,774 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:14:02,774 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:14:02,774 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:14:02,774 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:14:02,774 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 187). +2026-06-24 06:14:02,774 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:14:02,774 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:14:02,774 - +2026-06-24 06:14:02,774 - ### Collecting reconstruction provenance ### +2026-06-24 06:14:02,774 - Reconstruction provenance is collected and initialized. +2026-06-24 06:14:02,774 - +2026-06-24 06:14:02,774 - ### Initializing loss function ### +2026-06-24 06:14:02,774 - Active loss types: +2026-06-24 06:14:02,775 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:14:02,775 - +2026-06-24 06:14:02,775 - ### Initializing constraint function ### +2026-06-24 06:14:02,775 - Active constraint types: +2026-06-24 06:14:02,775 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:14:02,775 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:14:02,775 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:14:02,775 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:14:02,775 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:14:02,775 - +2026-06-24 06:14:02,775 - ### Done initializing PtyRADSolver ### +2026-06-24 06:14:02,775 - +2026-06-24 06:14:02,898 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:14:02,898 - +2026-06-24 06:14:02,899 - ### Initializing PtychoModel model ### +2026-06-24 06:14:02,969 - ### PtychoModel optimizable variables ### +2026-06-24 06:14:02,970 - obja : torch.Size([1, 1, 188, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:02,970 - objp : torch.Size([1, 1, 188, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:02,970 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:14:02,970 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:14:02,970 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:14:02,970 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:02,970 - +2026-06-24 06:14:02,970 - ### Optimizable variables statitsics ### +2026-06-24 06:14:02,970 - Total measurement values : 4,194,304 +2026-06-24 06:14:02,970 - Total optimizing variables: 267,432 +2026-06-24 06:14:02,970 - Overdetermined ratio : 15.68 +2026-06-24 06:14:02,970 - +2026-06-24 06:14:02,970 - ### Model behavior ### +2026-06-24 06:14:02,970 - Tilt propagator : False +2026-06-24 06:14:02,970 - Change slice thickness : False +2026-06-24 06:14:02,970 - Detector blur : False +2026-06-24 06:14:02,970 - Preload data : True +2026-06-24 06:14:02,970 - On-the-fly meas padding : False +2026-06-24 06:14:02,970 - On-the-fly meas resample : False +2026-06-24 06:14:02,970 - On-the-fly simu match mode: None +2026-06-24 06:14:02,970 - +2026-06-24 06:14:03,011 - ### Done initializing PtychoModel model ### +2026-06-24 06:14:03,011 - +2026-06-24 06:14:03,011 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:14:03,011 - +2026-06-24 06:14:03,011 - ### Generating indices, batches, and output_path ### +2026-06-24 06:14:03,013 - d90 = 57.000 px or 11.400 Ang +2026-06-24 06:14:03,013 - Selecting indices with the 'full' mode +2026-06-24 06:14:03,478 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:14:03,552 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:14:03,552 - Original recon_dir_affixes = ['default'] +2026-06-24 06:14:03,552 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:14:03,559 - Path corrected for compatibility: +2026-06-24 06:14:03,559 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_9.2e+03_phi32_330_C34_-1.06e+04_phi34_37.7_C41_-3.91e+05_phi41_66.8_C43_-2.31e+05_phi43_17.9_C45_-4.78e+05_phi45_234_C50_-3.18e+08_C52_-1.12e+07_phi52_82.7_C54_-1.1e+07_phi54_296_C56_1.79e+07_phi56_349 +2026-06-24 06:14:03,559 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349 +2026-06-24 06:14:03,560 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349' is generated! +2026-06-24 06:14:03,707 - +2026-06-24 06:14:03,708 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/20260624_061403_ptyrad_log.txt ### +2026-06-24 06:14:03,708 - +2026-06-24 06:14:03,709 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:14:03,709 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:14:03,709 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:14:04,902 - Iter: 1, Total Loss: 0.8152, loss_single: 0.8152, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:14:04,939 - Iter: 2, Total Loss: 0.7761, loss_single: 0.7761, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:14:04,975 - Iter: 3, Total Loss: 0.7460, loss_single: 0.7460, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,010 - Iter: 4, Total Loss: 0.7174, loss_single: 0.7174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,045 - Iter: 5, Total Loss: 0.6869, loss_single: 0.6869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,081 - Iter: 6, Total Loss: 0.6545, loss_single: 0.6545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,116 - Iter: 7, Total Loss: 0.6235, loss_single: 0.6235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,151 - Iter: 8, Total Loss: 0.5949, loss_single: 0.5949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,187 - Iter: 9, Total Loss: 0.5702, loss_single: 0.5702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,222 - Iter: 10, Total Loss: 0.5457, loss_single: 0.5457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,257 - Iter: 11, Total Loss: 0.5256, loss_single: 0.5256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,293 - Iter: 12, Total Loss: 0.5062, loss_single: 0.5062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,328 - Iter: 13, Total Loss: 0.4863, loss_single: 0.4863, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,364 - Iter: 14, Total Loss: 0.4698, loss_single: 0.4698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,398 - Iter: 15, Total Loss: 0.4511, loss_single: 0.4511, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:05,432 - Iter: 16, Total Loss: 0.4320, loss_single: 0.4320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:05,467 - Iter: 17, Total Loss: 0.4176, loss_single: 0.4176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,502 - Iter: 18, Total Loss: 0.4058, loss_single: 0.4058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,538 - Iter: 19, Total Loss: 0.3928, loss_single: 0.3928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,572 - Iter: 20, Total Loss: 0.3806, loss_single: 0.3806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:05,608 - Iter: 21, Total Loss: 0.3685, loss_single: 0.3685, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,643 - Iter: 22, Total Loss: 0.3586, loss_single: 0.3586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,678 - Iter: 23, Total Loss: 0.3518, loss_single: 0.3518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,713 - Iter: 24, Total Loss: 0.3459, loss_single: 0.3459, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,748 - Iter: 25, Total Loss: 0.3408, loss_single: 0.3408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,784 - Iter: 26, Total Loss: 0.3370, loss_single: 0.3370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,822 - Iter: 27, Total Loss: 0.3326, loss_single: 0.3326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:14:05,858 - Iter: 28, Total Loss: 0.3288, loss_single: 0.3288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,893 - Iter: 29, Total Loss: 0.3258, loss_single: 0.3258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,928 - Iter: 30, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:05,963 - Iter: 31, Total Loss: 0.3225, loss_single: 0.3225, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:05,998 - Iter: 32, Total Loss: 0.3207, loss_single: 0.3207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,034 - Iter: 33, Total Loss: 0.3191, loss_single: 0.3191, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,069 - Iter: 34, Total Loss: 0.3179, loss_single: 0.3179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,104 - Iter: 35, Total Loss: 0.3167, loss_single: 0.3167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,139 - Iter: 36, Total Loss: 0.3156, loss_single: 0.3156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,174 - Iter: 37, Total Loss: 0.3148, loss_single: 0.3148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,209 - Iter: 38, Total Loss: 0.3139, loss_single: 0.3139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,245 - Iter: 39, Total Loss: 0.3132, loss_single: 0.3132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,280 - Iter: 40, Total Loss: 0.3125, loss_single: 0.3125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,318 - Iter: 41, Total Loss: 0.3118, loss_single: 0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,353 - Iter: 42, Total Loss: 0.3113, loss_single: 0.3113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,388 - Iter: 43, Total Loss: 0.3108, loss_single: 0.3108, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,423 - Iter: 44, Total Loss: 0.3104, loss_single: 0.3104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,458 - Iter: 45, Total Loss: 0.3100, loss_single: 0.3100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,494 - Iter: 46, Total Loss: 0.3097, loss_single: 0.3097, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,529 - Iter: 47, Total Loss: 0.3093, loss_single: 0.3093, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,564 - Iter: 48, Total Loss: 0.3089, loss_single: 0.3089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,599 - Iter: 49, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,635 - Iter: 50, Total Loss: 0.3083, loss_single: 0.3083, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,670 - Iter: 51, Total Loss: 0.3080, loss_single: 0.3080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,705 - Iter: 52, Total Loss: 0.3078, loss_single: 0.3078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:06,740 - Iter: 53, Total Loss: 0.3076, loss_single: 0.3076, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,775 - Iter: 54, Total Loss: 0.3074, loss_single: 0.3074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,810 - Iter: 55, Total Loss: 0.3072, loss_single: 0.3072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,845 - Iter: 56, Total Loss: 0.3070, loss_single: 0.3070, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,880 - Iter: 57, Total Loss: 0.3069, loss_single: 0.3069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,916 - Iter: 58, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,951 - Iter: 59, Total Loss: 0.3065, loss_single: 0.3065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:06,987 - Iter: 60, Total Loss: 0.3064, loss_single: 0.3064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,021 - Iter: 61, Total Loss: 0.3062, loss_single: 0.3062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:07,056 - Iter: 62, Total Loss: 0.3061, loss_single: 0.3061, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,092 - Iter: 63, Total Loss: 0.3060, loss_single: 0.3060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,127 - Iter: 64, Total Loss: 0.3058, loss_single: 0.3058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,162 - Iter: 65, Total Loss: 0.3057, loss_single: 0.3057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,198 - Iter: 66, Total Loss: 0.3055, loss_single: 0.3055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,233 - Iter: 67, Total Loss: 0.3053, loss_single: 0.3053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,269 - Iter: 68, Total Loss: 0.3052, loss_single: 0.3052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,304 - Iter: 69, Total Loss: 0.3051, loss_single: 0.3051, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,340 - Iter: 70, Total Loss: 0.3050, loss_single: 0.3050, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,375 - Iter: 71, Total Loss: 0.3049, loss_single: 0.3049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,410 - Iter: 72, Total Loss: 0.3048, loss_single: 0.3048, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,445 - Iter: 73, Total Loss: 0.3047, loss_single: 0.3047, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,481 - Iter: 74, Total Loss: 0.3046, loss_single: 0.3046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,516 - Iter: 75, Total Loss: 0.3045, loss_single: 0.3045, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,551 - Iter: 76, Total Loss: 0.3044, loss_single: 0.3044, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,587 - Iter: 77, Total Loss: 0.3043, loss_single: 0.3043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,623 - Iter: 78, Total Loss: 0.3042, loss_single: 0.3042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:14:07,658 - Iter: 79, Total Loss: 0.3041, loss_single: 0.3041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,694 - Iter: 80, Total Loss: 0.3040, loss_single: 0.3040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,729 - Iter: 81, Total Loss: 0.3039, loss_single: 0.3039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,764 - Iter: 82, Total Loss: 0.3038, loss_single: 0.3038, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,800 - Iter: 83, Total Loss: 0.3037, loss_single: 0.3037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,835 - Iter: 84, Total Loss: 0.3037, loss_single: 0.3037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:07,870 - Iter: 85, Total Loss: 0.3036, loss_single: 0.3036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,931 - Iter: 86, Total Loss: 0.3035, loss_single: 0.3035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:07,966 - Iter: 87, Total Loss: 0.3034, loss_single: 0.3034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,001 - Iter: 88, Total Loss: 0.3033, loss_single: 0.3033, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,036 - Iter: 89, Total Loss: 0.3032, loss_single: 0.3032, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,071 - Iter: 90, Total Loss: 0.3031, loss_single: 0.3031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:08,109 - Iter: 91, Total Loss: 0.3030, loss_single: 0.3030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:14:08,144 - Iter: 92, Total Loss: 0.3029, loss_single: 0.3029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,180 - Iter: 93, Total Loss: 0.3029, loss_single: 0.3029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,215 - Iter: 94, Total Loss: 0.3029, loss_single: 0.3029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,251 - Iter: 95, Total Loss: 0.3028, loss_single: 0.3028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,286 - Iter: 96, Total Loss: 0.3027, loss_single: 0.3027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,322 - Iter: 97, Total Loss: 0.3027, loss_single: 0.3027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,357 - Iter: 98, Total Loss: 0.3026, loss_single: 0.3026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,393 - Iter: 99, Total Loss: 0.3025, loss_single: 0.3025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,428 - Iter: 100, Total Loss: 0.3025, loss_single: 0.3025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:08,538 - Saving summary figures for iter 100 +2026-06-24 06:14:12,255 - ### Finished 100 iterations, averaged iter_t = 0.038909 with std = 0.040 ### +2026-06-24 06:14:12,255 - +2026-06-24 06:14:12,255 - ### The PtyRADSolver is finished in 9.357 sec ### +2026-06-24 06:14:12,255 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..df613115d908815baba6ae7c9503f19393561973 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/simulation_data4__sample_000030.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/simulation_data4__sample_000030.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7d53b2a99aa917fc88366da59a9e91a083693363 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030/c30_small__simulation_data4__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-549_C12_-11.2_phi12_126_C21_-519_phi21_225_C23_-650_phi23_87.9_C30_1.24e+06_C32_.79e+07_phi56_349/simulation_data4__sample_000030.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 12.082392692565918 + probe_aberrations: + C10: -548.8236694335938 + C12: -11.195591926574707 + C21: -518.7454223632812 + C23: -650.2861938476562 + C30: 1244609.0 + C32: 9197.4912109375 + C34: -10637.71484375 + C41: -391198.9375 + C43: -230725.828125 + C45: -478411.71875 + C50: -317700704.0 + C52: -11179447.0 + C54: -10970837.0 + C56: 17874432.0 + phi12: 125.61187800668345 + phi21: 224.63608353693337 + phi23: 87.86518589825566 + phi32: 329.7101427849004 + phi34: 37.67260163140608 + phi41: 66.78938728956321 + phi43: 17.889030417450435 + phi45: 234.1477639939581 + phi52: 82.73527669946921 + phi54: 295.77590517682285 + phi56: 349.4396632968592 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3654874265193939 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000030_measurement.h5 + key: measurement + random_seed: 20262006 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000030 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000030 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/20260624_061447_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/20260624_061447_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..627029c163ef5055c0dd647631a15562e54825ca --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/20260624_061447_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:14:46,320 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:14:46,321 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:14:46,321 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:14:46,321 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:14:46,321 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:14:46,321 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:14:46,321 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:14:46,321 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:14:46,321 - +2026-06-24 06:14:46,429 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:14:46,429 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:14:46,429 - Accelerator.num_process = 1 +2026-06-24 06:14:46,429 - Accelerator.mixed_precision = no +2026-06-24 06:14:46,440 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:14:46,440 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:14:46,440 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:14:46,440 - +2026-06-24 06:14:46,440 - ### System information ### +2026-06-24 06:14:46,440 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:14:46,440 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:14:46,440 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:14:46,440 - Machine: x86_64 +2026-06-24 06:14:46,440 - Processor: x86_64 +2026-06-24 06:14:46,440 - Available CPU cores: 8 +2026-06-24 06:14:46,440 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:14:46,440 - +2026-06-24 06:14:46,440 - ### GPU information ### +2026-06-24 06:14:46,440 - CUDA Available: True +2026-06-24 06:14:46,440 - CUDA Version: 13.0 +2026-06-24 06:14:46,441 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:14:46,441 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:14:46,441 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:14:46,441 - In addition, Triton does not directly support Windows. +2026-06-24 06:14:46,441 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:14:46,457 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:14:46,457 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:14:46,457 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:14:46,457 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:14:46,457 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:14:46,457 - +2026-06-24 06:14:46,457 - ### Python information ### +2026-06-24 06:14:46,459 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:14:46,459 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:14:46,459 - +2026-06-24 06:14:46,459 - ### Packages information ### +2026-06-24 06:14:46,459 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:14:46,460 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:14:46,460 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:14:46,461 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:14:46,462 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:14:46,462 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:14:46,462 - +2026-06-24 06:14:46,462 - ### Loading params file ### +2026-06-24 06:14:46,462 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000033.yaml +2026-06-24 06:14:46,468 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:14:46,469 - Success! Params file validated and defaults applied. +2026-06-24 06:14:46,469 - +2026-06-24 06:14:46,469 - ### Setting GPU Device ### +2026-06-24 06:14:46,469 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:14:46,469 - +2026-06-24 06:14:46,469 - Random seed: 20262009 provided by params file +2026-06-24 06:14:46,470 - ### Initializing Initializer ### +2026-06-24 06:14:46,470 - init_params are displayed below: +2026-06-24 06:14:46,470 - random_seed: 20262009 +2026-06-24 06:14:46,470 - probe_illum_type: electron +2026-06-24 06:14:46,470 - probe_kv: 160.0 +2026-06-24 06:14:46,470 - probe_conv_angle: 18.914682388305664 +2026-06-24 06:14:46,470 - probe_aberrations: {'C10': -290.221, 'C12': -28.959, 'phi12': 134.211, 'C21': -67.71, 'phi21': 198.998, 'C23': 434.591, 'phi23': 342.981, 'C30': 146599.641, 'C32': -8818.994, 'phi32': 355.285, 'C34': -8705.153, 'phi34': 114.818, 'C41': -298421.219, 'phi41': 241.456, 'C43': -438611.438, 'phi43': 349.993, 'C45': -304535.75, 'phi45': 264.445, 'C50': -98580512.0, 'C52': -11198145.0, 'phi52': 144.097, 'C54': -12999598.0, 'phi54': 338.616, 'C56': 13126693.0, 'phi56': 347.505} +2026-06-24 06:14:46,470 - beam_kev: None +2026-06-24 06:14:46,470 - probe_dRn: None +2026-06-24 06:14:46,470 - probe_Rn: None +2026-06-24 06:14:46,470 - probe_D_H: None +2026-06-24 06:14:46,470 - probe_D_FZP: None +2026-06-24 06:14:46,470 - probe_Ls: None +2026-06-24 06:14:46,470 - meas_Npix: 128 +2026-06-24 06:14:46,470 - pos_N_scans: 256 +2026-06-24 06:14:46,470 - pos_N_scan_slow: 16 +2026-06-24 06:14:46,470 - pos_N_scan_fast: 16 +2026-06-24 06:14:46,470 - pos_scan_step_size: 0.514159619808197 +2026-06-24 06:14:46,470 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:14:46,470 - probe_pmode_max: 6 +2026-06-24 06:14:46,470 - probe_pmode_init_pows: [0.02] +2026-06-24 06:14:46,470 - obj_omode_max: 1 +2026-06-24 06:14:46,470 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:14:46,470 - obj_Nlayer: 1 +2026-06-24 06:14:46,471 - obj_slice_thickness: 20.0 +2026-06-24 06:14:46,471 - simu_Npix: None +2026-06-24 06:14:46,471 - simu_match_mode: None +2026-06-24 06:14:46,471 - meas_permute: None +2026-06-24 06:14:46,471 - meas_reshape: [256, 128, 128] +2026-06-24 06:14:46,471 - meas_flipT: [0, 0, 0] +2026-06-24 06:14:46,471 - meas_crop: None +2026-06-24 06:14:46,471 - meas_pad: None +2026-06-24 06:14:46,471 - meas_resample: None +2026-06-24 06:14:46,471 - meas_add_source_size: None +2026-06-24 06:14:46,471 - meas_add_detector_blur: None +2026-06-24 06:14:46,471 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:14:46,471 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:14:46,471 - meas_add_poisson_noise: None +2026-06-24 06:14:46,471 - meas_export: None +2026-06-24 06:14:46,471 - probe_permute: None +2026-06-24 06:14:46,471 - probe_z_shift: None +2026-06-24 06:14:46,471 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:14:46,471 - pos_scan_flipT: None +2026-06-24 06:14:46,471 - pos_scan_affine: None +2026-06-24 06:14:46,471 - pos_scan_rand_std: 0.15 +2026-06-24 06:14:46,471 - obj_z_crop: None +2026-06-24 06:14:46,471 - obj_z_pad: None +2026-06-24 06:14:46,471 - obj_z_resample: None +2026-06-24 06:14:46,471 - meas_source: file +2026-06-24 06:14:46,471 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000033_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:14:46,471 - probe_source: simu +2026-06-24 06:14:46,471 - probe_params: None +2026-06-24 06:14:46,471 - pos_source: simu +2026-06-24 06:14:46,471 - pos_params: None +2026-06-24 06:14:46,471 - obj_source: simu +2026-06-24 06:14:46,471 - obj_params: None +2026-06-24 06:14:46,471 - tilt_source: simu +2026-06-24 06:14:46,471 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:14:46,471 - +2026-06-24 06:14:46,471 - ### Initializing cache ### +2026-06-24 06:14:46,471 - use_cached_obj = False +2026-06-24 06:14:46,471 - use_cached_probe = False +2026-06-24 06:14:46,471 - use_cached_pos = False +2026-06-24 06:14:46,471 - +2026-06-24 06:14:46,472 - ### Initializing measurements ### +2026-06-24 06:14:46,472 - Loading measurements from source = 'file' +2026-06-24 06:14:46,472 - Detected measurement file type = '.h5' +2026-06-24 06:14:46,553 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:14:46,553 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:14:46,555 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0016) +2026-06-24 06:14:46,555 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:14:46,555 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:14:46,556 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:14:46,556 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:14:46,557 - Normalizing by max of the 2D mean pattern intensity: 0.0010982637 +2026-06-24 06:14:46,557 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:14:46,559 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0555, 1.4420) +2026-06-24 06:14:46,559 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:14:46,560 - Pattern total int. statistics (min, mean, max) = (901.1768, 909.5198, 917.2472), with min/max = 98.2% +2026-06-24 06:14:46,562 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0555, 1.4420) +2026-06-24 06:14:46,562 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:14:46,562 - +2026-06-24 06:14:46,562 - ### Setting up calibration ### +2026-06-24 06:14:46,562 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:14:46,562 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:14:46,562 - Radius of fitted bright field disk (RBF) = 16.85 px with meas_Npix = 128 +2026-06-24 06:14:46,562 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2633 +2026-06-24 06:14:46,562 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:14:46,562 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:14:46,789 - Initial guess: center=(63.63, 63.62), radius=16.85, Gaussian blur std=0.50 +2026-06-24 06:14:46,803 - Final fit: center=(63.63, 63.62), radius=16.85, Gaussian blur std=0.75 +2026-06-24 06:14:46,803 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 16.98 px with Npix = 128 +2026-06-24 06:14:46,803 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:14:46,803 - +2026-06-24 06:14:46,803 - ### Setting init_variables dict ### +2026-06-24 06:14:46,803 - Derived values given input init_params: +2026-06-24 06:14:46,803 - kv = 160.0 kV +2026-06-24 06:14:46,803 - wavelength = 0.0285 Ang +2026-06-24 06:14:46,803 - conv_angle = 18.914682388305664 mrad +2026-06-24 06:14:46,803 - Npix = 128 px +2026-06-24 06:14:46,804 - dk = 0.0391 Ang^-1 +2026-06-24 06:14:46,804 - kMax = 2.5000 Ang^-1 +2026-06-24 06:14:46,804 - da = 1.1137 mrad +2026-06-24 06:14:46,804 - angleMax = 71.2751 mrad +2026-06-24 06:14:46,804 - RBF = 16.9840 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:14:46,804 - n_alpha = 3.7682 (# conv_angle) +2026-06-24 06:14:46,804 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:14:46,804 - Rayleigh-limited resolution = 0.9195 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:14:46,804 - Real space probe extent = 25.6000 Ang +2026-06-24 06:14:46,804 - +2026-06-24 06:14:46,804 - ### Initializing probe ### +2026-06-24 06:14:46,804 - Loading probe from source = 'simu' +2026-06-24 06:14:46,804 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:14:46,804 - Start simulating STEM probe +2026-06-24 06:14:46,804 - kv = 160.0 kV +2026-06-24 06:14:46,804 - wavelength = 0.0285 Ang +2026-06-24 06:14:46,804 - conv_angle = 18.914682388305664 mrad +2026-06-24 06:14:46,804 - Npix = 128 px +2026-06-24 06:14:46,804 - dk = 0.0391 Ang^-1 +2026-06-24 06:14:46,804 - kMax = 2.5000 Ang^-1 +2026-06-24 06:14:46,804 - alpha_max = 71.2751 mrad +2026-06-24 06:14:46,804 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:14:46,804 - Rayleigh-limited resolution = 0.9195 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:14:46,804 - Real space probe extent = 25.6000 Ang +2026-06-24 06:14:46,804 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:14:46,805 - ------------------------------------------------------------------------------------ +2026-06-24 06:14:46,805 - C1,0 C1 -290.2210 - Defocus (C10 = -df) +2026-06-24 06:14:46,805 - C1,2 A1 -28.9590 134.21 2-fold astigmatism +2026-06-24 06:14:46,805 - C2,1 3*B2 -67.7100 199.00 Axial coma +2026-06-24 06:14:46,805 - C2,3 A2 434.5910 342.98 3-fold astigmatism +2026-06-24 06:14:46,805 - C3,0 C3 146599.6410 - Spherical aberration +2026-06-24 06:14:46,805 - C3,2 4*S3 -8818.9940 355.29 Axial star aberration +2026-06-24 06:14:46,805 - C3,4 A3 -8705.1530 114.82 4-fold astigmatism +2026-06-24 06:14:46,805 - C4,1 4*B4 -298421.2190 241.46 Axial coma(4th) +2026-06-24 06:14:46,805 - C4,3 4*D4 -438611.4380 349.99 3-lobe aberration +2026-06-24 06:14:46,805 - C4,5 A4 -304535.7500 264.44 5-fold astigmatism +2026-06-24 06:14:46,805 - C5,0 C5 -98580512.0000 - Spherical aberration (5th) +2026-06-24 06:14:46,805 - C5,2 6*S5 -11198145.0000 144.10 Axial star aberration(5th) +2026-06-24 06:14:46,805 - C5,4 6*R5 -12999598.0000 338.62 4-lobe aberration +2026-06-24 06:14:46,805 - C5,6 A5 13126693.0000 347.50 6-fold astigmatism +2026-06-24 06:14:46,808 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:14:46,808 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:14:46,808 - Creating 5 new probe modes from the major mode +2026-06-24 06:14:46,808 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:14:46,976 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:14:46,977 - Orthogonalizing 6 pmodes +2026-06-24 06:14:46,980 - Sorting 6 pmodes by their intensities +2026-06-24 06:14:46,980 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:14:46,981 - sum(|probe_data|**2) = 909.52, while meas_total_ints (min, mean, max) = (901.1768, 909.5198, 917.2472) +2026-06-24 06:14:46,981 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:14:46,981 - +2026-06-24 06:14:46,981 - ### Initializing probe positions ### +2026-06-24 06:14:46,981 - Loading probe positions from source = 'simu' +2026-06-24 06:14:46,981 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:14:46,981 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5142, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:14:46,981 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:14:46,983 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:14:46,983 - crop_pos 1st and last px coords (y,x) = ([16, 17], [55, 55]) +2026-06-24 06:14:46,984 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 06:14:46,984 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:14:46,984 - +2026-06-24 06:14:46,984 - ### Initializing object ### +2026-06-24 06:14:46,984 - Loading object from source = 'simu' +2026-06-24 06:14:46,984 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:14:46,985 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:14:46,985 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 201, 201) +2026-06-24 06:14:46,985 - object extent (Z, Y, X) (Ang) = [20. 40.2 40.2] +2026-06-24 06:14:46,986 - +2026-06-24 06:14:46,986 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:14:46,986 - omode_occu (omode) = float32, (1,) +2026-06-24 06:14:46,986 - +2026-06-24 06:14:46,986 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:14:46,986 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:14:46,986 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:14:46,986 - +2026-06-24 06:14:46,986 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:14:46,986 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:14:46,987 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:14:46,987 - +2026-06-24 06:14:46,987 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:14:46,987 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:14:46,987 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:14:46,987 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:14:46,987 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:14:46,987 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (201, 201). +2026-06-24 06:14:46,987 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:14:46,987 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:14:46,987 - +2026-06-24 06:14:46,987 - ### Collecting reconstruction provenance ### +2026-06-24 06:14:46,987 - Reconstruction provenance is collected and initialized. +2026-06-24 06:14:46,987 - +2026-06-24 06:14:46,987 - ### Initializing loss function ### +2026-06-24 06:14:46,987 - Active loss types: +2026-06-24 06:14:46,987 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:14:46,987 - +2026-06-24 06:14:46,987 - ### Initializing constraint function ### +2026-06-24 06:14:46,987 - Active constraint types: +2026-06-24 06:14:46,987 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:14:46,987 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:14:46,988 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:14:46,988 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:14:46,988 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:14:46,988 - +2026-06-24 06:14:46,988 - ### Done initializing PtyRADSolver ### +2026-06-24 06:14:46,988 - +2026-06-24 06:14:47,112 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:14:47,113 - +2026-06-24 06:14:47,113 - ### Initializing PtychoModel model ### +2026-06-24 06:14:47,182 - ### PtychoModel optimizable variables ### +2026-06-24 06:14:47,182 - obja : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:47,182 - objp : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:47,182 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:14:47,182 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:14:47,182 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:14:47,183 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:14:47,183 - +2026-06-24 06:14:47,183 - ### Optimizable variables statitsics ### +2026-06-24 06:14:47,183 - Total measurement values : 4,194,304 +2026-06-24 06:14:47,183 - Total optimizing variables: 277,922 +2026-06-24 06:14:47,183 - Overdetermined ratio : 15.09 +2026-06-24 06:14:47,183 - +2026-06-24 06:14:47,183 - ### Model behavior ### +2026-06-24 06:14:47,183 - Tilt propagator : False +2026-06-24 06:14:47,183 - Change slice thickness : False +2026-06-24 06:14:47,183 - Detector blur : False +2026-06-24 06:14:47,183 - Preload data : True +2026-06-24 06:14:47,183 - On-the-fly meas padding : False +2026-06-24 06:14:47,183 - On-the-fly meas resample : False +2026-06-24 06:14:47,183 - On-the-fly simu match mode: None +2026-06-24 06:14:47,183 - +2026-06-24 06:14:47,224 - ### Done initializing PtychoModel model ### +2026-06-24 06:14:47,225 - +2026-06-24 06:14:47,225 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:14:47,225 - +2026-06-24 06:14:47,225 - ### Generating indices, batches, and output_path ### +2026-06-24 06:14:47,226 - d90 = 51.000 px or 10.200 Ang +2026-06-24 06:14:47,226 - Selecting indices with the 'full' mode +2026-06-24 06:14:47,683 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:14:47,759 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:14:47,759 - Original recon_dir_affixes = ['default'] +2026-06-24 06:14:47,759 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:14:47,766 - Path corrected for compatibility: +2026-06-24 06:14:47,766 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8.82e+03_phi32_355_C34_-8.71e+03_phi34_115_C41_-2.98e+05_phi41_241_C43_-4.39e+05_phi43_350_C45_-3.05e+05_phi45_264_C50_-9.86e+07_C52_-1.12e+07_phi52_144_C54_-1.3e+07_phi54_339_C56_1.31e+07_phi56_348 +2026-06-24 06:14:47,766 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348 +2026-06-24 06:14:47,767 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348' is generated! +2026-06-24 06:14:47,919 - +2026-06-24 06:14:47,920 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/20260624_061447_ptyrad_log.txt ### +2026-06-24 06:14:47,920 - +2026-06-24 06:14:47,921 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:14:47,921 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:14:47,921 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:14:49,098 - Iter: 1, Total Loss: 0.6790, loss_single: 0.6790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:14:49,134 - Iter: 2, Total Loss: 0.6579, loss_single: 0.6579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:14:49,170 - Iter: 3, Total Loss: 0.6425, loss_single: 0.6425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,205 - Iter: 4, Total Loss: 0.6273, loss_single: 0.6273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,240 - Iter: 5, Total Loss: 0.6113, loss_single: 0.6113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,275 - Iter: 6, Total Loss: 0.5958, loss_single: 0.5958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,311 - Iter: 7, Total Loss: 0.5807, loss_single: 0.5807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,347 - Iter: 8, Total Loss: 0.5669, loss_single: 0.5669, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,381 - Iter: 9, Total Loss: 0.5521, loss_single: 0.5521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:49,417 - Iter: 10, Total Loss: 0.5372, loss_single: 0.5372, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,452 - Iter: 11, Total Loss: 0.5245, loss_single: 0.5245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:49,486 - Iter: 12, Total Loss: 0.5123, loss_single: 0.5123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:49,522 - Iter: 13, Total Loss: 0.4994, loss_single: 0.4994, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,557 - Iter: 14, Total Loss: 0.4883, loss_single: 0.4883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,592 - Iter: 15, Total Loss: 0.4792, loss_single: 0.4792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,627 - Iter: 16, Total Loss: 0.4699, loss_single: 0.4699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:49,662 - Iter: 17, Total Loss: 0.4600, loss_single: 0.4600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,697 - Iter: 18, Total Loss: 0.4500, loss_single: 0.4500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,733 - Iter: 19, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,768 - Iter: 20, Total Loss: 0.4294, loss_single: 0.4294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,803 - Iter: 21, Total Loss: 0.4188, loss_single: 0.4188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,838 - Iter: 22, Total Loss: 0.4097, loss_single: 0.4097, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:49,873 - Iter: 23, Total Loss: 0.4013, loss_single: 0.4013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,909 - Iter: 24, Total Loss: 0.3933, loss_single: 0.3933, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,943 - Iter: 25, Total Loss: 0.3866, loss_single: 0.3866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:49,979 - Iter: 26, Total Loss: 0.3805, loss_single: 0.3805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,017 - Iter: 27, Total Loss: 0.3738, loss_single: 0.3738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:14:50,052 - Iter: 28, Total Loss: 0.3663, loss_single: 0.3663, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,087 - Iter: 29, Total Loss: 0.3594, loss_single: 0.3594, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,122 - Iter: 30, Total Loss: 0.3543, loss_single: 0.3543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,157 - Iter: 31, Total Loss: 0.3504, loss_single: 0.3504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:50,192 - Iter: 32, Total Loss: 0.3454, loss_single: 0.3454, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,228 - Iter: 33, Total Loss: 0.3394, loss_single: 0.3394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,263 - Iter: 34, Total Loss: 0.3346, loss_single: 0.3346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,298 - Iter: 35, Total Loss: 0.3307, loss_single: 0.3307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,333 - Iter: 36, Total Loss: 0.3260, loss_single: 0.3260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,368 - Iter: 37, Total Loss: 0.3204, loss_single: 0.3204, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,403 - Iter: 38, Total Loss: 0.3153, loss_single: 0.3153, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,438 - Iter: 39, Total Loss: 0.3106, loss_single: 0.3106, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,473 - Iter: 40, Total Loss: 0.3060, loss_single: 0.3060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,511 - Iter: 41, Total Loss: 0.3023, loss_single: 0.3023, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,545 - Iter: 42, Total Loss: 0.2985, loss_single: 0.2985, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,581 - Iter: 43, Total Loss: 0.2942, loss_single: 0.2942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,616 - Iter: 44, Total Loss: 0.2902, loss_single: 0.2902, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,651 - Iter: 45, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,689 - Iter: 46, Total Loss: 0.2845, loss_single: 0.2845, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:14:50,724 - Iter: 47, Total Loss: 0.2823, loss_single: 0.2823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,759 - Iter: 48, Total Loss: 0.2802, loss_single: 0.2802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:50,794 - Iter: 49, Total Loss: 0.2783, loss_single: 0.2783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,829 - Iter: 50, Total Loss: 0.2766, loss_single: 0.2766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,864 - Iter: 51, Total Loss: 0.2747, loss_single: 0.2747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:50,899 - Iter: 52, Total Loss: 0.2726, loss_single: 0.2726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,935 - Iter: 53, Total Loss: 0.2707, loss_single: 0.2707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:50,970 - Iter: 54, Total Loss: 0.2689, loss_single: 0.2689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:51,004 - Iter: 55, Total Loss: 0.2675, loss_single: 0.2675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:51,039 - Iter: 56, Total Loss: 0.2662, loss_single: 0.2662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:14:51,075 - Iter: 57, Total Loss: 0.2649, loss_single: 0.2649, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:14:51,110 - Iter: 58, Total Loss: 0.2640, loss_single: 0.2640, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/simulation_data4__sample_000033.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/simulation_data4__sample_000033.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ea0f8b87f58ce64fdb44d5948de3777c101c5cdc --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/simulation_data4__sample_000033.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 18.914682388305664 + probe_aberrations: + C10: -290.22064208984375 + C12: -28.958608627319336 + C21: -67.7098388671875 + C23: 434.5908508300781 + C30: 146599.640625 + C32: -8818.994140625 + C34: -8705.1533203125 + C41: -298421.21875 + C43: -438611.4375 + C45: -304535.75 + C50: -98580512.0 + C52: -11198145.0 + C54: -12999598.0 + C56: 13126693.0 + phi12: 134.2109768887028 + phi21: 198.99754780794316 + phi23: 342.9808451723984 + phi32: 355.28450205644924 + phi34: 114.8175836461787 + phi41: 241.45565659452157 + phi43: 349.9934550347638 + phi45: 264.4448712274906 + phi52: 144.09708831602762 + phi54: 338.61591716065334 + phi56: 347.5045614219679 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.514159619808197 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000033_measurement.h5 + key: measurement + random_seed: 20262009 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000033 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000033/c30_small__simulation_data4__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-290_C12_-29_phi12_134_C21_-67.7_phi21_199_C23_435_phi23_343_C30_1.47e+05_C32_-8..31e+07_phi56_348/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/20260624_061502_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:15:01,349 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:15:01,350 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:15:01,350 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:15:01,350 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:15:01,350 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:15:01,350 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:15:01,350 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:15:01,350 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:15:01,350 - +2026-06-24 06:15:01,459 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:15:01,459 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:15:01,459 - Accelerator.num_process = 1 +2026-06-24 06:15:01,459 - Accelerator.mixed_precision = no +2026-06-24 06:15:01,469 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:15:01,469 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:15:01,470 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:15:01,470 - +2026-06-24 06:15:01,470 - ### System information ### +2026-06-24 06:15:01,470 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:15:01,470 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:15:01,470 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:15:01,470 - Machine: x86_64 +2026-06-24 06:15:01,470 - Processor: x86_64 +2026-06-24 06:15:01,470 - Available CPU cores: 8 +2026-06-24 06:15:01,470 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:15:01,470 - +2026-06-24 06:15:01,470 - ### GPU information ### +2026-06-24 06:15:01,470 - CUDA Available: True +2026-06-24 06:15:01,470 - CUDA Version: 13.0 +2026-06-24 06:15:01,471 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:15:01,471 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:15:01,471 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:15:01,471 - In addition, Triton does not directly support Windows. +2026-06-24 06:15:01,471 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:15:01,486 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:15:01,486 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:15:01,486 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:15:01,486 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:15:01,486 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:15:01,486 - +2026-06-24 06:15:01,486 - ### Python information ### +2026-06-24 06:15:01,488 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:15:01,488 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:15:01,488 - +2026-06-24 06:15:01,488 - ### Packages information ### +2026-06-24 06:15:01,488 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:15:01,489 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:15:01,490 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:15:01,490 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:15:01,491 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:15:01,491 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:15:01,491 - +2026-06-24 06:15:01,491 - ### Loading params file ### +2026-06-24 06:15:01,491 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000034.yaml +2026-06-24 06:15:01,498 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:15:01,499 - Success! Params file validated and defaults applied. +2026-06-24 06:15:01,499 - +2026-06-24 06:15:01,499 - ### Setting GPU Device ### +2026-06-24 06:15:01,499 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:15:01,499 - +2026-06-24 06:15:01,499 - Random seed: 20262010 provided by params file +2026-06-24 06:15:01,499 - ### Initializing Initializer ### +2026-06-24 06:15:01,499 - init_params are displayed below: +2026-06-24 06:15:01,499 - random_seed: 20262010 +2026-06-24 06:15:01,499 - probe_illum_type: electron +2026-06-24 06:15:01,499 - probe_kv: 60.0 +2026-06-24 06:15:01,499 - probe_conv_angle: 13.967053413391113 +2026-06-24 06:15:01,499 - probe_aberrations: {'C10': -316.921, 'C12': -0.932, 'phi12': 154.301, 'C21': -960.099, 'phi21': 74.178, 'C23': 102.063, 'phi23': 341.866, 'C30': -186131.141, 'C32': -10914.968, 'phi32': 188.339, 'C34': -7417.761, 'phi34': 266.42, 'C41': 364542.281, 'phi41': 54.425, 'C43': 426279.0, 'phi43': 209.583, 'C45': -159263.844, 'phi45': 316.336, 'C50': -379219776.0, 'C52': -12873377.0, 'phi52': 75.943, 'C54': -5240924.0, 'phi54': 100.53, 'C56': 11050132.0, 'phi56': 1.2} +2026-06-24 06:15:01,500 - beam_kev: None +2026-06-24 06:15:01,500 - probe_dRn: None +2026-06-24 06:15:01,500 - probe_Rn: None +2026-06-24 06:15:01,500 - probe_D_H: None +2026-06-24 06:15:01,500 - probe_D_FZP: None +2026-06-24 06:15:01,500 - probe_Ls: None +2026-06-24 06:15:01,500 - meas_Npix: 128 +2026-06-24 06:15:01,500 - pos_N_scans: 256 +2026-06-24 06:15:01,500 - pos_N_scan_slow: 16 +2026-06-24 06:15:01,500 - pos_N_scan_fast: 16 +2026-06-24 06:15:01,500 - pos_scan_step_size: 0.455508291721344 +2026-06-24 06:15:01,500 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:15:01,500 - probe_pmode_max: 6 +2026-06-24 06:15:01,500 - probe_pmode_init_pows: [0.02] +2026-06-24 06:15:01,500 - obj_omode_max: 1 +2026-06-24 06:15:01,500 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:15:01,500 - obj_Nlayer: 1 +2026-06-24 06:15:01,500 - obj_slice_thickness: 20.0 +2026-06-24 06:15:01,500 - simu_Npix: None +2026-06-24 06:15:01,500 - simu_match_mode: None +2026-06-24 06:15:01,500 - meas_permute: None +2026-06-24 06:15:01,500 - meas_reshape: [256, 128, 128] +2026-06-24 06:15:01,500 - meas_flipT: [0, 0, 0] +2026-06-24 06:15:01,500 - meas_crop: None +2026-06-24 06:15:01,500 - meas_pad: None +2026-06-24 06:15:01,500 - meas_resample: None +2026-06-24 06:15:01,500 - meas_add_source_size: None +2026-06-24 06:15:01,500 - meas_add_detector_blur: None +2026-06-24 06:15:01,500 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:15:01,500 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:15:01,500 - meas_add_poisson_noise: None +2026-06-24 06:15:01,500 - meas_export: None +2026-06-24 06:15:01,500 - probe_permute: None +2026-06-24 06:15:01,500 - probe_z_shift: None +2026-06-24 06:15:01,500 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:15:01,500 - pos_scan_flipT: None +2026-06-24 06:15:01,500 - pos_scan_affine: None +2026-06-24 06:15:01,500 - pos_scan_rand_std: 0.15 +2026-06-24 06:15:01,500 - obj_z_crop: None +2026-06-24 06:15:01,501 - obj_z_pad: None +2026-06-24 06:15:01,501 - obj_z_resample: None +2026-06-24 06:15:01,501 - meas_source: file +2026-06-24 06:15:01,501 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000034_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:15:01,501 - probe_source: simu +2026-06-24 06:15:01,501 - probe_params: None +2026-06-24 06:15:01,501 - pos_source: simu +2026-06-24 06:15:01,501 - pos_params: None +2026-06-24 06:15:01,501 - obj_source: simu +2026-06-24 06:15:01,501 - obj_params: None +2026-06-24 06:15:01,501 - tilt_source: simu +2026-06-24 06:15:01,501 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:15:01,501 - +2026-06-24 06:15:01,501 - ### Initializing cache ### +2026-06-24 06:15:01,501 - use_cached_obj = False +2026-06-24 06:15:01,501 - use_cached_probe = False +2026-06-24 06:15:01,501 - use_cached_pos = False +2026-06-24 06:15:01,501 - +2026-06-24 06:15:01,501 - ### Initializing measurements ### +2026-06-24 06:15:01,501 - Loading measurements from source = 'file' +2026-06-24 06:15:01,501 - Detected measurement file type = '.h5' +2026-06-24 06:15:01,581 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:15:01,582 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:15:01,583 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0070) +2026-06-24 06:15:01,583 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:15:01,583 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:15:01,585 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:15:01,585 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:15:01,586 - Normalizing by max of the 2D mean pattern intensity: 0.0048970575 +2026-06-24 06:15:01,586 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:15:01,588 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0123, 1.4347) +2026-06-24 06:15:01,588 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:15:01,589 - Pattern total int. statistics (min, mean, max) = (201.2890, 202.2790, 203.2285), with min/max = 99.0% +2026-06-24 06:15:01,591 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0123, 1.4347) +2026-06-24 06:15:01,591 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:15:01,591 - +2026-06-24 06:15:01,591 - ### Setting up calibration ### +2026-06-24 06:15:01,591 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:15:01,591 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:15:01,591 - Radius of fitted bright field disk (RBF) = 7.23 px with meas_Npix = 128 +2026-06-24 06:15:01,591 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1129 +2026-06-24 06:15:01,591 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:15:01,591 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:15:01,813 - Initial guess: center=(63.64, 63.65), radius=7.23, Gaussian blur std=0.50 +2026-06-24 06:15:01,825 - Final fit: center=(63.64, 63.65), radius=7.23, Gaussian blur std=0.64 +2026-06-24 06:15:01,825 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 7.35 px with Npix = 128 +2026-06-24 06:15:01,826 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:15:01,826 - +2026-06-24 06:15:01,826 - ### Setting init_variables dict ### +2026-06-24 06:15:01,826 - Derived values given input init_params: +2026-06-24 06:15:01,826 - kv = 60.0 kV +2026-06-24 06:15:01,826 - wavelength = 0.0487 Ang +2026-06-24 06:15:01,826 - conv_angle = 13.967053413391113 mrad +2026-06-24 06:15:01,826 - Npix = 128 px +2026-06-24 06:15:01,826 - dk = 0.0391 Ang^-1 +2026-06-24 06:15:01,826 - kMax = 2.5000 Ang^-1 +2026-06-24 06:15:01,826 - da = 1.9008 mrad +2026-06-24 06:15:01,826 - angleMax = 121.6515 mrad +2026-06-24 06:15:01,826 - RBF = 7.3480 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:15:01,826 - n_alpha = 8.7099 (# conv_angle) +2026-06-24 06:15:01,826 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:15:01,826 - Rayleigh-limited resolution = 2.1252 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:15:01,826 - Real space probe extent = 25.6000 Ang +2026-06-24 06:15:01,826 - +2026-06-24 06:15:01,826 - ### Initializing probe ### +2026-06-24 06:15:01,826 - Loading probe from source = 'simu' +2026-06-24 06:15:01,826 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:15:01,826 - Start simulating STEM probe +2026-06-24 06:15:01,826 - kv = 60.0 kV +2026-06-24 06:15:01,826 - wavelength = 0.0487 Ang +2026-06-24 06:15:01,827 - conv_angle = 13.967053413391113 mrad +2026-06-24 06:15:01,827 - Npix = 128 px +2026-06-24 06:15:01,827 - dk = 0.0391 Ang^-1 +2026-06-24 06:15:01,827 - kMax = 2.5000 Ang^-1 +2026-06-24 06:15:01,827 - alpha_max = 121.6515 mrad +2026-06-24 06:15:01,827 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:15:01,827 - Rayleigh-limited resolution = 2.1252 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:15:01,827 - Real space probe extent = 25.6000 Ang +2026-06-24 06:15:01,827 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:15:01,827 - ------------------------------------------------------------------------------------- +2026-06-24 06:15:01,827 - C1,0 C1 -316.9210 - Defocus (C10 = -df) +2026-06-24 06:15:01,827 - C1,2 A1 -0.9320 154.30 2-fold astigmatism +2026-06-24 06:15:01,827 - C2,1 3*B2 -960.0990 74.18 Axial coma +2026-06-24 06:15:01,827 - C2,3 A2 102.0630 341.87 3-fold astigmatism +2026-06-24 06:15:01,827 - C3,0 C3 -186131.1410 - Spherical aberration +2026-06-24 06:15:01,827 - C3,2 4*S3 -10914.9680 188.34 Axial star aberration +2026-06-24 06:15:01,827 - C3,4 A3 -7417.7610 266.42 4-fold astigmatism +2026-06-24 06:15:01,827 - C4,1 4*B4 364542.2810 54.42 Axial coma(4th) +2026-06-24 06:15:01,827 - C4,3 4*D4 426279.0000 209.58 3-lobe aberration +2026-06-24 06:15:01,827 - C4,5 A4 -159263.8440 316.34 5-fold astigmatism +2026-06-24 06:15:01,827 - C5,0 C5 -379219776.0000 - Spherical aberration (5th) +2026-06-24 06:15:01,827 - C5,2 6*S5 -12873377.0000 75.94 Axial star aberration(5th) +2026-06-24 06:15:01,827 - C5,4 6*R5 -5240924.0000 100.53 4-lobe aberration +2026-06-24 06:15:01,827 - C5,6 A5 11050132.0000 1.20 6-fold astigmatism +2026-06-24 06:15:01,830 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:15:01,830 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:15:01,830 - Creating 5 new probe modes from the major mode +2026-06-24 06:15:01,830 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:15:02,049 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:15:02,050 - Orthogonalizing 6 pmodes +2026-06-24 06:15:02,052 - Sorting 6 pmodes by their intensities +2026-06-24 06:15:02,053 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:15:02,053 - sum(|probe_data|**2) = 202.28, while meas_total_ints (min, mean, max) = (201.2890, 202.2790, 203.2285) +2026-06-24 06:15:02,053 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:15:02,053 - +2026-06-24 06:15:02,053 - ### Initializing probe positions ### +2026-06-24 06:15:02,053 - Loading probe positions from source = 'simu' +2026-06-24 06:15:02,053 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:15:02,053 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4555, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:15:02,054 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:15:02,056 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:15:02,056 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 50]) +2026-06-24 06:15:02,056 - crop_pos extent (Ang) = [6.8 7. ] +2026-06-24 06:15:02,056 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:15:02,056 - +2026-06-24 06:15:02,056 - ### Initializing object ### +2026-06-24 06:15:02,056 - Loading object from source = 'simu' +2026-06-24 06:15:02,056 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:15:02,058 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:15:02,058 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 195, 195) +2026-06-24 06:15:02,058 - object extent (Z, Y, X) (Ang) = [20. 39. 39.] +2026-06-24 06:15:02,058 - +2026-06-24 06:15:02,058 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:15:02,058 - omode_occu (omode) = float32, (1,) +2026-06-24 06:15:02,058 - +2026-06-24 06:15:02,058 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:15:02,058 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 06:15:02,059 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:15:02,059 - +2026-06-24 06:15:02,059 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:15:02,059 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:15:02,059 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:15:02,059 - +2026-06-24 06:15:02,059 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:15:02,059 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:15:02,059 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:15:02,059 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:15:02,059 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:15:02,059 - crop positions (yx_min=[16 15], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (195, 195). +2026-06-24 06:15:02,059 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:15:02,059 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:15:02,059 - +2026-06-24 06:15:02,059 - ### Collecting reconstruction provenance ### +2026-06-24 06:15:02,059 - Reconstruction provenance is collected and initialized. +2026-06-24 06:15:02,060 - +2026-06-24 06:15:02,060 - ### Initializing loss function ### +2026-06-24 06:15:02,060 - Active loss types: +2026-06-24 06:15:02,060 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:15:02,060 - +2026-06-24 06:15:02,060 - ### Initializing constraint function ### +2026-06-24 06:15:02,060 - Active constraint types: +2026-06-24 06:15:02,060 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:15:02,060 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:15:02,060 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:15:02,060 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:15:02,060 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:15:02,060 - +2026-06-24 06:15:02,060 - ### Done initializing PtyRADSolver ### +2026-06-24 06:15:02,060 - +2026-06-24 06:15:02,187 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:15:02,187 - +2026-06-24 06:15:02,187 - ### Initializing PtychoModel model ### +2026-06-24 06:15:02,259 - ### PtychoModel optimizable variables ### +2026-06-24 06:15:02,259 - obja : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:02,259 - objp : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:02,259 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:15:02,259 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:15:02,259 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:15:02,259 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:02,259 - +2026-06-24 06:15:02,259 - ### Optimizable variables statitsics ### +2026-06-24 06:15:02,259 - Total measurement values : 4,194,304 +2026-06-24 06:15:02,259 - Total optimizing variables: 273,170 +2026-06-24 06:15:02,259 - Overdetermined ratio : 15.35 +2026-06-24 06:15:02,259 - +2026-06-24 06:15:02,259 - ### Model behavior ### +2026-06-24 06:15:02,259 - Tilt propagator : False +2026-06-24 06:15:02,259 - Change slice thickness : False +2026-06-24 06:15:02,259 - Detector blur : False +2026-06-24 06:15:02,259 - Preload data : True +2026-06-24 06:15:02,259 - On-the-fly meas padding : False +2026-06-24 06:15:02,259 - On-the-fly meas resample : False +2026-06-24 06:15:02,259 - On-the-fly simu match mode: None +2026-06-24 06:15:02,259 - +2026-06-24 06:15:02,301 - ### Done initializing PtychoModel model ### +2026-06-24 06:15:02,301 - +2026-06-24 06:15:02,301 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:15:02,301 - +2026-06-24 06:15:02,301 - ### Generating indices, batches, and output_path ### +2026-06-24 06:15:02,303 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:15:02,303 - Selecting indices with the 'full' mode +2026-06-24 06:15:02,764 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:15:02,839 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:15:02,839 - Original recon_dir_affixes = ['default'] +2026-06-24 06:15:02,839 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:15:02,845 - Path corrected for compatibility: +2026-06-24 06:15:02,845 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi32_188_C34_-7.42e+03_phi34_266_C41_3.65e+05_phi41_54.4_C43_4.26e+05_phi43_210_C45_-1.59e+05_phi45_316_C50_-3.79e+08_C52_-1.29e+07_phi52_75.9_C54_-5.24e+06_phi54_101_C56_1.11e+07_phi56_1.2 +2026-06-24 06:15:02,845 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2 +2026-06-24 06:15:02,846 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2' is generated! +2026-06-24 06:15:02,998 - +2026-06-24 06:15:02,999 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/20260624_061502_ptyrad_log.txt ### +2026-06-24 06:15:02,999 - +2026-06-24 06:15:03,001 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:15:03,001 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:15:03,001 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:15:04,222 - Iter: 1, Total Loss: 1.2200, loss_single: 1.2200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.442 sec +2026-06-24 06:15:04,259 - Iter: 2, Total Loss: 1.1716, loss_single: 1.1716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:15:04,295 - Iter: 3, Total Loss: 1.1281, loss_single: 1.1281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,331 - Iter: 4, Total Loss: 1.0994, loss_single: 1.0994, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:04,366 - Iter: 5, Total Loss: 1.0761, loss_single: 1.0761, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,402 - Iter: 6, Total Loss: 1.0450, loss_single: 1.0450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,437 - Iter: 7, Total Loss: 1.0112, loss_single: 1.0112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,473 - Iter: 8, Total Loss: 0.9784, loss_single: 0.9784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,508 - Iter: 9, Total Loss: 0.9477, loss_single: 0.9477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,543 - Iter: 10, Total Loss: 0.9196, loss_single: 0.9196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,579 - Iter: 11, Total Loss: 0.8890, loss_single: 0.8890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,614 - Iter: 12, Total Loss: 0.8540, loss_single: 0.8540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,650 - Iter: 13, Total Loss: 0.8263, loss_single: 0.8263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,685 - Iter: 14, Total Loss: 0.8004, loss_single: 0.8004, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,721 - Iter: 15, Total Loss: 0.7707, loss_single: 0.7707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,756 - Iter: 16, Total Loss: 0.7404, loss_single: 0.7404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,791 - Iter: 17, Total Loss: 0.7083, loss_single: 0.7083, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,827 - Iter: 18, Total Loss: 0.6759, loss_single: 0.6759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,862 - Iter: 19, Total Loss: 0.6421, loss_single: 0.6421, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,897 - Iter: 20, Total Loss: 0.6086, loss_single: 0.6086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,932 - Iter: 21, Total Loss: 0.5748, loss_single: 0.5748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:04,968 - Iter: 22, Total Loss: 0.5396, loss_single: 0.5396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,003 - Iter: 23, Total Loss: 0.5102, loss_single: 0.5102, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,042 - Iter: 24, Total Loss: 0.4825, loss_single: 0.4825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:15:05,077 - Iter: 25, Total Loss: 0.4596, loss_single: 0.4596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,113 - Iter: 26, Total Loss: 0.4464, loss_single: 0.4464, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,148 - Iter: 27, Total Loss: 0.4326, loss_single: 0.4326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,184 - Iter: 28, Total Loss: 0.4155, loss_single: 0.4155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,219 - Iter: 29, Total Loss: 0.3992, loss_single: 0.3992, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:05,253 - Iter: 30, Total Loss: 0.3885, loss_single: 0.3885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:05,289 - Iter: 31, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,324 - Iter: 32, Total Loss: 0.3693, loss_single: 0.3693, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:05,359 - Iter: 33, Total Loss: 0.3625, loss_single: 0.3625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,394 - Iter: 34, Total Loss: 0.3552, loss_single: 0.3552, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,430 - Iter: 35, Total Loss: 0.3474, loss_single: 0.3474, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,465 - Iter: 36, Total Loss: 0.3408, loss_single: 0.3408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,500 - Iter: 37, Total Loss: 0.3353, loss_single: 0.3353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,535 - Iter: 38, Total Loss: 0.3303, loss_single: 0.3303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,571 - Iter: 39, Total Loss: 0.3276, loss_single: 0.3276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,606 - Iter: 40, Total Loss: 0.3257, loss_single: 0.3257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,643 - Iter: 41, Total Loss: 0.3233, loss_single: 0.3233, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,678 - Iter: 42, Total Loss: 0.3219, loss_single: 0.3219, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,714 - Iter: 43, Total Loss: 0.3209, loss_single: 0.3209, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,749 - Iter: 44, Total Loss: 0.3194, loss_single: 0.3194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,784 - Iter: 45, Total Loss: 0.3181, loss_single: 0.3181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,820 - Iter: 46, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,855 - Iter: 47, Total Loss: 0.3159, loss_single: 0.3159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,890 - Iter: 48, Total Loss: 0.3151, loss_single: 0.3151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,925 - Iter: 49, Total Loss: 0.3145, loss_single: 0.3145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,961 - Iter: 50, Total Loss: 0.3139, loss_single: 0.3139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:05,996 - Iter: 51, Total Loss: 0.3133, loss_single: 0.3133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,031 - Iter: 52, Total Loss: 0.3129, loss_single: 0.3129, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,067 - Iter: 53, Total Loss: 0.3125, loss_single: 0.3125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,102 - Iter: 54, Total Loss: 0.3121, loss_single: 0.3121, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,137 - Iter: 55, Total Loss: 0.3118, loss_single: 0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,173 - Iter: 56, Total Loss: 0.3115, loss_single: 0.3115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,208 - Iter: 57, Total Loss: 0.3112, loss_single: 0.3112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,243 - Iter: 58, Total Loss: 0.3109, loss_single: 0.3109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,278 - Iter: 59, Total Loss: 0.3106, loss_single: 0.3106, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,313 - Iter: 60, Total Loss: 0.3104, loss_single: 0.3104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,349 - Iter: 61, Total Loss: 0.3101, loss_single: 0.3101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,384 - Iter: 62, Total Loss: 0.3099, loss_single: 0.3099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,419 - Iter: 63, Total Loss: 0.3096, loss_single: 0.3096, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,454 - Iter: 64, Total Loss: 0.3094, loss_single: 0.3094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,490 - Iter: 65, Total Loss: 0.3092, loss_single: 0.3092, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,525 - Iter: 66, Total Loss: 0.3090, loss_single: 0.3090, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,560 - Iter: 67, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,595 - Iter: 68, Total Loss: 0.3086, loss_single: 0.3086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,630 - Iter: 69, Total Loss: 0.3084, loss_single: 0.3084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,666 - Iter: 70, Total Loss: 0.3082, loss_single: 0.3082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,701 - Iter: 71, Total Loss: 0.3080, loss_single: 0.3080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,736 - Iter: 72, Total Loss: 0.3079, loss_single: 0.3079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,772 - Iter: 73, Total Loss: 0.3077, loss_single: 0.3077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,807 - Iter: 74, Total Loss: 0.3075, loss_single: 0.3075, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,842 - Iter: 75, Total Loss: 0.3073, loss_single: 0.3073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,877 - Iter: 76, Total Loss: 0.3071, loss_single: 0.3071, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:06,912 - Iter: 77, Total Loss: 0.3069, loss_single: 0.3069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,948 - Iter: 78, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:06,983 - Iter: 79, Total Loss: 0.3065, loss_single: 0.3065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,018 - Iter: 80, Total Loss: 0.3064, loss_single: 0.3064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,053 - Iter: 81, Total Loss: 0.3062, loss_single: 0.3062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:07,088 - Iter: 82, Total Loss: 0.3060, loss_single: 0.3060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,123 - Iter: 83, Total Loss: 0.3058, loss_single: 0.3058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,158 - Iter: 84, Total Loss: 0.3057, loss_single: 0.3057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,194 - Iter: 85, Total Loss: 0.3055, loss_single: 0.3055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,229 - Iter: 86, Total Loss: 0.3054, loss_single: 0.3054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,264 - Iter: 87, Total Loss: 0.3052, loss_single: 0.3052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,300 - Iter: 88, Total Loss: 0.3051, loss_single: 0.3051, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,335 - Iter: 89, Total Loss: 0.3050, loss_single: 0.3050, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:15:07,370 - Iter: 90, Total Loss: 0.3048, loss_single: 0.3048, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,405 - Iter: 91, Total Loss: 0.3046, loss_single: 0.3046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,442 - Iter: 92, Total Loss: 0.3045, loss_single: 0.3045, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:15:07,478 - Iter: 93, Total Loss: 0.3043, loss_single: 0.3043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,513 - Iter: 94, Total Loss: 0.3042, loss_single: 0.3042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,549 - Iter: 95, Total Loss: 0.3040, loss_single: 0.3040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,584 - Iter: 96, Total Loss: 0.3039, loss_single: 0.3039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,619 - Iter: 97, Total Loss: 0.3037, loss_single: 0.3037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,654 - Iter: 98, Total Loss: 0.3035, loss_single: 0.3035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,689 - Iter: 99, Total Loss: 0.3033, loss_single: 0.3033, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,724 - Iter: 100, Total Loss: 0.3032, loss_single: 0.3032, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:07,835 - Saving summary figures for iter 100 +2026-06-24 06:15:11,515 - ### Finished 100 iterations, averaged iter_t = 0.039 with std = 0.040 ### +2026-06-24 06:15:11,516 - +2026-06-24 06:15:11,516 - ### The PtyRADSolver is finished in 9.329 sec ### +2026-06-24 06:15:11,516 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..85661d0466e74e584952cd35a739ce4da13ae954 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/simulation_data4__sample_000034.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/simulation_data4__sample_000034.yaml new file mode 100644 index 0000000000000000000000000000000000000000..28061894f281c98bfed7ef84e4d27916358883cb --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034/c30_small__simulation_data4__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-317_C12_-0.932_phi12_154_C21_-960_phi21_74.2_C23_102_phi23_342_C30_-1.86e+05_C32_-1.09e+04_phi3.2/simulation_data4__sample_000034.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 13.967053413391113 + probe_aberrations: + C10: -316.9207458496094 + C12: -0.9317978620529175 + C21: -960.0990600585938 + C23: 102.0626220703125 + C30: -186131.140625 + C32: -10914.9677734375 + C34: -7417.76123046875 + C41: 364542.28125 + C43: 426279.0 + C45: -159263.84375 + C50: -379219776.0 + C52: -12873377.0 + C54: -5240924.0 + C56: 11050132.0 + phi12: 154.30059863408295 + phi21: 74.17773268836022 + phi23: 341.86596705455554 + phi32: 188.33916055154333 + phi34: 266.41991604864813 + phi41: 54.425003193601775 + phi43: 209.5825241911437 + phi45: 316.33600401261185 + phi52: 75.94342538126773 + phi54: 100.53049446866952 + phi56: 1.20007512278523 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.455508291721344 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000034_measurement.h5 + key: measurement + random_seed: 20262010 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000034 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000034 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/20260624_061546_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/20260624_061546_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b3f538250714629cd0b7b11792064471278bbd39 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/20260624_061546_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:15:45,217 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:15:45,217 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:15:45,217 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:15:45,217 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:15:45,217 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:15:45,217 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:15:45,217 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:15:45,217 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:15:45,217 - +2026-06-24 06:15:45,325 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:15:45,325 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:15:45,325 - Accelerator.num_process = 1 +2026-06-24 06:15:45,325 - Accelerator.mixed_precision = no +2026-06-24 06:15:45,336 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:15:45,336 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:15:45,336 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:15:45,336 - +2026-06-24 06:15:45,336 - ### System information ### +2026-06-24 06:15:45,336 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:15:45,336 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:15:45,336 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:15:45,336 - Machine: x86_64 +2026-06-24 06:15:45,336 - Processor: x86_64 +2026-06-24 06:15:45,336 - Available CPU cores: 8 +2026-06-24 06:15:45,336 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:15:45,336 - +2026-06-24 06:15:45,336 - ### GPU information ### +2026-06-24 06:15:45,336 - CUDA Available: True +2026-06-24 06:15:45,336 - CUDA Version: 13.0 +2026-06-24 06:15:45,337 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:15:45,337 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:15:45,337 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:15:45,337 - In addition, Triton does not directly support Windows. +2026-06-24 06:15:45,337 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:15:45,352 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:15:45,352 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:15:45,352 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:15:45,352 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:15:45,352 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:15:45,352 - +2026-06-24 06:15:45,352 - ### Python information ### +2026-06-24 06:15:45,354 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:15:45,354 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:15:45,354 - +2026-06-24 06:15:45,354 - ### Packages information ### +2026-06-24 06:15:45,355 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:15:45,356 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:15:45,356 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:15:45,357 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:15:45,357 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:15:45,357 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:15:45,357 - +2026-06-24 06:15:45,357 - ### Loading params file ### +2026-06-24 06:15:45,358 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000037.yaml +2026-06-24 06:15:45,364 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:15:45,365 - Success! Params file validated and defaults applied. +2026-06-24 06:15:45,365 - +2026-06-24 06:15:45,365 - ### Setting GPU Device ### +2026-06-24 06:15:45,365 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:15:45,365 - +2026-06-24 06:15:45,365 - Random seed: 20262013 provided by params file +2026-06-24 06:15:45,366 - ### Initializing Initializer ### +2026-06-24 06:15:45,366 - init_params are displayed below: +2026-06-24 06:15:45,366 - random_seed: 20262013 +2026-06-24 06:15:45,366 - probe_illum_type: electron +2026-06-24 06:15:45,366 - probe_kv: 80.0 +2026-06-24 06:15:45,366 - probe_conv_angle: 17.15309715270996 +2026-06-24 06:15:45,366 - probe_aberrations: {'C10': -223.338, 'C12': -0.047, 'phi12': 206.271, 'C21': 225.643, 'phi21': 12.912, 'C23': -287.068, 'phi23': 141.509, 'C30': -316932.25, 'C32': -6030.623, 'phi32': 150.007, 'C34': -5351.498, 'phi34': 26.054, 'C41': -397222.406, 'phi41': 122.432, 'C43': -260537.875, 'phi43': 334.646, 'C45': -415620.5, 'phi45': 119.3, 'C50': -379131392.0, 'C52': 7893658.0, 'phi52': 261.358, 'C54': -19939036.0, 'phi54': 315.502, 'C56': -6756708.0, 'phi56': 340.864} +2026-06-24 06:15:45,366 - beam_kev: None +2026-06-24 06:15:45,366 - probe_dRn: None +2026-06-24 06:15:45,366 - probe_Rn: None +2026-06-24 06:15:45,366 - probe_D_H: None +2026-06-24 06:15:45,366 - probe_D_FZP: None +2026-06-24 06:15:45,366 - probe_Ls: None +2026-06-24 06:15:45,366 - meas_Npix: 128 +2026-06-24 06:15:45,366 - pos_N_scans: 256 +2026-06-24 06:15:45,366 - pos_N_scan_slow: 16 +2026-06-24 06:15:45,366 - pos_N_scan_fast: 16 +2026-06-24 06:15:45,366 - pos_scan_step_size: 0.3598967492580414 +2026-06-24 06:15:45,366 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:15:45,366 - probe_pmode_max: 6 +2026-06-24 06:15:45,366 - probe_pmode_init_pows: [0.02] +2026-06-24 06:15:45,366 - obj_omode_max: 1 +2026-06-24 06:15:45,366 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:15:45,366 - obj_Nlayer: 1 +2026-06-24 06:15:45,366 - obj_slice_thickness: 20.0 +2026-06-24 06:15:45,366 - simu_Npix: None +2026-06-24 06:15:45,366 - simu_match_mode: None +2026-06-24 06:15:45,366 - meas_permute: None +2026-06-24 06:15:45,366 - meas_reshape: [256, 128, 128] +2026-06-24 06:15:45,366 - meas_flipT: [0, 0, 0] +2026-06-24 06:15:45,366 - meas_crop: None +2026-06-24 06:15:45,366 - meas_pad: None +2026-06-24 06:15:45,367 - meas_resample: None +2026-06-24 06:15:45,367 - meas_add_source_size: None +2026-06-24 06:15:45,367 - meas_add_detector_blur: None +2026-06-24 06:15:45,367 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:15:45,367 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:15:45,367 - meas_add_poisson_noise: None +2026-06-24 06:15:45,367 - meas_export: None +2026-06-24 06:15:45,367 - probe_permute: None +2026-06-24 06:15:45,367 - probe_z_shift: None +2026-06-24 06:15:45,367 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:15:45,367 - pos_scan_flipT: None +2026-06-24 06:15:45,367 - pos_scan_affine: None +2026-06-24 06:15:45,367 - pos_scan_rand_std: 0.15 +2026-06-24 06:15:45,367 - obj_z_crop: None +2026-06-24 06:15:45,367 - obj_z_pad: None +2026-06-24 06:15:45,367 - obj_z_resample: None +2026-06-24 06:15:45,367 - meas_source: file +2026-06-24 06:15:45,367 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000037_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:15:45,367 - probe_source: simu +2026-06-24 06:15:45,367 - probe_params: None +2026-06-24 06:15:45,367 - pos_source: simu +2026-06-24 06:15:45,367 - pos_params: None +2026-06-24 06:15:45,367 - obj_source: simu +2026-06-24 06:15:45,367 - obj_params: None +2026-06-24 06:15:45,367 - tilt_source: simu +2026-06-24 06:15:45,367 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:15:45,367 - +2026-06-24 06:15:45,367 - ### Initializing cache ### +2026-06-24 06:15:45,367 - use_cached_obj = False +2026-06-24 06:15:45,367 - use_cached_probe = False +2026-06-24 06:15:45,367 - use_cached_pos = False +2026-06-24 06:15:45,367 - +2026-06-24 06:15:45,367 - ### Initializing measurements ### +2026-06-24 06:15:45,367 - Loading measurements from source = 'file' +2026-06-24 06:15:45,367 - Detected measurement file type = '.h5' +2026-06-24 06:15:45,444 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:15:45,444 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:15:45,446 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0038) +2026-06-24 06:15:45,446 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:15:45,446 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:15:45,447 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:15:45,447 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:15:45,448 - Normalizing by max of the 2D mean pattern intensity: 0.0022899215 +2026-06-24 06:15:45,448 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:15:45,450 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0264, 1.6761) +2026-06-24 06:15:45,450 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:15:45,451 - Pattern total int. statistics (min, mean, max) = (425.8210, 432.3114, 438.1408), with min/max = 97.2% +2026-06-24 06:15:45,453 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0264, 1.6761) +2026-06-24 06:15:45,453 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:15:45,454 - +2026-06-24 06:15:45,454 - ### Setting up calibration ### +2026-06-24 06:15:45,454 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:15:45,454 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:15:45,454 - Radius of fitted bright field disk (RBF) = 10.40 px with meas_Npix = 128 +2026-06-24 06:15:45,454 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1625 +2026-06-24 06:15:45,454 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:15:45,454 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:15:45,687 - Initial guess: center=(63.62, 63.64), radius=10.40, Gaussian blur std=0.50 +2026-06-24 06:15:45,700 - Final fit: center=(63.62, 63.64), radius=10.40, Gaussian blur std=0.61 +2026-06-24 06:15:45,700 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.52 px with Npix = 128 +2026-06-24 06:15:45,700 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:15:45,700 - +2026-06-24 06:15:45,700 - ### Setting init_variables dict ### +2026-06-24 06:15:45,700 - Derived values given input init_params: +2026-06-24 06:15:45,700 - kv = 80.0 kV +2026-06-24 06:15:45,700 - wavelength = 0.0418 Ang +2026-06-24 06:15:45,700 - conv_angle = 17.15309715270996 mrad +2026-06-24 06:15:45,700 - Npix = 128 px +2026-06-24 06:15:45,700 - dk = 0.0391 Ang^-1 +2026-06-24 06:15:45,700 - kMax = 2.5000 Ang^-1 +2026-06-24 06:15:45,700 - da = 1.6311 mrad +2026-06-24 06:15:45,700 - angleMax = 104.3929 mrad +2026-06-24 06:15:45,700 - RBF = 10.5160 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:15:45,700 - n_alpha = 6.0860 (# conv_angle) +2026-06-24 06:15:45,700 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:15:45,700 - Rayleigh-limited resolution = 1.4850 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:15:45,700 - Real space probe extent = 25.6000 Ang +2026-06-24 06:15:45,700 - +2026-06-24 06:15:45,700 - ### Initializing probe ### +2026-06-24 06:15:45,700 - Loading probe from source = 'simu' +2026-06-24 06:15:45,700 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:15:45,701 - Start simulating STEM probe +2026-06-24 06:15:45,701 - kv = 80.0 kV +2026-06-24 06:15:45,701 - wavelength = 0.0418 Ang +2026-06-24 06:15:45,701 - conv_angle = 17.15309715270996 mrad +2026-06-24 06:15:45,701 - Npix = 128 px +2026-06-24 06:15:45,701 - dk = 0.0391 Ang^-1 +2026-06-24 06:15:45,701 - kMax = 2.5000 Ang^-1 +2026-06-24 06:15:45,701 - alpha_max = 104.3929 mrad +2026-06-24 06:15:45,701 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:15:45,701 - Rayleigh-limited resolution = 1.4850 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:15:45,701 - Real space probe extent = 25.6000 Ang +2026-06-24 06:15:45,701 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:15:45,701 - ------------------------------------------------------------------------------------- +2026-06-24 06:15:45,701 - C1,0 C1 -223.3380 - Defocus (C10 = -df) +2026-06-24 06:15:45,701 - C1,2 A1 -0.0470 206.27 2-fold astigmatism +2026-06-24 06:15:45,701 - C2,1 3*B2 225.6430 12.91 Axial coma +2026-06-24 06:15:45,701 - C2,3 A2 -287.0680 141.51 3-fold astigmatism +2026-06-24 06:15:45,701 - C3,0 C3 -316932.2500 - Spherical aberration +2026-06-24 06:15:45,701 - C3,2 4*S3 -6030.6230 150.01 Axial star aberration +2026-06-24 06:15:45,701 - C3,4 A3 -5351.4980 26.05 4-fold astigmatism +2026-06-24 06:15:45,701 - C4,1 4*B4 -397222.4060 122.43 Axial coma(4th) +2026-06-24 06:15:45,701 - C4,3 4*D4 -260537.8750 334.65 3-lobe aberration +2026-06-24 06:15:45,701 - C4,5 A4 -415620.5000 119.30 5-fold astigmatism +2026-06-24 06:15:45,701 - C5,0 C5 -379131392.0000 - Spherical aberration (5th) +2026-06-24 06:15:45,701 - C5,2 6*S5 7893658.0000 261.36 Axial star aberration(5th) +2026-06-24 06:15:45,701 - C5,4 6*R5 -19939036.0000 315.50 4-lobe aberration +2026-06-24 06:15:45,701 - C5,6 A5 -6756708.0000 340.86 6-fold astigmatism +2026-06-24 06:15:45,705 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:15:45,705 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:15:45,705 - Creating 5 new probe modes from the major mode +2026-06-24 06:15:45,705 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:15:45,807 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:15:45,809 - Orthogonalizing 6 pmodes +2026-06-24 06:15:45,811 - Sorting 6 pmodes by their intensities +2026-06-24 06:15:45,811 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:15:45,812 - sum(|probe_data|**2) = 432.31, while meas_total_ints (min, mean, max) = (425.8210, 432.3114, 438.1408) +2026-06-24 06:15:45,812 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:15:45,812 - +2026-06-24 06:15:45,812 - ### Initializing probe positions ### +2026-06-24 06:15:45,812 - Loading probe positions from source = 'simu' +2026-06-24 06:15:45,812 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:15:45,812 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3599, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:15:45,813 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:15:45,815 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:15:45,815 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 42]) +2026-06-24 06:15:45,815 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:15:45,815 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:15:45,815 - +2026-06-24 06:15:45,815 - ### Initializing object ### +2026-06-24 06:15:45,815 - Loading object from source = 'simu' +2026-06-24 06:15:45,815 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:15:45,816 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:15:45,816 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 06:15:45,817 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 06:15:45,817 - +2026-06-24 06:15:45,817 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:15:45,817 - omode_occu (omode) = float32, (1,) +2026-06-24 06:15:45,817 - +2026-06-24 06:15:45,817 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:15:45,817 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:15:45,817 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:15:45,817 - +2026-06-24 06:15:45,817 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:15:45,818 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:15:45,818 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:15:45,818 - +2026-06-24 06:15:45,818 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:15:45,818 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:15:45,818 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:15:45,818 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:15:45,818 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:15:45,818 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 06:15:45,818 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:15:45,818 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:15:45,818 - +2026-06-24 06:15:45,818 - ### Collecting reconstruction provenance ### +2026-06-24 06:15:45,818 - Reconstruction provenance is collected and initialized. +2026-06-24 06:15:45,818 - +2026-06-24 06:15:45,818 - ### Initializing loss function ### +2026-06-24 06:15:45,818 - Active loss types: +2026-06-24 06:15:45,818 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:15:45,818 - +2026-06-24 06:15:45,818 - ### Initializing constraint function ### +2026-06-24 06:15:45,819 - Active constraint types: +2026-06-24 06:15:45,819 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:15:45,819 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:15:45,819 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:15:45,819 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:15:45,819 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:15:45,819 - +2026-06-24 06:15:45,819 - ### Done initializing PtyRADSolver ### +2026-06-24 06:15:45,819 - +2026-06-24 06:15:45,944 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:15:45,944 - +2026-06-24 06:15:45,944 - ### Initializing PtychoModel model ### +2026-06-24 06:15:46,015 - ### PtychoModel optimizable variables ### +2026-06-24 06:15:46,016 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:46,016 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:46,016 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:15:46,016 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:15:46,016 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:15:46,016 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:15:46,016 - +2026-06-24 06:15:46,016 - ### Optimizable variables statitsics ### +2026-06-24 06:15:46,016 - Total measurement values : 4,194,304 +2026-06-24 06:15:46,016 - Total optimizing variables: 267,058 +2026-06-24 06:15:46,016 - Overdetermined ratio : 15.71 +2026-06-24 06:15:46,016 - +2026-06-24 06:15:46,016 - ### Model behavior ### +2026-06-24 06:15:46,016 - Tilt propagator : False +2026-06-24 06:15:46,016 - Change slice thickness : False +2026-06-24 06:15:46,016 - Detector blur : False +2026-06-24 06:15:46,016 - Preload data : True +2026-06-24 06:15:46,016 - On-the-fly meas padding : False +2026-06-24 06:15:46,016 - On-the-fly meas resample : False +2026-06-24 06:15:46,016 - On-the-fly simu match mode: None +2026-06-24 06:15:46,016 - +2026-06-24 06:15:46,058 - ### Done initializing PtychoModel model ### +2026-06-24 06:15:46,058 - +2026-06-24 06:15:46,058 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:15:46,058 - +2026-06-24 06:15:46,058 - ### Generating indices, batches, and output_path ### +2026-06-24 06:15:46,059 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:15:46,059 - Selecting indices with the 'full' mode +2026-06-24 06:15:46,521 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:15:46,592 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:15:46,592 - Original recon_dir_affixes = ['default'] +2026-06-24 06:15:46,592 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:15:46,597 - Path corrected for compatibility: +2026-06-24 06:15:46,597 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32_-6.03e+03_phi32_150_C34_-5.35e+03_phi34_26.1_C41_-3.97e+05_phi41_122_C43_-2.61e+05_phi43_335_C45_-4.16e+05_phi45_119_C50_-3.79e+08_C52_7.89e+06_phi52_261_C54_-1.99e+07_phi54_316_C56_-6.76e+06_phi56_341 +2026-06-24 06:15:46,597 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341 +2026-06-24 06:15:46,599 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341' is generated! +2026-06-24 06:15:46,750 - +2026-06-24 06:15:46,751 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/20260624_061546_ptyrad_log.txt ### +2026-06-24 06:15:46,751 - +2026-06-24 06:15:46,752 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:15:46,752 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:15:46,752 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:15:47,938 - Iter: 1, Total Loss: 1.2572, loss_single: 1.2572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:15:47,975 - Iter: 2, Total Loss: 1.2303, loss_single: 1.2303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:48,011 - Iter: 3, Total Loss: 1.2055, loss_single: 1.2055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,061 - Iter: 4, Total Loss: 1.1794, loss_single: 1.1794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,096 - Iter: 5, Total Loss: 1.1574, loss_single: 1.1574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,131 - Iter: 6, Total Loss: 1.1341, loss_single: 1.1341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,167 - Iter: 7, Total Loss: 1.1111, loss_single: 1.1111, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,202 - Iter: 8, Total Loss: 1.0939, loss_single: 1.0939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,238 - Iter: 9, Total Loss: 1.0770, loss_single: 1.0770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,273 - Iter: 10, Total Loss: 1.0604, loss_single: 1.0604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,309 - Iter: 11, Total Loss: 1.0438, loss_single: 1.0438, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,345 - Iter: 12, Total Loss: 1.0251, loss_single: 1.0251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:48,381 - Iter: 13, Total Loss: 1.0072, loss_single: 1.0072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,417 - Iter: 14, Total Loss: 0.9899, loss_single: 0.9899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,452 - Iter: 15, Total Loss: 0.9705, loss_single: 0.9705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,488 - Iter: 16, Total Loss: 0.9523, loss_single: 0.9523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,523 - Iter: 17, Total Loss: 0.9354, loss_single: 0.9354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,559 - Iter: 18, Total Loss: 0.9178, loss_single: 0.9178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,595 - Iter: 19, Total Loss: 0.9011, loss_single: 0.9011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,630 - Iter: 20, Total Loss: 0.8840, loss_single: 0.8840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,666 - Iter: 21, Total Loss: 0.8664, loss_single: 0.8664, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,701 - Iter: 22, Total Loss: 0.8501, loss_single: 0.8501, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,737 - Iter: 23, Total Loss: 0.8346, loss_single: 0.8346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,772 - Iter: 24, Total Loss: 0.8173, loss_single: 0.8173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,807 - Iter: 25, Total Loss: 0.8010, loss_single: 0.8010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,843 - Iter: 26, Total Loss: 0.7858, loss_single: 0.7858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:48,879 - Iter: 27, Total Loss: 0.7719, loss_single: 0.7719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,914 - Iter: 28, Total Loss: 0.7587, loss_single: 0.7587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,950 - Iter: 29, Total Loss: 0.7448, loss_single: 0.7448, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:48,985 - Iter: 30, Total Loss: 0.7319, loss_single: 0.7319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,020 - Iter: 31, Total Loss: 0.7179, loss_single: 0.7179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,056 - Iter: 32, Total Loss: 0.7053, loss_single: 0.7053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,091 - Iter: 33, Total Loss: 0.6944, loss_single: 0.6944, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,127 - Iter: 34, Total Loss: 0.6837, loss_single: 0.6837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,162 - Iter: 35, Total Loss: 0.6741, loss_single: 0.6741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,198 - Iter: 36, Total Loss: 0.6633, loss_single: 0.6633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,234 - Iter: 37, Total Loss: 0.6528, loss_single: 0.6528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,270 - Iter: 38, Total Loss: 0.6436, loss_single: 0.6436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,305 - Iter: 39, Total Loss: 0.6345, loss_single: 0.6345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,340 - Iter: 40, Total Loss: 0.6249, loss_single: 0.6249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,378 - Iter: 41, Total Loss: 0.6163, loss_single: 0.6163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,414 - Iter: 42, Total Loss: 0.6082, loss_single: 0.6082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:49,450 - Iter: 43, Total Loss: 0.6011, loss_single: 0.6011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,485 - Iter: 44, Total Loss: 0.5941, loss_single: 0.5941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,521 - Iter: 45, Total Loss: 0.5868, loss_single: 0.5868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,556 - Iter: 46, Total Loss: 0.5798, loss_single: 0.5798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,591 - Iter: 47, Total Loss: 0.5732, loss_single: 0.5732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,627 - Iter: 48, Total Loss: 0.5669, loss_single: 0.5669, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,662 - Iter: 49, Total Loss: 0.5611, loss_single: 0.5611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,698 - Iter: 50, Total Loss: 0.5572, loss_single: 0.5572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,733 - Iter: 51, Total Loss: 0.5541, loss_single: 0.5541, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,768 - Iter: 52, Total Loss: 0.5511, loss_single: 0.5511, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,803 - Iter: 53, Total Loss: 0.5481, loss_single: 0.5481, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,838 - Iter: 54, Total Loss: 0.5440, loss_single: 0.5440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,873 - Iter: 55, Total Loss: 0.5403, loss_single: 0.5403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,909 - Iter: 56, Total Loss: 0.5374, loss_single: 0.5374, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,944 - Iter: 57, Total Loss: 0.5341, loss_single: 0.5341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:49,979 - Iter: 58, Total Loss: 0.5310, loss_single: 0.5310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:50,015 - Iter: 59, Total Loss: 0.5280, loss_single: 0.5280, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:50,050 - Iter: 60, Total Loss: 0.5255, loss_single: 0.5255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:50,086 - Iter: 61, Total Loss: 0.5232, loss_single: 0.5232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:50,121 - Iter: 62, Total Loss: 0.5215, loss_single: 0.5215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:15:50,157 - Iter: 63, Total Loss: 0.5198, loss_single: 0.5198, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:15:50,192 - Iter: 64, 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/simulation_data4__sample_000037.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/simulation_data4__sample_000037.yaml new file mode 100644 index 0000000000000000000000000000000000000000..13a86dc56ece9fd51ffd51182a9d6b49cc0bb470 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037/c30_small__simulation_data4__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-223_C12_-0.047_phi12_206_C21_226_phi21_12.9_C23_-287_phi23_142_C30_-3.17e+05_C32.76e+06_phi56_341/simulation_data4__sample_000037.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 17.15309715270996 + probe_aberrations: + C10: -223.3376922607422 + C12: -0.04726111888885498 + C21: 225.64251708984375 + C23: -287.06787109375 + C30: -316932.25 + C32: -6030.62255859375 + C34: -5351.49755859375 + C41: -397222.40625 + C43: -260537.875 + C45: -415620.5 + C50: -379131392.0 + C52: 7893658.0 + C54: -19939036.0 + C56: -6756708.0 + phi12: 206.2712075003865 + phi21: 12.91200475795096 + phi23: 141.50873348853793 + phi32: 150.0067182500844 + phi34: 26.05384708902014 + phi41: 122.43213808009739 + phi43: 334.64634781882535 + phi45: 119.29963574181112 + phi52: 261.35849998685853 + phi54: 315.5022838017634 + phi56: 340.8637597372612 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3598967492580414 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000037_measurement.h5 + key: measurement + random_seed: 20262013 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000037 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_.65e+07_phi56_298/20260624_061616_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:16:14,942 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:16:14,942 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:16:14,942 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:16:14,942 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:16:14,942 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:16:14,942 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:16:14,942 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:16:14,942 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:16:14,942 - +2026-06-24 06:16:15,064 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:16:15,064 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:16:15,064 - Accelerator.num_process = 1 +2026-06-24 06:16:15,064 - Accelerator.mixed_precision = no +2026-06-24 06:16:15,075 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:16:15,075 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:16:15,075 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:16:15,075 - +2026-06-24 06:16:15,075 - ### System information ### +2026-06-24 06:16:15,075 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:16:15,075 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:16:15,075 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:16:15,075 - Machine: x86_64 +2026-06-24 06:16:15,075 - Processor: x86_64 +2026-06-24 06:16:15,075 - Available CPU cores: 8 +2026-06-24 06:16:15,075 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:16:15,075 - +2026-06-24 06:16:15,075 - ### GPU information ### +2026-06-24 06:16:15,075 - CUDA Available: True +2026-06-24 06:16:15,075 - CUDA Version: 13.0 +2026-06-24 06:16:15,076 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:16:15,076 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:16:15,076 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:16:15,076 - In addition, Triton does not directly support Windows. +2026-06-24 06:16:15,076 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:16:15,092 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:16:15,092 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:16:15,092 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:16:15,092 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:16:15,092 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:16:15,092 - +2026-06-24 06:16:15,092 - ### Python information ### +2026-06-24 06:16:15,094 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:16:15,094 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:16:15,094 - +2026-06-24 06:16:15,094 - ### Packages information ### +2026-06-24 06:16:15,094 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:16:15,095 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:16:15,096 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:16:15,096 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:16:15,097 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:16:15,097 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:16:15,097 - +2026-06-24 06:16:15,097 - ### Loading params file ### +2026-06-24 06:16:15,097 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000039.yaml +2026-06-24 06:16:15,104 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:16:15,105 - Success! Params file validated and defaults applied. +2026-06-24 06:16:15,105 - +2026-06-24 06:16:15,105 - ### Setting GPU Device ### +2026-06-24 06:16:15,105 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:16:15,105 - +2026-06-24 06:16:15,105 - Random seed: 20262015 provided by params file +2026-06-24 06:16:15,105 - ### Initializing Initializer ### +2026-06-24 06:16:15,105 - init_params are displayed below: +2026-06-24 06:16:15,105 - random_seed: 20262015 +2026-06-24 06:16:15,105 - probe_illum_type: electron +2026-06-24 06:16:15,105 - probe_kv: 80.0 +2026-06-24 06:16:15,105 - probe_conv_angle: 12.88296890258789 +2026-06-24 06:16:15,105 - probe_aberrations: {'C10': -265.636, 'C12': -38.608, 'phi12': 130.639, 'C21': -18.167, 'phi21': 65.821, 'C23': -822.88, 'phi23': 75.04, 'C30': 3530909.25, 'C32': 9259.623, 'phi32': 54.451, 'C34': 9392.43, 'phi34': 8.132, 'C41': -150262.391, 'phi41': 18.374, 'C43': 341837.156, 'phi43': 293.654, 'C45': -4149.008, 'phi45': 152.646, 'C50': 329600800.0, 'C52': -10346745.0, 'phi52': 9.251, 'C54': 15335027.0, 'phi54': 190.614, 'C56': 16533163.0, 'phi56': 297.783} +2026-06-24 06:16:15,105 - beam_kev: None +2026-06-24 06:16:15,105 - probe_dRn: None +2026-06-24 06:16:15,106 - probe_Rn: None +2026-06-24 06:16:15,106 - probe_D_H: None +2026-06-24 06:16:15,106 - probe_D_FZP: None +2026-06-24 06:16:15,106 - probe_Ls: None +2026-06-24 06:16:15,106 - meas_Npix: 128 +2026-06-24 06:16:15,106 - pos_N_scans: 256 +2026-06-24 06:16:15,106 - pos_N_scan_slow: 16 +2026-06-24 06:16:15,106 - pos_N_scan_fast: 16 +2026-06-24 06:16:15,106 - pos_scan_step_size: 0.5063364505767822 +2026-06-24 06:16:15,106 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:16:15,106 - probe_pmode_max: 6 +2026-06-24 06:16:15,106 - probe_pmode_init_pows: [0.02] +2026-06-24 06:16:15,106 - obj_omode_max: 1 +2026-06-24 06:16:15,106 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:16:15,106 - obj_Nlayer: 1 +2026-06-24 06:16:15,106 - obj_slice_thickness: 20.0 +2026-06-24 06:16:15,106 - simu_Npix: None +2026-06-24 06:16:15,106 - simu_match_mode: None +2026-06-24 06:16:15,106 - meas_permute: None +2026-06-24 06:16:15,106 - meas_reshape: [256, 128, 128] +2026-06-24 06:16:15,106 - meas_flipT: [0, 0, 0] +2026-06-24 06:16:15,106 - meas_crop: None +2026-06-24 06:16:15,106 - meas_pad: None +2026-06-24 06:16:15,106 - meas_resample: None +2026-06-24 06:16:15,106 - meas_add_source_size: None +2026-06-24 06:16:15,106 - meas_add_detector_blur: None +2026-06-24 06:16:15,106 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:16:15,106 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:16:15,106 - meas_add_poisson_noise: None +2026-06-24 06:16:15,106 - meas_export: None +2026-06-24 06:16:15,106 - probe_permute: None +2026-06-24 06:16:15,106 - probe_z_shift: None +2026-06-24 06:16:15,106 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:16:15,106 - pos_scan_flipT: None +2026-06-24 06:16:15,106 - pos_scan_affine: None +2026-06-24 06:16:15,106 - pos_scan_rand_std: 0.15 +2026-06-24 06:16:15,106 - obj_z_crop: None +2026-06-24 06:16:15,107 - obj_z_pad: None +2026-06-24 06:16:15,107 - obj_z_resample: None +2026-06-24 06:16:15,107 - meas_source: file +2026-06-24 06:16:15,107 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000039_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:16:15,107 - probe_source: simu +2026-06-24 06:16:15,107 - probe_params: None +2026-06-24 06:16:15,107 - pos_source: simu +2026-06-24 06:16:15,107 - pos_params: None +2026-06-24 06:16:15,107 - obj_source: simu +2026-06-24 06:16:15,107 - obj_params: None +2026-06-24 06:16:15,107 - tilt_source: simu +2026-06-24 06:16:15,107 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:16:15,107 - +2026-06-24 06:16:15,107 - ### Initializing cache ### +2026-06-24 06:16:15,107 - use_cached_obj = False +2026-06-24 06:16:15,107 - use_cached_probe = False +2026-06-24 06:16:15,107 - use_cached_pos = False +2026-06-24 06:16:15,107 - +2026-06-24 06:16:15,107 - ### Initializing measurements ### +2026-06-24 06:16:15,107 - Loading measurements from source = 'file' +2026-06-24 06:16:15,107 - Detected measurement file type = '.h5' +2026-06-24 06:16:15,187 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:16:15,188 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:16:15,189 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0058) +2026-06-24 06:16:15,189 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:16:15,189 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:16:15,191 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:16:15,191 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:16:15,191 - Normalizing by max of the 2D mean pattern intensity: 0.0041978057 +2026-06-24 06:16:15,192 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:16:15,193 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0144, 1.3792) +2026-06-24 06:16:15,194 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:16:15,195 - Pattern total int. statistics (min, mean, max) = (231.3659, 235.7231, 238.1479), with min/max = 97.2% +2026-06-24 06:16:15,196 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0144, 1.3792) +2026-06-24 06:16:15,197 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:16:15,197 - +2026-06-24 06:16:15,197 - ### Setting up calibration ### +2026-06-24 06:16:15,197 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:16:15,197 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:16:15,197 - Radius of fitted bright field disk (RBF) = 7.88 px with meas_Npix = 128 +2026-06-24 06:16:15,197 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1231 +2026-06-24 06:16:15,197 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:16:15,197 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:16:15,428 - Initial guess: center=(63.63, 63.65), radius=7.88, Gaussian blur std=0.50 +2026-06-24 06:16:15,439 - Final fit: center=(63.63, 63.65), radius=7.88, Gaussian blur std=0.58 +2026-06-24 06:16:15,439 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 7.90 px with Npix = 128 +2026-06-24 06:16:15,439 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:16:15,439 - +2026-06-24 06:16:15,439 - ### Setting init_variables dict ### +2026-06-24 06:16:15,439 - Derived values given input init_params: +2026-06-24 06:16:15,439 - kv = 80.0 kV +2026-06-24 06:16:15,439 - wavelength = 0.0418 Ang +2026-06-24 06:16:15,439 - conv_angle = 12.88296890258789 mrad +2026-06-24 06:16:15,439 - Npix = 128 px +2026-06-24 06:16:15,439 - dk = 0.0391 Ang^-1 +2026-06-24 06:16:15,439 - kMax = 2.5000 Ang^-1 +2026-06-24 06:16:15,439 - da = 1.6311 mrad +2026-06-24 06:16:15,439 - angleMax = 104.3929 mrad +2026-06-24 06:16:15,439 - RBF = 7.8981 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:16:15,439 - n_alpha = 8.1032 (# conv_angle) +2026-06-24 06:16:15,439 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:16:15,439 - Rayleigh-limited resolution = 1.9772 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:16:15,439 - Real space probe extent = 25.6000 Ang +2026-06-24 06:16:15,439 - +2026-06-24 06:16:15,439 - ### Initializing probe ### +2026-06-24 06:16:15,439 - Loading probe from source = 'simu' +2026-06-24 06:16:15,439 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:16:15,440 - Start simulating STEM probe +2026-06-24 06:16:15,440 - kv = 80.0 kV +2026-06-24 06:16:15,440 - wavelength = 0.0418 Ang +2026-06-24 06:16:15,440 - conv_angle = 12.88296890258789 mrad +2026-06-24 06:16:15,440 - Npix = 128 px +2026-06-24 06:16:15,440 - dk = 0.0391 Ang^-1 +2026-06-24 06:16:15,440 - kMax = 2.5000 Ang^-1 +2026-06-24 06:16:15,440 - alpha_max = 104.3929 mrad +2026-06-24 06:16:15,440 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:16:15,440 - Rayleigh-limited resolution = 1.9772 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:16:15,440 - Real space probe extent = 25.6000 Ang +2026-06-24 06:16:15,440 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:16:15,440 - ------------------------------------------------------------------------------------ +2026-06-24 06:16:15,440 - C1,0 C1 -265.6360 - Defocus (C10 = -df) +2026-06-24 06:16:15,440 - C1,2 A1 -38.6080 130.64 2-fold astigmatism +2026-06-24 06:16:15,440 - C2,1 3*B2 -18.1670 65.82 Axial coma +2026-06-24 06:16:15,440 - C2,3 A2 -822.8800 75.04 3-fold astigmatism +2026-06-24 06:16:15,440 - C3,0 C3 3530909.2500 - Spherical aberration +2026-06-24 06:16:15,440 - C3,2 4*S3 9259.6230 54.45 Axial star aberration +2026-06-24 06:16:15,440 - C3,4 A3 9392.4300 8.13 4-fold astigmatism +2026-06-24 06:16:15,440 - C4,1 4*B4 -150262.3910 18.37 Axial coma(4th) +2026-06-24 06:16:15,440 - C4,3 4*D4 341837.1560 293.65 3-lobe aberration +2026-06-24 06:16:15,440 - C4,5 A4 -4149.0080 152.65 5-fold astigmatism +2026-06-24 06:16:15,440 - C5,0 C5 329600800.0000 - Spherical aberration (5th) +2026-06-24 06:16:15,440 - C5,2 6*S5 -10346745.0000 9.25 Axial star aberration(5th) +2026-06-24 06:16:15,440 - C5,4 6*R5 15335027.0000 190.61 4-lobe aberration +2026-06-24 06:16:15,441 - C5,6 A5 16533163.0000 297.78 6-fold astigmatism +2026-06-24 06:16:15,444 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:16:15,444 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:16:15,444 - Creating 5 new probe modes from the major mode +2026-06-24 06:16:15,444 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:16:15,636 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:16:15,637 - Orthogonalizing 6 pmodes +2026-06-24 06:16:15,639 - Sorting 6 pmodes by their intensities +2026-06-24 06:16:15,639 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:16:15,640 - sum(|probe_data|**2) = 235.72, while meas_total_ints (min, mean, max) = (231.3659, 235.7231, 238.1479) +2026-06-24 06:16:15,640 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:16:15,640 - +2026-06-24 06:16:15,640 - ### Initializing probe positions ### +2026-06-24 06:16:15,640 - Loading probe positions from source = 'simu' +2026-06-24 06:16:15,640 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:16:15,640 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5063, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:16:15,641 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:16:15,643 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:16:15,643 - crop_pos 1st and last px coords (y,x) = ([16, 16], [54, 54]) +2026-06-24 06:16:15,643 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:16:15,643 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:16:15,643 - +2026-06-24 06:16:15,643 - ### Initializing object ### +2026-06-24 06:16:15,643 - Loading object from source = 'simu' +2026-06-24 06:16:15,643 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:16:15,644 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:16:15,644 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 200, 200) +2026-06-24 06:16:15,645 - object extent (Z, Y, X) (Ang) = [20. 40. 40.] +2026-06-24 06:16:15,645 - +2026-06-24 06:16:15,645 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:16:15,645 - omode_occu (omode) = float32, (1,) +2026-06-24 06:16:15,645 - +2026-06-24 06:16:15,645 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:16:15,645 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:16:15,646 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:16:15,646 - +2026-06-24 06:16:15,646 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:16:15,646 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:16:15,646 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:16:15,646 - +2026-06-24 06:16:15,646 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:16:15,646 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:16:15,646 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:16:15,646 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:16:15,646 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:16:15,646 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (200, 200). +2026-06-24 06:16:15,646 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:16:15,646 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:16:15,646 - +2026-06-24 06:16:15,646 - ### Collecting reconstruction provenance ### +2026-06-24 06:16:15,646 - Reconstruction provenance is collected and initialized. +2026-06-24 06:16:15,646 - +2026-06-24 06:16:15,646 - ### Initializing loss function ### +2026-06-24 06:16:15,646 - Active loss types: +2026-06-24 06:16:15,646 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:16:15,647 - +2026-06-24 06:16:15,647 - ### Initializing constraint function ### +2026-06-24 06:16:15,647 - Active constraint types: +2026-06-24 06:16:15,647 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:16:15,647 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:16:15,647 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:16:15,647 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:16:15,647 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:16:15,647 - +2026-06-24 06:16:15,647 - ### Done initializing PtyRADSolver ### +2026-06-24 06:16:15,647 - +2026-06-24 06:16:15,769 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:16:15,770 - +2026-06-24 06:16:15,770 - ### Initializing PtychoModel model ### +2026-06-24 06:16:15,840 - ### PtychoModel optimizable variables ### +2026-06-24 06:16:15,840 - obja : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:16:15,840 - objp : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:16:15,840 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:16:15,840 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:16:15,840 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:16:15,840 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:16:15,841 - +2026-06-24 06:16:15,841 - ### Optimizable variables statitsics ### +2026-06-24 06:16:15,841 - Total measurement values : 4,194,304 +2026-06-24 06:16:15,841 - Total optimizing variables: 277,120 +2026-06-24 06:16:15,841 - Overdetermined ratio : 15.14 +2026-06-24 06:16:15,841 - +2026-06-24 06:16:15,841 - ### Model behavior ### +2026-06-24 06:16:15,841 - Tilt propagator : False +2026-06-24 06:16:15,841 - Change slice thickness : False +2026-06-24 06:16:15,841 - Detector blur : False +2026-06-24 06:16:15,841 - Preload data : True +2026-06-24 06:16:15,841 - On-the-fly meas padding : False +2026-06-24 06:16:15,841 - On-the-fly meas resample : False +2026-06-24 06:16:15,841 - On-the-fly simu match mode: None +2026-06-24 06:16:15,841 - +2026-06-24 06:16:15,882 - ### Done initializing PtychoModel model ### +2026-06-24 06:16:15,883 - +2026-06-24 06:16:15,883 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:16:15,883 - +2026-06-24 06:16:15,883 - ### Generating indices, batches, and output_path ### +2026-06-24 06:16:15,884 - d90 = 43.000 px or 8.600 Ang +2026-06-24 06:16:15,884 - Selecting indices with the 'full' mode +2026-06-24 06:16:16,345 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:16:16,423 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:16:16,423 - Original recon_dir_affixes = ['default'] +2026-06-24 06:16:16,423 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:16:16,430 - Path corrected for compatibility: +2026-06-24 06:16:16,430 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_9.26e+03_phi32_54.5_C34_9.39e+03_phi34_8.13_C41_-1.5e+05_phi41_18.4_C43_3.42e+05_phi43_294_C45_-4.15e+03_phi45_153_C50_3.3e+08_C52_-1.03e+07_phi52_9.25_C54_1.53e+07_phi54_191_C56_1.65e+07_phi56_298 +2026-06-24 06:16:16,430 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_.65e+07_phi56_298 +2026-06-24 06:16:16,431 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_.65e+07_phi56_298' is generated! +2026-06-24 06:16:16,583 - +2026-06-24 06:16:16,585 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_.65e+07_phi56_298/20260624_061616_ptyrad_log.txt ### +2026-06-24 06:16:16,585 - +2026-06-24 06:16:16,586 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:16:16,586 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:16:16,586 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:16:17,776 - Iter: 1, Total Loss: 1.1704, loss_single: 1.1704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:16:17,813 - Iter: 2, Total Loss: 1.1291, loss_single: 1.1291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:16:17,849 - Iter: 3, Total Loss: 1.0963, loss_single: 1.0963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:17,885 - Iter: 4, Total Loss: 1.0710, loss_single: 1.0710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:17,921 - Iter: 5, Total Loss: 1.0469, loss_single: 1.0469, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:17,956 - Iter: 6, Total Loss: 1.0198, loss_single: 1.0198, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:17,993 - Iter: 7, Total Loss: 0.9900, loss_single: 0.9900, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:16:18,029 - Iter: 8, Total Loss: 0.9583, loss_single: 0.9583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:16:18,064 - Iter: 9, Total Loss: 0.9264, loss_single: 0.9264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:18,100 - Iter: 10, Total Loss: 0.8935, loss_single: 0.8935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,136 - Iter: 11, Total Loss: 0.8676, loss_single: 0.8676, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:16:18,171 - Iter: 12, Total Loss: 0.8449, loss_single: 0.8449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:18,206 - Iter: 13, Total Loss: 0.8181, loss_single: 0.8181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,241 - Iter: 14, Total Loss: 0.7903, loss_single: 0.7903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,277 - Iter: 15, Total Loss: 0.7650, loss_single: 0.7650, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,312 - Iter: 16, Total Loss: 0.7405, loss_single: 0.7405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,347 - Iter: 17, Total Loss: 0.7148, loss_single: 0.7148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,382 - Iter: 18, Total Loss: 0.6905, loss_single: 0.6905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,418 - Iter: 19, Total Loss: 0.6668, loss_single: 0.6668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,453 - Iter: 20, Total Loss: 0.6441, loss_single: 0.6441, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,488 - Iter: 21, Total Loss: 0.6210, loss_single: 0.6210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,523 - Iter: 22, Total Loss: 0.6001, loss_single: 0.6001, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,558 - Iter: 23, Total Loss: 0.5789, loss_single: 0.5789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,593 - Iter: 24, Total Loss: 0.5604, loss_single: 0.5604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:18,628 - Iter: 25, Total Loss: 0.5463, loss_single: 0.5463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,663 - Iter: 26, Total Loss: 0.5305, loss_single: 0.5305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,699 - Iter: 27, Total Loss: 0.5125, loss_single: 0.5125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,734 - Iter: 28, Total Loss: 0.4980, loss_single: 0.4980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,769 - Iter: 29, Total Loss: 0.4880, loss_single: 0.4880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,804 - Iter: 30, Total Loss: 0.4774, loss_single: 0.4774, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,839 - Iter: 31, Total Loss: 0.4655, loss_single: 0.4655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:18,874 - Iter: 32, Total Loss: 0.4559, loss_single: 0.4559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,909 - Iter: 33, Total Loss: 0.4477, loss_single: 0.4477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,944 - Iter: 34, Total Loss: 0.4407, loss_single: 0.4407, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:18,979 - Iter: 35, Total Loss: 0.4347, loss_single: 0.4347, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,014 - Iter: 36, Total Loss: 0.4282, loss_single: 0.4282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:19,049 - Iter: 37, Total Loss: 0.4221, loss_single: 0.4221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,084 - Iter: 38, Total Loss: 0.4164, loss_single: 0.4164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,119 - Iter: 39, Total Loss: 0.4110, loss_single: 0.4110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,154 - Iter: 40, Total Loss: 0.4075, loss_single: 0.4075, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:19,191 - Iter: 41, Total Loss: 0.4049, loss_single: 0.4049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,227 - Iter: 42, Total Loss: 0.4026, loss_single: 0.4026, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,262 - Iter: 43, Total Loss: 0.4002, loss_single: 0.4002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,297 - Iter: 44, Total Loss: 0.3976, loss_single: 0.3976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,332 - Iter: 45, Total Loss: 0.3955, loss_single: 0.3955, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,368 - Iter: 46, Total Loss: 0.3936, loss_single: 0.3936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,403 - Iter: 47, Total Loss: 0.3921, loss_single: 0.3921, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,438 - Iter: 48, Total Loss: 0.3906, loss_single: 0.3906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,474 - Iter: 49, Total Loss: 0.3893, loss_single: 0.3893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,509 - Iter: 50, Total Loss: 0.3884, loss_single: 0.3884, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,544 - Iter: 51, Total Loss: 0.3875, loss_single: 0.3875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:19,580 - Iter: 52, Total Loss: 0.3868, loss_single: 0.3868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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in 0.035 sec +2026-06-24 06:16:20,213 - Iter: 70, Total Loss: 0.3807, loss_single: 0.3807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,249 - Iter: 71, Total Loss: 0.3805, loss_single: 0.3805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,284 - Iter: 72, Total Loss: 0.3804, loss_single: 0.3804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,320 - Iter: 73, Total Loss: 0.3803, loss_single: 0.3803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,355 - Iter: 74, Total Loss: 0.3802, loss_single: 0.3802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,390 - Iter: 75, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,637 - Iter: 82, Total Loss: 0.3793, loss_single: 0.3793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,672 - Iter: 83, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,707 - Iter: 84, Total Loss: 0.3791, loss_single: 0.3791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,743 - Iter: 85, Total Loss: 0.3790, loss_single: 0.3790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,778 - Iter: 86, Total Loss: 0.3789, loss_single: 0.3789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,814 - Iter: 87, Total Loss: 0.3788, loss_single: 0.3788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,849 - Iter: 88, Total Loss: 0.3787, loss_single: 0.3787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,884 - Iter: 89, Total Loss: 0.3786, loss_single: 0.3786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:16:20,919 - Iter: 90, Total Loss: 0.3785, loss_single: 0.3785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,954 - Iter: 91, Total Loss: 0.3784, loss_single: 0.3784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:20,991 - Iter: 92, Total Loss: 0.3783, loss_single: 0.3783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:16:21,026 - Iter: 93, Total Loss: 0.3782, loss_single: 0.3782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,062 - Iter: 94, Total Loss: 0.3781, loss_single: 0.3781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,097 - Iter: 95, Total Loss: 0.3780, loss_single: 0.3780, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,132 - Iter: 96, Total Loss: 0.3779, loss_single: 0.3779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,167 - Iter: 97, Total Loss: 0.3778, loss_single: 0.3778, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,203 - Iter: 98, Total Loss: 0.3777, loss_single: 0.3777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,238 - Iter: 99, Total Loss: 0.3776, loss_single: 0.3776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,273 - Iter: 100, Total Loss: 0.3775, loss_single: 0.3775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:16:21,384 - Saving summary figures for iter 100 +2026-06-24 06:16:25,004 - ### Finished 100 iterations, averaged iter_t = 0.038896 with std = 0.040 ### +2026-06-24 06:16:25,004 - +2026-06-24 06:16:25,004 - ### The PtyRADSolver is finished in 9.235 sec ### +2026-06-24 06:16:25,004 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039/c30_small__simulation_data4__sample_000039_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_-38.6_phi12_131_C21_-18.2_phi21_65.8_C23_-823_phi23_75_C30_3.53e+06_C32_.65e+07_phi56_298/simulation_data4__sample_000039.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 12.88296890258789 + probe_aberrations: + C10: -265.6363525390625 + C12: -38.60789108276367 + C21: -18.16674041748047 + C23: -822.8801879882812 + C30: 3530909.25 + C32: 9259.623046875 + C34: 9392.4296875 + C41: -150262.390625 + C43: 341837.15625 + C45: -4149.0078125 + C50: 329600800.0 + C52: -10346745.0 + C54: 15335027.0 + C56: 16533163.0 + phi12: 130.6386513490027 + phi21: 65.82128310679477 + phi23: 75.0403719201545 + phi32: 54.451101346420394 + phi34: 8.132490240001681 + phi41: 18.373712593785587 + phi43: 293.65379272245656 + phi45: 152.64601262840404 + phi52: 9.250811626959855 + phi54: 190.61415996029118 + phi56: 297.78318849086287 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5063364505767822 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000039_measurement.h5 + key: measurement + random_seed: 20262015 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000039 + 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sha256:a3992f4a74b777a23fea300f7d1ad476400a6b5e48bfaabc5e1069d6b1c1df3a +size 47960 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/20260624_061716_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/20260624_061716_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b7c1db409ef2c6f7789a4e84def31b94e142c62d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/20260624_061716_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:17:14,657 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:17:14,657 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:17:14,657 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:17:14,658 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:17:14,658 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:17:14,658 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:17:14,658 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:17:14,658 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:17:14,658 - +2026-06-24 06:17:14,767 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:17:14,767 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:17:14,767 - Accelerator.num_process = 1 +2026-06-24 06:17:14,767 - Accelerator.mixed_precision = no +2026-06-24 06:17:14,777 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:17:14,777 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:17:14,777 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:17:14,777 - +2026-06-24 06:17:14,777 - ### System information ### +2026-06-24 06:17:14,777 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:17:14,777 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:17:14,778 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:17:14,778 - Machine: x86_64 +2026-06-24 06:17:14,778 - Processor: x86_64 +2026-06-24 06:17:14,778 - Available CPU cores: 8 +2026-06-24 06:17:14,778 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:17:14,778 - +2026-06-24 06:17:14,778 - ### GPU information ### +2026-06-24 06:17:14,778 - CUDA Available: True +2026-06-24 06:17:14,778 - CUDA Version: 13.0 +2026-06-24 06:17:14,778 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:17:14,778 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:17:14,778 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:17:14,778 - In addition, Triton does not directly support Windows. +2026-06-24 06:17:14,778 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:17:14,806 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:17:14,806 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:17:14,806 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:17:14,806 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:17:14,806 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:17:14,806 - +2026-06-24 06:17:14,806 - ### Python information ### +2026-06-24 06:17:14,808 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:17:14,808 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:17:14,808 - +2026-06-24 06:17:14,808 - ### Packages information ### +2026-06-24 06:17:14,809 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:17:14,810 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:17:14,810 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:17:14,811 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:17:14,812 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:17:14,812 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:17:14,812 - +2026-06-24 06:17:14,812 - ### Loading params file ### +2026-06-24 06:17:14,812 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000043.yaml +2026-06-24 06:17:14,818 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:17:14,819 - Success! Params file validated and defaults applied. +2026-06-24 06:17:14,819 - +2026-06-24 06:17:14,819 - ### Setting GPU Device ### +2026-06-24 06:17:14,819 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:17:14,819 - +2026-06-24 06:17:14,819 - Random seed: 20262019 provided by params file +2026-06-24 06:17:14,820 - ### Initializing Initializer ### +2026-06-24 06:17:14,820 - init_params are displayed below: +2026-06-24 06:17:14,820 - random_seed: 20262019 +2026-06-24 06:17:14,820 - probe_illum_type: electron +2026-06-24 06:17:14,820 - probe_kv: 80.0 +2026-06-24 06:17:14,820 - probe_conv_angle: 15.911824226379395 +2026-06-24 06:17:14,820 - probe_aberrations: {'C10': -639.557, 'C12': -17.667, 'phi12': 49.548, 'C21': -120.383, 'phi21': 108.088, 'C23': -32.767, 'phi23': 91.765, 'C30': 2911165.5, 'C32': -1862.191, 'phi32': 138.609, 'C34': 2844.3, 'phi34': 223.858, 'C41': -162812.547, 'phi41': 326.54, 'C43': -319252.656, 'phi43': 225.941, 'C45': -310760.125, 'phi45': 106.812, 'C50': -342244640.0, 'C52': -7230165.0, 'phi52': 291.006, 'C54': -10833546.0, 'phi54': 358.672, 'C56': 10324433.0, 'phi56': 129.704} +2026-06-24 06:17:14,820 - beam_kev: None +2026-06-24 06:17:14,820 - probe_dRn: None +2026-06-24 06:17:14,820 - probe_Rn: None +2026-06-24 06:17:14,820 - probe_D_H: None +2026-06-24 06:17:14,820 - probe_D_FZP: None +2026-06-24 06:17:14,820 - probe_Ls: None +2026-06-24 06:17:14,820 - meas_Npix: 128 +2026-06-24 06:17:14,820 - pos_N_scans: 256 +2026-06-24 06:17:14,820 - pos_N_scan_slow: 16 +2026-06-24 06:17:14,820 - pos_N_scan_fast: 16 +2026-06-24 06:17:14,820 - pos_scan_step_size: 0.4758055806159973 +2026-06-24 06:17:14,820 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:17:14,820 - probe_pmode_max: 6 +2026-06-24 06:17:14,821 - probe_pmode_init_pows: [0.02] +2026-06-24 06:17:14,821 - obj_omode_max: 1 +2026-06-24 06:17:14,821 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:17:14,821 - obj_Nlayer: 1 +2026-06-24 06:17:14,821 - obj_slice_thickness: 20.0 +2026-06-24 06:17:14,821 - simu_Npix: None +2026-06-24 06:17:14,821 - simu_match_mode: None +2026-06-24 06:17:14,821 - meas_permute: None +2026-06-24 06:17:14,821 - meas_reshape: [256, 128, 128] +2026-06-24 06:17:14,821 - meas_flipT: [0, 0, 0] +2026-06-24 06:17:14,821 - meas_crop: None +2026-06-24 06:17:14,821 - meas_pad: None +2026-06-24 06:17:14,821 - meas_resample: None +2026-06-24 06:17:14,821 - meas_add_source_size: None +2026-06-24 06:17:14,821 - meas_add_detector_blur: None +2026-06-24 06:17:14,821 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:17:14,821 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:17:14,821 - meas_add_poisson_noise: None +2026-06-24 06:17:14,821 - meas_export: None +2026-06-24 06:17:14,821 - probe_permute: None +2026-06-24 06:17:14,821 - probe_z_shift: None +2026-06-24 06:17:14,821 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:17:14,821 - pos_scan_flipT: None +2026-06-24 06:17:14,821 - pos_scan_affine: None +2026-06-24 06:17:14,821 - pos_scan_rand_std: 0.15 +2026-06-24 06:17:14,821 - obj_z_crop: None +2026-06-24 06:17:14,821 - obj_z_pad: None +2026-06-24 06:17:14,821 - obj_z_resample: None +2026-06-24 06:17:14,821 - meas_source: file +2026-06-24 06:17:14,821 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000043_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:17:14,821 - probe_source: simu +2026-06-24 06:17:14,821 - probe_params: None +2026-06-24 06:17:14,821 - pos_source: simu +2026-06-24 06:17:14,821 - pos_params: None +2026-06-24 06:17:14,821 - obj_source: simu +2026-06-24 06:17:14,821 - obj_params: None +2026-06-24 06:17:14,821 - tilt_source: simu +2026-06-24 06:17:14,821 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:17:14,821 - +2026-06-24 06:17:14,822 - ### Initializing cache ### +2026-06-24 06:17:14,822 - use_cached_obj = False +2026-06-24 06:17:14,822 - use_cached_probe = False +2026-06-24 06:17:14,822 - use_cached_pos = False +2026-06-24 06:17:14,822 - +2026-06-24 06:17:14,822 - ### Initializing measurements ### +2026-06-24 06:17:14,822 - Loading measurements from source = 'file' +2026-06-24 06:17:14,822 - Detected measurement file type = '.h5' +2026-06-24 06:17:14,904 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:17:14,904 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:17:14,905 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0048) +2026-06-24 06:17:14,905 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:17:14,905 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:17:14,907 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:17:14,907 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:17:14,908 - Normalizing by max of the 2D mean pattern intensity: 0.0030480528 +2026-06-24 06:17:14,908 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:17:14,909 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0199, 1.5721) +2026-06-24 06:17:14,910 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:17:14,911 - Pattern total int. statistics (min, mean, max) = (323.5204, 325.6661, 327.7085), with min/max = 98.7% +2026-06-24 06:17:14,912 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0199, 1.5721) +2026-06-24 06:17:14,912 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:17:14,912 - +2026-06-24 06:17:14,912 - ### Setting up calibration ### +2026-06-24 06:17:14,913 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:17:14,913 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:17:14,913 - Radius of fitted bright field disk (RBF) = 9.64 px with meas_Npix = 128 +2026-06-24 06:17:14,913 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1506 +2026-06-24 06:17:14,913 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:17:14,913 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:17:15,144 - Initial guess: center=(63.65, 63.62), radius=9.64, Gaussian blur std=0.50 +2026-06-24 06:17:15,158 - Final fit: center=(63.65, 63.62), radius=9.64, Gaussian blur std=0.76 +2026-06-24 06:17:15,158 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.76 px with Npix = 128 +2026-06-24 06:17:15,158 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:17:15,158 - +2026-06-24 06:17:15,158 - ### Setting init_variables dict ### +2026-06-24 06:17:15,158 - Derived values given input init_params: +2026-06-24 06:17:15,158 - kv = 80.0 kV +2026-06-24 06:17:15,158 - wavelength = 0.0418 Ang +2026-06-24 06:17:15,158 - conv_angle = 15.911824226379395 mrad +2026-06-24 06:17:15,158 - Npix = 128 px +2026-06-24 06:17:15,158 - dk = 0.0391 Ang^-1 +2026-06-24 06:17:15,158 - kMax = 2.5000 Ang^-1 +2026-06-24 06:17:15,158 - da = 1.6311 mrad +2026-06-24 06:17:15,158 - angleMax = 104.3929 mrad +2026-06-24 06:17:15,158 - RBF = 9.7550 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:17:15,158 - n_alpha = 6.5607 (# conv_angle) +2026-06-24 06:17:15,159 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:17:15,159 - Rayleigh-limited resolution = 1.6008 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:17:15,159 - Real space probe extent = 25.6000 Ang +2026-06-24 06:17:15,159 - +2026-06-24 06:17:15,159 - ### Initializing probe ### +2026-06-24 06:17:15,159 - Loading probe from source = 'simu' +2026-06-24 06:17:15,159 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:17:15,159 - Start simulating STEM probe +2026-06-24 06:17:15,159 - kv = 80.0 kV +2026-06-24 06:17:15,159 - wavelength = 0.0418 Ang +2026-06-24 06:17:15,159 - conv_angle = 15.911824226379395 mrad +2026-06-24 06:17:15,159 - Npix = 128 px +2026-06-24 06:17:15,159 - dk = 0.0391 Ang^-1 +2026-06-24 06:17:15,159 - kMax = 2.5000 Ang^-1 +2026-06-24 06:17:15,159 - alpha_max = 104.3929 mrad +2026-06-24 06:17:15,159 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:17:15,159 - Rayleigh-limited resolution = 1.6008 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:17:15,159 - Real space probe extent = 25.6000 Ang +2026-06-24 06:17:15,159 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:17:15,159 - ------------------------------------------------------------------------------------- +2026-06-24 06:17:15,159 - C1,0 C1 -639.5570 - Defocus (C10 = -df) +2026-06-24 06:17:15,159 - C1,2 A1 -17.6670 49.55 2-fold astigmatism +2026-06-24 06:17:15,159 - C2,1 3*B2 -120.3830 108.09 Axial coma +2026-06-24 06:17:15,159 - C2,3 A2 -32.7670 91.77 3-fold astigmatism +2026-06-24 06:17:15,160 - C3,0 C3 2911165.5000 - Spherical aberration +2026-06-24 06:17:15,160 - C3,2 4*S3 -1862.1910 138.61 Axial star aberration +2026-06-24 06:17:15,160 - C3,4 A3 2844.3000 223.86 4-fold astigmatism +2026-06-24 06:17:15,160 - C4,1 4*B4 -162812.5470 326.54 Axial coma(4th) +2026-06-24 06:17:15,160 - C4,3 4*D4 -319252.6560 225.94 3-lobe aberration +2026-06-24 06:17:15,160 - C4,5 A4 -310760.1250 106.81 5-fold astigmatism +2026-06-24 06:17:15,160 - C5,0 C5 -342244640.0000 - Spherical aberration (5th) +2026-06-24 06:17:15,160 - C5,2 6*S5 -7230165.0000 291.01 Axial star aberration(5th) +2026-06-24 06:17:15,160 - C5,4 6*R5 -10833546.0000 358.67 4-lobe aberration +2026-06-24 06:17:15,160 - C5,6 A5 10324433.0000 129.70 6-fold astigmatism +2026-06-24 06:17:15,163 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:17:15,163 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:17:15,163 - Creating 5 new probe modes from the major mode +2026-06-24 06:17:15,163 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:17:15,379 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:17:15,380 - Orthogonalizing 6 pmodes +2026-06-24 06:17:15,383 - Sorting 6 pmodes by their intensities +2026-06-24 06:17:15,383 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:17:15,384 - sum(|probe_data|**2) = 325.67, while meas_total_ints (min, mean, max) = (323.5204, 325.6661, 327.7085) +2026-06-24 06:17:15,384 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:17:15,384 - +2026-06-24 06:17:15,384 - ### Initializing probe positions ### +2026-06-24 06:17:15,384 - Loading probe positions from source = 'simu' +2026-06-24 06:17:15,384 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:17:15,384 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4758, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:17:15,384 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:17:15,386 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:17:15,386 - crop_pos 1st and last px coords (y,x) = ([16, 16], [52, 52]) +2026-06-24 06:17:15,387 - crop_pos extent (Ang) = [7.2 7.2] +2026-06-24 06:17:15,387 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:17:15,387 - +2026-06-24 06:17:15,387 - ### Initializing object ### +2026-06-24 06:17:15,387 - Loading object from source = 'simu' +2026-06-24 06:17:15,387 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:17:15,388 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:17:15,388 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 198, 198) +2026-06-24 06:17:15,389 - object extent (Z, Y, X) (Ang) = [20. 39.6 39.6] +2026-06-24 06:17:15,389 - +2026-06-24 06:17:15,389 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:17:15,389 - omode_occu (omode) = float32, (1,) +2026-06-24 06:17:15,389 - +2026-06-24 06:17:15,389 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:17:15,389 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:17:15,390 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:17:15,390 - +2026-06-24 06:17:15,390 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:17:15,390 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:17:15,390 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:17:15,390 - +2026-06-24 06:17:15,390 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:17:15,390 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:17:15,390 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:17:15,390 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:17:15,390 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:17:15,390 - crop positions (yx_min=[16 16], yx_max=[180 180]) are well contained inside object canvas (Ny,Nx) = (198, 198). +2026-06-24 06:17:15,390 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:17:15,390 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:17:15,390 - +2026-06-24 06:17:15,390 - ### Collecting reconstruction provenance ### +2026-06-24 06:17:15,390 - Reconstruction provenance is collected and initialized. +2026-06-24 06:17:15,390 - +2026-06-24 06:17:15,390 - ### Initializing loss function ### +2026-06-24 06:17:15,390 - Active loss types: +2026-06-24 06:17:15,390 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:17:15,391 - +2026-06-24 06:17:15,391 - ### Initializing constraint function ### +2026-06-24 06:17:15,391 - Active constraint types: +2026-06-24 06:17:15,391 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:17:15,391 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:17:15,391 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:17:15,391 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:17:15,391 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:17:15,391 - +2026-06-24 06:17:15,391 - ### Done initializing PtyRADSolver ### +2026-06-24 06:17:15,391 - +2026-06-24 06:17:15,515 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:17:15,515 - +2026-06-24 06:17:15,516 - ### Initializing PtychoModel model ### +2026-06-24 06:17:15,587 - ### PtychoModel optimizable variables ### +2026-06-24 06:17:15,587 - obja : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:15,587 - objp : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:15,587 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:17:15,587 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:17:15,587 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:17:15,587 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:15,587 - +2026-06-24 06:17:15,587 - ### Optimizable variables statitsics ### +2026-06-24 06:17:15,587 - Total measurement values : 4,194,304 +2026-06-24 06:17:15,587 - Total optimizing variables: 275,528 +2026-06-24 06:17:15,587 - Overdetermined ratio : 15.22 +2026-06-24 06:17:15,587 - +2026-06-24 06:17:15,587 - ### Model behavior ### +2026-06-24 06:17:15,587 - Tilt propagator : False +2026-06-24 06:17:15,587 - Change slice thickness : False +2026-06-24 06:17:15,587 - Detector blur : False +2026-06-24 06:17:15,588 - Preload data : True +2026-06-24 06:17:15,588 - On-the-fly meas padding : False +2026-06-24 06:17:15,588 - On-the-fly meas resample : False +2026-06-24 06:17:15,588 - On-the-fly simu match mode: None +2026-06-24 06:17:15,588 - +2026-06-24 06:17:15,629 - ### Done initializing PtychoModel model ### +2026-06-24 06:17:15,629 - +2026-06-24 06:17:15,629 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:17:15,629 - +2026-06-24 06:17:15,629 - ### Generating indices, batches, and output_path ### +2026-06-24 06:17:15,630 - d90 = 47.000 px or 9.400 Ang +2026-06-24 06:17:15,630 - Selecting indices with the 'full' mode +2026-06-24 06:17:16,089 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:17:16,166 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:17:16,167 - Original recon_dir_affixes = ['default'] +2026-06-24 06:17:16,167 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:17:16,173 - Path corrected for compatibility: +2026-06-24 06:17:16,173 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C32_-1.86e+03_phi32_139_C34_2.84e+03_phi34_224_C41_-1.63e+05_phi41_327_C43_-3.19e+05_phi43_226_C45_-3.11e+05_phi45_107_C50_-3.42e+08_C52_-7.23e+06_phi52_291_C54_-1.08e+07_phi54_359_C56_1.03e+07_phi56_130 +2026-06-24 06:17:16,173 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130 +2026-06-24 06:17:16,175 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130' is generated! +2026-06-24 06:17:16,332 - +2026-06-24 06:17:16,333 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/20260624_061716_ptyrad_log.txt ### +2026-06-24 06:17:16,333 - +2026-06-24 06:17:16,334 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:17:16,335 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:17:16,335 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:17:17,526 - Iter: 1, Total Loss: 1.0784, loss_single: 1.0784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.443 sec +2026-06-24 06:17:17,564 - Iter: 2, Total Loss: 1.0418, loss_single: 1.0418, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:17:17,599 - Iter: 3, Total Loss: 1.0139, loss_single: 1.0139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,634 - Iter: 4, Total Loss: 0.9881, loss_single: 0.9881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,670 - Iter: 5, Total Loss: 0.9632, loss_single: 0.9632, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,705 - Iter: 6, Total Loss: 0.9378, loss_single: 0.9378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,740 - Iter: 7, Total Loss: 0.9109, loss_single: 0.9109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,776 - Iter: 8, Total Loss: 0.8840, loss_single: 0.8840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:17:17,811 - Iter: 9, Total Loss: 0.8562, loss_single: 0.8562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,847 - Iter: 10, Total Loss: 0.8334, loss_single: 0.8334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,882 - Iter: 11, Total Loss: 0.8115, loss_single: 0.8115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:17,917 - Iter: 12, Total Loss: 0.7830, loss_single: 0.7830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,952 - Iter: 13, Total Loss: 0.7549, loss_single: 0.7549, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:17,988 - Iter: 14, Total Loss: 0.7289, loss_single: 0.7289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,023 - Iter: 15, Total Loss: 0.7057, loss_single: 0.7057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,058 - Iter: 16, Total Loss: 0.6850, loss_single: 0.6850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,093 - Iter: 17, Total Loss: 0.6677, loss_single: 0.6677, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:18,129 - Iter: 18, Total Loss: 0.6487, loss_single: 0.6487, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,169 - Iter: 19, Total Loss: 0.6257, loss_single: 0.6257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,204 - Iter: 20, Total Loss: 0.6046, loss_single: 0.6046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,239 - Iter: 21, Total Loss: 0.5822, loss_single: 0.5822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,275 - Iter: 22, Total Loss: 0.5581, loss_single: 0.5581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:17:18,310 - Iter: 23, Total Loss: 0.5358, loss_single: 0.5358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:18,345 - Iter: 24, Total Loss: 0.5215, loss_single: 0.5215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,381 - Iter: 25, Total Loss: 0.5074, loss_single: 0.5074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,416 - Iter: 26, Total Loss: 0.4907, loss_single: 0.4907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:18,451 - Iter: 27, Total Loss: 0.4755, loss_single: 0.4755, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,486 - Iter: 28, Total Loss: 0.4602, loss_single: 0.4602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:18,521 - Iter: 29, Total Loss: 0.4498, loss_single: 0.4498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/simulation_data4__sample_000043.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/simulation_data4__sample_000043.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7f6bbf7c2e68ae9d0085dfb713a4b548be4f07f7 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/simulation_data4__sample_000043.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 15.911824226379395 + probe_aberrations: + C10: -639.55712890625 + C12: -17.6671142578125 + C21: -120.38347625732422 + C23: -32.76704025268555 + C30: 2911165.5 + C32: -1862.191162109375 + C34: 2844.30029296875 + C41: -162812.546875 + C43: -319252.65625 + C45: -310760.125 + C50: -342244640.0 + C52: -7230165.0 + C54: -10833546.0 + C56: 10324433.0 + phi12: 49.54849401302279 + phi21: 108.0876479928034 + phi23: 91.76463651806432 + phi32: 138.60864882732886 + phi34: 223.8582206131173 + phi41: 326.53965093445055 + phi43: 225.94058136651412 + phi45: 106.8118642784934 + phi52: 291.00605623032277 + phi54: 358.6715655451019 + phi56: 129.70419950827494 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4758055806159973 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000043_measurement.h5 + key: measurement + random_seed: 20262019 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000043 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:445d0aef8e7404e9912511d5891e58ae2185e85e726322b64ded5ac9e47d8878 +size 1245019 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..c52c25ff4a935e93fc855d8c65f09b9fa284a126 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000043/c30_small__simulation_data4__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-640_C12_-17.7_phi12_49.5_C21_-120_phi21_108_C23_-32.8_phi23_91.8_C30_2.91e+06_C3.03e+07_phi56_130/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1a1563539f9cceee223f2e0e754860a786ff1de26bf8889e9cb9ae2a3b3ccb51 +size 47643 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/20260624_061746_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/20260624_061746_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..15e1adb183d75c640010414737176df630dbf0f4 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/20260624_061746_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:17:44,642 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:17:44,642 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:17:44,642 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:17:44,642 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:17:44,642 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:17:44,642 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:17:44,642 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:17:44,642 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:17:44,642 - +2026-06-24 06:17:44,749 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:17:44,749 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:17:44,749 - Accelerator.num_process = 1 +2026-06-24 06:17:44,749 - Accelerator.mixed_precision = no +2026-06-24 06:17:44,771 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:17:44,771 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:17:44,772 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:17:44,772 - +2026-06-24 06:17:44,772 - ### System information ### +2026-06-24 06:17:44,772 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:17:44,772 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:17:44,772 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:17:44,772 - Machine: x86_64 +2026-06-24 06:17:44,772 - Processor: x86_64 +2026-06-24 06:17:44,772 - Available CPU cores: 8 +2026-06-24 06:17:44,772 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:17:44,772 - +2026-06-24 06:17:44,772 - ### GPU information ### +2026-06-24 06:17:44,772 - CUDA Available: True +2026-06-24 06:17:44,772 - CUDA Version: 13.0 +2026-06-24 06:17:44,773 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:17:44,773 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:17:44,773 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:17:44,773 - In addition, Triton does not directly support Windows. +2026-06-24 06:17:44,773 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:17:44,788 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:17:44,789 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:17:44,789 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:17:44,789 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:17:44,789 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:17:44,789 - +2026-06-24 06:17:44,789 - ### Python information ### +2026-06-24 06:17:44,791 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:17:44,791 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:17:44,791 - +2026-06-24 06:17:44,791 - ### Packages information ### +2026-06-24 06:17:44,791 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:17:44,792 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:17:44,793 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:17:44,793 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:17:44,794 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:17:44,794 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:17:44,794 - +2026-06-24 06:17:44,794 - ### Loading params file ### +2026-06-24 06:17:44,794 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000045.yaml +2026-06-24 06:17:44,800 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:17:44,801 - Success! Params file validated and defaults applied. +2026-06-24 06:17:44,801 - +2026-06-24 06:17:44,801 - ### Setting GPU Device ### +2026-06-24 06:17:44,801 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:17:44,801 - +2026-06-24 06:17:44,801 - Random seed: 20262021 provided by params file +2026-06-24 06:17:44,802 - ### Initializing Initializer ### +2026-06-24 06:17:44,802 - init_params are displayed below: +2026-06-24 06:17:44,802 - random_seed: 20262021 +2026-06-24 06:17:44,802 - probe_illum_type: electron +2026-06-24 06:17:44,802 - probe_kv: 80.0 +2026-06-24 06:17:44,802 - probe_conv_angle: 9.790149688720703 +2026-06-24 06:17:44,802 - probe_aberrations: {'C10': 84.333, 'C12': 39.849, 'phi12': 278.188, 'C21': -826.5, 'phi21': 237.075, 'C23': 489.436, 'phi23': 233.963, 'C30': 4983339.0, 'C32': -2028.109, 'phi32': 69.962, 'C34': -11570.62, 'phi34': 55.468, 'C41': -36725.145, 'phi41': 266.052, 'C43': -5465.276, 'phi43': 39.878, 'C45': -420567.375, 'phi45': 274.158, 'C50': -381766560.0, 'C52': 11258962.0, 'phi52': 172.925, 'C54': 8557603.0, 'phi54': 164.776, 'C56': 18405858.0, 'phi56': 103.793} +2026-06-24 06:17:44,802 - beam_kev: None +2026-06-24 06:17:44,802 - probe_dRn: None +2026-06-24 06:17:44,802 - probe_Rn: None +2026-06-24 06:17:44,802 - probe_D_H: None +2026-06-24 06:17:44,802 - probe_D_FZP: None +2026-06-24 06:17:44,802 - probe_Ls: None +2026-06-24 06:17:44,802 - meas_Npix: 128 +2026-06-24 06:17:44,802 - pos_N_scans: 256 +2026-06-24 06:17:44,802 - pos_N_scan_slow: 16 +2026-06-24 06:17:44,802 - pos_N_scan_fast: 16 +2026-06-24 06:17:44,802 - pos_scan_step_size: 0.36826351284980774 +2026-06-24 06:17:44,802 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:17:44,802 - probe_pmode_max: 6 +2026-06-24 06:17:44,802 - probe_pmode_init_pows: [0.02] +2026-06-24 06:17:44,803 - obj_omode_max: 1 +2026-06-24 06:17:44,803 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:17:44,803 - obj_Nlayer: 1 +2026-06-24 06:17:44,803 - obj_slice_thickness: 20.0 +2026-06-24 06:17:44,803 - simu_Npix: None +2026-06-24 06:17:44,803 - simu_match_mode: None +2026-06-24 06:17:44,803 - meas_permute: None +2026-06-24 06:17:44,803 - meas_reshape: [256, 128, 128] +2026-06-24 06:17:44,803 - meas_flipT: [0, 0, 0] +2026-06-24 06:17:44,803 - meas_crop: None +2026-06-24 06:17:44,803 - meas_pad: None +2026-06-24 06:17:44,803 - meas_resample: None +2026-06-24 06:17:44,803 - meas_add_source_size: None +2026-06-24 06:17:44,803 - meas_add_detector_blur: None +2026-06-24 06:17:44,803 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:17:44,803 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:17:44,803 - meas_add_poisson_noise: None +2026-06-24 06:17:44,803 - meas_export: None +2026-06-24 06:17:44,803 - probe_permute: None +2026-06-24 06:17:44,803 - probe_z_shift: None +2026-06-24 06:17:44,803 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:17:44,803 - pos_scan_flipT: None +2026-06-24 06:17:44,803 - pos_scan_affine: None +2026-06-24 06:17:44,803 - pos_scan_rand_std: 0.15 +2026-06-24 06:17:44,803 - obj_z_crop: None +2026-06-24 06:17:44,803 - obj_z_pad: None +2026-06-24 06:17:44,803 - obj_z_resample: None +2026-06-24 06:17:44,803 - meas_source: file +2026-06-24 06:17:44,803 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000045_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:17:44,803 - probe_source: simu +2026-06-24 06:17:44,803 - probe_params: None +2026-06-24 06:17:44,803 - pos_source: simu +2026-06-24 06:17:44,803 - pos_params: None +2026-06-24 06:17:44,803 - obj_source: simu +2026-06-24 06:17:44,803 - obj_params: None +2026-06-24 06:17:44,803 - tilt_source: simu +2026-06-24 06:17:44,803 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:17:44,803 - +2026-06-24 06:17:44,803 - ### Initializing cache ### +2026-06-24 06:17:44,803 - use_cached_obj = False +2026-06-24 06:17:44,803 - use_cached_probe = False +2026-06-24 06:17:44,803 - use_cached_pos = False +2026-06-24 06:17:44,804 - +2026-06-24 06:17:44,804 - ### Initializing measurements ### +2026-06-24 06:17:44,804 - Loading measurements from source = 'file' +2026-06-24 06:17:44,804 - Detected measurement file type = '.h5' +2026-06-24 06:17:44,882 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:17:44,882 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:17:44,884 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0097) +2026-06-24 06:17:44,884 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:17:44,884 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:17:44,885 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:17:44,885 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:17:44,886 - Normalizing by max of the 2D mean pattern intensity: 0.008087866 +2026-06-24 06:17:44,886 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:17:44,888 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0075, 1.1950) +2026-06-24 06:17:44,888 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:17:44,889 - Pattern total int. statistics (min, mean, max) = (121.4200, 122.6862, 124.0351), with min/max = 97.9% +2026-06-24 06:17:44,891 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0075, 1.1950) +2026-06-24 06:17:44,891 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:17:44,891 - +2026-06-24 06:17:44,891 - ### Setting up calibration ### +2026-06-24 06:17:44,891 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:17:44,891 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:17:44,891 - Radius of fitted bright field disk (RBF) = 6.02 px with meas_Npix = 128 +2026-06-24 06:17:44,891 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0941 +2026-06-24 06:17:44,891 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:17:44,891 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:17:45,108 - Initial guess: center=(63.60, 63.68), radius=6.02, Gaussian blur std=0.50 +2026-06-24 06:17:45,120 - Final fit: center=(63.60, 63.68), radius=6.02, Gaussian blur std=0.70 +2026-06-24 06:17:45,120 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.00 px with Npix = 128 +2026-06-24 06:17:45,120 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:17:45,120 - +2026-06-24 06:17:45,120 - ### Setting init_variables dict ### +2026-06-24 06:17:45,120 - Derived values given input init_params: +2026-06-24 06:17:45,120 - kv = 80.0 kV +2026-06-24 06:17:45,120 - wavelength = 0.0418 Ang +2026-06-24 06:17:45,120 - conv_angle = 9.790149688720703 mrad +2026-06-24 06:17:45,120 - Npix = 128 px +2026-06-24 06:17:45,120 - dk = 0.0391 Ang^-1 +2026-06-24 06:17:45,120 - kMax = 2.5000 Ang^-1 +2026-06-24 06:17:45,120 - da = 1.6311 mrad +2026-06-24 06:17:45,120 - angleMax = 104.3929 mrad +2026-06-24 06:17:45,120 - RBF = 6.0020 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:17:45,120 - n_alpha = 10.6631 (# conv_angle) +2026-06-24 06:17:45,120 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:17:45,120 - Rayleigh-limited resolution = 2.6018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:17:45,120 - Real space probe extent = 25.6000 Ang +2026-06-24 06:17:45,120 - +2026-06-24 06:17:45,120 - ### Initializing probe ### +2026-06-24 06:17:45,120 - Loading probe from source = 'simu' +2026-06-24 06:17:45,120 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:17:45,121 - Start simulating STEM probe +2026-06-24 06:17:45,121 - kv = 80.0 kV +2026-06-24 06:17:45,121 - wavelength = 0.0418 Ang +2026-06-24 06:17:45,121 - conv_angle = 9.790149688720703 mrad +2026-06-24 06:17:45,121 - Npix = 128 px +2026-06-24 06:17:45,121 - dk = 0.0391 Ang^-1 +2026-06-24 06:17:45,121 - kMax = 2.5000 Ang^-1 +2026-06-24 06:17:45,121 - alpha_max = 104.3929 mrad +2026-06-24 06:17:45,121 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:17:45,121 - Rayleigh-limited resolution = 2.6018 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:17:45,121 - Real space probe extent = 25.6000 Ang +2026-06-24 06:17:45,121 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:17:45,121 - ------------------------------------------------------------------------------------- +2026-06-24 06:17:45,121 - C1,0 C1 84.3330 - Defocus (C10 = -df) +2026-06-24 06:17:45,121 - C1,2 A1 39.8490 278.19 2-fold astigmatism +2026-06-24 06:17:45,121 - C2,1 3*B2 -826.5000 237.07 Axial coma +2026-06-24 06:17:45,121 - C2,3 A2 489.4360 233.96 3-fold astigmatism +2026-06-24 06:17:45,121 - C3,0 C3 4983339.0000 - Spherical aberration +2026-06-24 06:17:45,121 - C3,2 4*S3 -2028.1090 69.96 Axial star aberration +2026-06-24 06:17:45,121 - C3,4 A3 -11570.6200 55.47 4-fold astigmatism +2026-06-24 06:17:45,121 - C4,1 4*B4 -36725.1450 266.05 Axial coma(4th) +2026-06-24 06:17:45,121 - C4,3 4*D4 -5465.2760 39.88 3-lobe aberration +2026-06-24 06:17:45,121 - C4,5 A4 -420567.3750 274.16 5-fold astigmatism +2026-06-24 06:17:45,121 - C5,0 C5 -381766560.0000 - Spherical aberration (5th) +2026-06-24 06:17:45,121 - C5,2 6*S5 11258962.0000 172.93 Axial star aberration(5th) +2026-06-24 06:17:45,121 - C5,4 6*R5 8557603.0000 164.78 4-lobe aberration +2026-06-24 06:17:45,122 - C5,6 A5 18405858.0000 103.79 6-fold astigmatism +2026-06-24 06:17:45,124 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:17:45,124 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:17:45,124 - Creating 5 new probe modes from the major mode +2026-06-24 06:17:45,124 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:17:45,316 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:17:45,317 - Orthogonalizing 6 pmodes +2026-06-24 06:17:45,319 - Sorting 6 pmodes by their intensities +2026-06-24 06:17:45,320 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:17:45,320 - sum(|probe_data|**2) = 122.69, while meas_total_ints (min, mean, max) = (121.4200, 122.6862, 124.0351) +2026-06-24 06:17:45,321 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:17:45,321 - +2026-06-24 06:17:45,321 - ### Initializing probe positions ### +2026-06-24 06:17:45,321 - Loading probe positions from source = 'simu' +2026-06-24 06:17:45,321 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:17:45,321 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3683, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:17:45,321 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:17:45,323 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:17:45,323 - crop_pos 1st and last px coords (y,x) = ([15, 15], [43, 43]) +2026-06-24 06:17:45,323 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:17:45,323 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:17:45,323 - +2026-06-24 06:17:45,323 - ### Initializing object ### +2026-06-24 06:17:45,323 - Loading object from source = 'simu' +2026-06-24 06:17:45,323 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:17:45,325 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:17:45,325 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:17:45,325 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:17:45,325 - +2026-06-24 06:17:45,325 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:17:45,325 - omode_occu (omode) = float32, (1,) +2026-06-24 06:17:45,325 - +2026-06-24 06:17:45,325 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:17:45,325 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:17:45,326 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:17:45,326 - +2026-06-24 06:17:45,326 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:17:45,326 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:17:45,326 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:17:45,326 - +2026-06-24 06:17:45,326 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:17:45,326 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:17:45,326 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:17:45,326 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:17:45,326 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:17:45,326 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:17:45,326 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:17:45,326 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:17:45,326 - +2026-06-24 06:17:45,326 - ### Collecting reconstruction provenance ### +2026-06-24 06:17:45,327 - Reconstruction provenance is collected and initialized. +2026-06-24 06:17:45,327 - +2026-06-24 06:17:45,327 - ### Initializing loss function ### +2026-06-24 06:17:45,327 - Active loss types: +2026-06-24 06:17:45,327 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:17:45,327 - +2026-06-24 06:17:45,327 - ### Initializing constraint function ### +2026-06-24 06:17:45,327 - Active constraint types: +2026-06-24 06:17:45,327 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:17:45,327 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:17:45,327 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:17:45,327 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:17:45,327 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:17:45,327 - +2026-06-24 06:17:45,327 - ### Done initializing PtyRADSolver ### +2026-06-24 06:17:45,327 - +2026-06-24 06:17:45,460 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:17:45,460 - +2026-06-24 06:17:45,460 - ### Initializing PtychoModel model ### +2026-06-24 06:17:45,531 - ### PtychoModel optimizable variables ### +2026-06-24 06:17:45,532 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:45,532 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:45,532 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:17:45,532 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:17:45,532 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:17:45,532 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:17:45,532 - +2026-06-24 06:17:45,532 - ### Optimizable variables statitsics ### +2026-06-24 06:17:45,532 - Total measurement values : 4,194,304 +2026-06-24 06:17:45,532 - Total optimizing variables: 267,808 +2026-06-24 06:17:45,532 - Overdetermined ratio : 15.66 +2026-06-24 06:17:45,532 - +2026-06-24 06:17:45,532 - ### Model behavior ### +2026-06-24 06:17:45,532 - Tilt propagator : False +2026-06-24 06:17:45,532 - Change slice thickness : False +2026-06-24 06:17:45,532 - Detector blur : False +2026-06-24 06:17:45,532 - Preload data : True +2026-06-24 06:17:45,532 - On-the-fly meas padding : False +2026-06-24 06:17:45,532 - On-the-fly meas resample : False +2026-06-24 06:17:45,532 - On-the-fly simu match mode: None +2026-06-24 06:17:45,532 - +2026-06-24 06:17:45,573 - ### Done initializing PtychoModel model ### +2026-06-24 06:17:45,573 - +2026-06-24 06:17:45,573 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:17:45,573 - +2026-06-24 06:17:45,573 - ### Generating indices, batches, and output_path ### +2026-06-24 06:17:45,575 - d90 = 65.000 px or 13.000 Ang +2026-06-24 06:17:45,575 - Selecting indices with the 'full' mode +2026-06-24 06:17:46,038 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:17:46,111 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:17:46,111 - Original recon_dir_affixes = ['default'] +2026-06-24 06:17:46,111 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:17:46,117 - Path corrected for compatibility: +2026-06-24 06:17:46,117 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2.03e+03_phi32_70_C34_-1.16e+04_phi34_55.5_C41_-3.67e+04_phi41_266_C43_-5.47e+03_phi43_39.9_C45_-4.21e+05_phi45_274_C50_-3.82e+08_C52_1.13e+07_phi52_173_C54_8.56e+06_phi54_165_C56_1.84e+07_phi56_104 +2026-06-24 06:17:46,117 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104 +2026-06-24 06:17:46,119 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104' is generated! +2026-06-24 06:17:46,263 - +2026-06-24 06:17:46,264 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/20260624_061746_ptyrad_log.txt ### +2026-06-24 06:17:46,264 - +2026-06-24 06:17:46,265 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:17:46,265 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:17:46,265 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:17:47,461 - Iter: 1, Total Loss: 1.3085, loss_single: 1.3085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:17:47,498 - Iter: 2, Total Loss: 1.2290, loss_single: 1.2290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:17:47,534 - Iter: 3, Total Loss: 1.1709, loss_single: 1.1709, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,569 - Iter: 4, Total Loss: 1.1228, loss_single: 1.1228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,605 - Iter: 5, Total Loss: 1.0722, loss_single: 1.0722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,640 - Iter: 6, Total Loss: 1.0179, loss_single: 1.0179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,675 - Iter: 7, Total Loss: 0.9660, loss_single: 0.9660, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,710 - Iter: 8, Total Loss: 0.9119, loss_single: 0.9119, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,745 - Iter: 9, Total Loss: 0.8613, loss_single: 0.8613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,781 - Iter: 10, Total Loss: 0.8181, loss_single: 0.8181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,816 - Iter: 11, Total Loss: 0.7709, loss_single: 0.7709, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,851 - Iter: 12, Total Loss: 0.7308, loss_single: 0.7308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,887 - Iter: 13, Total Loss: 0.6936, loss_single: 0.6936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,922 - Iter: 14, Total Loss: 0.6487, loss_single: 0.6487, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,957 - Iter: 15, Total Loss: 0.6108, loss_single: 0.6108, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:47,992 - Iter: 16, Total Loss: 0.5791, loss_single: 0.5791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,027 - Iter: 17, Total Loss: 0.5515, loss_single: 0.5515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,062 - Iter: 18, Total Loss: 0.5278, loss_single: 0.5278, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,096 - Iter: 19, Total Loss: 0.5021, loss_single: 0.5021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,149 - Iter: 20, Total Loss: 0.4792, loss_single: 0.4792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,184 - Iter: 21, Total Loss: 0.4663, loss_single: 0.4663, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,219 - Iter: 22, Total Loss: 0.4548, loss_single: 0.4548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,255 - Iter: 23, Total Loss: 0.4447, loss_single: 0.4447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,290 - Iter: 24, Total Loss: 0.4350, loss_single: 0.4350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,325 - Iter: 25, Total Loss: 0.4233, loss_single: 0.4233, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,361 - Iter: 26, Total Loss: 0.4154, loss_single: 0.4154, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,396 - Iter: 27, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,435 - Iter: 28, Total Loss: 0.4094, loss_single: 0.4094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:17:48,470 - Iter: 29, Total Loss: 0.4067, loss_single: 0.4067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,505 - Iter: 30, Total Loss: 0.4041, loss_single: 0.4041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,540 - Iter: 31, Total Loss: 0.4024, loss_single: 0.4024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,575 - Iter: 32, Total Loss: 0.4013, loss_single: 0.4013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,610 - Iter: 33, Total Loss: 0.4000, loss_single: 0.4000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,646 - Iter: 34, Total Loss: 0.3990, loss_single: 0.3990, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,681 - Iter: 35, Total Loss: 0.3980, loss_single: 0.3980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,716 - Iter: 36, Total Loss: 0.3971, loss_single: 0.3971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,751 - Iter: 37, Total Loss: 0.3964, loss_single: 0.3964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,787 - Iter: 38, Total Loss: 0.3958, loss_single: 0.3958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:17:48,822 - Iter: 39, Total Loss: 0.3953, loss_single: 0.3953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,857 - Iter: 40, Total Loss: 0.3949, loss_single: 0.3949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,894 - Iter: 41, Total Loss: 0.3947, loss_single: 0.3947, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:48,928 - Iter: 42, Total Loss: 0.3944, loss_single: 0.3944, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,963 - Iter: 43, Total Loss: 0.3943, loss_single: 0.3943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:17:48,999 - Iter: 44, Total Loss: 0.3940, loss_single: 0.3940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,034 - Iter: 45, Total Loss: 0.3938, loss_single: 0.3938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,069 - Iter: 46, Total Loss: 0.3936, loss_single: 0.3936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,104 - Iter: 47, Total Loss: 0.3934, loss_single: 0.3934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,139 - Iter: 48, Total Loss: 0.3932, loss_single: 0.3932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,175 - Iter: 49, Total Loss: 0.3931, loss_single: 0.3931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,210 - Iter: 50, Total Loss: 0.3930, loss_single: 0.3930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,245 - Iter: 51, Total Loss: 0.3929, loss_single: 0.3929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,280 - Iter: 52, Total Loss: 0.3927, loss_single: 0.3927, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:17:49,315 - 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Saving summary figures for iter 100 +2026-06-24 06:17:54,672 - ### Finished 100 iterations, averaged iter_t = 0.0389 with std = 0.040 ### +2026-06-24 06:17:54,672 - +2026-06-24 06:17:54,672 - ### The PtyRADSolver is finished in 9.212 sec ### +2026-06-24 06:17:54,672 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..709a5764c98aefbda3c4a8922134cc38ef5b118a Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/simulation_data4__sample_000045.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/simulation_data4__sample_000045.yaml new file mode 100644 index 0000000000000000000000000000000000000000..65958a3046c9f3246a0c704d5fb951f45abe44fb --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045/c30_small__simulation_data4__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_84.3_C12_39.8_phi12_278_C21_-826_phi21_237_C23_489_phi23_234_C30_4.98e+06_C32_-2..84e+07_phi56_104/simulation_data4__sample_000045.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 9.790149688720703 + probe_aberrations: + C10: 84.33330535888672 + C12: 39.849037170410156 + C21: -826.5001220703125 + C23: 489.4363708496094 + C30: 4983339.0 + C32: -2028.1092529296875 + C34: -11570.6201171875 + C41: -36725.14453125 + C43: -5465.27587890625 + C45: -420567.375 + C50: -381766560.0 + C52: 11258962.0 + C54: 8557603.0 + C56: 18405858.0 + phi12: 278.18803146025664 + phi21: 237.07450005330858 + phi23: 233.96280247123417 + phi32: 69.96203064960164 + phi34: 55.468099438362366 + phi41: 266.0522606260047 + phi43: 39.87820973328119 + phi45: 274.1579466423823 + phi52: 172.92526774590044 + phi54: 164.77574557542968 + phi56: 103.79281138232105 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.36826351284980774 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000045_measurement.h5 + key: measurement + random_seed: 20262021 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000045 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data4__sample_000045 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9/20260624_061929_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9/20260624_061929_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cafd35962e0da59de36ca25de106fa104d3d5a59 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9/20260624_061929_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:19:27,955 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:19:27,955 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:19:27,956 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:19:27,956 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:19:27,956 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:19:27,956 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:19:27,956 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:19:27,956 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:19:27,956 - +2026-06-24 06:19:28,063 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:19:28,063 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:19:28,063 - Accelerator.num_process = 1 +2026-06-24 06:19:28,063 - Accelerator.mixed_precision = no +2026-06-24 06:19:28,074 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:19:28,074 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:19:28,074 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:19:28,074 - +2026-06-24 06:19:28,074 - ### System information ### +2026-06-24 06:19:28,074 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:19:28,074 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:19:28,074 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:19:28,074 - Machine: x86_64 +2026-06-24 06:19:28,074 - Processor: x86_64 +2026-06-24 06:19:28,074 - Available CPU cores: 8 +2026-06-24 06:19:28,075 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:19:28,075 - +2026-06-24 06:19:28,075 - ### GPU information ### +2026-06-24 06:19:28,075 - CUDA Available: True +2026-06-24 06:19:28,075 - CUDA Version: 13.0 +2026-06-24 06:19:28,075 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:19:28,075 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:19:28,075 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:19:28,075 - In addition, Triton does not directly support Windows. +2026-06-24 06:19:28,075 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:19:28,091 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:19:28,091 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:19:28,091 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:19:28,091 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:19:28,091 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:19:28,091 - +2026-06-24 06:19:28,091 - ### Python information ### +2026-06-24 06:19:28,093 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:19:28,093 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:19:28,093 - +2026-06-24 06:19:28,093 - ### Packages information ### +2026-06-24 06:19:28,094 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:19:28,095 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:19:28,095 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:19:28,096 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:19:28,096 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:19:28,096 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:19:28,096 - +2026-06-24 06:19:28,096 - ### Loading params file ### +2026-06-24 06:19:28,096 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data4__sample_000052.yaml +2026-06-24 06:19:28,103 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:19:28,104 - Success! Params file validated and defaults applied. +2026-06-24 06:19:28,104 - +2026-06-24 06:19:28,104 - ### Setting GPU Device ### +2026-06-24 06:19:28,104 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:19:28,104 - +2026-06-24 06:19:28,104 - Random seed: 20262028 provided by params file +2026-06-24 06:19:28,104 - ### Initializing Initializer ### +2026-06-24 06:19:28,105 - init_params are displayed below: +2026-06-24 06:19:28,105 - random_seed: 20262028 +2026-06-24 06:19:28,105 - probe_illum_type: electron +2026-06-24 06:19:28,105 - probe_kv: 80.0 +2026-06-24 06:19:28,105 - probe_conv_angle: 13.439705848693848 +2026-06-24 06:19:28,105 - probe_aberrations: {'C10': -238.022, 'C12': 35.552, 'phi12': 31.717, 'C21': -514.786, 'phi21': 204.432, 'C23': -296.894, 'phi23': 238.11, 'C30': 4429709.5, 'C32': -3023.664, 'phi32': 166.017, 'C34': -7288.744, 'phi34': 339.93, 'C41': -340220.062, 'phi41': 42.72, 'C43': 493508.312, 'phi43': 14.557, 'C45': -254363.047, 'phi45': 88.588, 'C50': -457111136.0, 'C52': 8635936.0, 'phi52': 90.056, 'C54': -18434290.0, 'phi54': 184.614, 'C56': 10805769.0, 'phi56': 86.923} +2026-06-24 06:19:28,105 - beam_kev: None +2026-06-24 06:19:28,105 - probe_dRn: None +2026-06-24 06:19:28,105 - probe_Rn: None +2026-06-24 06:19:28,105 - probe_D_H: None +2026-06-24 06:19:28,105 - probe_D_FZP: None +2026-06-24 06:19:28,105 - probe_Ls: None +2026-06-24 06:19:28,105 - meas_Npix: 128 +2026-06-24 06:19:28,105 - pos_N_scans: 256 +2026-06-24 06:19:28,105 - pos_N_scan_slow: 16 +2026-06-24 06:19:28,105 - pos_N_scan_fast: 16 +2026-06-24 06:19:28,105 - pos_scan_step_size: 0.3558799624443054 +2026-06-24 06:19:28,105 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:19:28,105 - probe_pmode_max: 6 +2026-06-24 06:19:28,105 - probe_pmode_init_pows: [0.02] +2026-06-24 06:19:28,105 - obj_omode_max: 1 +2026-06-24 06:19:28,105 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:19:28,105 - obj_Nlayer: 1 +2026-06-24 06:19:28,105 - obj_slice_thickness: 20.0 +2026-06-24 06:19:28,105 - simu_Npix: None +2026-06-24 06:19:28,105 - simu_match_mode: None +2026-06-24 06:19:28,105 - meas_permute: None +2026-06-24 06:19:28,105 - meas_reshape: [256, 128, 128] +2026-06-24 06:19:28,105 - meas_flipT: [0, 0, 0] +2026-06-24 06:19:28,105 - meas_crop: None +2026-06-24 06:19:28,105 - meas_pad: None +2026-06-24 06:19:28,105 - meas_resample: None +2026-06-24 06:19:28,105 - meas_add_source_size: None +2026-06-24 06:19:28,105 - meas_add_detector_blur: None +2026-06-24 06:19:28,105 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:19:28,105 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:19:28,106 - meas_add_poisson_noise: None +2026-06-24 06:19:28,106 - meas_export: None +2026-06-24 06:19:28,106 - probe_permute: None +2026-06-24 06:19:28,106 - probe_z_shift: None +2026-06-24 06:19:28,106 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:19:28,106 - pos_scan_flipT: None +2026-06-24 06:19:28,106 - pos_scan_affine: None +2026-06-24 06:19:28,106 - pos_scan_rand_std: 0.15 +2026-06-24 06:19:28,106 - obj_z_crop: None +2026-06-24 06:19:28,106 - obj_z_pad: None +2026-06-24 06:19:28,106 - obj_z_resample: None +2026-06-24 06:19:28,106 - meas_source: file +2026-06-24 06:19:28,106 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000052_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:19:28,106 - probe_source: simu +2026-06-24 06:19:28,106 - probe_params: None +2026-06-24 06:19:28,106 - pos_source: simu +2026-06-24 06:19:28,106 - pos_params: None +2026-06-24 06:19:28,106 - obj_source: simu +2026-06-24 06:19:28,106 - obj_params: None +2026-06-24 06:19:28,106 - tilt_source: simu +2026-06-24 06:19:28,106 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:19:28,106 - +2026-06-24 06:19:28,106 - ### Initializing cache ### +2026-06-24 06:19:28,106 - use_cached_obj = False +2026-06-24 06:19:28,106 - use_cached_probe = False +2026-06-24 06:19:28,106 - use_cached_pos = False +2026-06-24 06:19:28,106 - +2026-06-24 06:19:28,106 - ### Initializing measurements ### +2026-06-24 06:19:28,106 - Loading measurements from source = 'file' +2026-06-24 06:19:28,106 - Detected measurement file type = '.h5' +2026-06-24 06:19:28,185 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:19:28,185 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:19:28,187 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0052) +2026-06-24 06:19:28,187 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:19:28,187 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:19:28,189 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:19:28,189 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:19:28,189 - Normalizing by max of the 2D mean pattern intensity: 0.0038392297 +2026-06-24 06:19:28,190 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:19:28,191 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0152, 1.3665) +2026-06-24 06:19:28,192 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:19:28,193 - Pattern total int. statistics (min, mean, max) = (244.2957, 249.7896, 254.3355), with min/max = 96.1% +2026-06-24 06:19:28,194 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0152, 1.3665) +2026-06-24 06:19:28,194 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:19:28,194 - +2026-06-24 06:19:28,194 - ### Setting up calibration ### +2026-06-24 06:19:28,194 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:19:28,194 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:19:28,194 - Radius of fitted bright field disk (RBF) = 8.18 px with meas_Npix = 128 +2026-06-24 06:19:28,194 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1277 +2026-06-24 06:19:28,194 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:19:28,194 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:19:28,414 - Initial guess: center=(63.61, 63.60), radius=8.18, Gaussian blur std=0.50 +2026-06-24 06:19:28,425 - Final fit: center=(63.61, 63.60), radius=8.18, Gaussian blur std=0.56 +2026-06-24 06:19:28,425 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.24 px with Npix = 128 +2026-06-24 06:19:28,425 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:19:28,425 - +2026-06-24 06:19:28,425 - ### Setting init_variables dict ### +2026-06-24 06:19:28,425 - Derived values given input init_params: +2026-06-24 06:19:28,425 - kv = 80.0 kV +2026-06-24 06:19:28,425 - wavelength = 0.0418 Ang +2026-06-24 06:19:28,425 - conv_angle = 13.439705848693848 mrad +2026-06-24 06:19:28,425 - Npix = 128 px +2026-06-24 06:19:28,425 - dk = 0.0391 Ang^-1 +2026-06-24 06:19:28,425 - kMax = 2.5000 Ang^-1 +2026-06-24 06:19:28,425 - da = 1.6311 mrad +2026-06-24 06:19:28,425 - angleMax = 104.3929 mrad +2026-06-24 06:19:28,426 - RBF = 8.2395 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:19:28,426 - n_alpha = 7.7675 (# conv_angle) +2026-06-24 06:19:28,426 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:19:28,426 - Rayleigh-limited resolution = 1.8953 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:19:28,426 - Real space probe extent = 25.6000 Ang +2026-06-24 06:19:28,426 - +2026-06-24 06:19:28,426 - ### Initializing probe ### +2026-06-24 06:19:28,426 - Loading probe from source = 'simu' +2026-06-24 06:19:28,426 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:19:28,426 - Start simulating STEM probe +2026-06-24 06:19:28,426 - kv = 80.0 kV +2026-06-24 06:19:28,426 - wavelength = 0.0418 Ang +2026-06-24 06:19:28,426 - conv_angle = 13.439705848693848 mrad +2026-06-24 06:19:28,426 - Npix = 128 px +2026-06-24 06:19:28,426 - dk = 0.0391 Ang^-1 +2026-06-24 06:19:28,426 - kMax = 2.5000 Ang^-1 +2026-06-24 06:19:28,426 - alpha_max = 104.3929 mrad +2026-06-24 06:19:28,426 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:19:28,426 - Rayleigh-limited resolution = 1.8953 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:19:28,426 - Real space probe extent = 25.6000 Ang +2026-06-24 06:19:28,426 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:19:28,426 - ------------------------------------------------------------------------------------- +2026-06-24 06:19:28,426 - C1,0 C1 -238.0220 - Defocus (C10 = -df) +2026-06-24 06:19:28,426 - C1,2 A1 35.5520 31.72 2-fold astigmatism +2026-06-24 06:19:28,427 - C2,1 3*B2 -514.7860 204.43 Axial coma +2026-06-24 06:19:28,427 - C2,3 A2 -296.8940 238.11 3-fold astigmatism +2026-06-24 06:19:28,427 - C3,0 C3 4429709.5000 - Spherical aberration +2026-06-24 06:19:28,427 - C3,2 4*S3 -3023.6640 166.02 Axial star aberration +2026-06-24 06:19:28,427 - C3,4 A3 -7288.7440 339.93 4-fold astigmatism +2026-06-24 06:19:28,427 - C4,1 4*B4 -340220.0620 42.72 Axial coma(4th) +2026-06-24 06:19:28,427 - C4,3 4*D4 493508.3120 14.56 3-lobe aberration +2026-06-24 06:19:28,427 - C4,5 A4 -254363.0470 88.59 5-fold astigmatism +2026-06-24 06:19:28,427 - C5,0 C5 -457111136.0000 - Spherical aberration (5th) +2026-06-24 06:19:28,427 - C5,2 6*S5 8635936.0000 90.06 Axial star aberration(5th) +2026-06-24 06:19:28,427 - C5,4 6*R5 -18434290.0000 184.61 4-lobe aberration +2026-06-24 06:19:28,427 - C5,6 A5 10805769.0000 86.92 6-fold astigmatism +2026-06-24 06:19:28,430 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:19:28,430 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:19:28,430 - Creating 5 new probe modes from the major mode +2026-06-24 06:19:28,430 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:19:28,672 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:19:28,673 - Orthogonalizing 6 pmodes +2026-06-24 06:19:28,675 - Sorting 6 pmodes by their intensities +2026-06-24 06:19:28,676 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:19:28,676 - sum(|probe_data|**2) = 249.79, while meas_total_ints (min, mean, max) = (244.2957, 249.7896, 254.3355) +2026-06-24 06:19:28,676 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:19:28,676 - +2026-06-24 06:19:28,676 - ### Initializing probe positions ### +2026-06-24 06:19:28,676 - Loading probe positions from source = 'simu' +2026-06-24 06:19:28,676 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:19:28,676 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3559, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:19:28,677 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:19:28,679 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:19:28,679 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 06:19:28,679 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:19:28,679 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:19:28,679 - +2026-06-24 06:19:28,679 - ### Initializing object ### +2026-06-24 06:19:28,679 - Loading object from source = 'simu' +2026-06-24 06:19:28,679 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:19:28,680 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:19:28,680 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 06:19:28,681 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 06:19:28,681 - +2026-06-24 06:19:28,681 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:19:28,681 - omode_occu (omode) = float32, (1,) +2026-06-24 06:19:28,681 - +2026-06-24 06:19:28,681 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:19:28,681 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:19:28,681 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:19:28,682 - +2026-06-24 06:19:28,682 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:19:28,682 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:19:28,682 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:19:28,682 - +2026-06-24 06:19:28,682 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:19:28,682 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:19:28,682 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:19:28,682 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:19:28,682 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:19:28,682 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 06:19:28,682 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:19:28,682 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:19:28,682 - +2026-06-24 06:19:28,682 - ### Collecting reconstruction provenance ### +2026-06-24 06:19:28,682 - Reconstruction provenance is collected and initialized. +2026-06-24 06:19:28,682 - +2026-06-24 06:19:28,682 - ### Initializing loss function ### +2026-06-24 06:19:28,682 - Active loss types: +2026-06-24 06:19:28,682 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:19:28,683 - +2026-06-24 06:19:28,683 - ### Initializing constraint function ### +2026-06-24 06:19:28,683 - Active constraint types: +2026-06-24 06:19:28,683 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:19:28,683 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:19:28,683 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:19:28,683 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:19:28,683 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:19:28,683 - +2026-06-24 06:19:28,683 - ### Done initializing PtyRADSolver ### +2026-06-24 06:19:28,683 - +2026-06-24 06:19:28,810 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:19:28,810 - +2026-06-24 06:19:28,810 - ### Initializing PtychoModel model ### +2026-06-24 06:19:28,881 - ### PtychoModel optimizable variables ### +2026-06-24 06:19:28,881 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:19:28,882 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:19:28,882 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:19:28,882 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:19:28,882 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:19:28,882 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:19:28,882 - +2026-06-24 06:19:28,882 - ### Optimizable variables statitsics ### +2026-06-24 06:19:28,882 - Total measurement values : 4,194,304 +2026-06-24 06:19:28,882 - Total optimizing variables: 267,058 +2026-06-24 06:19:28,882 - Overdetermined ratio : 15.71 +2026-06-24 06:19:28,882 - +2026-06-24 06:19:28,882 - ### Model behavior ### +2026-06-24 06:19:28,882 - Tilt propagator : False +2026-06-24 06:19:28,882 - Change slice thickness : False +2026-06-24 06:19:28,882 - Detector blur : False +2026-06-24 06:19:28,882 - Preload data : True +2026-06-24 06:19:28,882 - On-the-fly meas padding : False +2026-06-24 06:19:28,882 - On-the-fly meas resample : False +2026-06-24 06:19:28,882 - On-the-fly simu match mode: None +2026-06-24 06:19:28,882 - +2026-06-24 06:19:28,923 - ### Done initializing PtychoModel model ### +2026-06-24 06:19:28,923 - +2026-06-24 06:19:28,923 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:19:28,923 - +2026-06-24 06:19:28,923 - ### Generating indices, batches, and output_path ### +2026-06-24 06:19:28,925 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:19:28,925 - Selecting indices with the 'full' mode +2026-06-24 06:19:29,388 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:19:29,461 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:19:29,461 - Original recon_dir_affixes = ['default'] +2026-06-24 06:19:29,461 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:19:29,467 - Path corrected for compatibility: +2026-06-24 06:19:29,467 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_166_C34_-7.29e+03_phi34_340_C41_-3.4e+05_phi41_42.7_C43_4.94e+05_phi43_14.6_C45_-2.54e+05_phi45_88.6_C50_-4.57e+08_C52_8.64e+06_phi52_90.1_C54_-1.84e+07_phi54_185_C56_1.08e+07_phi56_86.9 +2026-06-24 06:19:29,467 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9 +2026-06-24 06:19:29,469 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9' is generated! +2026-06-24 06:19:29,616 - +2026-06-24 06:19:29,617 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9/20260624_061929_ptyrad_log.txt ### +2026-06-24 06:19:29,618 - +2026-06-24 06:19:29,619 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:19:29,619 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:19:29,619 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:19:30,812 - Iter: 1, Total Loss: 1.1732, loss_single: 1.1732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 06:19:30,849 - Iter: 2, Total Loss: 1.1345, loss_single: 1.1345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:19:30,885 - Iter: 3, Total Loss: 1.1079, loss_single: 1.1079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:30,920 - Iter: 4, Total Loss: 1.0870, loss_single: 1.0870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:30,956 - Iter: 5, Total Loss: 1.0619, loss_single: 1.0619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:30,991 - Iter: 6, Total Loss: 1.0349, loss_single: 1.0349, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,026 - Iter: 7, Total Loss: 1.0066, loss_single: 1.0066, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,061 - Iter: 8, Total Loss: 0.9819, loss_single: 0.9819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,097 - Iter: 9, Total Loss: 0.9606, loss_single: 0.9606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,132 - Iter: 10, Total Loss: 0.9379, loss_single: 0.9379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,168 - Iter: 11, Total Loss: 0.9126, loss_single: 0.9126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,203 - Iter: 12, Total Loss: 0.8883, loss_single: 0.8883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,238 - Iter: 13, Total Loss: 0.8672, loss_single: 0.8672, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,273 - Iter: 14, Total Loss: 0.8430, loss_single: 0.8430, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,309 - Iter: 15, Total Loss: 0.8160, loss_single: 0.8160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,343 - Iter: 16, Total Loss: 0.7881, loss_single: 0.7881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:19:31,378 - Iter: 17, Total Loss: 0.7622, loss_single: 0.7622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,414 - Iter: 18, Total Loss: 0.7360, loss_single: 0.7360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,450 - Iter: 19, Total Loss: 0.7088, loss_single: 0.7088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:19:31,486 - Iter: 20, Total Loss: 0.6897, loss_single: 0.6897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,521 - Iter: 21, Total Loss: 0.6737, loss_single: 0.6737, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,557 - Iter: 22, Total Loss: 0.6572, loss_single: 0.6572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,592 - Iter: 23, Total Loss: 0.6414, loss_single: 0.6414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,627 - Iter: 24, Total Loss: 0.6234, loss_single: 0.6234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,662 - Iter: 25, Total Loss: 0.6060, loss_single: 0.6060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,697 - Iter: 26, Total Loss: 0.5909, loss_single: 0.5909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,733 - Iter: 27, Total Loss: 0.5777, loss_single: 0.5777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,772 - Iter: 28, Total Loss: 0.5675, loss_single: 0.5675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:19:31,807 - Iter: 29, Total Loss: 0.5603, loss_single: 0.5603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,842 - Iter: 30, Total Loss: 0.5521, loss_single: 0.5521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:19:31,877 - Iter: 31, Total Loss: 0.5425, loss_single: 0.5425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,913 - Iter: 32, Total Loss: 0.5337, loss_single: 0.5337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,948 - Iter: 33, Total Loss: 0.5271, loss_single: 0.5271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:31,984 - Iter: 34, Total Loss: 0.5232, loss_single: 0.5232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,019 - Iter: 35, Total Loss: 0.5202, loss_single: 0.5202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,054 - Iter: 36, Total Loss: 0.5155, loss_single: 0.5155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,090 - Iter: 37, Total Loss: 0.5105, loss_single: 0.5105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,126 - Iter: 38, Total Loss: 0.5058, loss_single: 0.5058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:19:32,161 - Iter: 39, Total Loss: 0.5020, loss_single: 0.5020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,197 - Iter: 40, Total Loss: 0.4998, loss_single: 0.4998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,233 - Iter: 41, Total Loss: 0.4981, loss_single: 0.4981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,268 - Iter: 42, Total Loss: 0.4964, loss_single: 0.4964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,303 - Iter: 43, Total Loss: 0.4949, loss_single: 0.4949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,338 - Iter: 44, Total Loss: 0.4933, loss_single: 0.4933, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:19:32,373 - Iter: 45, Total Loss: 0.4919, loss_single: 0.4919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,409 - Iter: 46, Total Loss: 0.4908, loss_single: 0.4908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:19:32,444 - 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052/c30_small__simulation_data4__sample_000052_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-238_C12_35.6_phi12_31.7_C21_-515_phi21_204_C23_-297_phi23_238_C30_4.43e+06_C32_-3.02e+03_phi32_.9/simulation_data4__sample_000052.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 13.439705848693848 + probe_aberrations: + C10: -238.0218048095703 + C12: 35.5522575378418 + C21: -514.78564453125 + C23: -296.8935852050781 + C30: 4429709.5 + C32: -3023.6640625 + C34: -7288.744140625 + C41: -340220.0625 + C43: 493508.3125 + C45: -254363.046875 + C50: -457111136.0 + C52: 8635936.0 + C54: -18434290.0 + C56: 10805769.0 + phi12: 31.717086486505167 + phi21: 204.43182389652372 + phi23: 238.10962888240235 + phi32: 166.017473966538 + phi34: 339.92971770788364 + phi41: 42.72019339031555 + phi43: 14.556934583690763 + phi45: 88.58806579925313 + phi52: 90.05639937645496 + phi54: 184.61409832162343 + phi56: 86.92253100033469 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3558799624443054 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data4__sample_000052_measurement.h5 + key: measurement + random_seed: 20262028 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data4__sample_000052 + 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4/20260624_062028_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:20:27,451 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:20:27,451 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:20:27,451 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:20:27,451 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:20:27,451 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:20:27,451 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:20:27,451 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:20:27,451 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:20:27,451 - +2026-06-24 06:20:27,558 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:20:27,558 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:20:27,558 - Accelerator.num_process = 1 +2026-06-24 06:20:27,558 - Accelerator.mixed_precision = no +2026-06-24 06:20:27,569 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:20:27,569 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:20:27,569 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:20:27,569 - +2026-06-24 06:20:27,569 - ### System information ### +2026-06-24 06:20:27,569 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:20:27,569 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:20:27,569 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:20:27,569 - Machine: x86_64 +2026-06-24 06:20:27,569 - Processor: x86_64 +2026-06-24 06:20:27,569 - Available CPU cores: 8 +2026-06-24 06:20:27,569 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:20:27,569 - +2026-06-24 06:20:27,569 - ### GPU information ### +2026-06-24 06:20:27,569 - CUDA Available: True +2026-06-24 06:20:27,569 - CUDA Version: 13.0 +2026-06-24 06:20:27,570 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:20:27,570 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:20:27,570 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:20:27,570 - In addition, Triton does not directly support Windows. +2026-06-24 06:20:27,570 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:20:27,586 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:20:27,586 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:20:27,586 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:20:27,586 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:20:27,586 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:20:27,586 - +2026-06-24 06:20:27,586 - ### Python information ### +2026-06-24 06:20:27,587 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:20:27,587 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:20:27,587 - +2026-06-24 06:20:27,587 - ### Packages information ### +2026-06-24 06:20:27,588 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:20:27,589 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:20:27,589 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:20:27,590 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:20:27,590 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:20:27,590 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:20:27,591 - +2026-06-24 06:20:27,591 - ### Loading params file ### +2026-06-24 06:20:27,591 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000002.yaml +2026-06-24 06:20:27,597 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:20:27,598 - Success! Params file validated and defaults applied. +2026-06-24 06:20:27,598 - +2026-06-24 06:20:27,598 - ### Setting GPU Device ### +2026-06-24 06:20:27,598 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:20:27,598 - +2026-06-24 06:20:27,598 - Random seed: 20262032 provided by params file +2026-06-24 06:20:27,599 - ### Initializing Initializer ### +2026-06-24 06:20:27,599 - init_params are displayed below: +2026-06-24 06:20:27,599 - random_seed: 20262032 +2026-06-24 06:20:27,599 - probe_illum_type: electron +2026-06-24 06:20:27,599 - probe_kv: 300.0 +2026-06-24 06:20:27,599 - probe_conv_angle: 17.182743072509766 +2026-06-24 06:20:27,599 - probe_aberrations: {'C10': -173.483, 'C12': 17.905, 'phi12': 158.983, 'C21': 293.464, 'phi21': 274.063, 'C23': 950.837, 'phi23': 202.688, 'C30': 2235734.75, 'C32': -2779.425, 'phi32': 26.185, 'C34': 1164.115, 'phi34': 295.269, 'C41': 259018.859, 'phi41': 270.638, 'C43': -262139.094, 'phi43': 2.437, 'C45': -493590.156, 'phi45': 156.322, 'C50': -426012256.0, 'C52': 1669883.875, 'phi52': 324.771, 'C54': 1316206.5, 'phi54': 138.262, 'C56': 16020230.0, 'phi56': 74.368} +2026-06-24 06:20:27,599 - beam_kev: None +2026-06-24 06:20:27,599 - probe_dRn: None +2026-06-24 06:20:27,599 - probe_Rn: None +2026-06-24 06:20:27,599 - probe_D_H: None +2026-06-24 06:20:27,599 - probe_D_FZP: None +2026-06-24 06:20:27,599 - probe_Ls: None +2026-06-24 06:20:27,599 - meas_Npix: 128 +2026-06-24 06:20:27,599 - pos_N_scans: 256 +2026-06-24 06:20:27,599 - pos_N_scan_slow: 16 +2026-06-24 06:20:27,599 - pos_N_scan_fast: 16 +2026-06-24 06:20:27,599 - pos_scan_step_size: 0.3959338068962097 +2026-06-24 06:20:27,599 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:20:27,599 - probe_pmode_max: 6 +2026-06-24 06:20:27,599 - probe_pmode_init_pows: [0.02] +2026-06-24 06:20:27,599 - obj_omode_max: 1 +2026-06-24 06:20:27,599 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:20:27,599 - obj_Nlayer: 1 +2026-06-24 06:20:27,599 - obj_slice_thickness: 20.0 +2026-06-24 06:20:27,599 - simu_Npix: None +2026-06-24 06:20:27,600 - simu_match_mode: None +2026-06-24 06:20:27,600 - meas_permute: None +2026-06-24 06:20:27,600 - meas_reshape: [256, 128, 128] +2026-06-24 06:20:27,600 - meas_flipT: [0, 0, 0] +2026-06-24 06:20:27,600 - meas_crop: None +2026-06-24 06:20:27,600 - meas_pad: None +2026-06-24 06:20:27,600 - meas_resample: None +2026-06-24 06:20:27,600 - meas_add_source_size: None +2026-06-24 06:20:27,600 - meas_add_detector_blur: None +2026-06-24 06:20:27,600 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:20:27,600 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:20:27,600 - meas_add_poisson_noise: None +2026-06-24 06:20:27,600 - meas_export: None +2026-06-24 06:20:27,600 - probe_permute: None +2026-06-24 06:20:27,600 - probe_z_shift: None +2026-06-24 06:20:27,600 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:20:27,600 - pos_scan_flipT: None +2026-06-24 06:20:27,600 - pos_scan_affine: None +2026-06-24 06:20:27,600 - pos_scan_rand_std: 0.15 +2026-06-24 06:20:27,600 - obj_z_crop: None +2026-06-24 06:20:27,600 - obj_z_pad: None +2026-06-24 06:20:27,600 - obj_z_resample: None +2026-06-24 06:20:27,600 - meas_source: file +2026-06-24 06:20:27,600 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000002_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:20:27,600 - probe_source: simu +2026-06-24 06:20:27,600 - probe_params: None +2026-06-24 06:20:27,600 - pos_source: simu +2026-06-24 06:20:27,600 - pos_params: None +2026-06-24 06:20:27,600 - obj_source: simu +2026-06-24 06:20:27,600 - obj_params: None +2026-06-24 06:20:27,600 - tilt_source: simu +2026-06-24 06:20:27,600 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:20:27,600 - +2026-06-24 06:20:27,600 - ### Initializing cache ### +2026-06-24 06:20:27,600 - use_cached_obj = False +2026-06-24 06:20:27,600 - use_cached_probe = False +2026-06-24 06:20:27,600 - use_cached_pos = False +2026-06-24 06:20:27,600 - +2026-06-24 06:20:27,600 - ### Initializing measurements ### +2026-06-24 06:20:27,601 - Loading measurements from source = 'file' +2026-06-24 06:20:27,601 - Detected measurement file type = '.h5' +2026-06-24 06:20:27,679 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:20:27,679 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:20:27,681 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0010) +2026-06-24 06:20:27,681 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:20:27,681 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:20:27,683 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:20:27,683 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:20:27,683 - Normalizing by max of the 2D mean pattern intensity: 0.00064960861 +2026-06-24 06:20:27,684 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:20:27,685 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0939, 1.6051) +2026-06-24 06:20:27,686 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:20:27,687 - Pattern total int. statistics (min, mean, max) = (1525.2953, 1538.1633, 1549.4758), with min/max = 98.4% +2026-06-24 06:20:27,688 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0939, 1.6051) +2026-06-24 06:20:27,688 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:20:27,688 - +2026-06-24 06:20:27,688 - ### Setting up calibration ### +2026-06-24 06:20:27,688 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:20:27,689 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:20:27,689 - Radius of fitted bright field disk (RBF) = 22.20 px with meas_Npix = 128 +2026-06-24 06:20:27,689 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3468 +2026-06-24 06:20:27,689 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:20:27,689 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:20:27,912 - Initial guess: center=(63.62, 63.64), radius=22.20, Gaussian blur std=0.50 +2026-06-24 06:20:27,923 - Final fit: center=(63.62, 63.64), radius=22.20, Gaussian blur std=0.55 +2026-06-24 06:20:27,923 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 22.34 px with Npix = 128 +2026-06-24 06:20:27,923 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:20:27,923 - +2026-06-24 06:20:27,923 - ### Setting init_variables dict ### +2026-06-24 06:20:27,923 - Derived values given input init_params: +2026-06-24 06:20:27,923 - kv = 300.0 kV +2026-06-24 06:20:27,923 - wavelength = 0.0197 Ang +2026-06-24 06:20:27,923 - conv_angle = 17.182743072509766 mrad +2026-06-24 06:20:27,923 - Npix = 128 px +2026-06-24 06:20:27,923 - dk = 0.0391 Ang^-1 +2026-06-24 06:20:27,923 - kMax = 2.5000 Ang^-1 +2026-06-24 06:20:27,923 - da = 0.7690 mrad +2026-06-24 06:20:27,923 - angleMax = 49.2187 mrad +2026-06-24 06:20:27,923 - RBF = 22.3430 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:20:27,923 - n_alpha = 2.8644 (# conv_angle) +2026-06-24 06:20:27,923 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:20:27,923 - Rayleigh-limited resolution = 0.6989 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:20:27,923 - Real space probe extent = 25.6000 Ang +2026-06-24 06:20:27,923 - +2026-06-24 06:20:27,923 - ### Initializing probe ### +2026-06-24 06:20:27,923 - Loading probe from source = 'simu' +2026-06-24 06:20:27,923 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:20:27,924 - Start simulating STEM probe +2026-06-24 06:20:27,924 - kv = 300.0 kV +2026-06-24 06:20:27,924 - wavelength = 0.0197 Ang +2026-06-24 06:20:27,924 - conv_angle = 17.182743072509766 mrad +2026-06-24 06:20:27,924 - Npix = 128 px +2026-06-24 06:20:27,924 - dk = 0.0391 Ang^-1 +2026-06-24 06:20:27,924 - kMax = 2.5000 Ang^-1 +2026-06-24 06:20:27,924 - alpha_max = 49.2187 mrad +2026-06-24 06:20:27,924 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:20:27,924 - Rayleigh-limited resolution = 0.6989 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:20:27,924 - Real space probe extent = 25.6000 Ang +2026-06-24 06:20:27,924 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:20:27,924 - ------------------------------------------------------------------------------------- +2026-06-24 06:20:27,924 - C1,0 C1 -173.4830 - Defocus (C10 = -df) +2026-06-24 06:20:27,924 - C1,2 A1 17.9050 158.98 2-fold astigmatism +2026-06-24 06:20:27,924 - C2,1 3*B2 293.4640 274.06 Axial coma +2026-06-24 06:20:27,924 - C2,3 A2 950.8370 202.69 3-fold astigmatism +2026-06-24 06:20:27,924 - C3,0 C3 2235734.7500 - Spherical aberration +2026-06-24 06:20:27,924 - C3,2 4*S3 -2779.4250 26.18 Axial star aberration +2026-06-24 06:20:27,924 - C3,4 A3 1164.1150 295.27 4-fold astigmatism +2026-06-24 06:20:27,924 - C4,1 4*B4 259018.8590 270.64 Axial coma(4th) +2026-06-24 06:20:27,924 - C4,3 4*D4 -262139.0940 2.44 3-lobe aberration +2026-06-24 06:20:27,924 - C4,5 A4 -493590.1560 156.32 5-fold astigmatism +2026-06-24 06:20:27,924 - C5,0 C5 -426012256.0000 - Spherical aberration (5th) +2026-06-24 06:20:27,924 - C5,2 6*S5 1669883.8750 324.77 Axial star aberration(5th) +2026-06-24 06:20:27,924 - C5,4 6*R5 1316206.5000 138.26 4-lobe aberration +2026-06-24 06:20:27,924 - C5,6 A5 16020230.0000 74.37 6-fold astigmatism +2026-06-24 06:20:27,927 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:20:27,927 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:20:27,927 - Creating 5 new probe modes from the major mode +2026-06-24 06:20:27,927 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:20:28,030 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:20:28,031 - Orthogonalizing 6 pmodes +2026-06-24 06:20:28,034 - Sorting 6 pmodes by their intensities +2026-06-24 06:20:28,034 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:20:28,035 - sum(|probe_data|**2) = 1538.16, while meas_total_ints (min, mean, max) = (1525.2953, 1538.1633, 1549.4758) +2026-06-24 06:20:28,035 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:20:28,035 - +2026-06-24 06:20:28,035 - ### Initializing probe positions ### +2026-06-24 06:20:28,035 - Loading probe positions from source = 'simu' +2026-06-24 06:20:28,035 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:20:28,035 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3959, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:20:28,036 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:20:28,037 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:20:28,037 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 45]) +2026-06-24 06:20:28,038 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 06:20:28,038 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:20:28,038 - +2026-06-24 06:20:28,038 - ### Initializing object ### +2026-06-24 06:20:28,038 - Loading object from source = 'simu' +2026-06-24 06:20:28,038 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:20:28,039 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:20:28,039 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-24 06:20:28,039 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-24 06:20:28,039 - +2026-06-24 06:20:28,039 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:20:28,040 - omode_occu (omode) = float32, (1,) +2026-06-24 06:20:28,040 - +2026-06-24 06:20:28,040 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:20:28,040 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:20:28,040 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:20:28,040 - +2026-06-24 06:20:28,040 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:20:28,040 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:20:28,040 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:20:28,040 - +2026-06-24 06:20:28,041 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:20:28,041 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:20:28,041 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:20:28,041 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:20:28,041 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:20:28,041 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-24 06:20:28,041 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:20:28,041 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:20:28,041 - +2026-06-24 06:20:28,041 - ### Collecting reconstruction provenance ### +2026-06-24 06:20:28,041 - Reconstruction provenance is collected and initialized. +2026-06-24 06:20:28,041 - +2026-06-24 06:20:28,041 - ### Initializing loss function ### +2026-06-24 06:20:28,041 - Active loss types: +2026-06-24 06:20:28,041 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:20:28,041 - +2026-06-24 06:20:28,041 - ### Initializing constraint function ### +2026-06-24 06:20:28,041 - Active constraint types: +2026-06-24 06:20:28,041 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:20:28,041 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:20:28,041 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:20:28,041 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:20:28,042 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:20:28,042 - +2026-06-24 06:20:28,042 - ### Done initializing PtyRADSolver ### +2026-06-24 06:20:28,042 - +2026-06-24 06:20:28,167 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:20:28,167 - +2026-06-24 06:20:28,167 - ### Initializing PtychoModel model ### +2026-06-24 06:20:28,239 - ### PtychoModel optimizable variables ### +2026-06-24 06:20:28,239 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:20:28,239 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:20:28,239 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:20:28,239 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:20:28,239 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:20:28,239 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:20:28,239 - +2026-06-24 06:20:28,240 - ### Optimizable variables statitsics ### +2026-06-24 06:20:28,240 - Total measurement values : 4,194,304 +2026-06-24 06:20:28,240 - Total optimizing variables: 269,320 +2026-06-24 06:20:28,240 - Overdetermined ratio : 15.57 +2026-06-24 06:20:28,240 - +2026-06-24 06:20:28,240 - ### Model behavior ### +2026-06-24 06:20:28,240 - Tilt propagator : False +2026-06-24 06:20:28,240 - Change slice thickness : False +2026-06-24 06:20:28,240 - Detector blur : False +2026-06-24 06:20:28,240 - Preload data : True +2026-06-24 06:20:28,240 - On-the-fly meas padding : False +2026-06-24 06:20:28,240 - On-the-fly meas resample : False +2026-06-24 06:20:28,240 - On-the-fly simu match mode: None +2026-06-24 06:20:28,240 - +2026-06-24 06:20:28,280 - ### Done initializing PtychoModel model ### +2026-06-24 06:20:28,281 - +2026-06-24 06:20:28,281 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:20:28,281 - +2026-06-24 06:20:28,281 - ### Generating indices, batches, and output_path ### +2026-06-24 06:20:28,282 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:20:28,282 - Selecting indices with the 'full' mode +2026-06-24 06:20:28,749 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:20:28,822 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:20:28,822 - Original recon_dir_affixes = ['default'] +2026-06-24 06:20:28,822 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:20:28,828 - Path corrected for compatibility: +2026-06-24 06:20:28,828 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26.2_C34_1.16e+03_phi34_295_C41_2.59e+05_phi41_271_C43_-2.62e+05_phi43_2.44_C45_-4.94e+05_phi45_156_C50_-4.26e+08_C52_1.67e+06_phi52_325_C54_1.32e+06_phi54_138_C56_1.6e+07_phi56_74.4 +2026-06-24 06:20:28,828 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4 +2026-06-24 06:20:28,829 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4' is generated! +2026-06-24 06:20:28,973 - +2026-06-24 06:20:28,974 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4/20260624_062028_ptyrad_log.txt ### +2026-06-24 06:20:28,974 - +2026-06-24 06:20:28,976 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:20:28,976 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:20:28,976 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:20:30,174 - Iter: 1, Total Loss: 0.4965, loss_single: 0.4965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:20:30,211 - Iter: 2, Total Loss: 0.4818, loss_single: 0.4818, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:20:30,246 - Iter: 3, Total Loss: 0.4692, loss_single: 0.4692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,281 - Iter: 4, Total Loss: 0.4581, loss_single: 0.4581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,317 - Iter: 5, Total Loss: 0.4475, loss_single: 0.4475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,351 - Iter: 6, Total Loss: 0.4359, loss_single: 0.4359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:30,387 - Iter: 7, Total Loss: 0.4237, loss_single: 0.4237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,422 - Iter: 8, Total Loss: 0.4132, loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,457 - Iter: 9, Total Loss: 0.4040, loss_single: 0.4040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,492 - Iter: 10, Total Loss: 0.3945, loss_single: 0.3945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,527 - Iter: 11, Total Loss: 0.3851, loss_single: 0.3851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:30,562 - Iter: 12, Total Loss: 0.3769, loss_single: 0.3769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,598 - Iter: 13, Total Loss: 0.3690, loss_single: 0.3690, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,634 - Iter: 14, Total Loss: 0.3607, loss_single: 0.3607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,669 - Iter: 15, Total Loss: 0.3525, loss_single: 0.3525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,704 - Iter: 16, Total Loss: 0.3437, loss_single: 0.3437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,739 - Iter: 17, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,774 - Iter: 18, Total Loss: 0.3260, loss_single: 0.3260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,809 - Iter: 19, Total Loss: 0.3179, loss_single: 0.3179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,844 - Iter: 20, Total Loss: 0.3125, loss_single: 0.3125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,879 - Iter: 21, Total Loss: 0.3091, loss_single: 0.3091, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:30,914 - Iter: 22, Total Loss: 0.3051, loss_single: 0.3051, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,949 - Iter: 23, Total Loss: 0.3010, loss_single: 0.3010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:30,984 - Iter: 24, Total Loss: 0.2971, loss_single: 0.2971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,019 - Iter: 25, Total Loss: 0.2923, loss_single: 0.2923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,055 - Iter: 26, Total Loss: 0.2876, loss_single: 0.2876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,090 - Iter: 27, Total Loss: 0.2833, loss_single: 0.2833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,125 - Iter: 28, Total Loss: 0.2791, loss_single: 0.2791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,160 - Iter: 29, Total Loss: 0.2752, loss_single: 0.2752, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,194 - Iter: 30, Total Loss: 0.2717, loss_single: 0.2717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,230 - Iter: 31, Total Loss: 0.2684, loss_single: 0.2684, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,268 - Iter: 32, Total Loss: 0.2655, loss_single: 0.2655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:20:31,304 - Iter: 33, Total Loss: 0.2628, loss_single: 0.2628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,339 - Iter: 34, Total Loss: 0.2604, loss_single: 0.2604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,374 - Iter: 35, Total Loss: 0.2582, loss_single: 0.2582, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,409 - Iter: 36, Total Loss: 0.2563, loss_single: 0.2563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,444 - Iter: 37, Total Loss: 0.2546, loss_single: 0.2546, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,479 - Iter: 38, Total Loss: 0.2530, loss_single: 0.2530, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,514 - Iter: 39, Total Loss: 0.2516, loss_single: 0.2516, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,549 - Iter: 40, Total Loss: 0.2504, loss_single: 0.2504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,587 - Iter: 41, Total Loss: 0.2492, loss_single: 0.2492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,623 - Iter: 42, Total Loss: 0.2482, loss_single: 0.2482, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,658 - Iter: 43, Total Loss: 0.2476, loss_single: 0.2476, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,693 - Iter: 44, Total Loss: 0.2471, loss_single: 0.2471, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,728 - Iter: 45, Total Loss: 0.2464, loss_single: 0.2464, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,764 - Iter: 46, Total Loss: 0.2457, loss_single: 0.2457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,800 - Iter: 47, Total Loss: 0.2451, loss_single: 0.2451, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:20:31,835 - Iter: 48, Total Loss: 0.2445, loss_single: 0.2445, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,870 - Iter: 49, Total Loss: 0.2440, loss_single: 0.2440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,905 - Iter: 50, Total Loss: 0.2436, loss_single: 0.2436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:31,940 - Iter: 51, Total Loss: 0.2432, loss_single: 0.2432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:31,975 - Iter: 52, Total Loss: 0.2429, loss_single: 0.2429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:32,010 - Iter: 53, Total Loss: 0.2426, loss_single: 0.2426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,045 - Iter: 54, Total Loss: 0.2422, loss_single: 0.2422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,080 - Iter: 55, Total Loss: 0.2419, loss_single: 0.2419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:32,115 - Iter: 56, Total Loss: 0.2416, loss_single: 0.2416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,150 - Iter: 57, Total Loss: 0.2414, loss_single: 0.2414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,185 - Iter: 58, Total Loss: 0.2412, loss_single: 0.2412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,220 - Iter: 59, Total Loss: 0.2410, loss_single: 0.2410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,256 - Iter: 60, Total Loss: 0.2407, loss_single: 0.2407, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,291 - Iter: 61, Total Loss: 0.2405, loss_single: 0.2405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,326 - Iter: 62, Total Loss: 0.2403, loss_single: 0.2403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:20:32,361 - Iter: 63, Total Loss: 0.2401, loss_single: 0.2401, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:20:32,396 - Iter: 64, 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4/simulation_data5__sample_000002.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 17.182743072509766 + probe_aberrations: + C10: -173.4830780029297 + C12: 17.904556274414062 + C21: 293.464111328125 + C23: 950.8368530273438 + C30: 2235734.75 + C32: -2779.4248046875 + C34: 1164.1146240234375 + C41: 259018.859375 + C43: -262139.09375 + C45: -493590.15625 + C50: -426012256.0 + C52: 1669883.875 + C54: 1316206.5 + C56: 16020230.0 + phi12: 158.98295285731515 + phi21: 274.0630616544325 + phi23: 202.6879809787711 + phi32: 26.18473058899051 + phi34: 295.26932370646136 + phi41: 270.6377217856711 + phi43: 2.4368354050460104 + phi45: 156.32238926992008 + phi52: 324.7709871092541 + phi54: 138.26209868922075 + phi56: 74.36802858882595 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3959338068962097 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000002_measurement.h5 + key: measurement + random_seed: 20262032 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000002 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000002/c30_small__simulation_data5__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-173_C12_17.9_phi12_159_C21_293_phi21_274_C23_951_phi23_203_C30_2.24e+06_C32_-2.78e+03_phi32_26..4/summary_convergence_iter0100.png new file mode 100644 index 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sha256:5608ba47361ed52f61a79387b4fadef99355faa599d406e49fb50f484ea92cdc +size 48095 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4/20260624_062157_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4/20260624_062157_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cdc2a0a09f87a8dfc42ea710defb334972e60b7e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4/20260624_062157_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:21:56,083 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:21:56,083 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:21:56,083 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:21:56,083 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:21:56,083 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:21:56,083 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:21:56,083 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:21:56,083 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:21:56,083 - +2026-06-24 06:21:56,189 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:21:56,189 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:21:56,190 - Accelerator.num_process = 1 +2026-06-24 06:21:56,190 - Accelerator.mixed_precision = no +2026-06-24 06:21:56,200 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:21:56,200 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:21:56,200 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:21:56,200 - +2026-06-24 06:21:56,200 - ### System information ### +2026-06-24 06:21:56,201 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:21:56,201 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:21:56,201 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:21:56,201 - Machine: x86_64 +2026-06-24 06:21:56,201 - Processor: x86_64 +2026-06-24 06:21:56,201 - Available CPU cores: 8 +2026-06-24 06:21:56,201 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:21:56,201 - +2026-06-24 06:21:56,201 - ### GPU information ### +2026-06-24 06:21:56,201 - CUDA Available: True +2026-06-24 06:21:56,201 - CUDA Version: 13.0 +2026-06-24 06:21:56,201 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:21:56,201 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:21:56,201 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:21:56,202 - In addition, Triton does not directly support Windows. +2026-06-24 06:21:56,202 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:21:56,216 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:21:56,216 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:21:56,216 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:21:56,216 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:21:56,216 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:21:56,216 - +2026-06-24 06:21:56,217 - ### Python information ### +2026-06-24 06:21:56,218 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:21:56,218 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:21:56,218 - +2026-06-24 06:21:56,218 - ### Packages information ### +2026-06-24 06:21:56,220 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:21:56,220 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:21:56,221 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:21:56,222 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:21:56,222 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:21:56,222 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:21:56,222 - +2026-06-24 06:21:56,222 - ### Loading params file ### +2026-06-24 06:21:56,222 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000008.yaml +2026-06-24 06:21:56,229 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:21:56,230 - Success! Params file validated and defaults applied. +2026-06-24 06:21:56,230 - +2026-06-24 06:21:56,230 - ### Setting GPU Device ### +2026-06-24 06:21:56,230 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:21:56,230 - +2026-06-24 06:21:56,230 - Random seed: 20262038 provided by params file +2026-06-24 06:21:56,230 - ### Initializing Initializer ### +2026-06-24 06:21:56,230 - init_params are displayed below: +2026-06-24 06:21:56,230 - random_seed: 20262038 +2026-06-24 06:21:56,231 - probe_illum_type: electron +2026-06-24 06:21:56,231 - probe_kv: 60.0 +2026-06-24 06:21:56,231 - probe_conv_angle: 11.723858833312988 +2026-06-24 06:21:56,231 - probe_aberrations: {'C10': -423.72, 'C12': -40.58, 'phi12': 81.725, 'C21': 668.758, 'phi21': 207.825, 'C23': -413.841, 'phi23': 223.367, 'C30': 308381.25, 'C32': -8342.567, 'phi32': 36.72, 'C34': -10629.316, 'phi34': 336.444, 'C41': -37420.758, 'phi41': 9.248, 'C43': 285405.375, 'phi43': 344.15, 'C45': -258868.391, 'phi45': 141.736, 'C50': 304288288.0, 'C52': 8256316.0, 'phi52': 98.504, 'C54': 10389593.0, 'phi54': 260.232, 'C56': -10415177.0, 'phi56': 53.433} +2026-06-24 06:21:56,231 - beam_kev: None +2026-06-24 06:21:56,231 - probe_dRn: None +2026-06-24 06:21:56,231 - probe_Rn: None +2026-06-24 06:21:56,231 - probe_D_H: None +2026-06-24 06:21:56,231 - probe_D_FZP: None +2026-06-24 06:21:56,231 - probe_Ls: None +2026-06-24 06:21:56,231 - meas_Npix: 128 +2026-06-24 06:21:56,231 - pos_N_scans: 256 +2026-06-24 06:21:56,231 - pos_N_scan_slow: 16 +2026-06-24 06:21:56,231 - pos_N_scan_fast: 16 +2026-06-24 06:21:56,231 - pos_scan_step_size: 0.5094919800758362 +2026-06-24 06:21:56,231 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:21:56,231 - probe_pmode_max: 6 +2026-06-24 06:21:56,231 - probe_pmode_init_pows: [0.02] +2026-06-24 06:21:56,231 - obj_omode_max: 1 +2026-06-24 06:21:56,231 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:21:56,231 - obj_Nlayer: 1 +2026-06-24 06:21:56,231 - obj_slice_thickness: 20.0 +2026-06-24 06:21:56,231 - simu_Npix: None +2026-06-24 06:21:56,231 - simu_match_mode: None +2026-06-24 06:21:56,231 - meas_permute: None +2026-06-24 06:21:56,231 - meas_reshape: [256, 128, 128] +2026-06-24 06:21:56,231 - meas_flipT: [0, 0, 0] +2026-06-24 06:21:56,231 - meas_crop: None +2026-06-24 06:21:56,231 - meas_pad: None +2026-06-24 06:21:56,231 - meas_resample: None +2026-06-24 06:21:56,231 - meas_add_source_size: None +2026-06-24 06:21:56,231 - meas_add_detector_blur: None +2026-06-24 06:21:56,231 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:21:56,231 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:21:56,231 - meas_add_poisson_noise: None +2026-06-24 06:21:56,231 - meas_export: None +2026-06-24 06:21:56,231 - probe_permute: None +2026-06-24 06:21:56,231 - probe_z_shift: None +2026-06-24 06:21:56,232 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:21:56,232 - pos_scan_flipT: None +2026-06-24 06:21:56,232 - pos_scan_affine: None +2026-06-24 06:21:56,232 - pos_scan_rand_std: 0.15 +2026-06-24 06:21:56,232 - obj_z_crop: None +2026-06-24 06:21:56,232 - obj_z_pad: None +2026-06-24 06:21:56,232 - obj_z_resample: None +2026-06-24 06:21:56,232 - meas_source: file +2026-06-24 06:21:56,232 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000008_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:21:56,232 - probe_source: simu +2026-06-24 06:21:56,232 - probe_params: None +2026-06-24 06:21:56,232 - pos_source: simu +2026-06-24 06:21:56,232 - pos_params: None +2026-06-24 06:21:56,232 - obj_source: simu +2026-06-24 06:21:56,232 - obj_params: None +2026-06-24 06:21:56,232 - tilt_source: simu +2026-06-24 06:21:56,232 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:21:56,232 - +2026-06-24 06:21:56,232 - ### Initializing cache ### +2026-06-24 06:21:56,232 - use_cached_obj = False +2026-06-24 06:21:56,232 - use_cached_probe = False +2026-06-24 06:21:56,232 - use_cached_pos = False +2026-06-24 06:21:56,232 - +2026-06-24 06:21:56,232 - ### Initializing measurements ### +2026-06-24 06:21:56,232 - Loading measurements from source = 'file' +2026-06-24 06:21:56,232 - Detected measurement file type = '.h5' +2026-06-24 06:21:56,312 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:21:56,312 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:21:56,314 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0100) +2026-06-24 06:21:56,314 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:21:56,314 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:21:56,316 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:21:56,316 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:21:56,317 - Normalizing by max of the 2D mean pattern intensity: 0.0076671857 +2026-06-24 06:21:56,317 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:21:56,318 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0079, 1.3058) +2026-06-24 06:21:56,319 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:21:56,320 - Pattern total int. statistics (min, mean, max) = (129.3973, 129.9690, 130.4746), with min/max = 99.2% +2026-06-24 06:21:56,322 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0079, 1.3058) +2026-06-24 06:21:56,322 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:21:56,322 - +2026-06-24 06:21:56,322 - ### Setting up calibration ### +2026-06-24 06:21:56,322 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:21:56,322 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:21:56,322 - Radius of fitted bright field disk (RBF) = 6.08 px with meas_Npix = 128 +2026-06-24 06:21:56,322 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0949 +2026-06-24 06:21:56,322 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:21:56,322 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:21:56,544 - Initial guess: center=(63.64, 63.61), radius=6.08, Gaussian blur std=0.50 +2026-06-24 06:21:56,553 - Final fit: center=(63.64, 63.61), radius=6.08, Gaussian blur std=0.53 +2026-06-24 06:21:56,553 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.17 px with Npix = 128 +2026-06-24 06:21:56,553 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:21:56,553 - +2026-06-24 06:21:56,553 - ### Setting init_variables dict ### +2026-06-24 06:21:56,553 - Derived values given input init_params: +2026-06-24 06:21:56,553 - kv = 60.0 kV +2026-06-24 06:21:56,553 - wavelength = 0.0487 Ang +2026-06-24 06:21:56,553 - conv_angle = 11.723858833312988 mrad +2026-06-24 06:21:56,553 - Npix = 128 px +2026-06-24 06:21:56,553 - dk = 0.0391 Ang^-1 +2026-06-24 06:21:56,553 - kMax = 2.5000 Ang^-1 +2026-06-24 06:21:56,553 - da = 1.9008 mrad +2026-06-24 06:21:56,553 - angleMax = 121.6515 mrad +2026-06-24 06:21:56,553 - RBF = 6.1678 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:21:56,553 - n_alpha = 10.3764 (# conv_angle) +2026-06-24 06:21:56,553 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:21:56,553 - Rayleigh-limited resolution = 2.5318 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:21:56,553 - Real space probe extent = 25.6000 Ang +2026-06-24 06:21:56,553 - +2026-06-24 06:21:56,553 - ### Initializing probe ### +2026-06-24 06:21:56,553 - Loading probe from source = 'simu' +2026-06-24 06:21:56,553 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:21:56,554 - Start simulating STEM probe +2026-06-24 06:21:56,554 - kv = 60.0 kV +2026-06-24 06:21:56,554 - wavelength = 0.0487 Ang +2026-06-24 06:21:56,554 - conv_angle = 11.723858833312988 mrad +2026-06-24 06:21:56,554 - Npix = 128 px +2026-06-24 06:21:56,554 - dk = 0.0391 Ang^-1 +2026-06-24 06:21:56,554 - kMax = 2.5000 Ang^-1 +2026-06-24 06:21:56,554 - alpha_max = 121.6515 mrad +2026-06-24 06:21:56,554 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:21:56,554 - Rayleigh-limited resolution = 2.5318 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:21:56,554 - Real space probe extent = 25.6000 Ang +2026-06-24 06:21:56,554 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:21:56,554 - ------------------------------------------------------------------------------------ +2026-06-24 06:21:56,554 - C1,0 C1 -423.7200 - Defocus (C10 = -df) +2026-06-24 06:21:56,554 - C1,2 A1 -40.5800 81.72 2-fold astigmatism +2026-06-24 06:21:56,554 - C2,1 3*B2 668.7580 207.82 Axial coma +2026-06-24 06:21:56,554 - C2,3 A2 -413.8410 223.37 3-fold astigmatism +2026-06-24 06:21:56,554 - C3,0 C3 308381.2500 - Spherical aberration +2026-06-24 06:21:56,554 - C3,2 4*S3 -8342.5670 36.72 Axial star aberration +2026-06-24 06:21:56,554 - C3,4 A3 -10629.3160 336.44 4-fold astigmatism +2026-06-24 06:21:56,554 - C4,1 4*B4 -37420.7580 9.25 Axial coma(4th) +2026-06-24 06:21:56,554 - C4,3 4*D4 285405.3750 344.15 3-lobe aberration +2026-06-24 06:21:56,554 - C4,5 A4 -258868.3910 141.74 5-fold astigmatism +2026-06-24 06:21:56,554 - C5,0 C5 304288288.0000 - Spherical aberration (5th) +2026-06-24 06:21:56,554 - C5,2 6*S5 8256316.0000 98.50 Axial star aberration(5th) +2026-06-24 06:21:56,554 - C5,4 6*R5 10389593.0000 260.23 4-lobe aberration +2026-06-24 06:21:56,554 - C5,6 A5 -10415177.0000 53.43 6-fold astigmatism +2026-06-24 06:21:56,557 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:21:56,557 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:21:56,557 - Creating 5 new probe modes from the major mode +2026-06-24 06:21:56,557 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:21:56,654 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:21:56,655 - Orthogonalizing 6 pmodes +2026-06-24 06:21:56,657 - Sorting 6 pmodes by their intensities +2026-06-24 06:21:56,658 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:21:56,658 - sum(|probe_data|**2) = 129.97, while meas_total_ints (min, mean, max) = (129.3973, 129.9690, 130.4746) +2026-06-24 06:21:56,658 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:21:56,658 - +2026-06-24 06:21:56,658 - ### Initializing probe positions ### +2026-06-24 06:21:56,658 - Loading probe positions from source = 'simu' +2026-06-24 06:21:56,658 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:21:56,658 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5095, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:21:56,659 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:21:56,660 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:21:56,661 - crop_pos 1st and last px coords (y,x) = ([17, 17], [55, 55]) +2026-06-24 06:21:56,661 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:21:56,661 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:21:56,661 - +2026-06-24 06:21:56,661 - ### Initializing object ### +2026-06-24 06:21:56,661 - Loading object from source = 'simu' +2026-06-24 06:21:56,661 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:21:56,662 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:21:56,662 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 200, 200) +2026-06-24 06:21:56,663 - object extent (Z, Y, X) (Ang) = [20. 40. 40.] +2026-06-24 06:21:56,663 - +2026-06-24 06:21:56,663 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:21:56,663 - omode_occu (omode) = float32, (1,) +2026-06-24 06:21:56,663 - +2026-06-24 06:21:56,663 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:21:56,663 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 06:21:56,664 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:21:56,664 - +2026-06-24 06:21:56,664 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:21:56,664 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:21:56,664 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:21:56,664 - +2026-06-24 06:21:56,664 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:21:56,664 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:21:56,664 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:21:56,664 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:21:56,664 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:21:56,664 - crop positions (yx_min=[17 17], yx_max=[183 183]) are well contained inside object canvas (Ny,Nx) = (200, 200). +2026-06-24 06:21:56,664 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:21:56,664 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:21:56,664 - +2026-06-24 06:21:56,664 - ### Collecting reconstruction provenance ### +2026-06-24 06:21:56,664 - Reconstruction provenance is collected and initialized. +2026-06-24 06:21:56,664 - +2026-06-24 06:21:56,664 - ### Initializing loss function ### +2026-06-24 06:21:56,664 - Active loss types: +2026-06-24 06:21:56,665 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:21:56,665 - +2026-06-24 06:21:56,665 - ### Initializing constraint function ### +2026-06-24 06:21:56,665 - Active constraint types: +2026-06-24 06:21:56,665 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:21:56,665 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:21:56,665 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:21:56,665 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:21:56,665 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:21:56,665 - +2026-06-24 06:21:56,665 - ### Done initializing PtyRADSolver ### +2026-06-24 06:21:56,665 - +2026-06-24 06:21:56,790 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:21:56,790 - +2026-06-24 06:21:56,790 - ### Initializing PtychoModel model ### +2026-06-24 06:21:56,861 - ### PtychoModel optimizable variables ### +2026-06-24 06:21:56,861 - obja : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:21:56,862 - objp : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:21:56,862 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:21:56,862 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:21:56,862 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:21:56,862 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:21:56,862 - +2026-06-24 06:21:56,862 - ### Optimizable variables statitsics ### +2026-06-24 06:21:56,862 - Total measurement values : 4,194,304 +2026-06-24 06:21:56,862 - Total optimizing variables: 277,120 +2026-06-24 06:21:56,862 - Overdetermined ratio : 15.14 +2026-06-24 06:21:56,862 - +2026-06-24 06:21:56,862 - ### Model behavior ### +2026-06-24 06:21:56,862 - Tilt propagator : False +2026-06-24 06:21:56,862 - Change slice thickness : False +2026-06-24 06:21:56,862 - Detector blur : False +2026-06-24 06:21:56,862 - Preload data : True +2026-06-24 06:21:56,862 - On-the-fly meas padding : False +2026-06-24 06:21:56,862 - On-the-fly meas resample : False +2026-06-24 06:21:56,862 - On-the-fly simu match mode: None +2026-06-24 06:21:56,862 - +2026-06-24 06:21:56,904 - ### Done initializing PtychoModel model ### +2026-06-24 06:21:56,904 - +2026-06-24 06:21:56,904 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:21:56,904 - +2026-06-24 06:21:56,904 - ### Generating indices, batches, and output_path ### +2026-06-24 06:21:56,906 - d90 = 65.000 px or 13.000 Ang +2026-06-24 06:21:56,906 - Selecting indices with the 'full' mode +2026-06-24 06:21:57,364 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:21:57,443 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:21:57,443 - Original recon_dir_affixes = ['default'] +2026-06-24 06:21:57,443 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:21:57,449 - Path corrected for compatibility: +2026-06-24 06:21:57,450 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_36.7_C34_-1.06e+04_phi34_336_C41_-3.74e+04_phi41_9.25_C43_2.85e+05_phi43_344_C45_-2.59e+05_phi45_142_C50_3.04e+08_C52_8.26e+06_phi52_98.5_C54_1.04e+07_phi54_260_C56_-1.04e+07_phi56_53.4 +2026-06-24 06:21:57,450 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4 +2026-06-24 06:21:57,451 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4' is generated! +2026-06-24 06:21:57,603 - +2026-06-24 06:21:57,605 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4/20260624_062157_ptyrad_log.txt ### +2026-06-24 06:21:57,605 - +2026-06-24 06:21:57,606 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:21:57,606 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:21:57,606 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:21:58,799 - Iter: 1, Total Loss: 1.2933, loss_single: 1.2933, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:21:58,835 - Iter: 2, Total Loss: 1.2214, loss_single: 1.2214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:21:58,871 - Iter: 3, Total Loss: 1.1642, loss_single: 1.1642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:58,906 - Iter: 4, Total Loss: 1.0983, loss_single: 1.0983, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:58,942 - Iter: 5, Total Loss: 1.0318, loss_single: 1.0318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:58,977 - Iter: 6, Total Loss: 0.9767, loss_single: 0.9767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,012 - Iter: 7, Total Loss: 0.9245, loss_single: 0.9245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,047 - Iter: 8, Total Loss: 0.8707, loss_single: 0.8707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,082 - Iter: 9, Total Loss: 0.8107, loss_single: 0.8107, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,117 - Iter: 10, Total Loss: 0.7473, loss_single: 0.7473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:21:59,152 - Iter: 11, Total Loss: 0.6906, loss_single: 0.6906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,187 - Iter: 12, Total Loss: 0.6353, loss_single: 0.6353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,222 - Iter: 13, Total Loss: 0.5829, loss_single: 0.5829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,257 - Iter: 14, Total Loss: 0.5494, loss_single: 0.5494, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,292 - Iter: 15, Total Loss: 0.5164, loss_single: 0.5164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,328 - Iter: 16, Total Loss: 0.4792, loss_single: 0.4792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,362 - Iter: 17, Total Loss: 0.4516, loss_single: 0.4516, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:21:59,397 - Iter: 18, Total Loss: 0.4201, loss_single: 0.4201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,433 - Iter: 19, Total Loss: 0.3951, loss_single: 0.3951, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,468 - Iter: 20, Total Loss: 0.3748, loss_single: 0.3748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,503 - Iter: 21, Total Loss: 0.3576, loss_single: 0.3576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,539 - Iter: 22, Total Loss: 0.3465, loss_single: 0.3465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,574 - Iter: 23, Total Loss: 0.3339, loss_single: 0.3339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,609 - Iter: 24, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,644 - Iter: 25, Total Loss: 0.3170, loss_single: 0.3170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,679 - Iter: 26, Total Loss: 0.3109, loss_single: 0.3109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,714 - Iter: 27, Total Loss: 0.3069, loss_single: 0.3069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,749 - Iter: 28, Total Loss: 0.3042, loss_single: 0.3042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,784 - Iter: 29, Total Loss: 0.3021, loss_single: 0.3021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,820 - Iter: 30, Total Loss: 0.3000, loss_single: 0.3000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,854 - Iter: 31, Total Loss: 0.2988, loss_single: 0.2988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:21:59,889 - Iter: 32, Total Loss: 0.2979, loss_single: 0.2979, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,925 - Iter: 33, Total Loss: 0.2970, loss_single: 0.2970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,960 - Iter: 34, Total Loss: 0.2964, loss_single: 0.2964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:21:59,999 - Iter: 35, Total Loss: 0.2958, loss_single: 0.2958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:22:00,034 - Iter: 36, Total Loss: 0.2953, loss_single: 0.2953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,069 - Iter: 37, Total Loss: 0.2948, loss_single: 0.2948, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,104 - Iter: 38, Total Loss: 0.2945, loss_single: 0.2945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,139 - Iter: 39, Total Loss: 0.2941, loss_single: 0.2941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,174 - Iter: 40, Total Loss: 0.2938, loss_single: 0.2938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,212 - Iter: 41, Total Loss: 0.2936, loss_single: 0.2936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,247 - Iter: 42, Total Loss: 0.2934, loss_single: 0.2934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,282 - Iter: 43, Total Loss: 0.2931, loss_single: 0.2931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,317 - Iter: 44, Total Loss: 0.2930, loss_single: 0.2930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,353 - Iter: 45, Total Loss: 0.2928, loss_single: 0.2928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,388 - Iter: 46, Total Loss: 0.2926, loss_single: 0.2926, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:00,423 - Iter: 47, Total Loss: 0.2925, loss_single: 0.2925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,458 - Iter: 48, Total Loss: 0.2923, loss_single: 0.2923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,493 - Iter: 49, Total Loss: 0.2921, loss_single: 0.2921, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,528 - Iter: 50, Total Loss: 0.2920, loss_single: 0.2920, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,564 - Iter: 51, Total Loss: 0.2919, loss_single: 0.2919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,599 - Iter: 52, Total Loss: 0.2917, loss_single: 0.2917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,634 - Iter: 53, Total Loss: 0.2916, loss_single: 0.2916, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,669 - Iter: 54, Total Loss: 0.2915, loss_single: 0.2915, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,704 - Iter: 55, Total Loss: 0.2914, loss_single: 0.2914, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:00,739 - Iter: 56, Total Loss: 0.2913, loss_single: 0.2913, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,775 - Iter: 57, Total Loss: 0.2912, loss_single: 0.2912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,810 - Iter: 58, Total Loss: 0.2911, loss_single: 0.2911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,845 - Iter: 59, Total Loss: 0.2910, loss_single: 0.2910, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,880 - Iter: 60, Total Loss: 0.2909, loss_single: 0.2909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,916 - Iter: 61, Total Loss: 0.2908, loss_single: 0.2908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,951 - Iter: 62, Total Loss: 0.2907, loss_single: 0.2907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:00,986 - Iter: 63, Total Loss: 0.2906, loss_single: 0.2906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,021 - Iter: 64, 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in 0.035 sec +2026-06-24 06:22:01,231 - Iter: 70, Total Loss: 0.2899, loss_single: 0.2899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:01,266 - Iter: 71, Total Loss: 0.2897, loss_single: 0.2897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,301 - Iter: 72, Total Loss: 0.2897, loss_single: 0.2897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,337 - Iter: 73, Total Loss: 0.2896, loss_single: 0.2896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,371 - Iter: 74, Total Loss: 0.2895, loss_single: 0.2895, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:01,406 - Iter: 75, Total Loss: 0.2894, loss_single: 0.2894, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,652 - Iter: 82, Total Loss: 0.2888, loss_single: 0.2888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,687 - Iter: 83, Total Loss: 0.2888, loss_single: 0.2888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,723 - Iter: 84, Total Loss: 0.2887, loss_single: 0.2887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,758 - Iter: 85, Total Loss: 0.2886, loss_single: 0.2886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,793 - Iter: 86, Total Loss: 0.2886, loss_single: 0.2886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,829 - Iter: 87, Total Loss: 0.2885, loss_single: 0.2885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,864 - Iter: 88, Total Loss: 0.2884, loss_single: 0.2884, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,900 - Iter: 89, Total Loss: 0.2883, loss_single: 0.2883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,935 - Iter: 90, Total Loss: 0.2882, loss_single: 0.2882, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:01,969 - Iter: 91, Total Loss: 0.2881, loss_single: 0.2881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:02,005 - Iter: 92, Total Loss: 0.2880, loss_single: 0.2880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,040 - Iter: 93, Total Loss: 0.2879, loss_single: 0.2879, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,075 - Iter: 94, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,110 - Iter: 95, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,145 - Iter: 96, Total Loss: 0.2877, loss_single: 0.2877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,180 - Iter: 97, Total Loss: 0.2876, loss_single: 0.2876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,215 - Iter: 98, Total Loss: 0.2876, loss_single: 0.2876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,250 - Iter: 99, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:22:02,285 - Iter: 100, Total Loss: 0.2874, loss_single: 0.2874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:22:02,397 - Saving summary figures for iter 100 +2026-06-24 06:22:05,990 - ### Finished 100 iterations, averaged iter_t = 0.038775 with std = 0.040 ### +2026-06-24 06:22:05,990 - +2026-06-24 06:22:05,990 - ### The PtyRADSolver is finished in 9.201 sec ### +2026-06-24 06:22:05,991 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008/c30_small__simulation_data5__sample_000008_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-40.6_phi12_81.7_C21_669_phi21_208_C23_-414_phi23_223_C30_3.08e+05_C32_-8.34e+03_phi32_.4/simulation_data5__sample_000008.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 11.723858833312988 + probe_aberrations: + C10: -423.7198486328125 + C12: -40.58011245727539 + C21: 668.7578125 + C23: -413.8406677246094 + C30: 308381.25 + C32: -8342.5673828125 + C34: -10629.31640625 + C41: -37420.7578125 + C43: 285405.375 + C45: -258868.390625 + C50: 304288288.0 + C52: 8256316.0 + C54: 10389593.0 + C56: -10415177.0 + phi12: 81.72483900422503 + phi21: 207.82495259315934 + phi23: 223.36687046460494 + phi32: 36.7200190535265 + phi34: 336.44413557064274 + phi41: 9.248078697518203 + phi43: 344.1496544639276 + phi45: 141.73634271243944 + phi52: 98.50407979476428 + phi54: 260.23192858515665 + phi56: 53.43337242423723 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5094919800758362 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000008_measurement.h5 + key: measurement + random_seed: 20262038 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000008 + 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sha256:24a8a549848e70856635337104873ce9b9f5573b4d8fb2ddfa316bde68e9b232 +size 48316 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/20260624_062311_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/20260624_062311_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..3e1d01e34528138581c6f19f5c94a32bd9670028 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/20260624_062311_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:23:09,642 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:23:09,642 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:23:09,642 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:23:09,642 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:23:09,642 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:23:09,642 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:23:09,642 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:23:09,642 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:23:09,642 - +2026-06-24 06:23:09,753 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:23:09,753 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:23:09,753 - Accelerator.num_process = 1 +2026-06-24 06:23:09,754 - Accelerator.mixed_precision = no +2026-06-24 06:23:09,764 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:23:09,764 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:23:09,764 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:23:09,765 - +2026-06-24 06:23:09,765 - ### System information ### +2026-06-24 06:23:09,765 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:23:09,765 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:23:09,765 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:23:09,765 - Machine: x86_64 +2026-06-24 06:23:09,765 - Processor: x86_64 +2026-06-24 06:23:09,765 - Available CPU cores: 8 +2026-06-24 06:23:09,765 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:23:09,765 - +2026-06-24 06:23:09,765 - ### GPU information ### +2026-06-24 06:23:09,765 - CUDA Available: True +2026-06-24 06:23:09,765 - CUDA Version: 13.0 +2026-06-24 06:23:09,765 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:23:09,766 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:23:09,766 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:23:09,766 - In addition, Triton does not directly support Windows. +2026-06-24 06:23:09,766 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:23:09,781 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:23:09,781 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:23:09,781 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:23:09,781 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:23:09,781 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:23:09,781 - +2026-06-24 06:23:09,781 - ### Python information ### +2026-06-24 06:23:09,783 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:23:09,783 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:23:09,783 - +2026-06-24 06:23:09,783 - ### Packages information ### +2026-06-24 06:23:09,784 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:23:09,785 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:23:09,785 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:23:09,786 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:23:09,786 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:23:09,786 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:23:09,786 - +2026-06-24 06:23:09,786 - ### Loading params file ### +2026-06-24 06:23:09,786 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000013.yaml +2026-06-24 06:23:09,793 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:23:09,794 - Success! Params file validated and defaults applied. +2026-06-24 06:23:09,794 - +2026-06-24 06:23:09,794 - ### Setting GPU Device ### +2026-06-24 06:23:09,794 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:23:09,794 - +2026-06-24 06:23:09,794 - Random seed: 20262043 provided by params file +2026-06-24 06:23:09,795 - ### Initializing Initializer ### +2026-06-24 06:23:09,795 - init_params are displayed below: +2026-06-24 06:23:09,795 - random_seed: 20262043 +2026-06-24 06:23:09,795 - probe_illum_type: electron +2026-06-24 06:23:09,795 - probe_kv: 160.0 +2026-06-24 06:23:09,795 - probe_conv_angle: 11.648499488830566 +2026-06-24 06:23:09,795 - probe_aberrations: {'C10': 37.288, 'C12': 10.519, 'phi12': 229.437, 'C21': -81.635, 'phi21': 312.413, 'C23': -804.886, 'phi23': 342.844, 'C30': 4285037.5, 'C32': -8719.27, 'phi32': 65.872, 'C34': 10792.896, 'phi34': 175.703, 'C41': 489775.031, 'phi41': 290.652, 'C43': -370250.719, 'phi43': 3.144, 'C45': -427713.719, 'phi45': 231.835, 'C50': -395111360.0, 'C52': -6819994.5, 'phi52': 152.754, 'C54': -11792731.0, 'phi54': 238.43, 'C56': 1392187.625, 'phi56': 23.569} +2026-06-24 06:23:09,795 - beam_kev: None +2026-06-24 06:23:09,795 - probe_dRn: None +2026-06-24 06:23:09,795 - probe_Rn: None +2026-06-24 06:23:09,795 - probe_D_H: None +2026-06-24 06:23:09,795 - probe_D_FZP: None +2026-06-24 06:23:09,795 - probe_Ls: None +2026-06-24 06:23:09,795 - meas_Npix: 128 +2026-06-24 06:23:09,795 - pos_N_scans: 256 +2026-06-24 06:23:09,795 - pos_N_scan_slow: 16 +2026-06-24 06:23:09,795 - pos_N_scan_fast: 16 +2026-06-24 06:23:09,795 - pos_scan_step_size: 0.5273715853691101 +2026-06-24 06:23:09,795 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:23:09,795 - probe_pmode_max: 6 +2026-06-24 06:23:09,795 - probe_pmode_init_pows: [0.02] +2026-06-24 06:23:09,795 - obj_omode_max: 1 +2026-06-24 06:23:09,795 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:23:09,795 - obj_Nlayer: 1 +2026-06-24 06:23:09,795 - obj_slice_thickness: 20.0 +2026-06-24 06:23:09,795 - simu_Npix: None +2026-06-24 06:23:09,795 - simu_match_mode: None +2026-06-24 06:23:09,795 - meas_permute: None +2026-06-24 06:23:09,795 - meas_reshape: [256, 128, 128] +2026-06-24 06:23:09,795 - meas_flipT: [0, 0, 0] +2026-06-24 06:23:09,795 - meas_crop: None +2026-06-24 06:23:09,795 - meas_pad: None +2026-06-24 06:23:09,796 - meas_resample: None +2026-06-24 06:23:09,796 - meas_add_source_size: None +2026-06-24 06:23:09,796 - meas_add_detector_blur: None +2026-06-24 06:23:09,796 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:23:09,796 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:23:09,796 - meas_add_poisson_noise: None +2026-06-24 06:23:09,796 - meas_export: None +2026-06-24 06:23:09,796 - probe_permute: None +2026-06-24 06:23:09,796 - probe_z_shift: None +2026-06-24 06:23:09,796 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:23:09,796 - pos_scan_flipT: None +2026-06-24 06:23:09,796 - pos_scan_affine: None +2026-06-24 06:23:09,796 - pos_scan_rand_std: 0.15 +2026-06-24 06:23:09,796 - obj_z_crop: None +2026-06-24 06:23:09,796 - obj_z_pad: None +2026-06-24 06:23:09,796 - obj_z_resample: None +2026-06-24 06:23:09,796 - meas_source: file +2026-06-24 06:23:09,796 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000013_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:23:09,796 - probe_source: simu +2026-06-24 06:23:09,796 - probe_params: None +2026-06-24 06:23:09,796 - pos_source: simu +2026-06-24 06:23:09,796 - pos_params: None +2026-06-24 06:23:09,796 - obj_source: simu +2026-06-24 06:23:09,796 - obj_params: None +2026-06-24 06:23:09,796 - tilt_source: simu +2026-06-24 06:23:09,796 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:23:09,796 - +2026-06-24 06:23:09,796 - ### Initializing cache ### +2026-06-24 06:23:09,796 - use_cached_obj = False +2026-06-24 06:23:09,796 - use_cached_probe = False +2026-06-24 06:23:09,796 - use_cached_pos = False +2026-06-24 06:23:09,796 - +2026-06-24 06:23:09,796 - ### Initializing measurements ### +2026-06-24 06:23:09,796 - Loading measurements from source = 'file' +2026-06-24 06:23:09,796 - Detected measurement file type = '.h5' +2026-06-24 06:23:09,875 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:23:09,875 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:23:09,877 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0035) +2026-06-24 06:23:09,877 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:23:09,877 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:23:09,878 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:23:09,878 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:23:09,878 - Normalizing by max of the 2D mean pattern intensity: 0.0028434682 +2026-06-24 06:23:09,879 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:23:09,880 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0214, 1.2164) +2026-06-24 06:23:09,881 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:23:09,882 - Pattern total int. statistics (min, mean, max) = (349.1335, 350.9621, 352.4598), with min/max = 99.1% +2026-06-24 06:23:09,883 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0214, 1.2164) +2026-06-24 06:23:09,884 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:23:09,884 - +2026-06-24 06:23:09,884 - ### Setting up calibration ### +2026-06-24 06:23:09,884 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:23:09,884 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:23:09,884 - Radius of fitted bright field disk (RBF) = 10.30 px with meas_Npix = 128 +2026-06-24 06:23:09,884 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1609 +2026-06-24 06:23:09,884 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:23:09,884 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:23:10,107 - Initial guess: center=(63.63, 63.62), radius=10.30, Gaussian blur std=0.50 +2026-06-24 06:23:10,119 - Final fit: center=(63.63, 63.62), radius=10.30, Gaussian blur std=0.63 +2026-06-24 06:23:10,119 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.46 px with Npix = 128 +2026-06-24 06:23:10,119 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:23:10,119 - +2026-06-24 06:23:10,119 - ### Setting init_variables dict ### +2026-06-24 06:23:10,119 - Derived values given input init_params: +2026-06-24 06:23:10,120 - kv = 160.0 kV +2026-06-24 06:23:10,120 - wavelength = 0.0285 Ang +2026-06-24 06:23:10,120 - conv_angle = 11.648499488830566 mrad +2026-06-24 06:23:10,120 - Npix = 128 px +2026-06-24 06:23:10,120 - dk = 0.0391 Ang^-1 +2026-06-24 06:23:10,120 - kMax = 2.5000 Ang^-1 +2026-06-24 06:23:10,120 - da = 1.1137 mrad +2026-06-24 06:23:10,120 - angleMax = 71.2751 mrad +2026-06-24 06:23:10,120 - RBF = 10.4595 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:23:10,120 - n_alpha = 6.1188 (# conv_angle) +2026-06-24 06:23:10,120 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:23:10,120 - Rayleigh-limited resolution = 1.4930 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:23:10,120 - Real space probe extent = 25.6000 Ang +2026-06-24 06:23:10,120 - +2026-06-24 06:23:10,120 - ### Initializing probe ### +2026-06-24 06:23:10,120 - Loading probe from source = 'simu' +2026-06-24 06:23:10,120 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:23:10,120 - Start simulating STEM probe +2026-06-24 06:23:10,120 - kv = 160.0 kV +2026-06-24 06:23:10,120 - wavelength = 0.0285 Ang +2026-06-24 06:23:10,120 - conv_angle = 11.648499488830566 mrad +2026-06-24 06:23:10,120 - Npix = 128 px +2026-06-24 06:23:10,120 - dk = 0.0391 Ang^-1 +2026-06-24 06:23:10,120 - kMax = 2.5000 Ang^-1 +2026-06-24 06:23:10,120 - alpha_max = 71.2751 mrad +2026-06-24 06:23:10,120 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:23:10,121 - Rayleigh-limited resolution = 1.4930 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:23:10,121 - Real space probe extent = 25.6000 Ang +2026-06-24 06:23:10,121 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:23:10,121 - ------------------------------------------------------------------------------------- +2026-06-24 06:23:10,121 - C1,0 C1 37.2880 - Defocus (C10 = -df) +2026-06-24 06:23:10,121 - C1,2 A1 10.5190 229.44 2-fold astigmatism +2026-06-24 06:23:10,121 - C2,1 3*B2 -81.6350 312.41 Axial coma +2026-06-24 06:23:10,121 - C2,3 A2 -804.8860 342.84 3-fold astigmatism +2026-06-24 06:23:10,121 - C3,0 C3 4285037.5000 - Spherical aberration +2026-06-24 06:23:10,121 - C3,2 4*S3 -8719.2700 65.87 Axial star aberration +2026-06-24 06:23:10,121 - C3,4 A3 10792.8960 175.70 4-fold astigmatism +2026-06-24 06:23:10,121 - C4,1 4*B4 489775.0310 290.65 Axial coma(4th) +2026-06-24 06:23:10,121 - C4,3 4*D4 -370250.7190 3.14 3-lobe aberration +2026-06-24 06:23:10,121 - C4,5 A4 -427713.7190 231.84 5-fold astigmatism +2026-06-24 06:23:10,121 - C5,0 C5 -395111360.0000 - Spherical aberration (5th) +2026-06-24 06:23:10,121 - C5,2 6*S5 -6819994.5000 152.75 Axial star aberration(5th) +2026-06-24 06:23:10,121 - C5,4 6*R5 -11792731.0000 238.43 4-lobe aberration +2026-06-24 06:23:10,121 - C5,6 A5 1392187.6250 23.57 6-fold astigmatism +2026-06-24 06:23:10,124 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:23:10,124 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:23:10,124 - Creating 5 new probe modes from the major mode +2026-06-24 06:23:10,124 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:23:10,352 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:23:10,353 - Orthogonalizing 6 pmodes +2026-06-24 06:23:10,364 - Sorting 6 pmodes by their intensities +2026-06-24 06:23:10,364 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:23:10,365 - sum(|probe_data|**2) = 350.96, while meas_total_ints (min, mean, max) = (349.1335, 350.9621, 352.4598) +2026-06-24 06:23:10,365 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:23:10,365 - +2026-06-24 06:23:10,365 - ### Initializing probe positions ### +2026-06-24 06:23:10,365 - Loading probe positions from source = 'simu' +2026-06-24 06:23:10,365 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:23:10,365 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5274, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:23:10,365 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:23:10,367 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:23:10,367 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 06:23:10,367 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 06:23:10,367 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:23:10,367 - +2026-06-24 06:23:10,367 - ### Initializing object ### +2026-06-24 06:23:10,367 - Loading object from source = 'simu' +2026-06-24 06:23:10,368 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:23:10,369 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:23:10,369 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 201) +2026-06-24 06:23:10,369 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.2] +2026-06-24 06:23:10,369 - +2026-06-24 06:23:10,369 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:23:10,369 - omode_occu (omode) = float32, (1,) +2026-06-24 06:23:10,369 - +2026-06-24 06:23:10,369 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:23:10,369 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:23:10,370 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:23:10,370 - +2026-06-24 06:23:10,370 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:23:10,370 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:23:10,370 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:23:10,370 - +2026-06-24 06:23:10,370 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:23:10,370 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:23:10,370 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:23:10,370 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:23:10,370 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:23:10,371 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 201). +2026-06-24 06:23:10,371 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:23:10,371 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:23:10,371 - +2026-06-24 06:23:10,371 - ### Collecting reconstruction provenance ### +2026-06-24 06:23:10,371 - Reconstruction provenance is collected and initialized. +2026-06-24 06:23:10,371 - +2026-06-24 06:23:10,371 - ### Initializing loss function ### +2026-06-24 06:23:10,371 - Active loss types: +2026-06-24 06:23:10,371 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:23:10,371 - +2026-06-24 06:23:10,371 - ### Initializing constraint function ### +2026-06-24 06:23:10,371 - Active constraint types: +2026-06-24 06:23:10,371 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:23:10,371 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:23:10,371 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:23:10,371 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:23:10,371 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:23:10,371 - +2026-06-24 06:23:10,371 - ### Done initializing PtyRADSolver ### +2026-06-24 06:23:10,371 - +2026-06-24 06:23:10,500 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:23:10,501 - +2026-06-24 06:23:10,501 - ### Initializing PtychoModel model ### +2026-06-24 06:23:10,573 - ### PtychoModel optimizable variables ### +2026-06-24 06:23:10,573 - obja : torch.Size([1, 1, 202, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:23:10,573 - objp : torch.Size([1, 1, 202, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:23:10,573 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:23:10,573 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:23:10,573 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:23:10,574 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:23:10,574 - +2026-06-24 06:23:10,574 - ### Optimizable variables statitsics ### +2026-06-24 06:23:10,574 - Total measurement values : 4,194,304 +2026-06-24 06:23:10,574 - Total optimizing variables: 278,324 +2026-06-24 06:23:10,574 - Overdetermined ratio : 15.07 +2026-06-24 06:23:10,574 - +2026-06-24 06:23:10,574 - ### Model behavior ### +2026-06-24 06:23:10,574 - Tilt propagator : False +2026-06-24 06:23:10,574 - Change slice thickness : False +2026-06-24 06:23:10,574 - Detector blur : False +2026-06-24 06:23:10,574 - Preload data : True +2026-06-24 06:23:10,574 - On-the-fly meas padding : False +2026-06-24 06:23:10,574 - On-the-fly meas resample : False +2026-06-24 06:23:10,574 - On-the-fly simu match mode: None +2026-06-24 06:23:10,574 - +2026-06-24 06:23:10,615 - ### Done initializing PtychoModel model ### +2026-06-24 06:23:10,616 - +2026-06-24 06:23:10,616 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:23:10,616 - +2026-06-24 06:23:10,616 - ### Generating indices, batches, and output_path ### +2026-06-24 06:23:10,617 - d90 = 65.000 px or 13.000 Ang +2026-06-24 06:23:10,618 - Selecting indices with the 'full' mode +2026-06-24 06:23:11,080 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:23:11,156 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:23:11,156 - Original recon_dir_affixes = ['default'] +2026-06-24 06:23:11,156 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:23:11,162 - Path corrected for compatibility: +2026-06-24 06:23:11,162 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_65.9_C34_1.08e+04_phi34_176_C41_4.9e+05_phi41_291_C43_-3.7e+05_phi43_3.14_C45_-4.28e+05_phi45_232_C50_-3.95e+08_C52_-6.82e+06_phi52_153_C54_-1.18e+07_phi54_238_C56_1.39e+06_phi56_23.6 +2026-06-24 06:23:11,162 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6 +2026-06-24 06:23:11,163 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6' is generated! +2026-06-24 06:23:11,314 - +2026-06-24 06:23:11,315 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/20260624_062311_ptyrad_log.txt ### +2026-06-24 06:23:11,315 - +2026-06-24 06:23:11,317 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:23:11,317 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:23:11,317 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:23:12,542 - Iter: 1, Total Loss: 0.8804, loss_single: 0.8804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.442 sec +2026-06-24 06:23:12,579 - Iter: 2, Total Loss: 0.8350, loss_single: 0.8350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:23:12,615 - Iter: 3, Total Loss: 0.8022, loss_single: 0.8022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,650 - Iter: 4, Total Loss: 0.7718, loss_single: 0.7718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,686 - Iter: 5, Total Loss: 0.7405, loss_single: 0.7405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,721 - Iter: 6, Total Loss: 0.7094, loss_single: 0.7094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,756 - Iter: 7, Total Loss: 0.6747, loss_single: 0.6747, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,792 - Iter: 8, Total Loss: 0.6358, loss_single: 0.6358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,827 - Iter: 9, Total Loss: 0.5980, loss_single: 0.5980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,863 - Iter: 10, Total Loss: 0.5621, loss_single: 0.5621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,898 - Iter: 11, Total Loss: 0.5366, loss_single: 0.5366, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,934 - Iter: 12, Total Loss: 0.5163, loss_single: 0.5163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:12,969 - Iter: 13, Total Loss: 0.4905, loss_single: 0.4905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,005 - Iter: 14, Total Loss: 0.4638, loss_single: 0.4638, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,040 - Iter: 15, Total Loss: 0.4422, loss_single: 0.4422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,076 - Iter: 16, Total Loss: 0.4241, loss_single: 0.4241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,112 - Iter: 17, Total Loss: 0.4036, loss_single: 0.4036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,147 - Iter: 18, Total Loss: 0.3803, loss_single: 0.3803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,183 - Iter: 19, Total Loss: 0.3569, loss_single: 0.3569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,219 - Iter: 20, Total Loss: 0.3424, loss_single: 0.3424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,254 - Iter: 21, Total Loss: 0.3291, loss_single: 0.3291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,290 - Iter: 22, Total Loss: 0.3138, loss_single: 0.3138, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:23:13,328 - Iter: 23, Total Loss: 0.3016, loss_single: 0.3016, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:23:13,364 - Iter: 24, Total Loss: 0.2898, loss_single: 0.2898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:23:13,400 - Iter: 25, Total Loss: 0.2799, loss_single: 0.2799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,435 - Iter: 26, Total Loss: 0.2707, loss_single: 0.2707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,471 - Iter: 27, Total Loss: 0.2625, loss_single: 0.2625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:23:13,507 - Iter: 28, Total Loss: 0.2562, loss_single: 0.2562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:23:13,543 - Iter: 29, Total Loss: 0.2503, loss_single: 0.2503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/simulation_data5__sample_000013.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/simulation_data5__sample_000013.yaml new file mode 100644 index 0000000000000000000000000000000000000000..81a9ed9f686d88575e836e89a216b0e75c7b7d8c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/simulation_data5__sample_000013.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 11.648499488830566 + probe_aberrations: + C10: 37.288063049316406 + C12: 10.519309997558594 + C21: -81.63529205322266 + C23: -804.886474609375 + C30: 4285037.5 + C32: -8719.26953125 + C34: 10792.896484375 + C41: 489775.03125 + C43: -370250.71875 + C45: -427713.71875 + C50: -395111360.0 + C52: -6819994.5 + C54: -11792731.0 + C56: 1392187.625 + phi12: 229.43722841021045 + phi21: 312.4131804854634 + phi23: 342.84407746445805 + phi32: 65.87192895949042 + phi34: 175.70280515302116 + phi41: 290.65151477088574 + phi43: 3.143521140964791 + phi45: 231.83489801645172 + phi52: 152.75413452296536 + phi54: 238.4299101129626 + phi56: 23.568778382159383 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5273715853691101 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000013_measurement.h5 + key: measurement + random_seed: 20262043 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000013 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:32c60877cd4538e8ca7b22f3dcb062233eda7805a09f1cfd8ff6f36323362f91 +size 1377472 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000013/c30_small__simulation_data5__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_37.3_C12_10.5_phi12_229_C21_-81.6_phi21_312_C23_-805_phi23_343_C30_4.29e+06_C32_-8.72e+03_phi32_.6/summary_scan_pos_iter0100.png 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sha256:bbf54ecc129e5e6c74c684cbd7cf9a810b093f2b8070e5d9e22eaa85626d8134 +size 48062 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/20260624_062440_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/20260624_062440_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ea3a79c11af6ba05e0c5b78aaa06aa41f0e4c19a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/20260624_062440_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:24:39,233 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:24:39,233 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:24:39,233 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:24:39,233 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:24:39,233 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:24:39,233 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:24:39,233 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:24:39,233 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:24:39,233 - +2026-06-24 06:24:39,341 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:24:39,341 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:24:39,341 - Accelerator.num_process = 1 +2026-06-24 06:24:39,341 - Accelerator.mixed_precision = no +2026-06-24 06:24:39,351 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:24:39,352 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:24:39,352 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:24:39,352 - +2026-06-24 06:24:39,352 - ### System information ### +2026-06-24 06:24:39,352 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:24:39,352 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:24:39,352 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:24:39,352 - Machine: x86_64 +2026-06-24 06:24:39,352 - Processor: x86_64 +2026-06-24 06:24:39,352 - Available CPU cores: 8 +2026-06-24 06:24:39,352 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:24:39,352 - +2026-06-24 06:24:39,352 - ### GPU information ### +2026-06-24 06:24:39,352 - CUDA Available: True +2026-06-24 06:24:39,352 - CUDA Version: 13.0 +2026-06-24 06:24:39,353 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:24:39,353 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:24:39,353 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:24:39,353 - In addition, Triton does not directly support Windows. +2026-06-24 06:24:39,353 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:24:39,379 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:24:39,380 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:24:39,380 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:24:39,380 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:24:39,380 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:24:39,380 - +2026-06-24 06:24:39,380 - ### Python information ### +2026-06-24 06:24:39,381 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:24:39,381 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:24:39,381 - +2026-06-24 06:24:39,381 - ### Packages information ### +2026-06-24 06:24:39,381 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:24:39,382 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:24:39,383 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:24:39,383 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:24:39,384 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:24:39,384 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:24:39,384 - +2026-06-24 06:24:39,384 - ### Loading params file ### +2026-06-24 06:24:39,384 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000019.yaml +2026-06-24 06:24:39,391 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:24:39,392 - Success! Params file validated and defaults applied. +2026-06-24 06:24:39,392 - +2026-06-24 06:24:39,392 - ### Setting GPU Device ### +2026-06-24 06:24:39,392 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:24:39,392 - +2026-06-24 06:24:39,392 - Random seed: 20262049 provided by params file +2026-06-24 06:24:39,392 - ### Initializing Initializer ### +2026-06-24 06:24:39,392 - init_params are displayed below: +2026-06-24 06:24:39,392 - random_seed: 20262049 +2026-06-24 06:24:39,393 - probe_illum_type: electron +2026-06-24 06:24:39,393 - probe_kv: 200.0 +2026-06-24 06:24:39,393 - probe_conv_angle: 22.058151245117188 +2026-06-24 06:24:39,393 - probe_aberrations: {'C10': -595.756, 'C12': -28.42, 'phi12': 99.467, 'C21': -66.592, 'phi21': 322.639, 'C23': -922.37, 'phi23': 164.967, 'C30': 2169158.0, 'C32': 8499.262, 'phi32': 68.697, 'C34': 4144.188, 'phi34': 256.535, 'C41': 49737.934, 'phi41': 62.546, 'C43': -360899.0, 'phi43': 24.993, 'C45': 331877.281, 'phi45': 168.593, 'C50': -182909456.0, 'C52': 1327981.5, 'phi52': 31.833, 'C54': 6731486.0, 'phi54': 10.741, 'C56': -3214623.5, 'phi56': 30.818} +2026-06-24 06:24:39,393 - beam_kev: None +2026-06-24 06:24:39,393 - probe_dRn: None +2026-06-24 06:24:39,393 - probe_Rn: None +2026-06-24 06:24:39,393 - probe_D_H: None +2026-06-24 06:24:39,393 - probe_D_FZP: None +2026-06-24 06:24:39,393 - probe_Ls: None +2026-06-24 06:24:39,393 - meas_Npix: 128 +2026-06-24 06:24:39,393 - pos_N_scans: 256 +2026-06-24 06:24:39,393 - pos_N_scan_slow: 16 +2026-06-24 06:24:39,393 - pos_N_scan_fast: 16 +2026-06-24 06:24:39,393 - pos_scan_step_size: 0.3346472382545471 +2026-06-24 06:24:39,393 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:24:39,393 - probe_pmode_max: 6 +2026-06-24 06:24:39,393 - probe_pmode_init_pows: [0.02] +2026-06-24 06:24:39,393 - obj_omode_max: 1 +2026-06-24 06:24:39,393 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:24:39,393 - obj_Nlayer: 1 +2026-06-24 06:24:39,393 - obj_slice_thickness: 20.0 +2026-06-24 06:24:39,393 - simu_Npix: None +2026-06-24 06:24:39,393 - simu_match_mode: None +2026-06-24 06:24:39,393 - meas_permute: None +2026-06-24 06:24:39,393 - meas_reshape: [256, 128, 128] +2026-06-24 06:24:39,393 - meas_flipT: [0, 0, 0] +2026-06-24 06:24:39,393 - meas_crop: None +2026-06-24 06:24:39,393 - meas_pad: None +2026-06-24 06:24:39,393 - meas_resample: None +2026-06-24 06:24:39,393 - meas_add_source_size: None +2026-06-24 06:24:39,393 - meas_add_detector_blur: None +2026-06-24 06:24:39,393 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:24:39,393 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:24:39,393 - meas_add_poisson_noise: None +2026-06-24 06:24:39,393 - meas_export: None +2026-06-24 06:24:39,393 - probe_permute: None +2026-06-24 06:24:39,393 - probe_z_shift: None +2026-06-24 06:24:39,394 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:24:39,394 - pos_scan_flipT: None +2026-06-24 06:24:39,394 - pos_scan_affine: None +2026-06-24 06:24:39,394 - pos_scan_rand_std: 0.15 +2026-06-24 06:24:39,394 - obj_z_crop: None +2026-06-24 06:24:39,394 - obj_z_pad: None +2026-06-24 06:24:39,394 - obj_z_resample: None +2026-06-24 06:24:39,394 - meas_source: file +2026-06-24 06:24:39,394 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000019_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:24:39,394 - probe_source: simu +2026-06-24 06:24:39,394 - probe_params: None +2026-06-24 06:24:39,394 - pos_source: simu +2026-06-24 06:24:39,394 - pos_params: None +2026-06-24 06:24:39,394 - obj_source: simu +2026-06-24 06:24:39,394 - obj_params: None +2026-06-24 06:24:39,394 - tilt_source: simu +2026-06-24 06:24:39,394 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:24:39,394 - +2026-06-24 06:24:39,394 - ### Initializing cache ### +2026-06-24 06:24:39,394 - use_cached_obj = False +2026-06-24 06:24:39,394 - use_cached_probe = False +2026-06-24 06:24:39,394 - use_cached_pos = False +2026-06-24 06:24:39,394 - +2026-06-24 06:24:39,394 - ### Initializing measurements ### +2026-06-24 06:24:39,394 - Loading measurements from source = 'file' +2026-06-24 06:24:39,394 - Detected measurement file type = '.h5' +2026-06-24 06:24:39,469 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:24:39,469 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:24:39,471 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0011) +2026-06-24 06:24:39,471 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:24:39,471 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:24:39,472 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:24:39,472 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:24:39,473 - Normalizing by max of the 2D mean pattern intensity: 0.00065365864 +2026-06-24 06:24:39,473 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:24:39,475 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0934, 1.7374) +2026-06-24 06:24:39,475 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:24:39,476 - Pattern total int. statistics (min, mean, max) = (1514.8112, 1530.1804, 1544.1903), with min/max = 98.1% +2026-06-24 06:24:39,478 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0934, 1.7374) +2026-06-24 06:24:39,478 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:24:39,478 - +2026-06-24 06:24:39,478 - ### Setting up calibration ### +2026-06-24 06:24:39,478 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:24:39,478 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:24:39,478 - Radius of fitted bright field disk (RBF) = 22.30 px with meas_Npix = 128 +2026-06-24 06:24:39,478 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3484 +2026-06-24 06:24:39,478 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:24:39,478 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:24:39,702 - Initial guess: center=(63.63, 63.62), radius=22.30, Gaussian blur std=0.50 +2026-06-24 06:24:39,714 - Final fit: center=(63.63, 63.62), radius=22.30, Gaussian blur std=0.59 +2026-06-24 06:24:39,714 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 22.52 px with Npix = 128 +2026-06-24 06:24:39,714 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:24:39,714 - +2026-06-24 06:24:39,714 - ### Setting init_variables dict ### +2026-06-24 06:24:39,714 - Derived values given input init_params: +2026-06-24 06:24:39,714 - kv = 200.0 kV +2026-06-24 06:24:39,714 - wavelength = 0.0251 Ang +2026-06-24 06:24:39,714 - conv_angle = 22.058151245117188 mrad +2026-06-24 06:24:39,714 - Npix = 128 px +2026-06-24 06:24:39,714 - dk = 0.0391 Ang^-1 +2026-06-24 06:24:39,714 - kMax = 2.5000 Ang^-1 +2026-06-24 06:24:39,714 - da = 0.9797 mrad +2026-06-24 06:24:39,714 - angleMax = 62.6984 mrad +2026-06-24 06:24:39,714 - RBF = 22.5161 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:24:39,714 - n_alpha = 2.8424 (# conv_angle) +2026-06-24 06:24:39,714 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:24:39,714 - Rayleigh-limited resolution = 0.6935 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:24:39,714 - Real space probe extent = 25.6000 Ang +2026-06-24 06:24:39,714 - +2026-06-24 06:24:39,714 - ### Initializing probe ### +2026-06-24 06:24:39,714 - Loading probe from source = 'simu' +2026-06-24 06:24:39,714 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:24:39,715 - Start simulating STEM probe +2026-06-24 06:24:39,715 - kv = 200.0 kV +2026-06-24 06:24:39,715 - wavelength = 0.0251 Ang +2026-06-24 06:24:39,715 - conv_angle = 22.058151245117188 mrad +2026-06-24 06:24:39,715 - Npix = 128 px +2026-06-24 06:24:39,715 - dk = 0.0391 Ang^-1 +2026-06-24 06:24:39,715 - kMax = 2.5000 Ang^-1 +2026-06-24 06:24:39,715 - alpha_max = 62.6984 mrad +2026-06-24 06:24:39,715 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:24:39,715 - Rayleigh-limited resolution = 0.6935 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:24:39,715 - Real space probe extent = 25.6000 Ang +2026-06-24 06:24:39,715 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:24:39,715 - ------------------------------------------------------------------------------------- +2026-06-24 06:24:39,715 - C1,0 C1 -595.7560 - Defocus (C10 = -df) +2026-06-24 06:24:39,715 - C1,2 A1 -28.4200 99.47 2-fold astigmatism +2026-06-24 06:24:39,715 - C2,1 3*B2 -66.5920 322.64 Axial coma +2026-06-24 06:24:39,715 - C2,3 A2 -922.3700 164.97 3-fold astigmatism +2026-06-24 06:24:39,715 - C3,0 C3 2169158.0000 - Spherical aberration +2026-06-24 06:24:39,715 - C3,2 4*S3 8499.2620 68.70 Axial star aberration +2026-06-24 06:24:39,715 - C3,4 A3 4144.1880 256.54 4-fold astigmatism +2026-06-24 06:24:39,715 - C4,1 4*B4 49737.9340 62.55 Axial coma(4th) +2026-06-24 06:24:39,715 - C4,3 4*D4 -360899.0000 24.99 3-lobe aberration +2026-06-24 06:24:39,715 - C4,5 A4 331877.2810 168.59 5-fold astigmatism +2026-06-24 06:24:39,715 - C5,0 C5 -182909456.0000 - Spherical aberration (5th) +2026-06-24 06:24:39,715 - C5,2 6*S5 1327981.5000 31.83 Axial star aberration(5th) +2026-06-24 06:24:39,715 - C5,4 6*R5 6731486.0000 10.74 4-lobe aberration +2026-06-24 06:24:39,715 - C5,6 A5 -3214623.5000 30.82 6-fold astigmatism +2026-06-24 06:24:39,718 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:24:39,718 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:24:39,718 - Creating 5 new probe modes from the major mode +2026-06-24 06:24:39,718 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:24:39,862 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:24:39,863 - Orthogonalizing 6 pmodes +2026-06-24 06:24:39,866 - Sorting 6 pmodes by their intensities +2026-06-24 06:24:39,866 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:24:39,867 - sum(|probe_data|**2) = 1530.18, while meas_total_ints (min, mean, max) = (1514.8112, 1530.1804, 1544.1903) +2026-06-24 06:24:39,867 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:24:39,867 - +2026-06-24 06:24:39,867 - ### Initializing probe positions ### +2026-06-24 06:24:39,867 - Loading probe positions from source = 'simu' +2026-06-24 06:24:39,867 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:24:39,867 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3346, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:24:39,867 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:24:39,869 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:24:39,870 - crop_pos 1st and last px coords (y,x) = ([15, 16], [40, 40]) +2026-06-24 06:24:39,870 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:24:39,870 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:24:39,870 - +2026-06-24 06:24:39,870 - ### Initializing object ### +2026-06-24 06:24:39,870 - Loading object from source = 'simu' +2026-06-24 06:24:39,870 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:24:39,871 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:24:39,871 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 184, 184) +2026-06-24 06:24:39,871 - object extent (Z, Y, X) (Ang) = [20. 36.8 36.8] +2026-06-24 06:24:39,872 - +2026-06-24 06:24:39,872 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:24:39,872 - omode_occu (omode) = float32, (1,) +2026-06-24 06:24:39,872 - +2026-06-24 06:24:39,872 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:24:39,872 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:24:39,872 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:24:39,872 - +2026-06-24 06:24:39,872 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:24:39,872 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:24:39,873 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:24:39,873 - +2026-06-24 06:24:39,873 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:24:39,873 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:24:39,873 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:24:39,873 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:24:39,873 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:24:39,873 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (184, 184). +2026-06-24 06:24:39,873 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:24:39,873 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:24:39,873 - +2026-06-24 06:24:39,873 - ### Collecting reconstruction provenance ### +2026-06-24 06:24:39,873 - Reconstruction provenance is collected and initialized. +2026-06-24 06:24:39,873 - +2026-06-24 06:24:39,873 - ### Initializing loss function ### +2026-06-24 06:24:39,873 - Active loss types: +2026-06-24 06:24:39,873 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:24:39,873 - +2026-06-24 06:24:39,873 - ### Initializing constraint function ### +2026-06-24 06:24:39,873 - Active constraint types: +2026-06-24 06:24:39,873 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:24:39,874 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:24:39,874 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:24:39,874 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:24:39,874 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:24:39,874 - +2026-06-24 06:24:39,874 - ### Done initializing PtyRADSolver ### +2026-06-24 06:24:39,874 - +2026-06-24 06:24:39,998 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:24:39,998 - +2026-06-24 06:24:39,998 - ### Initializing PtychoModel model ### +2026-06-24 06:24:40,085 - ### PtychoModel optimizable variables ### +2026-06-24 06:24:40,085 - obja : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:40,085 - objp : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:40,085 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:24:40,085 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:24:40,085 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:24:40,085 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:40,086 - +2026-06-24 06:24:40,086 - ### Optimizable variables statitsics ### +2026-06-24 06:24:40,086 - Total measurement values : 4,194,304 +2026-06-24 06:24:40,086 - Total optimizing variables: 264,832 +2026-06-24 06:24:40,086 - Overdetermined ratio : 15.84 +2026-06-24 06:24:40,086 - +2026-06-24 06:24:40,086 - ### Model behavior ### +2026-06-24 06:24:40,086 - Tilt propagator : False +2026-06-24 06:24:40,086 - Change slice thickness : False +2026-06-24 06:24:40,086 - Detector blur : False +2026-06-24 06:24:40,086 - Preload data : True +2026-06-24 06:24:40,086 - On-the-fly meas padding : False +2026-06-24 06:24:40,086 - On-the-fly meas resample : False +2026-06-24 06:24:40,086 - On-the-fly simu match mode: None +2026-06-24 06:24:40,086 - +2026-06-24 06:24:40,127 - ### Done initializing PtychoModel model ### +2026-06-24 06:24:40,128 - +2026-06-24 06:24:40,128 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:24:40,128 - +2026-06-24 06:24:40,128 - ### Generating indices, batches, and output_path ### +2026-06-24 06:24:40,129 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:24:40,129 - Selecting indices with the 'full' mode +2026-06-24 06:24:40,593 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:24:40,667 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:24:40,667 - Original recon_dir_affixes = ['default'] +2026-06-24 06:24:40,667 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:24:40,673 - Path corrected for compatibility: +2026-06-24 06:24:40,673 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_68.7_C34_4.14e+03_phi34_257_C41_4.97e+04_phi41_62.5_C43_-3.61e+05_phi43_25_C45_3.32e+05_phi45_169_C50_-1.83e+08_C52_1.33e+06_phi52_31.8_C54_6.73e+06_phi54_10.7_C56_-3.21e+06_phi56_30.8 +2026-06-24 06:24:40,673 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8 +2026-06-24 06:24:40,674 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8' is generated! +2026-06-24 06:24:40,825 - +2026-06-24 06:24:40,826 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/20260624_062440_ptyrad_log.txt ### +2026-06-24 06:24:40,826 - +2026-06-24 06:24:40,827 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:24:40,827 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:24:40,827 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:24:42,031 - Iter: 1, Total Loss: 0.4466, loss_single: 0.4466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.440 sec +2026-06-24 06:24:42,068 - Iter: 2, Total Loss: 0.4305, loss_single: 0.4305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:24:42,104 - Iter: 3, Total Loss: 0.4162, loss_single: 0.4162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,139 - Iter: 4, Total Loss: 0.4034, loss_single: 0.4034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:42,174 - Iter: 5, Total Loss: 0.3923, loss_single: 0.3923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:42,209 - Iter: 6, Total Loss: 0.3812, loss_single: 0.3812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,245 - Iter: 7, Total Loss: 0.3702, loss_single: 0.3702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,280 - Iter: 8, Total Loss: 0.3593, loss_single: 0.3593, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,315 - Iter: 9, Total Loss: 0.3495, loss_single: 0.3495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,351 - Iter: 10, Total Loss: 0.3408, loss_single: 0.3408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,386 - Iter: 11, Total Loss: 0.3323, loss_single: 0.3323, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,421 - Iter: 12, Total Loss: 0.3249, loss_single: 0.3249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,457 - Iter: 13, Total Loss: 0.3185, loss_single: 0.3185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,492 - Iter: 14, Total Loss: 0.3125, loss_single: 0.3125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:42,527 - Iter: 15, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,562 - Iter: 16, Total Loss: 0.3010, loss_single: 0.3010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,597 - Iter: 17, Total Loss: 0.2956, loss_single: 0.2956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:42,632 - Iter: 18, Total Loss: 0.2905, loss_single: 0.2905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,668 - Iter: 19, Total Loss: 0.2859, loss_single: 0.2859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,703 - Iter: 20, Total Loss: 0.2815, loss_single: 0.2815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,738 - Iter: 21, Total Loss: 0.2775, loss_single: 0.2775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,774 - Iter: 22, Total Loss: 0.2739, loss_single: 0.2739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,809 - Iter: 23, Total Loss: 0.2708, loss_single: 0.2708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,845 - Iter: 24, Total Loss: 0.2681, loss_single: 0.2681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,884 - Iter: 25, Total Loss: 0.2656, loss_single: 0.2656, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:24:42,919 - Iter: 26, Total Loss: 0.2635, loss_single: 0.2635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,954 - Iter: 27, Total Loss: 0.2620, loss_single: 0.2620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:42,989 - Iter: 28, Total Loss: 0.2609, loss_single: 0.2609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,025 - Iter: 29, Total Loss: 0.2598, loss_single: 0.2598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,060 - Iter: 30, Total Loss: 0.2587, loss_single: 0.2587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,095 - Iter: 31, Total Loss: 0.2576, loss_single: 0.2576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,131 - Iter: 32, Total Loss: 0.2565, loss_single: 0.2565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,166 - Iter: 33, Total Loss: 0.2557, loss_single: 0.2557, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,201 - Iter: 34, Total Loss: 0.2550, loss_single: 0.2550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,236 - Iter: 35, Total Loss: 0.2544, loss_single: 0.2544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,271 - Iter: 36, Total Loss: 0.2538, loss_single: 0.2538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,306 - Iter: 37, Total Loss: 0.2533, loss_single: 0.2533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,341 - Iter: 38, Total Loss: 0.2529, loss_single: 0.2529, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,376 - Iter: 39, Total Loss: 0.2524, loss_single: 0.2524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,411 - Iter: 40, Total Loss: 0.2521, loss_single: 0.2521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,448 - Iter: 41, Total Loss: 0.2517, loss_single: 0.2517, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:43,483 - Iter: 42, Total Loss: 0.2514, loss_single: 0.2514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,519 - Iter: 43, Total Loss: 0.2511, loss_single: 0.2511, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,556 - Iter: 44, Total Loss: 0.2508, loss_single: 0.2508, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,591 - Iter: 45, Total Loss: 0.2506, loss_single: 0.2506, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,626 - Iter: 46, Total Loss: 0.2504, loss_single: 0.2504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,661 - Iter: 47, Total Loss: 0.2502, loss_single: 0.2502, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,696 - Iter: 48, Total Loss: 0.2500, loss_single: 0.2500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:24:43,731 - Iter: 49, Total Loss: 0.2498, loss_single: 0.2498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,766 - Iter: 50, Total Loss: 0.2496, loss_single: 0.2496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,801 - Iter: 51, Total Loss: 0.2494, loss_single: 0.2494, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,836 - Iter: 52, Total Loss: 0.2493, loss_single: 0.2493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,872 - Iter: 53, Total Loss: 0.2492, loss_single: 0.2492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,907 - Iter: 54, Total Loss: 0.2490, loss_single: 0.2490, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,943 - Iter: 55, Total Loss: 0.2489, loss_single: 0.2489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:43,978 - Iter: 56, Total Loss: 0.2488, loss_single: 0.2488, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:44,013 - Iter: 57, Total Loss: 0.2487, loss_single: 0.2487, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:44,049 - Iter: 58, Total Loss: 0.2487, loss_single: 0.2487, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/simulation_data5__sample_000019.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/simulation_data5__sample_000019.yaml new file mode 100644 index 0000000000000000000000000000000000000000..07820809249bcf3e78c40ce29c978c8b84baa7b6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/simulation_data5__sample_000019.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 22.058151245117188 + probe_aberrations: + C10: -595.7556762695312 + C12: -28.419960021972656 + C21: -66.5924072265625 + C23: -922.3695068359375 + C30: 2169158.0 + C32: 8499.26171875 + C34: 4144.1875 + C41: 49737.93359375 + C43: -360899.0 + C45: 331877.28125 + C50: -182909456.0 + C52: 1327981.5 + C54: 6731486.0 + C56: -3214623.5 + phi12: 99.46703401489853 + phi21: 322.63884793718626 + phi23: 164.9674143439186 + phi32: 68.6967107851001 + phi34: 256.5347745081854 + phi41: 62.54639181488125 + phi43: 24.99326726753161 + phi45: 168.5927558119563 + phi52: 31.833138230692853 + phi54: 10.740615903817622 + phi56: 30.817980874732196 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3346472382545471 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000019_measurement.h5 + key: measurement + random_seed: 20262049 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000019 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000019/c30_small__simulation_data5__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_-28.4_phi12_99.5_C21_-66.6_phi21_323_C23_-922_phi23_165_C30_2.17e+06_C32_8.5e+03_phi32_.8/summary_convergence_iter0100.png new file mode 100644 index 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sha256:0b53a4e41077b048d07321a0d5cbe96b68ea9cbe093203c7691b2fef5eecb9e6 +size 47669 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203/20260624_062455_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203/20260624_062455_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..8d35e7e5fb8092c3d23c774b422c9161a019377c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203/20260624_062455_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:24:54,198 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:24:54,198 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:24:54,198 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:24:54,198 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:24:54,199 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:24:54,199 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:24:54,199 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:24:54,199 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:24:54,199 - +2026-06-24 06:24:54,307 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:24:54,307 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:24:54,307 - Accelerator.num_process = 1 +2026-06-24 06:24:54,307 - Accelerator.mixed_precision = no +2026-06-24 06:24:54,329 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:24:54,329 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:24:54,329 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:24:54,330 - +2026-06-24 06:24:54,330 - ### System information ### +2026-06-24 06:24:54,330 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:24:54,330 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:24:54,330 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:24:54,330 - Machine: x86_64 +2026-06-24 06:24:54,330 - Processor: x86_64 +2026-06-24 06:24:54,330 - Available CPU cores: 8 +2026-06-24 06:24:54,330 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:24:54,330 - +2026-06-24 06:24:54,330 - ### GPU information ### +2026-06-24 06:24:54,330 - CUDA Available: True +2026-06-24 06:24:54,330 - CUDA Version: 13.0 +2026-06-24 06:24:54,330 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:24:54,331 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:24:54,331 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:24:54,331 - In addition, Triton does not directly support Windows. +2026-06-24 06:24:54,331 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:24:54,346 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:24:54,346 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:24:54,346 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:24:54,346 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:24:54,346 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:24:54,346 - +2026-06-24 06:24:54,346 - ### Python information ### +2026-06-24 06:24:54,347 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:24:54,347 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:24:54,347 - +2026-06-24 06:24:54,347 - ### Packages information ### +2026-06-24 06:24:54,348 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:24:54,348 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:24:54,349 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:24:54,350 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:24:54,350 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:24:54,350 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:24:54,350 - +2026-06-24 06:24:54,350 - ### Loading params file ### +2026-06-24 06:24:54,350 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000020.yaml +2026-06-24 06:24:54,357 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:24:54,358 - Success! Params file validated and defaults applied. +2026-06-24 06:24:54,358 - +2026-06-24 06:24:54,358 - ### Setting GPU Device ### +2026-06-24 06:24:54,358 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:24:54,358 - +2026-06-24 06:24:54,358 - Random seed: 20262050 provided by params file +2026-06-24 06:24:54,358 - ### Initializing Initializer ### +2026-06-24 06:24:54,358 - init_params are displayed below: +2026-06-24 06:24:54,358 - random_seed: 20262050 +2026-06-24 06:24:54,358 - probe_illum_type: electron +2026-06-24 06:24:54,358 - probe_kv: 200.0 +2026-06-24 06:24:54,358 - probe_conv_angle: 13.457980155944824 +2026-06-24 06:24:54,358 - probe_aberrations: {'C10': -13.294, 'C12': -18.959, 'phi12': 196.64, 'C21': -186.464, 'phi21': 246.173, 'C23': -23.756, 'phi23': 269.894, 'C30': 1077613.375, 'C32': -542.235, 'phi32': 116.463, 'C34': 8025.276, 'phi34': 33.982, 'C41': 216163.594, 'phi41': 9.217, 'C43': 435477.594, 'phi43': 331.406, 'C45': -492555.656, 'phi45': 77.481, 'C50': 368548192.0, 'C52': 18868922.0, 'phi52': 30.88, 'C54': 18074452.0, 'phi54': 64.9, 'C56': -11368262.0, 'phi56': 202.503} +2026-06-24 06:24:54,358 - beam_kev: None +2026-06-24 06:24:54,358 - probe_dRn: None +2026-06-24 06:24:54,359 - probe_Rn: None +2026-06-24 06:24:54,359 - probe_D_H: None +2026-06-24 06:24:54,359 - probe_D_FZP: None +2026-06-24 06:24:54,359 - probe_Ls: None +2026-06-24 06:24:54,359 - meas_Npix: 128 +2026-06-24 06:24:54,359 - pos_N_scans: 256 +2026-06-24 06:24:54,359 - pos_N_scan_slow: 16 +2026-06-24 06:24:54,359 - pos_N_scan_fast: 16 +2026-06-24 06:24:54,359 - pos_scan_step_size: 0.4567227363586426 +2026-06-24 06:24:54,359 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:24:54,359 - probe_pmode_max: 6 +2026-06-24 06:24:54,359 - probe_pmode_init_pows: [0.02] +2026-06-24 06:24:54,359 - obj_omode_max: 1 +2026-06-24 06:24:54,359 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:24:54,359 - obj_Nlayer: 1 +2026-06-24 06:24:54,359 - obj_slice_thickness: 20.0 +2026-06-24 06:24:54,359 - simu_Npix: None +2026-06-24 06:24:54,359 - simu_match_mode: None +2026-06-24 06:24:54,359 - meas_permute: None +2026-06-24 06:24:54,359 - meas_reshape: [256, 128, 128] +2026-06-24 06:24:54,359 - meas_flipT: [0, 0, 0] +2026-06-24 06:24:54,359 - meas_crop: None +2026-06-24 06:24:54,359 - meas_pad: None +2026-06-24 06:24:54,359 - meas_resample: None +2026-06-24 06:24:54,359 - meas_add_source_size: None +2026-06-24 06:24:54,359 - meas_add_detector_blur: None +2026-06-24 06:24:54,359 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:24:54,359 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:24:54,359 - meas_add_poisson_noise: None +2026-06-24 06:24:54,359 - meas_export: None +2026-06-24 06:24:54,359 - probe_permute: None +2026-06-24 06:24:54,359 - probe_z_shift: None +2026-06-24 06:24:54,359 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:24:54,359 - pos_scan_flipT: None +2026-06-24 06:24:54,359 - pos_scan_affine: None +2026-06-24 06:24:54,359 - pos_scan_rand_std: 0.15 +2026-06-24 06:24:54,359 - obj_z_crop: None +2026-06-24 06:24:54,359 - obj_z_pad: None +2026-06-24 06:24:54,359 - obj_z_resample: None +2026-06-24 06:24:54,359 - meas_source: file +2026-06-24 06:24:54,359 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000020_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:24:54,360 - probe_source: simu +2026-06-24 06:24:54,360 - probe_params: None +2026-06-24 06:24:54,360 - pos_source: simu +2026-06-24 06:24:54,360 - pos_params: None +2026-06-24 06:24:54,360 - obj_source: simu +2026-06-24 06:24:54,360 - obj_params: None +2026-06-24 06:24:54,360 - tilt_source: simu +2026-06-24 06:24:54,360 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:24:54,360 - +2026-06-24 06:24:54,360 - ### Initializing cache ### +2026-06-24 06:24:54,360 - use_cached_obj = False +2026-06-24 06:24:54,360 - use_cached_probe = False +2026-06-24 06:24:54,360 - use_cached_pos = False +2026-06-24 06:24:54,360 - +2026-06-24 06:24:54,360 - ### Initializing measurements ### +2026-06-24 06:24:54,360 - Loading measurements from source = 'file' +2026-06-24 06:24:54,360 - Detected measurement file type = '.h5' +2026-06-24 06:24:54,440 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:24:54,440 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:24:54,442 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0031) +2026-06-24 06:24:54,442 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:24:54,442 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:24:54,443 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:24:54,443 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:24:54,444 - Normalizing by max of the 2D mean pattern intensity: 0.0015232454 +2026-06-24 06:24:54,445 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:24:54,446 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0396, 2.0052) +2026-06-24 06:24:54,446 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:24:54,448 - Pattern total int. statistics (min, mean, max) = (627.1834, 648.2015, 658.7847), with min/max = 95.2% +2026-06-24 06:24:54,449 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0396, 2.0052) +2026-06-24 06:24:54,449 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:24:54,449 - +2026-06-24 06:24:54,449 - ### Setting up calibration ### +2026-06-24 06:24:54,449 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:24:54,449 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:24:54,449 - Radius of fitted bright field disk (RBF) = 13.60 px with meas_Npix = 128 +2026-06-24 06:24:54,449 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2125 +2026-06-24 06:24:54,449 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:24:54,449 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:24:54,675 - Initial guess: center=(63.59, 63.54), radius=13.60, Gaussian blur std=0.50 +2026-06-24 06:24:54,688 - Final fit: center=(63.59, 63.54), radius=13.60, Gaussian blur std=0.64 +2026-06-24 06:24:54,688 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.74 px with Npix = 128 +2026-06-24 06:24:54,688 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:24:54,688 - +2026-06-24 06:24:54,688 - ### Setting init_variables dict ### +2026-06-24 06:24:54,688 - Derived values given input init_params: +2026-06-24 06:24:54,688 - kv = 200.0 kV +2026-06-24 06:24:54,688 - wavelength = 0.0251 Ang +2026-06-24 06:24:54,688 - conv_angle = 13.457980155944824 mrad +2026-06-24 06:24:54,688 - Npix = 128 px +2026-06-24 06:24:54,688 - dk = 0.0391 Ang^-1 +2026-06-24 06:24:54,688 - kMax = 2.5000 Ang^-1 +2026-06-24 06:24:54,688 - da = 0.9797 mrad +2026-06-24 06:24:54,688 - angleMax = 62.6984 mrad +2026-06-24 06:24:54,688 - RBF = 13.7374 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:24:54,688 - n_alpha = 4.6588 (# conv_angle) +2026-06-24 06:24:54,688 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:24:54,688 - Rayleigh-limited resolution = 1.1368 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:24:54,688 - Real space probe extent = 25.6000 Ang +2026-06-24 06:24:54,688 - +2026-06-24 06:24:54,689 - ### Initializing probe ### +2026-06-24 06:24:54,689 - Loading probe from source = 'simu' +2026-06-24 06:24:54,689 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:24:54,689 - Start simulating STEM probe +2026-06-24 06:24:54,689 - kv = 200.0 kV +2026-06-24 06:24:54,689 - wavelength = 0.0251 Ang +2026-06-24 06:24:54,689 - conv_angle = 13.457980155944824 mrad +2026-06-24 06:24:54,689 - Npix = 128 px +2026-06-24 06:24:54,689 - dk = 0.0391 Ang^-1 +2026-06-24 06:24:54,689 - kMax = 2.5000 Ang^-1 +2026-06-24 06:24:54,689 - alpha_max = 62.6984 mrad +2026-06-24 06:24:54,689 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:24:54,689 - Rayleigh-limited resolution = 1.1368 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:24:54,689 - Real space probe extent = 25.6000 Ang +2026-06-24 06:24:54,689 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:24:54,689 - ------------------------------------------------------------------------------------ +2026-06-24 06:24:54,689 - C1,0 C1 -13.2940 - Defocus (C10 = -df) +2026-06-24 06:24:54,689 - C1,2 A1 -18.9590 196.64 2-fold astigmatism +2026-06-24 06:24:54,689 - C2,1 3*B2 -186.4640 246.17 Axial coma +2026-06-24 06:24:54,689 - C2,3 A2 -23.7560 269.89 3-fold astigmatism +2026-06-24 06:24:54,689 - C3,0 C3 1077613.3750 - Spherical aberration +2026-06-24 06:24:54,689 - C3,2 4*S3 -542.2350 116.46 Axial star aberration +2026-06-24 06:24:54,689 - C3,4 A3 8025.2760 33.98 4-fold astigmatism +2026-06-24 06:24:54,689 - C4,1 4*B4 216163.5940 9.22 Axial coma(4th) +2026-06-24 06:24:54,689 - C4,3 4*D4 435477.5940 331.41 3-lobe aberration +2026-06-24 06:24:54,690 - C4,5 A4 -492555.6560 77.48 5-fold astigmatism +2026-06-24 06:24:54,690 - C5,0 C5 368548192.0000 - Spherical aberration (5th) +2026-06-24 06:24:54,690 - C5,2 6*S5 18868922.0000 30.88 Axial star aberration(5th) +2026-06-24 06:24:54,690 - C5,4 6*R5 18074452.0000 64.90 4-lobe aberration +2026-06-24 06:24:54,690 - C5,6 A5 -11368262.0000 202.50 6-fold astigmatism +2026-06-24 06:24:54,692 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:24:54,693 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:24:54,693 - Creating 5 new probe modes from the major mode +2026-06-24 06:24:54,693 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:24:54,889 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:24:54,890 - Orthogonalizing 6 pmodes +2026-06-24 06:24:54,903 - Sorting 6 pmodes by their intensities +2026-06-24 06:24:54,903 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:24:54,904 - sum(|probe_data|**2) = 648.20, while meas_total_ints (min, mean, max) = (627.1834, 648.2015, 658.7847) +2026-06-24 06:24:54,904 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:24:54,904 - +2026-06-24 06:24:54,904 - ### Initializing probe positions ### +2026-06-24 06:24:54,904 - Loading probe positions from source = 'simu' +2026-06-24 06:24:54,904 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:24:54,904 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4567, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:24:54,904 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:24:54,906 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:24:54,906 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 50]) +2026-06-24 06:24:54,906 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 06:24:54,906 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:24:54,906 - +2026-06-24 06:24:54,907 - ### Initializing object ### +2026-06-24 06:24:54,907 - Loading object from source = 'simu' +2026-06-24 06:24:54,907 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:24:54,908 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:24:54,908 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 195, 195) +2026-06-24 06:24:54,908 - object extent (Z, Y, X) (Ang) = [20. 39. 39.] +2026-06-24 06:24:54,908 - +2026-06-24 06:24:54,908 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:24:54,908 - omode_occu (omode) = float32, (1,) +2026-06-24 06:24:54,908 - +2026-06-24 06:24:54,908 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:24:54,908 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:24:54,909 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:24:54,909 - +2026-06-24 06:24:54,909 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:24:54,909 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:24:54,909 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:24:54,909 - +2026-06-24 06:24:54,909 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:24:54,909 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:24:54,909 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:24:54,909 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:24:54,909 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:24:54,910 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (195, 195). +2026-06-24 06:24:54,910 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:24:54,910 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:24:54,910 - +2026-06-24 06:24:54,910 - ### Collecting reconstruction provenance ### +2026-06-24 06:24:54,910 - Reconstruction provenance is collected and initialized. +2026-06-24 06:24:54,910 - +2026-06-24 06:24:54,910 - ### Initializing loss function ### +2026-06-24 06:24:54,910 - Active loss types: +2026-06-24 06:24:54,910 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:24:54,910 - +2026-06-24 06:24:54,910 - ### Initializing constraint function ### +2026-06-24 06:24:54,910 - Active constraint types: +2026-06-24 06:24:54,910 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:24:54,910 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:24:54,910 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:24:54,910 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:24:54,910 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:24:54,910 - +2026-06-24 06:24:54,910 - ### Done initializing PtyRADSolver ### +2026-06-24 06:24:54,910 - +2026-06-24 06:24:55,040 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:24:55,040 - +2026-06-24 06:24:55,040 - ### Initializing PtychoModel model ### +2026-06-24 06:24:55,110 - ### PtychoModel optimizable variables ### +2026-06-24 06:24:55,110 - obja : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:55,110 - objp : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:55,110 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:24:55,110 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:24:55,110 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:24:55,110 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:24:55,110 - +2026-06-24 06:24:55,110 - ### Optimizable variables statitsics ### +2026-06-24 06:24:55,110 - Total measurement values : 4,194,304 +2026-06-24 06:24:55,111 - Total optimizing variables: 273,170 +2026-06-24 06:24:55,111 - Overdetermined ratio : 15.35 +2026-06-24 06:24:55,111 - +2026-06-24 06:24:55,111 - ### Model behavior ### +2026-06-24 06:24:55,111 - Tilt propagator : False +2026-06-24 06:24:55,111 - Change slice thickness : False +2026-06-24 06:24:55,111 - Detector blur : False +2026-06-24 06:24:55,111 - Preload data : True +2026-06-24 06:24:55,111 - On-the-fly meas padding : False +2026-06-24 06:24:55,111 - On-the-fly meas resample : False +2026-06-24 06:24:55,111 - On-the-fly simu match mode: None +2026-06-24 06:24:55,111 - +2026-06-24 06:24:55,152 - ### Done initializing PtychoModel model ### +2026-06-24 06:24:55,152 - +2026-06-24 06:24:55,152 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:24:55,152 - +2026-06-24 06:24:55,152 - ### Generating indices, batches, and output_path ### +2026-06-24 06:24:55,154 - d90 = 31.000 px or 6.200 Ang +2026-06-24 06:24:55,154 - Selecting indices with the 'full' mode +2026-06-24 06:24:55,613 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:24:55,691 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:24:55,691 - Original recon_dir_affixes = ['default'] +2026-06-24 06:24:55,691 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:24:55,697 - Path corrected for compatibility: +2026-06-24 06:24:55,697 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-542_phi32_116_C34_8.03e+03_phi34_34_C41_2.16e+05_phi41_9.22_C43_4.35e+05_phi43_331_C45_-4.93e+05_phi45_77.5_C50_3.69e+08_C52_1.89e+07_phi52_30.9_C54_1.81e+07_phi54_64.9_C56_-1.14e+07_phi56_203 +2026-06-24 06:24:55,697 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203 +2026-06-24 06:24:55,698 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203' is generated! +2026-06-24 06:24:55,847 - +2026-06-24 06:24:55,848 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203/20260624_062455_ptyrad_log.txt ### +2026-06-24 06:24:55,848 - +2026-06-24 06:24:55,850 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:24:55,850 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:24:55,850 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:24:57,033 - Iter: 1, Total Loss: 0.9690, loss_single: 0.9690, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:24:57,070 - Iter: 2, Total Loss: 0.9497, loss_single: 0.9497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:24:57,106 - Iter: 3, Total Loss: 0.9365, loss_single: 0.9365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,141 - Iter: 4, Total Loss: 0.9242, loss_single: 0.9242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,178 - Iter: 5, Total Loss: 0.9103, loss_single: 0.9103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:24:57,214 - Iter: 6, Total Loss: 0.8961, loss_single: 0.8961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,249 - Iter: 7, Total Loss: 0.8816, loss_single: 0.8816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,285 - Iter: 8, Total Loss: 0.8691, loss_single: 0.8691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,321 - Iter: 9, Total Loss: 0.8559, loss_single: 0.8559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,356 - Iter: 10, Total Loss: 0.8413, loss_single: 0.8413, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,392 - Iter: 11, Total Loss: 0.8273, loss_single: 0.8273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,427 - Iter: 12, Total Loss: 0.8153, loss_single: 0.8153, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,463 - Iter: 13, Total Loss: 0.8035, loss_single: 0.8035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,498 - Iter: 14, Total Loss: 0.7901, loss_single: 0.7901, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,533 - Iter: 15, Total Loss: 0.7775, loss_single: 0.7775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,568 - Iter: 16, Total Loss: 0.7673, loss_single: 0.7673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,603 - Iter: 17, Total Loss: 0.7579, loss_single: 0.7579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,639 - Iter: 18, Total Loss: 0.7463, loss_single: 0.7463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,674 - Iter: 19, Total Loss: 0.7360, loss_single: 0.7360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,709 - Iter: 20, Total Loss: 0.7266, loss_single: 0.7266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,745 - Iter: 21, Total Loss: 0.7163, loss_single: 0.7163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,780 - Iter: 22, Total Loss: 0.7063, loss_single: 0.7063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,815 - Iter: 23, Total Loss: 0.6969, loss_single: 0.6969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,851 - Iter: 24, Total Loss: 0.6880, loss_single: 0.6880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,886 - Iter: 25, Total Loss: 0.6793, loss_single: 0.6793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,922 - Iter: 26, Total Loss: 0.6712, loss_single: 0.6712, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,957 - Iter: 27, Total Loss: 0.6625, loss_single: 0.6625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:57,992 - Iter: 28, Total Loss: 0.6543, loss_single: 0.6543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,027 - Iter: 29, Total Loss: 0.6475, loss_single: 0.6475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,062 - Iter: 30, Total Loss: 0.6408, loss_single: 0.6408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,097 - Iter: 31, Total Loss: 0.6337, loss_single: 0.6337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,133 - Iter: 32, Total Loss: 0.6272, loss_single: 0.6272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,168 - Iter: 33, Total Loss: 0.6218, loss_single: 0.6218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,204 - Iter: 34, Total Loss: 0.6166, loss_single: 0.6166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,239 - Iter: 35, Total Loss: 0.6113, loss_single: 0.6113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,274 - Iter: 36, Total Loss: 0.6062, loss_single: 0.6062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,309 - Iter: 37, Total Loss: 0.6015, loss_single: 0.6015, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,345 - Iter: 38, Total Loss: 0.5970, loss_single: 0.5970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,380 - Iter: 39, Total Loss: 0.5928, loss_single: 0.5928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,416 - Iter: 40, Total Loss: 0.5891, loss_single: 0.5891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,454 - Iter: 41, Total Loss: 0.5851, loss_single: 0.5851, 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Iter: 47, Total Loss: 0.5694, loss_single: 0.5694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,702 - Iter: 48, Total Loss: 0.5678, loss_single: 0.5678, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:24:58,737 - Iter: 49, Total Loss: 0.5667, loss_single: 0.5667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,773 - Iter: 50, Total Loss: 0.5658, loss_single: 0.5658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,808 - Iter: 51, Total Loss: 0.5647, loss_single: 0.5647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:58,843 - Iter: 52, Total Loss: 0.5635, loss_single: 0.5635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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in 0.035 sec +2026-06-24 06:24:59,480 - Iter: 70, Total Loss: 0.5512, loss_single: 0.5512, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:59,515 - Iter: 71, Total Loss: 0.5508, loss_single: 0.5508, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:59,551 - Iter: 72, Total Loss: 0.5504, loss_single: 0.5504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:59,586 - Iter: 73, Total Loss: 0.5500, loss_single: 0.5500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:59,622 - Iter: 74, Total Loss: 0.5496, loss_single: 0.5496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:24:59,657 - Iter: 75, Total Loss: 0.5492, loss_single: 0.5492, loss_poissn: 0.0000, loss_pacbed: 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+2026-06-24 06:25:00,083 - Iter: 87, Total Loss: 0.5447, loss_single: 0.5447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:25:00,118 - Iter: 88, Total Loss: 0.5443, loss_single: 0.5443, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,153 - Iter: 89, Total Loss: 0.5440, loss_single: 0.5440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,188 - Iter: 90, Total Loss: 0.5436, loss_single: 0.5436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,226 - Iter: 91, Total Loss: 0.5432, loss_single: 0.5432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:25:00,261 - Iter: 92, Total Loss: 0.5429, loss_single: 0.5429, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.5407, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,509 - Iter: 99, Total Loss: 0.5403, loss_single: 0.5403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,544 - Iter: 100, Total Loss: 0.5399, loss_single: 0.5399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:00,654 - Saving summary figures for iter 100 +2026-06-24 06:25:04,290 - ### Finished 100 iterations, averaged iter_t = 0.039055 with std = 0.040 ### +2026-06-24 06:25:04,290 - +2026-06-24 06:25:04,290 - ### The PtyRADSolver is finished in 9.250 sec ### +2026-06-24 06:25:04,290 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000020/c30_small__simulation_data5__sample_000020_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-13.3_C12_-19_phi12_197_C21_-186_phi21_246_C23_-23.8_phi23_270_C30_1.08e+06_C32_-.14e+07_phi56_203/simulation_data5__sample_000020.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 13.457980155944824 + probe_aberrations: + C10: -13.293852806091309 + C12: -18.958763122558594 + C21: -186.46376037597656 + C23: -23.75577735900879 + C30: 1077613.375 + C32: -542.2347412109375 + C34: 8025.27587890625 + C41: 216163.59375 + C43: 435477.59375 + C45: -492555.65625 + C50: 368548192.0 + C52: 18868922.0 + C54: 18074452.0 + C56: -11368262.0 + phi12: 196.63983480834645 + phi21: 246.17299504668256 + phi23: 269.8939141850567 + phi32: 116.46258006626292 + phi34: 33.982311894550726 + phi41: 9.217207096243392 + phi43: 331.4063519633814 + phi45: 77.48059360492495 + phi52: 30.87965406784283 + phi54: 64.89999987078677 + phi56: 202.50301945604716 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4567227363586426 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000020_measurement.h5 + key: measurement + random_seed: 20262050 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/20260624_062540_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:25:38,554 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:25:38,554 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:25:38,554 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:25:38,554 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:25:38,554 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:25:38,554 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:25:38,554 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:25:38,554 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:25:38,554 - +2026-06-24 06:25:38,637 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:25:38,637 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:25:38,637 - Accelerator.num_process = 1 +2026-06-24 06:25:38,637 - Accelerator.mixed_precision = no +2026-06-24 06:25:38,647 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:25:38,648 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:25:38,648 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:25:38,648 - +2026-06-24 06:25:38,648 - ### System information ### +2026-06-24 06:25:38,648 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:25:38,648 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:25:38,648 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:25:38,648 - Machine: x86_64 +2026-06-24 06:25:38,648 - Processor: x86_64 +2026-06-24 06:25:38,648 - Available CPU cores: 8 +2026-06-24 06:25:38,648 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:25:38,648 - +2026-06-24 06:25:38,648 - ### GPU information ### +2026-06-24 06:25:38,648 - CUDA Available: True +2026-06-24 06:25:38,648 - CUDA Version: 13.0 +2026-06-24 06:25:38,649 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:25:38,649 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:25:38,649 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:25:38,649 - In addition, Triton does not directly support Windows. +2026-06-24 06:25:38,649 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:25:38,664 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:25:38,664 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:25:38,664 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:25:38,664 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:25:38,664 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:25:38,664 - +2026-06-24 06:25:38,664 - ### Python information ### +2026-06-24 06:25:38,666 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:25:38,666 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:25:38,666 - +2026-06-24 06:25:38,666 - ### Packages information ### +2026-06-24 06:25:38,666 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:25:38,667 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:25:38,668 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:25:38,668 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:25:38,669 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:25:38,669 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:25:38,669 - +2026-06-24 06:25:38,669 - ### Loading params file ### +2026-06-24 06:25:38,669 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000023.yaml +2026-06-24 06:25:38,676 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:25:38,678 - Success! Params file validated and defaults applied. +2026-06-24 06:25:38,678 - +2026-06-24 06:25:38,678 - ### Setting GPU Device ### +2026-06-24 06:25:38,678 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:25:38,678 - +2026-06-24 06:25:38,678 - Random seed: 20262053 provided by params file +2026-06-24 06:25:38,678 - ### Initializing Initializer ### +2026-06-24 06:25:38,678 - init_params are displayed below: +2026-06-24 06:25:38,678 - random_seed: 20262053 +2026-06-24 06:25:38,678 - probe_illum_type: electron +2026-06-24 06:25:38,678 - probe_kv: 80.0 +2026-06-24 06:25:38,678 - probe_conv_angle: 11.226186752319336 +2026-06-24 06:25:38,679 - probe_aberrations: {'C10': 76.365, 'C12': 43.655, 'phi12': 189.851, 'C21': -861.46, 'phi21': 297.672, 'C23': -9.18, 'phi23': 51.465, 'C30': 3302940.0, 'C32': 7588.215, 'phi32': 62.368, 'C34': 4771.23, 'phi34': 55.394, 'C41': 111281.625, 'phi41': 337.518, 'C43': -14763.273, 'phi43': 332.829, 'C45': -411061.594, 'phi45': 135.443, 'C50': 81083696.0, 'C52': -14134963.0, 'phi52': 121.991, 'C54': -9462577.0, 'phi54': 228.341, 'C56': -15042904.0, 'phi56': 339.015} +2026-06-24 06:25:38,679 - beam_kev: None +2026-06-24 06:25:38,679 - probe_dRn: None +2026-06-24 06:25:38,679 - probe_Rn: None +2026-06-24 06:25:38,679 - probe_D_H: None +2026-06-24 06:25:38,679 - probe_D_FZP: None +2026-06-24 06:25:38,679 - probe_Ls: None +2026-06-24 06:25:38,679 - meas_Npix: 128 +2026-06-24 06:25:38,679 - pos_N_scans: 256 +2026-06-24 06:25:38,679 - pos_N_scan_slow: 16 +2026-06-24 06:25:38,679 - pos_N_scan_fast: 16 +2026-06-24 06:25:38,679 - pos_scan_step_size: 0.31666725873947144 +2026-06-24 06:25:38,679 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:25:38,679 - probe_pmode_max: 6 +2026-06-24 06:25:38,679 - probe_pmode_init_pows: [0.02] +2026-06-24 06:25:38,679 - obj_omode_max: 1 +2026-06-24 06:25:38,679 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:25:38,679 - obj_Nlayer: 1 +2026-06-24 06:25:38,679 - obj_slice_thickness: 20.0 +2026-06-24 06:25:38,679 - simu_Npix: None +2026-06-24 06:25:38,679 - simu_match_mode: None +2026-06-24 06:25:38,679 - meas_permute: None +2026-06-24 06:25:38,679 - meas_reshape: [256, 128, 128] +2026-06-24 06:25:38,679 - meas_flipT: [0, 0, 0] +2026-06-24 06:25:38,679 - meas_crop: None +2026-06-24 06:25:38,679 - meas_pad: None +2026-06-24 06:25:38,679 - meas_resample: None +2026-06-24 06:25:38,679 - meas_add_source_size: None +2026-06-24 06:25:38,679 - meas_add_detector_blur: None +2026-06-24 06:25:38,679 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:25:38,679 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:25:38,679 - meas_add_poisson_noise: None +2026-06-24 06:25:38,679 - meas_export: None +2026-06-24 06:25:38,679 - probe_permute: None +2026-06-24 06:25:38,679 - probe_z_shift: None +2026-06-24 06:25:38,679 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:25:38,679 - pos_scan_flipT: None +2026-06-24 06:25:38,679 - pos_scan_affine: None +2026-06-24 06:25:38,680 - pos_scan_rand_std: 0.15 +2026-06-24 06:25:38,680 - obj_z_crop: None +2026-06-24 06:25:38,680 - obj_z_pad: None +2026-06-24 06:25:38,680 - obj_z_resample: None +2026-06-24 06:25:38,680 - meas_source: file +2026-06-24 06:25:38,680 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000023_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:25:38,680 - probe_source: simu +2026-06-24 06:25:38,680 - probe_params: None +2026-06-24 06:25:38,680 - pos_source: simu +2026-06-24 06:25:38,680 - pos_params: None +2026-06-24 06:25:38,680 - obj_source: simu +2026-06-24 06:25:38,680 - obj_params: None +2026-06-24 06:25:38,680 - tilt_source: simu +2026-06-24 06:25:38,680 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:25:38,680 - +2026-06-24 06:25:38,680 - ### Initializing cache ### +2026-06-24 06:25:38,680 - use_cached_obj = False +2026-06-24 06:25:38,680 - use_cached_probe = False +2026-06-24 06:25:38,680 - use_cached_pos = False +2026-06-24 06:25:38,680 - +2026-06-24 06:25:38,680 - ### Initializing measurements ### +2026-06-24 06:25:38,680 - Loading measurements from source = 'file' +2026-06-24 06:25:38,680 - Detected measurement file type = '.h5' +2026-06-24 06:25:38,761 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:25:38,761 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:25:38,763 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0073) +2026-06-24 06:25:38,763 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:25:38,763 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:25:38,764 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:25:38,764 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:25:38,764 - Normalizing by max of the 2D mean pattern intensity: 0.0056356564 +2026-06-24 06:25:38,765 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:25:38,766 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0107, 1.2993) +2026-06-24 06:25:38,767 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:25:38,768 - Pattern total int. statistics (min, mean, max) = (172.2983, 175.1363, 176.7728), with min/max = 97.5% +2026-06-24 06:25:38,770 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0107, 1.2993) +2026-06-24 06:25:38,770 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:25:38,770 - +2026-06-24 06:25:38,770 - ### Setting up calibration ### +2026-06-24 06:25:38,770 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:25:38,770 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:25:38,770 - Radius of fitted bright field disk (RBF) = 6.82 px with meas_Npix = 128 +2026-06-24 06:25:38,770 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1065 +2026-06-24 06:25:38,770 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:25:38,770 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:25:38,999 - Initial guess: center=(63.61, 63.63), radius=6.82, Gaussian blur std=0.50 +2026-06-24 06:25:39,014 - Final fit: center=(63.61, 63.63), radius=6.82, Gaussian blur std=0.73 +2026-06-24 06:25:39,014 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.88 px with Npix = 128 +2026-06-24 06:25:39,014 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:25:39,014 - +2026-06-24 06:25:39,014 - ### Setting init_variables dict ### +2026-06-24 06:25:39,014 - Derived values given input init_params: +2026-06-24 06:25:39,014 - kv = 80.0 kV +2026-06-24 06:25:39,014 - wavelength = 0.0418 Ang +2026-06-24 06:25:39,014 - conv_angle = 11.226186752319336 mrad +2026-06-24 06:25:39,015 - Npix = 128 px +2026-06-24 06:25:39,015 - dk = 0.0391 Ang^-1 +2026-06-24 06:25:39,015 - kMax = 2.5000 Ang^-1 +2026-06-24 06:25:39,015 - da = 1.6311 mrad +2026-06-24 06:25:39,015 - angleMax = 104.3929 mrad +2026-06-24 06:25:39,015 - RBF = 6.8824 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:25:39,015 - n_alpha = 9.2991 (# conv_angle) +2026-06-24 06:25:39,015 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:25:39,015 - Rayleigh-limited resolution = 2.2690 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:25:39,015 - Real space probe extent = 25.6000 Ang +2026-06-24 06:25:39,015 - +2026-06-24 06:25:39,015 - ### Initializing probe ### +2026-06-24 06:25:39,015 - Loading probe from source = 'simu' +2026-06-24 06:25:39,015 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:25:39,015 - Start simulating STEM probe +2026-06-24 06:25:39,015 - kv = 80.0 kV +2026-06-24 06:25:39,015 - wavelength = 0.0418 Ang +2026-06-24 06:25:39,015 - conv_angle = 11.226186752319336 mrad +2026-06-24 06:25:39,015 - Npix = 128 px +2026-06-24 06:25:39,015 - dk = 0.0391 Ang^-1 +2026-06-24 06:25:39,015 - kMax = 2.5000 Ang^-1 +2026-06-24 06:25:39,015 - alpha_max = 104.3929 mrad +2026-06-24 06:25:39,015 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:25:39,015 - Rayleigh-limited resolution = 2.2690 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:25:39,015 - Real space probe extent = 25.6000 Ang +2026-06-24 06:25:39,016 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:25:39,016 - ------------------------------------------------------------------------------------ +2026-06-24 06:25:39,016 - C1,0 C1 76.3650 - Defocus (C10 = -df) +2026-06-24 06:25:39,016 - C1,2 A1 43.6550 189.85 2-fold astigmatism +2026-06-24 06:25:39,016 - C2,1 3*B2 -861.4600 297.67 Axial coma +2026-06-24 06:25:39,016 - C2,3 A2 -9.1800 51.47 3-fold astigmatism +2026-06-24 06:25:39,016 - C3,0 C3 3302940.0000 - Spherical aberration +2026-06-24 06:25:39,016 - C3,2 4*S3 7588.2150 62.37 Axial star aberration +2026-06-24 06:25:39,016 - C3,4 A3 4771.2300 55.39 4-fold astigmatism +2026-06-24 06:25:39,016 - C4,1 4*B4 111281.6250 337.52 Axial coma(4th) +2026-06-24 06:25:39,016 - C4,3 4*D4 -14763.2730 332.83 3-lobe aberration +2026-06-24 06:25:39,016 - C4,5 A4 -411061.5940 135.44 5-fold astigmatism +2026-06-24 06:25:39,016 - C5,0 C5 81083696.0000 - Spherical aberration (5th) +2026-06-24 06:25:39,016 - C5,2 6*S5 -14134963.0000 121.99 Axial star aberration(5th) +2026-06-24 06:25:39,016 - C5,4 6*R5 -9462577.0000 228.34 4-lobe aberration +2026-06-24 06:25:39,016 - C5,6 A5 -15042904.0000 339.01 6-fold astigmatism +2026-06-24 06:25:39,019 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:25:39,019 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:25:39,019 - Creating 5 new probe modes from the major mode +2026-06-24 06:25:39,019 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:25:39,266 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:25:39,267 - Orthogonalizing 6 pmodes +2026-06-24 06:25:39,280 - Sorting 6 pmodes by their intensities +2026-06-24 06:25:39,280 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:25:39,281 - sum(|probe_data|**2) = 175.14, while meas_total_ints (min, mean, max) = (172.2983, 175.1363, 176.7728) +2026-06-24 06:25:39,281 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:25:39,281 - +2026-06-24 06:25:39,281 - ### Initializing probe positions ### +2026-06-24 06:25:39,281 - Loading probe positions from source = 'simu' +2026-06-24 06:25:39,281 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:25:39,281 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3167, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:25:39,281 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:25:39,283 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:25:39,283 - crop_pos 1st and last px coords (y,x) = ([15, 15], [39, 39]) +2026-06-24 06:25:39,284 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 06:25:39,284 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:25:39,284 - +2026-06-24 06:25:39,284 - ### Initializing object ### +2026-06-24 06:25:39,284 - Loading object from source = 'simu' +2026-06-24 06:25:39,284 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:25:39,285 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:25:39,285 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 183, 183) +2026-06-24 06:25:39,285 - object extent (Z, Y, X) (Ang) = [20. 36.6 36.6] +2026-06-24 06:25:39,285 - +2026-06-24 06:25:39,285 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:25:39,285 - omode_occu (omode) = float32, (1,) +2026-06-24 06:25:39,285 - +2026-06-24 06:25:39,286 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:25:39,286 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:25:39,286 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:25:39,286 - +2026-06-24 06:25:39,286 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:25:39,286 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:25:39,286 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:25:39,286 - +2026-06-24 06:25:39,286 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:25:39,286 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:25:39,286 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:25:39,287 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:25:39,287 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:25:39,287 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (183, 183). +2026-06-24 06:25:39,287 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:25:39,287 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:25:39,287 - +2026-06-24 06:25:39,287 - ### Collecting reconstruction provenance ### +2026-06-24 06:25:39,287 - Reconstruction provenance is collected and initialized. +2026-06-24 06:25:39,287 - +2026-06-24 06:25:39,287 - ### Initializing loss function ### +2026-06-24 06:25:39,287 - Active loss types: +2026-06-24 06:25:39,287 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:25:39,287 - +2026-06-24 06:25:39,287 - ### Initializing constraint function ### +2026-06-24 06:25:39,287 - Active constraint types: +2026-06-24 06:25:39,287 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:25:39,287 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:25:39,287 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:25:39,287 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:25:39,287 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:25:39,288 - +2026-06-24 06:25:39,288 - ### Done initializing PtyRADSolver ### +2026-06-24 06:25:39,288 - +2026-06-24 06:25:39,411 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:25:39,411 - +2026-06-24 06:25:39,411 - ### Initializing PtychoModel model ### +2026-06-24 06:25:39,481 - ### PtychoModel optimizable variables ### +2026-06-24 06:25:39,481 - obja : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:25:39,481 - objp : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:25:39,481 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:25:39,481 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:25:39,482 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:25:39,482 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:25:39,482 - +2026-06-24 06:25:39,482 - ### Optimizable variables statitsics ### +2026-06-24 06:25:39,482 - Total measurement values : 4,194,304 +2026-06-24 06:25:39,482 - Total optimizing variables: 264,098 +2026-06-24 06:25:39,482 - Overdetermined ratio : 15.88 +2026-06-24 06:25:39,482 - +2026-06-24 06:25:39,482 - ### Model behavior ### +2026-06-24 06:25:39,482 - Tilt propagator : False +2026-06-24 06:25:39,482 - Change slice thickness : False +2026-06-24 06:25:39,482 - Detector blur : False +2026-06-24 06:25:39,482 - Preload data : True +2026-06-24 06:25:39,482 - On-the-fly meas padding : False +2026-06-24 06:25:39,482 - On-the-fly meas resample : False +2026-06-24 06:25:39,482 - On-the-fly simu match mode: None +2026-06-24 06:25:39,482 - +2026-06-24 06:25:39,524 - ### Done initializing PtychoModel model ### +2026-06-24 06:25:39,524 - +2026-06-24 06:25:39,524 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:25:39,524 - +2026-06-24 06:25:39,524 - ### Generating indices, batches, and output_path ### +2026-06-24 06:25:39,525 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:25:39,526 - Selecting indices with the 'full' mode +2026-06-24 06:25:39,984 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:25:40,073 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:25:40,073 - Original recon_dir_affixes = ['default'] +2026-06-24 06:25:40,073 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:25:40,079 - Path corrected for compatibility: +2026-06-24 06:25:40,079 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7.59e+03_phi32_62.4_C34_4.77e+03_phi34_55.4_C41_1.11e+05_phi41_338_C43_-1.48e+04_phi43_333_C45_-4.11e+05_phi45_135_C50_8.11e+07_C52_-1.41e+07_phi52_122_C54_-9.46e+06_phi54_228_C56_-1.5e+07_phi56_339 +2026-06-24 06:25:40,079 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339 +2026-06-24 06:25:40,081 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339' is generated! +2026-06-24 06:25:40,247 - +2026-06-24 06:25:40,248 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/20260624_062540_ptyrad_log.txt ### +2026-06-24 06:25:40,248 - +2026-06-24 06:25:40,250 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:25:40,250 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:25:40,250 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:25:41,450 - Iter: 1, Total Loss: 1.2289, loss_single: 1.2289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.443 sec +2026-06-24 06:25:41,487 - Iter: 2, Total Loss: 1.1809, loss_single: 1.1809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:25:41,522 - Iter: 3, Total Loss: 1.1418, loss_single: 1.1418, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,558 - Iter: 4, Total Loss: 1.1108, loss_single: 1.1108, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,593 - Iter: 5, Total Loss: 1.0822, loss_single: 1.0822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,629 - Iter: 6, Total Loss: 1.0493, loss_single: 1.0493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,664 - Iter: 7, Total Loss: 1.0098, loss_single: 1.0098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:41,698 - Iter: 8, Total Loss: 0.9750, loss_single: 0.9750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:41,733 - Iter: 9, Total Loss: 0.9457, loss_single: 0.9457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,769 - Iter: 10, Total Loss: 0.9130, loss_single: 0.9130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,803 - Iter: 11, Total Loss: 0.8818, loss_single: 0.8818, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:41,839 - Iter: 12, Total Loss: 0.8493, loss_single: 0.8493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,874 - Iter: 13, Total Loss: 0.8136, loss_single: 0.8136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,909 - Iter: 14, Total Loss: 0.7814, loss_single: 0.7814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:41,944 - Iter: 15, Total Loss: 0.7512, loss_single: 0.7512, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:41,979 - Iter: 16, Total Loss: 0.7205, loss_single: 0.7205, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:42,014 - Iter: 17, Total Loss: 0.6908, loss_single: 0.6908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:42,049 - Iter: 18, Total Loss: 0.6573, loss_single: 0.6573, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:42,084 - Iter: 19, Total Loss: 0.6301, loss_single: 0.6301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:42,119 - Iter: 20, Total Loss: 0.6064, loss_single: 0.6064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:42,154 - Iter: 21, Total Loss: 0.5819, loss_single: 0.5819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:42,190 - Iter: 22, Total Loss: 0.5558, loss_single: 0.5558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:42,225 - 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Iter: 89, Total Loss: 0.3404, loss_single: 0.3404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,591 - Iter: 90, Total Loss: 0.3403, loss_single: 0.3403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,626 - Iter: 91, Total Loss: 0.3402, loss_single: 0.3402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,661 - Iter: 92, Total Loss: 0.3402, loss_single: 0.3402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,696 - Iter: 93, Total Loss: 0.3401, loss_single: 0.3401, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,731 - Iter: 94, Total Loss: 0.3401, loss_single: 0.3401, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,766 - Iter: 95, Total Loss: 0.3400, loss_single: 0.3400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,801 - Iter: 96, Total Loss: 0.3400, loss_single: 0.3400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:44,836 - Iter: 97, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:44,872 - Iter: 98, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:44,907 - Iter: 99, Total Loss: 0.3398, loss_single: 0.3398, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:25:44,942 - Iter: 100, Total Loss: 0.3398, loss_single: 0.3398, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:25:45,053 - Saving summary figures for iter 100 +2026-06-24 06:25:48,672 - ### Finished 100 iterations, averaged iter_t = 0.038779 with std = 0.041 ### +2026-06-24 06:25:48,672 - +2026-06-24 06:25:48,672 - ### The PtyRADSolver is finished in 9.262 sec ### +2026-06-24 06:25:48,672 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..3bfd1baef235e46d883e1386ed27c50b6fdab61d Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/simulation_data5__sample_000023.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/simulation_data5__sample_000023.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5c7b396ff3728b970e866824f7d53103ec5c4f04 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023/c30_small__simulation_data5__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_76.4_C12_43.7_phi12_190_C21_-861_phi21_298_C23_-9.18_phi23_51.5_C30_3.3e+06_C32_7..5e+07_phi56_339/simulation_data5__sample_000023.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 11.226186752319336 + probe_aberrations: + C10: 76.36492156982422 + C12: 43.65479278564453 + C21: -861.4601440429688 + C23: -9.180187225341797 + C30: 3302940.0 + C32: 7588.21484375 + C34: 4771.22998046875 + C41: 111281.625 + C43: -14763.2734375 + C45: -411061.59375 + C50: 81083696.0 + C52: -14134963.0 + C54: -9462577.0 + C56: -15042904.0 + phi12: 189.85106390546068 + phi21: 297.6721569357151 + phi23: 51.464990452615005 + phi32: 62.36793946243632 + phi34: 55.39379722547638 + phi41: 337.5181691572489 + phi43: 332.82886180144163 + phi45: 135.44326595837816 + phi52: 121.99094884084958 + phi54: 228.3414201805303 + phi56: 339.01512805726225 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.31666725873947144 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000023_measurement.h5 + key: measurement + random_seed: 20262053 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000023 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000023 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7/20260624_062624_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7/20260624_062624_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..3447b6d06438a0050529d3953867a735351c2991 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7/20260624_062624_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:26:22,752 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:26:22,752 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:26:22,752 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:26:22,752 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:26:22,752 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:26:22,752 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:26:22,752 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:26:22,752 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:26:22,752 - +2026-06-24 06:26:22,836 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:26:22,836 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:26:22,836 - Accelerator.num_process = 1 +2026-06-24 06:26:22,836 - Accelerator.mixed_precision = no +2026-06-24 06:26:22,847 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:26:22,847 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:26:22,847 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:26:22,847 - +2026-06-24 06:26:22,847 - ### System information ### +2026-06-24 06:26:22,847 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:26:22,847 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:26:22,847 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:26:22,847 - Machine: x86_64 +2026-06-24 06:26:22,847 - Processor: x86_64 +2026-06-24 06:26:22,847 - Available CPU cores: 8 +2026-06-24 06:26:22,847 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:26:22,847 - +2026-06-24 06:26:22,847 - ### GPU information ### +2026-06-24 06:26:22,847 - CUDA Available: True +2026-06-24 06:26:22,847 - CUDA Version: 13.0 +2026-06-24 06:26:22,848 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:26:22,848 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:26:22,848 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:26:22,848 - In addition, Triton does not directly support Windows. +2026-06-24 06:26:22,848 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:26:22,863 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:26:22,863 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:26:22,863 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:26:22,863 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:26:22,863 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:26:22,863 - +2026-06-24 06:26:22,863 - ### Python information ### +2026-06-24 06:26:22,865 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:26:22,865 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:26:22,865 - +2026-06-24 06:26:22,865 - ### Packages information ### +2026-06-24 06:26:22,866 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:26:22,867 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:26:22,867 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:26:22,868 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:26:22,869 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:26:22,869 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:26:22,869 - +2026-06-24 06:26:22,869 - ### Loading params file ### +2026-06-24 06:26:22,869 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000026.yaml +2026-06-24 06:26:22,875 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:26:22,876 - Success! Params file validated and defaults applied. +2026-06-24 06:26:22,877 - +2026-06-24 06:26:22,877 - ### Setting GPU Device ### +2026-06-24 06:26:22,877 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:26:22,877 - +2026-06-24 06:26:22,877 - Random seed: 20262056 provided by params file +2026-06-24 06:26:22,877 - ### Initializing Initializer ### +2026-06-24 06:26:22,877 - init_params are displayed below: +2026-06-24 06:26:22,877 - random_seed: 20262056 +2026-06-24 06:26:22,877 - probe_illum_type: electron +2026-06-24 06:26:22,877 - probe_kv: 160.0 +2026-06-24 06:26:22,877 - probe_conv_angle: 13.512282371520996 +2026-06-24 06:26:22,877 - probe_aberrations: {'C10': -587.228, 'C12': -36.841, 'phi12': 109.208, 'C21': 440.403, 'phi21': 254.914, 'C23': -480.348, 'phi23': 204.277, 'C30': 2403710.5, 'C32': 2423.705, 'phi32': 143.078, 'C34': -11617.724, 'phi34': 6.726, 'C41': 112329.883, 'phi41': 248.797, 'C43': 53259.117, 'phi43': 358.085, 'C45': -5684.918, 'phi45': 176.329, 'C50': -318992256.0, 'C52': -8533833.0, 'phi52': 167.098, 'C54': 16564927.0, 'phi54': 23.609, 'C56': -3937610.0, 'phi56': 16.683} +2026-06-24 06:26:22,877 - beam_kev: None +2026-06-24 06:26:22,877 - probe_dRn: None +2026-06-24 06:26:22,878 - probe_Rn: None +2026-06-24 06:26:22,878 - probe_D_H: None +2026-06-24 06:26:22,878 - probe_D_FZP: None +2026-06-24 06:26:22,878 - probe_Ls: None +2026-06-24 06:26:22,878 - meas_Npix: 128 +2026-06-24 06:26:22,878 - pos_N_scans: 256 +2026-06-24 06:26:22,878 - pos_N_scan_slow: 16 +2026-06-24 06:26:22,878 - pos_N_scan_fast: 16 +2026-06-24 06:26:22,878 - pos_scan_step_size: 0.44868361949920654 +2026-06-24 06:26:22,878 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:26:22,878 - probe_pmode_max: 6 +2026-06-24 06:26:22,878 - probe_pmode_init_pows: [0.02] +2026-06-24 06:26:22,878 - obj_omode_max: 1 +2026-06-24 06:26:22,878 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:26:22,878 - obj_Nlayer: 1 +2026-06-24 06:26:22,878 - obj_slice_thickness: 20.0 +2026-06-24 06:26:22,878 - simu_Npix: None +2026-06-24 06:26:22,878 - simu_match_mode: None +2026-06-24 06:26:22,878 - meas_permute: None +2026-06-24 06:26:22,878 - meas_reshape: [256, 128, 128] +2026-06-24 06:26:22,878 - meas_flipT: [0, 0, 0] +2026-06-24 06:26:22,878 - meas_crop: None +2026-06-24 06:26:22,878 - meas_pad: None +2026-06-24 06:26:22,878 - meas_resample: None +2026-06-24 06:26:22,878 - meas_add_source_size: None +2026-06-24 06:26:22,878 - meas_add_detector_blur: None +2026-06-24 06:26:22,878 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:26:22,878 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:26:22,878 - meas_add_poisson_noise: None +2026-06-24 06:26:22,878 - meas_export: None +2026-06-24 06:26:22,878 - probe_permute: None +2026-06-24 06:26:22,878 - probe_z_shift: None +2026-06-24 06:26:22,878 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:26:22,878 - pos_scan_flipT: None +2026-06-24 06:26:22,878 - pos_scan_affine: None +2026-06-24 06:26:22,878 - pos_scan_rand_std: 0.15 +2026-06-24 06:26:22,878 - obj_z_crop: None +2026-06-24 06:26:22,878 - obj_z_pad: None +2026-06-24 06:26:22,878 - obj_z_resample: None +2026-06-24 06:26:22,878 - meas_source: file +2026-06-24 06:26:22,879 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000026_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:26:22,879 - probe_source: simu +2026-06-24 06:26:22,879 - probe_params: None +2026-06-24 06:26:22,879 - pos_source: simu +2026-06-24 06:26:22,879 - pos_params: None +2026-06-24 06:26:22,879 - obj_source: simu +2026-06-24 06:26:22,879 - obj_params: None +2026-06-24 06:26:22,879 - tilt_source: simu +2026-06-24 06:26:22,879 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:26:22,879 - +2026-06-24 06:26:22,879 - ### Initializing cache ### +2026-06-24 06:26:22,879 - use_cached_obj = False +2026-06-24 06:26:22,879 - use_cached_probe = False +2026-06-24 06:26:22,879 - use_cached_pos = False +2026-06-24 06:26:22,879 - +2026-06-24 06:26:22,879 - ### Initializing measurements ### +2026-06-24 06:26:22,879 - Loading measurements from source = 'file' +2026-06-24 06:26:22,879 - Detected measurement file type = '.h5' +2026-06-24 06:26:22,951 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:26:22,951 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:26:22,953 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0032) +2026-06-24 06:26:22,953 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:26:22,953 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:26:22,955 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:26:22,955 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:26:22,955 - Normalizing by max of the 2D mean pattern intensity: 0.0022464502 +2026-06-24 06:26:22,956 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:26:22,957 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0272, 1.4333) +2026-06-24 06:26:22,958 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:26:22,959 - Pattern total int. statistics (min, mean, max) = (440.3113, 445.6064, 451.1466), with min/max = 97.6% +2026-06-24 06:26:22,960 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0272, 1.4333) +2026-06-24 06:26:22,960 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:26:22,960 - +2026-06-24 06:26:22,960 - ### Setting up calibration ### +2026-06-24 06:26:22,960 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:26:22,960 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:26:22,960 - Radius of fitted bright field disk (RBF) = 12.01 px with meas_Npix = 128 +2026-06-24 06:26:22,960 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1876 +2026-06-24 06:26:22,960 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:26:22,961 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:26:23,185 - Initial guess: center=(63.62, 63.63), radius=12.01, Gaussian blur std=0.50 +2026-06-24 06:26:23,194 - Final fit: center=(63.62, 63.63), radius=12.01, Gaussian blur std=0.54 +2026-06-24 06:26:23,194 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.13 px with Npix = 128 +2026-06-24 06:26:23,194 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:26:23,194 - +2026-06-24 06:26:23,194 - ### Setting init_variables dict ### +2026-06-24 06:26:23,194 - Derived values given input init_params: +2026-06-24 06:26:23,194 - kv = 160.0 kV +2026-06-24 06:26:23,194 - wavelength = 0.0285 Ang +2026-06-24 06:26:23,194 - conv_angle = 13.512282371520996 mrad +2026-06-24 06:26:23,194 - Npix = 128 px +2026-06-24 06:26:23,194 - dk = 0.0391 Ang^-1 +2026-06-24 06:26:23,194 - kMax = 2.5000 Ang^-1 +2026-06-24 06:26:23,194 - da = 1.1137 mrad +2026-06-24 06:26:23,194 - angleMax = 71.2751 mrad +2026-06-24 06:26:23,194 - RBF = 12.1331 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:26:23,194 - n_alpha = 5.2748 (# conv_angle) +2026-06-24 06:26:23,194 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:26:23,194 - Rayleigh-limited resolution = 1.2871 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:26:23,194 - Real space probe extent = 25.6000 Ang +2026-06-24 06:26:23,195 - +2026-06-24 06:26:23,195 - ### Initializing probe ### +2026-06-24 06:26:23,195 - Loading probe from source = 'simu' +2026-06-24 06:26:23,195 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:26:23,195 - Start simulating STEM probe +2026-06-24 06:26:23,195 - kv = 160.0 kV +2026-06-24 06:26:23,195 - wavelength = 0.0285 Ang +2026-06-24 06:26:23,195 - conv_angle = 13.512282371520996 mrad +2026-06-24 06:26:23,195 - Npix = 128 px +2026-06-24 06:26:23,195 - dk = 0.0391 Ang^-1 +2026-06-24 06:26:23,195 - kMax = 2.5000 Ang^-1 +2026-06-24 06:26:23,195 - alpha_max = 71.2751 mrad +2026-06-24 06:26:23,195 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:26:23,195 - Rayleigh-limited resolution = 1.2871 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:26:23,195 - Real space probe extent = 25.6000 Ang +2026-06-24 06:26:23,195 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:26:23,195 - ------------------------------------------------------------------------------------- +2026-06-24 06:26:23,195 - C1,0 C1 -587.2280 - Defocus (C10 = -df) +2026-06-24 06:26:23,195 - C1,2 A1 -36.8410 109.21 2-fold astigmatism +2026-06-24 06:26:23,195 - C2,1 3*B2 440.4030 254.91 Axial coma +2026-06-24 06:26:23,195 - C2,3 A2 -480.3480 204.28 3-fold astigmatism +2026-06-24 06:26:23,195 - C3,0 C3 2403710.5000 - Spherical aberration +2026-06-24 06:26:23,195 - C3,2 4*S3 2423.7050 143.08 Axial star aberration +2026-06-24 06:26:23,195 - C3,4 A3 -11617.7240 6.73 4-fold astigmatism +2026-06-24 06:26:23,195 - C4,1 4*B4 112329.8830 248.80 Axial coma(4th) +2026-06-24 06:26:23,196 - C4,3 4*D4 53259.1170 358.08 3-lobe aberration +2026-06-24 06:26:23,196 - C4,5 A4 -5684.9180 176.33 5-fold astigmatism +2026-06-24 06:26:23,196 - C5,0 C5 -318992256.0000 - Spherical aberration (5th) +2026-06-24 06:26:23,196 - C5,2 6*S5 -8533833.0000 167.10 Axial star aberration(5th) +2026-06-24 06:26:23,196 - C5,4 6*R5 16564927.0000 23.61 4-lobe aberration +2026-06-24 06:26:23,196 - C5,6 A5 -3937610.0000 16.68 6-fold astigmatism +2026-06-24 06:26:23,198 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:26:23,198 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:26:23,198 - Creating 5 new probe modes from the major mode +2026-06-24 06:26:23,199 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:26:23,295 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:26:23,296 - Orthogonalizing 6 pmodes +2026-06-24 06:26:23,298 - Sorting 6 pmodes by their intensities +2026-06-24 06:26:23,299 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:26:23,299 - sum(|probe_data|**2) = 445.61, while meas_total_ints (min, mean, max) = (440.3113, 445.6064, 451.1466) +2026-06-24 06:26:23,300 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:26:23,300 - +2026-06-24 06:26:23,300 - ### Initializing probe positions ### +2026-06-24 06:26:23,300 - Loading probe positions from source = 'simu' +2026-06-24 06:26:23,300 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:26:23,300 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4487, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:26:23,300 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:26:23,302 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:26:23,302 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 50]) +2026-06-24 06:26:23,302 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 06:26:23,302 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:26:23,302 - +2026-06-24 06:26:23,302 - ### Initializing object ### +2026-06-24 06:26:23,302 - Loading object from source = 'simu' +2026-06-24 06:26:23,302 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:26:23,304 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:26:23,304 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 195, 195) +2026-06-24 06:26:23,304 - object extent (Z, Y, X) (Ang) = [20. 39. 39.] +2026-06-24 06:26:23,304 - +2026-06-24 06:26:23,304 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:26:23,304 - omode_occu (omode) = float32, (1,) +2026-06-24 06:26:23,304 - +2026-06-24 06:26:23,304 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:26:23,304 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:26:23,305 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:26:23,305 - +2026-06-24 06:26:23,305 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:26:23,305 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:26:23,305 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:26:23,305 - +2026-06-24 06:26:23,305 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:26:23,305 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:26:23,305 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:26:23,305 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:26:23,305 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:26:23,305 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (195, 195). +2026-06-24 06:26:23,305 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:26:23,306 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:26:23,306 - +2026-06-24 06:26:23,306 - ### Collecting reconstruction provenance ### +2026-06-24 06:26:23,306 - Reconstruction provenance is collected and initialized. +2026-06-24 06:26:23,306 - +2026-06-24 06:26:23,306 - ### Initializing loss function ### +2026-06-24 06:26:23,306 - Active loss types: +2026-06-24 06:26:23,306 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:26:23,306 - +2026-06-24 06:26:23,306 - ### Initializing constraint function ### +2026-06-24 06:26:23,306 - Active constraint types: +2026-06-24 06:26:23,306 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:26:23,306 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:26:23,306 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:26:23,306 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:26:23,306 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:26:23,306 - +2026-06-24 06:26:23,306 - ### Done initializing PtyRADSolver ### +2026-06-24 06:26:23,306 - +2026-06-24 06:26:23,432 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:26:23,432 - +2026-06-24 06:26:23,433 - ### Initializing PtychoModel model ### +2026-06-24 06:26:23,503 - ### PtychoModel optimizable variables ### +2026-06-24 06:26:23,503 - obja : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:23,503 - objp : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:23,503 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:26:23,503 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:26:23,504 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:26:23,504 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:23,504 - +2026-06-24 06:26:23,504 - ### Optimizable variables statitsics ### +2026-06-24 06:26:23,504 - Total measurement values : 4,194,304 +2026-06-24 06:26:23,504 - Total optimizing variables: 273,170 +2026-06-24 06:26:23,504 - Overdetermined ratio : 15.35 +2026-06-24 06:26:23,504 - +2026-06-24 06:26:23,504 - ### Model behavior ### +2026-06-24 06:26:23,504 - Tilt propagator : False +2026-06-24 06:26:23,504 - Change slice thickness : False +2026-06-24 06:26:23,504 - Detector blur : False +2026-06-24 06:26:23,504 - Preload data : True +2026-06-24 06:26:23,504 - On-the-fly meas padding : False +2026-06-24 06:26:23,504 - On-the-fly meas resample : False +2026-06-24 06:26:23,504 - On-the-fly simu match mode: None +2026-06-24 06:26:23,504 - +2026-06-24 06:26:23,545 - ### Done initializing PtychoModel model ### +2026-06-24 06:26:23,545 - +2026-06-24 06:26:23,545 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:26:23,545 - +2026-06-24 06:26:23,545 - ### Generating indices, batches, and output_path ### +2026-06-24 06:26:23,547 - d90 = 49.000 px or 9.800 Ang +2026-06-24 06:26:23,547 - Selecting indices with the 'full' mode +2026-06-24 06:26:24,013 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:26:24,090 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:26:24,090 - Original recon_dir_affixes = ['default'] +2026-06-24 06:26:24,091 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:26:24,097 - Path corrected for compatibility: +2026-06-24 06:26:24,097 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143_C34_-1.16e+04_phi34_6.73_C41_1.12e+05_phi41_249_C43_5.33e+04_phi43_358_C45_-5.68e+03_phi45_176_C50_-3.19e+08_C52_-8.53e+06_phi52_167_C54_1.66e+07_phi54_23.6_C56_-3.94e+06_phi56_16.7 +2026-06-24 06:26:24,097 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7 +2026-06-24 06:26:24,099 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7' is generated! +2026-06-24 06:26:24,250 - +2026-06-24 06:26:24,251 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7/20260624_062624_ptyrad_log.txt ### +2026-06-24 06:26:24,251 - +2026-06-24 06:26:24,253 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:26:24,253 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:26:24,253 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:26:25,451 - Iter: 1, Total Loss: 0.8797, loss_single: 0.8797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:26:25,489 - Iter: 2, Total Loss: 0.8349, loss_single: 0.8349, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:26:25,525 - Iter: 3, Total Loss: 0.8001, loss_single: 0.8001, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,560 - Iter: 4, Total Loss: 0.7667, loss_single: 0.7667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,596 - Iter: 5, Total Loss: 0.7333, loss_single: 0.7333, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,632 - Iter: 6, Total Loss: 0.7029, loss_single: 0.7029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:25,667 - Iter: 7, Total Loss: 0.6734, loss_single: 0.6734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,703 - Iter: 8, Total Loss: 0.6479, loss_single: 0.6479, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:25,738 - Iter: 9, Total Loss: 0.6274, loss_single: 0.6274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,773 - Iter: 10, Total Loss: 0.6046, loss_single: 0.6046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,809 - Iter: 11, Total Loss: 0.5799, loss_single: 0.5799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:25,844 - Iter: 12, Total Loss: 0.5585, loss_single: 0.5585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,879 - Iter: 13, Total Loss: 0.5383, loss_single: 0.5383, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,916 - Iter: 14, Total Loss: 0.5204, loss_single: 0.5204, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:25,952 - Iter: 15, Total Loss: 0.5049, loss_single: 0.5049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:25,988 - Iter: 16, Total Loss: 0.4889, loss_single: 0.4889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:26,024 - Iter: 17, Total Loss: 0.4741, loss_single: 0.4741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,059 - Iter: 18, Total Loss: 0.4596, loss_single: 0.4596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,095 - Iter: 19, Total Loss: 0.4477, loss_single: 0.4477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,131 - Iter: 20, Total Loss: 0.4383, loss_single: 0.4383, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,166 - Iter: 21, Total Loss: 0.4308, loss_single: 0.4308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,202 - Iter: 22, Total Loss: 0.4238, loss_single: 0.4238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,237 - Iter: 23, Total Loss: 0.4182, loss_single: 0.4182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,273 - Iter: 24, Total Loss: 0.4131, loss_single: 0.4131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,308 - Iter: 25, Total Loss: 0.4080, loss_single: 0.4080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,343 - Iter: 26, Total Loss: 0.4039, loss_single: 0.4039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:26:26,379 - Iter: 27, Total Loss: 0.3999, loss_single: 0.3999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,414 - Iter: 28, Total Loss: 0.3959, loss_single: 0.3959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,453 - Iter: 29, Total Loss: 0.3928, loss_single: 0.3928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:26:26,489 - Iter: 30, Total Loss: 0.3905, loss_single: 0.3905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,524 - Iter: 31, Total Loss: 0.3887, loss_single: 0.3887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,560 - Iter: 32, Total Loss: 0.3876, loss_single: 0.3876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,595 - Iter: 33, Total Loss: 0.3868, loss_single: 0.3868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,631 - Iter: 34, Total Loss: 0.3862, loss_single: 0.3862, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,666 - Iter: 35, Total Loss: 0.3857, loss_single: 0.3857, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,701 - Iter: 36, Total Loss: 0.3852, loss_single: 0.3852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,736 - Iter: 37, Total Loss: 0.3848, loss_single: 0.3848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,772 - Iter: 38, Total Loss: 0.3844, loss_single: 0.3844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,807 - Iter: 39, Total Loss: 0.3841, loss_single: 0.3841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,843 - Iter: 40, Total Loss: 0.3838, loss_single: 0.3838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,882 - Iter: 41, Total Loss: 0.3836, loss_single: 0.3836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:26,917 - Iter: 42, Total Loss: 0.3833, loss_single: 0.3833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,953 - Iter: 43, Total Loss: 0.3831, loss_single: 0.3831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:26,988 - Iter: 44, Total Loss: 0.3829, loss_single: 0.3829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,023 - Iter: 45, Total Loss: 0.3828, loss_single: 0.3828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,058 - Iter: 46, Total Loss: 0.3826, loss_single: 0.3826, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,094 - Iter: 47, Total Loss: 0.3825, loss_single: 0.3825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,129 - Iter: 48, Total Loss: 0.3824, loss_single: 0.3824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,164 - Iter: 49, Total Loss: 0.3823, loss_single: 0.3823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,199 - Iter: 50, Total Loss: 0.3822, loss_single: 0.3822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,235 - Iter: 51, Total Loss: 0.3822, loss_single: 0.3822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,270 - Iter: 52, Total Loss: 0.3821, loss_single: 0.3821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,305 - Iter: 53, Total Loss: 0.3820, loss_single: 0.3820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,341 - Iter: 54, Total Loss: 0.3819, loss_single: 0.3819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,376 - Iter: 55, Total Loss: 0.3818, loss_single: 0.3818, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,412 - Iter: 56, Total Loss: 0.3817, loss_single: 0.3817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,447 - Iter: 57, Total Loss: 0.3816, loss_single: 0.3816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,483 - Iter: 58, Total Loss: 0.3816, loss_single: 0.3816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,519 - Iter: 59, Total Loss: 0.3815, loss_single: 0.3815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,554 - Iter: 60, Total Loss: 0.3814, loss_single: 0.3814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,589 - Iter: 61, Total Loss: 0.3814, loss_single: 0.3814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,625 - Iter: 62, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,660 - Iter: 63, Total Loss: 0.3812, loss_single: 0.3812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,696 - Iter: 64, 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in 0.035 sec +2026-06-24 06:26:27,908 - Iter: 70, Total Loss: 0.3807, loss_single: 0.3807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,943 - Iter: 71, Total Loss: 0.3806, loss_single: 0.3806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:27,979 - Iter: 72, Total Loss: 0.3806, loss_single: 0.3806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,014 - Iter: 73, Total Loss: 0.3805, loss_single: 0.3805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,050 - Iter: 74, Total Loss: 0.3805, loss_single: 0.3805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,086 - Iter: 75, Total Loss: 0.3804, loss_single: 0.3804, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.3801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,333 - Iter: 82, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,368 - Iter: 83, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,404 - Iter: 84, Total Loss: 0.3799, loss_single: 0.3799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,439 - Iter: 85, Total Loss: 0.3799, loss_single: 0.3799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,475 - Iter: 86, Total Loss: 0.3799, loss_single: 0.3799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,511 - Iter: 87, Total Loss: 0.3798, loss_single: 0.3798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,546 - Iter: 88, Total Loss: 0.3798, loss_single: 0.3798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,582 - Iter: 89, Total Loss: 0.3797, loss_single: 0.3797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,623 - Iter: 90, Total Loss: 0.3796, loss_single: 0.3796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,658 - Iter: 91, Total Loss: 0.3796, loss_single: 0.3796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,696 - Iter: 92, Total Loss: 0.3795, loss_single: 0.3795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:26:28,732 - Iter: 93, Total Loss: 0.3795, loss_single: 0.3795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,767 - Iter: 94, Total Loss: 0.3794, loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,802 - Iter: 95, Total Loss: 0.3794, loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,838 - Iter: 96, Total Loss: 0.3794, loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,873 - Iter: 97, Total Loss: 0.3794, loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,909 - Iter: 98, Total Loss: 0.3793, loss_single: 0.3793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,945 - Iter: 99, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:28,980 - Iter: 100, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:29,091 - Saving summary figures for iter 100 +2026-06-24 06:26:32,734 - ### Finished 100 iterations, averaged iter_t = 0.039148 with std = 0.040 ### +2026-06-24 06:26:32,734 - +2026-06-24 06:26:32,734 - ### The PtyRADSolver is finished in 9.302 sec ### +2026-06-24 06:26:32,734 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000026/c30_small__simulation_data5__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-587_C12_-36.8_phi12_109_C21_440_phi21_255_C23_-480_phi23_204_C30_2.4e+06_C32_2.42e+03_phi32_143.7/simulation_data5__sample_000026.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 13.512282371520996 + probe_aberrations: + C10: -587.2276611328125 + C12: -36.84132766723633 + C21: 440.4028625488281 + C23: -480.348388671875 + C30: 2403710.5 + C32: 2423.704833984375 + C34: -11617.7236328125 + C41: 112329.8828125 + C43: 53259.1171875 + C45: -5684.91845703125 + C50: -318992256.0 + C52: -8533833.0 + C54: 16564927.0 + C56: -3937610.0 + phi12: 109.20753263930787 + phi21: 254.91421650495153 + phi23: 204.27694252690452 + phi32: 143.0780514126184 + phi34: 6.725504995038081 + phi41: 248.79677123520796 + phi43: 358.08526210674796 + phi45: 176.32921546218137 + phi52: 167.09790061020732 + phi54: 23.60851813029781 + phi56: 16.683105877971325 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.44868361949920654 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000026_measurement.h5 + key: measurement + random_seed: 20262056 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:b4b75499a61b9a1a64e29463d8f9038e4434f7017467a26b02e1e56d9a13894c +size 48103 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/20260624_062654_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/20260624_062654_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..7b4ed71521de8172e42532d06f925e77344cfc33 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/20260624_062654_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:26:52,504 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:26:52,504 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:26:52,504 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:26:52,504 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:26:52,504 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:26:52,504 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:26:52,504 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:26:52,504 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:26:52,504 - +2026-06-24 06:26:52,624 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:26:52,624 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:26:52,624 - Accelerator.num_process = 1 +2026-06-24 06:26:52,624 - Accelerator.mixed_precision = no +2026-06-24 06:26:52,635 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:26:52,635 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:26:52,635 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:26:52,635 - +2026-06-24 06:26:52,635 - ### System information ### +2026-06-24 06:26:52,635 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:26:52,635 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:26:52,635 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:26:52,635 - Machine: x86_64 +2026-06-24 06:26:52,635 - Processor: x86_64 +2026-06-24 06:26:52,635 - Available CPU cores: 8 +2026-06-24 06:26:52,635 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:26:52,635 - +2026-06-24 06:26:52,635 - ### GPU information ### +2026-06-24 06:26:52,635 - CUDA Available: True +2026-06-24 06:26:52,635 - CUDA Version: 13.0 +2026-06-24 06:26:52,636 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:26:52,636 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:26:52,636 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:26:52,636 - In addition, Triton does not directly support Windows. +2026-06-24 06:26:52,636 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:26:52,651 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:26:52,651 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:26:52,651 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:26:52,651 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:26:52,651 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:26:52,651 - +2026-06-24 06:26:52,651 - ### Python information ### +2026-06-24 06:26:52,653 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:26:52,653 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:26:52,653 - +2026-06-24 06:26:52,653 - ### Packages information ### +2026-06-24 06:26:52,654 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:26:52,655 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:26:52,655 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:26:52,656 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:26:52,657 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:26:52,657 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:26:52,657 - +2026-06-24 06:26:52,657 - ### Loading params file ### +2026-06-24 06:26:52,657 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000028.yaml +2026-06-24 06:26:52,663 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:26:52,664 - Success! Params file validated and defaults applied. +2026-06-24 06:26:52,664 - +2026-06-24 06:26:52,664 - ### Setting GPU Device ### +2026-06-24 06:26:52,665 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:26:52,665 - +2026-06-24 06:26:52,665 - Random seed: 20262058 provided by params file +2026-06-24 06:26:52,665 - ### Initializing Initializer ### +2026-06-24 06:26:52,665 - init_params are displayed below: +2026-06-24 06:26:52,665 - random_seed: 20262058 +2026-06-24 06:26:52,665 - probe_illum_type: electron +2026-06-24 06:26:52,665 - probe_kv: 120.0 +2026-06-24 06:26:52,665 - probe_conv_angle: 13.67462158203125 +2026-06-24 06:26:52,665 - probe_aberrations: {'C10': -37.883, 'C12': -4.039, 'phi12': 269.34, 'C21': 890.349, 'phi21': 106.681, 'C23': -227.692, 'phi23': 154.013, 'C30': 2792412.75, 'C32': -9213.668, 'phi32': 200.215, 'C34': 11987.289, 'phi34': 152.323, 'C41': 4655.684, 'phi41': 350.778, 'C43': 307885.125, 'phi43': 73.969, 'C45': -61559.816, 'phi45': 335.655, 'C50': 336173280.0, 'C52': 15304924.0, 'phi52': 239.516, 'C54': -13701384.0, 'phi54': 296.539, 'C56': 2372729.75, 'phi56': 31.274} +2026-06-24 06:26:52,665 - beam_kev: None +2026-06-24 06:26:52,665 - probe_dRn: None +2026-06-24 06:26:52,665 - probe_Rn: None +2026-06-24 06:26:52,665 - probe_D_H: None +2026-06-24 06:26:52,665 - probe_D_FZP: None +2026-06-24 06:26:52,665 - probe_Ls: None +2026-06-24 06:26:52,665 - meas_Npix: 128 +2026-06-24 06:26:52,665 - pos_N_scans: 256 +2026-06-24 06:26:52,666 - pos_N_scan_slow: 16 +2026-06-24 06:26:52,666 - pos_N_scan_fast: 16 +2026-06-24 06:26:52,666 - pos_scan_step_size: 0.4896918833255768 +2026-06-24 06:26:52,666 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:26:52,666 - probe_pmode_max: 6 +2026-06-24 06:26:52,666 - probe_pmode_init_pows: [0.02] +2026-06-24 06:26:52,666 - obj_omode_max: 1 +2026-06-24 06:26:52,666 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:26:52,666 - obj_Nlayer: 1 +2026-06-24 06:26:52,666 - obj_slice_thickness: 20.0 +2026-06-24 06:26:52,666 - simu_Npix: None +2026-06-24 06:26:52,666 - simu_match_mode: None +2026-06-24 06:26:52,666 - meas_permute: None +2026-06-24 06:26:52,666 - meas_reshape: [256, 128, 128] +2026-06-24 06:26:52,666 - meas_flipT: [0, 0, 0] +2026-06-24 06:26:52,666 - meas_crop: None +2026-06-24 06:26:52,666 - meas_pad: None +2026-06-24 06:26:52,666 - meas_resample: None +2026-06-24 06:26:52,666 - meas_add_source_size: None +2026-06-24 06:26:52,666 - meas_add_detector_blur: None +2026-06-24 06:26:52,666 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:26:52,666 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:26:52,666 - meas_add_poisson_noise: None +2026-06-24 06:26:52,666 - meas_export: None +2026-06-24 06:26:52,666 - probe_permute: None +2026-06-24 06:26:52,666 - probe_z_shift: None +2026-06-24 06:26:52,666 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:26:52,666 - pos_scan_flipT: None +2026-06-24 06:26:52,666 - pos_scan_affine: None +2026-06-24 06:26:52,666 - pos_scan_rand_std: 0.15 +2026-06-24 06:26:52,666 - obj_z_crop: None +2026-06-24 06:26:52,666 - obj_z_pad: None +2026-06-24 06:26:52,666 - obj_z_resample: None +2026-06-24 06:26:52,666 - meas_source: file +2026-06-24 06:26:52,666 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000028_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:26:52,666 - probe_source: simu +2026-06-24 06:26:52,666 - probe_params: None +2026-06-24 06:26:52,666 - pos_source: simu +2026-06-24 06:26:52,666 - pos_params: None +2026-06-24 06:26:52,666 - obj_source: simu +2026-06-24 06:26:52,667 - obj_params: None +2026-06-24 06:26:52,667 - tilt_source: simu +2026-06-24 06:26:52,667 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:26:52,667 - +2026-06-24 06:26:52,667 - ### Initializing cache ### +2026-06-24 06:26:52,667 - use_cached_obj = False +2026-06-24 06:26:52,667 - use_cached_probe = False +2026-06-24 06:26:52,667 - use_cached_pos = False +2026-06-24 06:26:52,667 - +2026-06-24 06:26:52,667 - ### Initializing measurements ### +2026-06-24 06:26:52,667 - Loading measurements from source = 'file' +2026-06-24 06:26:52,667 - Detected measurement file type = '.h5' +2026-06-24 06:26:52,744 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:26:52,744 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:26:52,746 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0041) +2026-06-24 06:26:52,746 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:26:52,746 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:26:52,747 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:26:52,747 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:26:52,748 - Normalizing by max of the 2D mean pattern intensity: 0.0027690216 +2026-06-24 06:26:52,749 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:26:52,750 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0220, 1.4694) +2026-06-24 06:26:52,750 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:26:52,752 - Pattern total int. statistics (min, mean, max) = (357.1419, 360.3317, 363.8383), with min/max = 98.2% +2026-06-24 06:26:52,753 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0220, 1.4694) +2026-06-24 06:26:52,753 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:26:52,753 - +2026-06-24 06:26:52,753 - ### Setting up calibration ### +2026-06-24 06:26:52,753 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:26:52,753 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:26:52,753 - Radius of fitted bright field disk (RBF) = 10.33 px with meas_Npix = 128 +2026-06-24 06:26:52,753 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1613 +2026-06-24 06:26:52,753 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:26:52,753 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:26:52,979 - Initial guess: center=(63.62, 63.61), radius=10.33, Gaussian blur std=0.50 +2026-06-24 06:26:52,989 - Final fit: center=(63.62, 63.61), radius=10.33, Gaussian blur std=0.55 +2026-06-24 06:26:52,989 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.45 px with Npix = 128 +2026-06-24 06:26:52,990 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:26:52,990 - +2026-06-24 06:26:52,990 - ### Setting init_variables dict ### +2026-06-24 06:26:52,990 - Derived values given input init_params: +2026-06-24 06:26:52,990 - kv = 120.0 kV +2026-06-24 06:26:52,990 - wavelength = 0.0335 Ang +2026-06-24 06:26:52,990 - conv_angle = 13.67462158203125 mrad +2026-06-24 06:26:52,990 - Npix = 128 px +2026-06-24 06:26:52,990 - dk = 0.0391 Ang^-1 +2026-06-24 06:26:52,990 - kMax = 2.5000 Ang^-1 +2026-06-24 06:26:52,990 - da = 1.3083 mrad +2026-06-24 06:26:52,990 - angleMax = 83.7304 mrad +2026-06-24 06:26:52,990 - RBF = 10.4523 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:26:52,990 - n_alpha = 6.1230 (# conv_angle) +2026-06-24 06:26:52,990 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:26:52,990 - Rayleigh-limited resolution = 1.4940 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:26:52,990 - Real space probe extent = 25.6000 Ang +2026-06-24 06:26:52,990 - +2026-06-24 06:26:52,990 - ### Initializing probe ### +2026-06-24 06:26:52,990 - Loading probe from source = 'simu' +2026-06-24 06:26:52,990 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:26:52,991 - Start simulating STEM probe +2026-06-24 06:26:52,991 - kv = 120.0 kV +2026-06-24 06:26:52,991 - wavelength = 0.0335 Ang +2026-06-24 06:26:52,991 - conv_angle = 13.67462158203125 mrad +2026-06-24 06:26:52,991 - Npix = 128 px +2026-06-24 06:26:52,991 - dk = 0.0391 Ang^-1 +2026-06-24 06:26:52,991 - kMax = 2.5000 Ang^-1 +2026-06-24 06:26:52,991 - alpha_max = 83.7304 mrad +2026-06-24 06:26:52,991 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:26:52,991 - Rayleigh-limited resolution = 1.4940 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:26:52,991 - Real space probe extent = 25.6000 Ang +2026-06-24 06:26:52,991 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:26:52,991 - ------------------------------------------------------------------------------------ +2026-06-24 06:26:52,991 - C1,0 C1 -37.8830 - Defocus (C10 = -df) +2026-06-24 06:26:52,991 - C1,2 A1 -4.0390 269.34 2-fold astigmatism +2026-06-24 06:26:52,991 - C2,1 3*B2 890.3490 106.68 Axial coma +2026-06-24 06:26:52,991 - C2,3 A2 -227.6920 154.01 3-fold astigmatism +2026-06-24 06:26:52,991 - C3,0 C3 2792412.7500 - Spherical aberration +2026-06-24 06:26:52,991 - C3,2 4*S3 -9213.6680 200.22 Axial star aberration +2026-06-24 06:26:52,991 - C3,4 A3 11987.2890 152.32 4-fold astigmatism +2026-06-24 06:26:52,991 - C4,1 4*B4 4655.6840 350.78 Axial coma(4th) +2026-06-24 06:26:52,991 - C4,3 4*D4 307885.1250 73.97 3-lobe aberration +2026-06-24 06:26:52,991 - C4,5 A4 -61559.8160 335.65 5-fold astigmatism +2026-06-24 06:26:52,991 - C5,0 C5 336173280.0000 - Spherical aberration (5th) +2026-06-24 06:26:52,991 - C5,2 6*S5 15304924.0000 239.52 Axial star aberration(5th) +2026-06-24 06:26:52,991 - C5,4 6*R5 -13701384.0000 296.54 4-lobe aberration +2026-06-24 06:26:52,991 - C5,6 A5 2372729.7500 31.27 6-fold astigmatism +2026-06-24 06:26:52,994 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:26:52,994 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:26:52,994 - Creating 5 new probe modes from the major mode +2026-06-24 06:26:52,994 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:26:53,107 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:26:53,109 - Orthogonalizing 6 pmodes +2026-06-24 06:26:53,112 - Sorting 6 pmodes by their intensities +2026-06-24 06:26:53,112 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:26:53,113 - sum(|probe_data|**2) = 360.33, while meas_total_ints (min, mean, max) = (357.1419, 360.3317, 363.8383) +2026-06-24 06:26:53,113 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:26:53,113 - +2026-06-24 06:26:53,113 - ### Initializing probe positions ### +2026-06-24 06:26:53,113 - Loading probe positions from source = 'simu' +2026-06-24 06:26:53,113 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:26:53,113 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4897, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:26:53,113 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:26:53,115 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:26:53,115 - crop_pos 1st and last px coords (y,x) = ([17, 17], [53, 53]) +2026-06-24 06:26:53,116 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:26:53,116 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:26:53,116 - +2026-06-24 06:26:53,116 - ### Initializing object ### +2026-06-24 06:26:53,116 - Loading object from source = 'simu' +2026-06-24 06:26:53,116 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:26:53,117 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:26:53,117 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 06:26:53,117 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 06:26:53,117 - +2026-06-24 06:26:53,118 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:26:53,118 - omode_occu (omode) = float32, (1,) +2026-06-24 06:26:53,118 - +2026-06-24 06:26:53,118 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:26:53,118 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:26:53,118 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:26:53,118 - +2026-06-24 06:26:53,118 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:26:53,118 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:26:53,118 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:26:53,119 - +2026-06-24 06:26:53,119 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:26:53,119 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:26:53,119 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:26:53,119 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:26:53,119 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:26:53,119 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 06:26:53,119 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:26:53,119 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:26:53,119 - +2026-06-24 06:26:53,119 - ### Collecting reconstruction provenance ### +2026-06-24 06:26:53,119 - Reconstruction provenance is collected and initialized. +2026-06-24 06:26:53,119 - +2026-06-24 06:26:53,119 - ### Initializing loss function ### +2026-06-24 06:26:53,119 - Active loss types: +2026-06-24 06:26:53,119 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:26:53,119 - +2026-06-24 06:26:53,119 - ### Initializing constraint function ### +2026-06-24 06:26:53,119 - Active constraint types: +2026-06-24 06:26:53,119 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:26:53,119 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:26:53,120 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:26:53,120 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:26:53,120 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:26:53,120 - +2026-06-24 06:26:53,120 - ### Done initializing PtyRADSolver ### +2026-06-24 06:26:53,120 - +2026-06-24 06:26:53,246 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:26:53,246 - +2026-06-24 06:26:53,246 - ### Initializing PtychoModel model ### +2026-06-24 06:26:53,317 - ### PtychoModel optimizable variables ### +2026-06-24 06:26:53,317 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:53,317 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:53,317 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:26:53,317 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:26:53,317 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:26:53,317 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:26:53,317 - +2026-06-24 06:26:53,317 - ### Optimizable variables statitsics ### +2026-06-24 06:26:53,317 - Total measurement values : 4,194,304 +2026-06-24 06:26:53,317 - Total optimizing variables: 276,322 +2026-06-24 06:26:53,318 - Overdetermined ratio : 15.18 +2026-06-24 06:26:53,318 - +2026-06-24 06:26:53,318 - ### Model behavior ### +2026-06-24 06:26:53,318 - Tilt propagator : False +2026-06-24 06:26:53,318 - Change slice thickness : False +2026-06-24 06:26:53,318 - Detector blur : False +2026-06-24 06:26:53,318 - Preload data : True +2026-06-24 06:26:53,318 - On-the-fly meas padding : False +2026-06-24 06:26:53,318 - On-the-fly meas resample : False +2026-06-24 06:26:53,318 - On-the-fly simu match mode: None +2026-06-24 06:26:53,318 - +2026-06-24 06:26:53,359 - ### Done initializing PtychoModel model ### +2026-06-24 06:26:53,359 - +2026-06-24 06:26:53,359 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:26:53,360 - +2026-06-24 06:26:53,360 - ### Generating indices, batches, and output_path ### +2026-06-24 06:26:53,361 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:26:53,361 - Selecting indices with the 'full' mode +2026-06-24 06:26:53,826 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:26:53,901 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:26:53,901 - Original recon_dir_affixes = ['default'] +2026-06-24 06:26:53,901 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:26:53,907 - Path corrected for compatibility: +2026-06-24 06:26:53,907 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_200_C34_1.2e+04_phi34_152_C41_4.66e+03_phi41_351_C43_3.08e+05_phi43_74_C45_-6.16e+04_phi45_336_C50_3.36e+08_C52_1.53e+07_phi52_240_C54_-1.37e+07_phi54_297_C56_2.37e+06_phi56_31.3 +2026-06-24 06:26:53,908 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3 +2026-06-24 06:26:53,908 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3' is generated! +2026-06-24 06:26:54,059 - +2026-06-24 06:26:54,060 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/20260624_062654_ptyrad_log.txt ### +2026-06-24 06:26:54,060 - +2026-06-24 06:26:54,062 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:26:54,062 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:26:54,062 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:26:55,260 - Iter: 1, Total Loss: 1.0134, loss_single: 1.0134, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:26:55,298 - Iter: 2, Total Loss: 0.9712, loss_single: 0.9712, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:26:55,334 - Iter: 3, Total Loss: 0.9381, loss_single: 0.9381, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,370 - Iter: 4, Total Loss: 0.9028, loss_single: 0.9028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,406 - Iter: 5, Total Loss: 0.8689, loss_single: 0.8689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,442 - Iter: 6, Total Loss: 0.8453, loss_single: 0.8453, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,478 - Iter: 7, Total Loss: 0.8206, loss_single: 0.8206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,514 - Iter: 8, Total Loss: 0.7928, loss_single: 0.7928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,550 - Iter: 9, Total Loss: 0.7627, loss_single: 0.7627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,586 - Iter: 10, Total Loss: 0.7298, loss_single: 0.7298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,622 - Iter: 11, Total Loss: 0.6982, loss_single: 0.6982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,657 - Iter: 12, Total Loss: 0.6699, loss_single: 0.6699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,693 - Iter: 13, Total Loss: 0.6444, loss_single: 0.6444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,729 - Iter: 14, Total Loss: 0.6236, loss_single: 0.6236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,765 - Iter: 15, Total Loss: 0.6055, loss_single: 0.6055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,802 - Iter: 16, Total Loss: 0.5860, loss_single: 0.5860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:55,837 - Iter: 17, Total Loss: 0.5685, loss_single: 0.5685, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,873 - Iter: 18, Total Loss: 0.5528, loss_single: 0.5528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,909 - Iter: 19, Total Loss: 0.5392, loss_single: 0.5392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,945 - Iter: 20, Total Loss: 0.5263, loss_single: 0.5263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:55,981 - Iter: 21, Total Loss: 0.5151, loss_single: 0.5151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:56,017 - Iter: 22, Total Loss: 0.5053, loss_single: 0.5053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:56,056 - Iter: 23, Total Loss: 0.4962, loss_single: 0.4962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:26:56,092 - Iter: 24, Total Loss: 0.4874, loss_single: 0.4874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:56,128 - Iter: 25, Total Loss: 0.4797, loss_single: 0.4797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:56,164 - Iter: 26, Total Loss: 0.4728, loss_single: 0.4728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:26:56,200 - Iter: 27, Total Loss: 0.4656, loss_single: 0.4656, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:56,236 - Iter: 28, Total Loss: 0.4596, loss_single: 0.4596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:26:56,271 - Iter: 29, Total Loss: 0.4547, loss_single: 0.4547, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/simulation_data5__sample_000028.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/simulation_data5__sample_000028.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7bcef79d64f4068c314f99e4f8236d367ced8b5c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/simulation_data5__sample_000028.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 13.67462158203125 + probe_aberrations: + C10: -37.882591247558594 + C12: -4.038687229156494 + C21: 890.3486328125 + C23: -227.69155883789062 + C30: 2792412.75 + C32: -9213.66796875 + C34: 11987.2890625 + C41: 4655.68359375 + C43: 307885.125 + C45: -61559.81640625 + C50: 336173280.0 + C52: 15304924.0 + C54: -13701384.0 + C56: 2372729.75 + phi12: 269.34045029623223 + phi21: 106.68058121245659 + phi23: 154.0126925001886 + phi32: 200.21547981998316 + phi34: 152.32261683158228 + phi41: 350.7779432420748 + phi43: 73.96918652243222 + phi45: 335.6550028346961 + phi52: 239.5158009079679 + phi54: 296.5387007033299 + phi56: 31.27390283201972 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4896918833255768 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000028_measurement.h5 + key: measurement + random_seed: 20262058 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000028 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8ef3388e1a9932a77e11ff9018c4f2ee2d1ce62785e9addb6824b24cd6a40aaa +size 1251820 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_scan_pos_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_scan_pos_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..6086046bab7fa803b01df6aba73e45fc578bfabf --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000028/c30_small__simulation_data5__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-37.9_C12_-4.04_phi12_269_C21_890_phi21_107_C23_-228_phi23_154_C30_2.79e+06_C32_-9.21e+03_phi32_.3/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cfd4c76fb1e75eba8998ba60617c3c0eb450f4f318c2efea833778f45d5f7677 +size 48107 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/20260624_062807_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/20260624_062807_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..59ef85b872122ba5a39eff2066e2985d07861a60 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/20260624_062807_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:28:05,585 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:28:05,586 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:28:05,586 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:28:05,586 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:28:05,586 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:28:05,586 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:28:05,586 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:28:05,586 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:28:05,586 - +2026-06-24 06:28:05,684 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:28:05,684 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:28:05,684 - Accelerator.num_process = 1 +2026-06-24 06:28:05,684 - Accelerator.mixed_precision = no +2026-06-24 06:28:05,695 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:28:05,695 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:28:05,695 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:28:05,695 - +2026-06-24 06:28:05,695 - ### System information ### +2026-06-24 06:28:05,695 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:28:05,695 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:28:05,695 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:28:05,695 - Machine: x86_64 +2026-06-24 06:28:05,695 - Processor: x86_64 +2026-06-24 06:28:05,695 - Available CPU cores: 8 +2026-06-24 06:28:05,695 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:28:05,695 - +2026-06-24 06:28:05,695 - ### GPU information ### +2026-06-24 06:28:05,695 - CUDA Available: True +2026-06-24 06:28:05,695 - CUDA Version: 13.0 +2026-06-24 06:28:05,696 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:28:05,696 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:28:05,696 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:28:05,696 - In addition, Triton does not directly support Windows. +2026-06-24 06:28:05,696 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:28:05,711 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:28:05,711 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:28:05,711 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:28:05,712 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:28:05,712 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:28:05,712 - +2026-06-24 06:28:05,712 - ### Python information ### +2026-06-24 06:28:05,713 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:28:05,713 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:28:05,713 - +2026-06-24 06:28:05,713 - ### Packages information ### +2026-06-24 06:28:05,714 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:28:05,715 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:28:05,716 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:28:05,716 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:28:05,717 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:28:05,717 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:28:05,717 - +2026-06-24 06:28:05,717 - ### Loading params file ### +2026-06-24 06:28:05,717 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000033.yaml +2026-06-24 06:28:05,723 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:28:05,725 - Success! Params file validated and defaults applied. +2026-06-24 06:28:05,725 - +2026-06-24 06:28:05,725 - ### Setting GPU Device ### +2026-06-24 06:28:05,725 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:28:05,725 - +2026-06-24 06:28:05,725 - Random seed: 20262063 provided by params file +2026-06-24 06:28:05,725 - ### Initializing Initializer ### +2026-06-24 06:28:05,725 - init_params are displayed below: +2026-06-24 06:28:05,725 - random_seed: 20262063 +2026-06-24 06:28:05,725 - probe_illum_type: electron +2026-06-24 06:28:05,725 - probe_kv: 60.0 +2026-06-24 06:28:05,725 - probe_conv_angle: 9.590072631835938 +2026-06-24 06:28:05,725 - probe_aberrations: {'C10': -371.08, 'C12': 7.541, 'phi12': 302.345, 'C21': -953.848, 'phi21': 116.246, 'C23': -147.792, 'phi23': 215.409, 'C30': 1070425.25, 'C32': -1472.573, 'phi32': 111.7, 'C34': -5063.648, 'phi34': 240.791, 'C41': 60190.543, 'phi41': 215.992, 'C43': 55719.047, 'phi43': 288.889, 'C45': -31333.41, 'phi45': 108.939, 'C50': -481034080.0, 'C52': -13047937.0, 'phi52': 153.959, 'C54': 15262138.0, 'phi54': 310.478, 'C56': -11906696.0, 'phi56': 160.462} +2026-06-24 06:28:05,725 - beam_kev: None +2026-06-24 06:28:05,726 - probe_dRn: None +2026-06-24 06:28:05,726 - probe_Rn: None +2026-06-24 06:28:05,726 - probe_D_H: None +2026-06-24 06:28:05,726 - probe_D_FZP: None +2026-06-24 06:28:05,726 - probe_Ls: None +2026-06-24 06:28:05,726 - meas_Npix: 128 +2026-06-24 06:28:05,726 - pos_N_scans: 256 +2026-06-24 06:28:05,726 - pos_N_scan_slow: 16 +2026-06-24 06:28:05,726 - pos_N_scan_fast: 16 +2026-06-24 06:28:05,726 - pos_scan_step_size: 0.32882818579673767 +2026-06-24 06:28:05,726 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:28:05,726 - probe_pmode_max: 6 +2026-06-24 06:28:05,726 - probe_pmode_init_pows: [0.02] +2026-06-24 06:28:05,726 - obj_omode_max: 1 +2026-06-24 06:28:05,726 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:28:05,726 - obj_Nlayer: 1 +2026-06-24 06:28:05,726 - obj_slice_thickness: 20.0 +2026-06-24 06:28:05,726 - simu_Npix: None +2026-06-24 06:28:05,726 - simu_match_mode: None +2026-06-24 06:28:05,726 - meas_permute: None +2026-06-24 06:28:05,726 - meas_reshape: [256, 128, 128] +2026-06-24 06:28:05,726 - meas_flipT: [0, 0, 0] +2026-06-24 06:28:05,726 - meas_crop: None +2026-06-24 06:28:05,726 - meas_pad: None +2026-06-24 06:28:05,726 - meas_resample: None +2026-06-24 06:28:05,726 - meas_add_source_size: None +2026-06-24 06:28:05,726 - meas_add_detector_blur: None +2026-06-24 06:28:05,726 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:28:05,726 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:28:05,726 - meas_add_poisson_noise: None +2026-06-24 06:28:05,726 - meas_export: None +2026-06-24 06:28:05,726 - probe_permute: None +2026-06-24 06:28:05,726 - probe_z_shift: None +2026-06-24 06:28:05,726 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:28:05,726 - pos_scan_flipT: None +2026-06-24 06:28:05,726 - pos_scan_affine: None +2026-06-24 06:28:05,726 - pos_scan_rand_std: 0.15 +2026-06-24 06:28:05,726 - obj_z_crop: None +2026-06-24 06:28:05,726 - obj_z_pad: None +2026-06-24 06:28:05,726 - obj_z_resample: None +2026-06-24 06:28:05,726 - meas_source: file +2026-06-24 06:28:05,727 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000033_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:28:05,727 - probe_source: simu +2026-06-24 06:28:05,727 - probe_params: None +2026-06-24 06:28:05,727 - pos_source: simu +2026-06-24 06:28:05,727 - pos_params: None +2026-06-24 06:28:05,727 - obj_source: simu +2026-06-24 06:28:05,727 - obj_params: None +2026-06-24 06:28:05,727 - tilt_source: simu +2026-06-24 06:28:05,727 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:28:05,727 - +2026-06-24 06:28:05,727 - ### Initializing cache ### +2026-06-24 06:28:05,727 - use_cached_obj = False +2026-06-24 06:28:05,727 - use_cached_probe = False +2026-06-24 06:28:05,727 - use_cached_pos = False +2026-06-24 06:28:05,727 - +2026-06-24 06:28:05,727 - ### Initializing measurements ### +2026-06-24 06:28:05,727 - Loading measurements from source = 'file' +2026-06-24 06:28:05,727 - Detected measurement file type = '.h5' +2026-06-24 06:28:05,802 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:28:05,802 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:28:05,804 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0136) +2026-06-24 06:28:05,804 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:28:05,804 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:28:05,806 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:28:05,806 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:28:05,806 - Normalizing by max of the 2D mean pattern intensity: 0.012201927 +2026-06-24 06:28:05,807 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:28:05,808 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0050, 1.1175) +2026-06-24 06:28:05,809 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:28:05,810 - Pattern total int. statistics (min, mean, max) = (80.9419, 82.0058, 83.0582), with min/max = 97.5% +2026-06-24 06:28:05,811 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0050, 1.1175) +2026-06-24 06:28:05,811 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:28:05,811 - +2026-06-24 06:28:05,811 - ### Setting up calibration ### +2026-06-24 06:28:05,811 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:28:05,811 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:28:05,812 - Radius of fitted bright field disk (RBF) = 4.95 px with meas_Npix = 128 +2026-06-24 06:28:05,812 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0774 +2026-06-24 06:28:05,812 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:28:05,812 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:28:06,032 - Initial guess: center=(63.62, 63.62), radius=4.95, Gaussian blur std=0.50 +2026-06-24 06:28:06,042 - Final fit: center=(63.62, 63.62), radius=4.95, Gaussian blur std=0.59 +2026-06-24 06:28:06,042 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 5.05 px with Npix = 128 +2026-06-24 06:28:06,042 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:28:06,042 - +2026-06-24 06:28:06,042 - ### Setting init_variables dict ### +2026-06-24 06:28:06,042 - Derived values given input init_params: +2026-06-24 06:28:06,042 - kv = 60.0 kV +2026-06-24 06:28:06,042 - wavelength = 0.0487 Ang +2026-06-24 06:28:06,042 - conv_angle = 9.590072631835938 mrad +2026-06-24 06:28:06,042 - Npix = 128 px +2026-06-24 06:28:06,042 - dk = 0.0391 Ang^-1 +2026-06-24 06:28:06,042 - kMax = 2.5000 Ang^-1 +2026-06-24 06:28:06,042 - da = 1.9008 mrad +2026-06-24 06:28:06,042 - angleMax = 121.6515 mrad +2026-06-24 06:28:06,042 - RBF = 5.0453 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:28:06,042 - n_alpha = 12.6852 (# conv_angle) +2026-06-24 06:28:06,042 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:28:06,043 - Rayleigh-limited resolution = 3.0952 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:28:06,043 - Real space probe extent = 25.6000 Ang +2026-06-24 06:28:06,043 - +2026-06-24 06:28:06,043 - ### Initializing probe ### +2026-06-24 06:28:06,043 - Loading probe from source = 'simu' +2026-06-24 06:28:06,043 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:28:06,043 - Start simulating STEM probe +2026-06-24 06:28:06,043 - kv = 60.0 kV +2026-06-24 06:28:06,043 - wavelength = 0.0487 Ang +2026-06-24 06:28:06,043 - conv_angle = 9.590072631835938 mrad +2026-06-24 06:28:06,043 - Npix = 128 px +2026-06-24 06:28:06,043 - dk = 0.0391 Ang^-1 +2026-06-24 06:28:06,043 - kMax = 2.5000 Ang^-1 +2026-06-24 06:28:06,043 - alpha_max = 121.6515 mrad +2026-06-24 06:28:06,043 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:28:06,043 - Rayleigh-limited resolution = 3.0952 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:28:06,043 - Real space probe extent = 25.6000 Ang +2026-06-24 06:28:06,043 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:28:06,043 - ------------------------------------------------------------------------------------- +2026-06-24 06:28:06,043 - C1,0 C1 -371.0800 - Defocus (C10 = -df) +2026-06-24 06:28:06,043 - C1,2 A1 7.5410 302.35 2-fold astigmatism +2026-06-24 06:28:06,043 - C2,1 3*B2 -953.8480 116.25 Axial coma +2026-06-24 06:28:06,043 - C2,3 A2 -147.7920 215.41 3-fold astigmatism +2026-06-24 06:28:06,043 - C3,0 C3 1070425.2500 - Spherical aberration +2026-06-24 06:28:06,044 - C3,2 4*S3 -1472.5730 111.70 Axial star aberration +2026-06-24 06:28:06,044 - C3,4 A3 -5063.6480 240.79 4-fold astigmatism +2026-06-24 06:28:06,044 - C4,1 4*B4 60190.5430 215.99 Axial coma(4th) +2026-06-24 06:28:06,044 - C4,3 4*D4 55719.0470 288.89 3-lobe aberration +2026-06-24 06:28:06,044 - C4,5 A4 -31333.4100 108.94 5-fold astigmatism +2026-06-24 06:28:06,044 - C5,0 C5 -481034080.0000 - Spherical aberration (5th) +2026-06-24 06:28:06,044 - C5,2 6*S5 -13047937.0000 153.96 Axial star aberration(5th) +2026-06-24 06:28:06,044 - C5,4 6*R5 15262138.0000 310.48 4-lobe aberration +2026-06-24 06:28:06,044 - C5,6 A5 -11906696.0000 160.46 6-fold astigmatism +2026-06-24 06:28:06,047 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:28:06,047 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:28:06,047 - Creating 5 new probe modes from the major mode +2026-06-24 06:28:06,047 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:28:06,150 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:28:06,151 - Orthogonalizing 6 pmodes +2026-06-24 06:28:06,154 - Sorting 6 pmodes by their intensities +2026-06-24 06:28:06,154 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:28:06,155 - sum(|probe_data|**2) = 82.01, while meas_total_ints (min, mean, max) = (80.9419, 82.0058, 83.0582) +2026-06-24 06:28:06,155 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:28:06,155 - +2026-06-24 06:28:06,155 - ### Initializing probe positions ### +2026-06-24 06:28:06,155 - Loading probe positions from source = 'simu' +2026-06-24 06:28:06,155 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:28:06,155 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3288, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:28:06,155 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:28:06,157 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:28:06,157 - crop_pos 1st and last px coords (y,x) = ([15, 15], [39, 39]) +2026-06-24 06:28:06,158 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:28:06,158 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:28:06,158 - +2026-06-24 06:28:06,158 - ### Initializing object ### +2026-06-24 06:28:06,158 - Loading object from source = 'simu' +2026-06-24 06:28:06,158 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:28:06,159 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:28:06,159 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 184, 184) +2026-06-24 06:28:06,159 - object extent (Z, Y, X) (Ang) = [20. 36.8 36.8] +2026-06-24 06:28:06,159 - +2026-06-24 06:28:06,159 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:28:06,160 - omode_occu (omode) = float32, (1,) +2026-06-24 06:28:06,160 - +2026-06-24 06:28:06,160 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:28:06,160 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 06:28:06,160 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:28:06,160 - +2026-06-24 06:28:06,160 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:28:06,160 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:28:06,160 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:28:06,160 - +2026-06-24 06:28:06,161 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:28:06,161 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:28:06,161 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:28:06,161 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:28:06,161 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:28:06,161 - crop positions (yx_min=[14 14], yx_max=[168 168]) are well contained inside object canvas (Ny,Nx) = (184, 184). +2026-06-24 06:28:06,161 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:28:06,161 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:28:06,161 - +2026-06-24 06:28:06,161 - ### Collecting reconstruction provenance ### +2026-06-24 06:28:06,161 - Reconstruction provenance is collected and initialized. +2026-06-24 06:28:06,161 - +2026-06-24 06:28:06,161 - ### Initializing loss function ### +2026-06-24 06:28:06,161 - Active loss types: +2026-06-24 06:28:06,161 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:28:06,161 - +2026-06-24 06:28:06,161 - ### Initializing constraint function ### +2026-06-24 06:28:06,161 - Active constraint types: +2026-06-24 06:28:06,161 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:28:06,161 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:28:06,161 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:28:06,161 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:28:06,162 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:28:06,162 - +2026-06-24 06:28:06,162 - ### Done initializing PtyRADSolver ### +2026-06-24 06:28:06,162 - +2026-06-24 06:28:06,287 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:28:06,287 - +2026-06-24 06:28:06,287 - ### Initializing PtychoModel model ### +2026-06-24 06:28:06,357 - ### PtychoModel optimizable variables ### +2026-06-24 06:28:06,357 - obja : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:06,357 - objp : torch.Size([1, 1, 184, 184]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:06,357 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:28:06,357 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:28:06,357 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:28:06,357 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:06,357 - +2026-06-24 06:28:06,358 - ### Optimizable variables statitsics ### +2026-06-24 06:28:06,358 - Total measurement values : 4,194,304 +2026-06-24 06:28:06,358 - Total optimizing variables: 264,832 +2026-06-24 06:28:06,358 - Overdetermined ratio : 15.84 +2026-06-24 06:28:06,358 - +2026-06-24 06:28:06,358 - ### Model behavior ### +2026-06-24 06:28:06,358 - Tilt propagator : False +2026-06-24 06:28:06,358 - Change slice thickness : False +2026-06-24 06:28:06,358 - Detector blur : False +2026-06-24 06:28:06,358 - Preload data : True +2026-06-24 06:28:06,358 - On-the-fly meas padding : False +2026-06-24 06:28:06,358 - On-the-fly meas resample : False +2026-06-24 06:28:06,358 - On-the-fly simu match mode: None +2026-06-24 06:28:06,358 - +2026-06-24 06:28:06,400 - ### Done initializing PtychoModel model ### +2026-06-24 06:28:06,400 - +2026-06-24 06:28:06,400 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:28:06,400 - +2026-06-24 06:28:06,400 - ### Generating indices, batches, and output_path ### +2026-06-24 06:28:06,402 - d90 = 65.000 px or 13.000 Ang +2026-06-24 06:28:06,402 - Selecting indices with the 'full' mode +2026-06-24 06:28:06,861 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:28:06,933 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:28:06,933 - Original recon_dir_affixes = ['default'] +2026-06-24 06:28:06,933 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:28:06,940 - Path corrected for compatibility: +2026-06-24 06:28:06,940 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.47e+03_phi32_112_C34_-5.06e+03_phi34_241_C41_6.02e+04_phi41_216_C43_5.57e+04_phi43_289_C45_-3.13e+04_phi45_109_C50_-4.81e+08_C52_-1.3e+07_phi52_154_C54_1.53e+07_phi54_310_C56_-1.19e+07_phi56_160 +2026-06-24 06:28:06,940 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160 +2026-06-24 06:28:06,941 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160' is generated! +2026-06-24 06:28:07,087 - +2026-06-24 06:28:07,088 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/20260624_062807_ptyrad_log.txt ### +2026-06-24 06:28:07,088 - +2026-06-24 06:28:07,090 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:28:07,090 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:28:07,090 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:28:08,287 - Iter: 1, Total Loss: 1.7615, loss_single: 1.7615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:28:08,324 - Iter: 2, Total Loss: 1.6270, loss_single: 1.6270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:28:08,359 - Iter: 3, Total Loss: 1.5157, loss_single: 1.5157, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,395 - Iter: 4, Total Loss: 1.4164, loss_single: 1.4164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,431 - Iter: 5, Total Loss: 1.3266, loss_single: 1.3266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,466 - Iter: 6, Total Loss: 1.2650, loss_single: 1.2650, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,501 - Iter: 7, Total Loss: 1.2144, loss_single: 1.2144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,537 - Iter: 8, Total Loss: 1.1510, loss_single: 1.1510, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,573 - Iter: 9, Total Loss: 1.0898, loss_single: 1.0898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,609 - Iter: 10, Total Loss: 1.0151, loss_single: 1.0151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:08,644 - Iter: 11, Total Loss: 0.9540, loss_single: 0.9540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,713 - Iter: 12, Total Loss: 0.9074, loss_single: 0.9074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,749 - Iter: 13, Total Loss: 0.8662, loss_single: 0.8662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,784 - Iter: 14, Total Loss: 0.8290, loss_single: 0.8290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,820 - Iter: 15, Total Loss: 0.7848, loss_single: 0.7848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,856 - Iter: 16, Total Loss: 0.7410, loss_single: 0.7410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,891 - Iter: 17, Total Loss: 0.6984, loss_single: 0.6984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,927 - Iter: 18, Total Loss: 0.6621, loss_single: 0.6621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,962 - Iter: 19, Total Loss: 0.6324, loss_single: 0.6324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:08,998 - Iter: 20, Total Loss: 0.6134, loss_single: 0.6134, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,033 - Iter: 21, Total Loss: 0.6018, loss_single: 0.6018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,069 - Iter: 22, Total Loss: 0.5913, loss_single: 0.5913, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,105 - Iter: 23, Total Loss: 0.5850, loss_single: 0.5850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,141 - Iter: 24, Total Loss: 0.5792, loss_single: 0.5792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,176 - Iter: 25, Total Loss: 0.5734, loss_single: 0.5734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,212 - Iter: 26, Total Loss: 0.5697, loss_single: 0.5697, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,247 - Iter: 27, Total Loss: 0.5668, loss_single: 0.5668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,283 - Iter: 28, Total Loss: 0.5645, loss_single: 0.5645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,319 - Iter: 29, Total Loss: 0.5632, loss_single: 0.5632, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,354 - Iter: 30, Total Loss: 0.5620, loss_single: 0.5620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,390 - Iter: 31, Total Loss: 0.5608, loss_single: 0.5608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,429 - Iter: 32, Total Loss: 0.5600, loss_single: 0.5600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:28:09,465 - Iter: 33, Total Loss: 0.5595, loss_single: 0.5595, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,500 - Iter: 34, Total Loss: 0.5590, loss_single: 0.5590, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,535 - Iter: 35, Total Loss: 0.5587, loss_single: 0.5587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,571 - Iter: 36, Total Loss: 0.5584, loss_single: 0.5584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:09,607 - Iter: 37, Total Loss: 0.5581, loss_single: 0.5581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,642 - Iter: 38, Total Loss: 0.5578, loss_single: 0.5578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,678 - Iter: 39, Total Loss: 0.5576, loss_single: 0.5576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:09,714 - Iter: 40, Total Loss: 0.5575, loss_single: 0.5575, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,753 - Iter: 41, Total Loss: 0.5574, loss_single: 0.5574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:09,788 - Iter: 42, Total Loss: 0.5572, loss_single: 0.5572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,824 - Iter: 43, Total Loss: 0.5572, loss_single: 0.5572, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:09,859 - Iter: 44, Total Loss: 0.5571, loss_single: 0.5571, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,895 - Iter: 45, Total Loss: 0.5570, loss_single: 0.5570, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:09,930 - Iter: 46, Total Loss: 0.5569, loss_single: 0.5569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:09,966 - Iter: 47, Total Loss: 0.5568, loss_single: 0.5568, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,002 - Iter: 48, Total Loss: 0.5566, loss_single: 0.5566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,038 - Iter: 49, Total Loss: 0.5566, loss_single: 0.5566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,073 - Iter: 50, Total Loss: 0.5565, loss_single: 0.5565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,108 - Iter: 51, Total Loss: 0.5564, loss_single: 0.5564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,144 - Iter: 52, Total Loss: 0.5564, loss_single: 0.5564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,179 - Iter: 53, Total Loss: 0.5564, loss_single: 0.5564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,214 - Iter: 54, Total Loss: 0.5563, loss_single: 0.5563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,249 - Iter: 55, Total Loss: 0.5561, loss_single: 0.5561, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,284 - Iter: 56, Total Loss: 0.5562, loss_single: 0.5562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,319 - Iter: 57, Total Loss: 0.5560, loss_single: 0.5560, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:10,355 - Iter: 58, Total Loss: 0.5560, loss_single: 0.5560, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/simulation_data5__sample_000033.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/simulation_data5__sample_000033.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ae7094f674f422c9da5341c457c148562493c232 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000033/c30_small__simulation_data5__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-371_C12_7.54_phi12_302_C21_-954_phi21_116_C23_-148_phi23_215_C30_1.07e+06_C32_-1.19e+07_phi56_160/simulation_data5__sample_000033.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 9.590072631835938 + probe_aberrations: + C10: -371.079833984375 + C12: 7.541051387786865 + C21: -953.8477783203125 + C23: -147.7920379638672 + C30: 1070425.25 + C32: -1472.5726318359375 + C34: -5063.6484375 + C41: 60190.54296875 + C43: 55719.046875 + C45: -31333.41015625 + C50: -481034080.0 + C52: -13047937.0 + C54: 15262138.0 + C56: -11906696.0 + phi12: 302.3446620261642 + phi21: 116.24633627714032 + phi23: 215.4087848361913 + phi32: 111.69953398817619 + phi34: 240.79064205617243 + phi41: 215.99155023655513 + phi43: 288.88853366307876 + phi45: 108.93886714830542 + phi52: 153.9588432887722 + phi54: 310.4781332520854 + phi56: 160.46231719002657 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.32882818579673767 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000033_measurement.h5 + key: measurement + random_seed: 20262063 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36.19e+05_phi56_267/20260624_062821_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:28:20,090 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:28:20,091 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:28:20,091 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:28:20,091 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:28:20,091 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:28:20,091 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:28:20,091 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:28:20,091 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:28:20,091 - +2026-06-24 06:28:20,200 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:28:20,200 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:28:20,201 - Accelerator.num_process = 1 +2026-06-24 06:28:20,201 - Accelerator.mixed_precision = no +2026-06-24 06:28:20,223 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:28:20,223 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:28:20,223 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:28:20,223 - +2026-06-24 06:28:20,223 - ### System information ### +2026-06-24 06:28:20,223 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:28:20,223 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:28:20,223 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:28:20,223 - Machine: x86_64 +2026-06-24 06:28:20,223 - Processor: x86_64 +2026-06-24 06:28:20,223 - Available CPU cores: 8 +2026-06-24 06:28:20,223 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:28:20,223 - +2026-06-24 06:28:20,223 - ### GPU information ### +2026-06-24 06:28:20,223 - CUDA Available: True +2026-06-24 06:28:20,223 - CUDA Version: 13.0 +2026-06-24 06:28:20,224 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:28:20,224 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:28:20,224 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:28:20,224 - In addition, Triton does not directly support Windows. +2026-06-24 06:28:20,224 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:28:20,240 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:28:20,240 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:28:20,240 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:28:20,240 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:28:20,240 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:28:20,240 - +2026-06-24 06:28:20,240 - ### Python information ### +2026-06-24 06:28:20,243 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:28:20,243 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:28:20,243 - +2026-06-24 06:28:20,243 - ### Packages information ### +2026-06-24 06:28:20,243 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:28:20,244 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:28:20,245 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:28:20,245 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:28:20,246 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:28:20,246 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:28:20,246 - +2026-06-24 06:28:20,246 - ### Loading params file ### +2026-06-24 06:28:20,246 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000034.yaml +2026-06-24 06:28:20,253 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:28:20,254 - Success! Params file validated and defaults applied. +2026-06-24 06:28:20,254 - +2026-06-24 06:28:20,254 - ### Setting GPU Device ### +2026-06-24 06:28:20,254 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:28:20,254 - +2026-06-24 06:28:20,254 - Random seed: 20262064 provided by params file +2026-06-24 06:28:20,254 - ### Initializing Initializer ### +2026-06-24 06:28:20,254 - init_params are displayed below: +2026-06-24 06:28:20,254 - random_seed: 20262064 +2026-06-24 06:28:20,254 - probe_illum_type: electron +2026-06-24 06:28:20,254 - probe_kv: 100.0 +2026-06-24 06:28:20,254 - probe_conv_angle: 10.459877967834473 +2026-06-24 06:28:20,254 - probe_aberrations: {'C10': -487.826, 'C12': 39.986, 'phi12': 192.526, 'C21': 119.542, 'phi21': 53.585, 'C23': 28.052, 'phi23': 148.247, 'C30': 4144869.25, 'C32': 1358.387, 'phi32': 67.705, 'C34': 3565.055, 'phi34': 129.092, 'C41': 42488.336, 'phi41': 209.509, 'C43': 106338.703, 'phi43': 142.675, 'C45': 240833.078, 'phi45': 110.291, 'C50': 90805328.0, 'C52': 1465688.25, 'phi52': 257.756, 'C54': -16558171.0, 'phi54': 76.886, 'C56': 619497.75, 'phi56': 266.987} +2026-06-24 06:28:20,255 - beam_kev: None +2026-06-24 06:28:20,255 - probe_dRn: None +2026-06-24 06:28:20,255 - probe_Rn: None +2026-06-24 06:28:20,255 - probe_D_H: None +2026-06-24 06:28:20,255 - probe_D_FZP: None +2026-06-24 06:28:20,255 - probe_Ls: None +2026-06-24 06:28:20,255 - meas_Npix: 128 +2026-06-24 06:28:20,255 - pos_N_scans: 256 +2026-06-24 06:28:20,255 - pos_N_scan_slow: 16 +2026-06-24 06:28:20,255 - pos_N_scan_fast: 16 +2026-06-24 06:28:20,255 - pos_scan_step_size: 0.3985167145729065 +2026-06-24 06:28:20,255 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:28:20,255 - probe_pmode_max: 6 +2026-06-24 06:28:20,255 - probe_pmode_init_pows: [0.02] +2026-06-24 06:28:20,255 - obj_omode_max: 1 +2026-06-24 06:28:20,255 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:28:20,255 - obj_Nlayer: 1 +2026-06-24 06:28:20,255 - obj_slice_thickness: 20.0 +2026-06-24 06:28:20,255 - simu_Npix: None +2026-06-24 06:28:20,255 - simu_match_mode: None +2026-06-24 06:28:20,255 - meas_permute: None +2026-06-24 06:28:20,255 - meas_reshape: [256, 128, 128] +2026-06-24 06:28:20,255 - meas_flipT: [0, 0, 0] +2026-06-24 06:28:20,255 - meas_crop: None +2026-06-24 06:28:20,255 - meas_pad: None +2026-06-24 06:28:20,255 - meas_resample: None +2026-06-24 06:28:20,255 - meas_add_source_size: None +2026-06-24 06:28:20,255 - meas_add_detector_blur: None +2026-06-24 06:28:20,255 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:28:20,255 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:28:20,255 - meas_add_poisson_noise: None +2026-06-24 06:28:20,255 - meas_export: None +2026-06-24 06:28:20,255 - probe_permute: None +2026-06-24 06:28:20,255 - probe_z_shift: None +2026-06-24 06:28:20,255 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:28:20,255 - pos_scan_flipT: None +2026-06-24 06:28:20,255 - pos_scan_affine: None +2026-06-24 06:28:20,255 - pos_scan_rand_std: 0.15 +2026-06-24 06:28:20,255 - obj_z_crop: None +2026-06-24 06:28:20,255 - obj_z_pad: None +2026-06-24 06:28:20,255 - obj_z_resample: None +2026-06-24 06:28:20,256 - meas_source: file +2026-06-24 06:28:20,256 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000034_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:28:20,256 - probe_source: simu +2026-06-24 06:28:20,256 - probe_params: None +2026-06-24 06:28:20,256 - pos_source: simu +2026-06-24 06:28:20,256 - pos_params: None +2026-06-24 06:28:20,256 - obj_source: simu +2026-06-24 06:28:20,256 - obj_params: None +2026-06-24 06:28:20,256 - tilt_source: simu +2026-06-24 06:28:20,256 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:28:20,256 - +2026-06-24 06:28:20,256 - ### Initializing cache ### +2026-06-24 06:28:20,256 - use_cached_obj = False +2026-06-24 06:28:20,256 - use_cached_probe = False +2026-06-24 06:28:20,256 - use_cached_pos = False +2026-06-24 06:28:20,256 - +2026-06-24 06:28:20,256 - ### Initializing measurements ### +2026-06-24 06:28:20,256 - Loading measurements from source = 'file' +2026-06-24 06:28:20,256 - Detected measurement file type = '.h5' +2026-06-24 06:28:20,331 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:28:20,331 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:28:20,332 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0065) +2026-06-24 06:28:20,332 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:28:20,333 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:28:20,334 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:28:20,334 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:28:20,335 - Normalizing by max of the 2D mean pattern intensity: 0.0060654865 +2026-06-24 06:28:20,335 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:28:20,337 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0101, 1.0734) +2026-06-24 06:28:20,337 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:28:20,339 - Pattern total int. statistics (min, mean, max) = (163.8974, 164.8700, 166.0775), with min/max = 98.7% +2026-06-24 06:28:20,340 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0101, 1.0734) +2026-06-24 06:28:20,340 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:28:20,340 - +2026-06-24 06:28:20,340 - ### Setting up calibration ### +2026-06-24 06:28:20,340 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:28:20,340 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:28:20,340 - Radius of fitted bright field disk (RBF) = 7.18 px with meas_Npix = 128 +2026-06-24 06:28:20,340 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1122 +2026-06-24 06:28:20,340 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:28:20,340 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:28:20,560 - Initial guess: center=(63.63, 63.63), radius=7.18, Gaussian blur std=0.50 +2026-06-24 06:28:20,570 - Final fit: center=(63.63, 63.63), radius=7.18, Gaussian blur std=0.59 +2026-06-24 06:28:20,570 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 7.23 px with Npix = 128 +2026-06-24 06:28:20,570 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:28:20,570 - +2026-06-24 06:28:20,570 - ### Setting init_variables dict ### +2026-06-24 06:28:20,570 - Derived values given input init_params: +2026-06-24 06:28:20,570 - kv = 100.0 kV +2026-06-24 06:28:20,570 - wavelength = 0.0370 Ang +2026-06-24 06:28:20,570 - conv_angle = 10.459877967834473 mrad +2026-06-24 06:28:20,570 - Npix = 128 px +2026-06-24 06:28:20,570 - dk = 0.0391 Ang^-1 +2026-06-24 06:28:20,570 - kMax = 2.5000 Ang^-1 +2026-06-24 06:28:20,570 - da = 1.4459 mrad +2026-06-24 06:28:20,571 - angleMax = 92.5359 mrad +2026-06-24 06:28:20,571 - RBF = 7.2343 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:28:20,571 - n_alpha = 8.8467 (# conv_angle) +2026-06-24 06:28:20,571 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:28:20,571 - Rayleigh-limited resolution = 2.1586 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:28:20,571 - Real space probe extent = 25.6000 Ang +2026-06-24 06:28:20,571 - +2026-06-24 06:28:20,571 - ### Initializing probe ### +2026-06-24 06:28:20,571 - Loading probe from source = 'simu' +2026-06-24 06:28:20,571 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:28:20,571 - Start simulating STEM probe +2026-06-24 06:28:20,571 - kv = 100.0 kV +2026-06-24 06:28:20,571 - wavelength = 0.0370 Ang +2026-06-24 06:28:20,571 - conv_angle = 10.459877967834473 mrad +2026-06-24 06:28:20,571 - Npix = 128 px +2026-06-24 06:28:20,571 - dk = 0.0391 Ang^-1 +2026-06-24 06:28:20,571 - kMax = 2.5000 Ang^-1 +2026-06-24 06:28:20,571 - alpha_max = 92.5359 mrad +2026-06-24 06:28:20,571 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:28:20,571 - Rayleigh-limited resolution = 2.1586 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:28:20,571 - Real space probe extent = 25.6000 Ang +2026-06-24 06:28:20,571 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:28:20,572 - ------------------------------------------------------------------------------------ +2026-06-24 06:28:20,572 - C1,0 C1 -487.8260 - Defocus (C10 = -df) +2026-06-24 06:28:20,572 - C1,2 A1 39.9860 192.53 2-fold astigmatism +2026-06-24 06:28:20,572 - C2,1 3*B2 119.5420 53.59 Axial coma +2026-06-24 06:28:20,572 - C2,3 A2 28.0520 148.25 3-fold astigmatism +2026-06-24 06:28:20,572 - C3,0 C3 4144869.2500 - Spherical aberration +2026-06-24 06:28:20,572 - C3,2 4*S3 1358.3870 67.70 Axial star aberration +2026-06-24 06:28:20,572 - C3,4 A3 3565.0550 129.09 4-fold astigmatism +2026-06-24 06:28:20,572 - C4,1 4*B4 42488.3360 209.51 Axial coma(4th) +2026-06-24 06:28:20,572 - C4,3 4*D4 106338.7030 142.68 3-lobe aberration +2026-06-24 06:28:20,572 - C4,5 A4 240833.0780 110.29 5-fold astigmatism +2026-06-24 06:28:20,572 - C5,0 C5 90805328.0000 - Spherical aberration (5th) +2026-06-24 06:28:20,572 - C5,2 6*S5 1465688.2500 257.76 Axial star aberration(5th) +2026-06-24 06:28:20,572 - C5,4 6*R5 -16558171.0000 76.89 4-lobe aberration +2026-06-24 06:28:20,572 - C5,6 A5 619497.7500 266.99 6-fold astigmatism +2026-06-24 06:28:20,575 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:28:20,575 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:28:20,575 - Creating 5 new probe modes from the major mode +2026-06-24 06:28:20,575 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:28:20,678 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:28:20,679 - Orthogonalizing 6 pmodes +2026-06-24 06:28:20,681 - Sorting 6 pmodes by their intensities +2026-06-24 06:28:20,682 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:28:20,682 - sum(|probe_data|**2) = 164.87, while meas_total_ints (min, mean, max) = (163.8974, 164.8700, 166.0775) +2026-06-24 06:28:20,682 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:28:20,682 - +2026-06-24 06:28:20,682 - ### Initializing probe positions ### +2026-06-24 06:28:20,682 - Loading probe positions from source = 'simu' +2026-06-24 06:28:20,683 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:28:20,683 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3985, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:28:20,683 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:28:20,685 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:28:20,685 - crop_pos 1st and last px coords (y,x) = ([15, 15], [45, 45]) +2026-06-24 06:28:20,685 - crop_pos extent (Ang) = [6. 6.] +2026-06-24 06:28:20,685 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:28:20,685 - +2026-06-24 06:28:20,685 - ### Initializing object ### +2026-06-24 06:28:20,685 - Loading object from source = 'simu' +2026-06-24 06:28:20,685 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:28:20,687 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:28:20,687 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-24 06:28:20,687 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-24 06:28:20,687 - +2026-06-24 06:28:20,687 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:28:20,687 - omode_occu (omode) = float32, (1,) +2026-06-24 06:28:20,687 - +2026-06-24 06:28:20,687 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:28:20,687 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:28:20,688 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:28:20,688 - +2026-06-24 06:28:20,688 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:28:20,688 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:28:20,688 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:28:20,688 - +2026-06-24 06:28:20,688 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:28:20,688 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:28:20,688 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:28:20,688 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:28:20,688 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:28:20,688 - crop positions (yx_min=[15 15], yx_max=[173 173]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-24 06:28:20,688 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:28:20,688 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:28:20,688 - +2026-06-24 06:28:20,688 - ### Collecting reconstruction provenance ### +2026-06-24 06:28:20,688 - Reconstruction provenance is collected and initialized. +2026-06-24 06:28:20,688 - +2026-06-24 06:28:20,689 - ### Initializing loss function ### +2026-06-24 06:28:20,689 - Active loss types: +2026-06-24 06:28:20,689 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:28:20,689 - +2026-06-24 06:28:20,689 - ### Initializing constraint function ### +2026-06-24 06:28:20,689 - Active constraint types: +2026-06-24 06:28:20,689 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:28:20,689 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:28:20,689 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:28:20,689 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:28:20,689 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:28:20,689 - +2026-06-24 06:28:20,689 - ### Done initializing PtyRADSolver ### +2026-06-24 06:28:20,689 - +2026-06-24 06:28:20,816 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:28:20,816 - +2026-06-24 06:28:20,816 - ### Initializing PtychoModel model ### +2026-06-24 06:28:20,887 - ### PtychoModel optimizable variables ### +2026-06-24 06:28:20,887 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:20,887 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:20,887 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:28:20,887 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:28:20,887 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:28:20,887 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:28:20,887 - +2026-06-24 06:28:20,887 - ### Optimizable variables statitsics ### +2026-06-24 06:28:20,887 - Total measurement values : 4,194,304 +2026-06-24 06:28:20,887 - Total optimizing variables: 269,320 +2026-06-24 06:28:20,887 - Overdetermined ratio : 15.57 +2026-06-24 06:28:20,887 - +2026-06-24 06:28:20,887 - ### Model behavior ### +2026-06-24 06:28:20,887 - Tilt propagator : False +2026-06-24 06:28:20,888 - Change slice thickness : False +2026-06-24 06:28:20,888 - Detector blur : False +2026-06-24 06:28:20,888 - Preload data : True +2026-06-24 06:28:20,888 - On-the-fly meas padding : False +2026-06-24 06:28:20,888 - On-the-fly meas resample : False +2026-06-24 06:28:20,888 - On-the-fly simu match mode: None +2026-06-24 06:28:20,888 - +2026-06-24 06:28:20,929 - ### Done initializing PtychoModel model ### +2026-06-24 06:28:20,929 - +2026-06-24 06:28:20,929 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:28:20,929 - +2026-06-24 06:28:20,929 - ### Generating indices, batches, and output_path ### +2026-06-24 06:28:20,931 - d90 = 45.000 px or 9.000 Ang +2026-06-24 06:28:20,931 - Selecting indices with the 'full' mode +2026-06-24 06:28:21,396 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:28:21,467 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:28:21,467 - Original recon_dir_affixes = ['default'] +2026-06-24 06:28:21,467 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:28:21,474 - Path corrected for compatibility: +2026-06-24 06:28:21,474 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36e+03_phi32_67.7_C34_3.57e+03_phi34_129_C41_4.25e+04_phi41_210_C43_1.06e+05_phi43_143_C45_2.41e+05_phi45_110_C50_9.08e+07_C52_1.47e+06_phi52_258_C54_-1.66e+07_phi54_76.9_C56_6.19e+05_phi56_267 +2026-06-24 06:28:21,474 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36.19e+05_phi56_267 +2026-06-24 06:28:21,476 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36.19e+05_phi56_267' is generated! +2026-06-24 06:28:21,622 - +2026-06-24 06:28:21,624 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36.19e+05_phi56_267/20260624_062821_ptyrad_log.txt ### +2026-06-24 06:28:21,624 - +2026-06-24 06:28:21,625 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:28:21,625 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:28:21,625 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:28:22,828 - Iter: 1, Total Loss: 1.2876, loss_single: 1.2876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.441 sec +2026-06-24 06:28:22,865 - Iter: 2, Total Loss: 1.1913, loss_single: 1.1913, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:28:22,901 - Iter: 3, Total Loss: 1.1036, loss_single: 1.1036, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:22,937 - Iter: 4, Total Loss: 1.0207, loss_single: 1.0207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:22,972 - Iter: 5, Total Loss: 0.9484, loss_single: 0.9484, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,008 - Iter: 6, Total Loss: 0.8959, loss_single: 0.8959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,044 - Iter: 7, Total Loss: 0.8524, loss_single: 0.8524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,080 - Iter: 8, Total Loss: 0.8054, loss_single: 0.8054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,115 - Iter: 9, Total Loss: 0.7533, loss_single: 0.7533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,151 - Iter: 10, Total Loss: 0.6901, loss_single: 0.6901, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,187 - Iter: 11, Total Loss: 0.6419, loss_single: 0.6419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,223 - Iter: 12, Total Loss: 0.5993, loss_single: 0.5993, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,258 - Iter: 13, Total Loss: 0.5484, loss_single: 0.5484, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,293 - Iter: 14, Total Loss: 0.5043, loss_single: 0.5043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,329 - Iter: 15, Total Loss: 0.4621, loss_single: 0.4621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,365 - Iter: 16, Total Loss: 0.4221, loss_single: 0.4221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,400 - Iter: 17, Total Loss: 0.3931, loss_single: 0.3931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,436 - Iter: 18, Total Loss: 0.3694, loss_single: 0.3694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,472 - Iter: 19, Total Loss: 0.3451, loss_single: 0.3451, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,507 - Iter: 20, Total Loss: 0.3275, loss_single: 0.3275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,543 - Iter: 21, Total Loss: 0.3193, loss_single: 0.3193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,579 - Iter: 22, Total Loss: 0.3131, loss_single: 0.3131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,614 - Iter: 23, Total Loss: 0.3078, loss_single: 0.3078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,650 - Iter: 24, Total Loss: 0.3037, loss_single: 0.3037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,686 - Iter: 25, Total Loss: 0.2999, loss_single: 0.2999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,722 - Iter: 26, Total Loss: 0.2976, loss_single: 0.2976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,757 - Iter: 27, Total Loss: 0.2964, loss_single: 0.2964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,793 - Iter: 28, Total Loss: 0.2954, loss_single: 0.2954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,828 - Iter: 29, Total Loss: 0.2944, loss_single: 0.2944, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,866 - Iter: 30, Total Loss: 0.2932, loss_single: 0.2932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:28:23,902 - Iter: 31, Total Loss: 0.2923, loss_single: 0.2923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:23,938 - Iter: 32, Total Loss: 0.2916, loss_single: 0.2916, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:23,974 - Iter: 33, Total Loss: 0.2911, loss_single: 0.2911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,010 - Iter: 34, Total Loss: 0.2908, loss_single: 0.2908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,045 - Iter: 35, Total Loss: 0.2905, loss_single: 0.2905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,297 - Iter: 42, Total Loss: 0.2895, loss_single: 0.2895, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,333 - Iter: 43, Total Loss: 0.2894, loss_single: 0.2894, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:24,369 - Iter: 44, Total Loss: 0.2893, loss_single: 0.2893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,404 - Iter: 45, Total Loss: 0.2892, loss_single: 0.2892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,440 - Iter: 46, Total Loss: 0.2891, loss_single: 0.2891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,476 - Iter: 47, Total Loss: 0.2890, loss_single: 0.2890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:24,511 - Iter: 48, Total Loss: 0.2890, loss_single: 0.2890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,547 - Iter: 49, Total Loss: 0.2889, loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,583 - Iter: 50, Total Loss: 0.2888, loss_single: 0.2888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,618 - Iter: 51, Total Loss: 0.2888, loss_single: 0.2888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:24,654 - Iter: 52, Total Loss: 0.2887, loss_single: 0.2887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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in 0.035 sec +2026-06-24 06:28:25,295 - Iter: 70, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,330 - Iter: 71, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,366 - Iter: 72, Total Loss: 0.2877, loss_single: 0.2877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,401 - Iter: 73, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,437 - Iter: 74, Total Loss: 0.2877, loss_single: 0.2877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,473 - Iter: 75, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,722 - Iter: 82, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,759 - Iter: 83, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:25,794 - Iter: 84, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,829 - Iter: 85, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,865 - Iter: 86, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:25,901 - Iter: 87, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:25,937 - Iter: 88, Total Loss: 0.2874, loss_single: 0.2874, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:25,973 - Iter: 89, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:26,009 - Iter: 90, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:28:26,046 - Iter: 91, Total Loss: 0.2873, loss_single: 0.2873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:28:26,082 - Iter: 92, Total Loss: 0.2871, loss_single: 0.2871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,118 - Iter: 93, Total Loss: 0.2872, loss_single: 0.2872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,153 - Iter: 94, Total Loss: 0.2872, loss_single: 0.2872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,189 - Iter: 95, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,224 - Iter: 96, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,259 - Iter: 97, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,294 - Iter: 98, Total Loss: 0.2869, loss_single: 0.2869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,330 - Iter: 99, Total Loss: 0.2870, loss_single: 0.2870, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,366 - Iter: 100, Total Loss: 0.2869, loss_single: 0.2869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:28:26,479 - Saving summary figures for iter 100 +2026-06-24 06:28:29,998 - ### Finished 100 iterations, averaged iter_t = 0.039344 with std = 0.040 ### +2026-06-24 06:28:29,999 - +2026-06-24 06:28:29,999 - ### The PtyRADSolver is finished in 9.183 sec ### +2026-06-24 06:28:29,999 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034/c30_small__simulation_data5__sample_000034_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-488_C12_40_phi12_193_C21_120_phi21_53.6_C23_28.1_phi23_148_C30_4.14e+06_C32_1.36.19e+05_phi56_267/simulation_data5__sample_000034.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 10.459877967834473 + probe_aberrations: + C10: -487.8259582519531 + C12: 39.98636245727539 + C21: 119.54243469238281 + C23: 28.05155372619629 + C30: 4144869.25 + C32: 1358.3870849609375 + C34: 3565.055419921875 + C41: 42488.3359375 + C43: 106338.703125 + C45: 240833.078125 + C50: 90805328.0 + C52: 1465688.25 + C54: -16558171.0 + C56: 619497.75 + phi12: 192.52560205989758 + phi21: 53.584801133231 + phi23: 148.24668778399882 + phi32: 67.70530199688358 + phi34: 129.0917637661566 + phi41: 209.50867618583752 + phi43: 142.6752205157494 + phi45: 110.29057524542928 + phi52: 257.7560396525404 + phi54: 76.88582073200024 + phi56: 266.98676710824583 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3985167145729065 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000034_measurement.h5 + key: measurement + random_seed: 20262064 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000034 + 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sha256:fbdffcf6623e7d34d4a0ecc431a001f10c47aca957f34325f57c92933b25cb7c +size 49387 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/20260624_062949_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/20260624_062949_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..aef1e4c013195d09021bd52db29ad2a20aac349c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/20260624_062949_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:29:47,988 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:29:47,988 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:29:47,988 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:29:47,988 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:29:47,988 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:29:47,988 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:29:47,988 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:29:47,988 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:29:47,988 - +2026-06-24 06:29:48,100 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:29:48,100 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:29:48,100 - Accelerator.num_process = 1 +2026-06-24 06:29:48,100 - Accelerator.mixed_precision = no +2026-06-24 06:29:48,110 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:29:48,110 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:29:48,110 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:29:48,110 - +2026-06-24 06:29:48,110 - ### System information ### +2026-06-24 06:29:48,110 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:29:48,110 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:29:48,110 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:29:48,110 - Machine: x86_64 +2026-06-24 06:29:48,110 - Processor: x86_64 +2026-06-24 06:29:48,111 - Available CPU cores: 8 +2026-06-24 06:29:48,111 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:29:48,111 - +2026-06-24 06:29:48,111 - ### GPU information ### +2026-06-24 06:29:48,111 - CUDA Available: True +2026-06-24 06:29:48,111 - CUDA Version: 13.0 +2026-06-24 06:29:48,111 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:29:48,111 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:29:48,111 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:29:48,111 - In addition, Triton does not directly support Windows. +2026-06-24 06:29:48,111 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:29:48,138 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:29:48,139 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:29:48,139 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:29:48,139 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:29:48,139 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:29:48,139 - +2026-06-24 06:29:48,139 - ### Python information ### +2026-06-24 06:29:48,140 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:29:48,140 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:29:48,140 - +2026-06-24 06:29:48,141 - ### Packages information ### +2026-06-24 06:29:48,141 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:29:48,142 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:29:48,142 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:29:48,143 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:29:48,144 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:29:48,144 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:29:48,144 - +2026-06-24 06:29:48,144 - ### Loading params file ### +2026-06-24 06:29:48,144 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000040.yaml +2026-06-24 06:29:48,150 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:29:48,151 - Success! Params file validated and defaults applied. +2026-06-24 06:29:48,151 - +2026-06-24 06:29:48,151 - ### Setting GPU Device ### +2026-06-24 06:29:48,152 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:29:48,152 - +2026-06-24 06:29:48,152 - Random seed: 20262070 provided by params file +2026-06-24 06:29:48,152 - ### Initializing Initializer ### +2026-06-24 06:29:48,152 - init_params are displayed below: +2026-06-24 06:29:48,152 - random_seed: 20262070 +2026-06-24 06:29:48,152 - probe_illum_type: electron +2026-06-24 06:29:48,152 - probe_kv: 80.0 +2026-06-24 06:29:48,152 - probe_conv_angle: 19.200496673583984 +2026-06-24 06:29:48,152 - probe_aberrations: {'C10': -291.398, 'C12': -0.844, 'phi12': 320.569, 'C21': -410.287, 'phi21': 61.815, 'C23': 822.152, 'phi23': 345.142, 'C30': 655780.938, 'C32': 9067.975, 'phi32': 232.69, 'C34': 4065.619, 'phi34': 184.596, 'C41': 150502.438, 'phi41': 292.613, 'C43': -306506.75, 'phi43': 308.99, 'C45': -74310.0, 'phi45': 204.89, 'C50': -188006400.0, 'C52': 7804305.5, 'phi52': 279.461, 'C54': 12622110.0, 'phi54': 257.597, 'C56': -18799760.0, 'phi56': 138.954} +2026-06-24 06:29:48,152 - beam_kev: None +2026-06-24 06:29:48,152 - probe_dRn: None +2026-06-24 06:29:48,152 - probe_Rn: None +2026-06-24 06:29:48,152 - probe_D_H: None +2026-06-24 06:29:48,152 - probe_D_FZP: None +2026-06-24 06:29:48,152 - probe_Ls: None +2026-06-24 06:29:48,152 - meas_Npix: 128 +2026-06-24 06:29:48,153 - pos_N_scans: 256 +2026-06-24 06:29:48,153 - pos_N_scan_slow: 16 +2026-06-24 06:29:48,153 - pos_N_scan_fast: 16 +2026-06-24 06:29:48,153 - pos_scan_step_size: 0.31721946597099304 +2026-06-24 06:29:48,153 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:29:48,153 - probe_pmode_max: 6 +2026-06-24 06:29:48,153 - probe_pmode_init_pows: [0.02] +2026-06-24 06:29:48,153 - obj_omode_max: 1 +2026-06-24 06:29:48,153 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:29:48,153 - obj_Nlayer: 1 +2026-06-24 06:29:48,153 - obj_slice_thickness: 20.0 +2026-06-24 06:29:48,153 - simu_Npix: None +2026-06-24 06:29:48,153 - simu_match_mode: None +2026-06-24 06:29:48,153 - meas_permute: None +2026-06-24 06:29:48,153 - meas_reshape: [256, 128, 128] +2026-06-24 06:29:48,153 - meas_flipT: [0, 0, 0] +2026-06-24 06:29:48,153 - meas_crop: None +2026-06-24 06:29:48,153 - meas_pad: None +2026-06-24 06:29:48,153 - meas_resample: None +2026-06-24 06:29:48,153 - meas_add_source_size: None +2026-06-24 06:29:48,153 - meas_add_detector_blur: None +2026-06-24 06:29:48,153 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:29:48,153 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:29:48,153 - meas_add_poisson_noise: None +2026-06-24 06:29:48,153 - meas_export: None +2026-06-24 06:29:48,153 - probe_permute: None +2026-06-24 06:29:48,153 - probe_z_shift: None +2026-06-24 06:29:48,153 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:29:48,153 - pos_scan_flipT: None +2026-06-24 06:29:48,153 - pos_scan_affine: None +2026-06-24 06:29:48,153 - pos_scan_rand_std: 0.15 +2026-06-24 06:29:48,153 - obj_z_crop: None +2026-06-24 06:29:48,153 - obj_z_pad: None +2026-06-24 06:29:48,153 - obj_z_resample: None +2026-06-24 06:29:48,153 - meas_source: file +2026-06-24 06:29:48,153 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000040_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:29:48,153 - probe_source: simu +2026-06-24 06:29:48,153 - probe_params: None +2026-06-24 06:29:48,153 - pos_source: simu +2026-06-24 06:29:48,154 - pos_params: None +2026-06-24 06:29:48,154 - obj_source: simu +2026-06-24 06:29:48,154 - obj_params: None +2026-06-24 06:29:48,154 - tilt_source: simu +2026-06-24 06:29:48,154 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:29:48,154 - +2026-06-24 06:29:48,154 - ### Initializing cache ### +2026-06-24 06:29:48,154 - use_cached_obj = False +2026-06-24 06:29:48,154 - use_cached_probe = False +2026-06-24 06:29:48,154 - use_cached_pos = False +2026-06-24 06:29:48,154 - +2026-06-24 06:29:48,154 - ### Initializing measurements ### +2026-06-24 06:29:48,154 - Loading measurements from source = 'file' +2026-06-24 06:29:48,154 - Detected measurement file type = '.h5' +2026-06-24 06:29:48,232 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:29:48,232 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:29:48,234 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0038) +2026-06-24 06:29:48,234 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:29:48,234 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:29:48,235 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:29:48,235 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:29:48,236 - Normalizing by max of the 2D mean pattern intensity: 0.0020310362 +2026-06-24 06:29:48,237 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:29:48,238 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0299, 1.8746) +2026-06-24 06:29:48,238 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:29:48,240 - Pattern total int. statistics (min, mean, max) = (486.2409, 489.8983, 493.9089), with min/max = 98.4% +2026-06-24 06:29:48,241 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0299, 1.8746) +2026-06-24 06:29:48,241 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:29:48,241 - +2026-06-24 06:29:48,241 - ### Setting up calibration ### +2026-06-24 06:29:48,241 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:29:48,241 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:29:48,241 - Radius of fitted bright field disk (RBF) = 11.70 px with meas_Npix = 128 +2026-06-24 06:29:48,241 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1828 +2026-06-24 06:29:48,241 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:29:48,241 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:29:48,470 - Initial guess: center=(63.63, 63.63), radius=11.70, Gaussian blur std=0.50 +2026-06-24 06:29:48,484 - Final fit: center=(63.63, 63.63), radius=11.70, Gaussian blur std=0.84 +2026-06-24 06:29:48,484 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.77 px with Npix = 128 +2026-06-24 06:29:48,484 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:29:48,484 - +2026-06-24 06:29:48,484 - ### Setting init_variables dict ### +2026-06-24 06:29:48,485 - Derived values given input init_params: +2026-06-24 06:29:48,485 - kv = 80.0 kV +2026-06-24 06:29:48,485 - wavelength = 0.0418 Ang +2026-06-24 06:29:48,485 - conv_angle = 19.200496673583984 mrad +2026-06-24 06:29:48,485 - Npix = 128 px +2026-06-24 06:29:48,485 - dk = 0.0391 Ang^-1 +2026-06-24 06:29:48,485 - kMax = 2.5000 Ang^-1 +2026-06-24 06:29:48,485 - da = 1.6311 mrad +2026-06-24 06:29:48,485 - angleMax = 104.3929 mrad +2026-06-24 06:29:48,485 - RBF = 11.7712 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:29:48,485 - n_alpha = 5.4370 (# conv_angle) +2026-06-24 06:29:48,485 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:29:48,485 - Rayleigh-limited resolution = 1.3266 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:29:48,485 - Real space probe extent = 25.6000 Ang +2026-06-24 06:29:48,485 - +2026-06-24 06:29:48,485 - ### Initializing probe ### +2026-06-24 06:29:48,485 - Loading probe from source = 'simu' +2026-06-24 06:29:48,485 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:29:48,485 - Start simulating STEM probe +2026-06-24 06:29:48,485 - kv = 80.0 kV +2026-06-24 06:29:48,485 - wavelength = 0.0418 Ang +2026-06-24 06:29:48,485 - conv_angle = 19.200496673583984 mrad +2026-06-24 06:29:48,485 - Npix = 128 px +2026-06-24 06:29:48,485 - dk = 0.0391 Ang^-1 +2026-06-24 06:29:48,486 - kMax = 2.5000 Ang^-1 +2026-06-24 06:29:48,486 - alpha_max = 104.3929 mrad +2026-06-24 06:29:48,486 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:29:48,486 - Rayleigh-limited resolution = 1.3266 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:29:48,486 - Real space probe extent = 25.6000 Ang +2026-06-24 06:29:48,486 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:29:48,486 - ------------------------------------------------------------------------------------- +2026-06-24 06:29:48,486 - C1,0 C1 -291.3980 - Defocus (C10 = -df) +2026-06-24 06:29:48,486 - C1,2 A1 -0.8440 320.57 2-fold astigmatism +2026-06-24 06:29:48,486 - C2,1 3*B2 -410.2870 61.81 Axial coma +2026-06-24 06:29:48,486 - C2,3 A2 822.1520 345.14 3-fold astigmatism +2026-06-24 06:29:48,486 - C3,0 C3 655780.9380 - Spherical aberration +2026-06-24 06:29:48,486 - C3,2 4*S3 9067.9750 232.69 Axial star aberration +2026-06-24 06:29:48,486 - C3,4 A3 4065.6190 184.60 4-fold astigmatism +2026-06-24 06:29:48,486 - C4,1 4*B4 150502.4380 292.61 Axial coma(4th) +2026-06-24 06:29:48,486 - C4,3 4*D4 -306506.7500 308.99 3-lobe aberration +2026-06-24 06:29:48,486 - C4,5 A4 -74310.0000 204.89 5-fold astigmatism +2026-06-24 06:29:48,486 - C5,0 C5 -188006400.0000 - Spherical aberration (5th) +2026-06-24 06:29:48,486 - C5,2 6*S5 7804305.5000 279.46 Axial star aberration(5th) +2026-06-24 06:29:48,486 - C5,4 6*R5 12622110.0000 257.60 4-lobe aberration +2026-06-24 06:29:48,486 - C5,6 A5 -18799760.0000 138.95 6-fold astigmatism +2026-06-24 06:29:48,489 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:29:48,489 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:29:48,489 - Creating 5 new probe modes from the major mode +2026-06-24 06:29:48,490 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:29:48,590 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:29:48,591 - Orthogonalizing 6 pmodes +2026-06-24 06:29:48,594 - Sorting 6 pmodes by their intensities +2026-06-24 06:29:48,594 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:29:48,595 - sum(|probe_data|**2) = 489.90, while meas_total_ints (min, mean, max) = (486.2409, 489.8983, 493.9089) +2026-06-24 06:29:48,595 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:29:48,595 - +2026-06-24 06:29:48,595 - ### Initializing probe positions ### +2026-06-24 06:29:48,595 - Loading probe positions from source = 'simu' +2026-06-24 06:29:48,595 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:29:48,595 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3172, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:29:48,595 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:29:48,597 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:29:48,597 - crop_pos 1st and last px coords (y,x) = ([15, 15], [39, 39]) +2026-06-24 06:29:48,597 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 06:29:48,598 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:29:48,598 - +2026-06-24 06:29:48,598 - ### Initializing object ### +2026-06-24 06:29:48,598 - Loading object from source = 'simu' +2026-06-24 06:29:48,598 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:29:48,599 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:29:48,599 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 183, 183) +2026-06-24 06:29:48,599 - object extent (Z, Y, X) (Ang) = [20. 36.6 36.6] +2026-06-24 06:29:48,599 - +2026-06-24 06:29:48,599 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:29:48,599 - omode_occu (omode) = float32, (1,) +2026-06-24 06:29:48,599 - +2026-06-24 06:29:48,599 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:29:48,599 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:29:48,600 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:29:48,600 - +2026-06-24 06:29:48,600 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:29:48,600 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:29:48,600 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:29:48,600 - +2026-06-24 06:29:48,600 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:29:48,600 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:29:48,600 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:29:48,600 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:29:48,600 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:29:48,601 - crop positions (yx_min=[15 15], yx_max=[167 167]) are well contained inside object canvas (Ny,Nx) = (183, 183). +2026-06-24 06:29:48,601 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:29:48,601 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:29:48,601 - +2026-06-24 06:29:48,601 - ### Collecting reconstruction provenance ### +2026-06-24 06:29:48,601 - Reconstruction provenance is collected and initialized. +2026-06-24 06:29:48,601 - +2026-06-24 06:29:48,601 - ### Initializing loss function ### +2026-06-24 06:29:48,601 - Active loss types: +2026-06-24 06:29:48,601 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:29:48,601 - +2026-06-24 06:29:48,601 - ### Initializing constraint function ### +2026-06-24 06:29:48,601 - Active constraint types: +2026-06-24 06:29:48,601 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:29:48,601 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:29:48,601 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:29:48,601 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:29:48,601 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:29:48,601 - +2026-06-24 06:29:48,601 - ### Done initializing PtyRADSolver ### +2026-06-24 06:29:48,601 - +2026-06-24 06:29:48,731 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:29:48,731 - +2026-06-24 06:29:48,731 - ### Initializing PtychoModel model ### +2026-06-24 06:29:48,803 - ### PtychoModel optimizable variables ### +2026-06-24 06:29:48,803 - obja : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:29:48,803 - objp : torch.Size([1, 1, 183, 183]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:29:48,803 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:29:48,803 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:29:48,803 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:29:48,803 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:29:48,803 - +2026-06-24 06:29:48,803 - ### Optimizable variables statitsics ### +2026-06-24 06:29:48,803 - Total measurement values : 4,194,304 +2026-06-24 06:29:48,803 - Total optimizing variables: 264,098 +2026-06-24 06:29:48,803 - Overdetermined ratio : 15.88 +2026-06-24 06:29:48,803 - +2026-06-24 06:29:48,803 - ### Model behavior ### +2026-06-24 06:29:48,803 - Tilt propagator : False +2026-06-24 06:29:48,804 - Change slice thickness : False +2026-06-24 06:29:48,804 - Detector blur : False +2026-06-24 06:29:48,804 - Preload data : True +2026-06-24 06:29:48,804 - On-the-fly meas padding : False +2026-06-24 06:29:48,804 - On-the-fly meas resample : False +2026-06-24 06:29:48,804 - On-the-fly simu match mode: None +2026-06-24 06:29:48,804 - +2026-06-24 06:29:48,845 - ### Done initializing PtychoModel model ### +2026-06-24 06:29:48,845 - +2026-06-24 06:29:48,845 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:29:48,845 - +2026-06-24 06:29:48,845 - ### Generating indices, batches, and output_path ### +2026-06-24 06:29:48,846 - d90 = 37.000 px or 7.400 Ang +2026-06-24 06:29:48,846 - Selecting indices with the 'full' mode +2026-06-24 06:29:49,305 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:29:49,391 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:29:49,392 - Original recon_dir_affixes = ['default'] +2026-06-24 06:29:49,392 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:29:49,398 - Path corrected for compatibility: +2026-06-24 06:29:49,398 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_9.07e+03_phi32_233_C34_4.07e+03_phi34_185_C41_1.51e+05_phi41_293_C43_-3.07e+05_phi43_309_C45_-7.43e+04_phi45_205_C50_-1.88e+08_C52_7.8e+06_phi52_279_C54_1.26e+07_phi54_258_C56_-1.88e+07_phi56_139 +2026-06-24 06:29:49,398 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139 +2026-06-24 06:29:49,399 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139' is generated! +2026-06-24 06:29:49,568 - +2026-06-24 06:29:49,569 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/20260624_062949_ptyrad_log.txt ### +2026-06-24 06:29:49,569 - +2026-06-24 06:29:49,570 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:29:49,570 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:29:49,570 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:29:50,749 - Iter: 1, Total Loss: 1.1195, loss_single: 1.1195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:29:50,788 - Iter: 2, Total Loss: 1.0936, loss_single: 1.0936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:29:50,824 - Iter: 3, Total Loss: 1.0728, loss_single: 1.0728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:50,858 - Iter: 4, Total Loss: 1.0523, loss_single: 1.0523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:29:50,893 - Iter: 5, Total Loss: 1.0304, loss_single: 1.0304, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:50,928 - Iter: 6, Total Loss: 1.0102, loss_single: 1.0102, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:50,964 - Iter: 7, Total Loss: 0.9917, loss_single: 0.9917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:50,999 - Iter: 8, Total Loss: 0.9708, loss_single: 0.9708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,034 - Iter: 9, Total Loss: 0.9476, loss_single: 0.9476, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,069 - Iter: 10, Total Loss: 0.9228, loss_single: 0.9228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:29:51,104 - Iter: 11, Total Loss: 0.8984, loss_single: 0.8984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,139 - Iter: 12, Total Loss: 0.8788, loss_single: 0.8788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,174 - Iter: 13, Total Loss: 0.8591, loss_single: 0.8591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,209 - Iter: 14, Total Loss: 0.8373, loss_single: 0.8373, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,244 - Iter: 15, Total Loss: 0.8178, loss_single: 0.8178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,279 - Iter: 16, Total Loss: 0.7987, loss_single: 0.7987, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,314 - Iter: 17, Total Loss: 0.7781, loss_single: 0.7781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,350 - Iter: 18, Total Loss: 0.7578, loss_single: 0.7578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,385 - Iter: 19, Total Loss: 0.7410, loss_single: 0.7410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,420 - Iter: 20, Total Loss: 0.7238, loss_single: 0.7238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,458 - Iter: 21, Total Loss: 0.7064, loss_single: 0.7064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:29:51,500 - Iter: 22, Total Loss: 0.6909, loss_single: 0.6909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.041 sec +2026-06-24 06:29:51,535 - Iter: 23, Total Loss: 0.6749, loss_single: 0.6749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,570 - Iter: 24, Total Loss: 0.6579, loss_single: 0.6579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,606 - Iter: 25, Total Loss: 0.6403, loss_single: 0.6403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,641 - Iter: 26, Total Loss: 0.6226, loss_single: 0.6226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,676 - Iter: 27, Total Loss: 0.6045, loss_single: 0.6045, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:29:51,711 - Iter: 28, Total Loss: 0.5866, loss_single: 0.5866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:29:51,746 - Iter: 29, Total Loss: 0.5699, loss_single: 0.5699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/simulation_data5__sample_000040.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/simulation_data5__sample_000040.yaml new file mode 100644 index 0000000000000000000000000000000000000000..70602dcff90a2532d36804bdd1a4bfe8182dec4d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/simulation_data5__sample_000040.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 19.200496673583984 + probe_aberrations: + C10: -291.3979187011719 + C12: -0.8437598347663879 + C21: -410.2870788574219 + C23: 822.152099609375 + C30: 655780.9375 + C32: 9067.974609375 + C34: 4065.61865234375 + C41: 150502.4375 + C43: -306506.75 + C45: -74310.0 + C50: -188006400.0 + C52: 7804305.5 + C54: 12622110.0 + C56: -18799760.0 + phi12: 320.56864492051204 + phi21: 61.81483074344869 + phi23: 345.1418077427637 + phi32: 232.68998305902394 + phi34: 184.59583439578282 + phi41: 292.6125440438665 + phi43: 308.99021752253316 + phi45: 204.8898017407514 + phi52: 279.4606049856567 + phi54: 257.5971967732026 + phi56: 138.9538465879813 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.31721946597099304 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000040_measurement.h5 + key: measurement + random_seed: 20262070 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000040 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/summary_convergence_iter0100.png new file mode 100644 index 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--- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3fbbfe6a87ffb27376d2dd413217587258bcabdf08f21736800b77e518c1a686 +size 1281268 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000040/c30_small__simulation_data5__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-291_C12_-0.844_phi12_321_C21_-410_phi21_61.8_C23_822_phi23_345_C30_6.56e+05_C32_.88e+07_phi56_139/summary_scan_pos_iter0100.png 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sha256:5719c1187f060b71c091e04bef271ad3c18b9855172596e0b813c9f227b3f268 +size 49915 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/20260624_063034_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/20260624_063034_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b252d14b71c8cc96649b9c84f2ffda12e8ddf772 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/20260624_063034_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:30:32,544 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:30:32,544 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:30:32,544 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:30:32,544 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:30:32,544 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:30:32,544 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:30:32,544 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:30:32,544 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:30:32,544 - +2026-06-24 06:30:32,649 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:30:32,649 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:30:32,649 - Accelerator.num_process = 1 +2026-06-24 06:30:32,649 - Accelerator.mixed_precision = no +2026-06-24 06:30:32,660 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:30:32,660 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:30:32,660 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:30:32,660 - +2026-06-24 06:30:32,660 - ### System information ### +2026-06-24 06:30:32,660 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:30:32,660 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:30:32,660 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:30:32,660 - Machine: x86_64 +2026-06-24 06:30:32,660 - Processor: x86_64 +2026-06-24 06:30:32,660 - Available CPU cores: 8 +2026-06-24 06:30:32,660 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:30:32,660 - +2026-06-24 06:30:32,661 - ### GPU information ### +2026-06-24 06:30:32,661 - CUDA Available: True +2026-06-24 06:30:32,661 - CUDA Version: 13.0 +2026-06-24 06:30:32,661 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:30:32,661 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:30:32,661 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:30:32,661 - In addition, Triton does not directly support Windows. +2026-06-24 06:30:32,661 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:30:32,676 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:30:32,677 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:30:32,677 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:30:32,677 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:30:32,677 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:30:32,677 - +2026-06-24 06:30:32,677 - ### Python information ### +2026-06-24 06:30:32,679 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:30:32,679 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:30:32,679 - +2026-06-24 06:30:32,679 - ### Packages information ### +2026-06-24 06:30:32,679 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:30:32,680 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:30:32,681 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:30:32,682 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:30:32,682 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:30:32,682 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:30:32,682 - +2026-06-24 06:30:32,682 - ### Loading params file ### +2026-06-24 06:30:32,682 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000043.yaml +2026-06-24 06:30:32,689 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:30:32,690 - Success! Params file validated and defaults applied. +2026-06-24 06:30:32,690 - +2026-06-24 06:30:32,690 - ### Setting GPU Device ### +2026-06-24 06:30:32,690 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:30:32,690 - +2026-06-24 06:30:32,690 - Random seed: 20262073 provided by params file +2026-06-24 06:30:32,690 - ### Initializing Initializer ### +2026-06-24 06:30:32,691 - init_params are displayed below: +2026-06-24 06:30:32,691 - random_seed: 20262073 +2026-06-24 06:30:32,691 - probe_illum_type: electron +2026-06-24 06:30:32,691 - probe_kv: 300.0 +2026-06-24 06:30:32,691 - probe_conv_angle: 12.285101890563965 +2026-06-24 06:30:32,691 - probe_aberrations: {'C10': 45.535, 'C12': 26.919, 'phi12': 137.73, 'C21': 402.864, 'phi21': 339.034, 'C23': -845.674, 'phi23': 254.371, 'C30': 3011251.25, 'C32': 6324.952, 'phi32': 134.707, 'C34': 3537.252, 'phi34': 49.341, 'C41': 39035.332, 'phi41': 261.55, 'C43': 94385.75, 'phi43': 35.02, 'C45': 2521.217, 'phi45': 216.559, 'C50': 473289568.0, 'C52': -6778251.0, 'phi52': 73.433, 'C54': 3233668.25, 'phi54': 191.34, 'C56': -9353782.0, 'phi56': 274.529} +2026-06-24 06:30:32,691 - beam_kev: None +2026-06-24 06:30:32,691 - probe_dRn: None +2026-06-24 06:30:32,691 - probe_Rn: None +2026-06-24 06:30:32,691 - probe_D_H: None +2026-06-24 06:30:32,691 - probe_D_FZP: None +2026-06-24 06:30:32,691 - probe_Ls: None +2026-06-24 06:30:32,691 - meas_Npix: 128 +2026-06-24 06:30:32,691 - pos_N_scans: 256 +2026-06-24 06:30:32,691 - pos_N_scan_slow: 16 +2026-06-24 06:30:32,691 - pos_N_scan_fast: 16 +2026-06-24 06:30:32,691 - pos_scan_step_size: 0.37635698914527893 +2026-06-24 06:30:32,691 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:30:32,691 - probe_pmode_max: 6 +2026-06-24 06:30:32,691 - probe_pmode_init_pows: [0.02] +2026-06-24 06:30:32,691 - obj_omode_max: 1 +2026-06-24 06:30:32,691 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:30:32,691 - obj_Nlayer: 1 +2026-06-24 06:30:32,691 - obj_slice_thickness: 20.0 +2026-06-24 06:30:32,691 - simu_Npix: None +2026-06-24 06:30:32,691 - simu_match_mode: None +2026-06-24 06:30:32,691 - meas_permute: None +2026-06-24 06:30:32,691 - meas_reshape: [256, 128, 128] +2026-06-24 06:30:32,691 - meas_flipT: [0, 0, 0] +2026-06-24 06:30:32,691 - meas_crop: None +2026-06-24 06:30:32,691 - meas_pad: None +2026-06-24 06:30:32,691 - meas_resample: None +2026-06-24 06:30:32,691 - meas_add_source_size: None +2026-06-24 06:30:32,691 - meas_add_detector_blur: None +2026-06-24 06:30:32,691 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:30:32,691 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:30:32,692 - meas_add_poisson_noise: None +2026-06-24 06:30:32,692 - meas_export: None +2026-06-24 06:30:32,692 - probe_permute: None +2026-06-24 06:30:32,692 - probe_z_shift: None +2026-06-24 06:30:32,692 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:30:32,692 - pos_scan_flipT: None +2026-06-24 06:30:32,692 - pos_scan_affine: None +2026-06-24 06:30:32,692 - pos_scan_rand_std: 0.15 +2026-06-24 06:30:32,692 - obj_z_crop: None +2026-06-24 06:30:32,692 - obj_z_pad: None +2026-06-24 06:30:32,692 - obj_z_resample: None +2026-06-24 06:30:32,692 - meas_source: file +2026-06-24 06:30:32,692 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000043_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:30:32,692 - probe_source: simu +2026-06-24 06:30:32,692 - probe_params: None +2026-06-24 06:30:32,692 - pos_source: simu +2026-06-24 06:30:32,692 - pos_params: None +2026-06-24 06:30:32,692 - obj_source: simu +2026-06-24 06:30:32,692 - obj_params: None +2026-06-24 06:30:32,692 - tilt_source: simu +2026-06-24 06:30:32,692 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:30:32,692 - +2026-06-24 06:30:32,692 - ### Initializing cache ### +2026-06-24 06:30:32,692 - use_cached_obj = False +2026-06-24 06:30:32,692 - use_cached_probe = False +2026-06-24 06:30:32,692 - use_cached_pos = False +2026-06-24 06:30:32,692 - +2026-06-24 06:30:32,692 - ### Initializing measurements ### +2026-06-24 06:30:32,692 - Loading measurements from source = 'file' +2026-06-24 06:30:32,692 - Detected measurement file type = '.h5' +2026-06-24 06:30:32,770 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:30:32,770 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:30:32,772 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0019) +2026-06-24 06:30:32,772 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:30:32,772 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:30:32,774 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:30:32,774 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:30:32,774 - Normalizing by max of the 2D mean pattern intensity: 0.0012692555 +2026-06-24 06:30:32,775 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:30:32,776 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0480, 1.4946) +2026-06-24 06:30:32,779 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:30:32,780 - Pattern total int. statistics (min, mean, max) = (782.0533, 786.7343, 792.6855), with min/max = 98.7% +2026-06-24 06:30:32,781 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0480, 1.4946) +2026-06-24 06:30:32,782 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:30:32,782 - +2026-06-24 06:30:32,782 - ### Setting up calibration ### +2026-06-24 06:30:32,782 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:30:32,782 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:30:32,782 - Radius of fitted bright field disk (RBF) = 15.89 px with meas_Npix = 128 +2026-06-24 06:30:32,782 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2482 +2026-06-24 06:30:32,782 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:30:32,782 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:30:33,014 - Initial guess: center=(63.61, 63.62), radius=15.89, Gaussian blur std=0.50 +2026-06-24 06:30:33,025 - Final fit: center=(63.61, 63.62), radius=15.89, Gaussian blur std=0.59 +2026-06-24 06:30:33,025 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 15.97 px with Npix = 128 +2026-06-24 06:30:33,025 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:30:33,025 - +2026-06-24 06:30:33,025 - ### Setting init_variables dict ### +2026-06-24 06:30:33,025 - Derived values given input init_params: +2026-06-24 06:30:33,025 - kv = 300.0 kV +2026-06-24 06:30:33,025 - wavelength = 0.0197 Ang +2026-06-24 06:30:33,025 - conv_angle = 12.285101890563965 mrad +2026-06-24 06:30:33,025 - Npix = 128 px +2026-06-24 06:30:33,025 - dk = 0.0391 Ang^-1 +2026-06-24 06:30:33,025 - kMax = 2.5000 Ang^-1 +2026-06-24 06:30:33,025 - da = 0.7690 mrad +2026-06-24 06:30:33,025 - angleMax = 49.2187 mrad +2026-06-24 06:30:33,025 - RBF = 15.9745 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:30:33,025 - n_alpha = 4.0064 (# conv_angle) +2026-06-24 06:30:33,025 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:30:33,025 - Rayleigh-limited resolution = 0.9776 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:30:33,025 - Real space probe extent = 25.6000 Ang +2026-06-24 06:30:33,025 - +2026-06-24 06:30:33,025 - ### Initializing probe ### +2026-06-24 06:30:33,025 - Loading probe from source = 'simu' +2026-06-24 06:30:33,025 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:30:33,026 - Start simulating STEM probe +2026-06-24 06:30:33,026 - kv = 300.0 kV +2026-06-24 06:30:33,026 - wavelength = 0.0197 Ang +2026-06-24 06:30:33,026 - conv_angle = 12.285101890563965 mrad +2026-06-24 06:30:33,026 - Npix = 128 px +2026-06-24 06:30:33,026 - dk = 0.0391 Ang^-1 +2026-06-24 06:30:33,026 - kMax = 2.5000 Ang^-1 +2026-06-24 06:30:33,026 - alpha_max = 49.2187 mrad +2026-06-24 06:30:33,026 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:30:33,026 - Rayleigh-limited resolution = 0.9776 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:30:33,026 - Real space probe extent = 25.6000 Ang +2026-06-24 06:30:33,026 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:30:33,026 - ------------------------------------------------------------------------------------ +2026-06-24 06:30:33,026 - C1,0 C1 45.5350 - Defocus (C10 = -df) +2026-06-24 06:30:33,026 - C1,2 A1 26.9190 137.73 2-fold astigmatism +2026-06-24 06:30:33,026 - C2,1 3*B2 402.8640 339.03 Axial coma +2026-06-24 06:30:33,026 - C2,3 A2 -845.6740 254.37 3-fold astigmatism +2026-06-24 06:30:33,026 - C3,0 C3 3011251.2500 - Spherical aberration +2026-06-24 06:30:33,026 - C3,2 4*S3 6324.9520 134.71 Axial star aberration +2026-06-24 06:30:33,026 - C3,4 A3 3537.2520 49.34 4-fold astigmatism +2026-06-24 06:30:33,026 - C4,1 4*B4 39035.3320 261.55 Axial coma(4th) +2026-06-24 06:30:33,026 - C4,3 4*D4 94385.7500 35.02 3-lobe aberration +2026-06-24 06:30:33,026 - C4,5 A4 2521.2170 216.56 5-fold astigmatism +2026-06-24 06:30:33,026 - C5,0 C5 473289568.0000 - Spherical aberration (5th) +2026-06-24 06:30:33,026 - C5,2 6*S5 -6778251.0000 73.43 Axial star aberration(5th) +2026-06-24 06:30:33,026 - C5,4 6*R5 3233668.2500 191.34 4-lobe aberration +2026-06-24 06:30:33,026 - C5,6 A5 -9353782.0000 274.53 6-fold astigmatism +2026-06-24 06:30:33,030 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:30:33,030 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:30:33,030 - Creating 5 new probe modes from the major mode +2026-06-24 06:30:33,030 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:30:33,225 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:30:33,226 - Orthogonalizing 6 pmodes +2026-06-24 06:30:33,239 - Sorting 6 pmodes by their intensities +2026-06-24 06:30:33,239 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:30:33,240 - sum(|probe_data|**2) = 786.73, while meas_total_ints (min, mean, max) = (782.0533, 786.7343, 792.6855) +2026-06-24 06:30:33,240 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:30:33,240 - +2026-06-24 06:30:33,240 - ### Initializing probe positions ### +2026-06-24 06:30:33,240 - Loading probe positions from source = 'simu' +2026-06-24 06:30:33,240 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:30:33,240 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3764, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:30:33,240 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:30:33,242 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:30:33,242 - crop_pos 1st and last px coords (y,x) = ([16, 16], [44, 44]) +2026-06-24 06:30:33,243 - crop_pos extent (Ang) = [5.8 5.6] +2026-06-24 06:30:33,243 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:30:33,243 - +2026-06-24 06:30:33,243 - ### Initializing object ### +2026-06-24 06:30:33,243 - Loading object from source = 'simu' +2026-06-24 06:30:33,243 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:30:33,244 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:30:33,244 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:30:33,244 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:30:33,245 - +2026-06-24 06:30:33,245 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:30:33,245 - omode_occu (omode) = float32, (1,) +2026-06-24 06:30:33,245 - +2026-06-24 06:30:33,245 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:30:33,245 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:30:33,245 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:30:33,245 - +2026-06-24 06:30:33,245 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:30:33,245 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:30:33,245 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:30:33,246 - +2026-06-24 06:30:33,246 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:30:33,246 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:30:33,246 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:30:33,246 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:30:33,246 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:30:33,246 - crop positions (yx_min=[15 16], yx_max=[172 172]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:30:33,246 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:30:33,246 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:30:33,246 - +2026-06-24 06:30:33,246 - ### Collecting reconstruction provenance ### +2026-06-24 06:30:33,246 - Reconstruction provenance is collected and initialized. +2026-06-24 06:30:33,246 - +2026-06-24 06:30:33,246 - ### Initializing loss function ### +2026-06-24 06:30:33,246 - Active loss types: +2026-06-24 06:30:33,246 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:30:33,246 - +2026-06-24 06:30:33,246 - ### Initializing constraint function ### +2026-06-24 06:30:33,246 - Active constraint types: +2026-06-24 06:30:33,246 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:30:33,247 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:30:33,247 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:30:33,247 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:30:33,247 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:30:33,247 - +2026-06-24 06:30:33,247 - ### Done initializing PtyRADSolver ### +2026-06-24 06:30:33,247 - +2026-06-24 06:30:33,373 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:30:33,373 - +2026-06-24 06:30:33,373 - ### Initializing PtychoModel model ### +2026-06-24 06:30:33,444 - ### PtychoModel optimizable variables ### +2026-06-24 06:30:33,444 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:30:33,444 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:30:33,444 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:30:33,444 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:30:33,445 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:30:33,445 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:30:33,445 - +2026-06-24 06:30:33,445 - ### Optimizable variables statitsics ### +2026-06-24 06:30:33,445 - Total measurement values : 4,194,304 +2026-06-24 06:30:33,445 - Total optimizing variables: 267,808 +2026-06-24 06:30:33,445 - Overdetermined ratio : 15.66 +2026-06-24 06:30:33,445 - +2026-06-24 06:30:33,445 - ### Model behavior ### +2026-06-24 06:30:33,445 - Tilt propagator : False +2026-06-24 06:30:33,445 - Change slice thickness : False +2026-06-24 06:30:33,445 - Detector blur : False +2026-06-24 06:30:33,445 - Preload data : True +2026-06-24 06:30:33,445 - On-the-fly meas padding : False +2026-06-24 06:30:33,445 - On-the-fly meas resample : False +2026-06-24 06:30:33,445 - On-the-fly simu match mode: None +2026-06-24 06:30:33,445 - +2026-06-24 06:30:33,486 - ### Done initializing PtychoModel model ### +2026-06-24 06:30:33,486 - +2026-06-24 06:30:33,486 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:30:33,487 - +2026-06-24 06:30:33,487 - ### Generating indices, batches, and output_path ### +2026-06-24 06:30:33,488 - d90 = 53.000 px or 10.600 Ang +2026-06-24 06:30:33,488 - Selecting indices with the 'full' mode +2026-06-24 06:30:33,950 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:30:34,022 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:30:34,023 - Original recon_dir_affixes = ['default'] +2026-06-24 06:30:34,023 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:30:34,029 - Path corrected for compatibility: +2026-06-24 06:30:34,029 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.32e+03_phi32_135_C34_3.54e+03_phi34_49.3_C41_3.9e+04_phi41_262_C43_9.44e+04_phi43_35_C45_2.52e+03_phi45_217_C50_4.73e+08_C52_-6.78e+06_phi52_73.4_C54_3.23e+06_phi54_191_C56_-9.35e+06_phi56_275 +2026-06-24 06:30:34,029 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275 +2026-06-24 06:30:34,030 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275' is generated! +2026-06-24 06:30:34,181 - +2026-06-24 06:30:34,182 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/20260624_063034_ptyrad_log.txt ### +2026-06-24 06:30:34,182 - +2026-06-24 06:30:34,183 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:30:34,183 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:30:34,183 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:30:35,372 - Iter: 1, Total Loss: 0.6523, loss_single: 0.6523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 06:30:35,409 - Iter: 2, Total Loss: 0.6267, loss_single: 0.6267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:30:35,445 - Iter: 3, Total Loss: 0.6062, loss_single: 0.6062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:30:35,481 - Iter: 4, Total Loss: 0.5887, loss_single: 0.5887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,516 - Iter: 5, Total Loss: 0.5722, loss_single: 0.5722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,551 - Iter: 6, Total Loss: 0.5544, loss_single: 0.5544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,587 - Iter: 7, Total Loss: 0.5350, loss_single: 0.5350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,624 - Iter: 8, Total Loss: 0.5165, loss_single: 0.5165, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:30:35,660 - Iter: 9, Total Loss: 0.5021, loss_single: 0.5021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,695 - Iter: 10, Total Loss: 0.4876, loss_single: 0.4876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,731 - Iter: 11, Total Loss: 0.4728, loss_single: 0.4728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,766 - Iter: 12, Total Loss: 0.4613, loss_single: 0.4613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,802 - Iter: 13, Total Loss: 0.4509, loss_single: 0.4509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,837 - Iter: 14, Total Loss: 0.4396, loss_single: 0.4396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,872 - Iter: 15, Total Loss: 0.4277, loss_single: 0.4277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,907 - Iter: 16, Total Loss: 0.4179, loss_single: 0.4179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:35,943 - Iter: 17, Total Loss: 0.4094, loss_single: 0.4094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:30:35,979 - Iter: 18, Total Loss: 0.3990, loss_single: 0.3990, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,014 - Iter: 19, Total Loss: 0.3880, loss_single: 0.3880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,049 - Iter: 20, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,085 - Iter: 21, Total Loss: 0.3733, loss_single: 0.3733, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,120 - Iter: 22, Total Loss: 0.3678, loss_single: 0.3678, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,156 - Iter: 23, Total Loss: 0.3625, loss_single: 0.3625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,191 - Iter: 24, Total Loss: 0.3567, loss_single: 0.3567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,226 - Iter: 25, Total Loss: 0.3528, loss_single: 0.3528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,262 - Iter: 26, Total Loss: 0.3492, loss_single: 0.3492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,297 - Iter: 27, Total Loss: 0.3444, loss_single: 0.3444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,333 - Iter: 28, Total Loss: 0.3400, loss_single: 0.3400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,368 - Iter: 29, Total Loss: 0.3356, loss_single: 0.3356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,404 - Iter: 30, Total Loss: 0.3320, loss_single: 0.3320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,439 - Iter: 31, Total Loss: 0.3296, loss_single: 0.3296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,475 - Iter: 32, Total Loss: 0.3268, loss_single: 0.3268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,510 - Iter: 33, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,545 - Iter: 34, Total Loss: 0.3213, loss_single: 0.3213, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,580 - Iter: 35, Total Loss: 0.3187, loss_single: 0.3187, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,616 - Iter: 36, Total Loss: 0.3163, loss_single: 0.3163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,651 - Iter: 37, Total Loss: 0.3141, loss_single: 0.3141, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,687 - Iter: 38, Total Loss: 0.3121, loss_single: 0.3121, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,722 - Iter: 39, Total Loss: 0.3104, loss_single: 0.3104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,758 - Iter: 40, Total Loss: 0.3085, loss_single: 0.3085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,796 - Iter: 41, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,831 - Iter: 42, Total Loss: 0.3053, loss_single: 0.3053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,867 - Iter: 43, Total Loss: 0.3040, loss_single: 0.3040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,902 - Iter: 44, Total Loss: 0.3029, loss_single: 0.3029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,937 - Iter: 45, Total Loss: 0.3020, loss_single: 0.3020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:36,973 - Iter: 46, Total Loss: 0.3014, loss_single: 0.3014, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,009 - Iter: 47, Total Loss: 0.3007, loss_single: 0.3007, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,044 - Iter: 48, Total Loss: 0.3000, loss_single: 0.3000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,080 - Iter: 49, Total Loss: 0.2994, loss_single: 0.2994, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,115 - Iter: 50, Total Loss: 0.2988, loss_single: 0.2988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,150 - Iter: 51, Total Loss: 0.2982, loss_single: 0.2982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,185 - Iter: 52, Total Loss: 0.2977, loss_single: 0.2977, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,221 - Iter: 53, Total Loss: 0.2973, loss_single: 0.2973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:30:37,256 - Iter: 54, Total Loss: 0.2969, loss_single: 0.2969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,292 - Iter: 55, Total Loss: 0.2965, loss_single: 0.2965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,327 - Iter: 56, Total Loss: 0.2962, loss_single: 0.2962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,363 - Iter: 57, Total Loss: 0.2959, loss_single: 0.2959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:30:37,398 - Iter: 58, Total Loss: 0.2956, loss_single: 0.2956, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/simulation_data5__sample_000043.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/simulation_data5__sample_000043.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3e1d6c9c953a5714ecfc645ea433b471e9d5421f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/simulation_data5__sample_000043.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 12.285101890563965 + probe_aberrations: + C10: 45.535369873046875 + C12: 26.919254302978516 + C21: 402.8643798828125 + C23: -845.6743774414062 + C30: 3011251.25 + C32: 6324.9521484375 + C34: 3537.25244140625 + C41: 39035.33203125 + C43: 94385.75 + C45: 2521.21728515625 + C50: 473289568.0 + C52: -6778251.0 + C54: 3233668.25 + C56: -9353782.0 + phi12: 137.73009525476846 + phi21: 339.03441651147836 + phi23: 254.37132574896222 + phi32: 134.70690326395908 + phi34: 49.34130363964504 + phi41: 261.5499365289157 + phi43: 35.02009425213705 + phi45: 216.55946680566333 + phi52: 73.43324206882883 + phi54: 191.33994952187507 + phi56: 274.5286619897739 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37635698914527893 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000043_measurement.h5 + key: measurement + random_seed: 20262073 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data5__sample_000043 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000043/c30_small__simulation_data5__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_45.5_C12_26.9_phi12_138_C21_403_phi21_339_C23_-846_phi23_254_C30_3.01e+06_C32_6.3.35e+06_phi56_275/summary_convergence_iter0100.png new file mode 100644 index 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sha256:c4f4bb82814e026e652bbe66be9b4532c0d9c544fd35afb362df9e56616ccaaf +size 47053 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166/20260624_063103_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166/20260624_063103_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a097bdf3cb7fffad8b4a288ede5dcfa22f1d0c6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166/20260624_063103_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:31:02,255 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:31:02,256 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:31:02,256 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:31:02,256 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:31:02,256 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:31:02,256 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:31:02,256 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:31:02,256 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:31:02,256 - +2026-06-24 06:31:02,365 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:31:02,365 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:31:02,365 - Accelerator.num_process = 1 +2026-06-24 06:31:02,365 - Accelerator.mixed_precision = no +2026-06-24 06:31:02,376 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:31:02,376 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:31:02,376 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:31:02,376 - +2026-06-24 06:31:02,376 - ### System information ### +2026-06-24 06:31:02,376 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:31:02,376 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:31:02,376 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:31:02,376 - Machine: x86_64 +2026-06-24 06:31:02,376 - Processor: x86_64 +2026-06-24 06:31:02,376 - Available CPU cores: 8 +2026-06-24 06:31:02,376 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:31:02,376 - +2026-06-24 06:31:02,376 - ### GPU information ### +2026-06-24 06:31:02,376 - CUDA Available: True +2026-06-24 06:31:02,376 - CUDA Version: 13.0 +2026-06-24 06:31:02,377 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:31:02,377 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:31:02,377 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:31:02,377 - In addition, Triton does not directly support Windows. +2026-06-24 06:31:02,377 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:31:02,392 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:31:02,392 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:31:02,392 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:31:02,392 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:31:02,392 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:31:02,392 - +2026-06-24 06:31:02,392 - ### Python information ### +2026-06-24 06:31:02,394 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:31:02,394 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:31:02,394 - +2026-06-24 06:31:02,394 - ### Packages information ### +2026-06-24 06:31:02,395 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:31:02,396 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:31:02,396 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:31:02,397 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:31:02,398 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:31:02,398 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:31:02,398 - +2026-06-24 06:31:02,398 - ### Loading params file ### +2026-06-24 06:31:02,398 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000045.yaml +2026-06-24 06:31:02,404 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:31:02,406 - Success! Params file validated and defaults applied. +2026-06-24 06:31:02,406 - +2026-06-24 06:31:02,406 - ### Setting GPU Device ### +2026-06-24 06:31:02,406 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:31:02,406 - +2026-06-24 06:31:02,406 - Random seed: 20262075 provided by params file +2026-06-24 06:31:02,406 - ### Initializing Initializer ### +2026-06-24 06:31:02,406 - init_params are displayed below: +2026-06-24 06:31:02,406 - random_seed: 20262075 +2026-06-24 06:31:02,406 - probe_illum_type: electron +2026-06-24 06:31:02,406 - probe_kv: 100.0 +2026-06-24 06:31:02,406 - probe_conv_angle: 21.830028533935547 +2026-06-24 06:31:02,406 - probe_aberrations: {'C10': -556.056, 'C12': -16.296, 'phi12': 51.914, 'C21': 709.417, 'phi21': 109.412, 'C23': -277.342, 'phi23': 168.423, 'C30': 1803313.125, 'C32': -5073.355, 'phi32': 31.872, 'C34': -1162.331, 'phi34': 240.971, 'C41': -288232.031, 'phi41': 88.803, 'C43': -7764.681, 'phi43': 16.988, 'C45': -231497.766, 'phi45': 142.764, 'C50': 285509280.0, 'C52': -5018603.0, 'phi52': 279.254, 'C54': -7011146.0, 'phi54': 184.745, 'C56': 6330160.5, 'phi56': 165.876} +2026-06-24 06:31:02,406 - beam_kev: None +2026-06-24 06:31:02,407 - probe_dRn: None +2026-06-24 06:31:02,407 - probe_Rn: None +2026-06-24 06:31:02,407 - probe_D_H: None +2026-06-24 06:31:02,407 - probe_D_FZP: None +2026-06-24 06:31:02,407 - probe_Ls: None +2026-06-24 06:31:02,407 - meas_Npix: 128 +2026-06-24 06:31:02,407 - pos_N_scans: 256 +2026-06-24 06:31:02,407 - pos_N_scan_slow: 16 +2026-06-24 06:31:02,407 - pos_N_scan_fast: 16 +2026-06-24 06:31:02,407 - pos_scan_step_size: 0.4023469090461731 +2026-06-24 06:31:02,407 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:31:02,407 - probe_pmode_max: 6 +2026-06-24 06:31:02,407 - probe_pmode_init_pows: [0.02] +2026-06-24 06:31:02,407 - obj_omode_max: 1 +2026-06-24 06:31:02,407 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:31:02,407 - obj_Nlayer: 1 +2026-06-24 06:31:02,407 - obj_slice_thickness: 20.0 +2026-06-24 06:31:02,407 - simu_Npix: None +2026-06-24 06:31:02,407 - simu_match_mode: None +2026-06-24 06:31:02,407 - meas_permute: None +2026-06-24 06:31:02,407 - meas_reshape: [256, 128, 128] +2026-06-24 06:31:02,407 - meas_flipT: [0, 0, 0] +2026-06-24 06:31:02,407 - meas_crop: None +2026-06-24 06:31:02,407 - meas_pad: None +2026-06-24 06:31:02,407 - meas_resample: None +2026-06-24 06:31:02,407 - meas_add_source_size: None +2026-06-24 06:31:02,407 - meas_add_detector_blur: None +2026-06-24 06:31:02,407 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:31:02,407 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:31:02,407 - meas_add_poisson_noise: None +2026-06-24 06:31:02,407 - meas_export: None +2026-06-24 06:31:02,407 - probe_permute: None +2026-06-24 06:31:02,407 - probe_z_shift: None +2026-06-24 06:31:02,407 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:31:02,407 - pos_scan_flipT: None +2026-06-24 06:31:02,407 - pos_scan_affine: None +2026-06-24 06:31:02,407 - pos_scan_rand_std: 0.15 +2026-06-24 06:31:02,407 - obj_z_crop: None +2026-06-24 06:31:02,407 - obj_z_pad: None +2026-06-24 06:31:02,408 - obj_z_resample: None +2026-06-24 06:31:02,408 - meas_source: file +2026-06-24 06:31:02,408 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000045_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:31:02,408 - probe_source: simu +2026-06-24 06:31:02,408 - probe_params: None +2026-06-24 06:31:02,408 - pos_source: simu +2026-06-24 06:31:02,408 - pos_params: None +2026-06-24 06:31:02,408 - obj_source: simu +2026-06-24 06:31:02,408 - obj_params: None +2026-06-24 06:31:02,408 - tilt_source: simu +2026-06-24 06:31:02,408 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:31:02,408 - +2026-06-24 06:31:02,408 - ### Initializing cache ### +2026-06-24 06:31:02,408 - use_cached_obj = False +2026-06-24 06:31:02,408 - use_cached_probe = False +2026-06-24 06:31:02,408 - use_cached_pos = False +2026-06-24 06:31:02,408 - +2026-06-24 06:31:02,408 - ### Initializing measurements ### +2026-06-24 06:31:02,408 - Loading measurements from source = 'file' +2026-06-24 06:31:02,408 - Detected measurement file type = '.h5' +2026-06-24 06:31:02,484 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:31:02,484 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:31:02,486 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0019) +2026-06-24 06:31:02,486 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:31:02,486 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:31:02,488 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:31:02,488 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:31:02,488 - Normalizing by max of the 2D mean pattern intensity: 0.0014672859 +2026-06-24 06:31:02,489 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:31:02,490 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0416, 1.2671) +2026-06-24 06:31:02,491 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:31:02,493 - Pattern total int. statistics (min, mean, max) = (677.0657, 682.0780, 686.4932), with min/max = 98.6% +2026-06-24 06:31:02,495 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0416, 1.2671) +2026-06-24 06:31:02,495 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:31:02,495 - +2026-06-24 06:31:02,495 - ### Setting up calibration ### +2026-06-24 06:31:02,495 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:31:02,495 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:31:02,495 - Radius of fitted bright field disk (RBF) = 14.98 px with meas_Npix = 128 +2026-06-24 06:31:02,495 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2341 +2026-06-24 06:31:02,495 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:31:02,495 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:31:02,725 - Initial guess: center=(63.64, 63.61), radius=14.98, Gaussian blur std=0.50 +2026-06-24 06:31:02,741 - Final fit: center=(63.64, 63.61), radius=14.98, Gaussian blur std=0.72 +2026-06-24 06:31:02,741 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 15.10 px with Npix = 128 +2026-06-24 06:31:02,741 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:31:02,741 - +2026-06-24 06:31:02,741 - ### Setting init_variables dict ### +2026-06-24 06:31:02,741 - Derived values given input init_params: +2026-06-24 06:31:02,741 - kv = 100.0 kV +2026-06-24 06:31:02,741 - wavelength = 0.0370 Ang +2026-06-24 06:31:02,741 - conv_angle = 21.830028533935547 mrad +2026-06-24 06:31:02,741 - Npix = 128 px +2026-06-24 06:31:02,741 - dk = 0.0391 Ang^-1 +2026-06-24 06:31:02,741 - kMax = 2.5000 Ang^-1 +2026-06-24 06:31:02,741 - da = 1.4459 mrad +2026-06-24 06:31:02,741 - angleMax = 92.5359 mrad +2026-06-24 06:31:02,741 - RBF = 15.0982 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:31:02,741 - n_alpha = 4.2389 (# conv_angle) +2026-06-24 06:31:02,741 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:31:02,741 - Rayleigh-limited resolution = 1.0343 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:31:02,741 - Real space probe extent = 25.6000 Ang +2026-06-24 06:31:02,742 - +2026-06-24 06:31:02,742 - ### Initializing probe ### +2026-06-24 06:31:02,742 - Loading probe from source = 'simu' +2026-06-24 06:31:02,742 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:31:02,742 - Start simulating STEM probe +2026-06-24 06:31:02,742 - kv = 100.0 kV +2026-06-24 06:31:02,742 - wavelength = 0.0370 Ang +2026-06-24 06:31:02,742 - conv_angle = 21.830028533935547 mrad +2026-06-24 06:31:02,742 - Npix = 128 px +2026-06-24 06:31:02,742 - dk = 0.0391 Ang^-1 +2026-06-24 06:31:02,742 - kMax = 2.5000 Ang^-1 +2026-06-24 06:31:02,742 - alpha_max = 92.5359 mrad +2026-06-24 06:31:02,742 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:31:02,742 - Rayleigh-limited resolution = 1.0343 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:31:02,742 - Real space probe extent = 25.6000 Ang +2026-06-24 06:31:02,742 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:31:02,742 - ------------------------------------------------------------------------------------ +2026-06-24 06:31:02,742 - C1,0 C1 -556.0560 - Defocus (C10 = -df) +2026-06-24 06:31:02,742 - C1,2 A1 -16.2960 51.91 2-fold astigmatism +2026-06-24 06:31:02,742 - C2,1 3*B2 709.4170 109.41 Axial coma +2026-06-24 06:31:02,742 - C2,3 A2 -277.3420 168.42 3-fold astigmatism +2026-06-24 06:31:02,742 - C3,0 C3 1803313.1250 - Spherical aberration +2026-06-24 06:31:02,743 - C3,2 4*S3 -5073.3550 31.87 Axial star aberration +2026-06-24 06:31:02,743 - C3,4 A3 -1162.3310 240.97 4-fold astigmatism +2026-06-24 06:31:02,743 - C4,1 4*B4 -288232.0310 88.80 Axial coma(4th) +2026-06-24 06:31:02,743 - C4,3 4*D4 -7764.6810 16.99 3-lobe aberration +2026-06-24 06:31:02,743 - C4,5 A4 -231497.7660 142.76 5-fold astigmatism +2026-06-24 06:31:02,743 - C5,0 C5 285509280.0000 - Spherical aberration (5th) +2026-06-24 06:31:02,743 - C5,2 6*S5 -5018603.0000 279.25 Axial star aberration(5th) +2026-06-24 06:31:02,743 - C5,4 6*R5 -7011146.0000 184.75 4-lobe aberration +2026-06-24 06:31:02,743 - C5,6 A5 6330160.5000 165.88 6-fold astigmatism +2026-06-24 06:31:02,746 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:31:02,746 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:31:02,746 - Creating 5 new probe modes from the major mode +2026-06-24 06:31:02,746 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:31:02,912 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:31:02,914 - Orthogonalizing 6 pmodes +2026-06-24 06:31:02,917 - Sorting 6 pmodes by their intensities +2026-06-24 06:31:02,918 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:31:02,919 - sum(|probe_data|**2) = 682.08, while meas_total_ints (min, mean, max) = (677.0657, 682.0780, 686.4932) +2026-06-24 06:31:02,919 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:31:02,919 - +2026-06-24 06:31:02,919 - ### Initializing probe positions ### +2026-06-24 06:31:02,919 - Loading probe positions from source = 'simu' +2026-06-24 06:31:02,919 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:31:02,919 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4023, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:31:02,919 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:31:02,921 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:31:02,921 - crop_pos 1st and last px coords (y,x) = ([16, 16], [46, 46]) +2026-06-24 06:31:02,921 - crop_pos extent (Ang) = [6. 6.2] +2026-06-24 06:31:02,921 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:31:02,921 - +2026-06-24 06:31:02,921 - ### Initializing object ### +2026-06-24 06:31:02,921 - Loading object from source = 'simu' +2026-06-24 06:31:02,921 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:31:02,923 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:31:02,923 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-24 06:31:02,923 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-24 06:31:02,923 - +2026-06-24 06:31:02,923 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:31:02,923 - omode_occu (omode) = float32, (1,) +2026-06-24 06:31:02,923 - +2026-06-24 06:31:02,923 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:31:02,923 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:31:02,924 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:31:02,924 - +2026-06-24 06:31:02,924 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:31:02,924 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:31:02,924 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:31:02,924 - +2026-06-24 06:31:02,924 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:31:02,924 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:31:02,924 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:31:02,924 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:31:02,924 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:31:02,925 - crop positions (yx_min=[16 16], yx_max=[174 175]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-24 06:31:02,925 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:31:02,925 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:31:02,925 - +2026-06-24 06:31:02,925 - ### Collecting reconstruction provenance ### +2026-06-24 06:31:02,925 - Reconstruction provenance is collected and initialized. +2026-06-24 06:31:02,925 - +2026-06-24 06:31:02,925 - ### Initializing loss function ### +2026-06-24 06:31:02,925 - Active loss types: +2026-06-24 06:31:02,925 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:31:02,925 - +2026-06-24 06:31:02,925 - ### Initializing constraint function ### +2026-06-24 06:31:02,925 - Active constraint types: +2026-06-24 06:31:02,925 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:31:02,925 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:31:02,925 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:31:02,925 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:31:02,925 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:31:02,925 - +2026-06-24 06:31:02,925 - ### Done initializing PtyRADSolver ### +2026-06-24 06:31:02,925 - +2026-06-24 06:31:03,051 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:31:03,051 - +2026-06-24 06:31:03,051 - ### Initializing PtychoModel model ### +2026-06-24 06:31:03,135 - ### PtychoModel optimizable variables ### +2026-06-24 06:31:03,135 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:31:03,135 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:31:03,135 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:31:03,135 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:31:03,135 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:31:03,135 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:31:03,135 - +2026-06-24 06:31:03,135 - ### Optimizable variables statitsics ### +2026-06-24 06:31:03,135 - Total measurement values : 4,194,304 +2026-06-24 06:31:03,135 - Total optimizing variables: 269,320 +2026-06-24 06:31:03,135 - Overdetermined ratio : 15.57 +2026-06-24 06:31:03,135 - +2026-06-24 06:31:03,135 - ### Model behavior ### +2026-06-24 06:31:03,135 - Tilt propagator : False +2026-06-24 06:31:03,135 - Change slice thickness : False +2026-06-24 06:31:03,135 - Detector blur : False +2026-06-24 06:31:03,135 - Preload data : True +2026-06-24 06:31:03,135 - On-the-fly meas padding : False +2026-06-24 06:31:03,136 - On-the-fly meas resample : False +2026-06-24 06:31:03,136 - On-the-fly simu match mode: None +2026-06-24 06:31:03,136 - +2026-06-24 06:31:03,177 - ### Done initializing PtychoModel model ### +2026-06-24 06:31:03,178 - +2026-06-24 06:31:03,178 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:31:03,178 - +2026-06-24 06:31:03,178 - ### Generating indices, batches, and output_path ### +2026-06-24 06:31:03,179 - d90 = 51.000 px or 10.200 Ang +2026-06-24 06:31:03,179 - Selecting indices with the 'full' mode +2026-06-24 06:31:03,639 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:31:03,713 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:31:03,713 - Original recon_dir_affixes = ['default'] +2026-06-24 06:31:03,713 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:31:03,719 - Path corrected for compatibility: +2026-06-24 06:31:03,719 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.07e+03_phi32_31.9_C34_-1.16e+03_phi34_241_C41_-2.88e+05_phi41_88.8_C43_-7.76e+03_phi43_17_C45_-2.31e+05_phi45_143_C50_2.86e+08_C52_-5.02e+06_phi52_279_C54_-7.01e+06_phi54_185_C56_6.33e+06_phi56_166 +2026-06-24 06:31:03,719 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166 +2026-06-24 06:31:03,720 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166' is generated! +2026-06-24 06:31:03,870 - +2026-06-24 06:31:03,871 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166/20260624_063103_ptyrad_log.txt ### +2026-06-24 06:31:03,871 - +2026-06-24 06:31:03,873 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:31:03,873 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:31:03,873 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:31:05,053 - Iter: 1, Total Loss: 0.6085, loss_single: 0.6085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:31:05,090 - Iter: 2, Total Loss: 0.5766, loss_single: 0.5766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:31:05,126 - Iter: 3, Total Loss: 0.5532, loss_single: 0.5532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:31:05,162 - Iter: 4, Total Loss: 0.5311, loss_single: 0.5311, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,197 - Iter: 5, Total Loss: 0.5081, loss_single: 0.5081, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,233 - Iter: 6, Total Loss: 0.4858, loss_single: 0.4858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,268 - Iter: 7, Total Loss: 0.4670, loss_single: 0.4670, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,303 - Iter: 8, Total Loss: 0.4496, loss_single: 0.4496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,339 - Iter: 9, Total Loss: 0.4324, loss_single: 0.4324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,374 - Iter: 10, Total Loss: 0.4190, loss_single: 0.4190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,409 - Iter: 11, Total Loss: 0.4069, loss_single: 0.4069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,445 - Iter: 12, Total Loss: 0.3932, loss_single: 0.3932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,480 - Iter: 13, Total Loss: 0.3801, loss_single: 0.3801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,515 - Iter: 14, Total Loss: 0.3689, loss_single: 0.3689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,551 - Iter: 15, Total Loss: 0.3579, loss_single: 0.3579, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,586 - Iter: 16, Total Loss: 0.3465, loss_single: 0.3465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,621 - Iter: 17, Total Loss: 0.3365, loss_single: 0.3365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,657 - Iter: 18, Total Loss: 0.3269, loss_single: 0.3269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,692 - Iter: 19, Total Loss: 0.3148, loss_single: 0.3148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,727 - Iter: 20, Total Loss: 0.3030, loss_single: 0.3030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,762 - Iter: 21, Total Loss: 0.2941, loss_single: 0.2941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,797 - Iter: 22, Total Loss: 0.2864, loss_single: 0.2864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,832 - Iter: 23, Total Loss: 0.2800, loss_single: 0.2800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,868 - Iter: 24, Total Loss: 0.2745, loss_single: 0.2745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,903 - Iter: 25, Total Loss: 0.2686, loss_single: 0.2686, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,939 - Iter: 26, Total Loss: 0.2622, loss_single: 0.2622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:05,974 - Iter: 27, Total Loss: 0.2567, loss_single: 0.2567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,010 - Iter: 28, Total Loss: 0.2527, loss_single: 0.2527, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,046 - Iter: 29, Total Loss: 0.2497, loss_single: 0.2497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,081 - Iter: 30, Total Loss: 0.2472, loss_single: 0.2472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,116 - Iter: 31, Total Loss: 0.2450, loss_single: 0.2450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,152 - Iter: 32, Total Loss: 0.2434, loss_single: 0.2434, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:31:06,187 - Iter: 33, Total Loss: 0.2422, loss_single: 0.2422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,223 - Iter: 34, Total Loss: 0.2412, loss_single: 0.2412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:06,258 - Iter: 35, Total Loss: 0.2402, loss_single: 0.2402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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0.2332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:08,533 - Iter: 99, Total Loss: 0.2332, loss_single: 0.2332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:08,568 - Iter: 100, Total Loss: 0.2332, loss_single: 0.2332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:31:08,680 - Saving summary figures for iter 100 +2026-06-24 06:31:12,423 - ### Finished 100 iterations, averaged iter_t = 0.039052 with std = 0.040 ### +2026-06-24 06:31:12,423 - +2026-06-24 06:31:12,423 - ### The PtyRADSolver is finished in 9.372 sec ### +2026-06-24 06:31:12,423 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000045/c30_small__simulation_data5__sample_000045_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-556_C12_-16.3_phi12_51.9_C21_709_phi21_109_C23_-277_phi23_168_C30_1.8e+06_C32_-5.33e+06_phi56_166/simulation_data5__sample_000045.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 21.830028533935547 + probe_aberrations: + C10: -556.05615234375 + C12: -16.295883178710938 + C21: 709.4169311523438 + C23: -277.34222412109375 + C30: 1803313.125 + C32: -5073.35546875 + C34: -1162.33056640625 + C41: -288232.03125 + C43: -7764.68115234375 + C45: -231497.765625 + C50: 285509280.0 + C52: -5018603.0 + C54: -7011146.0 + C56: 6330160.5 + phi12: 51.9139046358141 + phi21: 109.4122880502465 + phi23: 168.42298462994646 + phi32: 31.87169123346299 + phi34: 240.97090440874743 + phi41: 88.80334653170276 + phi43: 16.988210428195796 + phi45: 142.76427252214802 + phi52: 279.2543332727223 + phi54: 184.74458225552735 + phi56: 165.87636225828555 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4023469090461731 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000045_measurement.h5 + key: measurement + random_seed: 20262075 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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sha256:6fd5d21cc0267790e862c743710f1145e0951b72fab69f1f633703561a836625 +size 48021 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325/20260624_063202_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325/20260624_063202_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fded338802be6b4f3fecc3c1be74112917efe351 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325/20260624_063202_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:32:00,989 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:32:00,989 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:32:00,989 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:32:00,989 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:32:00,989 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:32:00,989 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:32:00,989 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:32:00,989 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:32:00,989 - +2026-06-24 06:32:01,084 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:32:01,084 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:32:01,084 - Accelerator.num_process = 1 +2026-06-24 06:32:01,084 - Accelerator.mixed_precision = no +2026-06-24 06:32:01,107 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:32:01,107 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:32:01,107 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:32:01,107 - +2026-06-24 06:32:01,107 - ### System information ### +2026-06-24 06:32:01,107 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:32:01,107 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:32:01,107 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:32:01,107 - Machine: x86_64 +2026-06-24 06:32:01,107 - Processor: x86_64 +2026-06-24 06:32:01,107 - Available CPU cores: 8 +2026-06-24 06:32:01,107 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:32:01,107 - +2026-06-24 06:32:01,108 - ### GPU information ### +2026-06-24 06:32:01,108 - CUDA Available: True +2026-06-24 06:32:01,108 - CUDA Version: 13.0 +2026-06-24 06:32:01,108 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:32:01,108 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:32:01,108 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:32:01,108 - In addition, Triton does not directly support Windows. +2026-06-24 06:32:01,108 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:32:01,124 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:32:01,124 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:32:01,124 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:32:01,124 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:32:01,124 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:32:01,124 - +2026-06-24 06:32:01,124 - ### Python information ### +2026-06-24 06:32:01,126 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:32:01,126 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:32:01,126 - +2026-06-24 06:32:01,126 - ### Packages information ### +2026-06-24 06:32:01,126 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:32:01,127 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:32:01,128 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:32:01,128 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:32:01,129 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:32:01,129 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:32:01,129 - +2026-06-24 06:32:01,129 - ### Loading params file ### +2026-06-24 06:32:01,129 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data5__sample_000049.yaml +2026-06-24 06:32:01,135 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:32:01,136 - Success! Params file validated and defaults applied. +2026-06-24 06:32:01,136 - +2026-06-24 06:32:01,136 - ### Setting GPU Device ### +2026-06-24 06:32:01,137 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:32:01,137 - +2026-06-24 06:32:01,137 - Random seed: 20262079 provided by params file +2026-06-24 06:32:01,137 - ### Initializing Initializer ### +2026-06-24 06:32:01,137 - init_params are displayed below: +2026-06-24 06:32:01,137 - random_seed: 20262079 +2026-06-24 06:32:01,137 - probe_illum_type: electron +2026-06-24 06:32:01,137 - probe_kv: 160.0 +2026-06-24 06:32:01,137 - probe_conv_angle: 21.82898712158203 +2026-06-24 06:32:01,137 - probe_aberrations: {'C10': -595.703, 'C12': 23.555, 'phi12': 26.866, 'C21': 638.275, 'phi21': 325.381, 'C23': -939.371, 'phi23': 121.297, 'C30': 2190541.75, 'C32': 9429.849, 'phi32': 181.97, 'C34': -11660.103, 'phi34': 216.557, 'C41': 465853.656, 'phi41': 176.29, 'C43': -5446.188, 'phi43': 333.604, 'C45': 61901.887, 'phi45': 17.321, 'C50': 36565064.0, 'C52': 14674568.0, 'phi52': 334.671, 'C54': -17446964.0, 'phi54': 118.007, 'C56': -198726.172, 'phi56': 324.521} +2026-06-24 06:32:01,137 - beam_kev: None +2026-06-24 06:32:01,137 - probe_dRn: None +2026-06-24 06:32:01,137 - probe_Rn: None +2026-06-24 06:32:01,137 - probe_D_H: None +2026-06-24 06:32:01,137 - probe_D_FZP: None +2026-06-24 06:32:01,137 - probe_Ls: None +2026-06-24 06:32:01,137 - meas_Npix: 128 +2026-06-24 06:32:01,137 - pos_N_scans: 256 +2026-06-24 06:32:01,138 - pos_N_scan_slow: 16 +2026-06-24 06:32:01,138 - pos_N_scan_fast: 16 +2026-06-24 06:32:01,138 - pos_scan_step_size: 0.3654622733592987 +2026-06-24 06:32:01,138 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:32:01,138 - probe_pmode_max: 6 +2026-06-24 06:32:01,138 - probe_pmode_init_pows: [0.02] +2026-06-24 06:32:01,138 - obj_omode_max: 1 +2026-06-24 06:32:01,138 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:32:01,138 - obj_Nlayer: 1 +2026-06-24 06:32:01,138 - obj_slice_thickness: 20.0 +2026-06-24 06:32:01,138 - simu_Npix: None +2026-06-24 06:32:01,138 - simu_match_mode: None +2026-06-24 06:32:01,138 - meas_permute: None +2026-06-24 06:32:01,138 - meas_reshape: [256, 128, 128] +2026-06-24 06:32:01,138 - meas_flipT: [0, 0, 0] +2026-06-24 06:32:01,138 - meas_crop: None +2026-06-24 06:32:01,138 - meas_pad: None +2026-06-24 06:32:01,138 - meas_resample: None +2026-06-24 06:32:01,138 - meas_add_source_size: None +2026-06-24 06:32:01,138 - meas_add_detector_blur: None +2026-06-24 06:32:01,138 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:32:01,138 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:32:01,138 - meas_add_poisson_noise: None +2026-06-24 06:32:01,138 - meas_export: None +2026-06-24 06:32:01,138 - probe_permute: None +2026-06-24 06:32:01,138 - probe_z_shift: None +2026-06-24 06:32:01,138 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:32:01,138 - pos_scan_flipT: None +2026-06-24 06:32:01,138 - pos_scan_affine: None +2026-06-24 06:32:01,138 - pos_scan_rand_std: 0.15 +2026-06-24 06:32:01,138 - obj_z_crop: None +2026-06-24 06:32:01,138 - obj_z_pad: None +2026-06-24 06:32:01,138 - obj_z_resample: None +2026-06-24 06:32:01,138 - meas_source: file +2026-06-24 06:32:01,138 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000049_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:32:01,138 - probe_source: simu +2026-06-24 06:32:01,138 - probe_params: None +2026-06-24 06:32:01,138 - pos_source: simu +2026-06-24 06:32:01,138 - pos_params: None +2026-06-24 06:32:01,138 - obj_source: simu +2026-06-24 06:32:01,138 - obj_params: None +2026-06-24 06:32:01,139 - tilt_source: simu +2026-06-24 06:32:01,139 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:32:01,139 - +2026-06-24 06:32:01,139 - ### Initializing cache ### +2026-06-24 06:32:01,139 - use_cached_obj = False +2026-06-24 06:32:01,139 - use_cached_probe = False +2026-06-24 06:32:01,139 - use_cached_pos = False +2026-06-24 06:32:01,139 - +2026-06-24 06:32:01,139 - ### Initializing measurements ### +2026-06-24 06:32:01,139 - Loading measurements from source = 'file' +2026-06-24 06:32:01,139 - Detected measurement file type = '.h5' +2026-06-24 06:32:01,211 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:32:01,211 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:32:01,213 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0019) +2026-06-24 06:32:01,213 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:32:01,213 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:32:01,214 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:32:01,214 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:32:01,215 - Normalizing by max of the 2D mean pattern intensity: 0.00087218004 +2026-06-24 06:32:01,215 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:32:01,217 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0704, 2.1418) +2026-06-24 06:32:01,217 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:32:01,218 - Pattern total int. statistics (min, mean, max) = (1133.9447, 1152.9561, 1174.6655), with min/max = 96.5% +2026-06-24 06:32:01,220 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0704, 2.1418) +2026-06-24 06:32:01,220 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:32:01,220 - +2026-06-24 06:32:01,220 - ### Setting up calibration ### +2026-06-24 06:32:01,220 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:32:01,220 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:32:01,220 - Radius of fitted bright field disk (RBF) = 19.29 px with meas_Npix = 128 +2026-06-24 06:32:01,220 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.3014 +2026-06-24 06:32:01,220 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:32:01,220 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:32:01,443 - Initial guess: center=(63.62, 63.63), radius=19.29, Gaussian blur std=0.50 +2026-06-24 06:32:01,455 - Final fit: center=(63.62, 63.63), radius=19.29, Gaussian blur std=0.63 +2026-06-24 06:32:01,455 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 19.60 px with Npix = 128 +2026-06-24 06:32:01,455 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:32:01,455 - +2026-06-24 06:32:01,455 - ### Setting init_variables dict ### +2026-06-24 06:32:01,455 - Derived values given input init_params: +2026-06-24 06:32:01,455 - kv = 160.0 kV +2026-06-24 06:32:01,455 - wavelength = 0.0285 Ang +2026-06-24 06:32:01,455 - conv_angle = 21.82898712158203 mrad +2026-06-24 06:32:01,455 - Npix = 128 px +2026-06-24 06:32:01,455 - dk = 0.0391 Ang^-1 +2026-06-24 06:32:01,455 - kMax = 2.5000 Ang^-1 +2026-06-24 06:32:01,455 - da = 1.1137 mrad +2026-06-24 06:32:01,456 - angleMax = 71.2751 mrad +2026-06-24 06:32:01,456 - RBF = 19.6009 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:32:01,456 - n_alpha = 3.2652 (# conv_angle) +2026-06-24 06:32:01,456 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:32:01,456 - Rayleigh-limited resolution = 0.7967 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:32:01,456 - Real space probe extent = 25.6000 Ang +2026-06-24 06:32:01,456 - +2026-06-24 06:32:01,456 - ### Initializing probe ### +2026-06-24 06:32:01,456 - Loading probe from source = 'simu' +2026-06-24 06:32:01,456 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:32:01,456 - Start simulating STEM probe +2026-06-24 06:32:01,456 - kv = 160.0 kV +2026-06-24 06:32:01,456 - wavelength = 0.0285 Ang +2026-06-24 06:32:01,456 - conv_angle = 21.82898712158203 mrad +2026-06-24 06:32:01,456 - Npix = 128 px +2026-06-24 06:32:01,456 - dk = 0.0391 Ang^-1 +2026-06-24 06:32:01,456 - kMax = 2.5000 Ang^-1 +2026-06-24 06:32:01,456 - alpha_max = 71.2751 mrad +2026-06-24 06:32:01,456 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:32:01,456 - Rayleigh-limited resolution = 0.7967 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:32:01,456 - Real space probe extent = 25.6000 Ang +2026-06-24 06:32:01,456 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:32:01,456 - ------------------------------------------------------------------------------------ +2026-06-24 06:32:01,456 - C1,0 C1 -595.7030 - Defocus (C10 = -df) +2026-06-24 06:32:01,457 - C1,2 A1 23.5550 26.87 2-fold astigmatism +2026-06-24 06:32:01,457 - C2,1 3*B2 638.2750 325.38 Axial coma +2026-06-24 06:32:01,457 - C2,3 A2 -939.3710 121.30 3-fold astigmatism +2026-06-24 06:32:01,457 - C3,0 C3 2190541.7500 - Spherical aberration +2026-06-24 06:32:01,457 - C3,2 4*S3 9429.8490 181.97 Axial star aberration +2026-06-24 06:32:01,457 - C3,4 A3 -11660.1030 216.56 4-fold astigmatism +2026-06-24 06:32:01,457 - C4,1 4*B4 465853.6560 176.29 Axial coma(4th) +2026-06-24 06:32:01,457 - C4,3 4*D4 -5446.1880 333.60 3-lobe aberration +2026-06-24 06:32:01,457 - C4,5 A4 61901.8870 17.32 5-fold astigmatism +2026-06-24 06:32:01,457 - C5,0 C5 36565064.0000 - Spherical aberration (5th) +2026-06-24 06:32:01,457 - C5,2 6*S5 14674568.0000 334.67 Axial star aberration(5th) +2026-06-24 06:32:01,457 - C5,4 6*R5 -17446964.0000 118.01 4-lobe aberration +2026-06-24 06:32:01,457 - C5,6 A5 -198726.1720 324.52 6-fold astigmatism +2026-06-24 06:32:01,460 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:32:01,460 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:32:01,460 - Creating 5 new probe modes from the major mode +2026-06-24 06:32:01,460 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:32:01,604 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:32:01,605 - Orthogonalizing 6 pmodes +2026-06-24 06:32:01,608 - Sorting 6 pmodes by their intensities +2026-06-24 06:32:01,608 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:32:01,609 - sum(|probe_data|**2) = 1152.96, while meas_total_ints (min, mean, max) = (1133.9447, 1152.9561, 1174.6655) +2026-06-24 06:32:01,609 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:32:01,609 - +2026-06-24 06:32:01,609 - ### Initializing probe positions ### +2026-06-24 06:32:01,609 - Loading probe positions from source = 'simu' +2026-06-24 06:32:01,609 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:32:01,609 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3655, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:32:01,609 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:32:01,611 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:32:01,611 - crop_pos 1st and last px coords (y,x) = ([15, 15], [42, 43]) +2026-06-24 06:32:01,611 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:32:01,611 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:32:01,611 - +2026-06-24 06:32:01,611 - ### Initializing object ### +2026-06-24 06:32:01,611 - Loading object from source = 'simu' +2026-06-24 06:32:01,611 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:32:01,613 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:32:01,613 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:32:01,613 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:32:01,613 - +2026-06-24 06:32:01,613 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:32:01,613 - omode_occu (omode) = float32, (1,) +2026-06-24 06:32:01,613 - +2026-06-24 06:32:01,613 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:32:01,613 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:32:01,614 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:32:01,614 - +2026-06-24 06:32:01,614 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:32:01,614 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:32:01,614 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:32:01,614 - +2026-06-24 06:32:01,614 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:32:01,614 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:32:01,614 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:32:01,614 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:32:01,614 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:32:01,615 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:32:01,615 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:32:01,615 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:32:01,615 - +2026-06-24 06:32:01,615 - ### Collecting reconstruction provenance ### +2026-06-24 06:32:01,615 - Reconstruction provenance is collected and initialized. +2026-06-24 06:32:01,615 - +2026-06-24 06:32:01,615 - ### Initializing loss function ### +2026-06-24 06:32:01,615 - Active loss types: +2026-06-24 06:32:01,615 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:32:01,615 - +2026-06-24 06:32:01,615 - ### Initializing constraint function ### +2026-06-24 06:32:01,615 - Active constraint types: +2026-06-24 06:32:01,615 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:32:01,615 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:32:01,615 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:32:01,615 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:32:01,615 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:32:01,615 - +2026-06-24 06:32:01,615 - ### Done initializing PtyRADSolver ### +2026-06-24 06:32:01,615 - +2026-06-24 06:32:01,740 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:32:01,740 - +2026-06-24 06:32:01,740 - ### Initializing PtychoModel model ### +2026-06-24 06:32:01,825 - ### PtychoModel optimizable variables ### +2026-06-24 06:32:01,825 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:32:01,825 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:32:01,825 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:32:01,825 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:32:01,825 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:32:01,825 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:32:01,825 - +2026-06-24 06:32:01,825 - ### Optimizable variables statitsics ### +2026-06-24 06:32:01,825 - Total measurement values : 4,194,304 +2026-06-24 06:32:01,825 - Total optimizing variables: 267,808 +2026-06-24 06:32:01,825 - Overdetermined ratio : 15.66 +2026-06-24 06:32:01,825 - +2026-06-24 06:32:01,825 - ### Model behavior ### +2026-06-24 06:32:01,825 - Tilt propagator : False +2026-06-24 06:32:01,825 - Change slice thickness : False +2026-06-24 06:32:01,825 - Detector blur : False +2026-06-24 06:32:01,826 - Preload data : True +2026-06-24 06:32:01,826 - On-the-fly meas padding : False +2026-06-24 06:32:01,826 - On-the-fly meas resample : False +2026-06-24 06:32:01,826 - On-the-fly simu match mode: None +2026-06-24 06:32:01,826 - +2026-06-24 06:32:01,867 - ### Done initializing PtychoModel model ### +2026-06-24 06:32:01,867 - +2026-06-24 06:32:01,868 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:32:01,868 - +2026-06-24 06:32:01,868 - ### Generating indices, batches, and output_path ### +2026-06-24 06:32:01,869 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:32:01,869 - Selecting indices with the 'full' mode +2026-06-24 06:32:02,332 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:32:02,406 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:32:02,406 - Original recon_dir_affixes = ['default'] +2026-06-24 06:32:02,406 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:32:02,412 - Path corrected for compatibility: +2026-06-24 06:32:02,413 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9.43e+03_phi32_182_C34_-1.17e+04_phi34_217_C41_4.66e+05_phi41_176_C43_-5.45e+03_phi43_334_C45_6.19e+04_phi45_17.3_C50_3.66e+07_C52_1.47e+07_phi52_335_C54_-1.74e+07_phi54_118_C56_-1.99e+05_phi56_325 +2026-06-24 06:32:02,413 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325 +2026-06-24 06:32:02,414 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325' is generated! +2026-06-24 06:32:02,561 - +2026-06-24 06:32:02,562 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325/20260624_063202_ptyrad_log.txt ### +2026-06-24 06:32:02,562 - +2026-06-24 06:32:02,563 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:32:02,563 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:32:02,563 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:32:03,756 - Iter: 1, Total Loss: 0.7012, loss_single: 0.7012, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:32:03,793 - Iter: 2, Total Loss: 0.6873, loss_single: 0.6873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:32:03,828 - Iter: 3, Total Loss: 0.6753, loss_single: 0.6753, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:03,863 - Iter: 4, Total Loss: 0.6627, loss_single: 0.6627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:03,898 - Iter: 5, Total Loss: 0.6509, loss_single: 0.6509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:03,933 - Iter: 6, Total Loss: 0.6427, loss_single: 0.6427, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:03,968 - Iter: 7, Total Loss: 0.6355, loss_single: 0.6355, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:04,003 - Iter: 8, Total Loss: 0.6276, loss_single: 0.6276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,039 - Iter: 9, Total Loss: 0.6204, loss_single: 0.6204, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,073 - Iter: 10, Total Loss: 0.6135, loss_single: 0.6135, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,108 - Iter: 11, Total Loss: 0.6077, loss_single: 0.6077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,144 - Iter: 12, Total Loss: 0.6018, loss_single: 0.6018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,179 - Iter: 13, Total Loss: 0.5961, loss_single: 0.5961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,214 - Iter: 14, Total Loss: 0.5912, loss_single: 0.5912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,249 - Iter: 15, Total Loss: 0.5865, loss_single: 0.5865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:04,284 - Iter: 16, Total Loss: 0.5821, loss_single: 0.5821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,319 - Iter: 17, Total Loss: 0.5776, loss_single: 0.5776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,353 - Iter: 18, Total Loss: 0.5732, loss_single: 0.5732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:04,388 - Iter: 19, Total Loss: 0.5701, loss_single: 0.5701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,423 - Iter: 20, Total Loss: 0.5667, loss_single: 0.5667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,458 - Iter: 21, Total Loss: 0.5636, loss_single: 0.5636, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:04,493 - Iter: 22, Total Loss: 0.5611, loss_single: 0.5611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:32:04,528 - Iter: 23, Total Loss: 0.5578, loss_single: 0.5578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:32:04,563 - Iter: 24, Total Loss: 0.5545, loss_single: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data5__sample_000049/c30_small__simulation_data5__sample_000049_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-596_C12_23.6_phi12_26.9_C21_638_phi21_325_C23_-939_phi23_121_C30_2.19e+06_C32_9..99e+05_phi56_325/simulation_data5__sample_000049.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 21.82898712158203 + probe_aberrations: + C10: -595.7033081054688 + C12: 23.5554256439209 + C21: 638.2750244140625 + C23: -939.3709716796875 + C30: 2190541.75 + C32: 9429.8486328125 + C34: -11660.1025390625 + C41: 465853.65625 + C43: -5446.18798828125 + C45: 61901.88671875 + C50: 36565064.0 + C52: 14674568.0 + C54: -17446964.0 + C56: -198726.171875 + phi12: 26.866279307772942 + phi21: 325.3813601342431 + phi23: 121.29730214949977 + phi32: 181.97024137693822 + phi34: 216.55728114512894 + phi41: 176.29011945937222 + phi43: 333.6035691778612 + phi45: 17.320832103038953 + phi52: 334.6708545375673 + phi54: 118.00650334700929 + phi56: 324.5205923742814 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3654622733592987 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data5__sample_000049_measurement.h5 + key: measurement + random_seed: 20262079 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/20260624_063301_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..e8360aed4e6df8030f7477ed0cd660bcdd5e0fab --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/20260624_063301_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:33:00,137 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:33:00,137 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:33:00,137 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:33:00,137 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:33:00,137 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:33:00,137 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:33:00,137 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:33:00,137 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:33:00,137 - +2026-06-24 06:33:00,244 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:33:00,244 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:33:00,244 - Accelerator.num_process = 1 +2026-06-24 06:33:00,244 - Accelerator.mixed_precision = no +2026-06-24 06:33:00,255 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:33:00,255 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:33:00,255 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:33:00,255 - +2026-06-24 06:33:00,255 - ### System information ### +2026-06-24 06:33:00,255 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:33:00,255 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:33:00,255 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:33:00,255 - Machine: x86_64 +2026-06-24 06:33:00,255 - Processor: x86_64 +2026-06-24 06:33:00,255 - Available CPU cores: 8 +2026-06-24 06:33:00,255 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:33:00,255 - +2026-06-24 06:33:00,255 - ### GPU information ### +2026-06-24 06:33:00,255 - CUDA Available: True +2026-06-24 06:33:00,255 - CUDA Version: 13.0 +2026-06-24 06:33:00,256 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:33:00,256 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:33:00,256 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:33:00,256 - In addition, Triton does not directly support Windows. +2026-06-24 06:33:00,256 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:33:00,272 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:33:00,272 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:33:00,272 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:33:00,272 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:33:00,272 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:33:00,272 - +2026-06-24 06:33:00,273 - ### Python information ### +2026-06-24 06:33:00,274 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:33:00,274 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:33:00,274 - +2026-06-24 06:33:00,274 - ### Packages information ### +2026-06-24 06:33:00,275 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:33:00,276 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:33:00,276 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:33:00,277 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:33:00,278 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:33:00,278 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:33:00,278 - +2026-06-24 06:33:00,278 - ### Loading params file ### +2026-06-24 06:33:00,278 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000003.yaml +2026-06-24 06:33:00,284 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:33:00,285 - Success! Params file validated and defaults applied. +2026-06-24 06:33:00,285 - +2026-06-24 06:33:00,285 - ### Setting GPU Device ### +2026-06-24 06:33:00,285 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:33:00,285 - +2026-06-24 06:33:00,285 - Random seed: 20262083 provided by params file +2026-06-24 06:33:00,286 - ### Initializing Initializer ### +2026-06-24 06:33:00,286 - init_params are displayed below: +2026-06-24 06:33:00,286 - random_seed: 20262083 +2026-06-24 06:33:00,286 - probe_illum_type: electron +2026-06-24 06:33:00,286 - probe_kv: 300.0 +2026-06-24 06:33:00,286 - probe_conv_angle: 10.354225158691406 +2026-06-24 06:33:00,286 - probe_aberrations: {'C10': -437.032, 'C12': -33.907, 'phi12': 37.645, 'C21': -787.7, 'phi21': 249.984, 'C23': 240.214, 'phi23': 55.935, 'C30': 4202250.0, 'C32': 5536.298, 'phi32': 16.434, 'C34': 1749.105, 'phi34': 161.792, 'C41': 24905.414, 'phi41': 224.355, 'C43': 435209.0, 'phi43': 69.741, 'C45': -352834.844, 'phi45': 333.031, 'C50': -19323910.0, 'C52': -5282967.5, 'phi52': 82.031, 'C54': 8099238.0, 'phi54': 16.505, 'C56': 7669527.5, 'phi56': 40.252} +2026-06-24 06:33:00,286 - beam_kev: None +2026-06-24 06:33:00,286 - probe_dRn: None +2026-06-24 06:33:00,286 - probe_Rn: None +2026-06-24 06:33:00,286 - probe_D_H: None +2026-06-24 06:33:00,286 - probe_D_FZP: None +2026-06-24 06:33:00,286 - probe_Ls: None +2026-06-24 06:33:00,286 - meas_Npix: 128 +2026-06-24 06:33:00,286 - pos_N_scans: 256 +2026-06-24 06:33:00,286 - pos_N_scan_slow: 16 +2026-06-24 06:33:00,286 - pos_N_scan_fast: 16 +2026-06-24 06:33:00,286 - pos_scan_step_size: 0.3066469132900238 +2026-06-24 06:33:00,286 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:33:00,286 - probe_pmode_max: 6 +2026-06-24 06:33:00,286 - probe_pmode_init_pows: [0.02] +2026-06-24 06:33:00,286 - obj_omode_max: 1 +2026-06-24 06:33:00,286 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:33:00,286 - obj_Nlayer: 1 +2026-06-24 06:33:00,286 - obj_slice_thickness: 20.0 +2026-06-24 06:33:00,287 - simu_Npix: None +2026-06-24 06:33:00,287 - simu_match_mode: None +2026-06-24 06:33:00,287 - meas_permute: None +2026-06-24 06:33:00,287 - meas_reshape: [256, 128, 128] +2026-06-24 06:33:00,287 - meas_flipT: [0, 0, 0] +2026-06-24 06:33:00,287 - meas_crop: None +2026-06-24 06:33:00,287 - meas_pad: None +2026-06-24 06:33:00,287 - meas_resample: None +2026-06-24 06:33:00,287 - meas_add_source_size: None +2026-06-24 06:33:00,287 - meas_add_detector_blur: None +2026-06-24 06:33:00,287 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:33:00,287 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:33:00,287 - meas_add_poisson_noise: None +2026-06-24 06:33:00,287 - meas_export: None +2026-06-24 06:33:00,287 - probe_permute: None +2026-06-24 06:33:00,287 - probe_z_shift: None +2026-06-24 06:33:00,287 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:33:00,287 - pos_scan_flipT: None +2026-06-24 06:33:00,287 - pos_scan_affine: None +2026-06-24 06:33:00,287 - pos_scan_rand_std: 0.15 +2026-06-24 06:33:00,287 - obj_z_crop: None +2026-06-24 06:33:00,287 - obj_z_pad: None +2026-06-24 06:33:00,287 - obj_z_resample: None +2026-06-24 06:33:00,287 - meas_source: file +2026-06-24 06:33:00,287 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000003_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:33:00,287 - probe_source: simu +2026-06-24 06:33:00,287 - probe_params: None +2026-06-24 06:33:00,287 - pos_source: simu +2026-06-24 06:33:00,287 - pos_params: None +2026-06-24 06:33:00,287 - obj_source: simu +2026-06-24 06:33:00,287 - obj_params: None +2026-06-24 06:33:00,287 - tilt_source: simu +2026-06-24 06:33:00,287 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:33:00,287 - +2026-06-24 06:33:00,287 - ### Initializing cache ### +2026-06-24 06:33:00,287 - use_cached_obj = False +2026-06-24 06:33:00,287 - use_cached_probe = False +2026-06-24 06:33:00,287 - use_cached_pos = False +2026-06-24 06:33:00,287 - +2026-06-24 06:33:00,288 - ### Initializing measurements ### +2026-06-24 06:33:00,288 - Loading measurements from source = 'file' +2026-06-24 06:33:00,288 - Detected measurement file type = '.h5' +2026-06-24 06:33:00,363 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:33:00,364 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:33:00,365 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0026) +2026-06-24 06:33:00,365 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:33:00,365 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:33:00,367 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:33:00,367 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:33:00,367 - Normalizing by max of the 2D mean pattern intensity: 0.001757186 +2026-06-24 06:33:00,368 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:33:00,369 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0348, 1.4638) +2026-06-24 06:33:00,370 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:33:00,371 - Pattern total int. statistics (min, mean, max) = (564.7775, 569.4302, 574.0466), with min/max = 98.4% +2026-06-24 06:33:00,372 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0348, 1.4638) +2026-06-24 06:33:00,372 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:33:00,372 - +2026-06-24 06:33:00,372 - ### Setting up calibration ### +2026-06-24 06:33:00,372 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:33:00,372 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:33:00,373 - Radius of fitted bright field disk (RBF) = 13.24 px with meas_Npix = 128 +2026-06-24 06:33:00,373 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2069 +2026-06-24 06:33:00,373 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:33:00,373 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:33:00,592 - Initial guess: center=(63.61, 63.62), radius=13.24, Gaussian blur std=0.50 +2026-06-24 06:33:00,604 - Final fit: center=(63.61, 63.62), radius=13.24, Gaussian blur std=0.67 +2026-06-24 06:33:00,605 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.46 px with Npix = 128 +2026-06-24 06:33:00,605 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:33:00,605 - +2026-06-24 06:33:00,605 - ### Setting init_variables dict ### +2026-06-24 06:33:00,605 - Derived values given input init_params: +2026-06-24 06:33:00,605 - kv = 300.0 kV +2026-06-24 06:33:00,605 - wavelength = 0.0197 Ang +2026-06-24 06:33:00,605 - conv_angle = 10.354225158691406 mrad +2026-06-24 06:33:00,605 - Npix = 128 px +2026-06-24 06:33:00,605 - dk = 0.0391 Ang^-1 +2026-06-24 06:33:00,605 - kMax = 2.5000 Ang^-1 +2026-06-24 06:33:00,605 - da = 0.7690 mrad +2026-06-24 06:33:00,605 - angleMax = 49.2187 mrad +2026-06-24 06:33:00,605 - RBF = 13.4638 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:33:00,605 - n_alpha = 4.7535 (# conv_angle) +2026-06-24 06:33:00,605 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:33:00,605 - Rayleigh-limited resolution = 1.1599 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:33:00,605 - Real space probe extent = 25.6000 Ang +2026-06-24 06:33:00,605 - +2026-06-24 06:33:00,605 - ### Initializing probe ### +2026-06-24 06:33:00,605 - Loading probe from source = 'simu' +2026-06-24 06:33:00,605 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:33:00,605 - Start simulating STEM probe +2026-06-24 06:33:00,606 - kv = 300.0 kV +2026-06-24 06:33:00,606 - wavelength = 0.0197 Ang +2026-06-24 06:33:00,606 - conv_angle = 10.354225158691406 mrad +2026-06-24 06:33:00,606 - Npix = 128 px +2026-06-24 06:33:00,606 - dk = 0.0391 Ang^-1 +2026-06-24 06:33:00,606 - kMax = 2.5000 Ang^-1 +2026-06-24 06:33:00,606 - alpha_max = 49.2187 mrad +2026-06-24 06:33:00,606 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:33:00,606 - Rayleigh-limited resolution = 1.1599 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:33:00,606 - Real space probe extent = 25.6000 Ang +2026-06-24 06:33:00,606 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:33:00,606 - ------------------------------------------------------------------------------------ +2026-06-24 06:33:00,606 - C1,0 C1 -437.0320 - Defocus (C10 = -df) +2026-06-24 06:33:00,606 - C1,2 A1 -33.9070 37.65 2-fold astigmatism +2026-06-24 06:33:00,606 - C2,1 3*B2 -787.7000 249.98 Axial coma +2026-06-24 06:33:00,606 - C2,3 A2 240.2140 55.94 3-fold astigmatism +2026-06-24 06:33:00,606 - C3,0 C3 4202250.0000 - Spherical aberration +2026-06-24 06:33:00,606 - C3,2 4*S3 5536.2980 16.43 Axial star aberration +2026-06-24 06:33:00,606 - C3,4 A3 1749.1050 161.79 4-fold astigmatism +2026-06-24 06:33:00,606 - C4,1 4*B4 24905.4140 224.35 Axial coma(4th) +2026-06-24 06:33:00,606 - C4,3 4*D4 435209.0000 69.74 3-lobe aberration +2026-06-24 06:33:00,606 - C4,5 A4 -352834.8440 333.03 5-fold astigmatism +2026-06-24 06:33:00,606 - C5,0 C5 -19323910.0000 - Spherical aberration (5th) +2026-06-24 06:33:00,606 - C5,2 6*S5 -5282967.5000 82.03 Axial star aberration(5th) +2026-06-24 06:33:00,606 - C5,4 6*R5 8099238.0000 16.50 4-lobe aberration +2026-06-24 06:33:00,606 - C5,6 A5 7669527.5000 40.25 6-fold astigmatism +2026-06-24 06:33:00,609 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:33:00,609 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:33:00,609 - Creating 5 new probe modes from the major mode +2026-06-24 06:33:00,609 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:33:00,713 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:33:00,714 - Orthogonalizing 6 pmodes +2026-06-24 06:33:00,717 - Sorting 6 pmodes by their intensities +2026-06-24 06:33:00,717 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:33:00,718 - sum(|probe_data|**2) = 569.43, while meas_total_ints (min, mean, max) = (564.7775, 569.4302, 574.0466) +2026-06-24 06:33:00,718 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:33:00,718 - +2026-06-24 06:33:00,718 - ### Initializing probe positions ### +2026-06-24 06:33:00,718 - Loading probe positions from source = 'simu' +2026-06-24 06:33:00,718 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:33:00,718 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3066, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:33:00,719 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:33:00,720 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:33:00,721 - crop_pos 1st and last px coords (y,x) = ([14, 15], [37, 38]) +2026-06-24 06:33:00,721 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 06:33:00,721 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:33:00,721 - +2026-06-24 06:33:00,721 - ### Initializing object ### +2026-06-24 06:33:00,721 - Loading object from source = 'simu' +2026-06-24 06:33:00,721 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:33:00,722 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:33:00,722 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 182, 182) +2026-06-24 06:33:00,722 - object extent (Z, Y, X) (Ang) = [20. 36.4 36.4] +2026-06-24 06:33:00,722 - +2026-06-24 06:33:00,722 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:33:00,723 - omode_occu (omode) = float32, (1,) +2026-06-24 06:33:00,723 - +2026-06-24 06:33:00,723 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:33:00,723 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:33:00,723 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:33:00,723 - +2026-06-24 06:33:00,723 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:33:00,723 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:33:00,723 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:33:00,723 - +2026-06-24 06:33:00,724 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:33:00,724 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:33:00,724 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:33:00,724 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:33:00,724 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:33:00,724 - crop positions (yx_min=[14 14], yx_max=[166 166]) are well contained inside object canvas (Ny,Nx) = (182, 182). +2026-06-24 06:33:00,724 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:33:00,724 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:33:00,724 - +2026-06-24 06:33:00,724 - ### Collecting reconstruction provenance ### +2026-06-24 06:33:00,724 - Reconstruction provenance is collected and initialized. +2026-06-24 06:33:00,724 - +2026-06-24 06:33:00,724 - ### Initializing loss function ### +2026-06-24 06:33:00,724 - Active loss types: +2026-06-24 06:33:00,724 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:33:00,724 - +2026-06-24 06:33:00,724 - ### Initializing constraint function ### +2026-06-24 06:33:00,724 - Active constraint types: +2026-06-24 06:33:00,724 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:33:00,724 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:33:00,724 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:33:00,724 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:33:00,725 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:33:00,725 - +2026-06-24 06:33:00,725 - ### Done initializing PtyRADSolver ### +2026-06-24 06:33:00,725 - +2026-06-24 06:33:00,850 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:33:00,850 - +2026-06-24 06:33:00,851 - ### Initializing PtychoModel model ### +2026-06-24 06:33:00,921 - ### PtychoModel optimizable variables ### +2026-06-24 06:33:00,921 - obja : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:00,921 - objp : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:00,921 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:33:00,921 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:33:00,921 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:33:00,921 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:00,921 - +2026-06-24 06:33:00,921 - ### Optimizable variables statitsics ### +2026-06-24 06:33:00,921 - Total measurement values : 4,194,304 +2026-06-24 06:33:00,921 - Total optimizing variables: 263,368 +2026-06-24 06:33:00,921 - Overdetermined ratio : 15.93 +2026-06-24 06:33:00,921 - +2026-06-24 06:33:00,921 - ### Model behavior ### +2026-06-24 06:33:00,921 - Tilt propagator : False +2026-06-24 06:33:00,921 - Change slice thickness : False +2026-06-24 06:33:00,921 - Detector blur : False +2026-06-24 06:33:00,921 - Preload data : True +2026-06-24 06:33:00,921 - On-the-fly meas padding : False +2026-06-24 06:33:00,921 - On-the-fly meas resample : False +2026-06-24 06:33:00,921 - On-the-fly simu match mode: None +2026-06-24 06:33:00,922 - +2026-06-24 06:33:00,962 - ### Done initializing PtychoModel model ### +2026-06-24 06:33:00,962 - +2026-06-24 06:33:00,962 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:33:00,962 - +2026-06-24 06:33:00,963 - ### Generating indices, batches, and output_path ### +2026-06-24 06:33:00,964 - d90 = 27.000 px or 5.400 Ang +2026-06-24 06:33:00,964 - Selecting indices with the 'full' mode +2026-06-24 06:33:01,424 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:33:01,510 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:33:01,510 - Original recon_dir_affixes = ['default'] +2026-06-24 06:33:01,510 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:33:01,516 - Path corrected for compatibility: +2026-06-24 06:33:01,516 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi32_16.4_C34_1.75e+03_phi34_162_C41_2.49e+04_phi41_224_C43_4.35e+05_phi43_69.7_C45_-3.53e+05_phi45_333_C50_-1.93e+07_C52_-5.28e+06_phi52_82_C54_8.1e+06_phi54_16.5_C56_7.67e+06_phi56_40.3 +2026-06-24 06:33:01,516 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3 +2026-06-24 06:33:01,518 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3' is generated! +2026-06-24 06:33:01,685 - +2026-06-24 06:33:01,686 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/20260624_063301_ptyrad_log.txt ### +2026-06-24 06:33:01,686 - +2026-06-24 06:33:01,688 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:33:01,688 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:33:01,688 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:33:02,910 - Iter: 1, Total Loss: 0.7275, loss_single: 0.7275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.444 sec +2026-06-24 06:33:02,948 - Iter: 2, Total Loss: 0.6976, loss_single: 0.6976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:33:02,983 - Iter: 3, Total Loss: 0.6760, loss_single: 0.6760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,018 - Iter: 4, Total Loss: 0.6574, loss_single: 0.6574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,053 - Iter: 5, Total Loss: 0.6358, loss_single: 0.6358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,088 - Iter: 6, Total Loss: 0.6125, loss_single: 0.6125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,124 - Iter: 7, Total Loss: 0.5904, loss_single: 0.5904, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,159 - Iter: 8, Total Loss: 0.5679, loss_single: 0.5679, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,194 - Iter: 9, Total Loss: 0.5507, loss_single: 0.5507, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,230 - Iter: 10, Total Loss: 0.5359, loss_single: 0.5359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,265 - Iter: 11, Total Loss: 0.5207, loss_single: 0.5207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,299 - Iter: 12, Total Loss: 0.5058, loss_single: 0.5058, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,335 - Iter: 13, Total Loss: 0.4892, loss_single: 0.4892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,370 - Iter: 14, Total Loss: 0.4739, loss_single: 0.4739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,405 - Iter: 15, Total Loss: 0.4601, loss_single: 0.4601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,442 - Iter: 16, Total Loss: 0.4483, loss_single: 0.4483, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:33:03,477 - Iter: 17, Total Loss: 0.4368, loss_single: 0.4368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,512 - Iter: 18, Total Loss: 0.4249, loss_single: 0.4249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,547 - Iter: 19, Total Loss: 0.4147, loss_single: 0.4147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,582 - Iter: 20, Total Loss: 0.4048, loss_single: 0.4048, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,617 - Iter: 21, Total Loss: 0.3963, loss_single: 0.3963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,652 - Iter: 22, Total Loss: 0.3901, loss_single: 0.3901, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,687 - Iter: 23, Total Loss: 0.3833, loss_single: 0.3833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,722 - Iter: 24, Total Loss: 0.3772, loss_single: 0.3772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,757 - Iter: 25, Total Loss: 0.3718, loss_single: 0.3718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,792 - Iter: 26, Total Loss: 0.3667, loss_single: 0.3667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,827 - Iter: 27, Total Loss: 0.3627, loss_single: 0.3627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,862 - Iter: 28, Total Loss: 0.3584, loss_single: 0.3584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:03,897 - Iter: 29, Total Loss: 0.3547, loss_single: 0.3547, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,932 - Iter: 30, Total Loss: 0.3514, loss_single: 0.3514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:03,966 - Iter: 31, Total Loss: 0.3488, loss_single: 0.3488, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,001 - Iter: 32, Total Loss: 0.3469, loss_single: 0.3469, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,036 - Iter: 33, Total Loss: 0.3450, loss_single: 0.3450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,071 - Iter: 34, Total Loss: 0.3435, loss_single: 0.3435, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,108 - Iter: 35, Total Loss: 0.3419, loss_single: 0.3419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:33:04,143 - Iter: 36, Total Loss: 0.3403, loss_single: 0.3403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,178 - Iter: 37, Total Loss: 0.3390, loss_single: 0.3390, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,213 - Iter: 38, Total Loss: 0.3376, loss_single: 0.3376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,248 - Iter: 39, Total Loss: 0.3366, loss_single: 0.3366, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,283 - Iter: 40, Total Loss: 0.3356, loss_single: 0.3356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,319 - Iter: 41, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,354 - Iter: 42, Total Loss: 0.3341, loss_single: 0.3341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,389 - Iter: 43, Total Loss: 0.3334, loss_single: 0.3334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,424 - Iter: 44, Total Loss: 0.3328, loss_single: 0.3328, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,459 - Iter: 45, Total Loss: 0.3323, loss_single: 0.3323, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,494 - Iter: 46, Total Loss: 0.3318, loss_single: 0.3318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,529 - Iter: 47, Total Loss: 0.3314, loss_single: 0.3314, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,564 - Iter: 48, Total Loss: 0.3310, loss_single: 0.3310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,599 - Iter: 49, Total Loss: 0.3306, loss_single: 0.3306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,635 - Iter: 50, Total Loss: 0.3301, loss_single: 0.3301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,669 - Iter: 51, Total Loss: 0.3297, loss_single: 0.3297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,704 - Iter: 52, Total Loss: 0.3294, loss_single: 0.3294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,739 - Iter: 53, Total Loss: 0.3291, loss_single: 0.3291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,774 - Iter: 54, Total Loss: 0.3288, loss_single: 0.3288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,809 - Iter: 55, Total Loss: 0.3285, loss_single: 0.3285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,846 - Iter: 56, Total Loss: 0.3282, loss_single: 0.3282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:33:04,881 - Iter: 57, Total Loss: 0.3279, loss_single: 0.3279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,916 - Iter: 58, Total Loss: 0.3276, loss_single: 0.3276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:04,951 - Iter: 59, Total Loss: 0.3274, loss_single: 0.3274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:04,986 - Iter: 60, Total Loss: 0.3272, loss_single: 0.3272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,020 - Iter: 61, Total Loss: 0.3269, loss_single: 0.3269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,056 - Iter: 62, Total Loss: 0.3266, loss_single: 0.3266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,091 - Iter: 63, Total Loss: 0.3263, loss_single: 0.3263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,125 - Iter: 64, Total Loss: 0.3260, loss_single: 0.3260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,160 - Iter: 65, Total Loss: 0.3258, loss_single: 0.3258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,195 - Iter: 66, Total Loss: 0.3256, loss_single: 0.3256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,230 - Iter: 67, Total Loss: 0.3254, loss_single: 0.3254, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,265 - Iter: 68, Total Loss: 0.3252, loss_single: 0.3252, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,300 - Iter: 69, Total Loss: 0.3249, loss_single: 0.3249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,335 - Iter: 70, Total Loss: 0.3246, loss_single: 0.3246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,371 - Iter: 71, Total Loss: 0.3243, loss_single: 0.3243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:05,405 - Iter: 72, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,440 - Iter: 73, Total Loss: 0.3238, loss_single: 0.3238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:33:05,476 - Iter: 74, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:33:05,512 - Iter: 75, Total Loss: 0.3233, loss_single: 0.3233, loss_poissn: 0.0000, loss_pacbed: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/simulation_data_aug1__sample_000003.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 10.354225158691406 + probe_aberrations: + C10: -437.0322570800781 + C12: -33.90692901611328 + C21: -787.699951171875 + C23: 240.21405029296875 + C30: 4202250.0 + C32: 5536.2978515625 + C34: 1749.10546875 + C41: 24905.4140625 + C43: 435209.0 + C45: -352834.84375 + C50: -19323910.0 + C52: -5282967.5 + C54: 8099238.0 + C56: 7669527.5 + phi12: 37.64468664826824 + phi21: 249.98445916960313 + phi23: 55.93548245307717 + phi32: 16.433517105320718 + phi34: 161.79233260634646 + phi41: 224.35478902615557 + phi43: 69.74066421860152 + phi45: 333.0313359291975 + phi52: 82.03098174320334 + phi54: 16.504569855709068 + phi56: 40.25244262809535 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3066469132900238 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000003_measurement.h5 + key: measurement + random_seed: 20262083 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug1__sample_000003 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000003/c30_small__simulation_data_aug1__sample_000003_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-437_C12_-33.9_phi12_37.6_C21_-788_phi21_250_C23_240_phi23_55.9_C30_4.2e+06_C32_5.54e+03_phi.3/summary_convergence_iter0100.png new file mode 100644 index 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/20260624_063345_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..a18dc8996389831a9ea2ae5de56855132010f41c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/20260624_063345_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:33:44,081 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:33:44,081 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:33:44,082 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:33:44,082 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:33:44,082 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:33:44,082 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:33:44,082 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:33:44,082 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:33:44,082 - +2026-06-24 06:33:44,188 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:33:44,188 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:33:44,188 - Accelerator.num_process = 1 +2026-06-24 06:33:44,188 - Accelerator.mixed_precision = no +2026-06-24 06:33:44,199 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:33:44,199 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:33:44,199 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:33:44,199 - +2026-06-24 06:33:44,199 - ### System information ### +2026-06-24 06:33:44,199 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:33:44,199 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:33:44,199 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:33:44,199 - Machine: x86_64 +2026-06-24 06:33:44,199 - Processor: x86_64 +2026-06-24 06:33:44,199 - Available CPU cores: 8 +2026-06-24 06:33:44,199 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:33:44,199 - +2026-06-24 06:33:44,199 - ### GPU information ### +2026-06-24 06:33:44,199 - CUDA Available: True +2026-06-24 06:33:44,199 - CUDA Version: 13.0 +2026-06-24 06:33:44,200 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:33:44,200 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:33:44,200 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:33:44,200 - In addition, Triton does not directly support Windows. +2026-06-24 06:33:44,200 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:33:44,215 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:33:44,215 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:33:44,215 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:33:44,215 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:33:44,216 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:33:44,216 - +2026-06-24 06:33:44,216 - ### Python information ### +2026-06-24 06:33:44,218 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:33:44,218 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:33:44,218 - +2026-06-24 06:33:44,218 - ### Packages information ### +2026-06-24 06:33:44,219 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:33:44,219 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:33:44,220 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:33:44,221 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:33:44,221 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:33:44,221 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:33:44,221 - +2026-06-24 06:33:44,221 - ### Loading params file ### +2026-06-24 06:33:44,221 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000006.yaml +2026-06-24 06:33:44,228 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:33:44,229 - Success! Params file validated and defaults applied. +2026-06-24 06:33:44,229 - +2026-06-24 06:33:44,229 - ### Setting GPU Device ### +2026-06-24 06:33:44,229 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:33:44,229 - +2026-06-24 06:33:44,229 - Random seed: 20262086 provided by params file +2026-06-24 06:33:44,229 - ### Initializing Initializer ### +2026-06-24 06:33:44,230 - init_params are displayed below: +2026-06-24 06:33:44,230 - random_seed: 20262086 +2026-06-24 06:33:44,230 - probe_illum_type: electron +2026-06-24 06:33:44,230 - probe_kv: 120.0 +2026-06-24 06:33:44,230 - probe_conv_angle: 12.336362838745117 +2026-06-24 06:33:44,230 - probe_aberrations: {'C10': -442.145, 'C12': 40.874, 'phi12': 100.18, 'C21': 781.125, 'phi21': 342.997, 'C23': -20.786, 'phi23': 187.795, 'C30': -59405.977, 'C32': -9429.709, 'phi32': 333.781, 'C34': 7343.977, 'phi34': 342.544, 'C41': 253643.156, 'phi41': 166.584, 'C43': -236337.516, 'phi43': 159.926, 'C45': -371914.281, 'phi45': 112.764, 'C50': 496905056.0, 'C52': -6997994.0, 'phi52': 0.193, 'C54': 11449285.0, 'phi54': 313.675, 'C56': -8793493.0, 'phi56': 92.489} +2026-06-24 06:33:44,230 - beam_kev: None +2026-06-24 06:33:44,230 - probe_dRn: None +2026-06-24 06:33:44,230 - probe_Rn: None +2026-06-24 06:33:44,230 - probe_D_H: None +2026-06-24 06:33:44,230 - probe_D_FZP: None +2026-06-24 06:33:44,230 - probe_Ls: None +2026-06-24 06:33:44,230 - meas_Npix: 128 +2026-06-24 06:33:44,230 - pos_N_scans: 256 +2026-06-24 06:33:44,230 - pos_N_scan_slow: 16 +2026-06-24 06:33:44,230 - pos_N_scan_fast: 16 +2026-06-24 06:33:44,230 - pos_scan_step_size: 0.4910949170589447 +2026-06-24 06:33:44,230 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:33:44,230 - probe_pmode_max: 6 +2026-06-24 06:33:44,230 - probe_pmode_init_pows: [0.02] +2026-06-24 06:33:44,230 - obj_omode_max: 1 +2026-06-24 06:33:44,230 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:33:44,230 - obj_Nlayer: 1 +2026-06-24 06:33:44,230 - obj_slice_thickness: 20.0 +2026-06-24 06:33:44,230 - simu_Npix: None +2026-06-24 06:33:44,230 - simu_match_mode: None +2026-06-24 06:33:44,230 - meas_permute: None +2026-06-24 06:33:44,230 - meas_reshape: [256, 128, 128] +2026-06-24 06:33:44,230 - meas_flipT: [0, 0, 0] +2026-06-24 06:33:44,230 - meas_crop: None +2026-06-24 06:33:44,230 - meas_pad: None +2026-06-24 06:33:44,230 - meas_resample: None +2026-06-24 06:33:44,230 - meas_add_source_size: None +2026-06-24 06:33:44,230 - meas_add_detector_blur: None +2026-06-24 06:33:44,230 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:33:44,231 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:33:44,231 - meas_add_poisson_noise: None +2026-06-24 06:33:44,231 - meas_export: None +2026-06-24 06:33:44,231 - probe_permute: None +2026-06-24 06:33:44,231 - probe_z_shift: None +2026-06-24 06:33:44,231 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:33:44,231 - pos_scan_flipT: None +2026-06-24 06:33:44,231 - pos_scan_affine: None +2026-06-24 06:33:44,231 - pos_scan_rand_std: 0.15 +2026-06-24 06:33:44,231 - obj_z_crop: None +2026-06-24 06:33:44,231 - obj_z_pad: None +2026-06-24 06:33:44,231 - obj_z_resample: None +2026-06-24 06:33:44,231 - meas_source: file +2026-06-24 06:33:44,231 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000006_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:33:44,231 - probe_source: simu +2026-06-24 06:33:44,231 - probe_params: None +2026-06-24 06:33:44,231 - pos_source: simu +2026-06-24 06:33:44,231 - pos_params: None +2026-06-24 06:33:44,231 - obj_source: simu +2026-06-24 06:33:44,231 - obj_params: None +2026-06-24 06:33:44,231 - tilt_source: simu +2026-06-24 06:33:44,231 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:33:44,231 - +2026-06-24 06:33:44,231 - ### Initializing cache ### +2026-06-24 06:33:44,231 - use_cached_obj = False +2026-06-24 06:33:44,231 - use_cached_probe = False +2026-06-24 06:33:44,231 - use_cached_pos = False +2026-06-24 06:33:44,231 - +2026-06-24 06:33:44,231 - ### Initializing measurements ### +2026-06-24 06:33:44,231 - Loading measurements from source = 'file' +2026-06-24 06:33:44,231 - Detected measurement file type = '.h5' +2026-06-24 06:33:44,305 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:33:44,305 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:33:44,306 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0046) +2026-06-24 06:33:44,307 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:33:44,307 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:33:44,308 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:33:44,308 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:33:44,309 - Normalizing by max of the 2D mean pattern intensity: 0.0036609429 +2026-06-24 06:33:44,310 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:33:44,311 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0167, 1.2499) +2026-06-24 06:33:44,311 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:33:44,313 - Pattern total int. statistics (min, mean, max) = (271.6032, 273.3888, 275.7719), with min/max = 98.5% +2026-06-24 06:33:44,314 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0167, 1.2499) +2026-06-24 06:33:44,314 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:33:44,314 - +2026-06-24 06:33:44,314 - ### Setting up calibration ### +2026-06-24 06:33:44,314 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:33:44,314 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:33:44,314 - Radius of fitted bright field disk (RBF) = 9.25 px with meas_Npix = 128 +2026-06-24 06:33:44,314 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1446 +2026-06-24 06:33:44,314 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:33:44,314 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:33:44,545 - Initial guess: center=(63.63, 63.63), radius=9.25, Gaussian blur std=0.50 +2026-06-24 06:33:44,560 - Final fit: center=(63.63, 63.63), radius=9.25, Gaussian blur std=0.72 +2026-06-24 06:33:44,560 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.43 px with Npix = 128 +2026-06-24 06:33:44,560 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:33:44,561 - +2026-06-24 06:33:44,561 - ### Setting init_variables dict ### +2026-06-24 06:33:44,561 - Derived values given input init_params: +2026-06-24 06:33:44,561 - kv = 120.0 kV +2026-06-24 06:33:44,561 - wavelength = 0.0335 Ang +2026-06-24 06:33:44,561 - conv_angle = 12.336362838745117 mrad +2026-06-24 06:33:44,561 - Npix = 128 px +2026-06-24 06:33:44,561 - dk = 0.0391 Ang^-1 +2026-06-24 06:33:44,561 - kMax = 2.5000 Ang^-1 +2026-06-24 06:33:44,561 - da = 1.3083 mrad +2026-06-24 06:33:44,561 - angleMax = 83.7304 mrad +2026-06-24 06:33:44,561 - RBF = 9.4294 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:33:44,561 - n_alpha = 6.7873 (# conv_angle) +2026-06-24 06:33:44,561 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:33:44,561 - Rayleigh-limited resolution = 1.6561 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:33:44,561 - Real space probe extent = 25.6000 Ang +2026-06-24 06:33:44,561 - +2026-06-24 06:33:44,561 - ### Initializing probe ### +2026-06-24 06:33:44,561 - Loading probe from source = 'simu' +2026-06-24 06:33:44,561 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:33:44,561 - Start simulating STEM probe +2026-06-24 06:33:44,561 - kv = 120.0 kV +2026-06-24 06:33:44,561 - wavelength = 0.0335 Ang +2026-06-24 06:33:44,561 - conv_angle = 12.336362838745117 mrad +2026-06-24 06:33:44,561 - Npix = 128 px +2026-06-24 06:33:44,562 - dk = 0.0391 Ang^-1 +2026-06-24 06:33:44,562 - kMax = 2.5000 Ang^-1 +2026-06-24 06:33:44,562 - alpha_max = 83.7304 mrad +2026-06-24 06:33:44,562 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:33:44,562 - Rayleigh-limited resolution = 1.6561 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:33:44,562 - Real space probe extent = 25.6000 Ang +2026-06-24 06:33:44,562 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:33:44,562 - ------------------------------------------------------------------------------------ +2026-06-24 06:33:44,562 - C1,0 C1 -442.1450 - Defocus (C10 = -df) +2026-06-24 06:33:44,562 - C1,2 A1 40.8740 100.18 2-fold astigmatism +2026-06-24 06:33:44,562 - C2,1 3*B2 781.1250 343.00 Axial coma +2026-06-24 06:33:44,562 - C2,3 A2 -20.7860 187.79 3-fold astigmatism +2026-06-24 06:33:44,562 - C3,0 C3 -59405.9770 - Spherical aberration +2026-06-24 06:33:44,562 - C3,2 4*S3 -9429.7090 333.78 Axial star aberration +2026-06-24 06:33:44,562 - C3,4 A3 7343.9770 342.54 4-fold astigmatism +2026-06-24 06:33:44,562 - C4,1 4*B4 253643.1560 166.58 Axial coma(4th) +2026-06-24 06:33:44,562 - C4,3 4*D4 -236337.5160 159.93 3-lobe aberration +2026-06-24 06:33:44,562 - C4,5 A4 -371914.2810 112.76 5-fold astigmatism +2026-06-24 06:33:44,562 - C5,0 C5 496905056.0000 - Spherical aberration (5th) +2026-06-24 06:33:44,562 - C5,2 6*S5 -6997994.0000 0.19 Axial star aberration(5th) +2026-06-24 06:33:44,562 - C5,4 6*R5 11449285.0000 313.68 4-lobe aberration +2026-06-24 06:33:44,562 - C5,6 A5 -8793493.0000 92.49 6-fold astigmatism +2026-06-24 06:33:44,565 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:33:44,565 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:33:44,565 - Creating 5 new probe modes from the major mode +2026-06-24 06:33:44,565 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:33:44,709 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:33:44,711 - Orthogonalizing 6 pmodes +2026-06-24 06:33:44,713 - Sorting 6 pmodes by their intensities +2026-06-24 06:33:44,714 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:33:44,714 - sum(|probe_data|**2) = 273.39, while meas_total_ints (min, mean, max) = (271.6032, 273.3888, 275.7719) +2026-06-24 06:33:44,714 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:33:44,714 - +2026-06-24 06:33:44,714 - ### Initializing probe positions ### +2026-06-24 06:33:44,714 - Loading probe positions from source = 'simu' +2026-06-24 06:33:44,715 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:33:44,715 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4911, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:33:44,715 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:33:44,717 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:33:44,717 - crop_pos 1st and last px coords (y,x) = ([17, 17], [53, 53]) +2026-06-24 06:33:44,717 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 06:33:44,717 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:33:44,717 - +2026-06-24 06:33:44,717 - ### Initializing object ### +2026-06-24 06:33:44,717 - Loading object from source = 'simu' +2026-06-24 06:33:44,717 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:33:44,719 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:33:44,719 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 199, 199) +2026-06-24 06:33:44,719 - object extent (Z, Y, X) (Ang) = [20. 39.8 39.8] +2026-06-24 06:33:44,719 - +2026-06-24 06:33:44,719 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:33:44,719 - omode_occu (omode) = float32, (1,) +2026-06-24 06:33:44,719 - +2026-06-24 06:33:44,719 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:33:44,719 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:33:44,720 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:33:44,720 - +2026-06-24 06:33:44,720 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:33:44,720 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:33:44,720 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:33:44,720 - +2026-06-24 06:33:44,720 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:33:44,720 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:33:44,720 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:33:44,720 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:33:44,720 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:33:44,720 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (199, 199). +2026-06-24 06:33:44,720 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:33:44,720 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:33:44,720 - +2026-06-24 06:33:44,720 - ### Collecting reconstruction provenance ### +2026-06-24 06:33:44,720 - Reconstruction provenance is collected and initialized. +2026-06-24 06:33:44,721 - +2026-06-24 06:33:44,721 - ### Initializing loss function ### +2026-06-24 06:33:44,721 - Active loss types: +2026-06-24 06:33:44,721 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:33:44,721 - +2026-06-24 06:33:44,721 - ### Initializing constraint function ### +2026-06-24 06:33:44,721 - Active constraint types: +2026-06-24 06:33:44,721 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:33:44,721 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:33:44,721 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:33:44,721 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:33:44,721 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:33:44,721 - +2026-06-24 06:33:44,721 - ### Done initializing PtyRADSolver ### +2026-06-24 06:33:44,721 - +2026-06-24 06:33:44,846 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:33:44,846 - +2026-06-24 06:33:44,846 - ### Initializing PtychoModel model ### +2026-06-24 06:33:44,918 - ### PtychoModel optimizable variables ### +2026-06-24 06:33:44,918 - obja : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:44,918 - objp : torch.Size([1, 1, 199, 199]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:44,918 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:33:44,918 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:33:44,918 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:33:44,918 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:33:44,918 - +2026-06-24 06:33:44,919 - ### Optimizable variables statitsics ### +2026-06-24 06:33:44,919 - Total measurement values : 4,194,304 +2026-06-24 06:33:44,919 - Total optimizing variables: 276,322 +2026-06-24 06:33:44,919 - Overdetermined ratio : 15.18 +2026-06-24 06:33:44,919 - +2026-06-24 06:33:44,919 - ### Model behavior ### +2026-06-24 06:33:44,919 - Tilt propagator : False +2026-06-24 06:33:44,919 - Change slice thickness : False +2026-06-24 06:33:44,919 - Detector blur : False +2026-06-24 06:33:44,919 - Preload data : True +2026-06-24 06:33:44,919 - On-the-fly meas padding : False +2026-06-24 06:33:44,919 - On-the-fly meas resample : False +2026-06-24 06:33:44,919 - On-the-fly simu match mode: None +2026-06-24 06:33:44,919 - +2026-06-24 06:33:44,960 - ### Done initializing PtychoModel model ### +2026-06-24 06:33:44,960 - +2026-06-24 06:33:44,960 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:33:44,960 - +2026-06-24 06:33:44,960 - ### Generating indices, batches, and output_path ### +2026-06-24 06:33:44,962 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:33:44,962 - Selecting indices with the 'full' mode +2026-06-24 06:33:45,421 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:33:45,498 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:33:45,498 - Original recon_dir_affixes = ['default'] +2026-06-24 06:33:45,498 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:33:45,505 - Path corrected for compatibility: +2026-06-24 06:33:45,505 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_phi32_334_C34_7.34e+03_phi34_343_C41_2.54e+05_phi41_167_C43_-2.36e+05_phi43_160_C45_-3.72e+05_phi45_113_C50_4.97e+08_C52_-7e+06_phi52_0.193_C54_1.14e+07_phi54_314_C56_-8.79e+06_phi56_92.5 +2026-06-24 06:33:45,505 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5 +2026-06-24 06:33:45,506 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5' is generated! +2026-06-24 06:33:45,659 - +2026-06-24 06:33:45,660 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/20260624_063345_ptyrad_log.txt ### +2026-06-24 06:33:45,660 - +2026-06-24 06:33:45,661 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:33:45,661 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:33:45,661 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:33:46,845 - Iter: 1, Total Loss: 1.0400, loss_single: 1.0400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 06:33:46,883 - Iter: 2, Total Loss: 0.9675, loss_single: 0.9675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:33:46,919 - Iter: 3, Total Loss: 0.9082, loss_single: 0.9082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:46,954 - Iter: 4, Total Loss: 0.8591, loss_single: 0.8591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:46,989 - Iter: 5, Total Loss: 0.8241, loss_single: 0.8241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,025 - Iter: 6, Total Loss: 0.7886, loss_single: 0.7886, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:33:47,060 - Iter: 7, Total Loss: 0.7538, loss_single: 0.7538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,096 - Iter: 8, Total Loss: 0.7232, loss_single: 0.7232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,131 - Iter: 9, Total Loss: 0.6876, loss_single: 0.6876, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,166 - Iter: 10, Total Loss: 0.6564, loss_single: 0.6564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,201 - Iter: 11, Total Loss: 0.6314, loss_single: 0.6314, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,237 - Iter: 12, Total Loss: 0.6052, loss_single: 0.6052, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,272 - Iter: 13, Total Loss: 0.5698, loss_single: 0.5698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,309 - Iter: 14, Total Loss: 0.5297, loss_single: 0.5297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:33:47,344 - Iter: 15, Total Loss: 0.4916, loss_single: 0.4916, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,380 - Iter: 16, Total Loss: 0.4582, loss_single: 0.4582, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:47,415 - 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Iter: 89, Total Loss: 0.2844, loss_single: 0.2844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:49,988 - Iter: 90, Total Loss: 0.2842, loss_single: 0.2842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,023 - Iter: 91, Total Loss: 0.2840, loss_single: 0.2840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,061 - Iter: 92, Total Loss: 0.2839, loss_single: 0.2839, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:33:50,096 - Iter: 93, Total Loss: 0.2837, loss_single: 0.2837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,131 - Iter: 94, Total Loss: 0.2836, loss_single: 0.2836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,166 - Iter: 95, Total Loss: 0.2834, loss_single: 0.2834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,201 - Iter: 96, Total Loss: 0.2833, loss_single: 0.2833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,237 - Iter: 97, Total Loss: 0.2831, loss_single: 0.2831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,273 - Iter: 98, Total Loss: 0.2830, loss_single: 0.2830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,308 - Iter: 99, Total Loss: 0.2828, loss_single: 0.2828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,344 - Iter: 100, Total Loss: 0.2827, loss_single: 0.2827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:33:50,456 - Saving summary figures for iter 100 +2026-06-24 06:33:54,165 - ### Finished 100 iterations, averaged iter_t = 0.038865 with std = 0.040 ### +2026-06-24 06:33:54,166 - +2026-06-24 06:33:54,166 - ### The PtyRADSolver is finished in 9.320 sec ### +2026-06-24 06:33:54,166 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..02b0303521b729653b7aee998c0563162af2cebe Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/simulation_data_aug1__sample_000006.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/simulation_data_aug1__sample_000006.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e9e5baa0a25edd6b66fb56ce9c2c81d4b428e4b8 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006/c30_small__simulation_data_aug1__sample_000006_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_40.9_phi12_100_C21_781_phi21_343_C23_-20.8_phi23_188_C30_-5.94e+04_C32_-9.43e+03_ph.5/simulation_data_aug1__sample_000006.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 12.336362838745117 + probe_aberrations: + C10: -442.14544677734375 + C12: 40.87379837036133 + C21: 781.125244140625 + C23: -20.786285400390625 + C30: -59405.9765625 + C32: -9429.708984375 + C34: 7343.97705078125 + C41: 253643.15625 + C43: -236337.515625 + C45: -371914.28125 + C50: 496905056.0 + C52: -6997994.0 + C54: 11449285.0 + C56: -8793493.0 + phi12: 100.17977108497853 + phi21: 342.9965272867327 + phi23: 187.7945212671265 + phi32: 333.7812087377948 + phi34: 342.5439862730844 + phi41: 166.58376495062376 + phi43: 159.92631126472065 + phi45: 112.76429900807864 + phi52: 0.19268409211727608 + phi54: 313.6747710666781 + phi56: 92.48877317386908 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4910949170589447 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000006_measurement.h5 + key: measurement + random_seed: 20262086 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000006 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug1__sample_000006 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259/20260624_063444_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259/20260624_063444_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..bd6b2b28dbfc2907eacbaf359bcef5f38f00476e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259/20260624_063444_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:34:43,183 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:34:43,183 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:34:43,183 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:34:43,183 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:34:43,183 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:34:43,184 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:34:43,184 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:34:43,184 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:34:43,184 - +2026-06-24 06:34:43,289 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:34:43,289 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:34:43,289 - Accelerator.num_process = 1 +2026-06-24 06:34:43,289 - Accelerator.mixed_precision = no +2026-06-24 06:34:43,312 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:34:43,312 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:34:43,312 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:34:43,312 - +2026-06-24 06:34:43,312 - ### System information ### +2026-06-24 06:34:43,312 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:34:43,312 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:34:43,313 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:34:43,313 - Machine: x86_64 +2026-06-24 06:34:43,313 - Processor: x86_64 +2026-06-24 06:34:43,313 - Available CPU cores: 8 +2026-06-24 06:34:43,313 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:34:43,313 - +2026-06-24 06:34:43,313 - ### GPU information ### +2026-06-24 06:34:43,313 - CUDA Available: True +2026-06-24 06:34:43,313 - CUDA Version: 13.0 +2026-06-24 06:34:43,313 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:34:43,313 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:34:43,313 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:34:43,313 - In addition, Triton does not directly support Windows. +2026-06-24 06:34:43,313 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:34:43,341 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:34:43,341 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:34:43,341 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:34:43,341 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:34:43,341 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:34:43,341 - +2026-06-24 06:34:43,341 - ### Python information ### +2026-06-24 06:34:43,343 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:34:43,343 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:34:43,343 - +2026-06-24 06:34:43,343 - ### Packages information ### +2026-06-24 06:34:43,344 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:34:43,345 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:34:43,345 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:34:43,346 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:34:43,347 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:34:43,347 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:34:43,347 - +2026-06-24 06:34:43,347 - ### Loading params file ### +2026-06-24 06:34:43,347 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000010.yaml +2026-06-24 06:34:43,353 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:34:43,354 - Success! Params file validated and defaults applied. +2026-06-24 06:34:43,354 - +2026-06-24 06:34:43,354 - ### Setting GPU Device ### +2026-06-24 06:34:43,355 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:34:43,355 - +2026-06-24 06:34:43,355 - Random seed: 20262090 provided by params file +2026-06-24 06:34:43,355 - ### Initializing Initializer ### +2026-06-24 06:34:43,355 - init_params are displayed below: +2026-06-24 06:34:43,355 - random_seed: 20262090 +2026-06-24 06:34:43,355 - probe_illum_type: electron +2026-06-24 06:34:43,355 - probe_kv: 80.0 +2026-06-24 06:34:43,355 - probe_conv_angle: 12.468847274780273 +2026-06-24 06:34:43,355 - probe_aberrations: {'C10': -163.488, 'C12': 20.364, 'phi12': 116.661, 'C21': 445.474, 'phi21': 272.13, 'C23': -194.24, 'phi23': 125.76, 'C30': 4334961.0, 'C32': -7050.403, 'phi32': 53.932, 'C34': -11483.338, 'phi34': 173.458, 'C41': -473989.469, 'phi41': 39.813, 'C43': -185213.828, 'phi43': 61.472, 'C45': -193005.484, 'phi45': 199.641, 'C50': 344949696.0, 'C52': 294822.375, 'phi52': 137.806, 'C54': -1091407.125, 'phi54': 41.109, 'C56': 16090397.0, 'phi56': 258.665} +2026-06-24 06:34:43,355 - beam_kev: None +2026-06-24 06:34:43,355 - probe_dRn: None +2026-06-24 06:34:43,355 - probe_Rn: None +2026-06-24 06:34:43,355 - probe_D_H: None +2026-06-24 06:34:43,355 - probe_D_FZP: None +2026-06-24 06:34:43,355 - probe_Ls: None +2026-06-24 06:34:43,355 - meas_Npix: 128 +2026-06-24 06:34:43,355 - pos_N_scans: 256 +2026-06-24 06:34:43,356 - pos_N_scan_slow: 16 +2026-06-24 06:34:43,356 - pos_N_scan_fast: 16 +2026-06-24 06:34:43,356 - pos_scan_step_size: 0.3574179708957672 +2026-06-24 06:34:43,356 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:34:43,356 - probe_pmode_max: 6 +2026-06-24 06:34:43,356 - probe_pmode_init_pows: [0.02] +2026-06-24 06:34:43,356 - obj_omode_max: 1 +2026-06-24 06:34:43,356 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:34:43,356 - obj_Nlayer: 1 +2026-06-24 06:34:43,356 - obj_slice_thickness: 20.0 +2026-06-24 06:34:43,356 - simu_Npix: None +2026-06-24 06:34:43,356 - simu_match_mode: None +2026-06-24 06:34:43,356 - meas_permute: None +2026-06-24 06:34:43,356 - meas_reshape: [256, 128, 128] +2026-06-24 06:34:43,356 - meas_flipT: [0, 0, 0] +2026-06-24 06:34:43,356 - meas_crop: None +2026-06-24 06:34:43,356 - meas_pad: None +2026-06-24 06:34:43,356 - meas_resample: None +2026-06-24 06:34:43,356 - meas_add_source_size: None +2026-06-24 06:34:43,356 - meas_add_detector_blur: None +2026-06-24 06:34:43,356 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:34:43,356 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:34:43,356 - meas_add_poisson_noise: None +2026-06-24 06:34:43,356 - meas_export: None +2026-06-24 06:34:43,356 - probe_permute: None +2026-06-24 06:34:43,356 - probe_z_shift: None +2026-06-24 06:34:43,356 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:34:43,356 - pos_scan_flipT: None +2026-06-24 06:34:43,356 - pos_scan_affine: None +2026-06-24 06:34:43,356 - pos_scan_rand_std: 0.15 +2026-06-24 06:34:43,356 - obj_z_crop: None +2026-06-24 06:34:43,356 - obj_z_pad: None +2026-06-24 06:34:43,356 - obj_z_resample: None +2026-06-24 06:34:43,356 - meas_source: file +2026-06-24 06:34:43,356 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000010_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:34:43,356 - probe_source: simu +2026-06-24 06:34:43,356 - probe_params: None +2026-06-24 06:34:43,356 - pos_source: simu +2026-06-24 06:34:43,357 - pos_params: None +2026-06-24 06:34:43,357 - obj_source: simu +2026-06-24 06:34:43,357 - obj_params: None +2026-06-24 06:34:43,357 - tilt_source: simu +2026-06-24 06:34:43,357 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:34:43,357 - +2026-06-24 06:34:43,357 - ### Initializing cache ### +2026-06-24 06:34:43,357 - use_cached_obj = False +2026-06-24 06:34:43,357 - use_cached_probe = False +2026-06-24 06:34:43,357 - use_cached_pos = False +2026-06-24 06:34:43,357 - +2026-06-24 06:34:43,357 - ### Initializing measurements ### +2026-06-24 06:34:43,357 - Loading measurements from source = 'file' +2026-06-24 06:34:43,357 - Detected measurement file type = '.h5' +2026-06-24 06:34:43,434 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:34:43,434 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:34:43,435 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0068) +2026-06-24 06:34:43,435 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:34:43,435 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:34:43,437 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:34:43,437 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:34:43,438 - Normalizing by max of the 2D mean pattern intensity: 0.0053279041 +2026-06-24 06:34:43,438 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:34:43,440 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0114, 1.2856) +2026-06-24 06:34:43,440 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:34:43,441 - Pattern total int. statistics (min, mean, max) = (186.1251, 187.5645, 188.5991), with min/max = 98.7% +2026-06-24 06:34:43,443 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0114, 1.2856) +2026-06-24 06:34:43,443 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:34:43,443 - +2026-06-24 06:34:43,443 - ### Setting up calibration ### +2026-06-24 06:34:43,443 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:34:43,443 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:34:43,443 - Radius of fitted bright field disk (RBF) = 7.51 px with meas_Npix = 128 +2026-06-24 06:34:43,443 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1173 +2026-06-24 06:34:43,443 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:34:43,443 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:34:43,675 - Initial guess: center=(63.64, 63.64), radius=7.51, Gaussian blur std=0.50 +2026-06-24 06:34:43,685 - Final fit: center=(63.64, 63.64), radius=7.51, Gaussian blur std=0.56 +2026-06-24 06:34:43,685 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 7.64 px with Npix = 128 +2026-06-24 06:34:43,685 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:34:43,685 - +2026-06-24 06:34:43,685 - ### Setting init_variables dict ### +2026-06-24 06:34:43,685 - Derived values given input init_params: +2026-06-24 06:34:43,685 - kv = 80.0 kV +2026-06-24 06:34:43,685 - wavelength = 0.0418 Ang +2026-06-24 06:34:43,685 - conv_angle = 12.468847274780273 mrad +2026-06-24 06:34:43,685 - Npix = 128 px +2026-06-24 06:34:43,685 - dk = 0.0391 Ang^-1 +2026-06-24 06:34:43,685 - kMax = 2.5000 Ang^-1 +2026-06-24 06:34:43,685 - da = 1.6311 mrad +2026-06-24 06:34:43,685 - angleMax = 104.3929 mrad +2026-06-24 06:34:43,685 - RBF = 7.6443 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:34:43,685 - n_alpha = 8.3723 (# conv_angle) +2026-06-24 06:34:43,685 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:34:43,685 - Rayleigh-limited resolution = 2.0428 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:34:43,686 - Real space probe extent = 25.6000 Ang +2026-06-24 06:34:43,686 - +2026-06-24 06:34:43,686 - ### Initializing probe ### +2026-06-24 06:34:43,686 - Loading probe from source = 'simu' +2026-06-24 06:34:43,686 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:34:43,686 - Start simulating STEM probe +2026-06-24 06:34:43,686 - kv = 80.0 kV +2026-06-24 06:34:43,686 - wavelength = 0.0418 Ang +2026-06-24 06:34:43,686 - conv_angle = 12.468847274780273 mrad +2026-06-24 06:34:43,686 - Npix = 128 px +2026-06-24 06:34:43,686 - dk = 0.0391 Ang^-1 +2026-06-24 06:34:43,686 - kMax = 2.5000 Ang^-1 +2026-06-24 06:34:43,686 - alpha_max = 104.3929 mrad +2026-06-24 06:34:43,686 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:34:43,686 - Rayleigh-limited resolution = 2.0428 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:34:43,686 - Real space probe extent = 25.6000 Ang +2026-06-24 06:34:43,686 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:34:43,686 - ------------------------------------------------------------------------------------ +2026-06-24 06:34:43,686 - C1,0 C1 -163.4880 - Defocus (C10 = -df) +2026-06-24 06:34:43,686 - C1,2 A1 20.3640 116.66 2-fold astigmatism +2026-06-24 06:34:43,686 - C2,1 3*B2 445.4740 272.13 Axial coma +2026-06-24 06:34:43,686 - C2,3 A2 -194.2400 125.76 3-fold astigmatism +2026-06-24 06:34:43,686 - C3,0 C3 4334961.0000 - Spherical aberration +2026-06-24 06:34:43,686 - C3,2 4*S3 -7050.4030 53.93 Axial star aberration +2026-06-24 06:34:43,686 - C3,4 A3 -11483.3380 173.46 4-fold astigmatism +2026-06-24 06:34:43,687 - C4,1 4*B4 -473989.4690 39.81 Axial coma(4th) +2026-06-24 06:34:43,687 - C4,3 4*D4 -185213.8280 61.47 3-lobe aberration +2026-06-24 06:34:43,687 - C4,5 A4 -193005.4840 199.64 5-fold astigmatism +2026-06-24 06:34:43,687 - C5,0 C5 344949696.0000 - Spherical aberration (5th) +2026-06-24 06:34:43,687 - C5,2 6*S5 294822.3750 137.81 Axial star aberration(5th) +2026-06-24 06:34:43,687 - C5,4 6*R5 -1091407.1250 41.11 4-lobe aberration +2026-06-24 06:34:43,687 - C5,6 A5 16090397.0000 258.67 6-fold astigmatism +2026-06-24 06:34:43,690 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:34:43,690 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:34:43,690 - Creating 5 new probe modes from the major mode +2026-06-24 06:34:43,690 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:34:43,793 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:34:43,794 - Orthogonalizing 6 pmodes +2026-06-24 06:34:43,797 - Sorting 6 pmodes by their intensities +2026-06-24 06:34:43,797 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:34:43,798 - sum(|probe_data|**2) = 187.56, while meas_total_ints (min, mean, max) = (186.1251, 187.5645, 188.5991) +2026-06-24 06:34:43,798 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:34:43,798 - +2026-06-24 06:34:43,798 - ### Initializing probe positions ### +2026-06-24 06:34:43,798 - Loading probe positions from source = 'simu' +2026-06-24 06:34:43,798 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:34:43,798 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3574, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:34:43,799 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:34:43,801 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:34:43,801 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 43]) +2026-06-24 06:34:43,801 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:34:43,801 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:34:43,801 - +2026-06-24 06:34:43,801 - ### Initializing object ### +2026-06-24 06:34:43,801 - Loading object from source = 'simu' +2026-06-24 06:34:43,801 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:34:43,802 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:34:43,802 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 187) +2026-06-24 06:34:43,802 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.4] +2026-06-24 06:34:43,803 - +2026-06-24 06:34:43,803 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:34:43,803 - omode_occu (omode) = float32, (1,) +2026-06-24 06:34:43,803 - +2026-06-24 06:34:43,803 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:34:43,803 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:34:43,803 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:34:43,803 - +2026-06-24 06:34:43,803 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:34:43,803 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:34:43,804 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:34:43,804 - +2026-06-24 06:34:43,804 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:34:43,804 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:34:43,804 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:34:43,804 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:34:43,804 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:34:43,804 - crop positions (yx_min=[15 15], yx_max=[171 171]) are well contained inside object canvas (Ny,Nx) = (187, 187). +2026-06-24 06:34:43,804 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:34:43,804 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:34:43,804 - +2026-06-24 06:34:43,804 - ### Collecting reconstruction provenance ### +2026-06-24 06:34:43,804 - Reconstruction provenance is collected and initialized. +2026-06-24 06:34:43,804 - +2026-06-24 06:34:43,804 - ### Initializing loss function ### +2026-06-24 06:34:43,804 - Active loss types: +2026-06-24 06:34:43,804 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:34:43,804 - +2026-06-24 06:34:43,804 - ### Initializing constraint function ### +2026-06-24 06:34:43,804 - Active constraint types: +2026-06-24 06:34:43,805 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:34:43,805 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:34:43,805 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:34:43,805 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:34:43,805 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:34:43,805 - +2026-06-24 06:34:43,805 - ### Done initializing PtyRADSolver ### +2026-06-24 06:34:43,805 - +2026-06-24 06:34:43,929 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:34:43,929 - +2026-06-24 06:34:43,929 - ### Initializing PtychoModel model ### +2026-06-24 06:34:44,001 - ### PtychoModel optimizable variables ### +2026-06-24 06:34:44,001 - obja : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:34:44,001 - objp : torch.Size([1, 1, 187, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:34:44,001 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:34:44,001 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:34:44,001 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:34:44,001 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:34:44,001 - +2026-06-24 06:34:44,001 - ### Optimizable variables statitsics ### +2026-06-24 06:34:44,001 - Total measurement values : 4,194,304 +2026-06-24 06:34:44,001 - Total optimizing variables: 267,058 +2026-06-24 06:34:44,001 - Overdetermined ratio : 15.71 +2026-06-24 06:34:44,002 - +2026-06-24 06:34:44,002 - ### Model behavior ### +2026-06-24 06:34:44,002 - Tilt propagator : False +2026-06-24 06:34:44,002 - Change slice thickness : False +2026-06-24 06:34:44,002 - Detector blur : False +2026-06-24 06:34:44,002 - Preload data : True +2026-06-24 06:34:44,002 - On-the-fly meas padding : False +2026-06-24 06:34:44,002 - On-the-fly meas resample : False +2026-06-24 06:34:44,002 - On-the-fly simu match mode: None +2026-06-24 06:34:44,002 - +2026-06-24 06:34:44,043 - ### Done initializing PtychoModel model ### +2026-06-24 06:34:44,043 - +2026-06-24 06:34:44,043 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:34:44,044 - +2026-06-24 06:34:44,044 - ### Generating indices, batches, and output_path ### +2026-06-24 06:34:44,045 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:34:44,045 - Selecting indices with the 'full' mode +2026-06-24 06:34:44,505 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:34:44,579 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:34:44,579 - Original recon_dir_affixes = ['default'] +2026-06-24 06:34:44,579 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:34:44,585 - Path corrected for compatibility: +2026-06-24 06:34:44,585 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32_-7.05e+03_phi32_53.9_C34_-1.15e+04_phi34_173_C41_-4.74e+05_phi41_39.8_C43_-1.85e+05_phi43_61.5_C45_-1.93e+05_phi45_200_C50_3.45e+08_C52_2.95e+05_phi52_138_C54_-1.09e+06_phi54_41.1_C56_1.61e+07_phi56_259 +2026-06-24 06:34:44,585 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259 +2026-06-24 06:34:44,586 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259' is generated! +2026-06-24 06:34:44,728 - +2026-06-24 06:34:44,729 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259/20260624_063444_ptyrad_log.txt ### +2026-06-24 06:34:44,729 - +2026-06-24 06:34:44,731 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:34:44,731 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:34:44,731 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:34:45,911 - Iter: 1, Total Loss: 1.1668, loss_single: 1.1668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:34:45,948 - Iter: 2, Total Loss: 1.0939, loss_single: 1.0939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:34:45,983 - Iter: 3, Total Loss: 1.0402, loss_single: 1.0402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,018 - Iter: 4, Total Loss: 0.9918, loss_single: 0.9918, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,054 - Iter: 5, Total Loss: 0.9421, loss_single: 0.9421, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,089 - Iter: 6, Total Loss: 0.8903, loss_single: 0.8903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,124 - Iter: 7, Total Loss: 0.8451, loss_single: 0.8451, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,159 - Iter: 8, Total Loss: 0.8105, loss_single: 0.8105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,193 - Iter: 9, Total Loss: 0.7718, loss_single: 0.7718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,229 - Iter: 10, Total Loss: 0.7382, loss_single: 0.7382, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,264 - Iter: 11, Total Loss: 0.7127, loss_single: 0.7127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,299 - Iter: 12, Total Loss: 0.6798, loss_single: 0.6798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,334 - Iter: 13, Total Loss: 0.6461, loss_single: 0.6461, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,369 - Iter: 14, Total Loss: 0.6144, loss_single: 0.6144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,405 - Iter: 15, Total Loss: 0.5836, loss_single: 0.5836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:34:46,440 - Iter: 16, Total Loss: 0.5531, loss_single: 0.5531, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,475 - Iter: 17, Total Loss: 0.5245, loss_single: 0.5245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,510 - Iter: 18, Total Loss: 0.5019, loss_single: 0.5019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,545 - Iter: 19, Total Loss: 0.4857, loss_single: 0.4857, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,580 - Iter: 20, Total Loss: 0.4729, loss_single: 0.4729, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,615 - Iter: 21, Total Loss: 0.4620, loss_single: 0.4620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,650 - Iter: 22, Total Loss: 0.4545, loss_single: 0.4545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,686 - Iter: 23, Total Loss: 0.4473, loss_single: 0.4473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,721 - Iter: 24, Total Loss: 0.4404, loss_single: 0.4404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:46,756 - Iter: 25, Total Loss: 0.4365, loss_single: 0.4365, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,791 - Iter: 26, Total Loss: 0.4341, loss_single: 0.4341, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,826 - Iter: 27, Total Loss: 0.4317, loss_single: 0.4317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,861 - Iter: 28, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,896 - Iter: 29, Total Loss: 0.4265, loss_single: 0.4265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,931 - Iter: 30, Total Loss: 0.4253, loss_single: 0.4253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:46,966 - Iter: 31, Total Loss: 0.4244, loss_single: 0.4244, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,001 - Iter: 32, Total Loss: 0.4235, loss_single: 0.4235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,036 - Iter: 33, Total Loss: 0.4228, loss_single: 0.4228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,072 - Iter: 34, Total Loss: 0.4220, loss_single: 0.4220, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,106 - Iter: 35, Total Loss: 0.4214, loss_single: 0.4214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,141 - Iter: 36, Total Loss: 0.4210, loss_single: 0.4210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,176 - Iter: 37, Total Loss: 0.4205, loss_single: 0.4205, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,211 - Iter: 38, Total Loss: 0.4200, loss_single: 0.4200, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,246 - Iter: 39, Total Loss: 0.4196, loss_single: 0.4196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,282 - Iter: 40, Total Loss: 0.4193, loss_single: 0.4193, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,320 - Iter: 41, Total Loss: 0.4190, loss_single: 0.4190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,355 - Iter: 42, Total Loss: 0.4187, loss_single: 0.4187, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,390 - Iter: 43, Total Loss: 0.4185, loss_single: 0.4185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,425 - Iter: 44, Total Loss: 0.4182, loss_single: 0.4182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,460 - Iter: 45, Total Loss: 0.4180, loss_single: 0.4180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,495 - Iter: 46, Total Loss: 0.4178, loss_single: 0.4178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,530 - Iter: 47, Total Loss: 0.4176, loss_single: 0.4176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,565 - Iter: 48, Total Loss: 0.4175, loss_single: 0.4175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,600 - Iter: 49, Total Loss: 0.4173, loss_single: 0.4173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,635 - Iter: 50, Total Loss: 0.4171, loss_single: 0.4171, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,671 - Iter: 51, Total Loss: 0.4170, loss_single: 0.4170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,706 - Iter: 52, Total Loss: 0.4168, loss_single: 0.4168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,741 - Iter: 53, Total Loss: 0.4167, loss_single: 0.4167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,776 - Iter: 54, Total Loss: 0.4165, loss_single: 0.4165, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,811 - Iter: 55, Total Loss: 0.4164, loss_single: 0.4164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,845 - Iter: 56, Total Loss: 0.4162, loss_single: 0.4162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,881 - Iter: 57, Total Loss: 0.4161, loss_single: 0.4161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,916 - Iter: 58, Total Loss: 0.4160, loss_single: 0.4160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:47,951 - Iter: 59, Total Loss: 0.4158, loss_single: 0.4158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:47,986 - Iter: 60, Total Loss: 0.4158, loss_single: 0.4158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,021 - Iter: 61, Total Loss: 0.4156, loss_single: 0.4156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,057 - Iter: 62, Total Loss: 0.4155, loss_single: 0.4155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,092 - Iter: 63, Total Loss: 0.4154, loss_single: 0.4154, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,127 - Iter: 64, 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in 0.035 sec +2026-06-24 06:34:48,338 - Iter: 70, Total Loss: 0.4146, loss_single: 0.4146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,373 - Iter: 71, Total Loss: 0.4145, loss_single: 0.4145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,408 - Iter: 72, Total Loss: 0.4144, loss_single: 0.4144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,443 - Iter: 73, Total Loss: 0.4143, loss_single: 0.4143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,478 - Iter: 74, Total Loss: 0.4141, loss_single: 0.4141, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,513 - Iter: 75, Total Loss: 0.4141, loss_single: 0.4141, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:48,760 - Iter: 82, Total Loss: 0.4131, loss_single: 0.4131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,795 - Iter: 83, Total Loss: 0.4130, loss_single: 0.4130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:48,829 - Iter: 84, Total Loss: 0.4129, loss_single: 0.4129, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:48,865 - Iter: 85, Total Loss: 0.4127, loss_single: 0.4127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,900 - Iter: 86, Total Loss: 0.4127, loss_single: 0.4127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:48,935 - Iter: 87, Total Loss: 0.4126, loss_single: 0.4126, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:48,970 - Iter: 88, Total Loss: 0.4125, loss_single: 0.4125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,005 - Iter: 89, Total Loss: 0.4124, loss_single: 0.4124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,060 - Iter: 90, Total Loss: 0.4122, loss_single: 0.4122, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,100 - Iter: 91, Total Loss: 0.4121, loss_single: 0.4121, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,137 - Iter: 92, Total Loss: 0.4120, loss_single: 0.4120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:34:49,173 - Iter: 93, Total Loss: 0.4119, loss_single: 0.4119, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,208 - Iter: 94, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,243 - Iter: 95, Total Loss: 0.4117, loss_single: 0.4117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:49,278 - Iter: 96, Total Loss: 0.4116, loss_single: 0.4116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,314 - Iter: 97, Total Loss: 0.4115, loss_single: 0.4115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,348 - Iter: 98, Total Loss: 0.4114, loss_single: 0.4114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:34:49,383 - Iter: 99, Total Loss: 0.4113, loss_single: 0.4113, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,419 - Iter: 100, Total Loss: 0.4112, loss_single: 0.4112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:34:49,528 - Saving summary figures for iter 100 +2026-06-24 06:34:53,070 - ### Finished 100 iterations, averaged iter_t = 0.038747 with std = 0.040 ### +2026-06-24 06:34:53,070 - +2026-06-24 06:34:53,070 - ### The PtyRADSolver is finished in 9.141 sec ### +2026-06-24 06:34:53,070 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000010/c30_small__simulation_data_aug1__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-163_C12_20.4_phi12_117_C21_445_phi21_272_C23_-194_phi23_126_C30_4.33e+06_C32.61e+07_phi56_259/simulation_data_aug1__sample_000010.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 12.468847274780273 + probe_aberrations: + C10: -163.487548828125 + C12: 20.36390495300293 + C21: 445.4737854003906 + C23: -194.24020385742188 + C30: 4334961.0 + C32: -7050.4033203125 + C34: -11483.337890625 + C41: -473989.46875 + C43: -185213.828125 + C45: -193005.484375 + C50: 344949696.0 + C52: 294822.375 + C54: -1091407.125 + C56: 16090397.0 + phi12: 116.66053260878823 + phi21: 272.1303913268857 + phi23: 125.7604209607529 + phi32: 53.93231091291749 + phi34: 173.4581181238098 + phi41: 39.8127696908433 + phi43: 61.47236505846425 + phi45: 199.6408013635966 + phi52: 137.80621088287907 + phi54: 41.10944695382437 + phi56: 258.6654656801492 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3574179708957672 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000010_measurement.h5 + key: measurement + random_seed: 20262090 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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+++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000012/c30_small__simulation_data_aug1__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-133_C12_-38.8_phi12_334_C21_694_phi21_302_C23_96.7_phi23_332_C30_4.51e+06_C32_-8.79e+03_phi.8/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7ddec6f98f264b5935c4c103689dfdd2451a32601bc6ad34ccdfca1c4a5a07ba +size 48043 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/20260624_063558_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/20260624_063558_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf5d8d03baa5d18965072d85acbb2128009a4fc7 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/20260624_063558_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:35:57,155 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:35:57,155 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:35:57,155 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:35:57,155 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:35:57,155 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:35:57,155 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:35:57,155 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:35:57,155 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:35:57,155 - +2026-06-24 06:35:57,262 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:35:57,262 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:35:57,262 - Accelerator.num_process = 1 +2026-06-24 06:35:57,262 - Accelerator.mixed_precision = no +2026-06-24 06:35:57,284 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:35:57,284 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:35:57,284 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:35:57,284 - +2026-06-24 06:35:57,284 - ### System information ### +2026-06-24 06:35:57,284 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:35:57,284 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:35:57,284 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:35:57,284 - Machine: x86_64 +2026-06-24 06:35:57,284 - Processor: x86_64 +2026-06-24 06:35:57,284 - Available CPU cores: 8 +2026-06-24 06:35:57,284 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:35:57,284 - +2026-06-24 06:35:57,284 - ### GPU information ### +2026-06-24 06:35:57,284 - CUDA Available: True +2026-06-24 06:35:57,284 - CUDA Version: 13.0 +2026-06-24 06:35:57,285 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:35:57,285 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:35:57,285 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:35:57,285 - In addition, Triton does not directly support Windows. +2026-06-24 06:35:57,285 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:35:57,325 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:35:57,325 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:35:57,325 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:35:57,325 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:35:57,325 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:35:57,325 - +2026-06-24 06:35:57,325 - ### Python information ### +2026-06-24 06:35:57,327 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:35:57,327 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:35:57,327 - +2026-06-24 06:35:57,327 - ### Packages information ### +2026-06-24 06:35:57,328 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:35:57,329 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:35:57,329 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:35:57,330 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:35:57,331 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:35:57,331 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:35:57,331 - +2026-06-24 06:35:57,331 - ### Loading params file ### +2026-06-24 06:35:57,331 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000015.yaml +2026-06-24 06:35:57,337 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:35:57,338 - Success! Params file validated and defaults applied. +2026-06-24 06:35:57,338 - +2026-06-24 06:35:57,338 - ### Setting GPU Device ### +2026-06-24 06:35:57,338 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:35:57,338 - +2026-06-24 06:35:57,338 - Random seed: 20262095 provided by params file +2026-06-24 06:35:57,339 - ### Initializing Initializer ### +2026-06-24 06:35:57,339 - init_params are displayed below: +2026-06-24 06:35:57,339 - random_seed: 20262095 +2026-06-24 06:35:57,339 - probe_illum_type: electron +2026-06-24 06:35:57,339 - probe_kv: 160.0 +2026-06-24 06:35:57,339 - probe_conv_angle: 13.374269485473633 +2026-06-24 06:35:57,339 - probe_aberrations: {'C10': -311.127, 'C12': -46.545, 'phi12': 110.979, 'C21': -981.787, 'phi21': 154.75, 'C23': 979.6, 'phi23': 280.477, 'C30': 3882130.0, 'C32': 2581.314, 'phi32': 28.398, 'C34': -9883.256, 'phi34': 54.793, 'C41': -340690.031, 'phi41': 191.276, 'C43': -85027.797, 'phi43': 120.893, 'C45': 436375.125, 'phi45': 219.602, 'C50': 287229152.0, 'C52': 8370089.0, 'phi52': 130.717, 'C54': -18177058.0, 'phi54': 163.199, 'C56': -391933.5, 'phi56': 264.613} +2026-06-24 06:35:57,339 - beam_kev: None +2026-06-24 06:35:57,339 - probe_dRn: None +2026-06-24 06:35:57,339 - probe_Rn: None +2026-06-24 06:35:57,339 - probe_D_H: None +2026-06-24 06:35:57,339 - probe_D_FZP: None +2026-06-24 06:35:57,339 - probe_Ls: None +2026-06-24 06:35:57,339 - meas_Npix: 128 +2026-06-24 06:35:57,339 - pos_N_scans: 256 +2026-06-24 06:35:57,339 - pos_N_scan_slow: 16 +2026-06-24 06:35:57,339 - pos_N_scan_fast: 16 +2026-06-24 06:35:57,339 - pos_scan_step_size: 0.302851140499115 +2026-06-24 06:35:57,339 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:35:57,339 - probe_pmode_max: 6 +2026-06-24 06:35:57,339 - probe_pmode_init_pows: [0.02] +2026-06-24 06:35:57,339 - obj_omode_max: 1 +2026-06-24 06:35:57,339 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:35:57,339 - obj_Nlayer: 1 +2026-06-24 06:35:57,339 - obj_slice_thickness: 20.0 +2026-06-24 06:35:57,339 - simu_Npix: None +2026-06-24 06:35:57,339 - simu_match_mode: None +2026-06-24 06:35:57,339 - meas_permute: None +2026-06-24 06:35:57,339 - meas_reshape: [256, 128, 128] +2026-06-24 06:35:57,339 - meas_flipT: [0, 0, 0] +2026-06-24 06:35:57,340 - meas_crop: None +2026-06-24 06:35:57,340 - meas_pad: None +2026-06-24 06:35:57,340 - meas_resample: None +2026-06-24 06:35:57,340 - meas_add_source_size: None +2026-06-24 06:35:57,340 - meas_add_detector_blur: None +2026-06-24 06:35:57,340 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:35:57,340 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:35:57,340 - meas_add_poisson_noise: None +2026-06-24 06:35:57,340 - meas_export: None +2026-06-24 06:35:57,340 - probe_permute: None +2026-06-24 06:35:57,340 - probe_z_shift: None +2026-06-24 06:35:57,340 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:35:57,340 - pos_scan_flipT: None +2026-06-24 06:35:57,340 - pos_scan_affine: None +2026-06-24 06:35:57,340 - pos_scan_rand_std: 0.15 +2026-06-24 06:35:57,340 - obj_z_crop: None +2026-06-24 06:35:57,340 - obj_z_pad: None +2026-06-24 06:35:57,340 - obj_z_resample: None +2026-06-24 06:35:57,340 - meas_source: file +2026-06-24 06:35:57,340 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000015_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:35:57,340 - probe_source: simu +2026-06-24 06:35:57,340 - probe_params: None +2026-06-24 06:35:57,340 - pos_source: simu +2026-06-24 06:35:57,340 - pos_params: None +2026-06-24 06:35:57,340 - obj_source: simu +2026-06-24 06:35:57,340 - obj_params: None +2026-06-24 06:35:57,340 - tilt_source: simu +2026-06-24 06:35:57,340 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:35:57,340 - +2026-06-24 06:35:57,340 - ### Initializing cache ### +2026-06-24 06:35:57,340 - use_cached_obj = False +2026-06-24 06:35:57,340 - use_cached_probe = False +2026-06-24 06:35:57,340 - use_cached_pos = False +2026-06-24 06:35:57,340 - +2026-06-24 06:35:57,340 - ### Initializing measurements ### +2026-06-24 06:35:57,340 - Loading measurements from source = 'file' +2026-06-24 06:35:57,340 - Detected measurement file type = '.h5' +2026-06-24 06:35:57,417 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:35:57,417 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:35:57,418 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0041) +2026-06-24 06:35:57,419 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:35:57,419 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:35:57,420 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:35:57,420 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:35:57,420 - Normalizing by max of the 2D mean pattern intensity: 0.0021641739 +2026-06-24 06:35:57,421 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:35:57,422 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0283, 1.9066) +2026-06-24 06:35:57,423 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:35:57,424 - Pattern total int. statistics (min, mean, max) = (458.2237, 462.8754, 469.0481), with min/max = 97.7% +2026-06-24 06:35:57,425 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0283, 1.9066) +2026-06-24 06:35:57,425 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:35:57,425 - +2026-06-24 06:35:57,425 - ### Setting up calibration ### +2026-06-24 06:35:57,425 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:35:57,425 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:35:57,425 - Radius of fitted bright field disk (RBF) = 11.90 px with meas_Npix = 128 +2026-06-24 06:35:57,425 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1860 +2026-06-24 06:35:57,425 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:35:57,426 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:35:57,649 - Initial guess: center=(63.63, 63.61), radius=11.90, Gaussian blur std=0.50 +2026-06-24 06:35:57,660 - Final fit: center=(63.63, 63.61), radius=11.90, Gaussian blur std=0.58 +2026-06-24 06:35:57,660 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 12.01 px with Npix = 128 +2026-06-24 06:35:57,660 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:35:57,660 - +2026-06-24 06:35:57,660 - ### Setting init_variables dict ### +2026-06-24 06:35:57,660 - Derived values given input init_params: +2026-06-24 06:35:57,660 - kv = 160.0 kV +2026-06-24 06:35:57,660 - wavelength = 0.0285 Ang +2026-06-24 06:35:57,660 - conv_angle = 13.374269485473633 mrad +2026-06-24 06:35:57,660 - Npix = 128 px +2026-06-24 06:35:57,660 - dk = 0.0391 Ang^-1 +2026-06-24 06:35:57,660 - kMax = 2.5000 Ang^-1 +2026-06-24 06:35:57,660 - da = 1.1137 mrad +2026-06-24 06:35:57,660 - angleMax = 71.2751 mrad +2026-06-24 06:35:57,660 - RBF = 12.0091 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:35:57,661 - n_alpha = 5.3293 (# conv_angle) +2026-06-24 06:35:57,661 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:35:57,661 - Rayleigh-limited resolution = 1.3003 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:35:57,661 - Real space probe extent = 25.6000 Ang +2026-06-24 06:35:57,661 - +2026-06-24 06:35:57,661 - ### Initializing probe ### +2026-06-24 06:35:57,661 - Loading probe from source = 'simu' +2026-06-24 06:35:57,661 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:35:57,661 - Start simulating STEM probe +2026-06-24 06:35:57,661 - kv = 160.0 kV +2026-06-24 06:35:57,661 - wavelength = 0.0285 Ang +2026-06-24 06:35:57,661 - conv_angle = 13.374269485473633 mrad +2026-06-24 06:35:57,661 - Npix = 128 px +2026-06-24 06:35:57,661 - dk = 0.0391 Ang^-1 +2026-06-24 06:35:57,661 - kMax = 2.5000 Ang^-1 +2026-06-24 06:35:57,661 - alpha_max = 71.2751 mrad +2026-06-24 06:35:57,661 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:35:57,661 - Rayleigh-limited resolution = 1.3003 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:35:57,661 - Real space probe extent = 25.6000 Ang +2026-06-24 06:35:57,661 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:35:57,661 - ------------------------------------------------------------------------------------ +2026-06-24 06:35:57,661 - C1,0 C1 -311.1270 - Defocus (C10 = -df) +2026-06-24 06:35:57,661 - C1,2 A1 -46.5450 110.98 2-fold astigmatism +2026-06-24 06:35:57,661 - C2,1 3*B2 -981.7870 154.75 Axial coma +2026-06-24 06:35:57,661 - C2,3 A2 979.6000 280.48 3-fold astigmatism +2026-06-24 06:35:57,662 - C3,0 C3 3882130.0000 - Spherical aberration +2026-06-24 06:35:57,662 - C3,2 4*S3 2581.3140 28.40 Axial star aberration +2026-06-24 06:35:57,662 - C3,4 A3 -9883.2560 54.79 4-fold astigmatism +2026-06-24 06:35:57,662 - C4,1 4*B4 -340690.0310 191.28 Axial coma(4th) +2026-06-24 06:35:57,662 - C4,3 4*D4 -85027.7970 120.89 3-lobe aberration +2026-06-24 06:35:57,662 - C4,5 A4 436375.1250 219.60 5-fold astigmatism +2026-06-24 06:35:57,662 - C5,0 C5 287229152.0000 - Spherical aberration (5th) +2026-06-24 06:35:57,662 - C5,2 6*S5 8370089.0000 130.72 Axial star aberration(5th) +2026-06-24 06:35:57,662 - C5,4 6*R5 -18177058.0000 163.20 4-lobe aberration +2026-06-24 06:35:57,662 - C5,6 A5 -391933.5000 264.61 6-fold astigmatism +2026-06-24 06:35:57,665 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:35:57,665 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:35:57,665 - Creating 5 new probe modes from the major mode +2026-06-24 06:35:57,665 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:35:57,856 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:35:57,857 - Orthogonalizing 6 pmodes +2026-06-24 06:35:57,860 - Sorting 6 pmodes by their intensities +2026-06-24 06:35:57,861 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:35:57,862 - sum(|probe_data|**2) = 462.88, while meas_total_ints (min, mean, max) = (458.2237, 462.8754, 469.0481) +2026-06-24 06:35:57,862 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:35:57,862 - +2026-06-24 06:35:57,862 - ### Initializing probe positions ### +2026-06-24 06:35:57,862 - Loading probe positions from source = 'simu' +2026-06-24 06:35:57,862 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:35:57,862 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3029, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:35:57,862 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:35:57,864 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:35:57,864 - crop_pos 1st and last px coords (y,x) = ([15, 14], [37, 37]) +2026-06-24 06:35:57,864 - crop_pos extent (Ang) = [4.8 4.8] +2026-06-24 06:35:57,864 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:35:57,864 - +2026-06-24 06:35:57,864 - ### Initializing object ### +2026-06-24 06:35:57,864 - Loading object from source = 'simu' +2026-06-24 06:35:57,864 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:35:57,866 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:35:57,866 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 182, 182) +2026-06-24 06:35:57,866 - object extent (Z, Y, X) (Ang) = [20. 36.4 36.4] +2026-06-24 06:35:57,866 - +2026-06-24 06:35:57,866 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:35:57,866 - omode_occu (omode) = float32, (1,) +2026-06-24 06:35:57,866 - +2026-06-24 06:35:57,866 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:35:57,866 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:35:57,867 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:35:57,867 - +2026-06-24 06:35:57,867 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:35:57,867 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:35:57,867 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:35:57,867 - +2026-06-24 06:35:57,867 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:35:57,867 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:35:57,867 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:35:57,867 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:35:57,867 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:35:57,867 - crop positions (yx_min=[14 14], yx_max=[166 166]) are well contained inside object canvas (Ny,Nx) = (182, 182). +2026-06-24 06:35:57,867 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:35:57,867 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:35:57,867 - +2026-06-24 06:35:57,867 - ### Collecting reconstruction provenance ### +2026-06-24 06:35:57,868 - Reconstruction provenance is collected and initialized. +2026-06-24 06:35:57,868 - +2026-06-24 06:35:57,868 - ### Initializing loss function ### +2026-06-24 06:35:57,868 - Active loss types: +2026-06-24 06:35:57,868 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:35:57,868 - +2026-06-24 06:35:57,868 - ### Initializing constraint function ### +2026-06-24 06:35:57,868 - Active constraint types: +2026-06-24 06:35:57,868 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:35:57,868 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:35:57,868 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:35:57,868 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:35:57,868 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:35:57,868 - +2026-06-24 06:35:57,868 - ### Done initializing PtyRADSolver ### +2026-06-24 06:35:57,868 - +2026-06-24 06:35:57,998 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:35:57,998 - +2026-06-24 06:35:57,998 - ### Initializing PtychoModel model ### +2026-06-24 06:35:58,069 - ### PtychoModel optimizable variables ### +2026-06-24 06:35:58,069 - obja : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:35:58,069 - objp : torch.Size([1, 1, 182, 182]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:35:58,069 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:35:58,069 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:35:58,069 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:35:58,069 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:35:58,069 - +2026-06-24 06:35:58,069 - ### Optimizable variables statitsics ### +2026-06-24 06:35:58,069 - Total measurement values : 4,194,304 +2026-06-24 06:35:58,069 - Total optimizing variables: 263,368 +2026-06-24 06:35:58,069 - Overdetermined ratio : 15.93 +2026-06-24 06:35:58,069 - +2026-06-24 06:35:58,069 - ### Model behavior ### +2026-06-24 06:35:58,069 - Tilt propagator : False +2026-06-24 06:35:58,070 - Change slice thickness : False +2026-06-24 06:35:58,070 - Detector blur : False +2026-06-24 06:35:58,070 - Preload data : True +2026-06-24 06:35:58,070 - On-the-fly meas padding : False +2026-06-24 06:35:58,070 - On-the-fly meas resample : False +2026-06-24 06:35:58,070 - On-the-fly simu match mode: None +2026-06-24 06:35:58,070 - +2026-06-24 06:35:58,111 - ### Done initializing PtychoModel model ### +2026-06-24 06:35:58,111 - +2026-06-24 06:35:58,111 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:35:58,111 - +2026-06-24 06:35:58,112 - ### Generating indices, batches, and output_path ### +2026-06-24 06:35:58,113 - d90 = 41.000 px or 8.200 Ang +2026-06-24 06:35:58,113 - Selecting indices with the 'full' mode +2026-06-24 06:35:58,567 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:35:58,654 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:35:58,654 - Original recon_dir_affixes = ['default'] +2026-06-24 06:35:58,654 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:35:58,660 - Path corrected for compatibility: +2026-06-24 06:35:58,660 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C32_2.58e+03_phi32_28.4_C34_-9.88e+03_phi34_54.8_C41_-3.41e+05_phi41_191_C43_-8.5e+04_phi43_121_C45_4.36e+05_phi45_220_C50_2.87e+08_C52_8.37e+06_phi52_131_C54_-1.82e+07_phi54_163_C56_-3.92e+05_phi56_265 +2026-06-24 06:35:58,660 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265 +2026-06-24 06:35:58,661 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265' is generated! +2026-06-24 06:35:58,829 - +2026-06-24 06:35:58,830 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/20260624_063558_ptyrad_log.txt ### +2026-06-24 06:35:58,830 - +2026-06-24 06:35:58,831 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:35:58,831 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:35:58,832 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:36:00,016 - Iter: 1, Total Loss: 0.9626, loss_single: 0.9626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:36:00,053 - Iter: 2, Total Loss: 0.9317, loss_single: 0.9317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:36:00,088 - Iter: 3, Total Loss: 0.9086, loss_single: 0.9086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,123 - Iter: 4, Total Loss: 0.8873, loss_single: 0.8873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,158 - Iter: 5, Total Loss: 0.8652, loss_single: 0.8652, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,194 - Iter: 6, Total Loss: 0.8416, loss_single: 0.8416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,229 - Iter: 7, Total Loss: 0.8251, loss_single: 0.8251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,264 - Iter: 8, Total Loss: 0.8112, loss_single: 0.8112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,299 - Iter: 9, Total Loss: 0.7937, loss_single: 0.7937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,334 - Iter: 10, Total Loss: 0.7764, loss_single: 0.7764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,369 - Iter: 11, Total Loss: 0.7594, loss_single: 0.7594, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,404 - Iter: 12, Total Loss: 0.7440, loss_single: 0.7440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,439 - Iter: 13, Total Loss: 0.7295, loss_single: 0.7295, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,474 - Iter: 14, Total Loss: 0.7160, loss_single: 0.7160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,509 - Iter: 15, Total Loss: 0.7031, loss_single: 0.7031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,544 - Iter: 16, Total Loss: 0.6873, loss_single: 0.6873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,579 - Iter: 17, Total Loss: 0.6727, loss_single: 0.6727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,614 - Iter: 18, Total Loss: 0.6626, loss_single: 0.6626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,649 - Iter: 19, Total Loss: 0.6524, loss_single: 0.6524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,685 - Iter: 20, Total Loss: 0.6396, loss_single: 0.6396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,719 - Iter: 21, Total Loss: 0.6301, loss_single: 0.6301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,755 - Iter: 22, Total Loss: 0.6226, loss_single: 0.6226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,790 - Iter: 23, Total Loss: 0.6124, loss_single: 0.6124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,825 - Iter: 24, Total Loss: 0.6024, loss_single: 0.6024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,860 - Iter: 25, Total Loss: 0.5952, loss_single: 0.5952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:00,895 - Iter: 26, Total Loss: 0.5891, loss_single: 0.5891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,930 - Iter: 27, Total Loss: 0.5820, loss_single: 0.5820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:00,965 - Iter: 28, Total Loss: 0.5751, loss_single: 0.5751, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,001 - Iter: 29, Total Loss: 0.5687, loss_single: 0.5687, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,036 - Iter: 30, Total Loss: 0.5626, loss_single: 0.5626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,071 - Iter: 31, Total Loss: 0.5577, loss_single: 0.5577, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,106 - Iter: 32, Total Loss: 0.5537, loss_single: 0.5537, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,141 - Iter: 33, Total Loss: 0.5499, loss_single: 0.5499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,176 - Iter: 34, Total Loss: 0.5469, loss_single: 0.5469, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,211 - Iter: 35, Total Loss: 0.5441, loss_single: 0.5441, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,246 - Iter: 36, Total Loss: 0.5409, loss_single: 0.5409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,281 - Iter: 37, Total Loss: 0.5387, loss_single: 0.5387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,316 - Iter: 38, Total Loss: 0.5370, loss_single: 0.5370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,351 - Iter: 39, Total Loss: 0.5352, loss_single: 0.5352, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,386 - Iter: 40, Total Loss: 0.5337, loss_single: 0.5337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,423 - Iter: 41, Total Loss: 0.5320, loss_single: 0.5320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,458 - Iter: 42, Total Loss: 0.5302, loss_single: 0.5302, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,493 - Iter: 43, Total Loss: 0.5290, loss_single: 0.5290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,528 - Iter: 44, Total Loss: 0.5279, loss_single: 0.5279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,563 - Iter: 45, Total Loss: 0.5267, loss_single: 0.5267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,598 - Iter: 46, Total Loss: 0.5256, loss_single: 0.5256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,632 - Iter: 47, Total Loss: 0.5246, loss_single: 0.5246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,667 - Iter: 48, Total Loss: 0.5236, loss_single: 0.5236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,702 - Iter: 49, Total Loss: 0.5226, loss_single: 0.5226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:01,737 - Iter: 50, Total Loss: 0.5218, loss_single: 0.5218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,772 - Iter: 51, Total Loss: 0.5209, loss_single: 0.5209, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,808 - Iter: 52, Total Loss: 0.5201, loss_single: 0.5201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,843 - Iter: 53, Total Loss: 0.5195, loss_single: 0.5195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,878 - Iter: 54, Total Loss: 0.5189, loss_single: 0.5189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,913 - Iter: 55, Total Loss: 0.5182, loss_single: 0.5182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,948 - Iter: 56, Total Loss: 0.5177, loss_single: 0.5177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:01,983 - Iter: 57, Total Loss: 0.5172, loss_single: 0.5172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:02,018 - Iter: 58, Total Loss: 0.5167, loss_single: 0.5167, loss_poissn: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/simulation_data_aug1__sample_000015.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/simulation_data_aug1__sample_000015.yaml new file mode 100644 index 0000000000000000000000000000000000000000..08d3d3fd3eab03a511a51a9c2afb41f8084da676 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/simulation_data_aug1__sample_000015.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 13.374269485473633 + probe_aberrations: + C10: -311.1267395019531 + C12: -46.545108795166016 + C21: -981.78662109375 + C23: 979.5999145507812 + C30: 3882130.0 + C32: 2581.31396484375 + C34: -9883.255859375 + C41: -340690.03125 + C43: -85027.796875 + C45: 436375.125 + C50: 287229152.0 + C52: 8370089.0 + C54: -18177058.0 + C56: -391933.5 + phi12: 110.97945446473842 + phi21: 154.75042123244165 + phi23: 280.4772103417214 + phi32: 28.397638455541063 + phi34: 54.792832786069056 + phi41: 191.27633313994556 + phi43: 120.89276370533825 + phi45: 219.60194725068885 + phi52: 130.71657014705423 + phi54: 163.19909202818062 + phi56: 264.6132490509097 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.302851140499115 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000015_measurement.h5 + key: measurement + random_seed: 20262095 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug1__sample_000015 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000015/c30_small__simulation_data_aug1__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-311_C12_-46.5_phi12_111_C21_-982_phi21_155_C23_980_phi23_280_C30_3.88e+06_C3.92e+05_phi56_265/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201/20260624_063657_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..a80b0104c1b7177253181b2fe1a790c88aba34dd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201/20260624_063657_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:36:56,094 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:36:56,094 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:36:56,094 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:36:56,094 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:36:56,094 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:36:56,094 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:36:56,094 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:36:56,094 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:36:56,094 - +2026-06-24 06:36:56,204 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:36:56,204 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:36:56,204 - Accelerator.num_process = 1 +2026-06-24 06:36:56,204 - Accelerator.mixed_precision = no +2026-06-24 06:36:56,214 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:36:56,214 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:36:56,214 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:36:56,214 - +2026-06-24 06:36:56,214 - ### System information ### +2026-06-24 06:36:56,215 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:36:56,215 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:36:56,215 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:36:56,215 - Machine: x86_64 +2026-06-24 06:36:56,215 - Processor: x86_64 +2026-06-24 06:36:56,215 - Available CPU cores: 8 +2026-06-24 06:36:56,215 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:36:56,215 - +2026-06-24 06:36:56,215 - ### GPU information ### +2026-06-24 06:36:56,215 - CUDA Available: True +2026-06-24 06:36:56,215 - CUDA Version: 13.0 +2026-06-24 06:36:56,215 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:36:56,215 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:36:56,216 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:36:56,216 - In addition, Triton does not directly support Windows. +2026-06-24 06:36:56,216 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:36:56,243 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:36:56,243 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:36:56,243 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:36:56,243 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:36:56,243 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:36:56,243 - +2026-06-24 06:36:56,243 - ### Python information ### +2026-06-24 06:36:56,245 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:36:56,245 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:36:56,245 - +2026-06-24 06:36:56,245 - ### Packages information ### +2026-06-24 06:36:56,245 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:36:56,246 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:36:56,247 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:36:56,247 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:36:56,248 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:36:56,248 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:36:56,248 - +2026-06-24 06:36:56,248 - ### Loading params file ### +2026-06-24 06:36:56,248 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000019.yaml +2026-06-24 06:36:56,255 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:36:56,256 - Success! Params file validated and defaults applied. +2026-06-24 06:36:56,256 - +2026-06-24 06:36:56,256 - ### Setting GPU Device ### +2026-06-24 06:36:56,256 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:36:56,256 - +2026-06-24 06:36:56,256 - Random seed: 20262099 provided by params file +2026-06-24 06:36:56,256 - ### Initializing Initializer ### +2026-06-24 06:36:56,256 - init_params are displayed below: +2026-06-24 06:36:56,256 - random_seed: 20262099 +2026-06-24 06:36:56,256 - probe_illum_type: electron +2026-06-24 06:36:56,256 - probe_kv: 120.0 +2026-06-24 06:36:56,256 - probe_conv_angle: 15.113967895507812 +2026-06-24 06:36:56,257 - probe_aberrations: {'C10': -122.457, 'C12': -0.499, 'phi12': 236.383, 'C21': -697.526, 'phi21': 250.935, 'C23': -411.262, 'phi23': 142.138, 'C30': -696954.5, 'C32': -4671.842, 'phi32': 225.918, 'C34': 5144.407, 'phi34': 342.445, 'C41': -317353.812, 'phi41': 210.74, 'C43': 183633.172, 'phi43': 75.187, 'C45': 153332.688, 'phi45': 266.449, 'C50': 469479648.0, 'C52': -6252632.5, 'phi52': 305.761, 'C54': 9106887.0, 'phi54': 324.091, 'C56': 5117083.5, 'phi56': 201.452} +2026-06-24 06:36:56,257 - beam_kev: None +2026-06-24 06:36:56,257 - probe_dRn: None +2026-06-24 06:36:56,257 - probe_Rn: None +2026-06-24 06:36:56,257 - probe_D_H: None +2026-06-24 06:36:56,257 - probe_D_FZP: None +2026-06-24 06:36:56,257 - probe_Ls: None +2026-06-24 06:36:56,257 - meas_Npix: 128 +2026-06-24 06:36:56,257 - pos_N_scans: 256 +2026-06-24 06:36:56,257 - pos_N_scan_slow: 16 +2026-06-24 06:36:56,257 - pos_N_scan_fast: 16 +2026-06-24 06:36:56,257 - pos_scan_step_size: 0.486725389957428 +2026-06-24 06:36:56,257 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:36:56,257 - probe_pmode_max: 6 +2026-06-24 06:36:56,257 - probe_pmode_init_pows: [0.02] +2026-06-24 06:36:56,257 - obj_omode_max: 1 +2026-06-24 06:36:56,257 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:36:56,257 - obj_Nlayer: 1 +2026-06-24 06:36:56,257 - obj_slice_thickness: 20.0 +2026-06-24 06:36:56,257 - simu_Npix: None +2026-06-24 06:36:56,257 - simu_match_mode: None +2026-06-24 06:36:56,257 - meas_permute: None +2026-06-24 06:36:56,257 - meas_reshape: [256, 128, 128] +2026-06-24 06:36:56,257 - meas_flipT: [0, 0, 0] +2026-06-24 06:36:56,257 - meas_crop: None +2026-06-24 06:36:56,257 - meas_pad: None +2026-06-24 06:36:56,257 - meas_resample: None +2026-06-24 06:36:56,257 - meas_add_source_size: None +2026-06-24 06:36:56,257 - meas_add_detector_blur: None +2026-06-24 06:36:56,257 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:36:56,257 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:36:56,257 - meas_add_poisson_noise: None +2026-06-24 06:36:56,257 - meas_export: None +2026-06-24 06:36:56,257 - probe_permute: None +2026-06-24 06:36:56,257 - probe_z_shift: None +2026-06-24 06:36:56,257 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:36:56,257 - pos_scan_flipT: None +2026-06-24 06:36:56,258 - pos_scan_affine: None +2026-06-24 06:36:56,258 - pos_scan_rand_std: 0.15 +2026-06-24 06:36:56,258 - obj_z_crop: None +2026-06-24 06:36:56,258 - obj_z_pad: None +2026-06-24 06:36:56,258 - obj_z_resample: None +2026-06-24 06:36:56,258 - meas_source: file +2026-06-24 06:36:56,258 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000019_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:36:56,258 - probe_source: simu +2026-06-24 06:36:56,258 - probe_params: None +2026-06-24 06:36:56,258 - pos_source: simu +2026-06-24 06:36:56,258 - pos_params: None +2026-06-24 06:36:56,258 - obj_source: simu +2026-06-24 06:36:56,258 - obj_params: None +2026-06-24 06:36:56,258 - tilt_source: simu +2026-06-24 06:36:56,258 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:36:56,258 - +2026-06-24 06:36:56,258 - ### Initializing cache ### +2026-06-24 06:36:56,258 - use_cached_obj = False +2026-06-24 06:36:56,258 - use_cached_probe = False +2026-06-24 06:36:56,258 - use_cached_pos = False +2026-06-24 06:36:56,258 - +2026-06-24 06:36:56,258 - ### Initializing measurements ### +2026-06-24 06:36:56,258 - Loading measurements from source = 'file' +2026-06-24 06:36:56,258 - Detected measurement file type = '.h5' +2026-06-24 06:36:56,333 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:36:56,333 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:36:56,335 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0035) +2026-06-24 06:36:56,335 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:36:56,335 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:36:56,336 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:36:56,336 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:36:56,337 - Normalizing by max of the 2D mean pattern intensity: 0.0022712478 +2026-06-24 06:36:56,337 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:36:56,338 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0269, 1.5326) +2026-06-24 06:36:56,339 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:36:56,340 - Pattern total int. statistics (min, mean, max) = (435.8218, 440.4668, 445.7436), with min/max = 97.8% +2026-06-24 06:36:56,342 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0269, 1.5326) +2026-06-24 06:36:56,342 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:36:56,342 - +2026-06-24 06:36:56,342 - ### Setting up calibration ### +2026-06-24 06:36:56,342 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:36:56,342 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:36:56,342 - Radius of fitted bright field disk (RBF) = 11.40 px with meas_Npix = 128 +2026-06-24 06:36:56,342 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1781 +2026-06-24 06:36:56,342 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:36:56,342 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:36:56,564 - Initial guess: center=(63.64, 63.61), radius=11.40, Gaussian blur std=0.50 +2026-06-24 06:36:56,574 - Final fit: center=(63.64, 63.61), radius=11.40, Gaussian blur std=0.59 +2026-06-24 06:36:56,575 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.55 px with Npix = 128 +2026-06-24 06:36:56,575 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:36:56,575 - +2026-06-24 06:36:56,575 - ### Setting init_variables dict ### +2026-06-24 06:36:56,575 - Derived values given input init_params: +2026-06-24 06:36:56,575 - kv = 120.0 kV +2026-06-24 06:36:56,575 - wavelength = 0.0335 Ang +2026-06-24 06:36:56,575 - conv_angle = 15.113967895507812 mrad +2026-06-24 06:36:56,575 - Npix = 128 px +2026-06-24 06:36:56,575 - dk = 0.0391 Ang^-1 +2026-06-24 06:36:56,575 - kMax = 2.5000 Ang^-1 +2026-06-24 06:36:56,575 - da = 1.3083 mrad +2026-06-24 06:36:56,575 - angleMax = 83.7304 mrad +2026-06-24 06:36:56,575 - RBF = 11.5525 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:36:56,575 - n_alpha = 5.5399 (# conv_angle) +2026-06-24 06:36:56,575 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:36:56,575 - Rayleigh-limited resolution = 1.3517 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:36:56,575 - Real space probe extent = 25.6000 Ang +2026-06-24 06:36:56,575 - +2026-06-24 06:36:56,575 - ### Initializing probe ### +2026-06-24 06:36:56,575 - Loading probe from source = 'simu' +2026-06-24 06:36:56,575 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:36:56,576 - Start simulating STEM probe +2026-06-24 06:36:56,576 - kv = 120.0 kV +2026-06-24 06:36:56,576 - wavelength = 0.0335 Ang +2026-06-24 06:36:56,576 - conv_angle = 15.113967895507812 mrad +2026-06-24 06:36:56,576 - Npix = 128 px +2026-06-24 06:36:56,576 - dk = 0.0391 Ang^-1 +2026-06-24 06:36:56,576 - kMax = 2.5000 Ang^-1 +2026-06-24 06:36:56,576 - alpha_max = 83.7304 mrad +2026-06-24 06:36:56,576 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:36:56,576 - Rayleigh-limited resolution = 1.3517 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:36:56,576 - Real space probe extent = 25.6000 Ang +2026-06-24 06:36:56,576 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:36:56,576 - ------------------------------------------------------------------------------------ +2026-06-24 06:36:56,576 - C1,0 C1 -122.4570 - Defocus (C10 = -df) +2026-06-24 06:36:56,576 - C1,2 A1 -0.4990 236.38 2-fold astigmatism +2026-06-24 06:36:56,576 - C2,1 3*B2 -697.5260 250.94 Axial coma +2026-06-24 06:36:56,576 - C2,3 A2 -411.2620 142.14 3-fold astigmatism +2026-06-24 06:36:56,576 - C3,0 C3 -696954.5000 - Spherical aberration +2026-06-24 06:36:56,576 - C3,2 4*S3 -4671.8420 225.92 Axial star aberration +2026-06-24 06:36:56,576 - C3,4 A3 5144.4070 342.44 4-fold astigmatism +2026-06-24 06:36:56,576 - C4,1 4*B4 -317353.8120 210.74 Axial coma(4th) +2026-06-24 06:36:56,576 - C4,3 4*D4 183633.1720 75.19 3-lobe aberration +2026-06-24 06:36:56,576 - C4,5 A4 153332.6880 266.45 5-fold astigmatism +2026-06-24 06:36:56,576 - C5,0 C5 469479648.0000 - Spherical aberration (5th) +2026-06-24 06:36:56,576 - C5,2 6*S5 -6252632.5000 305.76 Axial star aberration(5th) +2026-06-24 06:36:56,576 - C5,4 6*R5 9106887.0000 324.09 4-lobe aberration +2026-06-24 06:36:56,576 - C5,6 A5 5117083.5000 201.45 6-fold astigmatism +2026-06-24 06:36:56,579 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:36:56,579 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:36:56,579 - Creating 5 new probe modes from the major mode +2026-06-24 06:36:56,579 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:36:56,797 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:36:56,798 - Orthogonalizing 6 pmodes +2026-06-24 06:36:56,801 - Sorting 6 pmodes by their intensities +2026-06-24 06:36:56,801 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:36:56,802 - sum(|probe_data|**2) = 440.47, while meas_total_ints (min, mean, max) = (435.8218, 440.4668, 445.7436) +2026-06-24 06:36:56,802 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:36:56,802 - +2026-06-24 06:36:56,802 - ### Initializing probe positions ### +2026-06-24 06:36:56,802 - Loading probe positions from source = 'simu' +2026-06-24 06:36:56,802 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:36:56,802 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4867, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:36:56,803 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:36:56,805 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:36:56,805 - crop_pos 1st and last px coords (y,x) = ([17, 17], [53, 53]) +2026-06-24 06:36:56,805 - crop_pos extent (Ang) = [7.4 7.4] +2026-06-24 06:36:56,805 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:36:56,805 - +2026-06-24 06:36:56,805 - ### Initializing object ### +2026-06-24 06:36:56,805 - Loading object from source = 'simu' +2026-06-24 06:36:56,805 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:36:56,806 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:36:56,807 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 198, 198) +2026-06-24 06:36:56,807 - object extent (Z, Y, X) (Ang) = [20. 39.6 39.6] +2026-06-24 06:36:56,807 - +2026-06-24 06:36:56,807 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:36:56,807 - omode_occu (omode) = float32, (1,) +2026-06-24 06:36:56,807 - +2026-06-24 06:36:56,807 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:36:56,807 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:36:56,808 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:36:56,808 - +2026-06-24 06:36:56,808 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:36:56,808 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:36:56,808 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:36:56,808 - +2026-06-24 06:36:56,808 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:36:56,808 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:36:56,808 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:36:56,808 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:36:56,808 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:36:56,808 - crop positions (yx_min=[17 16], yx_max=[182 181]) are well contained inside object canvas (Ny,Nx) = (198, 198). +2026-06-24 06:36:56,808 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:36:56,808 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:36:56,808 - +2026-06-24 06:36:56,808 - ### Collecting reconstruction provenance ### +2026-06-24 06:36:56,808 - Reconstruction provenance is collected and initialized. +2026-06-24 06:36:56,808 - +2026-06-24 06:36:56,808 - ### Initializing loss function ### +2026-06-24 06:36:56,809 - Active loss types: +2026-06-24 06:36:56,809 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:36:56,809 - +2026-06-24 06:36:56,809 - ### Initializing constraint function ### +2026-06-24 06:36:56,809 - Active constraint types: +2026-06-24 06:36:56,809 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:36:56,809 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:36:56,809 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:36:56,809 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:36:56,809 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:36:56,809 - +2026-06-24 06:36:56,809 - ### Done initializing PtyRADSolver ### +2026-06-24 06:36:56,809 - +2026-06-24 06:36:56,934 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:36:56,934 - +2026-06-24 06:36:56,934 - ### Initializing PtychoModel model ### +2026-06-24 06:36:57,004 - ### PtychoModel optimizable variables ### +2026-06-24 06:36:57,004 - obja : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:36:57,004 - objp : torch.Size([1, 1, 198, 198]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:36:57,004 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:36:57,004 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:36:57,004 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:36:57,004 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:36:57,004 - +2026-06-24 06:36:57,004 - ### Optimizable variables statitsics ### +2026-06-24 06:36:57,004 - Total measurement values : 4,194,304 +2026-06-24 06:36:57,004 - Total optimizing variables: 275,528 +2026-06-24 06:36:57,004 - Overdetermined ratio : 15.22 +2026-06-24 06:36:57,004 - +2026-06-24 06:36:57,004 - ### Model behavior ### +2026-06-24 06:36:57,004 - Tilt propagator : False +2026-06-24 06:36:57,004 - Change slice thickness : False +2026-06-24 06:36:57,005 - Detector blur : False +2026-06-24 06:36:57,005 - Preload data : True +2026-06-24 06:36:57,005 - On-the-fly meas padding : False +2026-06-24 06:36:57,005 - On-the-fly meas resample : False +2026-06-24 06:36:57,005 - On-the-fly simu match mode: None +2026-06-24 06:36:57,005 - +2026-06-24 06:36:57,047 - ### Done initializing PtychoModel model ### +2026-06-24 06:36:57,047 - +2026-06-24 06:36:57,047 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:36:57,047 - +2026-06-24 06:36:57,047 - ### Generating indices, batches, and output_path ### +2026-06-24 06:36:57,049 - d90 = 43.000 px or 8.600 Ang +2026-06-24 06:36:57,049 - Selecting indices with the 'full' mode +2026-06-24 06:36:57,514 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:36:57,592 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:36:57,592 - Original recon_dir_affixes = ['default'] +2026-06-24 06:36:57,592 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:36:57,598 - Path corrected for compatibility: +2026-06-24 06:36:57,598 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05_C32_-4.67e+03_phi32_226_C34_5.14e+03_phi34_342_C41_-3.17e+05_phi41_211_C43_1.84e+05_phi43_75.2_C45_1.53e+05_phi45_266_C50_4.69e+08_C52_-6.25e+06_phi52_306_C54_9.11e+06_phi54_324_C56_5.12e+06_phi56_201 +2026-06-24 06:36:57,598 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201 +2026-06-24 06:36:57,599 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201' is generated! +2026-06-24 06:36:57,754 - +2026-06-24 06:36:57,755 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201/20260624_063657_ptyrad_log.txt ### +2026-06-24 06:36:57,755 - +2026-06-24 06:36:57,756 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:36:57,756 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:36:57,757 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:36:58,974 - Iter: 1, Total Loss: 0.9532, loss_single: 0.9532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:36:59,010 - Iter: 2, Total Loss: 0.9216, loss_single: 0.9216, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:36:59,046 - Iter: 3, Total Loss: 0.8953, loss_single: 0.8953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,081 - Iter: 4, Total Loss: 0.8742, loss_single: 0.8742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,116 - Iter: 5, Total Loss: 0.8544, loss_single: 0.8544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,178 - Iter: 6, Total Loss: 0.8334, loss_single: 0.8334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,213 - Iter: 7, Total Loss: 0.8155, loss_single: 0.8155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,248 - Iter: 8, Total Loss: 0.7960, loss_single: 0.7960, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,284 - Iter: 9, Total Loss: 0.7720, loss_single: 0.7720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,319 - Iter: 10, Total Loss: 0.7492, loss_single: 0.7492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,354 - Iter: 11, Total Loss: 0.7297, loss_single: 0.7297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,389 - Iter: 12, Total Loss: 0.7101, loss_single: 0.7101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,424 - Iter: 13, Total Loss: 0.6921, loss_single: 0.6921, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,459 - Iter: 14, Total Loss: 0.6754, loss_single: 0.6754, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,494 - Iter: 15, Total Loss: 0.6583, loss_single: 0.6583, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,529 - Iter: 16, Total Loss: 0.6423, loss_single: 0.6423, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,564 - Iter: 17, Total Loss: 0.6261, loss_single: 0.6261, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,599 - Iter: 18, Total Loss: 0.6115, loss_single: 0.6115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,634 - Iter: 19, Total Loss: 0.6000, loss_single: 0.6000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,669 - Iter: 20, Total Loss: 0.5889, loss_single: 0.5889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,708 - Iter: 21, Total Loss: 0.5779, loss_single: 0.5779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:36:59,742 - Iter: 22, Total Loss: 0.5679, loss_single: 0.5679, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,778 - Iter: 23, Total Loss: 0.5586, loss_single: 0.5586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,813 - Iter: 24, Total Loss: 0.5484, loss_single: 0.5484, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,848 - Iter: 25, Total Loss: 0.5386, loss_single: 0.5386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,883 - Iter: 26, Total Loss: 0.5297, loss_single: 0.5297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,918 - Iter: 27, Total Loss: 0.5222, loss_single: 0.5222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:36:59,953 - Iter: 28, Total Loss: 0.5160, loss_single: 0.5160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:36:59,988 - Iter: 29, Total Loss: 0.5100, loss_single: 0.5100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,023 - Iter: 30, Total Loss: 0.5053, loss_single: 0.5053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,058 - Iter: 31, Total Loss: 0.5010, loss_single: 0.5010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,093 - Iter: 32, Total Loss: 0.4968, loss_single: 0.4968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:00,128 - Iter: 33, Total Loss: 0.4932, loss_single: 0.4932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,163 - Iter: 34, Total Loss: 0.4898, loss_single: 0.4898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:00,198 - Iter: 35, Total Loss: 0.4865, loss_single: 0.4865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:00,233 - Iter: 36, Total Loss: 0.4830, loss_single: 0.4830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,268 - Iter: 37, Total Loss: 0.4797, loss_single: 0.4797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:00,303 - Iter: 38, Total Loss: 0.4766, loss_single: 0.4766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,339 - Iter: 39, Total Loss: 0.4744, loss_single: 0.4744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,374 - Iter: 40, Total Loss: 0.4727, loss_single: 0.4727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,412 - Iter: 41, Total Loss: 0.4709, loss_single: 0.4709, 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Iter: 47, Total Loss: 0.4628, loss_single: 0.4628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,657 - Iter: 48, Total Loss: 0.4619, loss_single: 0.4619, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,693 - Iter: 49, Total Loss: 0.4611, loss_single: 0.4611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:37:00,728 - Iter: 50, Total Loss: 0.4605, loss_single: 0.4605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,763 - Iter: 51, Total Loss: 0.4599, loss_single: 0.4599, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:00,798 - Iter: 52, Total Loss: 0.4594, loss_single: 0.4594, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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in 0.034 sec +2026-06-24 06:37:01,426 - Iter: 70, Total Loss: 0.4545, loss_single: 0.4545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:01,461 - Iter: 71, Total Loss: 0.4544, loss_single: 0.4544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:01,497 - Iter: 72, Total Loss: 0.4542, loss_single: 0.4542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:01,532 - Iter: 73, Total Loss: 0.4541, loss_single: 0.4541, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:01,567 - Iter: 74, Total Loss: 0.4540, loss_single: 0.4540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:01,602 - Iter: 75, Total Loss: 0.4539, loss_single: 0.4539, loss_poissn: 0.0000, loss_pacbed: 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+2026-06-24 06:37:02,023 - Iter: 87, Total Loss: 0.4528, loss_single: 0.4528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,058 - Iter: 88, Total Loss: 0.4527, loss_single: 0.4527, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,093 - Iter: 89, Total Loss: 0.4526, loss_single: 0.4526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:37:02,128 - Iter: 90, Total Loss: 0.4526, loss_single: 0.4526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,163 - Iter: 91, Total Loss: 0.4525, loss_single: 0.4525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,200 - Iter: 92, Total Loss: 0.4524, loss_single: 0.4524, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.4519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:37:02,446 - Iter: 99, Total Loss: 0.4519, loss_single: 0.4519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,481 - Iter: 100, Total Loss: 0.4518, loss_single: 0.4518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:37:02,593 - Saving summary figures for iter 100 +2026-06-24 06:37:06,278 - ### Finished 100 iterations, averaged iter_t = 0.038712 with std = 0.040 ### +2026-06-24 06:37:06,278 - +2026-06-24 06:37:06,279 - ### The PtyRADSolver is finished in 9.345 sec ### +2026-06-24 06:37:06,279 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000019/c30_small__simulation_data_aug1__sample_000019_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-122_C12_-0.499_phi12_236_C21_-698_phi21_251_C23_-411_phi23_142_C30_-6.97e+05.12e+06_phi56_201/simulation_data_aug1__sample_000019.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 15.113967895507812 + probe_aberrations: + C10: -122.45690155029297 + C12: -0.4985189139842987 + C21: -697.5261840820312 + C23: -411.2623596191406 + C30: -696954.5 + C32: -4671.84228515625 + C34: 5144.4072265625 + C41: -317353.8125 + C43: 183633.171875 + C45: 153332.6875 + C50: 469479648.0 + C52: -6252632.5 + C54: 9106887.0 + C56: 5117083.5 + phi12: 236.38301170173648 + phi21: 250.93459312466527 + phi23: 142.13797149601453 + phi32: 225.91841057246825 + phi34: 342.4448938886058 + phi41: 210.73985876486734 + phi43: 75.18677019482455 + phi45: 266.4485755224055 + phi52: 305.7613685358147 + phi54: 324.09089151321757 + phi56: 201.4518260220255 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.486725389957428 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000019_measurement.h5 + key: measurement + random_seed: 20262099 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342/20260624_063911_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cb7fabcd9e32b448e3ceb1b91447af096d8cc55c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342/20260624_063911_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:39:09,738 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:39:09,738 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:39:09,738 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:39:09,738 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:39:09,738 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:39:09,738 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:39:09,738 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:39:09,738 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:39:09,738 - +2026-06-24 06:39:09,846 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:39:09,846 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:39:09,846 - Accelerator.num_process = 1 +2026-06-24 06:39:09,846 - Accelerator.mixed_precision = no +2026-06-24 06:39:09,856 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:39:09,856 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:39:09,856 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:39:09,856 - +2026-06-24 06:39:09,856 - ### System information ### +2026-06-24 06:39:09,856 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:39:09,856 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:39:09,856 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:39:09,856 - Machine: x86_64 +2026-06-24 06:39:09,857 - Processor: x86_64 +2026-06-24 06:39:09,857 - Available CPU cores: 8 +2026-06-24 06:39:09,857 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:39:09,857 - +2026-06-24 06:39:09,857 - ### GPU information ### +2026-06-24 06:39:09,857 - CUDA Available: True +2026-06-24 06:39:09,857 - CUDA Version: 13.0 +2026-06-24 06:39:09,857 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:39:09,857 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:39:09,857 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:39:09,857 - In addition, Triton does not directly support Windows. +2026-06-24 06:39:09,857 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:39:09,872 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:39:09,872 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:39:09,872 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:39:09,872 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:39:09,872 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:39:09,872 - +2026-06-24 06:39:09,872 - ### Python information ### +2026-06-24 06:39:09,874 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:39:09,874 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:39:09,874 - +2026-06-24 06:39:09,874 - ### Packages information ### +2026-06-24 06:39:09,874 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:39:09,875 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:39:09,876 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:39:09,876 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:39:09,877 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:39:09,877 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:39:09,877 - +2026-06-24 06:39:09,877 - ### Loading params file ### +2026-06-24 06:39:09,877 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug1__sample_000028.yaml +2026-06-24 06:39:09,883 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:39:09,884 - Success! Params file validated and defaults applied. +2026-06-24 06:39:09,884 - +2026-06-24 06:39:09,884 - ### Setting GPU Device ### +2026-06-24 06:39:09,885 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:39:09,885 - +2026-06-24 06:39:09,885 - Random seed: 20262108 provided by params file +2026-06-24 06:39:09,885 - ### Initializing Initializer ### +2026-06-24 06:39:09,885 - init_params are displayed below: +2026-06-24 06:39:09,885 - random_seed: 20262108 +2026-06-24 06:39:09,885 - probe_illum_type: electron +2026-06-24 06:39:09,885 - probe_kv: 300.0 +2026-06-24 06:39:09,885 - probe_conv_angle: 11.46122932434082 +2026-06-24 06:39:09,885 - probe_aberrations: {'C10': -1.194, 'C12': 3.717, 'phi12': 71.234, 'C21': -195.557, 'phi21': 153.142, 'C23': -252.542, 'phi23': 291.707, 'C30': 4946428.0, 'C32': -4215.236, 'phi32': 225.616, 'C34': 1597.718, 'phi34': 48.388, 'C41': 261308.453, 'phi41': 153.605, 'C43': 291150.125, 'phi43': 61.109, 'C45': 249004.562, 'phi45': 72.077, 'C50': 204810896.0, 'C52': 15617392.0, 'phi52': 221.988, 'C54': 7445838.5, 'phi54': 25.08, 'C56': -18953590.0, 'phi56': 342.112} +2026-06-24 06:39:09,885 - beam_kev: None +2026-06-24 06:39:09,885 - probe_dRn: None +2026-06-24 06:39:09,885 - probe_Rn: None +2026-06-24 06:39:09,885 - probe_D_H: None +2026-06-24 06:39:09,885 - probe_D_FZP: None +2026-06-24 06:39:09,885 - probe_Ls: None +2026-06-24 06:39:09,885 - meas_Npix: 128 +2026-06-24 06:39:09,886 - pos_N_scans: 256 +2026-06-24 06:39:09,886 - pos_N_scan_slow: 16 +2026-06-24 06:39:09,886 - pos_N_scan_fast: 16 +2026-06-24 06:39:09,886 - pos_scan_step_size: 0.35307833552360535 +2026-06-24 06:39:09,886 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:39:09,886 - probe_pmode_max: 6 +2026-06-24 06:39:09,886 - probe_pmode_init_pows: [0.02] +2026-06-24 06:39:09,886 - obj_omode_max: 1 +2026-06-24 06:39:09,886 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:39:09,886 - obj_Nlayer: 1 +2026-06-24 06:39:09,886 - obj_slice_thickness: 20.0 +2026-06-24 06:39:09,886 - simu_Npix: None +2026-06-24 06:39:09,886 - simu_match_mode: None +2026-06-24 06:39:09,886 - meas_permute: None +2026-06-24 06:39:09,886 - meas_reshape: [256, 128, 128] +2026-06-24 06:39:09,886 - meas_flipT: [0, 0, 0] +2026-06-24 06:39:09,886 - meas_crop: None +2026-06-24 06:39:09,886 - meas_pad: None +2026-06-24 06:39:09,886 - meas_resample: None +2026-06-24 06:39:09,886 - meas_add_source_size: None +2026-06-24 06:39:09,886 - meas_add_detector_blur: None +2026-06-24 06:39:09,886 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:39:09,886 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:39:09,886 - meas_add_poisson_noise: None +2026-06-24 06:39:09,886 - meas_export: None +2026-06-24 06:39:09,886 - probe_permute: None +2026-06-24 06:39:09,886 - probe_z_shift: None +2026-06-24 06:39:09,886 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:39:09,886 - pos_scan_flipT: None +2026-06-24 06:39:09,886 - pos_scan_affine: None +2026-06-24 06:39:09,886 - pos_scan_rand_std: 0.15 +2026-06-24 06:39:09,886 - obj_z_crop: None +2026-06-24 06:39:09,886 - obj_z_pad: None +2026-06-24 06:39:09,886 - obj_z_resample: None +2026-06-24 06:39:09,886 - meas_source: file +2026-06-24 06:39:09,886 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000028_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:39:09,886 - probe_source: simu +2026-06-24 06:39:09,886 - probe_params: None +2026-06-24 06:39:09,886 - pos_source: simu +2026-06-24 06:39:09,886 - pos_params: None +2026-06-24 06:39:09,886 - obj_source: simu +2026-06-24 06:39:09,886 - obj_params: None +2026-06-24 06:39:09,887 - tilt_source: simu +2026-06-24 06:39:09,887 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:39:09,887 - +2026-06-24 06:39:09,887 - ### Initializing cache ### +2026-06-24 06:39:09,887 - use_cached_obj = False +2026-06-24 06:39:09,887 - use_cached_probe = False +2026-06-24 06:39:09,887 - use_cached_pos = False +2026-06-24 06:39:09,887 - +2026-06-24 06:39:09,887 - ### Initializing measurements ### +2026-06-24 06:39:09,887 - Loading measurements from source = 'file' +2026-06-24 06:39:09,887 - Detected measurement file type = '.h5' +2026-06-24 06:39:09,962 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:39:09,963 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:39:09,964 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0024) +2026-06-24 06:39:09,964 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:39:09,964 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:39:09,966 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:39:09,966 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:39:09,966 - Normalizing by max of the 2D mean pattern intensity: 0.0014433889 +2026-06-24 06:39:09,967 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:39:09,968 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0423, 1.6909) +2026-06-24 06:39:09,969 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:39:09,970 - Pattern total int. statistics (min, mean, max) = (686.1630, 693.5646, 700.7360), with min/max = 97.9% +2026-06-24 06:39:09,971 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0423, 1.6909) +2026-06-24 06:39:09,971 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:39:09,971 - +2026-06-24 06:39:09,971 - ### Setting up calibration ### +2026-06-24 06:39:09,971 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:39:09,971 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:39:09,971 - Radius of fitted bright field disk (RBF) = 14.79 px with meas_Npix = 128 +2026-06-24 06:39:09,971 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2311 +2026-06-24 06:39:09,971 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:39:09,972 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:39:10,193 - Initial guess: center=(63.61, 63.61), radius=14.79, Gaussian blur std=0.50 +2026-06-24 06:39:10,206 - Final fit: center=(63.61, 63.61), radius=14.79, Gaussian blur std=0.67 +2026-06-24 06:39:10,206 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 14.90 px with Npix = 128 +2026-06-24 06:39:10,206 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:39:10,206 - +2026-06-24 06:39:10,206 - ### Setting init_variables dict ### +2026-06-24 06:39:10,206 - Derived values given input init_params: +2026-06-24 06:39:10,206 - kv = 300.0 kV +2026-06-24 06:39:10,206 - wavelength = 0.0197 Ang +2026-06-24 06:39:10,206 - conv_angle = 11.46122932434082 mrad +2026-06-24 06:39:10,206 - Npix = 128 px +2026-06-24 06:39:10,206 - dk = 0.0391 Ang^-1 +2026-06-24 06:39:10,206 - kMax = 2.5000 Ang^-1 +2026-06-24 06:39:10,206 - da = 0.7690 mrad +2026-06-24 06:39:10,206 - angleMax = 49.2187 mrad +2026-06-24 06:39:10,206 - RBF = 14.9032 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:39:10,206 - n_alpha = 4.2944 (# conv_angle) +2026-06-24 06:39:10,206 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:39:10,206 - Rayleigh-limited resolution = 1.0478 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:39:10,206 - Real space probe extent = 25.6000 Ang +2026-06-24 06:39:10,206 - +2026-06-24 06:39:10,206 - ### Initializing probe ### +2026-06-24 06:39:10,206 - Loading probe from source = 'simu' +2026-06-24 06:39:10,206 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:39:10,207 - Start simulating STEM probe +2026-06-24 06:39:10,207 - kv = 300.0 kV +2026-06-24 06:39:10,207 - wavelength = 0.0197 Ang +2026-06-24 06:39:10,207 - conv_angle = 11.46122932434082 mrad +2026-06-24 06:39:10,207 - Npix = 128 px +2026-06-24 06:39:10,207 - dk = 0.0391 Ang^-1 +2026-06-24 06:39:10,207 - kMax = 2.5000 Ang^-1 +2026-06-24 06:39:10,207 - alpha_max = 49.2187 mrad +2026-06-24 06:39:10,207 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:39:10,207 - Rayleigh-limited resolution = 1.0478 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:39:10,207 - Real space probe extent = 25.6000 Ang +2026-06-24 06:39:10,207 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:39:10,207 - ------------------------------------------------------------------------------------ +2026-06-24 06:39:10,207 - C1,0 C1 -1.1940 - Defocus (C10 = -df) +2026-06-24 06:39:10,207 - C1,2 A1 3.7170 71.23 2-fold astigmatism +2026-06-24 06:39:10,207 - C2,1 3*B2 -195.5570 153.14 Axial coma +2026-06-24 06:39:10,207 - C2,3 A2 -252.5420 291.71 3-fold astigmatism +2026-06-24 06:39:10,207 - C3,0 C3 4946428.0000 - Spherical aberration +2026-06-24 06:39:10,207 - C3,2 4*S3 -4215.2360 225.62 Axial star aberration +2026-06-24 06:39:10,207 - C3,4 A3 1597.7180 48.39 4-fold astigmatism +2026-06-24 06:39:10,207 - C4,1 4*B4 261308.4530 153.60 Axial coma(4th) +2026-06-24 06:39:10,207 - C4,3 4*D4 291150.1250 61.11 3-lobe aberration +2026-06-24 06:39:10,207 - C4,5 A4 249004.5620 72.08 5-fold astigmatism +2026-06-24 06:39:10,207 - C5,0 C5 204810896.0000 - Spherical aberration (5th) +2026-06-24 06:39:10,207 - C5,2 6*S5 15617392.0000 221.99 Axial star aberration(5th) +2026-06-24 06:39:10,207 - C5,4 6*R5 7445838.5000 25.08 4-lobe aberration +2026-06-24 06:39:10,207 - C5,6 A5 -18953590.0000 342.11 6-fold astigmatism +2026-06-24 06:39:10,210 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:39:10,210 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:39:10,210 - Creating 5 new probe modes from the major mode +2026-06-24 06:39:10,210 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:39:10,313 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:39:10,314 - Orthogonalizing 6 pmodes +2026-06-24 06:39:10,316 - Sorting 6 pmodes by their intensities +2026-06-24 06:39:10,317 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:39:10,317 - sum(|probe_data|**2) = 693.56, while meas_total_ints (min, mean, max) = (686.1630, 693.5646, 700.7360) +2026-06-24 06:39:10,317 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:39:10,317 - +2026-06-24 06:39:10,317 - ### Initializing probe positions ### +2026-06-24 06:39:10,318 - Loading probe positions from source = 'simu' +2026-06-24 06:39:10,318 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:39:10,318 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3531, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:39:10,318 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:39:10,320 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:39:10,320 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 06:39:10,320 - crop_pos extent (Ang) = [5.4 5.2] +2026-06-24 06:39:10,320 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:39:10,320 - +2026-06-24 06:39:10,320 - ### Initializing object ### +2026-06-24 06:39:10,320 - Loading object from source = 'simu' +2026-06-24 06:39:10,320 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:39:10,321 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:39:10,322 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 187, 186) +2026-06-24 06:39:10,322 - object extent (Z, Y, X) (Ang) = [20. 37.4 37.2] +2026-06-24 06:39:10,322 - +2026-06-24 06:39:10,322 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:39:10,322 - omode_occu (omode) = float32, (1,) +2026-06-24 06:39:10,322 - +2026-06-24 06:39:10,322 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:39:10,322 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:39:10,323 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:39:10,323 - +2026-06-24 06:39:10,323 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:39:10,323 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:39:10,323 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:39:10,323 - +2026-06-24 06:39:10,323 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:39:10,323 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:39:10,323 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:39:10,323 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:39:10,323 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:39:10,323 - crop positions (yx_min=[15 16], yx_max=[170 170]) are well contained inside object canvas (Ny,Nx) = (187, 186). +2026-06-24 06:39:10,323 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:39:10,323 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:39:10,323 - +2026-06-24 06:39:10,323 - ### Collecting reconstruction provenance ### +2026-06-24 06:39:10,323 - Reconstruction provenance is collected and initialized. +2026-06-24 06:39:10,323 - +2026-06-24 06:39:10,323 - ### Initializing loss function ### +2026-06-24 06:39:10,323 - Active loss types: +2026-06-24 06:39:10,324 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:39:10,324 - +2026-06-24 06:39:10,324 - ### Initializing constraint function ### +2026-06-24 06:39:10,324 - Active constraint types: +2026-06-24 06:39:10,324 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:39:10,324 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:39:10,324 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:39:10,324 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:39:10,324 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:39:10,324 - +2026-06-24 06:39:10,324 - ### Done initializing PtyRADSolver ### +2026-06-24 06:39:10,324 - +2026-06-24 06:39:10,450 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:39:10,450 - +2026-06-24 06:39:10,450 - ### Initializing PtychoModel model ### +2026-06-24 06:39:10,522 - ### PtychoModel optimizable variables ### +2026-06-24 06:39:10,522 - obja : torch.Size([1, 1, 187, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:39:10,522 - objp : torch.Size([1, 1, 187, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:39:10,522 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:39:10,522 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:39:10,522 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:39:10,522 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:39:10,522 - +2026-06-24 06:39:10,522 - ### Optimizable variables statitsics ### +2026-06-24 06:39:10,522 - Total measurement values : 4,194,304 +2026-06-24 06:39:10,522 - Total optimizing variables: 266,684 +2026-06-24 06:39:10,522 - Overdetermined ratio : 15.73 +2026-06-24 06:39:10,522 - +2026-06-24 06:39:10,522 - ### Model behavior ### +2026-06-24 06:39:10,523 - Tilt propagator : False +2026-06-24 06:39:10,523 - Change slice thickness : False +2026-06-24 06:39:10,523 - Detector blur : False +2026-06-24 06:39:10,523 - Preload data : True +2026-06-24 06:39:10,523 - On-the-fly meas padding : False +2026-06-24 06:39:10,523 - On-the-fly meas resample : False +2026-06-24 06:39:10,523 - On-the-fly simu match mode: None +2026-06-24 06:39:10,523 - +2026-06-24 06:39:10,563 - ### Done initializing PtychoModel model ### +2026-06-24 06:39:10,563 - +2026-06-24 06:39:10,564 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:39:10,564 - +2026-06-24 06:39:10,564 - ### Generating indices, batches, and output_path ### +2026-06-24 06:39:10,565 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:39:10,565 - Selecting indices with the 'full' mode +2026-06-24 06:39:11,023 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:39:11,099 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:39:11,099 - Original recon_dir_affixes = ['default'] +2026-06-24 06:39:11,099 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:39:11,106 - Path corrected for compatibility: +2026-06-24 06:39:11,106 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C32_-4.22e+03_phi32_226_C34_1.6e+03_phi34_48.4_C41_2.61e+05_phi41_154_C43_2.91e+05_phi43_61.1_C45_2.49e+05_phi45_72.1_C50_2.05e+08_C52_1.56e+07_phi52_222_C54_7.45e+06_phi54_25.1_C56_-1.9e+07_phi56_342 +2026-06-24 06:39:11,106 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342 +2026-06-24 06:39:11,108 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342' is generated! +2026-06-24 06:39:11,251 - +2026-06-24 06:39:11,252 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342/20260624_063911_ptyrad_log.txt ### +2026-06-24 06:39:11,252 - +2026-06-24 06:39:11,254 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:39:11,254 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:39:11,254 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:39:12,450 - Iter: 1, Total Loss: 0.7795, loss_single: 0.7795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:39:12,487 - Iter: 2, Total Loss: 0.7529, loss_single: 0.7529, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:39:12,523 - Iter: 3, Total Loss: 0.7303, loss_single: 0.7303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:12,558 - Iter: 4, Total Loss: 0.7124, loss_single: 0.7124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:39:12,593 - Iter: 5, Total Loss: 0.6956, loss_single: 0.6956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:12,628 - Iter: 6, Total Loss: 0.6765, loss_single: 0.6765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:39:12,663 - Iter: 7, Total Loss: 0.6601, loss_single: 0.6601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:39:12,698 - Iter: 8, Total Loss: 0.6436, loss_single: 0.6436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:12,733 - Iter: 9, Total Loss: 0.6252, loss_single: 0.6252, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:39:12,768 - Iter: 10, Total Loss: 0.6069, loss_single: 0.6069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:12,803 - Iter: 11, Total Loss: 0.5926, loss_single: 0.5926, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:12,838 - Iter: 12, Total Loss: 0.5823, loss_single: 0.5823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 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loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,706 - Iter: 93, Total Loss: 0.3533, loss_single: 0.3533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,741 - Iter: 94, Total Loss: 0.3529, loss_single: 0.3529, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,776 - Iter: 95, Total Loss: 0.3525, loss_single: 0.3525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,811 - Iter: 96, Total Loss: 0.3521, loss_single: 0.3521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:39:15,846 - Iter: 97, Total Loss: 0.3516, loss_single: 0.3516, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,881 - Iter: 98, Total Loss: 0.3513, loss_single: 0.3513, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,916 - Iter: 99, Total Loss: 0.3509, loss_single: 0.3509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:15,951 - Iter: 100, Total Loss: 0.3505, loss_single: 0.3505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:39:16,062 - Saving summary figures for iter 100 +2026-06-24 06:39:19,720 - ### Finished 100 iterations, averaged iter_t = 0.038773 with std = 0.040 ### +2026-06-24 06:39:19,721 - +2026-06-24 06:39:19,721 - ### The PtyRADSolver is finished in 9.271 sec ### +2026-06-24 06:39:19,721 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug1__sample_000028/c30_small__simulation_data_aug1__sample_000028_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-1.19_C12_3.72_phi12_71.2_C21_-196_phi21_153_C23_-253_phi23_292_C30_4.95e+06_C.9e+07_phi56_342/simulation_data_aug1__sample_000028.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 11.46122932434082 + probe_aberrations: + C10: -1.1941628456115723 + C12: 3.7166237831115723 + C21: -195.55670166015625 + C23: -252.54225158691406 + C30: 4946428.0 + C32: -4215.23583984375 + C34: 1597.7183837890625 + C41: 261308.453125 + C43: 291150.125 + C45: 249004.5625 + C50: 204810896.0 + C52: 15617392.0 + C54: 7445838.5 + C56: -18953590.0 + phi12: 71.2343173070566 + phi21: 153.1415838338235 + phi23: 291.7068336391661 + phi32: 225.6161747016952 + phi34: 48.38828051456399 + phi41: 153.60499850863053 + phi43: 61.10912193802463 + phi45: 72.07697823552857 + phi52: 221.9880738372328 + phi54: 25.08002433036911 + phi56: 342.11177190240596 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.35307833552360535 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug1__sample_000028_measurement.h5 + key: measurement + random_seed: 20262108 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307/20260624_064054_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..14d8839d07ef2eedf38daa552acfd7428abae3d2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307/20260624_064054_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:40:52,670 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:40:52,670 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:40:52,670 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:40:52,670 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:40:52,671 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:40:52,671 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:40:52,671 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:40:52,671 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:40:52,671 - +2026-06-24 06:40:52,781 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:40:52,781 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:40:52,781 - Accelerator.num_process = 1 +2026-06-24 06:40:52,781 - Accelerator.mixed_precision = no +2026-06-24 06:40:52,791 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:40:52,791 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:40:52,791 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:40:52,791 - +2026-06-24 06:40:52,791 - ### System information ### +2026-06-24 06:40:52,791 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:40:52,791 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:40:52,791 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:40:52,791 - Machine: x86_64 +2026-06-24 06:40:52,791 - Processor: x86_64 +2026-06-24 06:40:52,791 - Available CPU cores: 8 +2026-06-24 06:40:52,792 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:40:52,792 - +2026-06-24 06:40:52,792 - ### GPU information ### +2026-06-24 06:40:52,792 - CUDA Available: True +2026-06-24 06:40:52,792 - CUDA Version: 13.0 +2026-06-24 06:40:52,792 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:40:52,792 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:40:52,792 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:40:52,792 - In addition, Triton does not directly support Windows. +2026-06-24 06:40:52,792 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:40:52,808 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:40:52,808 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:40:52,808 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:40:52,808 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:40:52,808 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:40:52,808 - +2026-06-24 06:40:52,808 - ### Python information ### +2026-06-24 06:40:52,809 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:40:52,809 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:40:52,809 - +2026-06-24 06:40:52,809 - ### Packages information ### +2026-06-24 06:40:52,810 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:40:52,811 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:40:52,811 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:40:52,812 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:40:52,813 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:40:52,813 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:40:52,813 - +2026-06-24 06:40:52,813 - ### Loading params file ### +2026-06-24 06:40:52,813 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000000.yaml +2026-06-24 06:40:52,819 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:40:52,820 - Success! Params file validated and defaults applied. +2026-06-24 06:40:52,820 - +2026-06-24 06:40:52,820 - ### Setting GPU Device ### +2026-06-24 06:40:52,821 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:40:52,821 - +2026-06-24 06:40:52,821 - Random seed: 20262115 provided by params file +2026-06-24 06:40:52,821 - ### Initializing Initializer ### +2026-06-24 06:40:52,821 - init_params are displayed below: +2026-06-24 06:40:52,821 - random_seed: 20262115 +2026-06-24 06:40:52,821 - probe_illum_type: electron +2026-06-24 06:40:52,821 - probe_kv: 80.0 +2026-06-24 06:40:52,821 - probe_conv_angle: 19.016590118408203 +2026-06-24 06:40:52,821 - probe_aberrations: {'C10': -564.738, 'C12': -3.362, 'phi12': 63.567, 'C21': -472.194, 'phi21': 337.026, 'C23': 165.155, 'phi23': 259.06, 'C30': 2692416.5, 'C32': -9666.918, 'phi32': 305.163, 'C34': -3761.156, 'phi34': 14.54, 'C41': -163184.484, 'phi41': 313.284, 'C43': 288142.375, 'phi43': 222.601, 'C45': 387368.688, 'phi45': 217.765, 'C50': 485856832.0, 'C52': -5371788.5, 'phi52': 127.553, 'C54': 11480743.0, 'phi54': 112.71, 'C56': -7605285.5, 'phi56': 307.322} +2026-06-24 06:40:52,821 - beam_kev: None +2026-06-24 06:40:52,821 - probe_dRn: None +2026-06-24 06:40:52,821 - probe_Rn: None +2026-06-24 06:40:52,821 - probe_D_H: None +2026-06-24 06:40:52,821 - probe_D_FZP: None +2026-06-24 06:40:52,821 - probe_Ls: None +2026-06-24 06:40:52,821 - meas_Npix: 128 +2026-06-24 06:40:52,822 - pos_N_scans: 256 +2026-06-24 06:40:52,822 - pos_N_scan_slow: 16 +2026-06-24 06:40:52,822 - pos_N_scan_fast: 16 +2026-06-24 06:40:52,822 - pos_scan_step_size: 0.3516256809234619 +2026-06-24 06:40:52,822 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:40:52,822 - probe_pmode_max: 6 +2026-06-24 06:40:52,822 - probe_pmode_init_pows: [0.02] +2026-06-24 06:40:52,822 - obj_omode_max: 1 +2026-06-24 06:40:52,822 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:40:52,822 - obj_Nlayer: 1 +2026-06-24 06:40:52,822 - obj_slice_thickness: 20.0 +2026-06-24 06:40:52,822 - simu_Npix: None +2026-06-24 06:40:52,822 - simu_match_mode: None +2026-06-24 06:40:52,822 - meas_permute: None +2026-06-24 06:40:52,822 - meas_reshape: [256, 128, 128] +2026-06-24 06:40:52,822 - meas_flipT: [0, 0, 0] +2026-06-24 06:40:52,822 - meas_crop: None +2026-06-24 06:40:52,822 - meas_pad: None +2026-06-24 06:40:52,822 - meas_resample: None +2026-06-24 06:40:52,822 - meas_add_source_size: None +2026-06-24 06:40:52,822 - meas_add_detector_blur: None +2026-06-24 06:40:52,822 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:40:52,822 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:40:52,822 - meas_add_poisson_noise: None +2026-06-24 06:40:52,822 - meas_export: None +2026-06-24 06:40:52,822 - probe_permute: None +2026-06-24 06:40:52,822 - probe_z_shift: None +2026-06-24 06:40:52,822 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:40:52,822 - pos_scan_flipT: None +2026-06-24 06:40:52,822 - pos_scan_affine: None +2026-06-24 06:40:52,822 - pos_scan_rand_std: 0.15 +2026-06-24 06:40:52,822 - obj_z_crop: None +2026-06-24 06:40:52,822 - obj_z_pad: None +2026-06-24 06:40:52,822 - obj_z_resample: None +2026-06-24 06:40:52,822 - meas_source: file +2026-06-24 06:40:52,822 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000000_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:40:52,822 - probe_source: simu +2026-06-24 06:40:52,822 - probe_params: None +2026-06-24 06:40:52,823 - pos_source: simu +2026-06-24 06:40:52,823 - pos_params: None +2026-06-24 06:40:52,823 - obj_source: simu +2026-06-24 06:40:52,823 - obj_params: None +2026-06-24 06:40:52,823 - tilt_source: simu +2026-06-24 06:40:52,823 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:40:52,823 - +2026-06-24 06:40:52,823 - ### Initializing cache ### +2026-06-24 06:40:52,823 - use_cached_obj = False +2026-06-24 06:40:52,823 - use_cached_probe = False +2026-06-24 06:40:52,823 - use_cached_pos = False +2026-06-24 06:40:52,823 - +2026-06-24 06:40:52,823 - ### Initializing measurements ### +2026-06-24 06:40:52,823 - Loading measurements from source = 'file' +2026-06-24 06:40:52,823 - Detected measurement file type = '.h5' +2026-06-24 06:40:52,900 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:40:52,901 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:40:52,902 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0030) +2026-06-24 06:40:52,902 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:40:52,902 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:40:52,904 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:40:52,904 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:40:52,904 - Normalizing by max of the 2D mean pattern intensity: 0.0022602023 +2026-06-24 06:40:52,905 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:40:52,906 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0270, 1.3345) +2026-06-24 06:40:52,907 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:40:52,908 - Pattern total int. statistics (min, mean, max) = (437.8293, 441.6143, 444.9018), with min/max = 98.4% +2026-06-24 06:40:52,909 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0270, 1.3345) +2026-06-24 06:40:52,909 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:40:52,909 - +2026-06-24 06:40:52,909 - ### Setting up calibration ### +2026-06-24 06:40:52,910 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:40:52,910 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:40:52,910 - Radius of fitted bright field disk (RBF) = 11.53 px with meas_Npix = 128 +2026-06-24 06:40:52,910 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1802 +2026-06-24 06:40:52,910 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:40:52,910 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:40:53,130 - Initial guess: center=(63.63, 63.66), radius=11.53, Gaussian blur std=0.50 +2026-06-24 06:40:53,142 - Final fit: center=(63.63, 63.66), radius=11.53, Gaussian blur std=0.69 +2026-06-24 06:40:53,142 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.66 px with Npix = 128 +2026-06-24 06:40:53,143 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:40:53,143 - +2026-06-24 06:40:53,143 - ### Setting init_variables dict ### +2026-06-24 06:40:53,143 - Derived values given input init_params: +2026-06-24 06:40:53,143 - kv = 80.0 kV +2026-06-24 06:40:53,143 - wavelength = 0.0418 Ang +2026-06-24 06:40:53,143 - conv_angle = 19.016590118408203 mrad +2026-06-24 06:40:53,143 - Npix = 128 px +2026-06-24 06:40:53,143 - dk = 0.0391 Ang^-1 +2026-06-24 06:40:53,143 - kMax = 2.5000 Ang^-1 +2026-06-24 06:40:53,143 - da = 1.6311 mrad +2026-06-24 06:40:53,143 - angleMax = 104.3929 mrad +2026-06-24 06:40:53,143 - RBF = 11.6585 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:40:53,143 - n_alpha = 5.4896 (# conv_angle) +2026-06-24 06:40:53,143 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:40:53,143 - Rayleigh-limited resolution = 1.3395 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:40:53,143 - Real space probe extent = 25.6000 Ang +2026-06-24 06:40:53,143 - +2026-06-24 06:40:53,143 - ### Initializing probe ### +2026-06-24 06:40:53,143 - Loading probe from source = 'simu' +2026-06-24 06:40:53,143 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:40:53,143 - Start simulating STEM probe +2026-06-24 06:40:53,143 - kv = 80.0 kV +2026-06-24 06:40:53,144 - wavelength = 0.0418 Ang +2026-06-24 06:40:53,144 - conv_angle = 19.016590118408203 mrad +2026-06-24 06:40:53,144 - Npix = 128 px +2026-06-24 06:40:53,144 - dk = 0.0391 Ang^-1 +2026-06-24 06:40:53,144 - kMax = 2.5000 Ang^-1 +2026-06-24 06:40:53,144 - alpha_max = 104.3929 mrad +2026-06-24 06:40:53,144 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:40:53,144 - Rayleigh-limited resolution = 1.3395 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:40:53,144 - Real space probe extent = 25.6000 Ang +2026-06-24 06:40:53,144 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:40:53,144 - ------------------------------------------------------------------------------------ +2026-06-24 06:40:53,144 - C1,0 C1 -564.7380 - Defocus (C10 = -df) +2026-06-24 06:40:53,144 - C1,2 A1 -3.3620 63.57 2-fold astigmatism +2026-06-24 06:40:53,144 - C2,1 3*B2 -472.1940 337.03 Axial coma +2026-06-24 06:40:53,144 - C2,3 A2 165.1550 259.06 3-fold astigmatism +2026-06-24 06:40:53,144 - C3,0 C3 2692416.5000 - Spherical aberration +2026-06-24 06:40:53,144 - C3,2 4*S3 -9666.9180 305.16 Axial star aberration +2026-06-24 06:40:53,144 - C3,4 A3 -3761.1560 14.54 4-fold astigmatism +2026-06-24 06:40:53,144 - C4,1 4*B4 -163184.4840 313.28 Axial coma(4th) +2026-06-24 06:40:53,144 - C4,3 4*D4 288142.3750 222.60 3-lobe aberration +2026-06-24 06:40:53,144 - C4,5 A4 387368.6880 217.76 5-fold astigmatism +2026-06-24 06:40:53,144 - C5,0 C5 485856832.0000 - Spherical aberration (5th) +2026-06-24 06:40:53,144 - C5,2 6*S5 -5371788.5000 127.55 Axial star aberration(5th) +2026-06-24 06:40:53,144 - C5,4 6*R5 11480743.0000 112.71 4-lobe aberration +2026-06-24 06:40:53,144 - C5,6 A5 -7605285.5000 307.32 6-fold astigmatism +2026-06-24 06:40:53,147 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:40:53,147 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:40:53,147 - Creating 5 new probe modes from the major mode +2026-06-24 06:40:53,147 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:40:53,343 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:40:53,344 - Orthogonalizing 6 pmodes +2026-06-24 06:40:53,357 - Sorting 6 pmodes by their intensities +2026-06-24 06:40:53,357 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:40:53,358 - sum(|probe_data|**2) = 441.61, while meas_total_ints (min, mean, max) = (437.8293, 441.6143, 444.9018) +2026-06-24 06:40:53,358 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:40:53,358 - +2026-06-24 06:40:53,358 - ### Initializing probe positions ### +2026-06-24 06:40:53,358 - Loading probe positions from source = 'simu' +2026-06-24 06:40:53,358 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:40:53,358 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3516, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:40:53,358 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:40:53,360 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:40:53,360 - crop_pos 1st and last px coords (y,x) = ([16, 16], [42, 42]) +2026-06-24 06:40:53,361 - crop_pos extent (Ang) = [5.4 5.4] +2026-06-24 06:40:53,361 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:40:53,361 - +2026-06-24 06:40:53,361 - ### Initializing object ### +2026-06-24 06:40:53,361 - Loading object from source = 'simu' +2026-06-24 06:40:53,361 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:40:53,362 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:40:53,362 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 187) +2026-06-24 06:40:53,362 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.4] +2026-06-24 06:40:53,362 - +2026-06-24 06:40:53,362 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:40:53,363 - omode_occu (omode) = float32, (1,) +2026-06-24 06:40:53,363 - +2026-06-24 06:40:53,363 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:40:53,363 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:40:53,363 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:40:53,363 - +2026-06-24 06:40:53,363 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:40:53,363 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:40:53,363 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:40:53,363 - +2026-06-24 06:40:53,363 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:40:53,364 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:40:53,364 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:40:53,364 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:40:53,364 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:40:53,364 - crop positions (yx_min=[15 16], yx_max=[170 171]) are well contained inside object canvas (Ny,Nx) = (186, 187). +2026-06-24 06:40:53,364 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:40:53,364 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:40:53,364 - +2026-06-24 06:40:53,364 - ### Collecting reconstruction provenance ### +2026-06-24 06:40:53,364 - Reconstruction provenance is collected and initialized. +2026-06-24 06:40:53,364 - +2026-06-24 06:40:53,364 - ### Initializing loss function ### +2026-06-24 06:40:53,364 - Active loss types: +2026-06-24 06:40:53,364 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:40:53,364 - +2026-06-24 06:40:53,364 - ### Initializing constraint function ### +2026-06-24 06:40:53,364 - Active constraint types: +2026-06-24 06:40:53,364 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:40:53,364 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:40:53,364 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:40:53,365 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:40:53,365 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:40:53,365 - +2026-06-24 06:40:53,365 - ### Done initializing PtyRADSolver ### +2026-06-24 06:40:53,365 - +2026-06-24 06:40:53,491 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:40:53,491 - +2026-06-24 06:40:53,491 - ### Initializing PtychoModel model ### +2026-06-24 06:40:53,561 - ### PtychoModel optimizable variables ### +2026-06-24 06:40:53,561 - obja : torch.Size([1, 1, 186, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:40:53,561 - objp : torch.Size([1, 1, 186, 187]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:40:53,561 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:40:53,561 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:40:53,561 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:40:53,561 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:40:53,561 - +2026-06-24 06:40:53,562 - ### Optimizable variables statitsics ### +2026-06-24 06:40:53,562 - Total measurement values : 4,194,304 +2026-06-24 06:40:53,562 - Total optimizing variables: 266,684 +2026-06-24 06:40:53,562 - Overdetermined ratio : 15.73 +2026-06-24 06:40:53,562 - +2026-06-24 06:40:53,562 - ### Model behavior ### +2026-06-24 06:40:53,562 - Tilt propagator : False +2026-06-24 06:40:53,562 - Change slice thickness : False +2026-06-24 06:40:53,562 - Detector blur : False +2026-06-24 06:40:53,562 - Preload data : True +2026-06-24 06:40:53,562 - On-the-fly meas padding : False +2026-06-24 06:40:53,562 - On-the-fly meas resample : False +2026-06-24 06:40:53,562 - On-the-fly simu match mode: None +2026-06-24 06:40:53,562 - +2026-06-24 06:40:53,604 - ### Done initializing PtychoModel model ### +2026-06-24 06:40:53,604 - +2026-06-24 06:40:53,604 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:40:53,604 - +2026-06-24 06:40:53,604 - ### Generating indices, batches, and output_path ### +2026-06-24 06:40:53,606 - d90 = 53.000 px or 10.600 Ang +2026-06-24 06:40:53,606 - Selecting indices with the 'full' mode +2026-06-24 06:40:54,075 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:40:54,147 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:40:54,147 - Original recon_dir_affixes = ['default'] +2026-06-24 06:40:54,147 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:40:54,154 - Path corrected for compatibility: +2026-06-24 06:40:54,154 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C32_-9.67e+03_phi32_305_C34_-3.76e+03_phi34_14.5_C41_-1.63e+05_phi41_313_C43_2.88e+05_phi43_223_C45_3.87e+05_phi45_218_C50_4.86e+08_C52_-5.37e+06_phi52_128_C54_1.15e+07_phi54_113_C56_-7.61e+06_phi56_307 +2026-06-24 06:40:54,154 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307 +2026-06-24 06:40:54,155 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307' is generated! +2026-06-24 06:40:54,304 - +2026-06-24 06:40:54,305 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307/20260624_064054_ptyrad_log.txt ### +2026-06-24 06:40:54,305 - +2026-06-24 06:40:54,306 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:40:54,306 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:40:54,306 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:40:55,506 - Iter: 1, Total Loss: 0.9274, loss_single: 0.9274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:40:55,543 - Iter: 2, Total Loss: 0.8924, loss_single: 0.8924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:40:55,578 - Iter: 3, Total Loss: 0.8654, loss_single: 0.8654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,613 - Iter: 4, Total Loss: 0.8437, loss_single: 0.8437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,649 - Iter: 5, Total Loss: 0.8224, loss_single: 0.8224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,685 - Iter: 6, Total Loss: 0.8025, loss_single: 0.8025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,720 - Iter: 7, Total Loss: 0.7817, loss_single: 0.7817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,756 - Iter: 8, Total Loss: 0.7597, loss_single: 0.7597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,791 - Iter: 9, Total Loss: 0.7385, loss_single: 0.7385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,827 - Iter: 10, Total Loss: 0.7145, loss_single: 0.7145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,862 - Iter: 11, Total Loss: 0.6890, loss_single: 0.6890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,898 - Iter: 12, Total Loss: 0.6641, loss_single: 0.6641, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,933 - Iter: 13, Total Loss: 0.6383, loss_single: 0.6383, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:55,969 - Iter: 14, Total Loss: 0.6099, loss_single: 0.6099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,004 - Iter: 15, Total Loss: 0.5816, loss_single: 0.5816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,039 - Iter: 16, Total Loss: 0.5635, loss_single: 0.5635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,075 - Iter: 17, Total Loss: 0.5478, loss_single: 0.5478, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,110 - Iter: 18, Total Loss: 0.5261, loss_single: 0.5261, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,145 - Iter: 19, Total Loss: 0.5068, loss_single: 0.5068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,181 - Iter: 20, Total Loss: 0.4903, loss_single: 0.4903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,216 - Iter: 21, Total Loss: 0.4719, loss_single: 0.4719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,252 - Iter: 22, Total Loss: 0.4520, loss_single: 0.4520, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,287 - Iter: 23, Total Loss: 0.4338, loss_single: 0.4338, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,327 - Iter: 24, Total Loss: 0.4168, loss_single: 0.4168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:40:56,362 - Iter: 25, Total Loss: 0.4053, loss_single: 0.4053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,398 - Iter: 26, Total Loss: 0.3975, loss_single: 0.3975, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,433 - Iter: 27, Total Loss: 0.3899, loss_single: 0.3899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,469 - Iter: 28, Total Loss: 0.3823, loss_single: 0.3823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,504 - Iter: 29, Total Loss: 0.3736, loss_single: 0.3736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,539 - Iter: 30, Total Loss: 0.3651, loss_single: 0.3651, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,574 - Iter: 31, Total Loss: 0.3588, loss_single: 0.3588, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,610 - Iter: 32, Total Loss: 0.3543, loss_single: 0.3543, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,646 - Iter: 33, Total Loss: 0.3499, loss_single: 0.3499, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,681 - Iter: 34, Total Loss: 0.3445, loss_single: 0.3445, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,716 - Iter: 35, Total Loss: 0.3404, loss_single: 0.3404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,752 - Iter: 36, Total Loss: 0.3368, loss_single: 0.3368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,787 - Iter: 37, Total Loss: 0.3334, loss_single: 0.3334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,822 - Iter: 38, Total Loss: 0.3310, loss_single: 0.3310, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,859 - Iter: 39, Total Loss: 0.3287, loss_single: 0.3287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:40:56,894 - Iter: 40, Total Loss: 0.3261, loss_single: 0.3261, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:40:56,931 - Iter: 41, Total Loss: 0.3235, loss_single: 0.3235, 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000000/c30_small__simulation_data_aug2__sample_000000_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-565_C12_-3.36_phi12_63.6_C21_-472_phi21_337_C23_165_phi23_259_C30_2.69e+06_C.61e+06_phi56_307/simulation_data_aug2__sample_000000.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 19.016590118408203 + probe_aberrations: + C10: -564.7379150390625 + C12: -3.361631155014038 + C21: -472.19415283203125 + C23: 165.1547088623047 + C30: 2692416.5 + C32: -9666.91796875 + C34: -3761.156005859375 + C41: -163184.484375 + C43: 288142.375 + C45: 387368.6875 + C50: 485856832.0 + C52: -5371788.5 + C54: 11480743.0 + C56: -7605285.5 + phi12: 63.5665147183685 + phi21: 337.025794480361 + phi23: 259.05978616131245 + phi32: 305.162579511658 + phi34: 14.539867648502193 + phi41: 313.28424817069344 + phi43: 222.60087840956635 + phi45: 217.7653776847641 + phi52: 127.55256697631586 + phi54: 112.70993753247451 + phi56: 307.32236728948607 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3516256809234619 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000000_measurement.h5 + key: measurement + random_seed: 20262115 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/20260624_064450_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..5eac468974405cc88bcf3e24053addcef94e4cc8 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/20260624_064450_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:44:48,711 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:44:48,711 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:44:48,711 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:44:48,711 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:44:48,711 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:44:48,711 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:44:48,711 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:44:48,711 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:44:48,711 - +2026-06-24 06:44:48,819 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:44:48,819 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:44:48,819 - Accelerator.num_process = 1 +2026-06-24 06:44:48,819 - Accelerator.mixed_precision = no +2026-06-24 06:44:48,829 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:44:48,829 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:44:48,829 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:44:48,829 - +2026-06-24 06:44:48,830 - ### System information ### +2026-06-24 06:44:48,830 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:44:48,830 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:44:48,830 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:44:48,830 - Machine: x86_64 +2026-06-24 06:44:48,830 - Processor: x86_64 +2026-06-24 06:44:48,830 - Available CPU cores: 8 +2026-06-24 06:44:48,830 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:44:48,830 - +2026-06-24 06:44:48,830 - ### GPU information ### +2026-06-24 06:44:48,830 - CUDA Available: True +2026-06-24 06:44:48,830 - CUDA Version: 13.0 +2026-06-24 06:44:48,830 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:44:48,831 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:44:48,831 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:44:48,831 - In addition, Triton does not directly support Windows. +2026-06-24 06:44:48,831 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:44:48,846 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:44:48,846 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:44:48,846 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:44:48,846 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:44:48,846 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:44:48,846 - +2026-06-24 06:44:48,846 - ### Python information ### +2026-06-24 06:44:48,848 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:44:48,848 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:44:48,848 - +2026-06-24 06:44:48,848 - ### Packages information ### +2026-06-24 06:44:48,849 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:44:48,849 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:44:48,850 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:44:48,850 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:44:48,851 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:44:48,851 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:44:48,851 - +2026-06-24 06:44:48,851 - ### Loading params file ### +2026-06-24 06:44:48,851 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000016.yaml +2026-06-24 06:44:48,858 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:44:48,859 - Success! Params file validated and defaults applied. +2026-06-24 06:44:48,859 - +2026-06-24 06:44:48,859 - ### Setting GPU Device ### +2026-06-24 06:44:48,859 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:44:48,859 - +2026-06-24 06:44:48,859 - Random seed: 20262131 provided by params file +2026-06-24 06:44:48,859 - ### Initializing Initializer ### +2026-06-24 06:44:48,859 - init_params are displayed below: +2026-06-24 06:44:48,859 - random_seed: 20262131 +2026-06-24 06:44:48,859 - probe_illum_type: electron +2026-06-24 06:44:48,859 - probe_kv: 200.0 +2026-06-24 06:44:48,859 - probe_conv_angle: 14.70396900177002 +2026-06-24 06:44:48,860 - probe_aberrations: {'C10': -533.199, 'C12': -33.872, 'phi12': 344.297, 'C21': -751.996, 'phi21': 344.408, 'C23': -159.937, 'phi23': 293.108, 'C30': 3864985.25, 'C32': -6949.665, 'phi32': 327.853, 'C34': 2164.829, 'phi34': 92.855, 'C41': 62468.414, 'phi41': 96.249, 'C43': 135374.688, 'phi43': 303.636, 'C45': 358734.031, 'phi45': 265.413, 'C50': 291160736.0, 'C52': -4108918.75, 'phi52': 138.797, 'C54': 12030275.0, 'phi54': 160.712, 'C56': 14365078.0, 'phi56': 76.651} +2026-06-24 06:44:48,860 - beam_kev: None +2026-06-24 06:44:48,860 - probe_dRn: None +2026-06-24 06:44:48,860 - probe_Rn: None +2026-06-24 06:44:48,860 - probe_D_H: None +2026-06-24 06:44:48,860 - probe_D_FZP: None +2026-06-24 06:44:48,860 - probe_Ls: None +2026-06-24 06:44:48,860 - meas_Npix: 128 +2026-06-24 06:44:48,860 - pos_N_scans: 256 +2026-06-24 06:44:48,860 - pos_N_scan_slow: 16 +2026-06-24 06:44:48,860 - pos_N_scan_fast: 16 +2026-06-24 06:44:48,860 - pos_scan_step_size: 0.44402602314949036 +2026-06-24 06:44:48,860 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:44:48,860 - probe_pmode_max: 6 +2026-06-24 06:44:48,860 - probe_pmode_init_pows: [0.02] +2026-06-24 06:44:48,860 - obj_omode_max: 1 +2026-06-24 06:44:48,860 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:44:48,860 - obj_Nlayer: 1 +2026-06-24 06:44:48,860 - obj_slice_thickness: 20.0 +2026-06-24 06:44:48,860 - simu_Npix: None +2026-06-24 06:44:48,860 - simu_match_mode: None +2026-06-24 06:44:48,860 - meas_permute: None +2026-06-24 06:44:48,860 - meas_reshape: [256, 128, 128] +2026-06-24 06:44:48,860 - meas_flipT: [0, 0, 0] +2026-06-24 06:44:48,860 - meas_crop: None +2026-06-24 06:44:48,860 - meas_pad: None +2026-06-24 06:44:48,860 - meas_resample: None +2026-06-24 06:44:48,860 - meas_add_source_size: None +2026-06-24 06:44:48,860 - meas_add_detector_blur: None +2026-06-24 06:44:48,860 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:44:48,860 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:44:48,860 - meas_add_poisson_noise: None +2026-06-24 06:44:48,860 - meas_export: None +2026-06-24 06:44:48,860 - probe_permute: None +2026-06-24 06:44:48,860 - probe_z_shift: None +2026-06-24 06:44:48,860 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:44:48,860 - pos_scan_flipT: None +2026-06-24 06:44:48,860 - pos_scan_affine: None +2026-06-24 06:44:48,860 - pos_scan_rand_std: 0.15 +2026-06-24 06:44:48,861 - obj_z_crop: None +2026-06-24 06:44:48,861 - obj_z_pad: None +2026-06-24 06:44:48,861 - obj_z_resample: None +2026-06-24 06:44:48,861 - meas_source: file +2026-06-24 06:44:48,861 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000016_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:44:48,861 - probe_source: simu +2026-06-24 06:44:48,861 - probe_params: None +2026-06-24 06:44:48,861 - pos_source: simu +2026-06-24 06:44:48,861 - pos_params: None +2026-06-24 06:44:48,861 - obj_source: simu +2026-06-24 06:44:48,861 - obj_params: None +2026-06-24 06:44:48,861 - tilt_source: simu +2026-06-24 06:44:48,861 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:44:48,861 - +2026-06-24 06:44:48,861 - ### Initializing cache ### +2026-06-24 06:44:48,861 - use_cached_obj = False +2026-06-24 06:44:48,861 - use_cached_probe = False +2026-06-24 06:44:48,861 - use_cached_pos = False +2026-06-24 06:44:48,861 - +2026-06-24 06:44:48,861 - ### Initializing measurements ### +2026-06-24 06:44:48,861 - Loading measurements from source = 'file' +2026-06-24 06:44:48,861 - Detected measurement file type = '.h5' +2026-06-24 06:44:48,937 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:44:48,937 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:44:48,939 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0020) +2026-06-24 06:44:48,939 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:44:48,939 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:44:48,940 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:44:48,940 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:44:48,941 - Normalizing by max of the 2D mean pattern intensity: 0.001452652 +2026-06-24 06:44:48,941 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:44:48,944 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0420, 1.3664) +2026-06-24 06:44:48,945 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:44:48,947 - Pattern total int. statistics (min, mean, max) = (684.4081, 688.4915, 692.3447), with min/max = 98.9% +2026-06-24 06:44:48,948 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0420, 1.3664) +2026-06-24 06:44:48,948 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:44:48,948 - +2026-06-24 06:44:48,948 - ### Setting up calibration ### +2026-06-24 06:44:48,948 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:44:48,948 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:44:48,948 - Radius of fitted bright field disk (RBF) = 14.92 px with meas_Npix = 128 +2026-06-24 06:44:48,948 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2331 +2026-06-24 06:44:48,948 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:44:48,948 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:44:49,179 - Initial guess: center=(63.62, 63.64), radius=14.92, Gaussian blur std=0.50 +2026-06-24 06:44:49,190 - Final fit: center=(63.62, 63.64), radius=14.92, Gaussian blur std=0.54 +2026-06-24 06:44:49,190 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 15.01 px with Npix = 128 +2026-06-24 06:44:49,190 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:44:49,190 - +2026-06-24 06:44:49,190 - ### Setting init_variables dict ### +2026-06-24 06:44:49,190 - Derived values given input init_params: +2026-06-24 06:44:49,190 - kv = 200.0 kV +2026-06-24 06:44:49,190 - wavelength = 0.0251 Ang +2026-06-24 06:44:49,190 - conv_angle = 14.70396900177002 mrad +2026-06-24 06:44:49,190 - Npix = 128 px +2026-06-24 06:44:49,190 - dk = 0.0391 Ang^-1 +2026-06-24 06:44:49,190 - kMax = 2.5000 Ang^-1 +2026-06-24 06:44:49,190 - da = 0.9797 mrad +2026-06-24 06:44:49,190 - angleMax = 62.6984 mrad +2026-06-24 06:44:49,190 - RBF = 15.0092 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:44:49,190 - n_alpha = 4.2640 (# conv_angle) +2026-06-24 06:44:49,190 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:44:49,190 - Rayleigh-limited resolution = 1.0404 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:44:49,190 - Real space probe extent = 25.6000 Ang +2026-06-24 06:44:49,190 - +2026-06-24 06:44:49,190 - ### Initializing probe ### +2026-06-24 06:44:49,190 - Loading probe from source = 'simu' +2026-06-24 06:44:49,190 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:44:49,191 - Start simulating STEM probe +2026-06-24 06:44:49,191 - kv = 200.0 kV +2026-06-24 06:44:49,191 - wavelength = 0.0251 Ang +2026-06-24 06:44:49,191 - conv_angle = 14.70396900177002 mrad +2026-06-24 06:44:49,191 - Npix = 128 px +2026-06-24 06:44:49,191 - dk = 0.0391 Ang^-1 +2026-06-24 06:44:49,191 - kMax = 2.5000 Ang^-1 +2026-06-24 06:44:49,191 - alpha_max = 62.6984 mrad +2026-06-24 06:44:49,191 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:44:49,191 - Rayleigh-limited resolution = 1.0404 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:44:49,191 - Real space probe extent = 25.6000 Ang +2026-06-24 06:44:49,191 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:44:49,191 - ------------------------------------------------------------------------------------ +2026-06-24 06:44:49,191 - C1,0 C1 -533.1990 - Defocus (C10 = -df) +2026-06-24 06:44:49,191 - C1,2 A1 -33.8720 344.30 2-fold astigmatism +2026-06-24 06:44:49,191 - C2,1 3*B2 -751.9960 344.41 Axial coma +2026-06-24 06:44:49,191 - C2,3 A2 -159.9370 293.11 3-fold astigmatism +2026-06-24 06:44:49,191 - C3,0 C3 3864985.2500 - Spherical aberration +2026-06-24 06:44:49,191 - C3,2 4*S3 -6949.6650 327.85 Axial star aberration +2026-06-24 06:44:49,191 - C3,4 A3 2164.8290 92.86 4-fold astigmatism +2026-06-24 06:44:49,191 - C4,1 4*B4 62468.4140 96.25 Axial coma(4th) +2026-06-24 06:44:49,191 - C4,3 4*D4 135374.6880 303.64 3-lobe aberration +2026-06-24 06:44:49,191 - C4,5 A4 358734.0310 265.41 5-fold astigmatism +2026-06-24 06:44:49,191 - C5,0 C5 291160736.0000 - Spherical aberration (5th) +2026-06-24 06:44:49,191 - C5,2 6*S5 -4108918.7500 138.80 Axial star aberration(5th) +2026-06-24 06:44:49,191 - C5,4 6*R5 12030275.0000 160.71 4-lobe aberration +2026-06-24 06:44:49,191 - C5,6 A5 14365078.0000 76.65 6-fold astigmatism +2026-06-24 06:44:49,195 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:44:49,195 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:44:49,195 - Creating 5 new probe modes from the major mode +2026-06-24 06:44:49,195 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:44:49,364 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:44:49,366 - Orthogonalizing 6 pmodes +2026-06-24 06:44:49,368 - Sorting 6 pmodes by their intensities +2026-06-24 06:44:49,369 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:44:49,369 - sum(|probe_data|**2) = 688.49, while meas_total_ints (min, mean, max) = (684.4081, 688.4915, 692.3447) +2026-06-24 06:44:49,369 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:44:49,370 - +2026-06-24 06:44:49,370 - ### Initializing probe positions ### +2026-06-24 06:44:49,370 - Loading probe positions from source = 'simu' +2026-06-24 06:44:49,370 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:44:49,370 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4440, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:44:49,370 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:44:49,372 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:44:49,372 - crop_pos 1st and last px coords (y,x) = ([16, 16], [49, 50]) +2026-06-24 06:44:49,372 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 06:44:49,372 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:44:49,372 - +2026-06-24 06:44:49,372 - ### Initializing object ### +2026-06-24 06:44:49,372 - Loading object from source = 'simu' +2026-06-24 06:44:49,372 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:44:49,374 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:44:49,374 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 06:44:49,374 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 06:44:49,374 - +2026-06-24 06:44:49,374 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:44:49,374 - omode_occu (omode) = float32, (1,) +2026-06-24 06:44:49,374 - +2026-06-24 06:44:49,374 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:44:49,374 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:44:49,375 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:44:49,375 - +2026-06-24 06:44:49,375 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:44:49,375 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:44:49,375 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:44:49,375 - +2026-06-24 06:44:49,375 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:44:49,375 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:44:49,375 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:44:49,375 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:44:49,375 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:44:49,375 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 06:44:49,375 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:44:49,375 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:44:49,375 - +2026-06-24 06:44:49,375 - ### Collecting reconstruction provenance ### +2026-06-24 06:44:49,376 - Reconstruction provenance is collected and initialized. +2026-06-24 06:44:49,376 - +2026-06-24 06:44:49,376 - ### Initializing loss function ### +2026-06-24 06:44:49,376 - Active loss types: +2026-06-24 06:44:49,376 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:44:49,376 - +2026-06-24 06:44:49,376 - ### Initializing constraint function ### +2026-06-24 06:44:49,376 - Active constraint types: +2026-06-24 06:44:49,376 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:44:49,376 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:44:49,376 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:44:49,376 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:44:49,376 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:44:49,376 - +2026-06-24 06:44:49,376 - ### Done initializing PtyRADSolver ### +2026-06-24 06:44:49,376 - +2026-06-24 06:44:49,500 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:44:49,501 - +2026-06-24 06:44:49,501 - ### Initializing PtychoModel model ### +2026-06-24 06:44:49,571 - ### PtychoModel optimizable variables ### +2026-06-24 06:44:49,571 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:44:49,571 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:44:49,571 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:44:49,572 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:44:49,572 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:44:49,572 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:44:49,572 - +2026-06-24 06:44:49,572 - ### Optimizable variables statitsics ### +2026-06-24 06:44:49,572 - Total measurement values : 4,194,304 +2026-06-24 06:44:49,572 - Total optimizing variables: 272,392 +2026-06-24 06:44:49,572 - Overdetermined ratio : 15.40 +2026-06-24 06:44:49,572 - +2026-06-24 06:44:49,572 - ### Model behavior ### +2026-06-24 06:44:49,572 - Tilt propagator : False +2026-06-24 06:44:49,572 - Change slice thickness : False +2026-06-24 06:44:49,572 - Detector blur : False +2026-06-24 06:44:49,572 - Preload data : True +2026-06-24 06:44:49,572 - On-the-fly meas padding : False +2026-06-24 06:44:49,572 - On-the-fly meas resample : False +2026-06-24 06:44:49,572 - On-the-fly simu match mode: None +2026-06-24 06:44:49,572 - +2026-06-24 06:44:49,614 - ### Done initializing PtychoModel model ### +2026-06-24 06:44:49,614 - +2026-06-24 06:44:49,614 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:44:49,614 - +2026-06-24 06:44:49,614 - ### Generating indices, batches, and output_path ### +2026-06-24 06:44:49,615 - d90 = 37.000 px or 7.400 Ang +2026-06-24 06:44:49,615 - Selecting indices with the 'full' mode +2026-06-24 06:44:50,075 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:44:50,149 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:44:50,149 - Original recon_dir_affixes = ['default'] +2026-06-24 06:44:50,149 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:44:50,156 - Path corrected for compatibility: +2026-06-24 06:44:50,156 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_phi32_328_C34_2.16e+03_phi34_92.9_C41_6.25e+04_phi41_96.2_C43_1.35e+05_phi43_304_C45_3.59e+05_phi45_265_C50_2.91e+08_C52_-4.11e+06_phi52_139_C54_1.2e+07_phi54_161_C56_1.44e+07_phi56_76.7 +2026-06-24 06:44:50,156 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7 +2026-06-24 06:44:50,157 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7' is generated! +2026-06-24 06:44:50,307 - +2026-06-24 06:44:50,308 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/20260624_064450_ptyrad_log.txt ### +2026-06-24 06:44:50,308 - +2026-06-24 06:44:50,309 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:44:50,309 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:44:50,309 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:44:51,496 - Iter: 1, Total Loss: 0.6962, loss_single: 0.6962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:44:51,533 - Iter: 2, Total Loss: 0.6636, loss_single: 0.6636, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:44:51,569 - Iter: 3, Total Loss: 0.6405, loss_single: 0.6405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,605 - Iter: 4, Total Loss: 0.6206, loss_single: 0.6206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:44:51,641 - Iter: 5, Total Loss: 0.5984, loss_single: 0.5984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,677 - Iter: 6, Total Loss: 0.5756, loss_single: 0.5756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:44:51,712 - Iter: 7, Total Loss: 0.5524, loss_single: 0.5524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,748 - Iter: 8, Total Loss: 0.5317, loss_single: 0.5317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,785 - Iter: 9, Total Loss: 0.5176, loss_single: 0.5176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:44:51,820 - Iter: 10, Total Loss: 0.5038, loss_single: 0.5038, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,855 - Iter: 11, Total Loss: 0.4898, loss_single: 0.4898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,891 - Iter: 12, Total Loss: 0.4784, loss_single: 0.4784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,926 - Iter: 13, Total Loss: 0.4640, loss_single: 0.4640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,961 - Iter: 14, Total Loss: 0.4493, loss_single: 0.4493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:51,997 - Iter: 15, Total Loss: 0.4372, loss_single: 0.4372, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:52,032 - Iter: 16, Total Loss: 0.4277, loss_single: 0.4277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:52,067 - Iter: 17, Total Loss: 0.4188, loss_single: 0.4188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:52,103 - Iter: 18, Total Loss: 0.4080, loss_single: 0.4080, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.2647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:55,005 - Iter: 99, Total Loss: 0.2645, loss_single: 0.2645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:44:55,040 - Iter: 100, Total Loss: 0.2645, loss_single: 0.2645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:44:55,150 - Saving summary figures for iter 100 +2026-06-24 06:44:58,756 - ### Finished 100 iterations, averaged iter_t = 0.039171 with std = 0.040 ### +2026-06-24 06:44:58,756 - +2026-06-24 06:44:58,756 - ### The PtyRADSolver is finished in 9.256 sec ### +2026-06-24 06:44:58,756 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/model_iter0100.hdf5 b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/model_iter0100.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..1284a979f2230679445fd8c3259107148bff7b8c --- /dev/null +++ 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/simulation_data_aug2__sample_000016.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/simulation_data_aug2__sample_000016.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d9a718be87bdb6eb330af0838c0c71d28fbf8f03 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/simulation_data_aug2__sample_000016.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 14.70396900177002 + probe_aberrations: + C10: -533.1986083984375 + C12: -33.871559143066406 + C21: -751.9963989257812 + C23: -159.93748474121094 + C30: 3864985.25 + C32: -6949.66455078125 + C34: 2164.828857421875 + C41: 62468.4140625 + C43: 135374.6875 + C45: 358734.03125 + C50: 291160736.0 + C52: -4108918.75 + C54: 12030275.0 + C56: 14365078.0 + phi12: 344.2971592292432 + phi21: 344.4080268598509 + phi23: 293.10847041912274 + phi32: 327.85331487789745 + phi34: 92.85462542657163 + phi41: 96.24896306669034 + phi43: 303.63581366610674 + phi45: 265.4125177875846 + phi52: 138.79724401069126 + phi54: 160.71190596267718 + phi56: 76.65075977171425 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.44402602314949036 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000016_measurement.h5 + key: measurement + random_seed: 20262131 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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0000000000000000000000000000000000000000..ded10deae7a78314f6c3c64e73e1c1f349cab843 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:888ef39bcc452b7478174d15624e8c5c71649aa7f17438450e94596261c202e3 +size 1013303 diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000016/c30_small__simulation_data_aug2__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-533_C12_-33.9_phi12_344_C21_-752_phi21_344_C23_-160_phi23_293_C30_3.86e+06_C32_-6.95e+03_ph.7/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a64ae2f099d5b192bb0f5fe16347dc5cfe5579ff20a3bfa516e689945c649e62 +size 48033 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/20260624_064505_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/20260624_064505_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d06aa646375ffb1f645a56a29cfbfe804ba6b186 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/20260624_064505_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:45:03,556 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:45:03,556 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:45:03,556 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:45:03,556 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:45:03,556 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:45:03,556 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:45:03,556 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:45:03,556 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:45:03,556 - +2026-06-24 06:45:03,666 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:45:03,666 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:45:03,667 - Accelerator.num_process = 1 +2026-06-24 06:45:03,667 - Accelerator.mixed_precision = no +2026-06-24 06:45:03,688 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:45:03,688 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:45:03,689 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:45:03,689 - +2026-06-24 06:45:03,689 - ### System information ### +2026-06-24 06:45:03,689 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:45:03,689 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:45:03,689 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:45:03,689 - Machine: x86_64 +2026-06-24 06:45:03,689 - Processor: x86_64 +2026-06-24 06:45:03,689 - Available CPU cores: 8 +2026-06-24 06:45:03,689 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:45:03,689 - +2026-06-24 06:45:03,689 - ### GPU information ### +2026-06-24 06:45:03,689 - CUDA Available: True +2026-06-24 06:45:03,689 - CUDA Version: 13.0 +2026-06-24 06:45:03,689 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:45:03,690 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:45:03,690 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:45:03,690 - In addition, Triton does not directly support Windows. +2026-06-24 06:45:03,690 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:45:03,705 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:45:03,705 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:45:03,705 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:45:03,705 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:45:03,705 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:45:03,705 - +2026-06-24 06:45:03,705 - ### Python information ### +2026-06-24 06:45:03,706 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:45:03,706 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:45:03,706 - +2026-06-24 06:45:03,706 - ### Packages information ### +2026-06-24 06:45:03,706 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:45:03,707 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:45:03,708 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:45:03,708 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:45:03,709 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:45:03,709 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:45:03,709 - +2026-06-24 06:45:03,709 - ### Loading params file ### +2026-06-24 06:45:03,709 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000017.yaml +2026-06-24 06:45:03,715 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:45:03,716 - Success! Params file validated and defaults applied. +2026-06-24 06:45:03,716 - +2026-06-24 06:45:03,716 - ### Setting GPU Device ### +2026-06-24 06:45:03,716 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:45:03,716 - +2026-06-24 06:45:03,717 - Random seed: 20262132 provided by params file +2026-06-24 06:45:03,717 - ### Initializing Initializer ### +2026-06-24 06:45:03,717 - init_params are displayed below: +2026-06-24 06:45:03,717 - random_seed: 20262132 +2026-06-24 06:45:03,717 - probe_illum_type: electron +2026-06-24 06:45:03,717 - probe_kv: 300.0 +2026-06-24 06:45:03,717 - probe_conv_angle: 10.03967571258545 +2026-06-24 06:45:03,717 - probe_aberrations: {'C10': -592.206, 'C12': 11.744, 'phi12': 89.022, 'C21': 696.932, 'phi21': 194.042, 'C23': -145.503, 'phi23': 125.699, 'C30': 1134286.5, 'C32': -3.074, 'phi32': 192.325, 'C34': 6781.109, 'phi34': 269.369, 'C41': 497771.438, 'phi41': 91.05, 'C43': 372438.969, 'phi43': 357.6, 'C45': -7653.97, 'phi45': 256.608, 'C50': -279318592.0, 'C52': -13222479.0, 'phi52': 334.462, 'C54': 16793126.0, 'phi54': 158.104, 'C56': 12036994.0, 'phi56': 210.04} +2026-06-24 06:45:03,717 - beam_kev: None +2026-06-24 06:45:03,717 - probe_dRn: None +2026-06-24 06:45:03,717 - probe_Rn: None +2026-06-24 06:45:03,717 - probe_D_H: None +2026-06-24 06:45:03,717 - probe_D_FZP: None +2026-06-24 06:45:03,717 - probe_Ls: None +2026-06-24 06:45:03,717 - meas_Npix: 128 +2026-06-24 06:45:03,717 - pos_N_scans: 256 +2026-06-24 06:45:03,717 - pos_N_scan_slow: 16 +2026-06-24 06:45:03,717 - pos_N_scan_fast: 16 +2026-06-24 06:45:03,717 - pos_scan_step_size: 0.41961896419525146 +2026-06-24 06:45:03,717 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:45:03,717 - probe_pmode_max: 6 +2026-06-24 06:45:03,717 - probe_pmode_init_pows: [0.02] +2026-06-24 06:45:03,718 - obj_omode_max: 1 +2026-06-24 06:45:03,718 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:45:03,718 - obj_Nlayer: 1 +2026-06-24 06:45:03,718 - obj_slice_thickness: 20.0 +2026-06-24 06:45:03,718 - simu_Npix: None +2026-06-24 06:45:03,718 - simu_match_mode: None +2026-06-24 06:45:03,718 - meas_permute: None +2026-06-24 06:45:03,718 - meas_reshape: [256, 128, 128] +2026-06-24 06:45:03,718 - meas_flipT: [0, 0, 0] +2026-06-24 06:45:03,718 - meas_crop: None +2026-06-24 06:45:03,718 - meas_pad: None +2026-06-24 06:45:03,718 - meas_resample: None +2026-06-24 06:45:03,718 - meas_add_source_size: None +2026-06-24 06:45:03,718 - meas_add_detector_blur: None +2026-06-24 06:45:03,718 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:45:03,718 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:45:03,718 - meas_add_poisson_noise: None +2026-06-24 06:45:03,718 - meas_export: None +2026-06-24 06:45:03,718 - probe_permute: None +2026-06-24 06:45:03,718 - probe_z_shift: None +2026-06-24 06:45:03,718 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:45:03,718 - pos_scan_flipT: None +2026-06-24 06:45:03,718 - pos_scan_affine: None +2026-06-24 06:45:03,718 - pos_scan_rand_std: 0.15 +2026-06-24 06:45:03,718 - obj_z_crop: None +2026-06-24 06:45:03,718 - obj_z_pad: None +2026-06-24 06:45:03,718 - obj_z_resample: None +2026-06-24 06:45:03,718 - meas_source: file +2026-06-24 06:45:03,718 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000017_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:45:03,718 - probe_source: simu +2026-06-24 06:45:03,718 - probe_params: None +2026-06-24 06:45:03,718 - pos_source: simu +2026-06-24 06:45:03,718 - pos_params: None +2026-06-24 06:45:03,718 - obj_source: simu +2026-06-24 06:45:03,718 - obj_params: None +2026-06-24 06:45:03,718 - tilt_source: simu +2026-06-24 06:45:03,718 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:45:03,718 - +2026-06-24 06:45:03,718 - ### Initializing cache ### +2026-06-24 06:45:03,718 - use_cached_obj = False +2026-06-24 06:45:03,718 - use_cached_probe = False +2026-06-24 06:45:03,719 - use_cached_pos = False +2026-06-24 06:45:03,719 - +2026-06-24 06:45:03,719 - ### Initializing measurements ### +2026-06-24 06:45:03,719 - Loading measurements from source = 'file' +2026-06-24 06:45:03,719 - Detected measurement file type = '.h5' +2026-06-24 06:45:03,795 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:45:03,796 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:45:03,797 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0026) +2026-06-24 06:45:03,797 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:45:03,797 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:45:03,798 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:45:03,798 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:45:03,799 - Normalizing by max of the 2D mean pattern intensity: 0.0018836902 +2026-06-24 06:45:03,799 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:45:03,801 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0324, 1.3834) +2026-06-24 06:45:03,801 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:45:03,803 - Pattern total int. statistics (min, mean, max) = (528.0632, 530.4348, 533.6312), with min/max = 99.0% +2026-06-24 06:45:03,804 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0324, 1.3834) +2026-06-24 06:45:03,804 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:45:03,804 - +2026-06-24 06:45:03,804 - ### Setting up calibration ### +2026-06-24 06:45:03,804 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:45:03,804 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:45:03,804 - Radius of fitted bright field disk (RBF) = 13.00 px with meas_Npix = 128 +2026-06-24 06:45:03,804 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2031 +2026-06-24 06:45:03,804 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:45:03,804 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:45:04,024 - Initial guess: center=(63.63, 63.63), radius=13.00, Gaussian blur std=0.50 +2026-06-24 06:45:04,034 - Final fit: center=(63.63, 63.63), radius=13.00, Gaussian blur std=0.59 +2026-06-24 06:45:04,034 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.05 px with Npix = 128 +2026-06-24 06:45:04,034 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:45:04,034 - +2026-06-24 06:45:04,034 - ### Setting init_variables dict ### +2026-06-24 06:45:04,034 - Derived values given input init_params: +2026-06-24 06:45:04,034 - kv = 300.0 kV +2026-06-24 06:45:04,034 - wavelength = 0.0197 Ang +2026-06-24 06:45:04,034 - conv_angle = 10.03967571258545 mrad +2026-06-24 06:45:04,034 - Npix = 128 px +2026-06-24 06:45:04,034 - dk = 0.0391 Ang^-1 +2026-06-24 06:45:04,035 - kMax = 2.5000 Ang^-1 +2026-06-24 06:45:04,035 - da = 0.7690 mrad +2026-06-24 06:45:04,035 - angleMax = 49.2187 mrad +2026-06-24 06:45:04,035 - RBF = 13.0548 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:45:04,035 - n_alpha = 4.9024 (# conv_angle) +2026-06-24 06:45:04,035 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:45:04,035 - Rayleigh-limited resolution = 1.1962 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:45:04,035 - Real space probe extent = 25.6000 Ang +2026-06-24 06:45:04,035 - +2026-06-24 06:45:04,035 - ### Initializing probe ### +2026-06-24 06:45:04,035 - Loading probe from source = 'simu' +2026-06-24 06:45:04,035 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:45:04,035 - Start simulating STEM probe +2026-06-24 06:45:04,035 - kv = 300.0 kV +2026-06-24 06:45:04,035 - wavelength = 0.0197 Ang +2026-06-24 06:45:04,035 - conv_angle = 10.03967571258545 mrad +2026-06-24 06:45:04,035 - Npix = 128 px +2026-06-24 06:45:04,035 - dk = 0.0391 Ang^-1 +2026-06-24 06:45:04,035 - kMax = 2.5000 Ang^-1 +2026-06-24 06:45:04,035 - alpha_max = 49.2187 mrad +2026-06-24 06:45:04,035 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:45:04,035 - Rayleigh-limited resolution = 1.1962 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:45:04,035 - Real space probe extent = 25.6000 Ang +2026-06-24 06:45:04,035 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:45:04,035 - ------------------------------------------------------------------------------------- +2026-06-24 06:45:04,036 - C1,0 C1 -592.2060 - Defocus (C10 = -df) +2026-06-24 06:45:04,036 - C1,2 A1 11.7440 89.02 2-fold astigmatism +2026-06-24 06:45:04,036 - C2,1 3*B2 696.9320 194.04 Axial coma +2026-06-24 06:45:04,036 - C2,3 A2 -145.5030 125.70 3-fold astigmatism +2026-06-24 06:45:04,036 - C3,0 C3 1134286.5000 - Spherical aberration +2026-06-24 06:45:04,036 - C3,2 4*S3 -3.0740 192.32 Axial star aberration +2026-06-24 06:45:04,036 - C3,4 A3 6781.1090 269.37 4-fold astigmatism +2026-06-24 06:45:04,036 - C4,1 4*B4 497771.4380 91.05 Axial coma(4th) +2026-06-24 06:45:04,036 - C4,3 4*D4 372438.9690 357.60 3-lobe aberration +2026-06-24 06:45:04,036 - C4,5 A4 -7653.9700 256.61 5-fold astigmatism +2026-06-24 06:45:04,036 - C5,0 C5 -279318592.0000 - Spherical aberration (5th) +2026-06-24 06:45:04,036 - C5,2 6*S5 -13222479.0000 334.46 Axial star aberration(5th) +2026-06-24 06:45:04,036 - C5,4 6*R5 16793126.0000 158.10 4-lobe aberration +2026-06-24 06:45:04,036 - C5,6 A5 12036994.0000 210.04 6-fold astigmatism +2026-06-24 06:45:04,039 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:45:04,039 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:45:04,039 - Creating 5 new probe modes from the major mode +2026-06-24 06:45:04,039 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:45:04,235 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:45:04,236 - Orthogonalizing 6 pmodes +2026-06-24 06:45:04,249 - Sorting 6 pmodes by their intensities +2026-06-24 06:45:04,249 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:45:04,250 - sum(|probe_data|**2) = 530.43, while meas_total_ints (min, mean, max) = (528.0632, 530.4348, 533.6312) +2026-06-24 06:45:04,250 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:45:04,250 - +2026-06-24 06:45:04,250 - ### Initializing probe positions ### +2026-06-24 06:45:04,250 - Loading probe positions from source = 'simu' +2026-06-24 06:45:04,250 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:45:04,250 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4196, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:45:04,251 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:45:04,253 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:45:04,253 - crop_pos 1st and last px coords (y,x) = ([16, 16], [47, 48]) +2026-06-24 06:45:04,253 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:45:04,253 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:45:04,253 - +2026-06-24 06:45:04,253 - ### Initializing object ### +2026-06-24 06:45:04,253 - Loading object from source = 'simu' +2026-06-24 06:45:04,253 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:45:04,254 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:45:04,254 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 192, 192) +2026-06-24 06:45:04,255 - object extent (Z, Y, X) (Ang) = [20. 38.4 38.4] +2026-06-24 06:45:04,255 - +2026-06-24 06:45:04,255 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:45:04,255 - omode_occu (omode) = float32, (1,) +2026-06-24 06:45:04,255 - +2026-06-24 06:45:04,255 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:45:04,255 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0197 Ang +2026-06-24 06:45:04,255 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:45:04,256 - +2026-06-24 06:45:04,256 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:45:04,256 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:45:04,256 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:45:04,256 - +2026-06-24 06:45:04,256 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:45:04,256 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:45:04,256 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:45:04,256 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:45:04,256 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:45:04,256 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (192, 192). +2026-06-24 06:45:04,256 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:45:04,256 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:45:04,256 - +2026-06-24 06:45:04,256 - ### Collecting reconstruction provenance ### +2026-06-24 06:45:04,256 - Reconstruction provenance is collected and initialized. +2026-06-24 06:45:04,256 - +2026-06-24 06:45:04,256 - ### Initializing loss function ### +2026-06-24 06:45:04,256 - Active loss types: +2026-06-24 06:45:04,256 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:45:04,256 - +2026-06-24 06:45:04,257 - ### Initializing constraint function ### +2026-06-24 06:45:04,257 - Active constraint types: +2026-06-24 06:45:04,257 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:45:04,257 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:45:04,257 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:45:04,257 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:45:04,257 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:45:04,257 - +2026-06-24 06:45:04,257 - ### Done initializing PtyRADSolver ### +2026-06-24 06:45:04,257 - +2026-06-24 06:45:04,385 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:45:04,385 - +2026-06-24 06:45:04,385 - ### Initializing PtychoModel model ### +2026-06-24 06:45:04,454 - ### PtychoModel optimizable variables ### +2026-06-24 06:45:04,454 - obja : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:45:04,454 - objp : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:45:04,454 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:45:04,454 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:45:04,454 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:45:04,454 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:45:04,454 - +2026-06-24 06:45:04,454 - ### Optimizable variables statitsics ### +2026-06-24 06:45:04,454 - Total measurement values : 4,194,304 +2026-06-24 06:45:04,454 - Total optimizing variables: 270,848 +2026-06-24 06:45:04,454 - Overdetermined ratio : 15.49 +2026-06-24 06:45:04,454 - +2026-06-24 06:45:04,454 - ### Model behavior ### +2026-06-24 06:45:04,454 - Tilt propagator : False +2026-06-24 06:45:04,454 - Change slice thickness : False +2026-06-24 06:45:04,454 - Detector blur : False +2026-06-24 06:45:04,454 - Preload data : True +2026-06-24 06:45:04,454 - On-the-fly meas padding : False +2026-06-24 06:45:04,455 - On-the-fly meas resample : False +2026-06-24 06:45:04,455 - On-the-fly simu match mode: None +2026-06-24 06:45:04,455 - +2026-06-24 06:45:04,496 - ### Done initializing PtychoModel model ### +2026-06-24 06:45:04,497 - +2026-06-24 06:45:04,497 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:45:04,497 - +2026-06-24 06:45:04,497 - ### Generating indices, batches, and output_path ### +2026-06-24 06:45:04,498 - d90 = 57.000 px or 11.400 Ang +2026-06-24 06:45:04,498 - Selecting indices with the 'full' mode +2026-06-24 06:45:04,957 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:45:05,029 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:45:05,029 - Original recon_dir_affixes = ['default'] +2026-06-24 06:45:05,029 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:45:05,035 - Path corrected for compatibility: +2026-06-24 06:45:05,035 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-3.07_phi32_192_C34_6.78e+03_phi34_269_C41_4.98e+05_phi41_91_C43_3.72e+05_phi43_358_C45_-7.65e+03_phi45_257_C50_-2.79e+08_C52_-1.32e+07_phi52_334_C54_1.68e+07_phi54_158_C56_1.2e+07_phi56_210 +2026-06-24 06:45:05,035 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210 +2026-06-24 06:45:05,036 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210' is generated! +2026-06-24 06:45:05,183 - +2026-06-24 06:45:05,184 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/20260624_064505_ptyrad_log.txt ### +2026-06-24 06:45:05,184 - +2026-06-24 06:45:05,186 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:45:05,186 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:45:05,186 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:45:06,376 - Iter: 1, Total Loss: 0.7831, loss_single: 0.7831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:45:06,413 - Iter: 2, Total Loss: 0.7450, loss_single: 0.7450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:45:06,448 - Iter: 3, Total Loss: 0.7128, loss_single: 0.7128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,483 - Iter: 4, Total Loss: 0.6842, loss_single: 0.6842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,518 - Iter: 5, Total Loss: 0.6615, loss_single: 0.6615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,553 - Iter: 6, Total Loss: 0.6389, loss_single: 0.6389, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,588 - Iter: 7, Total Loss: 0.6137, loss_single: 0.6137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:06,623 - Iter: 8, Total Loss: 0.5905, loss_single: 0.5905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,658 - Iter: 9, Total Loss: 0.5666, loss_single: 0.5666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,693 - Iter: 10, Total Loss: 0.5432, loss_single: 0.5432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,728 - Iter: 11, Total Loss: 0.5227, loss_single: 0.5227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,763 - Iter: 12, Total Loss: 0.5015, loss_single: 0.5015, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:06,799 - Iter: 13, Total Loss: 0.4798, loss_single: 0.4798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,833 - Iter: 14, Total Loss: 0.4605, loss_single: 0.4605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:06,869 - Iter: 15, Total Loss: 0.4432, loss_single: 0.4432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,904 - Iter: 16, Total Loss: 0.4246, loss_single: 0.4246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,939 - Iter: 17, Total Loss: 0.4088, loss_single: 0.4088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:06,974 - Iter: 18, Total Loss: 0.3969, loss_single: 0.3969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:07,009 - Iter: 19, Total Loss: 0.3858, loss_single: 0.3858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,044 - Iter: 20, Total Loss: 0.3732, loss_single: 0.3732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,079 - Iter: 21, Total Loss: 0.3580, loss_single: 0.3580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:07,113 - Iter: 22, Total Loss: 0.3477, loss_single: 0.3477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,148 - Iter: 23, Total Loss: 0.3407, loss_single: 0.3407, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,186 - Iter: 24, Total Loss: 0.3326, loss_single: 0.3326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:45:07,221 - Iter: 25, Total Loss: 0.3255, loss_single: 0.3255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,256 - Iter: 26, Total Loss: 0.3189, loss_single: 0.3189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,290 - Iter: 27, Total Loss: 0.3121, loss_single: 0.3121, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,325 - Iter: 28, Total Loss: 0.3059, loss_single: 0.3059, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,360 - Iter: 29, Total Loss: 0.3025, loss_single: 0.3025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,395 - Iter: 30, Total Loss: 0.3002, loss_single: 0.3002, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:07,430 - Iter: 31, Total Loss: 0.2974, loss_single: 0.2974, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,465 - Iter: 32, Total Loss: 0.2951, loss_single: 0.2951, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,500 - Iter: 33, Total Loss: 0.2928, loss_single: 0.2928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:07,534 - Iter: 34, Total Loss: 0.2907, loss_single: 0.2907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,569 - Iter: 35, Total Loss: 0.2889, loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,603 - Iter: 36, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,638 - Iter: 37, Total Loss: 0.2864, loss_single: 0.2864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,673 - Iter: 38, Total Loss: 0.2850, loss_single: 0.2850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:07,708 - Iter: 39, Total Loss: 0.2837, loss_single: 0.2837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,742 - Iter: 40, Total Loss: 0.2827, loss_single: 0.2827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,779 - Iter: 41, Total Loss: 0.2819, loss_single: 0.2819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,814 - Iter: 42, Total Loss: 0.2811, loss_single: 0.2811, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,849 - Iter: 43, Total Loss: 0.2802, loss_single: 0.2802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,883 - Iter: 44, Total Loss: 0.2795, loss_single: 0.2795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,918 - Iter: 45, Total Loss: 0.2789, loss_single: 0.2789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,953 - Iter: 46, Total Loss: 0.2782, loss_single: 0.2782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:07,987 - Iter: 47, Total Loss: 0.2776, loss_single: 0.2776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:08,022 - Iter: 48, Total Loss: 0.2771, loss_single: 0.2771, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:45:08,057 - Iter: 49, Total Loss: 0.2766, loss_single: 0.2766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:45:08,094 - Iter: 50, Total Loss: 0.2760, loss_single: 0.2760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:45:08,135 - Iter: 51, Total Loss: 0.2754, loss_single: 0.2754, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 06:45:08,170 - Iter: 52, Total Loss: 0.2750, loss_single: 0.2750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/simulation_data_aug2__sample_000017.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/simulation_data_aug2__sample_000017.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c24ab201c58da0b607d407507cb2b5a5a9d31dac --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017/c30_small__simulation_data_aug2__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-592_C12_11.7_phi12_89_C21_697_phi21_194_C23_-146_phi23_126_C30_1.13e+06_C32_-.2e+07_phi56_210/simulation_data_aug2__sample_000017.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 300.0 + probe_conv_angle: 10.03967571258545 + probe_aberrations: + C10: -592.2062377929688 + C12: 11.74423599243164 + C21: 696.931884765625 + C23: -145.5026092529297 + C30: 1134286.5 + C32: -3.074340343475342 + C34: 6781.109375 + C41: 497771.4375 + C43: 372438.96875 + C45: -7653.9697265625 + C50: -279318592.0 + C52: -13222479.0 + C54: 16793126.0 + C56: 12036994.0 + phi12: 89.021905754954 + phi21: 194.042409489639 + phi23: 125.69927710730295 + phi32: 192.3254775172162 + phi34: 269.3692190530163 + phi41: 91.04991186293584 + phi43: 357.59960833600337 + phi45: 256.60834930592483 + phi52: 334.46212395653174 + phi54: 158.10412607718797 + phi56: 210.04007856364285 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.41961896419525146 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000017_measurement.h5 + key: measurement + random_seed: 20262132 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000017 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218/20260624_064719_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf475043a3cee6821c6c9751706652051c81598e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218/20260624_064719_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:47:17,406 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:47:17,407 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:47:17,407 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:47:17,407 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:47:17,407 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:47:17,407 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:47:17,407 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:47:17,407 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:47:17,407 - +2026-06-24 06:47:17,514 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:47:17,514 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:47:17,514 - Accelerator.num_process = 1 +2026-06-24 06:47:17,514 - Accelerator.mixed_precision = no +2026-06-24 06:47:17,525 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:47:17,525 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:47:17,525 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:47:17,525 - +2026-06-24 06:47:17,525 - ### System information ### +2026-06-24 06:47:17,525 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:47:17,525 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:47:17,525 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:47:17,525 - Machine: x86_64 +2026-06-24 06:47:17,525 - Processor: x86_64 +2026-06-24 06:47:17,525 - Available CPU cores: 8 +2026-06-24 06:47:17,525 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:47:17,525 - +2026-06-24 06:47:17,525 - ### GPU information ### +2026-06-24 06:47:17,525 - CUDA Available: True +2026-06-24 06:47:17,525 - CUDA Version: 13.0 +2026-06-24 06:47:17,526 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:47:17,526 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:47:17,526 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:47:17,526 - In addition, Triton does not directly support Windows. +2026-06-24 06:47:17,526 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:47:17,541 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:47:17,541 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:47:17,541 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:47:17,541 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:47:17,541 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:47:17,541 - +2026-06-24 06:47:17,541 - ### Python information ### +2026-06-24 06:47:17,543 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:47:17,543 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:47:17,543 - +2026-06-24 06:47:17,543 - ### Packages information ### +2026-06-24 06:47:17,543 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:47:17,544 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:47:17,545 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:47:17,545 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:47:17,546 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:47:17,546 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:47:17,546 - +2026-06-24 06:47:17,546 - ### Loading params file ### +2026-06-24 06:47:17,546 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000026.yaml +2026-06-24 06:47:17,552 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:47:17,553 - Success! Params file validated and defaults applied. +2026-06-24 06:47:17,553 - +2026-06-24 06:47:17,554 - ### Setting GPU Device ### +2026-06-24 06:47:17,554 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:47:17,554 - +2026-06-24 06:47:17,554 - Random seed: 20262141 provided by params file +2026-06-24 06:47:17,554 - ### Initializing Initializer ### +2026-06-24 06:47:17,554 - init_params are displayed below: +2026-06-24 06:47:17,554 - random_seed: 20262141 +2026-06-24 06:47:17,554 - probe_illum_type: electron +2026-06-24 06:47:17,554 - probe_kv: 100.0 +2026-06-24 06:47:17,554 - probe_conv_angle: 9.42147445678711 +2026-06-24 06:47:17,554 - probe_aberrations: {'C10': -421.511, 'C12': -48.754, 'phi12': 214.439, 'C21': 362.83, 'phi21': 164.937, 'C23': 525.757, 'phi23': 3.501, 'C30': 845018.875, 'C32': -3747.513, 'phi32': 326.418, 'C34': 3120.769, 'phi34': 111.566, 'C41': -344759.281, 'phi41': 168.984, 'C43': 168714.328, 'phi43': 246.404, 'C45': 279517.125, 'phi45': 356.551, 'C50': 451527552.0, 'C52': -17298446.0, 'phi52': 353.549, 'C54': -15109052.0, 'phi54': 207.827, 'C56': -6703240.0, 'phi56': 217.886} +2026-06-24 06:47:17,554 - beam_kev: None +2026-06-24 06:47:17,554 - probe_dRn: None +2026-06-24 06:47:17,555 - probe_Rn: None +2026-06-24 06:47:17,555 - probe_D_H: None +2026-06-24 06:47:17,555 - probe_D_FZP: None +2026-06-24 06:47:17,555 - probe_Ls: None +2026-06-24 06:47:17,555 - meas_Npix: 128 +2026-06-24 06:47:17,555 - pos_N_scans: 256 +2026-06-24 06:47:17,555 - pos_N_scan_slow: 16 +2026-06-24 06:47:17,555 - pos_N_scan_fast: 16 +2026-06-24 06:47:17,555 - pos_scan_step_size: 0.41965925693511963 +2026-06-24 06:47:17,555 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:47:17,555 - probe_pmode_max: 6 +2026-06-24 06:47:17,555 - probe_pmode_init_pows: [0.02] +2026-06-24 06:47:17,555 - obj_omode_max: 1 +2026-06-24 06:47:17,555 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:47:17,555 - obj_Nlayer: 1 +2026-06-24 06:47:17,555 - obj_slice_thickness: 20.0 +2026-06-24 06:47:17,555 - simu_Npix: None +2026-06-24 06:47:17,555 - simu_match_mode: None +2026-06-24 06:47:17,555 - meas_permute: None +2026-06-24 06:47:17,555 - meas_reshape: [256, 128, 128] +2026-06-24 06:47:17,555 - meas_flipT: [0, 0, 0] +2026-06-24 06:47:17,555 - meas_crop: None +2026-06-24 06:47:17,555 - meas_pad: None +2026-06-24 06:47:17,555 - meas_resample: None +2026-06-24 06:47:17,555 - meas_add_source_size: None +2026-06-24 06:47:17,555 - meas_add_detector_blur: None +2026-06-24 06:47:17,555 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:47:17,555 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:47:17,555 - meas_add_poisson_noise: None +2026-06-24 06:47:17,555 - meas_export: None +2026-06-24 06:47:17,555 - probe_permute: None +2026-06-24 06:47:17,555 - probe_z_shift: None +2026-06-24 06:47:17,555 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:47:17,555 - pos_scan_flipT: None +2026-06-24 06:47:17,555 - pos_scan_affine: None +2026-06-24 06:47:17,555 - pos_scan_rand_std: 0.15 +2026-06-24 06:47:17,555 - obj_z_crop: None +2026-06-24 06:47:17,556 - obj_z_pad: None +2026-06-24 06:47:17,556 - obj_z_resample: None +2026-06-24 06:47:17,556 - meas_source: file +2026-06-24 06:47:17,556 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000026_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:47:17,556 - probe_source: simu +2026-06-24 06:47:17,556 - probe_params: None +2026-06-24 06:47:17,556 - pos_source: simu +2026-06-24 06:47:17,556 - pos_params: None +2026-06-24 06:47:17,556 - obj_source: simu +2026-06-24 06:47:17,556 - obj_params: None +2026-06-24 06:47:17,556 - tilt_source: simu +2026-06-24 06:47:17,556 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:47:17,556 - +2026-06-24 06:47:17,556 - ### Initializing cache ### +2026-06-24 06:47:17,556 - use_cached_obj = False +2026-06-24 06:47:17,556 - use_cached_probe = False +2026-06-24 06:47:17,556 - use_cached_pos = False +2026-06-24 06:47:17,556 - +2026-06-24 06:47:17,556 - ### Initializing measurements ### +2026-06-24 06:47:17,556 - Loading measurements from source = 'file' +2026-06-24 06:47:17,556 - Detected measurement file type = '.h5' +2026-06-24 06:47:17,636 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:47:17,636 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:47:17,638 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0087) +2026-06-24 06:47:17,638 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:47:17,638 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:47:17,639 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:47:17,639 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:47:17,640 - Normalizing by max of the 2D mean pattern intensity: 0.0074840323 +2026-06-24 06:47:17,640 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:47:17,642 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0082, 1.1571) +2026-06-24 06:47:17,642 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:47:17,643 - Pattern total int. statistics (min, mean, max) = (132.6178, 133.5731, 134.8552), with min/max = 98.3% +2026-06-24 06:47:17,645 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0082, 1.1571) +2026-06-24 06:47:17,645 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:47:17,645 - +2026-06-24 06:47:17,645 - ### Setting up calibration ### +2026-06-24 06:47:17,645 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:47:17,645 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:47:17,645 - Radius of fitted bright field disk (RBF) = 6.38 px with meas_Npix = 128 +2026-06-24 06:47:17,645 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.0997 +2026-06-24 06:47:17,645 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:47:17,645 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:47:17,873 - Initial guess: center=(63.63, 63.62), radius=6.38, Gaussian blur std=0.50 +2026-06-24 06:47:17,885 - Final fit: center=(63.63, 63.62), radius=6.38, Gaussian blur std=0.65 +2026-06-24 06:47:17,886 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.52 px with Npix = 128 +2026-06-24 06:47:17,886 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:47:17,886 - +2026-06-24 06:47:17,886 - ### Setting init_variables dict ### +2026-06-24 06:47:17,886 - Derived values given input init_params: +2026-06-24 06:47:17,886 - kv = 100.0 kV +2026-06-24 06:47:17,886 - wavelength = 0.0370 Ang +2026-06-24 06:47:17,886 - conv_angle = 9.42147445678711 mrad +2026-06-24 06:47:17,886 - Npix = 128 px +2026-06-24 06:47:17,886 - dk = 0.0391 Ang^-1 +2026-06-24 06:47:17,886 - kMax = 2.5000 Ang^-1 +2026-06-24 06:47:17,886 - da = 1.4459 mrad +2026-06-24 06:47:17,886 - angleMax = 92.5359 mrad +2026-06-24 06:47:17,886 - RBF = 6.5161 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:47:17,886 - n_alpha = 9.8218 (# conv_angle) +2026-06-24 06:47:17,886 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:47:17,886 - Rayleigh-limited resolution = 2.3965 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:47:17,886 - Real space probe extent = 25.6000 Ang +2026-06-24 06:47:17,886 - +2026-06-24 06:47:17,886 - ### Initializing probe ### +2026-06-24 06:47:17,886 - Loading probe from source = 'simu' +2026-06-24 06:47:17,886 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:47:17,886 - Start simulating STEM probe +2026-06-24 06:47:17,886 - kv = 100.0 kV +2026-06-24 06:47:17,887 - wavelength = 0.0370 Ang +2026-06-24 06:47:17,887 - conv_angle = 9.42147445678711 mrad +2026-06-24 06:47:17,887 - Npix = 128 px +2026-06-24 06:47:17,887 - dk = 0.0391 Ang^-1 +2026-06-24 06:47:17,887 - kMax = 2.5000 Ang^-1 +2026-06-24 06:47:17,887 - alpha_max = 92.5359 mrad +2026-06-24 06:47:17,887 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:47:17,887 - Rayleigh-limited resolution = 2.3965 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:47:17,887 - Real space probe extent = 25.6000 Ang +2026-06-24 06:47:17,887 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:47:17,887 - ------------------------------------------------------------------------------------ +2026-06-24 06:47:17,887 - C1,0 C1 -421.5110 - Defocus (C10 = -df) +2026-06-24 06:47:17,887 - C1,2 A1 -48.7540 214.44 2-fold astigmatism +2026-06-24 06:47:17,887 - C2,1 3*B2 362.8300 164.94 Axial coma +2026-06-24 06:47:17,887 - C2,3 A2 525.7570 3.50 3-fold astigmatism +2026-06-24 06:47:17,887 - C3,0 C3 845018.8750 - Spherical aberration +2026-06-24 06:47:17,887 - C3,2 4*S3 -3747.5130 326.42 Axial star aberration +2026-06-24 06:47:17,887 - C3,4 A3 3120.7690 111.57 4-fold astigmatism +2026-06-24 06:47:17,887 - C4,1 4*B4 -344759.2810 168.98 Axial coma(4th) +2026-06-24 06:47:17,887 - C4,3 4*D4 168714.3280 246.40 3-lobe aberration +2026-06-24 06:47:17,887 - C4,5 A4 279517.1250 356.55 5-fold astigmatism +2026-06-24 06:47:17,887 - C5,0 C5 451527552.0000 - Spherical aberration (5th) +2026-06-24 06:47:17,887 - C5,2 6*S5 -17298446.0000 353.55 Axial star aberration(5th) +2026-06-24 06:47:17,887 - C5,4 6*R5 -15109052.0000 207.83 4-lobe aberration +2026-06-24 06:47:17,887 - C5,6 A5 -6703240.0000 217.89 6-fold astigmatism +2026-06-24 06:47:17,890 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:47:17,890 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:47:17,890 - Creating 5 new probe modes from the major mode +2026-06-24 06:47:17,890 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:47:18,119 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:47:18,120 - Orthogonalizing 6 pmodes +2026-06-24 06:47:18,131 - Sorting 6 pmodes by their intensities +2026-06-24 06:47:18,131 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:47:18,132 - sum(|probe_data|**2) = 133.57, while meas_total_ints (min, mean, max) = (132.6178, 133.5731, 134.8552) +2026-06-24 06:47:18,132 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:47:18,132 - +2026-06-24 06:47:18,132 - ### Initializing probe positions ### +2026-06-24 06:47:18,132 - Loading probe positions from source = 'simu' +2026-06-24 06:47:18,132 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:47:18,132 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4197, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:47:18,132 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:47:18,134 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:47:18,134 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 06:47:18,135 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:47:18,135 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:47:18,135 - +2026-06-24 06:47:18,135 - ### Initializing object ### +2026-06-24 06:47:18,135 - Loading object from source = 'simu' +2026-06-24 06:47:18,135 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:47:18,136 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:47:18,136 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 193, 193) +2026-06-24 06:47:18,136 - object extent (Z, Y, X) (Ang) = [20. 38.6 38.6] +2026-06-24 06:47:18,136 - +2026-06-24 06:47:18,136 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:47:18,136 - omode_occu (omode) = float32, (1,) +2026-06-24 06:47:18,137 - +2026-06-24 06:47:18,137 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:47:18,137 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0370 Ang +2026-06-24 06:47:18,137 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:47:18,137 - +2026-06-24 06:47:18,137 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:47:18,137 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:47:18,137 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:47:18,137 - +2026-06-24 06:47:18,137 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:47:18,137 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:47:18,137 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:47:18,138 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:47:18,138 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:47:18,138 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (193, 193). +2026-06-24 06:47:18,138 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:47:18,138 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:47:18,138 - +2026-06-24 06:47:18,138 - ### Collecting reconstruction provenance ### +2026-06-24 06:47:18,138 - Reconstruction provenance is collected and initialized. +2026-06-24 06:47:18,138 - +2026-06-24 06:47:18,138 - ### Initializing loss function ### +2026-06-24 06:47:18,138 - Active loss types: +2026-06-24 06:47:18,138 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:47:18,138 - +2026-06-24 06:47:18,138 - ### Initializing constraint function ### +2026-06-24 06:47:18,138 - Active constraint types: +2026-06-24 06:47:18,138 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:47:18,138 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:47:18,138 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:47:18,138 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:47:18,138 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:47:18,138 - +2026-06-24 06:47:18,139 - ### Done initializing PtyRADSolver ### +2026-06-24 06:47:18,139 - +2026-06-24 06:47:18,263 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:47:18,263 - +2026-06-24 06:47:18,263 - ### Initializing PtychoModel model ### +2026-06-24 06:47:18,333 - ### PtychoModel optimizable variables ### +2026-06-24 06:47:18,333 - obja : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:47:18,333 - objp : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:47:18,333 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:47:18,333 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:47:18,333 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:47:18,333 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:47:18,333 - +2026-06-24 06:47:18,333 - ### Optimizable variables statitsics ### +2026-06-24 06:47:18,333 - Total measurement values : 4,194,304 +2026-06-24 06:47:18,333 - Total optimizing variables: 271,618 +2026-06-24 06:47:18,333 - Overdetermined ratio : 15.44 +2026-06-24 06:47:18,333 - +2026-06-24 06:47:18,333 - ### Model behavior ### +2026-06-24 06:47:18,334 - Tilt propagator : False +2026-06-24 06:47:18,334 - Change slice thickness : False +2026-06-24 06:47:18,334 - Detector blur : False +2026-06-24 06:47:18,334 - Preload data : True +2026-06-24 06:47:18,334 - On-the-fly meas padding : False +2026-06-24 06:47:18,334 - On-the-fly meas resample : False +2026-06-24 06:47:18,334 - On-the-fly simu match mode: None +2026-06-24 06:47:18,334 - +2026-06-24 06:47:18,375 - ### Done initializing PtychoModel model ### +2026-06-24 06:47:18,376 - +2026-06-24 06:47:18,376 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:47:18,376 - +2026-06-24 06:47:18,376 - ### Generating indices, batches, and output_path ### +2026-06-24 06:47:18,377 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:47:18,377 - Selecting indices with the 'full' mode +2026-06-24 06:47:18,836 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:47:18,909 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:47:18,909 - Original recon_dir_affixes = ['default'] +2026-06-24 06:47:18,909 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:47:18,916 - Path corrected for compatibility: +2026-06-24 06:47:18,916 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_-3.75e+03_phi32_326_C34_3.12e+03_phi34_112_C41_-3.45e+05_phi41_169_C43_1.69e+05_phi43_246_C45_2.8e+05_phi45_357_C50_4.52e+08_C52_-1.73e+07_phi52_354_C54_-1.51e+07_phi54_208_C56_-6.7e+06_phi56_218 +2026-06-24 06:47:18,916 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218 +2026-06-24 06:47:18,917 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218' is generated! +2026-06-24 06:47:19,064 - +2026-06-24 06:47:19,065 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218/20260624_064719_ptyrad_log.txt ### +2026-06-24 06:47:19,065 - +2026-06-24 06:47:19,067 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:47:19,067 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:47:19,067 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:47:20,258 - Iter: 1, Total Loss: 1.2305, loss_single: 1.2305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:47:20,295 - Iter: 2, Total Loss: 1.1300, loss_single: 1.1300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:47:20,331 - Iter: 3, Total Loss: 1.0537, loss_single: 1.0537, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,366 - Iter: 4, Total Loss: 0.9804, loss_single: 0.9804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,402 - Iter: 5, Total Loss: 0.9162, loss_single: 0.9162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,438 - Iter: 6, Total Loss: 0.8598, loss_single: 0.8598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,474 - Iter: 7, Total Loss: 0.8009, loss_single: 0.8009, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,510 - Iter: 8, Total Loss: 0.7455, loss_single: 0.7455, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,545 - Iter: 9, Total Loss: 0.7000, loss_single: 0.7000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,581 - Iter: 10, Total Loss: 0.6633, loss_single: 0.6633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,617 - Iter: 11, Total Loss: 0.6313, loss_single: 0.6313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,652 - Iter: 12, Total Loss: 0.5953, loss_single: 0.5953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,688 - Iter: 13, Total Loss: 0.5557, loss_single: 0.5557, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,724 - Iter: 14, Total Loss: 0.5185, loss_single: 0.5185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,759 - Iter: 15, Total Loss: 0.4824, loss_single: 0.4824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,795 - Iter: 16, Total Loss: 0.4596, loss_single: 0.4596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,831 - Iter: 17, Total Loss: 0.4479, loss_single: 0.4479, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,866 - Iter: 18, Total Loss: 0.4404, loss_single: 0.4404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,902 - Iter: 19, Total Loss: 0.4337, loss_single: 0.4337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:20,938 - Iter: 20, Total Loss: 0.4229, loss_single: 0.4229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:20,974 - Iter: 21, Total Loss: 0.4167, loss_single: 0.4167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,009 - Iter: 22, Total Loss: 0.4124, loss_single: 0.4124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,045 - Iter: 23, Total Loss: 0.4069, loss_single: 0.4069, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,080 - Iter: 24, Total Loss: 0.4029, loss_single: 0.4029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,116 - Iter: 25, Total Loss: 0.4003, loss_single: 0.4003, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,151 - Iter: 26, Total Loss: 0.3984, loss_single: 0.3984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,187 - Iter: 27, Total Loss: 0.3961, loss_single: 0.3961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,223 - Iter: 28, Total Loss: 0.3938, loss_single: 0.3938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:21,258 - Iter: 29, Total Loss: 0.3922, loss_single: 0.3922, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,294 - Iter: 30, Total Loss: 0.3909, loss_single: 0.3909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,330 - Iter: 31, Total Loss: 0.3898, loss_single: 0.3898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,365 - Iter: 32, Total Loss: 0.3889, loss_single: 0.3889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,401 - Iter: 33, Total Loss: 0.3881, loss_single: 0.3881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,436 - Iter: 34, Total Loss: 0.3873, loss_single: 0.3873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,473 - Iter: 35, Total Loss: 0.3866, loss_single: 0.3866, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:21,508 - Iter: 36, Total Loss: 0.3860, loss_single: 0.3860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,544 - Iter: 37, Total Loss: 0.3854, loss_single: 0.3854, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,580 - Iter: 38, Total Loss: 0.3848, loss_single: 0.3848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:21,615 - Iter: 39, Total Loss: 0.3842, loss_single: 0.3842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,650 - Iter: 40, Total Loss: 0.3836, loss_single: 0.3836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,687 - Iter: 41, Total Loss: 0.3831, loss_single: 0.3831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,722 - Iter: 42, Total Loss: 0.3825, loss_single: 0.3825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,758 - Iter: 43, Total Loss: 0.3819, loss_single: 0.3819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,794 - Iter: 44, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,829 - Iter: 45, Total Loss: 0.3807, loss_single: 0.3807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,865 - Iter: 46, Total Loss: 0.3801, loss_single: 0.3801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,901 - Iter: 47, Total Loss: 0.3794, loss_single: 0.3794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,936 - Iter: 48, Total Loss: 0.3788, loss_single: 0.3788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:21,971 - Iter: 49, Total Loss: 0.3780, loss_single: 0.3780, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,007 - Iter: 50, Total Loss: 0.3772, loss_single: 0.3772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,043 - Iter: 51, Total Loss: 0.3765, loss_single: 0.3765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,078 - Iter: 52, Total Loss: 0.3756, loss_single: 0.3756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,114 - Iter: 53, Total Loss: 0.3749, loss_single: 0.3749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,149 - Iter: 54, Total Loss: 0.3740, loss_single: 0.3740, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,185 - Iter: 55, Total Loss: 0.3732, loss_single: 0.3732, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,220 - Iter: 56, Total Loss: 0.3723, loss_single: 0.3723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,256 - Iter: 57, Total Loss: 0.3716, loss_single: 0.3716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,292 - Iter: 58, Total Loss: 0.3707, loss_single: 0.3707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,328 - Iter: 59, Total Loss: 0.3698, loss_single: 0.3698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:22,363 - Iter: 60, Total Loss: 0.3689, loss_single: 0.3689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,399 - Iter: 61, Total Loss: 0.3681, loss_single: 0.3681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,436 - Iter: 62, Total Loss: 0.3674, loss_single: 0.3674, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:47:22,471 - Iter: 63, Total Loss: 0.3665, loss_single: 0.3665, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,506 - Iter: 64, Total Loss: 0.3655, loss_single: 0.3655, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,542 - Iter: 65, Total Loss: 0.3647, loss_single: 0.3647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,578 - Iter: 66, Total Loss: 0.3640, loss_single: 0.3640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,613 - Iter: 67, Total Loss: 0.3632, loss_single: 0.3632, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,648 - Iter: 68, Total Loss: 0.3622, loss_single: 0.3622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,683 - Iter: 69, Total Loss: 0.3614, loss_single: 0.3614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,719 - Iter: 70, Total Loss: 0.3608, loss_single: 0.3608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,755 - Iter: 71, Total Loss: 0.3601, loss_single: 0.3601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,790 - Iter: 72, Total Loss: 0.3592, loss_single: 0.3592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,825 - Iter: 73, Total Loss: 0.3585, loss_single: 0.3585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,861 - Iter: 74, Total Loss: 0.3576, loss_single: 0.3576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:22,897 - Iter: 75, Total Loss: 0.3569, loss_single: 0.3569, loss_poissn: 0.0000, loss_pacbed: 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0.3450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:23,748 - Iter: 99, Total Loss: 0.3447, loss_single: 0.3447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:47:23,783 - Iter: 100, Total Loss: 0.3444, loss_single: 0.3444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:47:23,894 - Saving summary figures for iter 100 +2026-06-24 06:47:27,421 - ### Finished 100 iterations, averaged iter_t = 0.039184 with std = 0.040 ### +2026-06-24 06:47:27,421 - +2026-06-24 06:47:27,422 - ### The PtyRADSolver is finished in 9.159 sec ### +2026-06-24 06:47:27,422 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000026/c30_small__simulation_data_aug2__sample_000026_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-422_C12_-48.8_phi12_214_C21_363_phi21_165_C23_526_phi23_3.5_C30_8.45e+05_C32_.7e+06_phi56_218/simulation_data_aug2__sample_000026.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 100.0 + probe_conv_angle: 9.42147445678711 + probe_aberrations: + C10: -421.5107421875 + C12: -48.753936767578125 + C21: 362.83001708984375 + C23: 525.7565307617188 + C30: 845018.875 + C32: -3747.51318359375 + C34: 3120.769287109375 + C41: -344759.28125 + C43: 168714.328125 + C45: 279517.125 + C50: 451527552.0 + C52: -17298446.0 + C54: -15109052.0 + C56: -6703240.0 + phi12: 214.43910287972457 + phi21: 164.9370063417337 + phi23: 3.501053582928044 + phi32: 326.41790964268426 + phi34: 111.56637945030678 + phi41: 168.98403002874966 + phi43: 246.4036915160889 + phi45: 356.5510650153797 + phi52: 353.54903295061905 + phi54: 207.82659183856015 + phi56: 217.886258372695 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.41965925693511963 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000026_measurement.h5 + key: measurement + random_seed: 20262141 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4/20260624_064847_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..deb6a64b044502db34f6d0b950cafdb3ccba618f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4/20260624_064847_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:48:45,693 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:48:45,693 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:48:45,693 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:48:45,693 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:48:45,693 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:48:45,693 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:48:45,693 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:48:45,693 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:48:45,693 - +2026-06-24 06:48:45,798 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:48:45,798 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:48:45,798 - Accelerator.num_process = 1 +2026-06-24 06:48:45,798 - Accelerator.mixed_precision = no +2026-06-24 06:48:45,808 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:48:45,809 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:48:45,809 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:48:45,809 - +2026-06-24 06:48:45,809 - ### System information ### +2026-06-24 06:48:45,809 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:48:45,809 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:48:45,809 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:48:45,809 - Machine: x86_64 +2026-06-24 06:48:45,809 - Processor: x86_64 +2026-06-24 06:48:45,809 - Available CPU cores: 8 +2026-06-24 06:48:45,809 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:48:45,809 - +2026-06-24 06:48:45,809 - ### GPU information ### +2026-06-24 06:48:45,809 - CUDA Available: True +2026-06-24 06:48:45,809 - CUDA Version: 13.0 +2026-06-24 06:48:45,810 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:48:45,810 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:48:45,810 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:48:45,810 - In addition, Triton does not directly support Windows. +2026-06-24 06:48:45,810 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:48:45,825 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:48:45,825 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:48:45,825 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:48:45,825 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:48:45,825 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:48:45,825 - +2026-06-24 06:48:45,825 - ### Python information ### +2026-06-24 06:48:45,827 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:48:45,827 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:48:45,827 - +2026-06-24 06:48:45,827 - ### Packages information ### +2026-06-24 06:48:45,828 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:48:45,829 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:48:45,829 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:48:45,830 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:48:45,830 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:48:45,830 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:48:45,830 - +2026-06-24 06:48:45,830 - ### Loading params file ### +2026-06-24 06:48:45,830 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000032.yaml +2026-06-24 06:48:45,837 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:48:45,838 - Success! Params file validated and defaults applied. +2026-06-24 06:48:45,838 - +2026-06-24 06:48:45,838 - ### Setting GPU Device ### +2026-06-24 06:48:45,838 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:48:45,838 - +2026-06-24 06:48:45,838 - Random seed: 20262147 provided by params file +2026-06-24 06:48:45,838 - ### Initializing Initializer ### +2026-06-24 06:48:45,839 - init_params are displayed below: +2026-06-24 06:48:45,839 - random_seed: 20262147 +2026-06-24 06:48:45,839 - probe_illum_type: electron +2026-06-24 06:48:45,839 - probe_kv: 80.0 +2026-06-24 06:48:45,839 - probe_conv_angle: 15.631131172180176 +2026-06-24 06:48:45,839 - probe_aberrations: {'C10': -657.596, 'C12': -20.379, 'phi12': 3.545, 'C21': 979.629, 'phi21': 64.531, 'C23': 170.292, 'phi23': 120.187, 'C30': 4900453.5, 'C32': 7783.228, 'phi32': 115.151, 'C34': -2903.454, 'phi34': 287.986, 'C41': 59963.23, 'phi41': 30.574, 'C43': -434621.312, 'phi43': 100.395, 'C45': 188257.672, 'phi45': 67.01, 'C50': -366283104.0, 'C52': 18804352.0, 'phi52': 213.998, 'C54': 17784624.0, 'phi54': 186.52, 'C56': 9836762.0, 'phi56': 36.4} +2026-06-24 06:48:45,839 - beam_kev: None +2026-06-24 06:48:45,839 - probe_dRn: None +2026-06-24 06:48:45,839 - probe_Rn: None +2026-06-24 06:48:45,839 - probe_D_H: None +2026-06-24 06:48:45,839 - probe_D_FZP: None +2026-06-24 06:48:45,839 - probe_Ls: None +2026-06-24 06:48:45,839 - meas_Npix: 128 +2026-06-24 06:48:45,839 - pos_N_scans: 256 +2026-06-24 06:48:45,839 - pos_N_scan_slow: 16 +2026-06-24 06:48:45,839 - pos_N_scan_fast: 16 +2026-06-24 06:48:45,839 - pos_scan_step_size: 0.42182475328445435 +2026-06-24 06:48:45,839 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:48:45,839 - probe_pmode_max: 6 +2026-06-24 06:48:45,839 - probe_pmode_init_pows: [0.02] +2026-06-24 06:48:45,839 - obj_omode_max: 1 +2026-06-24 06:48:45,839 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:48:45,839 - obj_Nlayer: 1 +2026-06-24 06:48:45,839 - obj_slice_thickness: 20.0 +2026-06-24 06:48:45,839 - simu_Npix: None +2026-06-24 06:48:45,839 - simu_match_mode: None +2026-06-24 06:48:45,839 - meas_permute: None +2026-06-24 06:48:45,839 - meas_reshape: [256, 128, 128] +2026-06-24 06:48:45,839 - meas_flipT: [0, 0, 0] +2026-06-24 06:48:45,839 - meas_crop: None +2026-06-24 06:48:45,839 - meas_pad: None +2026-06-24 06:48:45,839 - meas_resample: None +2026-06-24 06:48:45,839 - meas_add_source_size: None +2026-06-24 06:48:45,839 - meas_add_detector_blur: None +2026-06-24 06:48:45,839 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:48:45,839 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:48:45,839 - meas_add_poisson_noise: None +2026-06-24 06:48:45,839 - meas_export: None +2026-06-24 06:48:45,840 - probe_permute: None +2026-06-24 06:48:45,840 - probe_z_shift: None +2026-06-24 06:48:45,840 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:48:45,840 - pos_scan_flipT: None +2026-06-24 06:48:45,840 - pos_scan_affine: None +2026-06-24 06:48:45,840 - pos_scan_rand_std: 0.15 +2026-06-24 06:48:45,840 - obj_z_crop: None +2026-06-24 06:48:45,840 - obj_z_pad: None +2026-06-24 06:48:45,840 - obj_z_resample: None +2026-06-24 06:48:45,840 - meas_source: file +2026-06-24 06:48:45,840 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000032_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:48:45,840 - probe_source: simu +2026-06-24 06:48:45,840 - probe_params: None +2026-06-24 06:48:45,840 - pos_source: simu +2026-06-24 06:48:45,840 - pos_params: None +2026-06-24 06:48:45,840 - obj_source: simu +2026-06-24 06:48:45,840 - obj_params: None +2026-06-24 06:48:45,840 - tilt_source: simu +2026-06-24 06:48:45,840 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:48:45,840 - +2026-06-24 06:48:45,840 - ### Initializing cache ### +2026-06-24 06:48:45,840 - use_cached_obj = False +2026-06-24 06:48:45,840 - use_cached_probe = False +2026-06-24 06:48:45,840 - use_cached_pos = False +2026-06-24 06:48:45,840 - +2026-06-24 06:48:45,840 - ### Initializing measurements ### +2026-06-24 06:48:45,840 - Loading measurements from source = 'file' +2026-06-24 06:48:45,840 - Detected measurement file type = '.h5' +2026-06-24 06:48:45,920 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:48:45,920 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:48:45,922 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0040) +2026-06-24 06:48:45,922 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:48:45,922 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:48:45,923 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:48:45,923 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:48:45,924 - Normalizing by max of the 2D mean pattern intensity: 0.0030121645 +2026-06-24 06:48:45,924 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:48:45,925 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0201, 1.3309) +2026-06-24 06:48:45,926 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:48:45,927 - Pattern total int. statistics (min, mean, max) = (326.7524, 329.0316, 331.3885), with min/max = 98.6% +2026-06-24 06:48:45,928 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0201, 1.3309) +2026-06-24 06:48:45,928 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:48:45,928 - +2026-06-24 06:48:45,929 - ### Setting up calibration ### +2026-06-24 06:48:45,929 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:48:45,929 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:48:45,929 - Radius of fitted bright field disk (RBF) = 9.49 px with meas_Npix = 128 +2026-06-24 06:48:45,929 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1483 +2026-06-24 06:48:45,929 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:48:45,929 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:48:46,154 - Initial guess: center=(63.63, 63.63), radius=9.49, Gaussian blur std=0.50 +2026-06-24 06:48:46,167 - Final fit: center=(63.63, 63.63), radius=9.49, Gaussian blur std=0.67 +2026-06-24 06:48:46,167 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.58 px with Npix = 128 +2026-06-24 06:48:46,167 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:48:46,167 - +2026-06-24 06:48:46,167 - ### Setting init_variables dict ### +2026-06-24 06:48:46,167 - Derived values given input init_params: +2026-06-24 06:48:46,167 - kv = 80.0 kV +2026-06-24 06:48:46,167 - wavelength = 0.0418 Ang +2026-06-24 06:48:46,167 - conv_angle = 15.631131172180176 mrad +2026-06-24 06:48:46,167 - Npix = 128 px +2026-06-24 06:48:46,167 - dk = 0.0391 Ang^-1 +2026-06-24 06:48:46,167 - kMax = 2.5000 Ang^-1 +2026-06-24 06:48:46,167 - da = 1.6311 mrad +2026-06-24 06:48:46,167 - angleMax = 104.3929 mrad +2026-06-24 06:48:46,167 - RBF = 9.5830 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:48:46,167 - n_alpha = 6.6785 (# conv_angle) +2026-06-24 06:48:46,167 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:48:46,167 - Rayleigh-limited resolution = 1.6296 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:48:46,168 - Real space probe extent = 25.6000 Ang +2026-06-24 06:48:46,168 - +2026-06-24 06:48:46,168 - ### Initializing probe ### +2026-06-24 06:48:46,168 - Loading probe from source = 'simu' +2026-06-24 06:48:46,168 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:48:46,168 - Start simulating STEM probe +2026-06-24 06:48:46,168 - kv = 80.0 kV +2026-06-24 06:48:46,168 - wavelength = 0.0418 Ang +2026-06-24 06:48:46,168 - conv_angle = 15.631131172180176 mrad +2026-06-24 06:48:46,168 - Npix = 128 px +2026-06-24 06:48:46,168 - dk = 0.0391 Ang^-1 +2026-06-24 06:48:46,168 - kMax = 2.5000 Ang^-1 +2026-06-24 06:48:46,168 - alpha_max = 104.3929 mrad +2026-06-24 06:48:46,168 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:48:46,168 - Rayleigh-limited resolution = 1.6296 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:48:46,168 - Real space probe extent = 25.6000 Ang +2026-06-24 06:48:46,168 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:48:46,168 - ------------------------------------------------------------------------------------- +2026-06-24 06:48:46,168 - C1,0 C1 -657.5960 - Defocus (C10 = -df) +2026-06-24 06:48:46,168 - C1,2 A1 -20.3790 3.54 2-fold astigmatism +2026-06-24 06:48:46,168 - C2,1 3*B2 979.6290 64.53 Axial coma +2026-06-24 06:48:46,168 - C2,3 A2 170.2920 120.19 3-fold astigmatism +2026-06-24 06:48:46,168 - C3,0 C3 4900453.5000 - Spherical aberration +2026-06-24 06:48:46,168 - C3,2 4*S3 7783.2280 115.15 Axial star aberration +2026-06-24 06:48:46,168 - C3,4 A3 -2903.4540 287.99 4-fold astigmatism +2026-06-24 06:48:46,169 - C4,1 4*B4 59963.2300 30.57 Axial coma(4th) +2026-06-24 06:48:46,169 - C4,3 4*D4 -434621.3120 100.39 3-lobe aberration +2026-06-24 06:48:46,169 - C4,5 A4 188257.6720 67.01 5-fold astigmatism +2026-06-24 06:48:46,169 - C5,0 C5 -366283104.0000 - Spherical aberration (5th) +2026-06-24 06:48:46,169 - C5,2 6*S5 18804352.0000 214.00 Axial star aberration(5th) +2026-06-24 06:48:46,169 - C5,4 6*R5 17784624.0000 186.52 4-lobe aberration +2026-06-24 06:48:46,169 - C5,6 A5 9836762.0000 36.40 6-fold astigmatism +2026-06-24 06:48:46,172 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:48:46,172 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:48:46,172 - Creating 5 new probe modes from the major mode +2026-06-24 06:48:46,172 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:48:46,407 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:48:46,408 - Orthogonalizing 6 pmodes +2026-06-24 06:48:46,412 - Sorting 6 pmodes by their intensities +2026-06-24 06:48:46,412 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:48:46,413 - sum(|probe_data|**2) = 329.03, while meas_total_ints (min, mean, max) = (326.7524, 329.0316, 331.3885) +2026-06-24 06:48:46,413 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:48:46,413 - +2026-06-24 06:48:46,413 - ### Initializing probe positions ### +2026-06-24 06:48:46,413 - Loading probe positions from source = 'simu' +2026-06-24 06:48:46,413 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:48:46,413 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4218, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:48:46,413 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:48:46,415 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:48:46,415 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 06:48:46,416 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:48:46,416 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:48:46,416 - +2026-06-24 06:48:46,416 - ### Initializing object ### +2026-06-24 06:48:46,416 - Loading object from source = 'simu' +2026-06-24 06:48:46,416 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:48:46,417 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:48:46,417 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 193, 193) +2026-06-24 06:48:46,417 - object extent (Z, Y, X) (Ang) = [20. 38.6 38.6] +2026-06-24 06:48:46,417 - +2026-06-24 06:48:46,418 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:48:46,418 - omode_occu (omode) = float32, (1,) +2026-06-24 06:48:46,418 - +2026-06-24 06:48:46,418 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:48:46,418 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:48:46,418 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:48:46,418 - +2026-06-24 06:48:46,418 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:48:46,418 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:48:46,418 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:48:46,419 - +2026-06-24 06:48:46,419 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:48:46,419 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:48:46,419 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:48:46,419 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:48:46,419 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:48:46,419 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (193, 193). +2026-06-24 06:48:46,419 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:48:46,419 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:48:46,419 - +2026-06-24 06:48:46,419 - ### Collecting reconstruction provenance ### +2026-06-24 06:48:46,419 - Reconstruction provenance is collected and initialized. +2026-06-24 06:48:46,419 - +2026-06-24 06:48:46,419 - ### Initializing loss function ### +2026-06-24 06:48:46,419 - Active loss types: +2026-06-24 06:48:46,419 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:48:46,419 - +2026-06-24 06:48:46,419 - ### Initializing constraint function ### +2026-06-24 06:48:46,419 - Active constraint types: +2026-06-24 06:48:46,419 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:48:46,419 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:48:46,419 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:48:46,420 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:48:46,420 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:48:46,420 - +2026-06-24 06:48:46,420 - ### Done initializing PtyRADSolver ### +2026-06-24 06:48:46,420 - +2026-06-24 06:48:46,543 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:48:46,543 - +2026-06-24 06:48:46,543 - ### Initializing PtychoModel model ### +2026-06-24 06:48:46,613 - ### PtychoModel optimizable variables ### +2026-06-24 06:48:46,613 - obja : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:48:46,613 - objp : torch.Size([1, 1, 193, 193]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:48:46,613 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:48:46,613 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:48:46,613 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:48:46,613 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:48:46,613 - +2026-06-24 06:48:46,613 - ### Optimizable variables statitsics ### +2026-06-24 06:48:46,613 - Total measurement values : 4,194,304 +2026-06-24 06:48:46,613 - Total optimizing variables: 271,618 +2026-06-24 06:48:46,613 - Overdetermined ratio : 15.44 +2026-06-24 06:48:46,613 - +2026-06-24 06:48:46,613 - ### Model behavior ### +2026-06-24 06:48:46,613 - Tilt propagator : False +2026-06-24 06:48:46,613 - Change slice thickness : False +2026-06-24 06:48:46,613 - Detector blur : False +2026-06-24 06:48:46,613 - Preload data : True +2026-06-24 06:48:46,613 - On-the-fly meas padding : False +2026-06-24 06:48:46,613 - On-the-fly meas resample : False +2026-06-24 06:48:46,613 - On-the-fly simu match mode: None +2026-06-24 06:48:46,613 - +2026-06-24 06:48:46,655 - ### Done initializing PtychoModel model ### +2026-06-24 06:48:46,655 - +2026-06-24 06:48:46,655 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:48:46,655 - +2026-06-24 06:48:46,655 - ### Generating indices, batches, and output_path ### +2026-06-24 06:48:46,657 - d90 = 59.000 px or 11.800 Ang +2026-06-24 06:48:46,657 - Selecting indices with the 'full' mode +2026-06-24 06:48:47,113 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:48:47,186 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:48:47,187 - Original recon_dir_affixes = ['default'] +2026-06-24 06:48:47,187 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:48:47,192 - Path corrected for compatibility: +2026-06-24 06:48:47,192 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi32_115_C34_-2.9e+03_phi34_288_C41_6e+04_phi41_30.6_C43_-4.35e+05_phi43_100_C45_1.88e+05_phi45_67_C50_-3.66e+08_C52_1.88e+07_phi52_214_C54_1.78e+07_phi54_187_C56_9.84e+06_phi56_36.4 +2026-06-24 06:48:47,192 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4 +2026-06-24 06:48:47,193 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4' is generated! +2026-06-24 06:48:47,343 - +2026-06-24 06:48:47,344 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4/20260624_064847_ptyrad_log.txt ### +2026-06-24 06:48:47,344 - +2026-06-24 06:48:47,345 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:48:47,345 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:48:47,345 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:48:48,527 - Iter: 1, Total Loss: 1.0444, loss_single: 1.0444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.439 sec +2026-06-24 06:48:48,564 - Iter: 2, Total Loss: 1.0091, loss_single: 1.0091, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:48:48,600 - Iter: 3, Total Loss: 0.9817, loss_single: 0.9817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,636 - Iter: 4, Total Loss: 0.9587, loss_single: 0.9587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,671 - Iter: 5, Total Loss: 0.9361, loss_single: 0.9361, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,707 - Iter: 6, Total Loss: 0.9120, loss_single: 0.9120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,743 - Iter: 7, Total Loss: 0.8880, loss_single: 0.8880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:48,778 - Iter: 8, Total Loss: 0.8664, loss_single: 0.8664, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,816 - Iter: 9, Total Loss: 0.8438, loss_single: 0.8438, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:48:48,852 - Iter: 10, Total Loss: 0.8173, loss_single: 0.8173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:48,887 - Iter: 11, Total Loss: 0.7919, loss_single: 0.7919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,923 - Iter: 12, Total Loss: 0.7699, loss_single: 0.7699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,958 - Iter: 13, Total Loss: 0.7486, loss_single: 0.7486, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:48,994 - Iter: 14, Total Loss: 0.7257, loss_single: 0.7257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,030 - Iter: 15, Total Loss: 0.7009, loss_single: 0.7009, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,065 - Iter: 16, Total Loss: 0.6748, loss_single: 0.6748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,101 - Iter: 17, Total Loss: 0.6465, loss_single: 0.6465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,136 - Iter: 18, Total Loss: 0.6231, loss_single: 0.6231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,172 - Iter: 19, Total Loss: 0.6046, loss_single: 0.6046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,207 - Iter: 20, Total Loss: 0.5841, loss_single: 0.5841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,243 - Iter: 21, Total Loss: 0.5616, loss_single: 0.5616, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,278 - Iter: 22, Total Loss: 0.5380, loss_single: 0.5380, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,314 - Iter: 23, Total Loss: 0.5140, loss_single: 0.5140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,350 - Iter: 24, Total Loss: 0.4955, loss_single: 0.4955, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,386 - Iter: 25, Total Loss: 0.4795, loss_single: 0.4795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,422 - Iter: 26, Total Loss: 0.4629, loss_single: 0.4629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,457 - Iter: 27, Total Loss: 0.4442, loss_single: 0.4442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,496 - Iter: 28, Total Loss: 0.4279, loss_single: 0.4279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:48:49,532 - Iter: 29, Total Loss: 0.4138, loss_single: 0.4138, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,567 - Iter: 30, Total Loss: 0.3962, loss_single: 0.3962, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,603 - Iter: 31, Total Loss: 0.3802, loss_single: 0.3802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,639 - Iter: 32, Total Loss: 0.3663, loss_single: 0.3663, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,675 - Iter: 33, Total Loss: 0.3521, loss_single: 0.3521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,711 - Iter: 34, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,747 - Iter: 35, Total Loss: 0.3298, loss_single: 0.3298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,782 - Iter: 36, Total Loss: 0.3206, loss_single: 0.3206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,818 - Iter: 37, Total Loss: 0.3124, loss_single: 0.3124, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,866 - Iter: 38, Total Loss: 0.3049, loss_single: 0.3049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:49,901 - Iter: 39, Total Loss: 0.2996, loss_single: 0.2996, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,937 - Iter: 40, Total Loss: 0.2952, loss_single: 0.2952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:49,975 - Iter: 41, Total Loss: 0.2914, loss_single: 0.2914, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:50,011 - Iter: 42, Total Loss: 0.2879, loss_single: 0.2879, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,046 - Iter: 43, Total Loss: 0.2832, loss_single: 0.2832, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,081 - Iter: 44, Total Loss: 0.2789, loss_single: 0.2789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,117 - Iter: 45, Total Loss: 0.2750, loss_single: 0.2750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,153 - Iter: 46, Total Loss: 0.2722, loss_single: 0.2722, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,188 - Iter: 47, Total Loss: 0.2701, loss_single: 0.2701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,229 - Iter: 48, Total Loss: 0.2683, loss_single: 0.2683, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 06:48:50,264 - Iter: 49, Total Loss: 0.2666, loss_single: 0.2666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,300 - Iter: 50, Total Loss: 0.2646, loss_single: 0.2646, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:50,336 - Iter: 51, Total Loss: 0.2629, loss_single: 0.2629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,372 - Iter: 52, Total Loss: 0.2618, loss_single: 0.2618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:50,407 - Iter: 53, Total Loss: 0.2607, loss_single: 0.2607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,442 - Iter: 54, Total Loss: 0.2597, loss_single: 0.2597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,479 - Iter: 55, Total Loss: 0.2588, loss_single: 0.2588, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:48:50,514 - Iter: 56, Total Loss: 0.2578, loss_single: 0.2578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,550 - Iter: 57, Total Loss: 0.2571, loss_single: 0.2571, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:50,585 - Iter: 58, Total Loss: 0.2565, loss_single: 0.2565, loss_poissn: 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0.2511, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:52,050 - Iter: 99, Total Loss: 0.2511, loss_single: 0.2511, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:52,085 - Iter: 100, Total Loss: 0.2510, loss_single: 0.2510, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:48:52,200 - Saving summary figures for iter 100 +2026-06-24 06:48:55,904 - ### Finished 100 iterations, averaged iter_t = 0.039421 with std = 0.040 ### +2026-06-24 06:48:55,904 - +2026-06-24 06:48:55,904 - ### The PtyRADSolver is finished in 9.362 sec ### +2026-06-24 06:48:55,905 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4/simulation_data_aug2__sample_000032.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 15.631131172180176 + probe_aberrations: + C10: -657.5961303710938 + C12: -20.378692626953125 + C21: 979.62890625 + C23: 170.29150390625 + C30: 4900453.5 + C32: 7783.22802734375 + C34: -2903.4541015625 + C41: 59963.23046875 + C43: -434621.3125 + C45: 188257.671875 + C50: -366283104.0 + C52: 18804352.0 + C54: 17784624.0 + C56: 9836762.0 + phi12: 3.544585366716297 + phi21: 64.53139505184869 + phi23: 120.18653580553728 + phi32: 115.15125204751217 + phi34: 287.98615639069334 + phi41: 30.574238744011122 + phi43: 100.39475128910468 + phi45: 67.01001606013295 + phi52: 213.99820050842192 + phi54: 186.51951619438188 + phi56: 36.400195445640655 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.42182475328445435 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000032_measurement.h5 + key: measurement + random_seed: 20262147 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug2__sample_000032 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000032/c30_small__simulation_data_aug2__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-658_C12_-20.4_phi12_3.54_C21_980_phi21_64.5_C23_170_phi23_120_C30_4.9e+06_C32_7.78e+03_phi3.4/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257/20260624_064931_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..69fb599190f3970c285674da05ff6cfbeb366b00 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257/20260624_064931_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:49:29,911 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:49:29,911 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:49:29,911 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:49:29,911 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:49:29,911 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:49:29,911 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:49:29,911 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:49:29,911 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:49:29,911 - +2026-06-24 06:49:30,017 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:49:30,017 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:49:30,017 - Accelerator.num_process = 1 +2026-06-24 06:49:30,017 - Accelerator.mixed_precision = no +2026-06-24 06:49:30,028 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:49:30,028 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:49:30,028 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:49:30,028 - +2026-06-24 06:49:30,028 - ### System information ### +2026-06-24 06:49:30,028 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:49:30,028 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:49:30,028 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:49:30,028 - Machine: x86_64 +2026-06-24 06:49:30,028 - Processor: x86_64 +2026-06-24 06:49:30,028 - Available CPU cores: 8 +2026-06-24 06:49:30,028 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:49:30,029 - +2026-06-24 06:49:30,029 - ### GPU information ### +2026-06-24 06:49:30,029 - CUDA Available: True +2026-06-24 06:49:30,029 - CUDA Version: 13.0 +2026-06-24 06:49:30,029 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:49:30,029 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:49:30,029 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:49:30,029 - In addition, Triton does not directly support Windows. +2026-06-24 06:49:30,029 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:49:30,044 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:49:30,044 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:49:30,044 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:49:30,044 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:49:30,044 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:49:30,044 - +2026-06-24 06:49:30,044 - ### Python information ### +2026-06-24 06:49:30,045 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:49:30,045 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:49:30,045 - +2026-06-24 06:49:30,045 - ### Packages information ### +2026-06-24 06:49:30,046 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:49:30,046 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:49:30,047 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:49:30,048 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:49:30,048 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:49:30,048 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:49:30,048 - +2026-06-24 06:49:30,048 - ### Loading params file ### +2026-06-24 06:49:30,048 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000035.yaml +2026-06-24 06:49:30,055 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:49:30,056 - Success! Params file validated and defaults applied. +2026-06-24 06:49:30,056 - +2026-06-24 06:49:30,056 - ### Setting GPU Device ### +2026-06-24 06:49:30,056 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:49:30,056 - +2026-06-24 06:49:30,056 - Random seed: 20262150 provided by params file +2026-06-24 06:49:30,056 - ### Initializing Initializer ### +2026-06-24 06:49:30,056 - init_params are displayed below: +2026-06-24 06:49:30,056 - random_seed: 20262150 +2026-06-24 06:49:30,056 - probe_illum_type: electron +2026-06-24 06:49:30,056 - probe_kv: 160.0 +2026-06-24 06:49:30,056 - probe_conv_angle: 11.426163673400879 +2026-06-24 06:49:30,057 - probe_aberrations: {'C10': -470.074, 'C12': 11.645, 'phi12': 51.078, 'C21': -462.655, 'phi21': 111.427, 'C23': 936.524, 'phi23': 176.076, 'C30': 1028718.5, 'C32': 4291.155, 'phi32': 300.057, 'C34': -11390.22, 'phi34': 252.832, 'C41': -109588.859, 'phi41': 165.827, 'C43': 98467.742, 'phi43': 237.853, 'C45': -282875.594, 'phi45': 10.816, 'C50': -177988304.0, 'C52': -14677788.0, 'phi52': 159.631, 'C54': -19647582.0, 'phi54': 135.165, 'C56': -2155054.75, 'phi56': 257.365} +2026-06-24 06:49:30,057 - beam_kev: None +2026-06-24 06:49:30,057 - probe_dRn: None +2026-06-24 06:49:30,057 - probe_Rn: None +2026-06-24 06:49:30,057 - probe_D_H: None +2026-06-24 06:49:30,057 - probe_D_FZP: None +2026-06-24 06:49:30,057 - probe_Ls: None +2026-06-24 06:49:30,057 - meas_Npix: 128 +2026-06-24 06:49:30,057 - pos_N_scans: 256 +2026-06-24 06:49:30,057 - pos_N_scan_slow: 16 +2026-06-24 06:49:30,057 - pos_N_scan_fast: 16 +2026-06-24 06:49:30,057 - pos_scan_step_size: 0.4624967575073242 +2026-06-24 06:49:30,057 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:49:30,057 - probe_pmode_max: 6 +2026-06-24 06:49:30,057 - probe_pmode_init_pows: [0.02] +2026-06-24 06:49:30,057 - obj_omode_max: 1 +2026-06-24 06:49:30,057 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:49:30,057 - obj_Nlayer: 1 +2026-06-24 06:49:30,057 - obj_slice_thickness: 20.0 +2026-06-24 06:49:30,057 - simu_Npix: None +2026-06-24 06:49:30,057 - simu_match_mode: None +2026-06-24 06:49:30,057 - meas_permute: None +2026-06-24 06:49:30,057 - meas_reshape: [256, 128, 128] +2026-06-24 06:49:30,057 - meas_flipT: [0, 0, 0] +2026-06-24 06:49:30,057 - meas_crop: None +2026-06-24 06:49:30,057 - meas_pad: None +2026-06-24 06:49:30,057 - meas_resample: None +2026-06-24 06:49:30,057 - meas_add_source_size: None +2026-06-24 06:49:30,057 - meas_add_detector_blur: None +2026-06-24 06:49:30,057 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:49:30,057 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:49:30,057 - meas_add_poisson_noise: None +2026-06-24 06:49:30,057 - meas_export: None +2026-06-24 06:49:30,057 - probe_permute: None +2026-06-24 06:49:30,057 - probe_z_shift: None +2026-06-24 06:49:30,057 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:49:30,057 - pos_scan_flipT: None +2026-06-24 06:49:30,057 - pos_scan_affine: None +2026-06-24 06:49:30,057 - pos_scan_rand_std: 0.15 +2026-06-24 06:49:30,058 - obj_z_crop: None +2026-06-24 06:49:30,058 - obj_z_pad: None +2026-06-24 06:49:30,058 - obj_z_resample: None +2026-06-24 06:49:30,058 - meas_source: file +2026-06-24 06:49:30,058 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000035_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:49:30,058 - probe_source: simu +2026-06-24 06:49:30,058 - probe_params: None +2026-06-24 06:49:30,058 - pos_source: simu +2026-06-24 06:49:30,058 - pos_params: None +2026-06-24 06:49:30,058 - obj_source: simu +2026-06-24 06:49:30,058 - obj_params: None +2026-06-24 06:49:30,058 - tilt_source: simu +2026-06-24 06:49:30,058 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:49:30,058 - +2026-06-24 06:49:30,058 - ### Initializing cache ### +2026-06-24 06:49:30,058 - use_cached_obj = False +2026-06-24 06:49:30,058 - use_cached_probe = False +2026-06-24 06:49:30,058 - use_cached_pos = False +2026-06-24 06:49:30,058 - +2026-06-24 06:49:30,058 - ### Initializing measurements ### +2026-06-24 06:49:30,058 - Loading measurements from source = 'file' +2026-06-24 06:49:30,058 - Detected measurement file type = '.h5' +2026-06-24 06:49:30,136 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:49:30,136 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:49:30,138 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0046) +2026-06-24 06:49:30,138 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:49:30,138 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:49:30,140 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:30,140 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:49:30,140 - Normalizing by max of the 2D mean pattern intensity: 0.0028508485 +2026-06-24 06:49:30,141 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:49:30,142 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0213, 1.6205) +2026-06-24 06:49:30,142 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:30,144 - Pattern total int. statistics (min, mean, max) = (346.7239, 349.0956, 351.6656), with min/max = 98.6% +2026-06-24 06:49:30,145 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0213, 1.6205) +2026-06-24 06:49:30,145 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:49:30,145 - +2026-06-24 06:49:30,145 - ### Setting up calibration ### +2026-06-24 06:49:30,145 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:49:30,145 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:49:30,145 - Radius of fitted bright field disk (RBF) = 10.17 px with meas_Npix = 128 +2026-06-24 06:49:30,145 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1589 +2026-06-24 06:49:30,145 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:49:30,145 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:49:30,376 - Initial guess: center=(63.63, 63.61), radius=10.17, Gaussian blur std=0.50 +2026-06-24 06:49:30,384 - Final fit: center=(63.63, 63.61), radius=10.17, Gaussian blur std=0.53 +2026-06-24 06:49:30,384 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.26 px with Npix = 128 +2026-06-24 06:49:30,384 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:49:30,384 - +2026-06-24 06:49:30,384 - ### Setting init_variables dict ### +2026-06-24 06:49:30,384 - Derived values given input init_params: +2026-06-24 06:49:30,384 - kv = 160.0 kV +2026-06-24 06:49:30,384 - wavelength = 0.0285 Ang +2026-06-24 06:49:30,384 - conv_angle = 11.426163673400879 mrad +2026-06-24 06:49:30,384 - Npix = 128 px +2026-06-24 06:49:30,384 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:30,384 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:30,384 - da = 1.1137 mrad +2026-06-24 06:49:30,384 - angleMax = 71.2751 mrad +2026-06-24 06:49:30,384 - RBF = 10.2599 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:49:30,384 - n_alpha = 6.2379 (# conv_angle) +2026-06-24 06:49:30,384 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:30,384 - Rayleigh-limited resolution = 1.5220 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:30,385 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:30,385 - +2026-06-24 06:49:30,385 - ### Initializing probe ### +2026-06-24 06:49:30,385 - Loading probe from source = 'simu' +2026-06-24 06:49:30,385 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:49:30,385 - Start simulating STEM probe +2026-06-24 06:49:30,385 - kv = 160.0 kV +2026-06-24 06:49:30,385 - wavelength = 0.0285 Ang +2026-06-24 06:49:30,385 - conv_angle = 11.426163673400879 mrad +2026-06-24 06:49:30,385 - Npix = 128 px +2026-06-24 06:49:30,385 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:30,385 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:30,385 - alpha_max = 71.2751 mrad +2026-06-24 06:49:30,385 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:30,385 - Rayleigh-limited resolution = 1.5220 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:30,385 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:30,385 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:49:30,385 - ------------------------------------------------------------------------------------- +2026-06-24 06:49:30,385 - C1,0 C1 -470.0740 - Defocus (C10 = -df) +2026-06-24 06:49:30,385 - C1,2 A1 11.6450 51.08 2-fold astigmatism +2026-06-24 06:49:30,385 - C2,1 3*B2 -462.6550 111.43 Axial coma +2026-06-24 06:49:30,385 - C2,3 A2 936.5240 176.08 3-fold astigmatism +2026-06-24 06:49:30,385 - C3,0 C3 1028718.5000 - Spherical aberration +2026-06-24 06:49:30,385 - C3,2 4*S3 4291.1550 300.06 Axial star aberration +2026-06-24 06:49:30,386 - C3,4 A3 -11390.2200 252.83 4-fold astigmatism +2026-06-24 06:49:30,386 - C4,1 4*B4 -109588.8590 165.83 Axial coma(4th) +2026-06-24 06:49:30,386 - C4,3 4*D4 98467.7420 237.85 3-lobe aberration +2026-06-24 06:49:30,386 - C4,5 A4 -282875.5940 10.82 5-fold astigmatism +2026-06-24 06:49:30,386 - C5,0 C5 -177988304.0000 - Spherical aberration (5th) +2026-06-24 06:49:30,386 - C5,2 6*S5 -14677788.0000 159.63 Axial star aberration(5th) +2026-06-24 06:49:30,386 - C5,4 6*R5 -19647582.0000 135.16 4-lobe aberration +2026-06-24 06:49:30,386 - C5,6 A5 -2155054.7500 257.37 6-fold astigmatism +2026-06-24 06:49:30,389 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:49:30,389 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:49:30,389 - Creating 5 new probe modes from the major mode +2026-06-24 06:49:30,389 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:49:30,490 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:49:30,491 - Orthogonalizing 6 pmodes +2026-06-24 06:49:30,494 - Sorting 6 pmodes by their intensities +2026-06-24 06:49:30,494 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:49:30,495 - sum(|probe_data|**2) = 349.10, while meas_total_ints (min, mean, max) = (346.7239, 349.0956, 351.6656) +2026-06-24 06:49:30,495 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:49:30,495 - +2026-06-24 06:49:30,495 - ### Initializing probe positions ### +2026-06-24 06:49:30,495 - Loading probe positions from source = 'simu' +2026-06-24 06:49:30,495 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:49:30,495 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4625, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:49:30,495 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:49:30,497 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:49:30,498 - crop_pos 1st and last px coords (y,x) = ([15, 16], [50, 50]) +2026-06-24 06:49:30,498 - crop_pos extent (Ang) = [7. 7.2] +2026-06-24 06:49:30,498 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:49:30,498 - +2026-06-24 06:49:30,498 - ### Initializing object ### +2026-06-24 06:49:30,498 - Loading object from source = 'simu' +2026-06-24 06:49:30,498 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:49:30,499 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:49:30,499 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 196, 196) +2026-06-24 06:49:30,500 - object extent (Z, Y, X) (Ang) = [20. 39.2 39.2] +2026-06-24 06:49:30,500 - +2026-06-24 06:49:30,500 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:49:30,500 - omode_occu (omode) = float32, (1,) +2026-06-24 06:49:30,500 - +2026-06-24 06:49:30,500 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:49:30,500 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:49:30,500 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:49:30,501 - +2026-06-24 06:49:30,501 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:49:30,501 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:49:30,501 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:49:30,501 - +2026-06-24 06:49:30,501 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:49:30,501 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:49:30,501 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:49:30,501 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:49:30,501 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:49:30,501 - crop positions (yx_min=[15 15], yx_max=[178 179]) are well contained inside object canvas (Ny,Nx) = (196, 196). +2026-06-24 06:49:30,501 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:49:30,501 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:49:30,501 - +2026-06-24 06:49:30,501 - ### Collecting reconstruction provenance ### +2026-06-24 06:49:30,501 - Reconstruction provenance is collected and initialized. +2026-06-24 06:49:30,501 - +2026-06-24 06:49:30,501 - ### Initializing loss function ### +2026-06-24 06:49:30,501 - Active loss types: +2026-06-24 06:49:30,501 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:49:30,502 - +2026-06-24 06:49:30,502 - ### Initializing constraint function ### +2026-06-24 06:49:30,502 - Active constraint types: +2026-06-24 06:49:30,502 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:49:30,502 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:49:30,502 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:49:30,502 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:49:30,502 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:49:30,502 - +2026-06-24 06:49:30,502 - ### Done initializing PtyRADSolver ### +2026-06-24 06:49:30,502 - +2026-06-24 06:49:30,628 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:49:30,628 - +2026-06-24 06:49:30,628 - ### Initializing PtychoModel model ### +2026-06-24 06:49:30,699 - ### PtychoModel optimizable variables ### +2026-06-24 06:49:30,699 - obja : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:30,699 - objp : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:30,699 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:49:30,699 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:49:30,699 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:49:30,699 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:30,700 - +2026-06-24 06:49:30,700 - ### Optimizable variables statitsics ### +2026-06-24 06:49:30,700 - Total measurement values : 4,194,304 +2026-06-24 06:49:30,700 - Total optimizing variables: 273,952 +2026-06-24 06:49:30,700 - Overdetermined ratio : 15.31 +2026-06-24 06:49:30,700 - +2026-06-24 06:49:30,700 - ### Model behavior ### +2026-06-24 06:49:30,700 - Tilt propagator : False +2026-06-24 06:49:30,700 - Change slice thickness : False +2026-06-24 06:49:30,700 - Detector blur : False +2026-06-24 06:49:30,700 - Preload data : True +2026-06-24 06:49:30,700 - On-the-fly meas padding : False +2026-06-24 06:49:30,700 - On-the-fly meas resample : False +2026-06-24 06:49:30,700 - On-the-fly simu match mode: None +2026-06-24 06:49:30,700 - +2026-06-24 06:49:30,742 - ### Done initializing PtychoModel model ### +2026-06-24 06:49:30,742 - +2026-06-24 06:49:30,742 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:49:30,742 - +2026-06-24 06:49:30,742 - ### Generating indices, batches, and output_path ### +2026-06-24 06:49:30,743 - d90 = 53.000 px or 10.600 Ang +2026-06-24 06:49:30,743 - Selecting indices with the 'full' mode +2026-06-24 06:49:31,203 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:49:31,279 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:49:31,279 - Original recon_dir_affixes = ['default'] +2026-06-24 06:49:31,279 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:49:31,285 - Path corrected for compatibility: +2026-06-24 06:49:31,285 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C32_4.29e+03_phi32_300_C34_-1.14e+04_phi34_253_C41_-1.1e+05_phi41_166_C43_9.85e+04_phi43_238_C45_-2.83e+05_phi45_10.8_C50_-1.78e+08_C52_-1.47e+07_phi52_160_C54_-1.96e+07_phi54_135_C56_-2.16e+06_phi56_257 +2026-06-24 06:49:31,285 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257 +2026-06-24 06:49:31,286 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257' is generated! +2026-06-24 06:49:31,441 - +2026-06-24 06:49:31,442 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257/20260624_064931_ptyrad_log.txt ### +2026-06-24 06:49:31,442 - +2026-06-24 06:49:31,444 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:49:31,444 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:49:31,444 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:49:32,623 - Iter: 1, Total Loss: 1.0281, loss_single: 1.0281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 06:49:32,660 - Iter: 2, Total Loss: 0.9897, loss_single: 0.9897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:32,696 - Iter: 3, Total Loss: 0.9581, loss_single: 0.9581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,732 - Iter: 4, Total Loss: 0.9316, loss_single: 0.9316, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,768 - Iter: 5, Total Loss: 0.9097, loss_single: 0.9097, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:32,803 - Iter: 6, Total Loss: 0.8868, loss_single: 0.8868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,838 - Iter: 7, Total Loss: 0.8624, loss_single: 0.8624, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,874 - Iter: 8, Total Loss: 0.8404, loss_single: 0.8404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,909 - Iter: 9, Total Loss: 0.8192, loss_single: 0.8192, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,945 - Iter: 10, Total Loss: 0.7969, loss_single: 0.7969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:32,980 - Iter: 11, Total Loss: 0.7738, loss_single: 0.7738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,016 - Iter: 12, Total Loss: 0.7509, loss_single: 0.7509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,051 - Iter: 13, Total Loss: 0.7298, loss_single: 0.7298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,087 - Iter: 14, Total Loss: 0.7071, loss_single: 0.7071, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,124 - Iter: 15, Total Loss: 0.6854, loss_single: 0.6854, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:33,159 - Iter: 16, Total Loss: 0.6643, loss_single: 0.6643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,195 - Iter: 17, Total Loss: 0.6439, loss_single: 0.6439, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,230 - Iter: 18, Total Loss: 0.6257, loss_single: 0.6257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,266 - Iter: 19, Total Loss: 0.6095, loss_single: 0.6095, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,301 - Iter: 20, Total Loss: 0.5954, loss_single: 0.5954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,337 - Iter: 21, Total Loss: 0.5833, loss_single: 0.5833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,373 - Iter: 22, Total Loss: 0.5713, loss_single: 0.5713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:33,409 - Iter: 23, Total Loss: 0.5553, loss_single: 0.5553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,444 - Iter: 24, Total Loss: 0.5397, loss_single: 0.5397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,480 - Iter: 25, Total Loss: 0.5273, loss_single: 0.5273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,515 - Iter: 26, Total Loss: 0.5148, loss_single: 0.5148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,551 - Iter: 27, Total Loss: 0.5031, loss_single: 0.5031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,586 - Iter: 28, Total Loss: 0.4929, loss_single: 0.4929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,621 - Iter: 29, Total Loss: 0.4838, loss_single: 0.4838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,656 - Iter: 30, Total Loss: 0.4763, loss_single: 0.4763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,692 - Iter: 31, Total Loss: 0.4699, loss_single: 0.4699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,727 - Iter: 32, Total Loss: 0.4651, loss_single: 0.4651, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,763 - Iter: 33, Total Loss: 0.4611, loss_single: 0.4611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,799 - Iter: 34, Total Loss: 0.4575, loss_single: 0.4575, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:33,834 - Iter: 35, Total Loss: 0.4540, loss_single: 0.4540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,870 - Iter: 36, Total Loss: 0.4498, loss_single: 0.4498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,906 - Iter: 37, Total Loss: 0.4468, loss_single: 0.4468, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:33,941 - Iter: 38, Total Loss: 0.4446, loss_single: 0.4446, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:33,976 - Iter: 39, Total Loss: 0.4426, loss_single: 0.4426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,012 - Iter: 40, Total Loss: 0.4409, loss_single: 0.4409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,049 - Iter: 41, Total Loss: 0.4391, loss_single: 0.4391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,084 - Iter: 42, Total Loss: 0.4374, loss_single: 0.4374, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,120 - Iter: 43, Total Loss: 0.4362, loss_single: 0.4362, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,155 - Iter: 44, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,190 - Iter: 45, Total Loss: 0.4340, loss_single: 0.4340, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,226 - Iter: 46, Total Loss: 0.4330, loss_single: 0.4330, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:34,262 - Iter: 47, Total Loss: 0.4320, loss_single: 0.4320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,297 - Iter: 48, Total Loss: 0.4312, loss_single: 0.4312, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,333 - Iter: 49, Total Loss: 0.4303, loss_single: 0.4303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,368 - Iter: 50, Total Loss: 0.4295, loss_single: 0.4295, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,403 - Iter: 51, Total Loss: 0.4287, loss_single: 0.4287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,439 - Iter: 52, Total Loss: 0.4279, loss_single: 0.4279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,474 - Iter: 53, Total Loss: 0.4271, loss_single: 0.4271, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,510 - Iter: 54, Total Loss: 0.4264, loss_single: 0.4264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,545 - Iter: 55, Total Loss: 0.4258, loss_single: 0.4258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,580 - Iter: 56, Total Loss: 0.4251, loss_single: 0.4251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,615 - Iter: 57, Total Loss: 0.4243, loss_single: 0.4243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,650 - Iter: 58, Total Loss: 0.4236, loss_single: 0.4236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,685 - Iter: 59, Total Loss: 0.4229, loss_single: 0.4229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,720 - Iter: 60, Total Loss: 0.4222, loss_single: 0.4222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,755 - Iter: 61, Total Loss: 0.4215, loss_single: 0.4215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,790 - Iter: 62, Total Loss: 0.4208, loss_single: 0.4208, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,825 - Iter: 63, Total Loss: 0.4201, loss_single: 0.4201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:34,921 - Iter: 64, 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in 0.035 sec +2026-06-24 06:49:35,133 - Iter: 70, Total Loss: 0.4156, loss_single: 0.4156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,168 - Iter: 71, Total Loss: 0.4149, loss_single: 0.4149, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,204 - Iter: 72, Total Loss: 0.4142, loss_single: 0.4142, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:35,239 - Iter: 73, Total Loss: 0.4136, loss_single: 0.4136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,275 - Iter: 74, Total Loss: 0.4129, loss_single: 0.4129, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,311 - Iter: 75, Total Loss: 0.4123, loss_single: 0.4123, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.4084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,559 - Iter: 82, Total Loss: 0.4077, loss_single: 0.4077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,594 - Iter: 83, Total Loss: 0.4071, loss_single: 0.4071, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,630 - Iter: 84, Total Loss: 0.4065, loss_single: 0.4065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,665 - Iter: 85, Total Loss: 0.4059, loss_single: 0.4059, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,700 - Iter: 86, Total Loss: 0.4053, loss_single: 0.4053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,736 - Iter: 87, Total Loss: 0.4046, loss_single: 0.4046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:35,772 - Iter: 88, Total Loss: 0.4040, loss_single: 0.4040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,807 - Iter: 89, Total Loss: 0.4034, loss_single: 0.4034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,842 - Iter: 90, Total Loss: 0.4028, loss_single: 0.4028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:35,880 - Iter: 91, Total Loss: 0.4022, loss_single: 0.4022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:49:35,916 - Iter: 92, Total Loss: 0.4016, loss_single: 0.4016, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.3977, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:36,164 - Iter: 99, Total Loss: 0.3971, loss_single: 0.3971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:36,200 - Iter: 100, Total Loss: 0.3964, loss_single: 0.3964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:36,311 - Saving summary figures for iter 100 +2026-06-24 06:49:39,983 - ### Finished 100 iterations, averaged iter_t = 0.039069 with std = 0.040 ### +2026-06-24 06:49:39,984 - +2026-06-24 06:49:39,984 - ### The PtyRADSolver is finished in 9.356 sec ### +2026-06-24 06:49:39,984 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000035/c30_small__simulation_data_aug2__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-470_C12_11.6_phi12_51.1_C21_-463_phi21_111_C23_937_phi23_176_C30_1.03e+06_C3.16e+06_phi56_257/simulation_data_aug2__sample_000035.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 11.426163673400879 + probe_aberrations: + C10: -470.07379150390625 + C12: 11.644535064697266 + C21: -462.6551818847656 + C23: 936.5242919921875 + C30: 1028718.5 + C32: 4291.1552734375 + C34: -11390.2197265625 + C41: -109588.859375 + C43: 98467.7421875 + C45: -282875.59375 + C50: -177988304.0 + C52: -14677788.0 + C54: -19647582.0 + C56: -2155054.75 + phi12: 51.07815927387675 + phi21: 111.42705725161687 + phi23: 176.0759930288923 + phi32: 300.05693114480346 + phi34: 252.8318557515547 + phi41: 165.82657017923614 + phi43: 237.8533055432301 + phi45: 10.815976796024957 + phi52: 159.63096022463094 + phi54: 135.1649903912135 + phi56: 257.36540747352905 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4624967575073242 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000035_measurement.h5 + key: measurement + random_seed: 20262150 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/20260624_064946_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ef23afc90fb90e27330c39d5c3b515e79ba34079 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/20260624_064946_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:49:44,648 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:49:44,648 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:49:44,648 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:49:44,648 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:49:44,648 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:49:44,648 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:49:44,648 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:49:44,648 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:49:44,648 - +2026-06-24 06:49:44,760 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:49:44,760 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:49:44,760 - Accelerator.num_process = 1 +2026-06-24 06:49:44,760 - Accelerator.mixed_precision = no +2026-06-24 06:49:44,782 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:49:44,782 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:49:44,782 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:49:44,782 - +2026-06-24 06:49:44,782 - ### System information ### +2026-06-24 06:49:44,782 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:49:44,783 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:49:44,783 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:49:44,783 - Machine: x86_64 +2026-06-24 06:49:44,783 - Processor: x86_64 +2026-06-24 06:49:44,783 - Available CPU cores: 8 +2026-06-24 06:49:44,783 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:49:44,783 - +2026-06-24 06:49:44,783 - ### GPU information ### +2026-06-24 06:49:44,783 - CUDA Available: True +2026-06-24 06:49:44,783 - CUDA Version: 13.0 +2026-06-24 06:49:44,783 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:49:44,783 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:49:44,783 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:49:44,783 - In addition, Triton does not directly support Windows. +2026-06-24 06:49:44,783 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:49:44,798 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:49:44,799 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:49:44,799 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:49:44,799 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:49:44,799 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:49:44,799 - +2026-06-24 06:49:44,799 - ### Python information ### +2026-06-24 06:49:44,801 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:49:44,801 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:49:44,801 - +2026-06-24 06:49:44,801 - ### Packages information ### +2026-06-24 06:49:44,802 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:49:44,803 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:49:44,803 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:49:44,804 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:49:44,804 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:49:44,804 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:49:44,804 - +2026-06-24 06:49:44,805 - ### Loading params file ### +2026-06-24 06:49:44,805 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000036.yaml +2026-06-24 06:49:44,811 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:49:44,812 - Success! Params file validated and defaults applied. +2026-06-24 06:49:44,812 - +2026-06-24 06:49:44,812 - ### Setting GPU Device ### +2026-06-24 06:49:44,812 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:49:44,812 - +2026-06-24 06:49:44,812 - Random seed: 20262151 provided by params file +2026-06-24 06:49:44,812 - ### Initializing Initializer ### +2026-06-24 06:49:44,813 - init_params are displayed below: +2026-06-24 06:49:44,813 - random_seed: 20262151 +2026-06-24 06:49:44,813 - probe_illum_type: electron +2026-06-24 06:49:44,813 - probe_kv: 120.0 +2026-06-24 06:49:44,813 - probe_conv_angle: 10.975295066833496 +2026-06-24 06:49:44,813 - probe_aberrations: {'C10': -179.777, 'C12': 22.07, 'phi12': 211.992, 'C21': -932.551, 'phi21': 358.627, 'C23': 311.504, 'phi23': 295.296, 'C30': 4932964.0, 'C32': -5480.449, 'phi32': 46.926, 'C34': 10596.893, 'phi34': 70.241, 'C41': -454608.062, 'phi41': 25.823, 'C43': -236445.547, 'phi43': 133.914, 'C45': 155105.172, 'phi45': 337.084, 'C50': -11338927.0, 'C52': 4239681.5, 'phi52': 137.23, 'C54': 18613014.0, 'phi54': 280.103, 'C56': 15428138.0, 'phi56': 340.005} +2026-06-24 06:49:44,813 - beam_kev: None +2026-06-24 06:49:44,813 - probe_dRn: None +2026-06-24 06:49:44,813 - probe_Rn: None +2026-06-24 06:49:44,813 - probe_D_H: None +2026-06-24 06:49:44,813 - probe_D_FZP: None +2026-06-24 06:49:44,813 - probe_Ls: None +2026-06-24 06:49:44,813 - meas_Npix: 128 +2026-06-24 06:49:44,813 - pos_N_scans: 256 +2026-06-24 06:49:44,813 - pos_N_scan_slow: 16 +2026-06-24 06:49:44,813 - pos_N_scan_fast: 16 +2026-06-24 06:49:44,813 - pos_scan_step_size: 0.30078911781311035 +2026-06-24 06:49:44,813 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:49:44,813 - probe_pmode_max: 6 +2026-06-24 06:49:44,813 - probe_pmode_init_pows: [0.02] +2026-06-24 06:49:44,813 - obj_omode_max: 1 +2026-06-24 06:49:44,813 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:49:44,813 - obj_Nlayer: 1 +2026-06-24 06:49:44,813 - obj_slice_thickness: 20.0 +2026-06-24 06:49:44,813 - simu_Npix: None +2026-06-24 06:49:44,813 - simu_match_mode: None +2026-06-24 06:49:44,813 - meas_permute: None +2026-06-24 06:49:44,813 - meas_reshape: [256, 128, 128] +2026-06-24 06:49:44,813 - meas_flipT: [0, 0, 0] +2026-06-24 06:49:44,813 - meas_crop: None +2026-06-24 06:49:44,813 - meas_pad: None +2026-06-24 06:49:44,813 - meas_resample: None +2026-06-24 06:49:44,813 - meas_add_source_size: None +2026-06-24 06:49:44,813 - meas_add_detector_blur: None +2026-06-24 06:49:44,813 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:49:44,814 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:49:44,814 - meas_add_poisson_noise: None +2026-06-24 06:49:44,814 - meas_export: None +2026-06-24 06:49:44,814 - probe_permute: None +2026-06-24 06:49:44,814 - probe_z_shift: None +2026-06-24 06:49:44,814 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:49:44,814 - pos_scan_flipT: None +2026-06-24 06:49:44,814 - pos_scan_affine: None +2026-06-24 06:49:44,814 - pos_scan_rand_std: 0.15 +2026-06-24 06:49:44,814 - obj_z_crop: None +2026-06-24 06:49:44,814 - obj_z_pad: None +2026-06-24 06:49:44,814 - obj_z_resample: None +2026-06-24 06:49:44,814 - meas_source: file +2026-06-24 06:49:44,814 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000036_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:49:44,814 - probe_source: simu +2026-06-24 06:49:44,814 - probe_params: None +2026-06-24 06:49:44,814 - pos_source: simu +2026-06-24 06:49:44,814 - pos_params: None +2026-06-24 06:49:44,814 - obj_source: simu +2026-06-24 06:49:44,814 - obj_params: None +2026-06-24 06:49:44,814 - tilt_source: simu +2026-06-24 06:49:44,814 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:49:44,814 - +2026-06-24 06:49:44,814 - ### Initializing cache ### +2026-06-24 06:49:44,814 - use_cached_obj = False +2026-06-24 06:49:44,814 - use_cached_probe = False +2026-06-24 06:49:44,814 - use_cached_pos = False +2026-06-24 06:49:44,814 - +2026-06-24 06:49:44,814 - ### Initializing measurements ### +2026-06-24 06:49:44,814 - Loading measurements from source = 'file' +2026-06-24 06:49:44,814 - Detected measurement file type = '.h5' +2026-06-24 06:49:44,893 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:49:44,893 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:49:44,895 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0060) +2026-06-24 06:49:44,895 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:49:44,895 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:49:44,897 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:44,897 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:49:44,897 - Normalizing by max of the 2D mean pattern intensity: 0.0045133107 +2026-06-24 06:49:44,898 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:49:44,899 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0135, 1.3359) +2026-06-24 06:49:44,900 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:44,901 - Pattern total int. statistics (min, mean, max) = (219.5254, 221.3834, 223.1991), with min/max = 98.4% +2026-06-24 06:49:44,902 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0135, 1.3359) +2026-06-24 06:49:44,902 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:49:44,903 - +2026-06-24 06:49:44,903 - ### Setting up calibration ### +2026-06-24 06:49:44,903 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:49:44,903 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:49:44,903 - Radius of fitted bright field disk (RBF) = 8.21 px with meas_Npix = 128 +2026-06-24 06:49:44,903 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1284 +2026-06-24 06:49:44,903 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:49:44,903 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:49:45,127 - Initial guess: center=(63.65, 63.58), radius=8.21, Gaussian blur std=0.50 +2026-06-24 06:49:45,140 - Final fit: center=(63.65, 63.58), radius=8.21, Gaussian blur std=0.62 +2026-06-24 06:49:45,140 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.39 px with Npix = 128 +2026-06-24 06:49:45,140 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:49:45,140 - +2026-06-24 06:49:45,140 - ### Setting init_variables dict ### +2026-06-24 06:49:45,140 - Derived values given input init_params: +2026-06-24 06:49:45,140 - kv = 120.0 kV +2026-06-24 06:49:45,140 - wavelength = 0.0335 Ang +2026-06-24 06:49:45,140 - conv_angle = 10.975295066833496 mrad +2026-06-24 06:49:45,140 - Npix = 128 px +2026-06-24 06:49:45,140 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:45,140 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:45,140 - da = 1.3083 mrad +2026-06-24 06:49:45,140 - angleMax = 83.7304 mrad +2026-06-24 06:49:45,140 - RBF = 8.3891 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:49:45,140 - n_alpha = 7.6290 (# conv_angle) +2026-06-24 06:49:45,140 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:45,140 - Rayleigh-limited resolution = 1.8615 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:45,140 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:45,140 - +2026-06-24 06:49:45,140 - ### Initializing probe ### +2026-06-24 06:49:45,141 - Loading probe from source = 'simu' +2026-06-24 06:49:45,141 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:49:45,141 - Start simulating STEM probe +2026-06-24 06:49:45,141 - kv = 120.0 kV +2026-06-24 06:49:45,141 - wavelength = 0.0335 Ang +2026-06-24 06:49:45,141 - conv_angle = 10.975295066833496 mrad +2026-06-24 06:49:45,141 - Npix = 128 px +2026-06-24 06:49:45,141 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:45,141 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:45,141 - alpha_max = 83.7304 mrad +2026-06-24 06:49:45,141 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:45,141 - Rayleigh-limited resolution = 1.8615 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:45,141 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:45,141 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:49:45,141 - ------------------------------------------------------------------------------------ +2026-06-24 06:49:45,141 - C1,0 C1 -179.7770 - Defocus (C10 = -df) +2026-06-24 06:49:45,141 - C1,2 A1 22.0700 211.99 2-fold astigmatism +2026-06-24 06:49:45,141 - C2,1 3*B2 -932.5510 358.63 Axial coma +2026-06-24 06:49:45,141 - C2,3 A2 311.5040 295.30 3-fold astigmatism +2026-06-24 06:49:45,141 - C3,0 C3 4932964.0000 - Spherical aberration +2026-06-24 06:49:45,141 - C3,2 4*S3 -5480.4490 46.93 Axial star aberration +2026-06-24 06:49:45,141 - C3,4 A3 10596.8930 70.24 4-fold astigmatism +2026-06-24 06:49:45,141 - C4,1 4*B4 -454608.0620 25.82 Axial coma(4th) +2026-06-24 06:49:45,142 - C4,3 4*D4 -236445.5470 133.91 3-lobe aberration +2026-06-24 06:49:45,142 - C4,5 A4 155105.1720 337.08 5-fold astigmatism +2026-06-24 06:49:45,142 - C5,0 C5 -11338927.0000 - Spherical aberration (5th) +2026-06-24 06:49:45,142 - C5,2 6*S5 4239681.5000 137.23 Axial star aberration(5th) +2026-06-24 06:49:45,142 - C5,4 6*R5 18613014.0000 280.10 4-lobe aberration +2026-06-24 06:49:45,142 - C5,6 A5 15428138.0000 340.00 6-fold astigmatism +2026-06-24 06:49:45,145 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:49:45,145 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:49:45,145 - Creating 5 new probe modes from the major mode +2026-06-24 06:49:45,145 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:49:45,371 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:49:45,372 - Orthogonalizing 6 pmodes +2026-06-24 06:49:45,385 - Sorting 6 pmodes by their intensities +2026-06-24 06:49:45,385 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:49:45,386 - sum(|probe_data|**2) = 221.38, while meas_total_ints (min, mean, max) = (219.5254, 221.3834, 223.1991) +2026-06-24 06:49:45,386 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:49:45,386 - +2026-06-24 06:49:45,386 - ### Initializing probe positions ### +2026-06-24 06:49:45,386 - Loading probe positions from source = 'simu' +2026-06-24 06:49:45,386 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:49:45,386 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3008, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:49:45,386 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:49:45,388 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:49:45,388 - crop_pos 1st and last px coords (y,x) = ([15, 15], [37, 37]) +2026-06-24 06:49:45,389 - crop_pos extent (Ang) = [4.6 4.4] +2026-06-24 06:49:45,389 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:49:45,389 - +2026-06-24 06:49:45,389 - ### Initializing object ### +2026-06-24 06:49:45,389 - Loading object from source = 'simu' +2026-06-24 06:49:45,389 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:49:45,390 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:49:45,390 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 181, 181) +2026-06-24 06:49:45,390 - object extent (Z, Y, X) (Ang) = [20. 36.2 36.2] +2026-06-24 06:49:45,390 - +2026-06-24 06:49:45,390 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:49:45,390 - omode_occu (omode) = float32, (1,) +2026-06-24 06:49:45,390 - +2026-06-24 06:49:45,390 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:49:45,391 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:49:45,391 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:49:45,391 - +2026-06-24 06:49:45,391 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:49:45,391 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:49:45,391 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:49:45,391 - +2026-06-24 06:49:45,391 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:49:45,391 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:49:45,391 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:49:45,391 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:49:45,392 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:49:45,392 - crop positions (yx_min=[14 15], yx_max=[165 165]) are well contained inside object canvas (Ny,Nx) = (181, 181). +2026-06-24 06:49:45,392 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:49:45,392 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:49:45,392 - +2026-06-24 06:49:45,392 - ### Collecting reconstruction provenance ### +2026-06-24 06:49:45,392 - Reconstruction provenance is collected and initialized. +2026-06-24 06:49:45,392 - +2026-06-24 06:49:45,392 - ### Initializing loss function ### +2026-06-24 06:49:45,392 - Active loss types: +2026-06-24 06:49:45,392 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:49:45,392 - +2026-06-24 06:49:45,392 - ### Initializing constraint function ### +2026-06-24 06:49:45,392 - Active constraint types: +2026-06-24 06:49:45,392 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:49:45,392 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:49:45,392 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:49:45,392 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:49:45,392 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:49:45,392 - +2026-06-24 06:49:45,393 - ### Done initializing PtyRADSolver ### +2026-06-24 06:49:45,393 - +2026-06-24 06:49:45,525 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:49:45,526 - +2026-06-24 06:49:45,526 - ### Initializing PtychoModel model ### +2026-06-24 06:49:45,595 - ### PtychoModel optimizable variables ### +2026-06-24 06:49:45,595 - obja : torch.Size([1, 1, 181, 181]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:45,595 - objp : torch.Size([1, 1, 181, 181]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:45,595 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:49:45,596 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:49:45,596 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:49:45,596 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:49:45,596 - +2026-06-24 06:49:45,596 - ### Optimizable variables statitsics ### +2026-06-24 06:49:45,596 - Total measurement values : 4,194,304 +2026-06-24 06:49:45,596 - Total optimizing variables: 262,642 +2026-06-24 06:49:45,596 - Overdetermined ratio : 15.97 +2026-06-24 06:49:45,596 - +2026-06-24 06:49:45,596 - ### Model behavior ### +2026-06-24 06:49:45,596 - Tilt propagator : False +2026-06-24 06:49:45,596 - Change slice thickness : False +2026-06-24 06:49:45,596 - Detector blur : False +2026-06-24 06:49:45,596 - Preload data : True +2026-06-24 06:49:45,596 - On-the-fly meas padding : False +2026-06-24 06:49:45,596 - On-the-fly meas resample : False +2026-06-24 06:49:45,596 - On-the-fly simu match mode: None +2026-06-24 06:49:45,596 - +2026-06-24 06:49:45,638 - ### Done initializing PtychoModel model ### +2026-06-24 06:49:45,638 - +2026-06-24 06:49:45,638 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:49:45,638 - +2026-06-24 06:49:45,638 - ### Generating indices, batches, and output_path ### +2026-06-24 06:49:45,639 - d90 = 45.000 px or 9.000 Ang +2026-06-24 06:49:45,639 - Selecting indices with the 'full' mode +2026-06-24 06:49:46,096 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:49:46,181 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:49:46,181 - Original recon_dir_affixes = ['default'] +2026-06-24 06:49:46,182 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:49:46,187 - Path corrected for compatibility: +2026-06-24 06:49:46,187 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32_-5.48e+03_phi32_46.9_C34_1.06e+04_phi34_70.2_C41_-4.55e+05_phi41_25.8_C43_-2.36e+05_phi43_134_C45_1.55e+05_phi45_337_C50_-1.13e+07_C52_4.24e+06_phi52_137_C54_1.86e+07_phi54_280_C56_1.54e+07_phi56_340 +2026-06-24 06:49:46,187 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340 +2026-06-24 06:49:46,190 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340' is generated! +2026-06-24 06:49:46,359 - +2026-06-24 06:49:46,360 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/20260624_064946_ptyrad_log.txt ### +2026-06-24 06:49:46,360 - +2026-06-24 06:49:46,361 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:49:46,361 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:49:46,361 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:49:47,541 - Iter: 1, Total Loss: 1.0782, loss_single: 1.0782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:49:47,577 - Iter: 2, Total Loss: 1.0145, loss_single: 1.0145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:47,612 - Iter: 3, Total Loss: 0.9664, loss_single: 0.9664, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:49:47,647 - Iter: 4, Total Loss: 0.9239, loss_single: 0.9239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,683 - Iter: 5, Total Loss: 0.8836, loss_single: 0.8836, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,717 - Iter: 6, Total Loss: 0.8420, loss_single: 0.8420, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:49:47,753 - Iter: 7, Total Loss: 0.8049, loss_single: 0.8049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,788 - Iter: 8, Total Loss: 0.7688, loss_single: 0.7688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,823 - Iter: 9, Total Loss: 0.7377, loss_single: 0.7377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,858 - Iter: 10, Total Loss: 0.7088, loss_single: 0.7088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,893 - Iter: 11, Total Loss: 0.6773, loss_single: 0.6773, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:49:47,928 - Iter: 12, Total Loss: 0.6472, loss_single: 0.6472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,963 - Iter: 13, Total Loss: 0.6175, loss_single: 0.6175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:47,998 - Iter: 14, Total Loss: 0.5959, loss_single: 0.5959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,033 - Iter: 15, Total Loss: 0.5749, loss_single: 0.5749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,069 - Iter: 16, Total Loss: 0.5504, loss_single: 0.5504, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,104 - Iter: 17, Total Loss: 0.5285, loss_single: 0.5285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,139 - Iter: 18, Total Loss: 0.5085, loss_single: 0.5085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,175 - Iter: 19, Total Loss: 0.4937, loss_single: 0.4937, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,209 - Iter: 20, Total Loss: 0.4828, loss_single: 0.4828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:49:48,245 - Iter: 21, Total Loss: 0.4720, loss_single: 0.4720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:49:48,281 - Iter: 22, Total Loss: 0.4628, loss_single: 0.4628, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:49:48,316 - Iter: 23, Total Loss: 0.4540, loss_single: 0.4540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:49:48,351 - Iter: 24, Total Loss: 0.4461, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/simulation_data_aug2__sample_000036.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/simulation_data_aug2__sample_000036.yaml new file mode 100644 index 0000000000000000000000000000000000000000..32f0ba7a3fe673ba2128ed7ecfff6c3d0d568be4 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/simulation_data_aug2__sample_000036.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 10.975295066833496 + probe_aberrations: + C10: -179.77682495117188 + C12: 22.07014274597168 + C21: -932.550537109375 + C23: 311.5041809082031 + C30: 4932964.0 + C32: -5480.44873046875 + C34: 10596.892578125 + C41: -454608.0625 + C43: -236445.546875 + C45: 155105.171875 + C50: -11338927.0 + C52: 4239681.5 + C54: 18613014.0 + C56: 15428138.0 + phi12: 211.99191440200073 + phi21: 358.62692342868667 + phi23: 295.29631661406125 + phi32: 46.925585258522005 + phi34: 70.24121463192591 + phi41: 25.823413581896837 + phi43: 133.91441007494083 + phi45: 337.08387840906283 + phi52: 137.22957899238992 + phi54: 280.1029706167181 + phi56: 340.00545084540073 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.30078911781311035 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000036_measurement.h5 + key: measurement + random_seed: 20262151 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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0000000000000000000000000000000000000000..e024d7b3d92c5d12ac088079958e43e9f43f6826 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c8a85f07cb576b2f2a681dd1546b28fd04bcb0c0bab9efbc9d00c32053dde0bb +size 1053444 diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000036/c30_small__simulation_data_aug2__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-180_C12_22.1_phi12_212_C21_-933_phi21_359_C23_312_phi23_295_C30_4.93e+06_C32.54e+07_phi56_340/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:52ba2fe9ca397bba776889ae18508e2bf15b5394c16bb7a2089d0c31ad231346 +size 51215 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/20260624_065000_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/20260624_065000_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..a32f58344cfda852bc93cf0a34124ae0fcb76f91 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/20260624_065000_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:49:59,439 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:49:59,439 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:49:59,439 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:49:59,439 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:49:59,439 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:49:59,439 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:49:59,439 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:49:59,439 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:49:59,439 - +2026-06-24 06:49:59,548 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:49:59,548 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:49:59,548 - Accelerator.num_process = 1 +2026-06-24 06:49:59,548 - Accelerator.mixed_precision = no +2026-06-24 06:49:59,559 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:49:59,559 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:49:59,559 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:49:59,559 - +2026-06-24 06:49:59,559 - ### System information ### +2026-06-24 06:49:59,559 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:49:59,559 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:49:59,559 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:49:59,559 - Machine: x86_64 +2026-06-24 06:49:59,559 - Processor: x86_64 +2026-06-24 06:49:59,560 - Available CPU cores: 8 +2026-06-24 06:49:59,560 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:49:59,560 - +2026-06-24 06:49:59,560 - ### GPU information ### +2026-06-24 06:49:59,560 - CUDA Available: True +2026-06-24 06:49:59,560 - CUDA Version: 13.0 +2026-06-24 06:49:59,560 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:49:59,560 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:49:59,560 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:49:59,560 - In addition, Triton does not directly support Windows. +2026-06-24 06:49:59,560 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:49:59,575 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:49:59,575 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:49:59,575 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:49:59,575 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:49:59,575 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:49:59,575 - +2026-06-24 06:49:59,575 - ### Python information ### +2026-06-24 06:49:59,577 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:49:59,577 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:49:59,577 - +2026-06-24 06:49:59,577 - ### Packages information ### +2026-06-24 06:49:59,577 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:49:59,578 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:49:59,579 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:49:59,579 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:49:59,580 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:49:59,580 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:49:59,580 - +2026-06-24 06:49:59,580 - ### Loading params file ### +2026-06-24 06:49:59,580 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000037.yaml +2026-06-24 06:49:59,586 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:49:59,587 - Success! Params file validated and defaults applied. +2026-06-24 06:49:59,588 - +2026-06-24 06:49:59,588 - ### Setting GPU Device ### +2026-06-24 06:49:59,588 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:49:59,588 - +2026-06-24 06:49:59,588 - Random seed: 20262152 provided by params file +2026-06-24 06:49:59,588 - ### Initializing Initializer ### +2026-06-24 06:49:59,588 - init_params are displayed below: +2026-06-24 06:49:59,588 - random_seed: 20262152 +2026-06-24 06:49:59,588 - probe_illum_type: electron +2026-06-24 06:49:59,588 - probe_kv: 80.0 +2026-06-24 06:49:59,588 - probe_conv_angle: 14.283119201660156 +2026-06-24 06:49:59,588 - probe_aberrations: {'C10': -369.369, 'C12': -1.698, 'phi12': 63.495, 'C21': -999.245, 'phi21': 159.432, 'C23': 442.398, 'phi23': 241.439, 'C30': 50560.504, 'C32': -10546.754, 'phi32': 334.681, 'C34': -5308.803, 'phi34': 221.868, 'C41': -241810.453, 'phi41': 347.746, 'C43': 143647.641, 'phi43': 118.914, 'C45': 367854.656, 'phi45': 28.354, 'C50': -233325408.0, 'C52': 3753429.0, 'phi52': 116.895, 'C54': -17457996.0, 'phi54': 302.754, 'C56': -1090239.125, 'phi56': 177.136} +2026-06-24 06:49:59,588 - beam_kev: None +2026-06-24 06:49:59,588 - probe_dRn: None +2026-06-24 06:49:59,588 - probe_Rn: None +2026-06-24 06:49:59,588 - probe_D_H: None +2026-06-24 06:49:59,589 - probe_D_FZP: None +2026-06-24 06:49:59,589 - probe_Ls: None +2026-06-24 06:49:59,589 - meas_Npix: 128 +2026-06-24 06:49:59,589 - pos_N_scans: 256 +2026-06-24 06:49:59,589 - pos_N_scan_slow: 16 +2026-06-24 06:49:59,589 - pos_N_scan_fast: 16 +2026-06-24 06:49:59,589 - pos_scan_step_size: 0.5203185081481934 +2026-06-24 06:49:59,589 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:49:59,589 - probe_pmode_max: 6 +2026-06-24 06:49:59,589 - probe_pmode_init_pows: [0.02] +2026-06-24 06:49:59,589 - obj_omode_max: 1 +2026-06-24 06:49:59,589 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:49:59,589 - obj_Nlayer: 1 +2026-06-24 06:49:59,589 - obj_slice_thickness: 20.0 +2026-06-24 06:49:59,589 - simu_Npix: None +2026-06-24 06:49:59,589 - simu_match_mode: None +2026-06-24 06:49:59,589 - meas_permute: None +2026-06-24 06:49:59,589 - meas_reshape: [256, 128, 128] +2026-06-24 06:49:59,589 - meas_flipT: [0, 0, 0] +2026-06-24 06:49:59,589 - meas_crop: None +2026-06-24 06:49:59,589 - meas_pad: None +2026-06-24 06:49:59,589 - meas_resample: None +2026-06-24 06:49:59,589 - meas_add_source_size: None +2026-06-24 06:49:59,589 - meas_add_detector_blur: None +2026-06-24 06:49:59,589 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:49:59,589 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:49:59,589 - meas_add_poisson_noise: None +2026-06-24 06:49:59,589 - meas_export: None +2026-06-24 06:49:59,589 - probe_permute: None +2026-06-24 06:49:59,589 - probe_z_shift: None +2026-06-24 06:49:59,589 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:49:59,589 - pos_scan_flipT: None +2026-06-24 06:49:59,589 - pos_scan_affine: None +2026-06-24 06:49:59,589 - pos_scan_rand_std: 0.15 +2026-06-24 06:49:59,589 - obj_z_crop: None +2026-06-24 06:49:59,589 - obj_z_pad: None +2026-06-24 06:49:59,589 - obj_z_resample: None +2026-06-24 06:49:59,589 - meas_source: file +2026-06-24 06:49:59,589 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000037_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:49:59,589 - probe_source: simu +2026-06-24 06:49:59,590 - probe_params: None +2026-06-24 06:49:59,590 - pos_source: simu +2026-06-24 06:49:59,590 - pos_params: None +2026-06-24 06:49:59,590 - obj_source: simu +2026-06-24 06:49:59,590 - obj_params: None +2026-06-24 06:49:59,590 - tilt_source: simu +2026-06-24 06:49:59,590 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:49:59,590 - +2026-06-24 06:49:59,590 - ### Initializing cache ### +2026-06-24 06:49:59,590 - use_cached_obj = False +2026-06-24 06:49:59,590 - use_cached_probe = False +2026-06-24 06:49:59,590 - use_cached_pos = False +2026-06-24 06:49:59,590 - +2026-06-24 06:49:59,590 - ### Initializing measurements ### +2026-06-24 06:49:59,590 - Loading measurements from source = 'file' +2026-06-24 06:49:59,590 - Detected measurement file type = '.h5' +2026-06-24 06:49:59,669 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:49:59,669 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:49:59,671 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0056) +2026-06-24 06:49:59,671 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:49:59,671 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:49:59,673 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:59,673 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:49:59,673 - Normalizing by max of the 2D mean pattern intensity: 0.003776774 +2026-06-24 06:49:59,674 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:49:59,675 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0161, 1.4929) +2026-06-24 06:49:59,676 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:49:59,677 - Pattern total int. statistics (min, mean, max) = (261.8257, 263.1338, 264.7841), with min/max = 98.9% +2026-06-24 06:49:59,678 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0161, 1.4929) +2026-06-24 06:49:59,678 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:49:59,678 - +2026-06-24 06:49:59,678 - ### Setting up calibration ### +2026-06-24 06:49:59,678 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:49:59,678 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:49:59,679 - Radius of fitted bright field disk (RBF) = 8.67 px with meas_Npix = 128 +2026-06-24 06:49:59,680 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1354 +2026-06-24 06:49:59,680 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:49:59,680 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:49:59,912 - Initial guess: center=(63.60, 63.62), radius=8.67, Gaussian blur std=0.50 +2026-06-24 06:49:59,925 - Final fit: center=(63.60, 63.62), radius=8.67, Gaussian blur std=0.65 +2026-06-24 06:49:59,925 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.76 px with Npix = 128 +2026-06-24 06:49:59,925 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:49:59,925 - +2026-06-24 06:49:59,925 - ### Setting init_variables dict ### +2026-06-24 06:49:59,925 - Derived values given input init_params: +2026-06-24 06:49:59,925 - kv = 80.0 kV +2026-06-24 06:49:59,925 - wavelength = 0.0418 Ang +2026-06-24 06:49:59,926 - conv_angle = 14.283119201660156 mrad +2026-06-24 06:49:59,926 - Npix = 128 px +2026-06-24 06:49:59,926 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:59,926 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:59,926 - da = 1.6311 mrad +2026-06-24 06:49:59,926 - angleMax = 104.3929 mrad +2026-06-24 06:49:59,926 - RBF = 8.7565 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:49:59,926 - n_alpha = 7.3088 (# conv_angle) +2026-06-24 06:49:59,926 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:59,926 - Rayleigh-limited resolution = 1.7834 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:59,926 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:59,926 - +2026-06-24 06:49:59,926 - ### Initializing probe ### +2026-06-24 06:49:59,926 - Loading probe from source = 'simu' +2026-06-24 06:49:59,926 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:49:59,926 - Start simulating STEM probe +2026-06-24 06:49:59,926 - kv = 80.0 kV +2026-06-24 06:49:59,926 - wavelength = 0.0418 Ang +2026-06-24 06:49:59,926 - conv_angle = 14.283119201660156 mrad +2026-06-24 06:49:59,926 - Npix = 128 px +2026-06-24 06:49:59,927 - dk = 0.0391 Ang^-1 +2026-06-24 06:49:59,927 - kMax = 2.5000 Ang^-1 +2026-06-24 06:49:59,927 - alpha_max = 104.3929 mrad +2026-06-24 06:49:59,927 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:49:59,927 - Rayleigh-limited resolution = 1.7834 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:49:59,927 - Real space probe extent = 25.6000 Ang +2026-06-24 06:49:59,927 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:49:59,927 - ------------------------------------------------------------------------------------- +2026-06-24 06:49:59,927 - C1,0 C1 -369.3690 - Defocus (C10 = -df) +2026-06-24 06:49:59,927 - C1,2 A1 -1.6980 63.49 2-fold astigmatism +2026-06-24 06:49:59,927 - C2,1 3*B2 -999.2450 159.43 Axial coma +2026-06-24 06:49:59,927 - C2,3 A2 442.3980 241.44 3-fold astigmatism +2026-06-24 06:49:59,927 - C3,0 C3 50560.5040 - Spherical aberration +2026-06-24 06:49:59,927 - C3,2 4*S3 -10546.7540 334.68 Axial star aberration +2026-06-24 06:49:59,927 - C3,4 A3 -5308.8030 221.87 4-fold astigmatism +2026-06-24 06:49:59,927 - C4,1 4*B4 -241810.4530 347.75 Axial coma(4th) +2026-06-24 06:49:59,927 - C4,3 4*D4 143647.6410 118.91 3-lobe aberration +2026-06-24 06:49:59,927 - C4,5 A4 367854.6560 28.35 5-fold astigmatism +2026-06-24 06:49:59,927 - C5,0 C5 -233325408.0000 - Spherical aberration (5th) +2026-06-24 06:49:59,927 - C5,2 6*S5 3753429.0000 116.89 Axial star aberration(5th) +2026-06-24 06:49:59,927 - C5,4 6*R5 -17457996.0000 302.75 4-lobe aberration +2026-06-24 06:49:59,927 - C5,6 A5 -1090239.1250 177.14 6-fold astigmatism +2026-06-24 06:49:59,931 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:49:59,931 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:49:59,931 - Creating 5 new probe modes from the major mode +2026-06-24 06:49:59,931 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:50:00,032 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:50:00,034 - Orthogonalizing 6 pmodes +2026-06-24 06:50:00,037 - Sorting 6 pmodes by their intensities +2026-06-24 06:50:00,037 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:50:00,038 - sum(|probe_data|**2) = 263.13, while meas_total_ints (min, mean, max) = (261.8257, 263.1338, 264.7841) +2026-06-24 06:50:00,038 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:50:00,038 - +2026-06-24 06:50:00,038 - ### Initializing probe positions ### +2026-06-24 06:50:00,038 - Loading probe positions from source = 'simu' +2026-06-24 06:50:00,038 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:50:00,038 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5203, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:50:00,038 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:50:00,040 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:50:00,040 - crop_pos 1st and last px coords (y,x) = ([17, 17], [56, 55]) +2026-06-24 06:50:00,041 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 06:50:00,041 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:50:00,041 - +2026-06-24 06:50:00,041 - ### Initializing object ### +2026-06-24 06:50:00,041 - Loading object from source = 'simu' +2026-06-24 06:50:00,041 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:50:00,042 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:50:00,042 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 201, 201) +2026-06-24 06:50:00,042 - object extent (Z, Y, X) (Ang) = [20. 40.2 40.2] +2026-06-24 06:50:00,043 - +2026-06-24 06:50:00,043 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:50:00,043 - omode_occu (omode) = float32, (1,) +2026-06-24 06:50:00,043 - +2026-06-24 06:50:00,043 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:50:00,043 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:50:00,043 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:50:00,043 - +2026-06-24 06:50:00,043 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:50:00,044 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:50:00,044 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:50:00,044 - +2026-06-24 06:50:00,044 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:50:00,044 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:50:00,044 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:50:00,044 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:50:00,044 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:50:00,044 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (201, 201). +2026-06-24 06:50:00,044 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:50:00,044 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:50:00,044 - +2026-06-24 06:50:00,044 - ### Collecting reconstruction provenance ### +2026-06-24 06:50:00,044 - Reconstruction provenance is collected and initialized. +2026-06-24 06:50:00,044 - +2026-06-24 06:50:00,044 - ### Initializing loss function ### +2026-06-24 06:50:00,044 - Active loss types: +2026-06-24 06:50:00,044 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:50:00,044 - +2026-06-24 06:50:00,044 - ### Initializing constraint function ### +2026-06-24 06:50:00,044 - Active constraint types: +2026-06-24 06:50:00,044 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:50:00,045 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:50:00,045 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:50:00,045 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:50:00,045 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:50:00,045 - +2026-06-24 06:50:00,045 - ### Done initializing PtyRADSolver ### +2026-06-24 06:50:00,045 - +2026-06-24 06:50:00,170 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:50:00,170 - +2026-06-24 06:50:00,170 - ### Initializing PtychoModel model ### +2026-06-24 06:50:00,241 - ### PtychoModel optimizable variables ### +2026-06-24 06:50:00,242 - obja : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:00,242 - objp : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:00,242 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:50:00,242 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:50:00,242 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:50:00,242 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:00,242 - +2026-06-24 06:50:00,242 - ### Optimizable variables statitsics ### +2026-06-24 06:50:00,242 - Total measurement values : 4,194,304 +2026-06-24 06:50:00,242 - Total optimizing variables: 277,922 +2026-06-24 06:50:00,242 - Overdetermined ratio : 15.09 +2026-06-24 06:50:00,242 - +2026-06-24 06:50:00,242 - ### Model behavior ### +2026-06-24 06:50:00,242 - Tilt propagator : False +2026-06-24 06:50:00,242 - Change slice thickness : False +2026-06-24 06:50:00,242 - Detector blur : False +2026-06-24 06:50:00,242 - Preload data : True +2026-06-24 06:50:00,242 - On-the-fly meas padding : False +2026-06-24 06:50:00,242 - On-the-fly meas resample : False +2026-06-24 06:50:00,242 - On-the-fly simu match mode: None +2026-06-24 06:50:00,242 - +2026-06-24 06:50:00,284 - ### Done initializing PtychoModel model ### +2026-06-24 06:50:00,284 - +2026-06-24 06:50:00,284 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:50:00,284 - +2026-06-24 06:50:00,284 - ### Generating indices, batches, and output_path ### +2026-06-24 06:50:00,286 - d90 = 63.000 px or 12.600 Ang +2026-06-24 06:50:00,286 - Selecting indices with the 'full' mode +2026-06-24 06:50:00,747 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:50:00,823 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:50:00,823 - Original recon_dir_affixes = ['default'] +2026-06-24 06:50:00,824 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:50:00,829 - Path corrected for compatibility: +2026-06-24 06:50:00,829 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C32_-1.05e+04_phi32_335_C34_-5.31e+03_phi34_222_C41_-2.42e+05_phi41_348_C43_1.44e+05_phi43_119_C45_3.68e+05_phi45_28.4_C50_-2.33e+08_C52_3.75e+06_phi52_117_C54_-1.75e+07_phi54_303_C56_-1.09e+06_phi56_177 +2026-06-24 06:50:00,829 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177 +2026-06-24 06:50:00,830 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177' is generated! +2026-06-24 06:50:00,985 - +2026-06-24 06:50:00,986 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/20260624_065000_ptyrad_log.txt ### +2026-06-24 06:50:00,986 - +2026-06-24 06:50:00,988 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:50:00,988 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:50:00,988 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:50:02,178 - Iter: 1, Total Loss: 1.0899, loss_single: 1.0899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 06:50:02,215 - Iter: 2, Total Loss: 1.0444, loss_single: 1.0444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:02,251 - Iter: 3, Total Loss: 1.0099, loss_single: 1.0099, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,286 - Iter: 4, Total Loss: 0.9776, loss_single: 0.9776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,322 - Iter: 5, Total Loss: 0.9495, loss_single: 0.9495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,357 - Iter: 6, Total Loss: 0.9210, loss_single: 0.9210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,392 - Iter: 7, Total Loss: 0.8897, loss_single: 0.8897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:02,428 - Iter: 8, Total Loss: 0.8597, loss_single: 0.8597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,463 - Iter: 9, Total Loss: 0.8313, loss_single: 0.8313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,498 - Iter: 10, Total Loss: 0.8013, loss_single: 0.8013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,534 - Iter: 11, Total Loss: 0.7648, loss_single: 0.7648, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:02,570 - Iter: 12, Total Loss: 0.7295, loss_single: 0.7295, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,605 - Iter: 13, Total Loss: 0.6960, loss_single: 0.6960, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,640 - Iter: 14, Total Loss: 0.6615, loss_single: 0.6615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:02,675 - Iter: 15, Total Loss: 0.6335, loss_single: 0.6335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,710 - Iter: 16, Total Loss: 0.6084, loss_single: 0.6084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,745 - Iter: 17, Total Loss: 0.5808, loss_single: 0.5808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,780 - Iter: 18, Total Loss: 0.5564, loss_single: 0.5564, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,816 - Iter: 19, Total Loss: 0.5344, loss_single: 0.5344, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,851 - Iter: 20, Total Loss: 0.5117, loss_single: 0.5117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,886 - Iter: 21, Total Loss: 0.4881, loss_single: 0.4881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,923 - Iter: 22, Total Loss: 0.4629, loss_single: 0.4629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:02,958 - Iter: 23, Total Loss: 0.4401, loss_single: 0.4401, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:02,993 - Iter: 24, Total Loss: 0.4195, loss_single: 0.4195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,028 - Iter: 25, Total Loss: 0.4031, loss_single: 0.4031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,063 - Iter: 26, Total Loss: 0.3923, loss_single: 0.3923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,099 - Iter: 27, Total Loss: 0.3819, loss_single: 0.3819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,134 - Iter: 28, Total Loss: 0.3726, loss_single: 0.3726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:03,169 - Iter: 29, Total Loss: 0.3658, loss_single: 0.3658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,205 - Iter: 30, Total Loss: 0.3595, loss_single: 0.3595, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,240 - Iter: 31, Total Loss: 0.3534, loss_single: 0.3534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,275 - Iter: 32, Total Loss: 0.3482, loss_single: 0.3482, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,311 - Iter: 33, Total Loss: 0.3444, loss_single: 0.3444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,346 - Iter: 34, Total Loss: 0.3404, loss_single: 0.3404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,381 - Iter: 35, Total Loss: 0.3359, loss_single: 0.3359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,417 - Iter: 36, Total Loss: 0.3323, loss_single: 0.3323, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,452 - Iter: 37, Total Loss: 0.3293, loss_single: 0.3293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,487 - Iter: 38, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,522 - Iter: 39, Total Loss: 0.3252, loss_single: 0.3252, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,557 - Iter: 40, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,595 - Iter: 41, Total Loss: 0.3222, loss_single: 0.3222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,630 - Iter: 42, Total Loss: 0.3212, loss_single: 0.3212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,665 - Iter: 43, Total Loss: 0.3203, loss_single: 0.3203, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,701 - Iter: 44, Total Loss: 0.3196, loss_single: 0.3196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,736 - Iter: 45, Total Loss: 0.3191, loss_single: 0.3191, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,771 - Iter: 46, Total Loss: 0.3185, loss_single: 0.3185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,807 - Iter: 47, Total Loss: 0.3181, loss_single: 0.3181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,841 - Iter: 48, Total Loss: 0.3177, loss_single: 0.3177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:03,876 - Iter: 49, Total Loss: 0.3173, loss_single: 0.3173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:03,912 - Iter: 50, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,947 - Iter: 51, Total Loss: 0.3166, loss_single: 0.3166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:03,982 - Iter: 52, Total Loss: 0.3162, loss_single: 0.3162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:04,018 - Iter: 53, Total Loss: 0.3159, loss_single: 0.3159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:04,053 - Iter: 54, Total Loss: 0.3156, loss_single: 0.3156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:04,087 - Iter: 55, Total Loss: 0.3153, loss_single: 0.3153, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:04,123 - Iter: 56, Total Loss: 0.3150, loss_single: 0.3150, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:04,158 - Iter: 57, Total Loss: 0.3148, loss_single: 0.3148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:50:04,193 - Iter: 58, Total Loss: 0.3145, loss_single: 0.3145, loss_poissn: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/simulation_data_aug2__sample_000037.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 14.283119201660156 + probe_aberrations: + C10: -369.3692626953125 + C12: -1.6984858512878418 + C21: -999.2454833984375 + C23: 442.3984069824219 + C30: 50560.50390625 + C32: -10546.75390625 + C34: -5308.80322265625 + C41: -241810.453125 + C43: 143647.640625 + C45: 367854.65625 + C50: -233325408.0 + C52: 3753429.0 + C54: -17457996.0 + C56: -1090239.125 + phi12: 63.495357807595305 + phi21: 159.4321334178919 + phi23: 241.43910021597344 + phi32: 334.6808266137556 + phi34: 221.86842258335253 + phi41: 347.74574906193936 + phi43: 118.91401692165053 + phi45: 28.35363154671867 + phi52: 116.89520424829152 + phi54: 302.7537083951779 + phi56: 177.13551929370138 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5203185081481934 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000037_measurement.h5 + key: measurement + random_seed: 20262152 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug2__sample_000037 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000037/c30_small__simulation_data_aug2__sample_000037_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-369_C12_-1.7_phi12_63.5_C21_-999_phi21_159_C23_442_phi23_241_C30_5.06e+04_C3.09e+06_phi56_177/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/20260624_065016_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6b1a22f14c6357b6fc39e7bda83db85dd66f062 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/20260624_065016_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:50:14,280 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:50:14,281 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:50:14,281 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:50:14,281 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:50:14,281 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:50:14,281 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:50:14,281 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:50:14,281 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:50:14,281 - +2026-06-24 06:50:14,389 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:50:14,389 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:50:14,389 - Accelerator.num_process = 1 +2026-06-24 06:50:14,389 - Accelerator.mixed_precision = no +2026-06-24 06:50:14,399 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:50:14,400 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:50:14,400 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:50:14,400 - +2026-06-24 06:50:14,400 - ### System information ### +2026-06-24 06:50:14,400 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:50:14,400 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:50:14,400 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:50:14,400 - Machine: x86_64 +2026-06-24 06:50:14,400 - Processor: x86_64 +2026-06-24 06:50:14,400 - Available CPU cores: 8 +2026-06-24 06:50:14,400 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:50:14,400 - +2026-06-24 06:50:14,400 - ### GPU information ### +2026-06-24 06:50:14,400 - CUDA Available: True +2026-06-24 06:50:14,400 - CUDA Version: 13.0 +2026-06-24 06:50:14,401 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:50:14,401 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:50:14,401 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:50:14,401 - In addition, Triton does not directly support Windows. +2026-06-24 06:50:14,401 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:50:14,428 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:50:14,428 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:50:14,428 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:50:14,428 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:50:14,428 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:50:14,428 - +2026-06-24 06:50:14,428 - ### Python information ### +2026-06-24 06:50:14,430 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:50:14,430 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:50:14,430 - +2026-06-24 06:50:14,430 - ### Packages information ### +2026-06-24 06:50:14,431 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:50:14,432 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:50:14,433 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:50:14,433 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:50:14,434 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:50:14,434 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:50:14,434 - +2026-06-24 06:50:14,434 - ### Loading params file ### +2026-06-24 06:50:14,434 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug2__sample_000038.yaml +2026-06-24 06:50:14,440 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:50:14,441 - Success! Params file validated and defaults applied. +2026-06-24 06:50:14,441 - +2026-06-24 06:50:14,441 - ### Setting GPU Device ### +2026-06-24 06:50:14,442 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:50:14,442 - +2026-06-24 06:50:14,442 - Random seed: 20262153 provided by params file +2026-06-24 06:50:14,442 - ### Initializing Initializer ### +2026-06-24 06:50:14,442 - init_params are displayed below: +2026-06-24 06:50:14,442 - random_seed: 20262153 +2026-06-24 06:50:14,442 - probe_illum_type: electron +2026-06-24 06:50:14,442 - probe_kv: 60.0 +2026-06-24 06:50:14,442 - probe_conv_angle: 12.50350570678711 +2026-06-24 06:50:14,442 - probe_aberrations: {'C10': -101.115, 'C12': 6.696, 'phi12': 301.953, 'C21': 219.038, 'phi21': 34.371, 'C23': -794.731, 'phi23': 36.721, 'C30': 3345945.5, 'C32': -2283.467, 'phi32': 171.96, 'C34': -1149.375, 'phi34': 302.81, 'C41': 27532.256, 'phi41': 195.383, 'C43': 458034.938, 'phi43': 13.067, 'C45': -293829.312, 'phi45': 188.602, 'C50': 379107904.0, 'C52': 8994720.0, 'phi52': 132.484, 'C54': -17523970.0, 'phi54': 116.027, 'C56': -16382928.0, 'phi56': 216.26} +2026-06-24 06:50:14,442 - beam_kev: None +2026-06-24 06:50:14,442 - probe_dRn: None +2026-06-24 06:50:14,442 - probe_Rn: None +2026-06-24 06:50:14,442 - probe_D_H: None +2026-06-24 06:50:14,442 - probe_D_FZP: None +2026-06-24 06:50:14,442 - probe_Ls: None +2026-06-24 06:50:14,442 - meas_Npix: 128 +2026-06-24 06:50:14,442 - pos_N_scans: 256 +2026-06-24 06:50:14,442 - pos_N_scan_slow: 16 +2026-06-24 06:50:14,443 - pos_N_scan_fast: 16 +2026-06-24 06:50:14,443 - pos_scan_step_size: 0.45035433769226074 +2026-06-24 06:50:14,443 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:50:14,443 - probe_pmode_max: 6 +2026-06-24 06:50:14,443 - probe_pmode_init_pows: [0.02] +2026-06-24 06:50:14,443 - obj_omode_max: 1 +2026-06-24 06:50:14,443 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:50:14,443 - obj_Nlayer: 1 +2026-06-24 06:50:14,443 - obj_slice_thickness: 20.0 +2026-06-24 06:50:14,443 - simu_Npix: None +2026-06-24 06:50:14,443 - simu_match_mode: None +2026-06-24 06:50:14,443 - meas_permute: None +2026-06-24 06:50:14,443 - meas_reshape: [256, 128, 128] +2026-06-24 06:50:14,443 - meas_flipT: [0, 0, 0] +2026-06-24 06:50:14,443 - meas_crop: None +2026-06-24 06:50:14,443 - meas_pad: None +2026-06-24 06:50:14,443 - meas_resample: None +2026-06-24 06:50:14,443 - meas_add_source_size: None +2026-06-24 06:50:14,443 - meas_add_detector_blur: None +2026-06-24 06:50:14,443 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:50:14,443 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:50:14,443 - meas_add_poisson_noise: None +2026-06-24 06:50:14,443 - meas_export: None +2026-06-24 06:50:14,443 - probe_permute: None +2026-06-24 06:50:14,443 - probe_z_shift: None +2026-06-24 06:50:14,443 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:50:14,443 - pos_scan_flipT: None +2026-06-24 06:50:14,443 - pos_scan_affine: None +2026-06-24 06:50:14,443 - pos_scan_rand_std: 0.15 +2026-06-24 06:50:14,443 - obj_z_crop: None +2026-06-24 06:50:14,443 - obj_z_pad: None +2026-06-24 06:50:14,443 - obj_z_resample: None +2026-06-24 06:50:14,443 - meas_source: file +2026-06-24 06:50:14,443 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000038_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:50:14,443 - probe_source: simu +2026-06-24 06:50:14,443 - probe_params: None +2026-06-24 06:50:14,443 - pos_source: simu +2026-06-24 06:50:14,443 - pos_params: None +2026-06-24 06:50:14,443 - obj_source: simu +2026-06-24 06:50:14,443 - obj_params: None +2026-06-24 06:50:14,443 - tilt_source: simu +2026-06-24 06:50:14,444 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:50:14,444 - +2026-06-24 06:50:14,444 - ### Initializing cache ### +2026-06-24 06:50:14,444 - use_cached_obj = False +2026-06-24 06:50:14,444 - use_cached_probe = False +2026-06-24 06:50:14,444 - use_cached_pos = False +2026-06-24 06:50:14,444 - +2026-06-24 06:50:14,444 - ### Initializing measurements ### +2026-06-24 06:50:14,444 - Loading measurements from source = 'file' +2026-06-24 06:50:14,444 - Detected measurement file type = '.h5' +2026-06-24 06:50:14,524 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:50:14,524 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:50:14,525 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0077) +2026-06-24 06:50:14,525 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:50:14,525 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:50:14,527 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:50:14,527 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:50:14,528 - Normalizing by max of the 2D mean pattern intensity: 0.0064998898 +2026-06-24 06:50:14,528 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:50:14,530 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0093, 1.1843) +2026-06-24 06:50:14,530 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:50:14,531 - Pattern total int. statistics (min, mean, max) = (151.9998, 152.8856, 153.6971), with min/max = 98.9% +2026-06-24 06:50:14,533 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0093, 1.1843) +2026-06-24 06:50:14,533 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:50:14,533 - +2026-06-24 06:50:14,533 - ### Setting up calibration ### +2026-06-24 06:50:14,533 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:50:14,533 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:50:14,533 - Radius of fitted bright field disk (RBF) = 6.43 px with meas_Npix = 128 +2026-06-24 06:50:14,533 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1005 +2026-06-24 06:50:14,533 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:50:14,533 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:50:14,754 - Initial guess: center=(63.62, 63.65), radius=6.43, Gaussian blur std=0.50 +2026-06-24 06:50:14,766 - Final fit: center=(63.62, 63.65), radius=6.43, Gaussian blur std=0.70 +2026-06-24 06:50:14,766 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 6.58 px with Npix = 128 +2026-06-24 06:50:14,766 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:50:14,766 - +2026-06-24 06:50:14,766 - ### Setting init_variables dict ### +2026-06-24 06:50:14,766 - Derived values given input init_params: +2026-06-24 06:50:14,766 - kv = 60.0 kV +2026-06-24 06:50:14,766 - wavelength = 0.0487 Ang +2026-06-24 06:50:14,766 - conv_angle = 12.50350570678711 mrad +2026-06-24 06:50:14,766 - Npix = 128 px +2026-06-24 06:50:14,766 - dk = 0.0391 Ang^-1 +2026-06-24 06:50:14,766 - kMax = 2.5000 Ang^-1 +2026-06-24 06:50:14,766 - da = 1.9008 mrad +2026-06-24 06:50:14,766 - angleMax = 121.6515 mrad +2026-06-24 06:50:14,766 - RBF = 6.5780 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:50:14,766 - n_alpha = 9.7294 (# conv_angle) +2026-06-24 06:50:14,766 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:50:14,767 - Rayleigh-limited resolution = 2.3740 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:50:14,767 - Real space probe extent = 25.6000 Ang +2026-06-24 06:50:14,767 - +2026-06-24 06:50:14,767 - ### Initializing probe ### +2026-06-24 06:50:14,767 - Loading probe from source = 'simu' +2026-06-24 06:50:14,767 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:50:14,767 - Start simulating STEM probe +2026-06-24 06:50:14,767 - kv = 60.0 kV +2026-06-24 06:50:14,767 - wavelength = 0.0487 Ang +2026-06-24 06:50:14,767 - conv_angle = 12.50350570678711 mrad +2026-06-24 06:50:14,767 - Npix = 128 px +2026-06-24 06:50:14,767 - dk = 0.0391 Ang^-1 +2026-06-24 06:50:14,767 - kMax = 2.5000 Ang^-1 +2026-06-24 06:50:14,767 - alpha_max = 121.6515 mrad +2026-06-24 06:50:14,767 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:50:14,767 - Rayleigh-limited resolution = 2.3740 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:50:14,767 - Real space probe extent = 25.6000 Ang +2026-06-24 06:50:14,767 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:50:14,767 - ------------------------------------------------------------------------------------ +2026-06-24 06:50:14,767 - C1,0 C1 -101.1150 - Defocus (C10 = -df) +2026-06-24 06:50:14,767 - C1,2 A1 6.6960 301.95 2-fold astigmatism +2026-06-24 06:50:14,767 - C2,1 3*B2 219.0380 34.37 Axial coma +2026-06-24 06:50:14,767 - C2,3 A2 -794.7310 36.72 3-fold astigmatism +2026-06-24 06:50:14,767 - C3,0 C3 3345945.5000 - Spherical aberration +2026-06-24 06:50:14,768 - C3,2 4*S3 -2283.4670 171.96 Axial star aberration +2026-06-24 06:50:14,768 - C3,4 A3 -1149.3750 302.81 4-fold astigmatism +2026-06-24 06:50:14,768 - C4,1 4*B4 27532.2560 195.38 Axial coma(4th) +2026-06-24 06:50:14,768 - C4,3 4*D4 458034.9380 13.07 3-lobe aberration +2026-06-24 06:50:14,768 - C4,5 A4 -293829.3120 188.60 5-fold astigmatism +2026-06-24 06:50:14,768 - C5,0 C5 379107904.0000 - Spherical aberration (5th) +2026-06-24 06:50:14,768 - C5,2 6*S5 8994720.0000 132.48 Axial star aberration(5th) +2026-06-24 06:50:14,768 - C5,4 6*R5 -17523970.0000 116.03 4-lobe aberration +2026-06-24 06:50:14,768 - C5,6 A5 -16382928.0000 216.26 6-fold astigmatism +2026-06-24 06:50:14,770 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:50:14,771 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:50:14,771 - Creating 5 new probe modes from the major mode +2026-06-24 06:50:14,771 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:50:15,143 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:50:15,144 - Orthogonalizing 6 pmodes +2026-06-24 06:50:15,155 - Sorting 6 pmodes by their intensities +2026-06-24 06:50:15,155 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:50:15,156 - sum(|probe_data|**2) = 152.89, while meas_total_ints (min, mean, max) = (151.9998, 152.8856, 153.6971) +2026-06-24 06:50:15,156 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:50:15,156 - +2026-06-24 06:50:15,156 - ### Initializing probe positions ### +2026-06-24 06:50:15,156 - Loading probe positions from source = 'simu' +2026-06-24 06:50:15,156 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:50:15,156 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4504, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:50:15,157 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:50:15,159 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:50:15,159 - crop_pos 1st and last px coords (y,x) = ([16, 16], [50, 50]) +2026-06-24 06:50:15,159 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 06:50:15,159 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:50:15,159 - +2026-06-24 06:50:15,159 - ### Initializing object ### +2026-06-24 06:50:15,159 - Loading object from source = 'simu' +2026-06-24 06:50:15,159 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:50:15,160 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:50:15,160 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 195, 195) +2026-06-24 06:50:15,161 - object extent (Z, Y, X) (Ang) = [20. 39. 39.] +2026-06-24 06:50:15,161 - +2026-06-24 06:50:15,161 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:50:15,161 - omode_occu (omode) = float32, (1,) +2026-06-24 06:50:15,161 - +2026-06-24 06:50:15,161 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:50:15,161 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0487 Ang +2026-06-24 06:50:15,162 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:50:15,162 - +2026-06-24 06:50:15,162 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:50:15,162 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:50:15,162 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:50:15,162 - +2026-06-24 06:50:15,162 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:50:15,162 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:50:15,162 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:50:15,162 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:50:15,162 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:50:15,162 - crop positions (yx_min=[16 16], yx_max=[178 178]) are well contained inside object canvas (Ny,Nx) = (195, 195). +2026-06-24 06:50:15,162 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:50:15,162 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:50:15,162 - +2026-06-24 06:50:15,162 - ### Collecting reconstruction provenance ### +2026-06-24 06:50:15,162 - Reconstruction provenance is collected and initialized. +2026-06-24 06:50:15,162 - +2026-06-24 06:50:15,162 - ### Initializing loss function ### +2026-06-24 06:50:15,162 - Active loss types: +2026-06-24 06:50:15,162 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:50:15,163 - +2026-06-24 06:50:15,163 - ### Initializing constraint function ### +2026-06-24 06:50:15,163 - Active constraint types: +2026-06-24 06:50:15,163 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:50:15,163 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:50:15,163 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:50:15,163 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:50:15,163 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:50:15,163 - +2026-06-24 06:50:15,163 - ### Done initializing PtyRADSolver ### +2026-06-24 06:50:15,163 - +2026-06-24 06:50:15,292 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:50:15,292 - +2026-06-24 06:50:15,292 - ### Initializing PtychoModel model ### +2026-06-24 06:50:15,362 - ### PtychoModel optimizable variables ### +2026-06-24 06:50:15,362 - obja : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:15,362 - objp : torch.Size([1, 1, 195, 195]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:15,362 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:50:15,362 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:50:15,362 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:50:15,363 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:50:15,363 - +2026-06-24 06:50:15,363 - ### Optimizable variables statitsics ### +2026-06-24 06:50:15,363 - Total measurement values : 4,194,304 +2026-06-24 06:50:15,363 - Total optimizing variables: 273,170 +2026-06-24 06:50:15,363 - Overdetermined ratio : 15.35 +2026-06-24 06:50:15,363 - +2026-06-24 06:50:15,363 - ### Model behavior ### +2026-06-24 06:50:15,363 - Tilt propagator : False +2026-06-24 06:50:15,363 - Change slice thickness : False +2026-06-24 06:50:15,363 - Detector blur : False +2026-06-24 06:50:15,363 - Preload data : True +2026-06-24 06:50:15,363 - On-the-fly meas padding : False +2026-06-24 06:50:15,363 - On-the-fly meas resample : False +2026-06-24 06:50:15,363 - On-the-fly simu match mode: None +2026-06-24 06:50:15,363 - +2026-06-24 06:50:15,404 - ### Done initializing PtychoModel model ### +2026-06-24 06:50:15,404 - +2026-06-24 06:50:15,404 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:50:15,404 - +2026-06-24 06:50:15,404 - ### Generating indices, batches, and output_path ### +2026-06-24 06:50:15,406 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:50:15,406 - Selecting indices with the 'full' mode +2026-06-24 06:50:15,870 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:50:15,947 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:50:15,947 - Original recon_dir_affixes = ['default'] +2026-06-24 06:50:15,947 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:50:15,954 - Path corrected for compatibility: +2026-06-24 06:50:15,954 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C32_-2.28e+03_phi32_172_C34_-1.15e+03_phi34_303_C41_2.75e+04_phi41_195_C43_4.58e+05_phi43_13.1_C45_-2.94e+05_phi45_189_C50_3.79e+08_C52_8.99e+06_phi52_132_C54_-1.75e+07_phi54_116_C56_-1.64e+07_phi56_216 +2026-06-24 06:50:15,954 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216 +2026-06-24 06:50:15,955 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216' is generated! +2026-06-24 06:50:16,110 - +2026-06-24 06:50:16,111 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/20260624_065016_ptyrad_log.txt ### +2026-06-24 06:50:16,111 - +2026-06-24 06:50:16,113 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:50:16,113 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:50:16,113 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:50:17,315 - Iter: 1, Total Loss: 1.1654, loss_single: 1.1654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.439 sec +2026-06-24 06:50:17,352 - Iter: 2, Total Loss: 1.1060, loss_single: 1.1060, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:50:17,388 - Iter: 3, Total Loss: 1.0642, loss_single: 1.0642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,424 - Iter: 4, Total Loss: 1.0223, loss_single: 1.0223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,460 - Iter: 5, Total Loss: 0.9771, loss_single: 0.9771, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,496 - Iter: 6, Total Loss: 0.9327, loss_single: 0.9327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,532 - Iter: 7, Total Loss: 0.8991, loss_single: 0.8991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,568 - Iter: 8, Total Loss: 0.8662, loss_single: 0.8662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,603 - Iter: 9, Total Loss: 0.8213, loss_single: 0.8213, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,639 - Iter: 10, Total Loss: 0.7737, loss_single: 0.7737, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,675 - Iter: 11, Total Loss: 0.7243, loss_single: 0.7243, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,711 - Iter: 12, Total Loss: 0.6871, loss_single: 0.6871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,746 - Iter: 13, Total Loss: 0.6495, loss_single: 0.6495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,782 - Iter: 14, Total Loss: 0.6152, loss_single: 0.6152, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,818 - Iter: 15, Total Loss: 0.5890, loss_single: 0.5890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,854 - Iter: 16, Total Loss: 0.5602, loss_single: 0.5602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,890 - Iter: 17, Total Loss: 0.5325, loss_single: 0.5325, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:17,926 - Iter: 18, Total Loss: 0.5053, loss_single: 0.5053, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,962 - Iter: 19, Total Loss: 0.4761, loss_single: 0.4761, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:17,997 - Iter: 20, Total Loss: 0.4452, loss_single: 0.4452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,033 - Iter: 21, Total Loss: 0.4177, loss_single: 0.4177, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,070 - Iter: 22, Total Loss: 0.3956, loss_single: 0.3956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,106 - Iter: 23, Total Loss: 0.3799, loss_single: 0.3799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,145 - Iter: 24, Total Loss: 0.3656, loss_single: 0.3656, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 06:50:18,181 - Iter: 25, Total Loss: 0.3527, loss_single: 0.3527, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,216 - Iter: 26, Total Loss: 0.3414, loss_single: 0.3414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,252 - Iter: 27, Total Loss: 0.3313, loss_single: 0.3313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,288 - Iter: 28, Total Loss: 0.3224, loss_single: 0.3224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,324 - Iter: 29, Total Loss: 0.3147, loss_single: 0.3147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,359 - Iter: 30, Total Loss: 0.3096, loss_single: 0.3096, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,395 - Iter: 31, Total Loss: 0.3046, loss_single: 0.3046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,431 - Iter: 32, Total Loss: 0.2998, loss_single: 0.2998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,467 - Iter: 33, Total Loss: 0.2971, loss_single: 0.2971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,503 - Iter: 34, Total Loss: 0.2946, loss_single: 0.2946, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,539 - Iter: 35, Total Loss: 0.2920, loss_single: 0.2920, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,575 - Iter: 36, Total Loss: 0.2902, loss_single: 0.2902, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,610 - Iter: 37, Total Loss: 0.2889, loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,647 - Iter: 38, Total Loss: 0.2877, loss_single: 0.2877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,682 - Iter: 39, Total Loss: 0.2869, loss_single: 0.2869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,718 - Iter: 40, Total Loss: 0.2862, loss_single: 0.2862, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,757 - Iter: 41, Total Loss: 0.2855, loss_single: 0.2855, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,792 - Iter: 42, Total Loss: 0.2851, loss_single: 0.2851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,828 - Iter: 43, Total Loss: 0.2847, loss_single: 0.2847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:18,864 - Iter: 44, Total Loss: 0.2844, loss_single: 0.2844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,899 - Iter: 45, Total Loss: 0.2840, loss_single: 0.2840, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,935 - Iter: 46, Total Loss: 0.2838, loss_single: 0.2838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:18,970 - Iter: 47, Total Loss: 0.2835, loss_single: 0.2835, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,006 - Iter: 48, Total Loss: 0.2833, loss_single: 0.2833, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,042 - Iter: 49, Total Loss: 0.2831, loss_single: 0.2831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,077 - Iter: 50, Total Loss: 0.2829, loss_single: 0.2829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,114 - Iter: 51, Total Loss: 0.2828, loss_single: 0.2828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,149 - Iter: 52, Total Loss: 0.2826, loss_single: 0.2826, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,185 - Iter: 53, Total Loss: 0.2824, loss_single: 0.2824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,221 - Iter: 54, Total Loss: 0.2823, loss_single: 0.2823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,256 - Iter: 55, Total Loss: 0.2822, loss_single: 0.2822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,292 - Iter: 56, Total Loss: 0.2821, loss_single: 0.2821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,328 - Iter: 57, Total Loss: 0.2820, loss_single: 0.2820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,363 - Iter: 58, Total Loss: 0.2819, loss_single: 0.2819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,399 - Iter: 59, Total Loss: 0.2818, loss_single: 0.2818, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,434 - Iter: 60, Total Loss: 0.2817, loss_single: 0.2817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,470 - Iter: 61, Total Loss: 0.2815, loss_single: 0.2815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,505 - Iter: 62, Total Loss: 0.2814, loss_single: 0.2814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,541 - Iter: 63, Total Loss: 0.2814, loss_single: 0.2814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,577 - Iter: 64, Total Loss: 0.2813, loss_single: 0.2813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,613 - Iter: 65, Total Loss: 0.2812, loss_single: 0.2812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,648 - Iter: 66, Total Loss: 0.2811, loss_single: 0.2811, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,684 - Iter: 67, Total Loss: 0.2811, loss_single: 0.2811, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,720 - Iter: 68, Total Loss: 0.2810, loss_single: 0.2810, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,756 - Iter: 69, Total Loss: 0.2809, loss_single: 0.2809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,792 - Iter: 70, Total Loss: 0.2808, loss_single: 0.2808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,828 - Iter: 71, Total Loss: 0.2808, loss_single: 0.2808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,864 - Iter: 72, Total Loss: 0.2807, loss_single: 0.2807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,900 - Iter: 73, Total Loss: 0.2807, loss_single: 0.2807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:19,945 - Iter: 74, Total Loss: 0.2806, loss_single: 0.2806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:19,981 - Iter: 75, Total Loss: 0.2805, loss_single: 0.2805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,017 - Iter: 76, Total Loss: 0.2805, loss_single: 0.2805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,053 - Iter: 77, Total Loss: 0.2804, loss_single: 0.2804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,088 - Iter: 78, Total Loss: 0.2804, loss_single: 0.2804, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,123 - Iter: 79, Total Loss: 0.2803, loss_single: 0.2803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,159 - Iter: 80, Total Loss: 0.2803, loss_single: 0.2803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,195 - Iter: 81, Total Loss: 0.2802, loss_single: 0.2802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,231 - Iter: 82, Total Loss: 0.2802, loss_single: 0.2802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,267 - Iter: 83, Total Loss: 0.2801, loss_single: 0.2801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,302 - Iter: 84, Total Loss: 0.2801, loss_single: 0.2801, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,338 - Iter: 85, Total Loss: 0.2800, loss_single: 0.2800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,374 - Iter: 86, Total Loss: 0.2800, loss_single: 0.2800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,409 - Iter: 87, Total Loss: 0.2799, loss_single: 0.2799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,445 - Iter: 88, Total Loss: 0.2799, loss_single: 0.2799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,480 - Iter: 89, Total Loss: 0.2798, loss_single: 0.2798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,516 - Iter: 90, Total Loss: 0.2798, loss_single: 0.2798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,552 - Iter: 91, Total Loss: 0.2797, loss_single: 0.2797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,590 - Iter: 92, Total Loss: 0.2797, loss_single: 0.2797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:50:20,625 - Iter: 93, Total Loss: 0.2796, loss_single: 0.2796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,661 - Iter: 94, Total Loss: 0.2796, loss_single: 0.2796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,697 - Iter: 95, Total Loss: 0.2795, loss_single: 0.2795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,733 - Iter: 96, Total Loss: 0.2795, loss_single: 0.2795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,768 - Iter: 97, Total Loss: 0.2794, loss_single: 0.2794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,804 - Iter: 98, Total Loss: 0.2794, loss_single: 0.2794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,840 - Iter: 99, Total Loss: 0.2794, loss_single: 0.2794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:50:20,876 - Iter: 100, Total Loss: 0.2793, loss_single: 0.2793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:50:20,986 - Saving summary figures for iter 100 +2026-06-24 06:50:24,593 - ### Finished 100 iterations, averaged iter_t = 0.039449 with std = 0.040 ### +2026-06-24 06:50:24,593 - +2026-06-24 06:50:24,593 - ### The PtyRADSolver is finished in 9.301 sec ### +2026-06-24 06:50:24,593 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..6219f74473f93d7892b92c9d9091739fc1d2952f Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/simulation_data_aug2__sample_000038.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/simulation_data_aug2__sample_000038.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7ce5254fca471d0be9856735ce9286aac8a83e6c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/simulation_data_aug2__sample_000038.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 60.0 + probe_conv_angle: 12.50350570678711 + probe_aberrations: + C10: -101.11515045166016 + C12: 6.6959404945373535 + C21: 219.0380096435547 + C23: -794.7305908203125 + C30: 3345945.5 + C32: -2283.467041015625 + C34: -1149.37548828125 + C41: 27532.255859375 + C43: 458034.9375 + C45: -293829.3125 + C50: 379107904.0 + C52: 8994720.0 + C54: -17523970.0 + C56: -16382928.0 + phi12: 301.95307362066904 + phi21: 34.37133214891797 + phi23: 36.72069524225433 + phi32: 171.9600800539076 + phi34: 302.8101530784789 + phi41: 195.38265652933558 + phi43: 13.067448764403048 + phi45: 188.6019862308054 + phi52: 132.48399087782175 + phi54: 116.02689595948614 + phi56: 216.26024987850343 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.45035433769226074 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug2__sample_000038_measurement.h5 + key: measurement + random_seed: 20262153 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug2__sample_000038 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_pos_grouping.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_pos_grouping.png new file mode 100644 index 0000000000000000000000000000000000000000..083f6ef2b50ecae8387adc4b96c5833e56df2973 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_pos_grouping.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0ad036b0b57ee25746f9391f084b21faa79f7a3db191c1a88ae2c13d0aee2389 +size 51532 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_probe_modes_real_amp_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_probe_modes_real_amp_iter0100.png new file mode 100644 index 0000000000000000000000000000000000000000..1b2b4decf9e54ed98f89e9474ce3a38f27fa7d60 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug2__sample_000038/c30_small__simulation_data_aug2__sample_000038_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-101_C12_6.7_phi12_302_C21_219_phi21_34.4_C23_-795_phi23_36.7_C30_3.35e+06_C3.64e+07_phi56_216/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5c3438a981c68befb4dc58fe8243ce206ac82aa51f41b96141a8fc6db828afef +size 1143885 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/20260624_065258_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/20260624_065258_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..0d4318d978dbe6c785e89fe8830c7eb3fb855de8 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/20260624_065258_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:52:57,129 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:52:57,129 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:52:57,129 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:52:57,129 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:52:57,129 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:52:57,129 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:52:57,129 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:52:57,129 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:52:57,129 - +2026-06-24 06:52:57,236 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:52:57,236 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:52:57,236 - Accelerator.num_process = 1 +2026-06-24 06:52:57,236 - Accelerator.mixed_precision = no +2026-06-24 06:52:57,247 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:52:57,247 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:52:57,247 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:52:57,247 - +2026-06-24 06:52:57,247 - ### System information ### +2026-06-24 06:52:57,247 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:52:57,247 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:52:57,247 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:52:57,247 - Machine: x86_64 +2026-06-24 06:52:57,247 - Processor: x86_64 +2026-06-24 06:52:57,247 - Available CPU cores: 8 +2026-06-24 06:52:57,247 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:52:57,247 - +2026-06-24 06:52:57,247 - ### GPU information ### +2026-06-24 06:52:57,247 - CUDA Available: True +2026-06-24 06:52:57,247 - CUDA Version: 13.0 +2026-06-24 06:52:57,248 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:52:57,248 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:52:57,248 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:52:57,248 - In addition, Triton does not directly support Windows. +2026-06-24 06:52:57,248 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:52:57,274 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:52:57,275 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:52:57,275 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:52:57,275 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:52:57,275 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:52:57,275 - +2026-06-24 06:52:57,275 - ### Python information ### +2026-06-24 06:52:57,277 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:52:57,277 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:52:57,277 - +2026-06-24 06:52:57,277 - ### Packages information ### +2026-06-24 06:52:57,277 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:52:57,278 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:52:57,279 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:52:57,279 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:52:57,280 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:52:57,280 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:52:57,280 - +2026-06-24 06:52:57,280 - ### Loading params file ### +2026-06-24 06:52:57,280 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000010.yaml +2026-06-24 06:52:57,287 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:52:57,288 - Success! Params file validated and defaults applied. +2026-06-24 06:52:57,288 - +2026-06-24 06:52:57,288 - ### Setting GPU Device ### +2026-06-24 06:52:57,288 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:52:57,288 - +2026-06-24 06:52:57,288 - Random seed: 20262164 provided by params file +2026-06-24 06:52:57,288 - ### Initializing Initializer ### +2026-06-24 06:52:57,288 - init_params are displayed below: +2026-06-24 06:52:57,288 - random_seed: 20262164 +2026-06-24 06:52:57,288 - probe_illum_type: electron +2026-06-24 06:52:57,289 - probe_kv: 160.0 +2026-06-24 06:52:57,289 - probe_conv_angle: 15.827966690063477 +2026-06-24 06:52:57,289 - probe_aberrations: {'C10': -325.69, 'C12': 1.902, 'phi12': 209.075, 'C21': 980.651, 'phi21': 161.707, 'C23': 64.387, 'phi23': 205.536, 'C30': 2185005.75, 'C32': -8778.697, 'phi32': 121.046, 'C34': 11004.506, 'phi34': 133.038, 'C41': -35725.531, 'phi41': 19.571, 'C43': -239267.422, 'phi43': 170.239, 'C45': 31548.393, 'phi45': 195.965, 'C50': 270360608.0, 'C52': 17503196.0, 'phi52': 105.229, 'C54': 7968582.5, 'phi54': 77.305, 'C56': 3939325.25, 'phi56': 20.681} +2026-06-24 06:52:57,289 - beam_kev: None +2026-06-24 06:52:57,289 - probe_dRn: None +2026-06-24 06:52:57,289 - probe_Rn: None +2026-06-24 06:52:57,289 - probe_D_H: None +2026-06-24 06:52:57,289 - probe_D_FZP: None +2026-06-24 06:52:57,289 - probe_Ls: None +2026-06-24 06:52:57,289 - meas_Npix: 128 +2026-06-24 06:52:57,289 - pos_N_scans: 256 +2026-06-24 06:52:57,289 - pos_N_scan_slow: 16 +2026-06-24 06:52:57,289 - pos_N_scan_fast: 16 +2026-06-24 06:52:57,289 - pos_scan_step_size: 0.3446712791919708 +2026-06-24 06:52:57,289 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:52:57,289 - probe_pmode_max: 6 +2026-06-24 06:52:57,289 - probe_pmode_init_pows: [0.02] +2026-06-24 06:52:57,289 - obj_omode_max: 1 +2026-06-24 06:52:57,289 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:52:57,289 - obj_Nlayer: 1 +2026-06-24 06:52:57,289 - obj_slice_thickness: 20.0 +2026-06-24 06:52:57,289 - simu_Npix: None +2026-06-24 06:52:57,289 - simu_match_mode: None +2026-06-24 06:52:57,289 - meas_permute: None +2026-06-24 06:52:57,289 - meas_reshape: [256, 128, 128] +2026-06-24 06:52:57,289 - meas_flipT: [0, 0, 0] +2026-06-24 06:52:57,289 - meas_crop: None +2026-06-24 06:52:57,289 - meas_pad: None +2026-06-24 06:52:57,289 - meas_resample: None +2026-06-24 06:52:57,289 - meas_add_source_size: None +2026-06-24 06:52:57,289 - meas_add_detector_blur: None +2026-06-24 06:52:57,289 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:52:57,289 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:52:57,289 - meas_add_poisson_noise: None +2026-06-24 06:52:57,289 - meas_export: None +2026-06-24 06:52:57,289 - probe_permute: None +2026-06-24 06:52:57,289 - probe_z_shift: None +2026-06-24 06:52:57,289 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:52:57,289 - pos_scan_flipT: None +2026-06-24 06:52:57,289 - pos_scan_affine: None +2026-06-24 06:52:57,290 - pos_scan_rand_std: 0.15 +2026-06-24 06:52:57,290 - obj_z_crop: None +2026-06-24 06:52:57,290 - obj_z_pad: None +2026-06-24 06:52:57,290 - obj_z_resample: None +2026-06-24 06:52:57,290 - meas_source: file +2026-06-24 06:52:57,290 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000010_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:52:57,290 - probe_source: simu +2026-06-24 06:52:57,290 - probe_params: None +2026-06-24 06:52:57,290 - pos_source: simu +2026-06-24 06:52:57,290 - pos_params: None +2026-06-24 06:52:57,290 - obj_source: simu +2026-06-24 06:52:57,290 - obj_params: None +2026-06-24 06:52:57,290 - tilt_source: simu +2026-06-24 06:52:57,290 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:52:57,290 - +2026-06-24 06:52:57,290 - ### Initializing cache ### +2026-06-24 06:52:57,290 - use_cached_obj = False +2026-06-24 06:52:57,290 - use_cached_probe = False +2026-06-24 06:52:57,290 - use_cached_pos = False +2026-06-24 06:52:57,290 - +2026-06-24 06:52:57,290 - ### Initializing measurements ### +2026-06-24 06:52:57,290 - Loading measurements from source = 'file' +2026-06-24 06:52:57,290 - Detected measurement file type = '.h5' +2026-06-24 06:52:57,363 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:52:57,363 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:52:57,365 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0025) +2026-06-24 06:52:57,365 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:52:57,365 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:52:57,366 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:52:57,366 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:52:57,367 - Normalizing by max of the 2D mean pattern intensity: 0.0016033349 +2026-06-24 06:52:57,367 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:52:57,369 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0384, 1.5593) +2026-06-24 06:52:57,369 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:52:57,370 - Pattern total int. statistics (min, mean, max) = (619.2833, 629.3726, 641.0447), with min/max = 96.6% +2026-06-24 06:52:57,372 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0384, 1.5593) +2026-06-24 06:52:57,372 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:52:57,372 - +2026-06-24 06:52:57,372 - ### Setting up calibration ### +2026-06-24 06:52:57,372 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:52:57,372 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:52:57,372 - Radius of fitted bright field disk (RBF) = 14.04 px with meas_Npix = 128 +2026-06-24 06:52:57,372 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2193 +2026-06-24 06:52:57,372 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:52:57,372 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:52:57,591 - Initial guess: center=(63.62, 63.62), radius=14.04, Gaussian blur std=0.50 +2026-06-24 06:52:57,603 - Final fit: center=(63.62, 63.62), radius=14.04, Gaussian blur std=0.64 +2026-06-24 06:52:57,603 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 14.21 px with Npix = 128 +2026-06-24 06:52:57,603 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:52:57,604 - +2026-06-24 06:52:57,604 - ### Setting init_variables dict ### +2026-06-24 06:52:57,604 - Derived values given input init_params: +2026-06-24 06:52:57,604 - kv = 160.0 kV +2026-06-24 06:52:57,604 - wavelength = 0.0285 Ang +2026-06-24 06:52:57,604 - conv_angle = 15.827966690063477 mrad +2026-06-24 06:52:57,604 - Npix = 128 px +2026-06-24 06:52:57,604 - dk = 0.0391 Ang^-1 +2026-06-24 06:52:57,604 - kMax = 2.5000 Ang^-1 +2026-06-24 06:52:57,604 - da = 1.1137 mrad +2026-06-24 06:52:57,604 - angleMax = 71.2751 mrad +2026-06-24 06:52:57,604 - RBF = 14.2124 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:52:57,604 - n_alpha = 4.5031 (# conv_angle) +2026-06-24 06:52:57,604 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:52:57,604 - Rayleigh-limited resolution = 1.0988 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:52:57,604 - Real space probe extent = 25.6000 Ang +2026-06-24 06:52:57,604 - +2026-06-24 06:52:57,604 - ### Initializing probe ### +2026-06-24 06:52:57,604 - Loading probe from source = 'simu' +2026-06-24 06:52:57,604 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:52:57,604 - Start simulating STEM probe +2026-06-24 06:52:57,604 - kv = 160.0 kV +2026-06-24 06:52:57,604 - wavelength = 0.0285 Ang +2026-06-24 06:52:57,604 - conv_angle = 15.827966690063477 mrad +2026-06-24 06:52:57,604 - Npix = 128 px +2026-06-24 06:52:57,605 - dk = 0.0391 Ang^-1 +2026-06-24 06:52:57,605 - kMax = 2.5000 Ang^-1 +2026-06-24 06:52:57,605 - alpha_max = 71.2751 mrad +2026-06-24 06:52:57,605 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:52:57,605 - Rayleigh-limited resolution = 1.0988 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:52:57,605 - Real space probe extent = 25.6000 Ang +2026-06-24 06:52:57,605 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:52:57,605 - ------------------------------------------------------------------------------------ +2026-06-24 06:52:57,605 - C1,0 C1 -325.6900 - Defocus (C10 = -df) +2026-06-24 06:52:57,605 - C1,2 A1 1.9020 209.07 2-fold astigmatism +2026-06-24 06:52:57,605 - C2,1 3*B2 980.6510 161.71 Axial coma +2026-06-24 06:52:57,605 - C2,3 A2 64.3870 205.54 3-fold astigmatism +2026-06-24 06:52:57,605 - C3,0 C3 2185005.7500 - Spherical aberration +2026-06-24 06:52:57,605 - C3,2 4*S3 -8778.6970 121.05 Axial star aberration +2026-06-24 06:52:57,605 - C3,4 A3 11004.5060 133.04 4-fold astigmatism +2026-06-24 06:52:57,605 - C4,1 4*B4 -35725.5310 19.57 Axial coma(4th) +2026-06-24 06:52:57,605 - C4,3 4*D4 -239267.4220 170.24 3-lobe aberration +2026-06-24 06:52:57,605 - C4,5 A4 31548.3930 195.97 5-fold astigmatism +2026-06-24 06:52:57,605 - C5,0 C5 270360608.0000 - Spherical aberration (5th) +2026-06-24 06:52:57,605 - C5,2 6*S5 17503196.0000 105.23 Axial star aberration(5th) +2026-06-24 06:52:57,605 - C5,4 6*R5 7968582.5000 77.31 4-lobe aberration +2026-06-24 06:52:57,605 - C5,6 A5 3939325.2500 20.68 6-fold astigmatism +2026-06-24 06:52:57,608 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:52:57,608 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:52:57,608 - Creating 5 new probe modes from the major mode +2026-06-24 06:52:57,608 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:52:57,843 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:52:57,844 - Orthogonalizing 6 pmodes +2026-06-24 06:52:57,849 - Sorting 6 pmodes by their intensities +2026-06-24 06:52:57,849 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:52:57,850 - sum(|probe_data|**2) = 629.37, while meas_total_ints (min, mean, max) = (619.2833, 629.3726, 641.0447) +2026-06-24 06:52:57,850 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:52:57,850 - +2026-06-24 06:52:57,850 - ### Initializing probe positions ### +2026-06-24 06:52:57,850 - Loading probe positions from source = 'simu' +2026-06-24 06:52:57,850 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:52:57,850 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3447, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:52:57,851 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:52:57,853 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:52:57,853 - crop_pos 1st and last px coords (y,x) = ([15, 15], [41, 41]) +2026-06-24 06:52:57,853 - crop_pos extent (Ang) = [5.2 5.2] +2026-06-24 06:52:57,853 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:52:57,853 - +2026-06-24 06:52:57,853 - ### Initializing object ### +2026-06-24 06:52:57,853 - Loading object from source = 'simu' +2026-06-24 06:52:57,853 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:52:57,854 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:52:57,855 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 186, 186) +2026-06-24 06:52:57,855 - object extent (Z, Y, X) (Ang) = [20. 37.2 37.2] +2026-06-24 06:52:57,855 - +2026-06-24 06:52:57,855 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:52:57,855 - omode_occu (omode) = float32, (1,) +2026-06-24 06:52:57,855 - +2026-06-24 06:52:57,855 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:52:57,855 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:52:57,856 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:52:57,856 - +2026-06-24 06:52:57,856 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:52:57,856 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:52:57,856 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:52:57,856 - +2026-06-24 06:52:57,856 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:52:57,856 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:52:57,856 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:52:57,856 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:52:57,856 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:52:57,856 - crop positions (yx_min=[15 15], yx_max=[169 169]) are well contained inside object canvas (Ny,Nx) = (186, 186). +2026-06-24 06:52:57,856 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:52:57,856 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:52:57,856 - +2026-06-24 06:52:57,856 - ### Collecting reconstruction provenance ### +2026-06-24 06:52:57,856 - Reconstruction provenance is collected and initialized. +2026-06-24 06:52:57,856 - +2026-06-24 06:52:57,856 - ### Initializing loss function ### +2026-06-24 06:52:57,856 - Active loss types: +2026-06-24 06:52:57,857 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:52:57,857 - +2026-06-24 06:52:57,857 - ### Initializing constraint function ### +2026-06-24 06:52:57,857 - Active constraint types: +2026-06-24 06:52:57,857 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:52:57,857 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:52:57,857 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:52:57,857 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:52:57,857 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:52:57,857 - +2026-06-24 06:52:57,857 - ### Done initializing PtyRADSolver ### +2026-06-24 06:52:57,857 - +2026-06-24 06:52:57,982 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:52:57,982 - +2026-06-24 06:52:57,982 - ### Initializing PtychoModel model ### +2026-06-24 06:52:58,054 - ### PtychoModel optimizable variables ### +2026-06-24 06:52:58,054 - obja : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:52:58,054 - objp : torch.Size([1, 1, 186, 186]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:52:58,054 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:52:58,054 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:52:58,054 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:52:58,054 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:52:58,054 - +2026-06-24 06:52:58,054 - ### Optimizable variables statitsics ### +2026-06-24 06:52:58,054 - Total measurement values : 4,194,304 +2026-06-24 06:52:58,054 - Total optimizing variables: 266,312 +2026-06-24 06:52:58,054 - Overdetermined ratio : 15.75 +2026-06-24 06:52:58,054 - +2026-06-24 06:52:58,055 - ### Model behavior ### +2026-06-24 06:52:58,055 - Tilt propagator : False +2026-06-24 06:52:58,055 - Change slice thickness : False +2026-06-24 06:52:58,055 - Detector blur : False +2026-06-24 06:52:58,055 - Preload data : True +2026-06-24 06:52:58,055 - On-the-fly meas padding : False +2026-06-24 06:52:58,055 - On-the-fly meas resample : False +2026-06-24 06:52:58,055 - On-the-fly simu match mode: None +2026-06-24 06:52:58,055 - +2026-06-24 06:52:58,096 - ### Done initializing PtychoModel model ### +2026-06-24 06:52:58,096 - +2026-06-24 06:52:58,097 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:52:58,097 - +2026-06-24 06:52:58,097 - ### Generating indices, batches, and output_path ### +2026-06-24 06:52:58,098 - d90 = 31.000 px or 6.200 Ang +2026-06-24 06:52:58,098 - Selecting indices with the 'full' mode +2026-06-24 06:52:58,559 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:52:58,634 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:52:58,634 - Original recon_dir_affixes = ['default'] +2026-06-24 06:52:58,634 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:52:58,640 - Path corrected for compatibility: +2026-06-24 06:52:58,640 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32_121_C34_1.1e+04_phi34_133_C41_-3.57e+04_phi41_19.6_C43_-2.39e+05_phi43_170_C45_3.15e+04_phi45_196_C50_2.7e+08_C52_1.75e+07_phi52_105_C54_7.97e+06_phi54_77.3_C56_3.94e+06_phi56_20.7 +2026-06-24 06:52:58,640 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7 +2026-06-24 06:52:58,641 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7' is generated! +2026-06-24 06:52:58,790 - +2026-06-24 06:52:58,792 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/20260624_065258_ptyrad_log.txt ### +2026-06-24 06:52:58,792 - +2026-06-24 06:52:58,793 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:52:58,793 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:52:58,794 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:52:59,982 - Iter: 1, Total Loss: 0.7575, loss_single: 0.7575, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:53:00,044 - Iter: 2, Total Loss: 0.7298, loss_single: 0.7298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:53:00,080 - Iter: 3, Total Loss: 0.7082, loss_single: 0.7082, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,115 - Iter: 4, Total Loss: 0.6877, loss_single: 0.6877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,150 - Iter: 5, Total Loss: 0.6677, loss_single: 0.6677, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,185 - Iter: 6, Total Loss: 0.6486, loss_single: 0.6486, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,220 - Iter: 7, Total Loss: 0.6324, loss_single: 0.6324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,255 - Iter: 8, Total Loss: 0.6175, loss_single: 0.6175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,290 - Iter: 9, Total Loss: 0.6019, loss_single: 0.6019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,325 - Iter: 10, Total Loss: 0.5898, loss_single: 0.5898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,360 - Iter: 11, Total Loss: 0.5798, loss_single: 0.5798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,395 - Iter: 12, Total Loss: 0.5719, loss_single: 0.5719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:00,431 - Iter: 13, Total Loss: 0.5651, loss_single: 0.5651, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,466 - Iter: 14, Total Loss: 0.5561, loss_single: 0.5561, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,506 - Iter: 15, Total Loss: 0.5468, loss_single: 0.5468, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 06:53:00,544 - Iter: 16, Total Loss: 0.5376, loss_single: 0.5376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:53:00,579 - Iter: 17, Total Loss: 0.5298, loss_single: 0.5298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,614 - Iter: 18, Total Loss: 0.5220, loss_single: 0.5220, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,649 - Iter: 19, Total Loss: 0.5131, loss_single: 0.5131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:00,684 - Iter: 20, Total Loss: 0.5074, loss_single: 0.5074, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,719 - Iter: 21, Total Loss: 0.5031, loss_single: 0.5031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,755 - Iter: 22, Total Loss: 0.4984, loss_single: 0.4984, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,790 - Iter: 23, Total Loss: 0.4940, loss_single: 0.4940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,825 - Iter: 24, Total Loss: 0.4909, loss_single: 0.4909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,860 - Iter: 25, Total Loss: 0.4883, loss_single: 0.4883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,895 - Iter: 26, Total Loss: 0.4852, loss_single: 0.4852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:00,934 - Iter: 27, Total Loss: 0.4823, loss_single: 0.4823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:53:00,969 - Iter: 28, Total Loss: 0.4791, loss_single: 0.4791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,005 - Iter: 29, Total Loss: 0.4769, loss_single: 0.4769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,040 - Iter: 30, Total Loss: 0.4749, loss_single: 0.4749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:01,075 - Iter: 31, Total Loss: 0.4728, loss_single: 0.4728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:01,110 - Iter: 32, Total Loss: 0.4702, loss_single: 0.4702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,145 - Iter: 33, Total Loss: 0.4680, loss_single: 0.4680, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,180 - Iter: 34, Total Loss: 0.4659, loss_single: 0.4659, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,215 - Iter: 35, Total Loss: 0.4636, loss_single: 0.4636, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,250 - Iter: 36, Total Loss: 0.4616, loss_single: 0.4616, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:01,285 - Iter: 37, Total Loss: 0.4598, loss_single: 0.4598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,322 - Iter: 38, Total Loss: 0.4581, loss_single: 0.4581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:53:01,358 - Iter: 39, Total Loss: 0.4566, loss_single: 0.4566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,392 - Iter: 40, Total Loss: 0.4550, loss_single: 0.4550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,431 - Iter: 41, Total Loss: 0.4535, loss_single: 0.4535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:53:01,466 - Iter: 42, Total Loss: 0.4524, loss_single: 0.4524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,502 - Iter: 43, Total Loss: 0.4514, loss_single: 0.4514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,537 - Iter: 44, Total Loss: 0.4503, loss_single: 0.4503, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,572 - Iter: 45, Total Loss: 0.4492, loss_single: 0.4492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,607 - Iter: 46, Total Loss: 0.4481, loss_single: 0.4481, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,643 - Iter: 47, Total Loss: 0.4468, loss_single: 0.4468, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,678 - Iter: 48, Total Loss: 0.4458, loss_single: 0.4458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,713 - Iter: 49, Total Loss: 0.4448, loss_single: 0.4448, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:53:01,748 - Iter: 50, Total Loss: 0.4437, loss_single: 0.4437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,783 - Iter: 51, Total Loss: 0.4426, loss_single: 0.4426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,818 - Iter: 52, Total Loss: 0.4417, loss_single: 0.4417, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,854 - Iter: 53, Total Loss: 0.4410, loss_single: 0.4410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,889 - Iter: 54, Total Loss: 0.4403, loss_single: 0.4403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,924 - Iter: 55, Total Loss: 0.4395, loss_single: 0.4395, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,960 - Iter: 56, Total Loss: 0.4387, loss_single: 0.4387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:01,995 - Iter: 57, Total Loss: 0.4382, loss_single: 0.4382, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:53:02,031 - Iter: 58, Total Loss: 0.4379, loss_single: 0.4379, loss_poissn: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/simulation_data_aug3__sample_000010.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 15.827966690063477 + probe_aberrations: + C10: -325.69024658203125 + C12: 1.9024043083190918 + C21: 980.6510620117188 + C23: 64.38719940185547 + C30: 2185005.75 + C32: -8778.697265625 + C34: 11004.505859375 + C41: -35725.53125 + C43: -239267.421875 + C45: 31548.392578125 + C50: 270360608.0 + C52: 17503196.0 + C54: 7968582.5 + C56: 3939325.25 + phi12: 209.07465864521822 + phi21: 161.7065727511278 + phi23: 205.53625182493644 + phi32: 121.04627903712345 + phi34: 133.0382060874549 + phi41: 19.57124795341663 + phi43: 170.23872211890264 + phi45: 195.9653126466727 + phi52: 105.22876986285702 + phi54: 77.30461378095957 + phi56: 20.680672165207216 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.3446712791919708 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000010_measurement.h5 + key: measurement + random_seed: 20262164 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug3__sample_000010 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000010/c30_small__simulation_data_aug3__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-326_C12_1.9_phi12_209_C21_981_phi21_162_C23_64.4_phi23_206_C30_2.19e+06_C32_-8.78e+03_phi32.7/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198/20260624_065412_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a227b315a9710c426aed18c9c91232d089ee6e4 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198/20260624_065412_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:54:11,200 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:54:11,200 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:54:11,200 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:54:11,200 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:54:11,200 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:54:11,200 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:54:11,200 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:54:11,200 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:54:11,200 - +2026-06-24 06:54:11,311 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:54:11,311 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:54:11,311 - Accelerator.num_process = 1 +2026-06-24 06:54:11,311 - Accelerator.mixed_precision = no +2026-06-24 06:54:11,321 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:54:11,321 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:54:11,321 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:54:11,321 - +2026-06-24 06:54:11,321 - ### System information ### +2026-06-24 06:54:11,321 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:54:11,321 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:54:11,321 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:54:11,321 - Machine: x86_64 +2026-06-24 06:54:11,321 - Processor: x86_64 +2026-06-24 06:54:11,321 - Available CPU cores: 8 +2026-06-24 06:54:11,321 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:54:11,322 - +2026-06-24 06:54:11,322 - ### GPU information ### +2026-06-24 06:54:11,322 - CUDA Available: True +2026-06-24 06:54:11,322 - CUDA Version: 13.0 +2026-06-24 06:54:11,322 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:54:11,322 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:54:11,322 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:54:11,322 - In addition, Triton does not directly support Windows. +2026-06-24 06:54:11,322 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:54:11,338 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:54:11,338 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:54:11,338 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:54:11,338 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:54:11,338 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:54:11,338 - +2026-06-24 06:54:11,338 - ### Python information ### +2026-06-24 06:54:11,341 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:54:11,341 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:54:11,341 - +2026-06-24 06:54:11,341 - ### Packages information ### +2026-06-24 06:54:11,342 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:54:11,342 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:54:11,343 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:54:11,344 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:54:11,344 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:54:11,344 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:54:11,344 - +2026-06-24 06:54:11,344 - ### Loading params file ### +2026-06-24 06:54:11,344 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000015.yaml +2026-06-24 06:54:11,351 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:54:11,352 - Success! Params file validated and defaults applied. +2026-06-24 06:54:11,352 - +2026-06-24 06:54:11,352 - ### Setting GPU Device ### +2026-06-24 06:54:11,352 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:54:11,352 - +2026-06-24 06:54:11,352 - Random seed: 20262169 provided by params file +2026-06-24 06:54:11,352 - ### Initializing Initializer ### +2026-06-24 06:54:11,353 - init_params are displayed below: +2026-06-24 06:54:11,353 - random_seed: 20262169 +2026-06-24 06:54:11,353 - probe_illum_type: electron +2026-06-24 06:54:11,353 - probe_kv: 200.0 +2026-06-24 06:54:11,353 - probe_conv_angle: 10.702360153198242 +2026-06-24 06:54:11,353 - probe_aberrations: {'C10': 89.299, 'C12': 35.109, 'phi12': 206.518, 'C21': 187.119, 'phi21': 80.012, 'C23': -527.64, 'phi23': 100.261, 'C30': -547473.125, 'C32': -3738.232, 'phi32': 163.609, 'C34': 875.872, 'phi34': 129.806, 'C41': -279750.562, 'phi41': 206.689, 'C43': 517.821, 'phi43': 240.71, 'C45': 309250.188, 'phi45': 95.44, 'C50': 306610944.0, 'C52': 14538245.0, 'phi52': 328.232, 'C54': -1032592.688, 'phi54': 18.178, 'C56': 11735153.0, 'phi56': 197.827} +2026-06-24 06:54:11,353 - beam_kev: None +2026-06-24 06:54:11,353 - probe_dRn: None +2026-06-24 06:54:11,353 - probe_Rn: None +2026-06-24 06:54:11,353 - probe_D_H: None +2026-06-24 06:54:11,353 - probe_D_FZP: None +2026-06-24 06:54:11,353 - probe_Ls: None +2026-06-24 06:54:11,353 - meas_Npix: 128 +2026-06-24 06:54:11,353 - pos_N_scans: 256 +2026-06-24 06:54:11,353 - pos_N_scan_slow: 16 +2026-06-24 06:54:11,353 - pos_N_scan_fast: 16 +2026-06-24 06:54:11,353 - pos_scan_step_size: 0.38140660524368286 +2026-06-24 06:54:11,353 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:54:11,353 - probe_pmode_max: 6 +2026-06-24 06:54:11,353 - probe_pmode_init_pows: [0.02] +2026-06-24 06:54:11,353 - obj_omode_max: 1 +2026-06-24 06:54:11,353 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:54:11,353 - obj_Nlayer: 1 +2026-06-24 06:54:11,353 - obj_slice_thickness: 20.0 +2026-06-24 06:54:11,353 - simu_Npix: None +2026-06-24 06:54:11,353 - simu_match_mode: None +2026-06-24 06:54:11,353 - meas_permute: None +2026-06-24 06:54:11,353 - meas_reshape: [256, 128, 128] +2026-06-24 06:54:11,353 - meas_flipT: [0, 0, 0] +2026-06-24 06:54:11,353 - meas_crop: None +2026-06-24 06:54:11,353 - meas_pad: None +2026-06-24 06:54:11,353 - meas_resample: None +2026-06-24 06:54:11,353 - meas_add_source_size: None +2026-06-24 06:54:11,353 - meas_add_detector_blur: None +2026-06-24 06:54:11,353 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:54:11,353 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:54:11,353 - meas_add_poisson_noise: None +2026-06-24 06:54:11,354 - meas_export: None +2026-06-24 06:54:11,354 - probe_permute: None +2026-06-24 06:54:11,354 - probe_z_shift: None +2026-06-24 06:54:11,354 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:54:11,354 - pos_scan_flipT: None +2026-06-24 06:54:11,354 - pos_scan_affine: None +2026-06-24 06:54:11,354 - pos_scan_rand_std: 0.15 +2026-06-24 06:54:11,354 - obj_z_crop: None +2026-06-24 06:54:11,354 - obj_z_pad: None +2026-06-24 06:54:11,354 - obj_z_resample: None +2026-06-24 06:54:11,354 - meas_source: file +2026-06-24 06:54:11,354 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000015_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:54:11,354 - probe_source: simu +2026-06-24 06:54:11,354 - probe_params: None +2026-06-24 06:54:11,354 - pos_source: simu +2026-06-24 06:54:11,354 - pos_params: None +2026-06-24 06:54:11,354 - obj_source: simu +2026-06-24 06:54:11,354 - obj_params: None +2026-06-24 06:54:11,354 - tilt_source: simu +2026-06-24 06:54:11,354 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:54:11,354 - +2026-06-24 06:54:11,354 - ### Initializing cache ### +2026-06-24 06:54:11,354 - use_cached_obj = False +2026-06-24 06:54:11,354 - use_cached_probe = False +2026-06-24 06:54:11,354 - use_cached_pos = False +2026-06-24 06:54:11,354 - +2026-06-24 06:54:11,354 - ### Initializing measurements ### +2026-06-24 06:54:11,354 - Loading measurements from source = 'file' +2026-06-24 06:54:11,354 - Detected measurement file type = '.h5' +2026-06-24 06:54:11,433 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:54:11,433 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:54:11,435 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0039) +2026-06-24 06:54:11,435 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:54:11,435 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:54:11,436 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:54:11,436 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:54:11,437 - Normalizing by max of the 2D mean pattern intensity: 0.0025926908 +2026-06-24 06:54:11,437 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:54:11,438 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0235, 1.4965) +2026-06-24 06:54:11,439 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:54:11,440 - Pattern total int. statistics (min, mean, max) = (381.1603, 384.9021, 388.1103), with min/max = 98.2% +2026-06-24 06:54:11,441 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0235, 1.4965) +2026-06-24 06:54:11,442 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:54:11,442 - +2026-06-24 06:54:11,442 - ### Setting up calibration ### +2026-06-24 06:54:11,442 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:54:11,442 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:54:11,442 - Radius of fitted bright field disk (RBF) = 10.88 px with meas_Npix = 128 +2026-06-24 06:54:11,442 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1700 +2026-06-24 06:54:11,442 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:54:11,442 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:54:11,667 - Initial guess: center=(63.61, 63.61), radius=10.88, Gaussian blur std=0.50 +2026-06-24 06:54:11,681 - Final fit: center=(63.61, 63.61), radius=10.88, Gaussian blur std=0.73 +2026-06-24 06:54:11,682 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.92 px with Npix = 128 +2026-06-24 06:54:11,682 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:54:11,682 - +2026-06-24 06:54:11,682 - ### Setting init_variables dict ### +2026-06-24 06:54:11,682 - Derived values given input init_params: +2026-06-24 06:54:11,682 - kv = 200.0 kV +2026-06-24 06:54:11,682 - wavelength = 0.0251 Ang +2026-06-24 06:54:11,682 - conv_angle = 10.702360153198242 mrad +2026-06-24 06:54:11,682 - Npix = 128 px +2026-06-24 06:54:11,682 - dk = 0.0391 Ang^-1 +2026-06-24 06:54:11,682 - kMax = 2.5000 Ang^-1 +2026-06-24 06:54:11,682 - da = 0.9797 mrad +2026-06-24 06:54:11,682 - angleMax = 62.6984 mrad +2026-06-24 06:54:11,682 - RBF = 10.9245 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:54:11,682 - n_alpha = 5.8584 (# conv_angle) +2026-06-24 06:54:11,682 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:54:11,682 - Rayleigh-limited resolution = 1.4294 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:54:11,682 - Real space probe extent = 25.6000 Ang +2026-06-24 06:54:11,682 - +2026-06-24 06:54:11,682 - ### Initializing probe ### +2026-06-24 06:54:11,682 - Loading probe from source = 'simu' +2026-06-24 06:54:11,682 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:54:11,682 - Start simulating STEM probe +2026-06-24 06:54:11,683 - kv = 200.0 kV +2026-06-24 06:54:11,683 - wavelength = 0.0251 Ang +2026-06-24 06:54:11,683 - conv_angle = 10.702360153198242 mrad +2026-06-24 06:54:11,683 - Npix = 128 px +2026-06-24 06:54:11,683 - dk = 0.0391 Ang^-1 +2026-06-24 06:54:11,683 - kMax = 2.5000 Ang^-1 +2026-06-24 06:54:11,683 - alpha_max = 62.6984 mrad +2026-06-24 06:54:11,683 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:54:11,683 - Rayleigh-limited resolution = 1.4294 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:54:11,683 - Real space probe extent = 25.6000 Ang +2026-06-24 06:54:11,683 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:54:11,683 - ------------------------------------------------------------------------------------ +2026-06-24 06:54:11,683 - C1,0 C1 89.2990 - Defocus (C10 = -df) +2026-06-24 06:54:11,683 - C1,2 A1 35.1090 206.52 2-fold astigmatism +2026-06-24 06:54:11,683 - C2,1 3*B2 187.1190 80.01 Axial coma +2026-06-24 06:54:11,683 - C2,3 A2 -527.6400 100.26 3-fold astigmatism +2026-06-24 06:54:11,683 - C3,0 C3 -547473.1250 - Spherical aberration +2026-06-24 06:54:11,683 - C3,2 4*S3 -3738.2320 163.61 Axial star aberration +2026-06-24 06:54:11,683 - C3,4 A3 875.8720 129.81 4-fold astigmatism +2026-06-24 06:54:11,683 - C4,1 4*B4 -279750.5620 206.69 Axial coma(4th) +2026-06-24 06:54:11,683 - C4,3 4*D4 517.8210 240.71 3-lobe aberration +2026-06-24 06:54:11,683 - C4,5 A4 309250.1880 95.44 5-fold astigmatism +2026-06-24 06:54:11,683 - C5,0 C5 306610944.0000 - Spherical aberration (5th) +2026-06-24 06:54:11,683 - C5,2 6*S5 14538245.0000 328.23 Axial star aberration(5th) +2026-06-24 06:54:11,683 - C5,4 6*R5 -1032592.6880 18.18 4-lobe aberration +2026-06-24 06:54:11,683 - C5,6 A5 11735153.0000 197.83 6-fold astigmatism +2026-06-24 06:54:11,686 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:54:11,686 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:54:11,686 - Creating 5 new probe modes from the major mode +2026-06-24 06:54:11,686 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:54:11,882 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:54:11,883 - Orthogonalizing 6 pmodes +2026-06-24 06:54:11,895 - Sorting 6 pmodes by their intensities +2026-06-24 06:54:11,896 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:54:11,896 - sum(|probe_data|**2) = 384.90, while meas_total_ints (min, mean, max) = (381.1603, 384.9021, 388.1103) +2026-06-24 06:54:11,897 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:54:11,897 - +2026-06-24 06:54:11,897 - ### Initializing probe positions ### +2026-06-24 06:54:11,897 - Loading probe positions from source = 'simu' +2026-06-24 06:54:11,897 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:54:11,897 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3814, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:54:11,897 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:54:11,899 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:54:11,899 - crop_pos 1st and last px coords (y,x) = ([16, 16], [44, 44]) +2026-06-24 06:54:11,899 - crop_pos extent (Ang) = [5.8 5.8] +2026-06-24 06:54:11,899 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:54:11,899 - +2026-06-24 06:54:11,899 - ### Initializing object ### +2026-06-24 06:54:11,899 - Loading object from source = 'simu' +2026-06-24 06:54:11,899 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:54:11,901 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:54:11,901 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:54:11,901 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:54:11,901 - +2026-06-24 06:54:11,901 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:54:11,901 - omode_occu (omode) = float32, (1,) +2026-06-24 06:54:11,901 - +2026-06-24 06:54:11,901 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:54:11,901 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 06:54:11,902 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:54:11,902 - +2026-06-24 06:54:11,902 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:54:11,902 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:54:11,902 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:54:11,902 - +2026-06-24 06:54:11,902 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:54:11,902 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:54:11,902 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:54:11,902 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:54:11,902 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:54:11,902 - crop positions (yx_min=[15 16], yx_max=[172 173]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:54:11,902 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:54:11,902 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:54:11,902 - +2026-06-24 06:54:11,902 - ### Collecting reconstruction provenance ### +2026-06-24 06:54:11,902 - Reconstruction provenance is collected and initialized. +2026-06-24 06:54:11,902 - +2026-06-24 06:54:11,902 - ### Initializing loss function ### +2026-06-24 06:54:11,903 - Active loss types: +2026-06-24 06:54:11,903 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:54:11,903 - +2026-06-24 06:54:11,903 - ### Initializing constraint function ### +2026-06-24 06:54:11,903 - Active constraint types: +2026-06-24 06:54:11,903 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:54:11,903 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:54:11,903 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:54:11,903 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:54:11,903 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:54:11,903 - +2026-06-24 06:54:11,903 - ### Done initializing PtyRADSolver ### +2026-06-24 06:54:11,903 - +2026-06-24 06:54:12,029 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:54:12,029 - +2026-06-24 06:54:12,029 - ### Initializing PtychoModel model ### +2026-06-24 06:54:12,101 - ### PtychoModel optimizable variables ### +2026-06-24 06:54:12,101 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:12,101 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:12,101 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:54:12,101 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:54:12,101 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:54:12,101 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:12,101 - +2026-06-24 06:54:12,101 - ### Optimizable variables statitsics ### +2026-06-24 06:54:12,101 - Total measurement values : 4,194,304 +2026-06-24 06:54:12,101 - Total optimizing variables: 267,808 +2026-06-24 06:54:12,101 - Overdetermined ratio : 15.66 +2026-06-24 06:54:12,101 - +2026-06-24 06:54:12,101 - ### Model behavior ### +2026-06-24 06:54:12,101 - Tilt propagator : False +2026-06-24 06:54:12,101 - Change slice thickness : False +2026-06-24 06:54:12,101 - Detector blur : False +2026-06-24 06:54:12,101 - Preload data : True +2026-06-24 06:54:12,101 - On-the-fly meas padding : False +2026-06-24 06:54:12,101 - On-the-fly meas resample : False +2026-06-24 06:54:12,101 - On-the-fly simu match mode: None +2026-06-24 06:54:12,101 - +2026-06-24 06:54:12,142 - ### Done initializing PtychoModel model ### +2026-06-24 06:54:12,142 - +2026-06-24 06:54:12,142 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:54:12,142 - +2026-06-24 06:54:12,142 - ### Generating indices, batches, and output_path ### +2026-06-24 06:54:12,144 - d90 = 25.000 px or 5.000 Ang +2026-06-24 06:54:12,144 - Selecting indices with the 'full' mode +2026-06-24 06:54:12,601 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:54:12,674 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:54:12,674 - Original recon_dir_affixes = ['default'] +2026-06-24 06:54:12,674 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:54:12,680 - Path corrected for compatibility: +2026-06-24 06:54:12,680 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32_-3.74e+03_phi32_164_C34_876_phi34_130_C41_-2.8e+05_phi41_207_C43_518_phi43_241_C45_3.09e+05_phi45_95.4_C50_3.07e+08_C52_1.45e+07_phi52_328_C54_-1.03e+06_phi54_18.2_C56_1.17e+07_phi56_198 +2026-06-24 06:54:12,680 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198 +2026-06-24 06:54:12,681 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198' is generated! +2026-06-24 06:54:12,827 - +2026-06-24 06:54:12,828 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198/20260624_065412_ptyrad_log.txt ### +2026-06-24 06:54:12,828 - +2026-06-24 06:54:12,829 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:54:12,829 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:54:12,829 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:54:14,004 - Iter: 1, Total Loss: 0.8954, loss_single: 0.8954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:54:14,040 - Iter: 2, Total Loss: 0.8573, loss_single: 0.8573, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:54:14,077 - Iter: 3, Total Loss: 0.8251, loss_single: 0.8251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:54:14,112 - Iter: 4, Total Loss: 0.7982, loss_single: 0.7982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,147 - Iter: 5, Total Loss: 0.7743, loss_single: 0.7743, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,182 - Iter: 6, Total Loss: 0.7498, loss_single: 0.7498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,217 - Iter: 7, Total Loss: 0.7308, loss_single: 0.7308, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,252 - Iter: 8, Total Loss: 0.7137, loss_single: 0.7137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,287 - Iter: 9, Total Loss: 0.6965, loss_single: 0.6965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,322 - Iter: 10, Total Loss: 0.6807, loss_single: 0.6807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,358 - Iter: 11, Total Loss: 0.6612, loss_single: 0.6612, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,392 - Iter: 12, Total Loss: 0.6384, loss_single: 0.6384, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,428 - Iter: 13, Total Loss: 0.6190, loss_single: 0.6190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,463 - Iter: 14, Total Loss: 0.6039, loss_single: 0.6039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,498 - Iter: 15, Total Loss: 0.5893, loss_single: 0.5893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,533 - Iter: 16, Total Loss: 0.5734, loss_single: 0.5734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,568 - Iter: 17, Total Loss: 0.5577, loss_single: 0.5577, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,602 - Iter: 18, Total Loss: 0.5437, loss_single: 0.5437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,637 - Iter: 19, Total Loss: 0.5290, loss_single: 0.5290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,672 - Iter: 20, Total Loss: 0.5159, loss_single: 0.5159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,707 - Iter: 21, Total Loss: 0.5059, loss_single: 0.5059, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,742 - Iter: 22, Total Loss: 0.4949, loss_single: 0.4949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,777 - Iter: 23, Total Loss: 0.4850, loss_single: 0.4850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,812 - Iter: 24, Total Loss: 0.4762, loss_single: 0.4762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,847 - Iter: 25, Total Loss: 0.4667, loss_single: 0.4667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,882 - Iter: 26, Total Loss: 0.4596, loss_single: 0.4596, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,917 - Iter: 27, Total Loss: 0.4536, loss_single: 0.4536, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:14,952 - Iter: 28, Total Loss: 0.4474, loss_single: 0.4474, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:14,987 - Iter: 29, Total Loss: 0.4420, loss_single: 0.4420, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:15,023 - Iter: 30, Total Loss: 0.4367, loss_single: 0.4367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:15,058 - Iter: 31, Total Loss: 0.4323, loss_single: 0.4323, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:15,093 - Iter: 32, Total Loss: 0.4272, loss_single: 0.4272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:15,128 - Iter: 33, Total Loss: 0.4213, loss_single: 0.4213, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:15,163 - Iter: 34, Total Loss: 0.4168, loss_single: 0.4168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:15,198 - Iter: 35, Total Loss: 0.4123, loss_single: 0.4123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 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in 0.034 sec +2026-06-24 06:54:16,426 - Iter: 70, Total Loss: 0.3447, loss_single: 0.3447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:16,461 - Iter: 71, Total Loss: 0.3435, loss_single: 0.3435, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:16,496 - Iter: 72, Total Loss: 0.3422, loss_single: 0.3422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:16,531 - Iter: 73, Total Loss: 0.3410, loss_single: 0.3410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:16,567 - Iter: 74, Total Loss: 0.3397, loss_single: 0.3397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:16,602 - Iter: 75, Total Loss: 0.3385, loss_single: 0.3385, loss_poissn: 0.0000, loss_pacbed: 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0.3163, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:17,450 - Iter: 99, Total Loss: 0.3155, loss_single: 0.3155, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:17,485 - Iter: 100, Total Loss: 0.3147, loss_single: 0.3147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:17,596 - Saving summary figures for iter 100 +2026-06-24 06:54:21,164 - ### Finished 100 iterations, averaged iter_t = 0.038722 with std = 0.040 ### +2026-06-24 06:54:21,164 - +2026-06-24 06:54:21,164 - ### The PtyRADSolver is finished in 9.135 sec ### +2026-06-24 06:54:21,164 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000015/c30_small__simulation_data_aug3__sample_000015_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_89.3_C12_35.1_phi12_207_C21_187_phi21_80_C23_-528_phi23_100_C30_-5.47e+05_C32.17e+07_phi56_198/simulation_data_aug3__sample_000015.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 10.702360153198242 + probe_aberrations: + C10: 89.29857635498047 + C12: 35.10851287841797 + C21: 187.11949157714844 + C23: -527.640380859375 + C30: -547473.125 + C32: -3738.231689453125 + C34: 875.8720092773438 + C41: -279750.5625 + C43: 517.8214721679688 + C45: 309250.1875 + C50: 306610944.0 + C52: 14538245.0 + C54: -1032592.6875 + C56: 11735153.0 + phi12: 206.51759974450553 + phi21: 80.01223737173603 + phi23: 100.26092739269663 + phi32: 163.60949077465003 + phi34: 129.80605128917816 + phi41: 206.6885047379176 + phi43: 240.7104556353165 + phi45: 95.44036429160921 + phi52: 328.2316527164028 + phi54: 18.178370891070518 + phi56: 197.82709927101308 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.38140660524368286 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000015_measurement.h5 + key: measurement + random_seed: 20262169 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230/20260624_065457_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..46db73bdf710c019b97c3c10f659db3d46824b73 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230/20260624_065457_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:54:55,491 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:54:55,491 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:54:55,491 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:54:55,491 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:54:55,491 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:54:55,491 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:54:55,491 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:54:55,491 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:54:55,491 - +2026-06-24 06:54:55,598 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:54:55,598 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:54:55,598 - Accelerator.num_process = 1 +2026-06-24 06:54:55,598 - Accelerator.mixed_precision = no +2026-06-24 06:54:55,608 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:54:55,608 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:54:55,608 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:54:55,608 - +2026-06-24 06:54:55,609 - ### System information ### +2026-06-24 06:54:55,609 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:54:55,609 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:54:55,609 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:54:55,609 - Machine: x86_64 +2026-06-24 06:54:55,609 - Processor: x86_64 +2026-06-24 06:54:55,609 - Available CPU cores: 8 +2026-06-24 06:54:55,609 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:54:55,609 - +2026-06-24 06:54:55,609 - ### GPU information ### +2026-06-24 06:54:55,609 - CUDA Available: True +2026-06-24 06:54:55,609 - CUDA Version: 13.0 +2026-06-24 06:54:55,610 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:54:55,610 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:54:55,610 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:54:55,610 - In addition, Triton does not directly support Windows. +2026-06-24 06:54:55,610 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:54:55,625 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:54:55,625 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:54:55,625 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:54:55,625 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:54:55,625 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:54:55,625 - +2026-06-24 06:54:55,625 - ### Python information ### +2026-06-24 06:54:55,626 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:54:55,626 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:54:55,626 - +2026-06-24 06:54:55,627 - ### Packages information ### +2026-06-24 06:54:55,627 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:54:55,628 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:54:55,628 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:54:55,629 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:54:55,630 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:54:55,630 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:54:55,630 - +2026-06-24 06:54:55,630 - ### Loading params file ### +2026-06-24 06:54:55,630 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000018.yaml +2026-06-24 06:54:55,638 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:54:55,639 - Success! Params file validated and defaults applied. +2026-06-24 06:54:55,639 - +2026-06-24 06:54:55,639 - ### Setting GPU Device ### +2026-06-24 06:54:55,639 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:54:55,639 - +2026-06-24 06:54:55,639 - Random seed: 20262172 provided by params file +2026-06-24 06:54:55,639 - ### Initializing Initializer ### +2026-06-24 06:54:55,639 - init_params are displayed below: +2026-06-24 06:54:55,639 - random_seed: 20262172 +2026-06-24 06:54:55,639 - probe_illum_type: electron +2026-06-24 06:54:55,639 - probe_kv: 160.0 +2026-06-24 06:54:55,640 - probe_conv_angle: 13.092960357666016 +2026-06-24 06:54:55,640 - probe_aberrations: {'C10': 19.302, 'C12': 38.123, 'phi12': 133.784, 'C21': -790.393, 'phi21': 68.407, 'C23': -563.431, 'phi23': 226.014, 'C30': 2939985.0, 'C32': 4630.43, 'phi32': 354.238, 'C34': 7143.182, 'phi34': 113.143, 'C41': -476386.969, 'phi41': 261.723, 'C43': -334667.562, 'phi43': 152.894, 'C45': -237153.672, 'phi45': 106.155, 'C50': 477455712.0, 'C52': -15748428.0, 'phi52': 32.42, 'C54': -12330208.0, 'phi54': 7.582, 'C56': 19710842.0, 'phi56': 230.257} +2026-06-24 06:54:55,640 - beam_kev: None +2026-06-24 06:54:55,640 - probe_dRn: None +2026-06-24 06:54:55,640 - probe_Rn: None +2026-06-24 06:54:55,640 - probe_D_H: None +2026-06-24 06:54:55,640 - probe_D_FZP: None +2026-06-24 06:54:55,640 - probe_Ls: None +2026-06-24 06:54:55,640 - meas_Npix: 128 +2026-06-24 06:54:55,640 - pos_N_scans: 256 +2026-06-24 06:54:55,640 - pos_N_scan_slow: 16 +2026-06-24 06:54:55,640 - pos_N_scan_fast: 16 +2026-06-24 06:54:55,640 - pos_scan_step_size: 0.46861714124679565 +2026-06-24 06:54:55,640 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:54:55,640 - probe_pmode_max: 6 +2026-06-24 06:54:55,640 - probe_pmode_init_pows: [0.02] +2026-06-24 06:54:55,640 - obj_omode_max: 1 +2026-06-24 06:54:55,640 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:54:55,640 - obj_Nlayer: 1 +2026-06-24 06:54:55,640 - obj_slice_thickness: 20.0 +2026-06-24 06:54:55,640 - simu_Npix: None +2026-06-24 06:54:55,640 - simu_match_mode: None +2026-06-24 06:54:55,640 - meas_permute: None +2026-06-24 06:54:55,640 - meas_reshape: [256, 128, 128] +2026-06-24 06:54:55,640 - meas_flipT: [0, 0, 0] +2026-06-24 06:54:55,640 - meas_crop: None +2026-06-24 06:54:55,640 - meas_pad: None +2026-06-24 06:54:55,640 - meas_resample: None +2026-06-24 06:54:55,640 - meas_add_source_size: None +2026-06-24 06:54:55,640 - meas_add_detector_blur: None +2026-06-24 06:54:55,640 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:54:55,640 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:54:55,640 - meas_add_poisson_noise: None +2026-06-24 06:54:55,640 - meas_export: None +2026-06-24 06:54:55,640 - probe_permute: None +2026-06-24 06:54:55,640 - probe_z_shift: None +2026-06-24 06:54:55,640 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:54:55,640 - pos_scan_flipT: None +2026-06-24 06:54:55,640 - pos_scan_affine: None +2026-06-24 06:54:55,641 - pos_scan_rand_std: 0.15 +2026-06-24 06:54:55,641 - obj_z_crop: None +2026-06-24 06:54:55,641 - obj_z_pad: None +2026-06-24 06:54:55,641 - obj_z_resample: None +2026-06-24 06:54:55,641 - meas_source: file +2026-06-24 06:54:55,641 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000018_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:54:55,641 - probe_source: simu +2026-06-24 06:54:55,641 - probe_params: None +2026-06-24 06:54:55,641 - pos_source: simu +2026-06-24 06:54:55,641 - pos_params: None +2026-06-24 06:54:55,641 - obj_source: simu +2026-06-24 06:54:55,641 - obj_params: None +2026-06-24 06:54:55,641 - tilt_source: simu +2026-06-24 06:54:55,641 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:54:55,641 - +2026-06-24 06:54:55,641 - ### Initializing cache ### +2026-06-24 06:54:55,641 - use_cached_obj = False +2026-06-24 06:54:55,641 - use_cached_probe = False +2026-06-24 06:54:55,641 - use_cached_pos = False +2026-06-24 06:54:55,641 - +2026-06-24 06:54:55,641 - ### Initializing measurements ### +2026-06-24 06:54:55,641 - Loading measurements from source = 'file' +2026-06-24 06:54:55,641 - Detected measurement file type = '.h5' +2026-06-24 06:54:55,718 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:54:55,718 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:54:55,720 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0030) +2026-06-24 06:54:55,720 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:54:55,720 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:54:55,722 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:54:55,722 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:54:55,722 - Normalizing by max of the 2D mean pattern intensity: 0.0021852662 +2026-06-24 06:54:55,723 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:54:55,724 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0278, 1.3624) +2026-06-24 06:54:55,725 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:54:55,726 - Pattern total int. statistics (min, mean, max) = (445.7879, 455.6831, 462.0718), with min/max = 96.5% +2026-06-24 06:54:55,728 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0278, 1.3624) +2026-06-24 06:54:55,728 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:54:55,728 - +2026-06-24 06:54:55,728 - ### Setting up calibration ### +2026-06-24 06:54:55,728 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:54:55,728 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:54:55,728 - Radius of fitted bright field disk (RBF) = 11.63 px with meas_Npix = 128 +2026-06-24 06:54:55,728 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1817 +2026-06-24 06:54:55,728 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:54:55,728 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:54:55,957 - Initial guess: center=(63.62, 63.64), radius=11.63, Gaussian blur std=0.50 +2026-06-24 06:54:55,970 - Final fit: center=(63.62, 63.64), radius=11.63, Gaussian blur std=0.68 +2026-06-24 06:54:55,970 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 11.76 px with Npix = 128 +2026-06-24 06:54:55,970 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:54:55,970 - +2026-06-24 06:54:55,970 - ### Setting init_variables dict ### +2026-06-24 06:54:55,970 - Derived values given input init_params: +2026-06-24 06:54:55,970 - kv = 160.0 kV +2026-06-24 06:54:55,970 - wavelength = 0.0285 Ang +2026-06-24 06:54:55,970 - conv_angle = 13.092960357666016 mrad +2026-06-24 06:54:55,970 - Npix = 128 px +2026-06-24 06:54:55,970 - dk = 0.0391 Ang^-1 +2026-06-24 06:54:55,970 - kMax = 2.5000 Ang^-1 +2026-06-24 06:54:55,970 - da = 1.1137 mrad +2026-06-24 06:54:55,970 - angleMax = 71.2751 mrad +2026-06-24 06:54:55,970 - RBF = 11.7565 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:54:55,970 - n_alpha = 5.4438 (# conv_angle) +2026-06-24 06:54:55,970 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:54:55,970 - Rayleigh-limited resolution = 1.3283 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:54:55,970 - Real space probe extent = 25.6000 Ang +2026-06-24 06:54:55,970 - +2026-06-24 06:54:55,970 - ### Initializing probe ### +2026-06-24 06:54:55,970 - Loading probe from source = 'simu' +2026-06-24 06:54:55,970 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:54:55,971 - Start simulating STEM probe +2026-06-24 06:54:55,971 - kv = 160.0 kV +2026-06-24 06:54:55,971 - wavelength = 0.0285 Ang +2026-06-24 06:54:55,971 - conv_angle = 13.092960357666016 mrad +2026-06-24 06:54:55,971 - Npix = 128 px +2026-06-24 06:54:55,971 - dk = 0.0391 Ang^-1 +2026-06-24 06:54:55,971 - kMax = 2.5000 Ang^-1 +2026-06-24 06:54:55,971 - alpha_max = 71.2751 mrad +2026-06-24 06:54:55,971 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:54:55,971 - Rayleigh-limited resolution = 1.3283 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:54:55,971 - Real space probe extent = 25.6000 Ang +2026-06-24 06:54:55,971 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:54:55,971 - ------------------------------------------------------------------------------------ +2026-06-24 06:54:55,971 - C1,0 C1 19.3020 - Defocus (C10 = -df) +2026-06-24 06:54:55,971 - C1,2 A1 38.1230 133.78 2-fold astigmatism +2026-06-24 06:54:55,971 - C2,1 3*B2 -790.3930 68.41 Axial coma +2026-06-24 06:54:55,971 - C2,3 A2 -563.4310 226.01 3-fold astigmatism +2026-06-24 06:54:55,971 - C3,0 C3 2939985.0000 - Spherical aberration +2026-06-24 06:54:55,971 - C3,2 4*S3 4630.4300 354.24 Axial star aberration +2026-06-24 06:54:55,971 - C3,4 A3 7143.1820 113.14 4-fold astigmatism +2026-06-24 06:54:55,971 - C4,1 4*B4 -476386.9690 261.72 Axial coma(4th) +2026-06-24 06:54:55,971 - C4,3 4*D4 -334667.5620 152.89 3-lobe aberration +2026-06-24 06:54:55,971 - C4,5 A4 -237153.6720 106.16 5-fold astigmatism +2026-06-24 06:54:55,971 - C5,0 C5 477455712.0000 - Spherical aberration (5th) +2026-06-24 06:54:55,971 - C5,2 6*S5 -15748428.0000 32.42 Axial star aberration(5th) +2026-06-24 06:54:55,971 - C5,4 6*R5 -12330208.0000 7.58 4-lobe aberration +2026-06-24 06:54:55,971 - C5,6 A5 19710842.0000 230.26 6-fold astigmatism +2026-06-24 06:54:55,974 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:54:55,974 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:54:55,974 - Creating 5 new probe modes from the major mode +2026-06-24 06:54:55,974 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:54:56,077 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:54:56,078 - Orthogonalizing 6 pmodes +2026-06-24 06:54:56,081 - Sorting 6 pmodes by their intensities +2026-06-24 06:54:56,081 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:54:56,082 - sum(|probe_data|**2) = 455.68, while meas_total_ints (min, mean, max) = (445.7879, 455.6831, 462.0718) +2026-06-24 06:54:56,082 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:54:56,082 - +2026-06-24 06:54:56,082 - ### Initializing probe positions ### +2026-06-24 06:54:56,082 - Loading probe positions from source = 'simu' +2026-06-24 06:54:56,082 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:54:56,082 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4686, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:54:56,082 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:54:56,084 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:54:56,084 - crop_pos 1st and last px coords (y,x) = ([16, 16], [52, 52]) +2026-06-24 06:54:56,084 - crop_pos extent (Ang) = [7.2 7.2] +2026-06-24 06:54:56,084 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:54:56,085 - +2026-06-24 06:54:56,085 - ### Initializing object ### +2026-06-24 06:54:56,085 - Loading object from source = 'simu' +2026-06-24 06:54:56,085 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:54:56,086 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:54:56,086 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 196, 196) +2026-06-24 06:54:56,086 - object extent (Z, Y, X) (Ang) = [20. 39.2 39.2] +2026-06-24 06:54:56,086 - +2026-06-24 06:54:56,086 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:54:56,086 - omode_occu (omode) = float32, (1,) +2026-06-24 06:54:56,086 - +2026-06-24 06:54:56,086 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:54:56,086 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0285 Ang +2026-06-24 06:54:56,087 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:54:56,087 - +2026-06-24 06:54:56,087 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:54:56,087 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:54:56,087 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:54:56,087 - +2026-06-24 06:54:56,087 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:54:56,087 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:54:56,087 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:54:56,087 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:54:56,087 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:54:56,088 - crop positions (yx_min=[16 16], yx_max=[180 180]) are well contained inside object canvas (Ny,Nx) = (196, 196). +2026-06-24 06:54:56,088 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:54:56,088 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:54:56,088 - +2026-06-24 06:54:56,088 - ### Collecting reconstruction provenance ### +2026-06-24 06:54:56,088 - Reconstruction provenance is collected and initialized. +2026-06-24 06:54:56,088 - +2026-06-24 06:54:56,088 - ### Initializing loss function ### +2026-06-24 06:54:56,088 - Active loss types: +2026-06-24 06:54:56,088 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:54:56,088 - +2026-06-24 06:54:56,088 - ### Initializing constraint function ### +2026-06-24 06:54:56,088 - Active constraint types: +2026-06-24 06:54:56,088 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:54:56,088 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:54:56,088 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:54:56,088 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:54:56,088 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:54:56,088 - +2026-06-24 06:54:56,088 - ### Done initializing PtyRADSolver ### +2026-06-24 06:54:56,088 - +2026-06-24 06:54:56,213 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:54:56,213 - +2026-06-24 06:54:56,213 - ### Initializing PtychoModel model ### +2026-06-24 06:54:56,295 - ### PtychoModel optimizable variables ### +2026-06-24 06:54:56,295 - obja : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:56,295 - objp : torch.Size([1, 1, 196, 196]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:56,295 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:54:56,295 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:54:56,295 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:54:56,295 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:54:56,295 - +2026-06-24 06:54:56,295 - ### Optimizable variables statitsics ### +2026-06-24 06:54:56,295 - Total measurement values : 4,194,304 +2026-06-24 06:54:56,295 - Total optimizing variables: 273,952 +2026-06-24 06:54:56,295 - Overdetermined ratio : 15.31 +2026-06-24 06:54:56,295 - +2026-06-24 06:54:56,295 - ### Model behavior ### +2026-06-24 06:54:56,295 - Tilt propagator : False +2026-06-24 06:54:56,295 - Change slice thickness : False +2026-06-24 06:54:56,295 - Detector blur : False +2026-06-24 06:54:56,296 - Preload data : True +2026-06-24 06:54:56,296 - On-the-fly meas padding : False +2026-06-24 06:54:56,296 - On-the-fly meas resample : False +2026-06-24 06:54:56,296 - On-the-fly simu match mode: None +2026-06-24 06:54:56,296 - +2026-06-24 06:54:56,338 - ### Done initializing PtychoModel model ### +2026-06-24 06:54:56,338 - +2026-06-24 06:54:56,338 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:54:56,338 - +2026-06-24 06:54:56,338 - ### Generating indices, batches, and output_path ### +2026-06-24 06:54:56,339 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:54:56,339 - Selecting indices with the 'full' mode +2026-06-24 06:54:56,797 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:54:56,872 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:54:56,873 - Original recon_dir_affixes = ['default'] +2026-06-24 06:54:56,873 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:54:56,879 - Path corrected for compatibility: +2026-06-24 06:54:56,879 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C32_4.63e+03_phi32_354_C34_7.14e+03_phi34_113_C41_-4.76e+05_phi41_262_C43_-3.35e+05_phi43_153_C45_-2.37e+05_phi45_106_C50_4.77e+08_C52_-1.57e+07_phi52_32.4_C54_-1.23e+07_phi54_7.58_C56_1.97e+07_phi56_230 +2026-06-24 06:54:56,879 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230 +2026-06-24 06:54:56,880 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230' is generated! +2026-06-24 06:54:57,031 - +2026-06-24 06:54:57,032 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230/20260624_065457_ptyrad_log.txt ### +2026-06-24 06:54:57,032 - +2026-06-24 06:54:57,034 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:54:57,034 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:54:57,034 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:54:58,215 - Iter: 1, Total Loss: 0.9361, loss_single: 0.9361, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 06:54:58,252 - Iter: 2, Total Loss: 0.9021, loss_single: 0.9021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:54:58,286 - Iter: 3, Total Loss: 0.8759, loss_single: 0.8759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,321 - Iter: 4, Total Loss: 0.8545, loss_single: 0.8545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,356 - Iter: 5, Total Loss: 0.8320, loss_single: 0.8320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,391 - Iter: 6, Total Loss: 0.8100, loss_single: 0.8100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,425 - Iter: 7, Total Loss: 0.7892, loss_single: 0.7892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,460 - Iter: 8, Total Loss: 0.7704, loss_single: 0.7704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,494 - Iter: 9, Total Loss: 0.7533, loss_single: 0.7533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,529 - Iter: 10, Total Loss: 0.7339, loss_single: 0.7339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,564 - Iter: 11, Total Loss: 0.7128, loss_single: 0.7128, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,599 - Iter: 12, Total Loss: 0.6899, loss_single: 0.6899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,634 - Iter: 13, Total Loss: 0.6647, loss_single: 0.6647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,669 - Iter: 14, Total Loss: 0.6415, loss_single: 0.6415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,704 - Iter: 15, Total Loss: 0.6226, loss_single: 0.6226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,739 - Iter: 16, Total Loss: 0.6034, loss_single: 0.6034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,774 - Iter: 17, Total Loss: 0.5829, loss_single: 0.5829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:54:58,809 - Iter: 18, Total Loss: 0.5688, loss_single: 0.5688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,844 - Iter: 19, Total Loss: 0.5584, loss_single: 0.5584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,878 - Iter: 20, Total Loss: 0.5473, loss_single: 0.5473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,913 - Iter: 21, Total Loss: 0.5361, loss_single: 0.5361, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,948 - Iter: 22, Total Loss: 0.5227, loss_single: 0.5227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:58,983 - Iter: 23, Total Loss: 0.5123, loss_single: 0.5123, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:54:59,017 - Iter: 24, Total Loss: 0.5035, loss_single: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000018/c30_small__simulation_data_aug3__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_19.3_C12_38.1_phi12_134_C21_-790_phi21_68.4_C23_-563_phi23_226_C30_2.94e+06_C.97e+07_phi56_230/simulation_data_aug3__sample_000018.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 160.0 + probe_conv_angle: 13.092960357666016 + probe_aberrations: + C10: 19.301504135131836 + C12: 38.12332534790039 + C21: -790.3927612304688 + C23: -563.4306030273438 + C30: 2939985.0 + C32: 4630.4296875 + C34: 7143.181640625 + C41: -476386.96875 + C43: -334667.5625 + C45: -237153.671875 + C50: 477455712.0 + C52: -15748428.0 + C54: -12330208.0 + C56: 19710842.0 + phi12: 133.78440425427883 + phi21: 68.40694683975147 + phi23: 226.01412884349682 + phi32: 354.2375979812264 + phi34: 113.14267782771901 + phi41: 261.7232594092939 + phi43: 152.89352502354697 + phi45: 106.15491619355407 + phi52: 32.420233970990466 + phi54: 7.582116158002992 + phi56: 230.25715163893545 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.46861714124679565 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000018_measurement.h5 + key: measurement + random_seed: 20262172 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/20260624_065754_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..809581fb1fb6c024605c556ed5260aa84977c46d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/20260624_065754_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:57:52,605 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:57:52,605 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:57:52,605 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:57:52,605 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:57:52,605 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:57:52,605 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:57:52,605 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:57:52,605 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:57:52,605 - +2026-06-24 06:57:52,738 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:57:52,738 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:57:52,738 - Accelerator.num_process = 1 +2026-06-24 06:57:52,738 - Accelerator.mixed_precision = no +2026-06-24 06:57:52,761 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:57:52,761 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:57:52,761 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:57:52,761 - +2026-06-24 06:57:52,761 - ### System information ### +2026-06-24 06:57:52,761 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:57:52,761 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:57:52,761 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:57:52,761 - Machine: x86_64 +2026-06-24 06:57:52,761 - Processor: x86_64 +2026-06-24 06:57:52,761 - Available CPU cores: 8 +2026-06-24 06:57:52,761 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:57:52,761 - +2026-06-24 06:57:52,761 - ### GPU information ### +2026-06-24 06:57:52,761 - CUDA Available: True +2026-06-24 06:57:52,761 - CUDA Version: 13.0 +2026-06-24 06:57:52,762 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:57:52,762 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:57:52,762 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:57:52,762 - In addition, Triton does not directly support Windows. +2026-06-24 06:57:52,762 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:57:52,790 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:57:52,790 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:57:52,790 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:57:52,790 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:57:52,790 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:57:52,790 - +2026-06-24 06:57:52,790 - ### Python information ### +2026-06-24 06:57:52,792 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:57:52,792 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:57:52,792 - +2026-06-24 06:57:52,793 - ### Packages information ### +2026-06-24 06:57:52,793 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:57:52,794 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:57:52,795 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:57:52,795 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:57:52,796 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:57:52,796 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:57:52,796 - +2026-06-24 06:57:52,796 - ### Loading params file ### +2026-06-24 06:57:52,796 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000030.yaml +2026-06-24 06:57:52,802 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:57:52,803 - Success! Params file validated and defaults applied. +2026-06-24 06:57:52,803 - +2026-06-24 06:57:52,804 - ### Setting GPU Device ### +2026-06-24 06:57:52,804 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:57:52,804 - +2026-06-24 06:57:52,804 - Random seed: 20262184 provided by params file +2026-06-24 06:57:52,804 - ### Initializing Initializer ### +2026-06-24 06:57:52,804 - init_params are displayed below: +2026-06-24 06:57:52,804 - random_seed: 20262184 +2026-06-24 06:57:52,804 - probe_illum_type: electron +2026-06-24 06:57:52,804 - probe_kv: 120.0 +2026-06-24 06:57:52,804 - probe_conv_angle: 17.265893936157227 +2026-06-24 06:57:52,804 - probe_aberrations: {'C10': -628.892, 'C12': 19.502, 'phi12': 302.065, 'C21': 62.982, 'phi21': 356.407, 'C23': -736.751, 'phi23': 321.661, 'C30': 3763833.5, 'C32': 10336.141, 'phi32': 200.68, 'C34': -8364.318, 'phi34': 17.339, 'C41': 82712.609, 'phi41': 295.893, 'C43': -394794.562, 'phi43': 17.211, 'C45': 166090.844, 'phi45': 237.39, 'C50': -258292192.0, 'C52': 19304924.0, 'phi52': 45.717, 'C54': -4551089.0, 'phi54': 171.399, 'C56': -16995614.0, 'phi56': 317.37} +2026-06-24 06:57:52,804 - beam_kev: None +2026-06-24 06:57:52,804 - probe_dRn: None +2026-06-24 06:57:52,804 - probe_Rn: None +2026-06-24 06:57:52,804 - probe_D_H: None +2026-06-24 06:57:52,804 - probe_D_FZP: None +2026-06-24 06:57:52,804 - probe_Ls: None +2026-06-24 06:57:52,804 - meas_Npix: 128 +2026-06-24 06:57:52,805 - pos_N_scans: 256 +2026-06-24 06:57:52,805 - pos_N_scan_slow: 16 +2026-06-24 06:57:52,805 - pos_N_scan_fast: 16 +2026-06-24 06:57:52,805 - pos_scan_step_size: 0.5206128358840942 +2026-06-24 06:57:52,805 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:57:52,805 - probe_pmode_max: 6 +2026-06-24 06:57:52,805 - probe_pmode_init_pows: [0.02] +2026-06-24 06:57:52,805 - obj_omode_max: 1 +2026-06-24 06:57:52,805 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:57:52,805 - obj_Nlayer: 1 +2026-06-24 06:57:52,805 - obj_slice_thickness: 20.0 +2026-06-24 06:57:52,805 - simu_Npix: None +2026-06-24 06:57:52,805 - simu_match_mode: None +2026-06-24 06:57:52,805 - meas_permute: None +2026-06-24 06:57:52,805 - meas_reshape: [256, 128, 128] +2026-06-24 06:57:52,805 - meas_flipT: [0, 0, 0] +2026-06-24 06:57:52,805 - meas_crop: None +2026-06-24 06:57:52,805 - meas_pad: None +2026-06-24 06:57:52,805 - meas_resample: None +2026-06-24 06:57:52,805 - meas_add_source_size: None +2026-06-24 06:57:52,805 - meas_add_detector_blur: None +2026-06-24 06:57:52,805 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:57:52,805 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:57:52,805 - meas_add_poisson_noise: None +2026-06-24 06:57:52,805 - meas_export: None +2026-06-24 06:57:52,805 - probe_permute: None +2026-06-24 06:57:52,805 - probe_z_shift: None +2026-06-24 06:57:52,805 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:57:52,805 - pos_scan_flipT: None +2026-06-24 06:57:52,805 - pos_scan_affine: None +2026-06-24 06:57:52,805 - pos_scan_rand_std: 0.15 +2026-06-24 06:57:52,805 - obj_z_crop: None +2026-06-24 06:57:52,805 - obj_z_pad: None +2026-06-24 06:57:52,805 - obj_z_resample: None +2026-06-24 06:57:52,805 - meas_source: file +2026-06-24 06:57:52,805 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000030_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:57:52,805 - probe_source: simu +2026-06-24 06:57:52,805 - probe_params: None +2026-06-24 06:57:52,805 - pos_source: simu +2026-06-24 06:57:52,805 - pos_params: None +2026-06-24 06:57:52,805 - obj_source: simu +2026-06-24 06:57:52,806 - obj_params: None +2026-06-24 06:57:52,806 - tilt_source: simu +2026-06-24 06:57:52,806 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:57:52,806 - +2026-06-24 06:57:52,806 - ### Initializing cache ### +2026-06-24 06:57:52,806 - use_cached_obj = False +2026-06-24 06:57:52,806 - use_cached_probe = False +2026-06-24 06:57:52,806 - use_cached_pos = False +2026-06-24 06:57:52,806 - +2026-06-24 06:57:52,806 - ### Initializing measurements ### +2026-06-24 06:57:52,806 - Loading measurements from source = 'file' +2026-06-24 06:57:52,806 - Detected measurement file type = '.h5' +2026-06-24 06:57:52,884 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:57:52,884 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:57:52,886 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0029) +2026-06-24 06:57:52,886 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:57:52,886 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:57:52,888 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:57:52,888 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:57:52,888 - Normalizing by max of the 2D mean pattern intensity: 0.0017796629 +2026-06-24 06:57:52,889 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:57:52,890 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0342, 1.6236) +2026-06-24 06:57:52,891 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:57:52,892 - Pattern total int. statistics (min, mean, max) = (557.1887, 560.9363, 566.1880), with min/max = 98.4% +2026-06-24 06:57:52,893 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0342, 1.6236) +2026-06-24 06:57:52,894 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:57:52,894 - +2026-06-24 06:57:52,894 - ### Setting up calibration ### +2026-06-24 06:57:52,894 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:57:52,894 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:57:52,894 - Radius of fitted bright field disk (RBF) = 13.06 px with meas_Npix = 128 +2026-06-24 06:57:52,894 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2041 +2026-06-24 06:57:52,894 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:57:52,894 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:57:53,122 - Initial guess: center=(63.62, 63.62), radius=13.06, Gaussian blur std=0.50 +2026-06-24 06:57:53,138 - Final fit: center=(63.62, 63.62), radius=13.06, Gaussian blur std=0.72 +2026-06-24 06:57:53,138 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 13.20 px with Npix = 128 +2026-06-24 06:57:53,138 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:57:53,138 - +2026-06-24 06:57:53,138 - ### Setting init_variables dict ### +2026-06-24 06:57:53,138 - Derived values given input init_params: +2026-06-24 06:57:53,138 - kv = 120.0 kV +2026-06-24 06:57:53,139 - wavelength = 0.0335 Ang +2026-06-24 06:57:53,139 - conv_angle = 17.265893936157227 mrad +2026-06-24 06:57:53,139 - Npix = 128 px +2026-06-24 06:57:53,139 - dk = 0.0391 Ang^-1 +2026-06-24 06:57:53,139 - kMax = 2.5000 Ang^-1 +2026-06-24 06:57:53,139 - da = 1.3083 mrad +2026-06-24 06:57:53,139 - angleMax = 83.7304 mrad +2026-06-24 06:57:53,139 - RBF = 13.1973 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:57:53,139 - n_alpha = 4.8495 (# conv_angle) +2026-06-24 06:57:53,139 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:57:53,139 - Rayleigh-limited resolution = 1.1833 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:57:53,139 - Real space probe extent = 25.6000 Ang +2026-06-24 06:57:53,139 - +2026-06-24 06:57:53,139 - ### Initializing probe ### +2026-06-24 06:57:53,139 - Loading probe from source = 'simu' +2026-06-24 06:57:53,139 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:57:53,139 - Start simulating STEM probe +2026-06-24 06:57:53,139 - kv = 120.0 kV +2026-06-24 06:57:53,139 - wavelength = 0.0335 Ang +2026-06-24 06:57:53,139 - conv_angle = 17.265893936157227 mrad +2026-06-24 06:57:53,139 - Npix = 128 px +2026-06-24 06:57:53,139 - dk = 0.0391 Ang^-1 +2026-06-24 06:57:53,139 - kMax = 2.5000 Ang^-1 +2026-06-24 06:57:53,139 - alpha_max = 83.7304 mrad +2026-06-24 06:57:53,139 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:57:53,139 - Rayleigh-limited resolution = 1.1833 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:57:53,140 - Real space probe extent = 25.6000 Ang +2026-06-24 06:57:53,140 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:57:53,140 - ------------------------------------------------------------------------------------- +2026-06-24 06:57:53,140 - C1,0 C1 -628.8920 - Defocus (C10 = -df) +2026-06-24 06:57:53,140 - C1,2 A1 19.5020 302.06 2-fold astigmatism +2026-06-24 06:57:53,140 - C2,1 3*B2 62.9820 356.41 Axial coma +2026-06-24 06:57:53,140 - C2,3 A2 -736.7510 321.66 3-fold astigmatism +2026-06-24 06:57:53,140 - C3,0 C3 3763833.5000 - Spherical aberration +2026-06-24 06:57:53,140 - C3,2 4*S3 10336.1410 200.68 Axial star aberration +2026-06-24 06:57:53,140 - C3,4 A3 -8364.3180 17.34 4-fold astigmatism +2026-06-24 06:57:53,140 - C4,1 4*B4 82712.6090 295.89 Axial coma(4th) +2026-06-24 06:57:53,140 - C4,3 4*D4 -394794.5620 17.21 3-lobe aberration +2026-06-24 06:57:53,140 - C4,5 A4 166090.8440 237.39 5-fold astigmatism +2026-06-24 06:57:53,140 - C5,0 C5 -258292192.0000 - Spherical aberration (5th) +2026-06-24 06:57:53,140 - C5,2 6*S5 19304924.0000 45.72 Axial star aberration(5th) +2026-06-24 06:57:53,140 - C5,4 6*R5 -4551089.0000 171.40 4-lobe aberration +2026-06-24 06:57:53,140 - C5,6 A5 -16995614.0000 317.37 6-fold astigmatism +2026-06-24 06:57:53,143 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:57:53,143 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:57:53,143 - Creating 5 new probe modes from the major mode +2026-06-24 06:57:53,143 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:57:53,386 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:57:53,388 - Orthogonalizing 6 pmodes +2026-06-24 06:57:53,400 - Sorting 6 pmodes by their intensities +2026-06-24 06:57:53,400 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:57:53,401 - sum(|probe_data|**2) = 560.94, while meas_total_ints (min, mean, max) = (557.1887, 560.9363, 566.1880) +2026-06-24 06:57:53,401 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:57:53,401 - +2026-06-24 06:57:53,401 - ### Initializing probe positions ### +2026-06-24 06:57:53,401 - Loading probe positions from source = 'simu' +2026-06-24 06:57:53,401 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:57:53,401 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5206, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:57:53,401 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:57:53,403 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:57:53,403 - crop_pos 1st and last px coords (y,x) = ([17, 16], [56, 56]) +2026-06-24 06:57:53,404 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 06:57:53,404 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:57:53,404 - +2026-06-24 06:57:53,404 - ### Initializing object ### +2026-06-24 06:57:53,404 - Loading object from source = 'simu' +2026-06-24 06:57:53,404 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:57:53,405 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:57:53,405 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 201, 201) +2026-06-24 06:57:53,405 - object extent (Z, Y, X) (Ang) = [20. 40.2 40.2] +2026-06-24 06:57:53,405 - +2026-06-24 06:57:53,406 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:57:53,406 - omode_occu (omode) = float32, (1,) +2026-06-24 06:57:53,406 - +2026-06-24 06:57:53,406 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:57:53,406 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:57:53,406 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:57:53,406 - +2026-06-24 06:57:53,406 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:57:53,406 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:57:53,406 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:57:53,406 - +2026-06-24 06:57:53,407 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:57:53,407 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:57:53,407 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:57:53,407 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:57:53,407 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:57:53,407 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (201, 201). +2026-06-24 06:57:53,407 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:57:53,407 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:57:53,407 - +2026-06-24 06:57:53,407 - ### Collecting reconstruction provenance ### +2026-06-24 06:57:53,407 - Reconstruction provenance is collected and initialized. +2026-06-24 06:57:53,407 - +2026-06-24 06:57:53,407 - ### Initializing loss function ### +2026-06-24 06:57:53,407 - Active loss types: +2026-06-24 06:57:53,407 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:57:53,407 - +2026-06-24 06:57:53,407 - ### Initializing constraint function ### +2026-06-24 06:57:53,407 - Active constraint types: +2026-06-24 06:57:53,407 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:57:53,407 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:57:53,407 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:57:53,408 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:57:53,408 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:57:53,408 - +2026-06-24 06:57:53,408 - ### Done initializing PtyRADSolver ### +2026-06-24 06:57:53,408 - +2026-06-24 06:57:53,533 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:57:53,533 - +2026-06-24 06:57:53,533 - ### Initializing PtychoModel model ### +2026-06-24 06:57:53,605 - ### PtychoModel optimizable variables ### +2026-06-24 06:57:53,605 - obja : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:57:53,605 - objp : torch.Size([1, 1, 201, 201]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:57:53,605 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:57:53,605 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:57:53,605 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:57:53,605 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:57:53,606 - +2026-06-24 06:57:53,606 - ### Optimizable variables statitsics ### +2026-06-24 06:57:53,606 - Total measurement values : 4,194,304 +2026-06-24 06:57:53,606 - Total optimizing variables: 277,922 +2026-06-24 06:57:53,606 - Overdetermined ratio : 15.09 +2026-06-24 06:57:53,606 - +2026-06-24 06:57:53,606 - ### Model behavior ### +2026-06-24 06:57:53,606 - Tilt propagator : False +2026-06-24 06:57:53,606 - Change slice thickness : False +2026-06-24 06:57:53,606 - Detector blur : False +2026-06-24 06:57:53,606 - Preload data : True +2026-06-24 06:57:53,606 - On-the-fly meas padding : False +2026-06-24 06:57:53,606 - On-the-fly meas resample : False +2026-06-24 06:57:53,606 - On-the-fly simu match mode: None +2026-06-24 06:57:53,606 - +2026-06-24 06:57:53,646 - ### Done initializing PtychoModel model ### +2026-06-24 06:57:53,646 - +2026-06-24 06:57:53,647 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:57:53,647 - +2026-06-24 06:57:53,647 - ### Generating indices, batches, and output_path ### +2026-06-24 06:57:53,648 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:57:53,648 - Selecting indices with the 'full' mode +2026-06-24 06:57:54,108 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:57:54,186 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:57:54,186 - Original recon_dir_affixes = ['default'] +2026-06-24 06:57:54,186 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:57:54,192 - Path corrected for compatibility: +2026-06-24 06:57:54,192 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.03e+04_phi32_201_C34_-8.36e+03_phi34_17.3_C41_8.27e+04_phi41_296_C43_-3.95e+05_phi43_17.2_C45_1.66e+05_phi45_237_C50_-2.58e+08_C52_1.93e+07_phi52_45.7_C54_-4.55e+06_phi54_171_C56_-1.7e+07_phi56_317 +2026-06-24 06:57:54,192 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317 +2026-06-24 06:57:54,194 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317' is generated! +2026-06-24 06:57:54,356 - +2026-06-24 06:57:54,357 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/20260624_065754_ptyrad_log.txt ### +2026-06-24 06:57:54,357 - +2026-06-24 06:57:54,358 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:57:54,358 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:57:54,359 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:57:55,540 - Iter: 1, Total Loss: 0.8084, loss_single: 0.8084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 06:57:55,577 - Iter: 2, Total Loss: 0.7790, loss_single: 0.7790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:57:55,613 - Iter: 3, Total Loss: 0.7558, loss_single: 0.7558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,649 - Iter: 4, Total Loss: 0.7360, loss_single: 0.7360, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,685 - Iter: 5, Total Loss: 0.7186, loss_single: 0.7186, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:57:55,720 - Iter: 6, Total Loss: 0.7018, loss_single: 0.7018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,756 - Iter: 7, Total Loss: 0.6855, loss_single: 0.6855, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,793 - Iter: 8, Total Loss: 0.6677, loss_single: 0.6677, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:57:55,829 - Iter: 9, Total Loss: 0.6492, loss_single: 0.6492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,864 - Iter: 10, Total Loss: 0.6324, loss_single: 0.6324, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,899 - Iter: 11, Total Loss: 0.6145, loss_single: 0.6145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,935 - Iter: 12, Total Loss: 0.5961, loss_single: 0.5961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:55,970 - Iter: 13, Total Loss: 0.5776, loss_single: 0.5776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,006 - Iter: 14, Total Loss: 0.5614, loss_single: 0.5614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,042 - Iter: 15, Total Loss: 0.5460, loss_single: 0.5460, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:57:56,077 - Iter: 16, Total Loss: 0.5296, loss_single: 0.5296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,113 - Iter: 17, Total Loss: 0.5146, loss_single: 0.5146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,148 - Iter: 18, Total Loss: 0.5004, loss_single: 0.5004, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,183 - Iter: 19, Total Loss: 0.4862, loss_single: 0.4862, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,218 - Iter: 20, Total Loss: 0.4731, loss_single: 0.4731, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,254 - Iter: 21, Total Loss: 0.4602, loss_single: 0.4602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,290 - Iter: 22, Total Loss: 0.4486, loss_single: 0.4486, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:57:56,325 - Iter: 23, Total Loss: 0.4386, loss_single: 0.4386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:57:56,361 - Iter: 24, Total Loss: 0.4275, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/simulation_data_aug3__sample_000030.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/simulation_data_aug3__sample_000030.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1147e4ca098931398c0fcd94ba59a54af8206230 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/simulation_data_aug3__sample_000030.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 17.265893936157227 + probe_aberrations: + C10: -628.8924560546875 + C12: 19.502201080322266 + C21: 62.98201370239258 + C23: -736.7506713867188 + C30: 3763833.5 + C32: 10336.140625 + C34: -8364.318359375 + C41: 82712.609375 + C43: -394794.5625 + C45: 166090.84375 + C50: -258292192.0 + C52: 19304924.0 + C54: -4551089.0 + C56: -16995614.0 + phi12: 302.06492479851715 + phi21: 356.407412476756 + phi23: 321.660710206527 + phi32: 200.68008294770576 + phi34: 17.3385871797864 + phi41: 295.8925101663333 + phi43: 17.211190491387324 + phi45: 237.39019139674656 + phi52: 45.7167203226052 + phi54: 171.39938982494127 + phi56: 317.3703951812752 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5206128358840942 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000030_measurement.h5 + key: measurement + random_seed: 20262184 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug3__sample_000030 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/summary_convergence_iter0100.png b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/summary_convergence_iter0100.png new file mode 100644 index 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0000000000000000000000000000000000000000..98892c4549fd7cac3ab107c1cf57430f6621283e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d2ddfc23a61aef044628c87c0bc3b59c08d1645ec13dd55b617b7b800b483380 +size 1296082 diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000030/c30_small__simulation_data_aug3__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-629_C12_19.5_phi12_302_C21_63_phi21_356_C23_-737_phi23_322_C30_3.76e+06_C32_1.7e+07_phi56_317/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e845139f897c7c91eb312db66d752b5ae52d4af876f5a3aa57afc9d8bdeb9d7f +size 47338 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/20260624_065823_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/20260624_065823_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..167730abfb338766540c6691cc826f4a82fb3cba --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/20260624_065823_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:58:22,247 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:58:22,248 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:58:22,248 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:58:22,248 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:58:22,248 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:58:22,248 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:58:22,248 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:58:22,248 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:58:22,248 - +2026-06-24 06:58:22,357 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:58:22,357 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:58:22,357 - Accelerator.num_process = 1 +2026-06-24 06:58:22,357 - Accelerator.mixed_precision = no +2026-06-24 06:58:22,367 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:58:22,368 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:58:22,368 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:58:22,368 - +2026-06-24 06:58:22,368 - ### System information ### +2026-06-24 06:58:22,368 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:58:22,368 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:58:22,368 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:58:22,368 - Machine: x86_64 +2026-06-24 06:58:22,368 - Processor: x86_64 +2026-06-24 06:58:22,368 - Available CPU cores: 8 +2026-06-24 06:58:22,368 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:58:22,368 - +2026-06-24 06:58:22,368 - ### GPU information ### +2026-06-24 06:58:22,368 - CUDA Available: True +2026-06-24 06:58:22,368 - CUDA Version: 13.0 +2026-06-24 06:58:22,369 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:58:22,369 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:58:22,369 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:58:22,369 - In addition, Triton does not directly support Windows. +2026-06-24 06:58:22,369 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:58:22,383 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:58:22,384 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:58:22,384 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:58:22,384 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:58:22,384 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:58:22,384 - +2026-06-24 06:58:22,384 - ### Python information ### +2026-06-24 06:58:22,385 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:58:22,386 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:58:22,386 - +2026-06-24 06:58:22,386 - ### Packages information ### +2026-06-24 06:58:22,386 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:58:22,387 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:58:22,387 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:58:22,388 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:58:22,389 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:58:22,389 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:58:22,389 - +2026-06-24 06:58:22,389 - ### Loading params file ### +2026-06-24 06:58:22,389 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000032.yaml +2026-06-24 06:58:22,395 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:58:22,396 - Success! Params file validated and defaults applied. +2026-06-24 06:58:22,396 - +2026-06-24 06:58:22,397 - ### Setting GPU Device ### +2026-06-24 06:58:22,397 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:58:22,397 - +2026-06-24 06:58:22,397 - Random seed: 20262186 provided by params file +2026-06-24 06:58:22,397 - ### Initializing Initializer ### +2026-06-24 06:58:22,397 - init_params are displayed below: +2026-06-24 06:58:22,397 - random_seed: 20262186 +2026-06-24 06:58:22,397 - probe_illum_type: electron +2026-06-24 06:58:22,397 - probe_kv: 80.0 +2026-06-24 06:58:22,397 - probe_conv_angle: 24.3415584564209 +2026-06-24 06:58:22,397 - probe_aberrations: {'C10': -629.519, 'C12': -8.802, 'phi12': 95.719, 'C21': 362.438, 'phi21': 198.509, 'C23': -120.148, 'phi23': 219.811, 'C30': 1122122.0, 'C32': 2834.926, 'phi32': 351.658, 'C34': -5432.228, 'phi34': 354.486, 'C41': -481127.094, 'phi41': 342.442, 'C43': -401575.469, 'phi43': 112.952, 'C45': -145142.875, 'phi45': 105.244, 'C50': -149249216.0, 'C52': -9506572.0, 'phi52': 6.127, 'C54': -19155148.0, 'phi54': 290.678, 'C56': -5630734.5, 'phi56': 117.032} +2026-06-24 06:58:22,397 - beam_kev: None +2026-06-24 06:58:22,397 - probe_dRn: None +2026-06-24 06:58:22,397 - probe_Rn: None +2026-06-24 06:58:22,397 - probe_D_H: None +2026-06-24 06:58:22,397 - probe_D_FZP: None +2026-06-24 06:58:22,397 - probe_Ls: None +2026-06-24 06:58:22,398 - meas_Npix: 128 +2026-06-24 06:58:22,398 - pos_N_scans: 256 +2026-06-24 06:58:22,398 - pos_N_scan_slow: 16 +2026-06-24 06:58:22,398 - pos_N_scan_fast: 16 +2026-06-24 06:58:22,398 - pos_scan_step_size: 0.37401965260505676 +2026-06-24 06:58:22,398 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:58:22,398 - probe_pmode_max: 6 +2026-06-24 06:58:22,398 - probe_pmode_init_pows: [0.02] +2026-06-24 06:58:22,398 - obj_omode_max: 1 +2026-06-24 06:58:22,398 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:58:22,398 - obj_Nlayer: 1 +2026-06-24 06:58:22,398 - obj_slice_thickness: 20.0 +2026-06-24 06:58:22,398 - simu_Npix: None +2026-06-24 06:58:22,398 - simu_match_mode: None +2026-06-24 06:58:22,398 - meas_permute: None +2026-06-24 06:58:22,398 - meas_reshape: [256, 128, 128] +2026-06-24 06:58:22,398 - meas_flipT: [0, 0, 0] +2026-06-24 06:58:22,398 - meas_crop: None +2026-06-24 06:58:22,398 - meas_pad: None +2026-06-24 06:58:22,398 - meas_resample: None +2026-06-24 06:58:22,398 - meas_add_source_size: None +2026-06-24 06:58:22,398 - meas_add_detector_blur: None +2026-06-24 06:58:22,398 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:58:22,398 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:58:22,398 - meas_add_poisson_noise: None +2026-06-24 06:58:22,398 - meas_export: None +2026-06-24 06:58:22,398 - probe_permute: None +2026-06-24 06:58:22,398 - probe_z_shift: None +2026-06-24 06:58:22,398 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:58:22,398 - pos_scan_flipT: None +2026-06-24 06:58:22,398 - pos_scan_affine: None +2026-06-24 06:58:22,398 - pos_scan_rand_std: 0.15 +2026-06-24 06:58:22,398 - obj_z_crop: None +2026-06-24 06:58:22,398 - obj_z_pad: None +2026-06-24 06:58:22,398 - obj_z_resample: None +2026-06-24 06:58:22,398 - meas_source: file +2026-06-24 06:58:22,398 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000032_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:58:22,398 - probe_source: simu +2026-06-24 06:58:22,398 - probe_params: None +2026-06-24 06:58:22,398 - pos_source: simu +2026-06-24 06:58:22,398 - pos_params: None +2026-06-24 06:58:22,399 - obj_source: simu +2026-06-24 06:58:22,399 - obj_params: None +2026-06-24 06:58:22,399 - tilt_source: simu +2026-06-24 06:58:22,399 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:58:22,399 - +2026-06-24 06:58:22,399 - ### Initializing cache ### +2026-06-24 06:58:22,399 - use_cached_obj = False +2026-06-24 06:58:22,399 - use_cached_probe = False +2026-06-24 06:58:22,399 - use_cached_pos = False +2026-06-24 06:58:22,399 - +2026-06-24 06:58:22,399 - ### Initializing measurements ### +2026-06-24 06:58:22,399 - Loading measurements from source = 'file' +2026-06-24 06:58:22,399 - Detected measurement file type = '.h5' +2026-06-24 06:58:22,479 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:58:22,479 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:58:22,481 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0022) +2026-06-24 06:58:22,481 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:58:22,481 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:58:22,482 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:58:22,482 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:58:22,483 - Normalizing by max of the 2D mean pattern intensity: 0.0012900991 +2026-06-24 06:58:22,483 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:58:22,486 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0466, 1.6816) +2026-06-24 06:58:22,487 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:58:22,488 - Pattern total int. statistics (min, mean, max) = (753.8368, 763.8416, 768.8050), with min/max = 98.1% +2026-06-24 06:58:22,490 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0466, 1.6816) +2026-06-24 06:58:22,490 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:58:22,490 - +2026-06-24 06:58:22,490 - ### Setting up calibration ### +2026-06-24 06:58:22,490 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:58:22,490 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:58:22,490 - Radius of fitted bright field disk (RBF) = 14.82 px with meas_Npix = 128 +2026-06-24 06:58:22,490 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2316 +2026-06-24 06:58:22,490 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:58:22,490 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:58:22,719 - Initial guess: center=(63.61, 63.63), radius=14.82, Gaussian blur std=0.50 +2026-06-24 06:58:22,734 - Final fit: center=(63.61, 63.63), radius=14.82, Gaussian blur std=0.77 +2026-06-24 06:58:22,734 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 14.92 px with Npix = 128 +2026-06-24 06:58:22,734 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:58:22,734 - +2026-06-24 06:58:22,734 - ### Setting init_variables dict ### +2026-06-24 06:58:22,734 - Derived values given input init_params: +2026-06-24 06:58:22,734 - kv = 80.0 kV +2026-06-24 06:58:22,734 - wavelength = 0.0418 Ang +2026-06-24 06:58:22,734 - conv_angle = 24.3415584564209 mrad +2026-06-24 06:58:22,734 - Npix = 128 px +2026-06-24 06:58:22,734 - dk = 0.0391 Ang^-1 +2026-06-24 06:58:22,734 - kMax = 2.5000 Ang^-1 +2026-06-24 06:58:22,734 - da = 1.6311 mrad +2026-06-24 06:58:22,734 - angleMax = 104.3929 mrad +2026-06-24 06:58:22,734 - RBF = 14.9230 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:58:22,734 - n_alpha = 4.2887 (# conv_angle) +2026-06-24 06:58:22,734 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:58:22,734 - Rayleigh-limited resolution = 1.0464 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:58:22,734 - Real space probe extent = 25.6000 Ang +2026-06-24 06:58:22,734 - +2026-06-24 06:58:22,734 - ### Initializing probe ### +2026-06-24 06:58:22,734 - Loading probe from source = 'simu' +2026-06-24 06:58:22,734 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:58:22,735 - Start simulating STEM probe +2026-06-24 06:58:22,735 - kv = 80.0 kV +2026-06-24 06:58:22,735 - wavelength = 0.0418 Ang +2026-06-24 06:58:22,735 - conv_angle = 24.3415584564209 mrad +2026-06-24 06:58:22,735 - Npix = 128 px +2026-06-24 06:58:22,735 - dk = 0.0391 Ang^-1 +2026-06-24 06:58:22,735 - kMax = 2.5000 Ang^-1 +2026-06-24 06:58:22,735 - alpha_max = 104.3929 mrad +2026-06-24 06:58:22,735 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:58:22,735 - Rayleigh-limited resolution = 1.0464 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:58:22,735 - Real space probe extent = 25.6000 Ang +2026-06-24 06:58:22,735 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:58:22,735 - ------------------------------------------------------------------------------------- +2026-06-24 06:58:22,735 - C1,0 C1 -629.5190 - Defocus (C10 = -df) +2026-06-24 06:58:22,735 - C1,2 A1 -8.8020 95.72 2-fold astigmatism +2026-06-24 06:58:22,735 - C2,1 3*B2 362.4380 198.51 Axial coma +2026-06-24 06:58:22,735 - C2,3 A2 -120.1480 219.81 3-fold astigmatism +2026-06-24 06:58:22,735 - C3,0 C3 1122122.0000 - Spherical aberration +2026-06-24 06:58:22,735 - C3,2 4*S3 2834.9260 351.66 Axial star aberration +2026-06-24 06:58:22,735 - C3,4 A3 -5432.2280 354.49 4-fold astigmatism +2026-06-24 06:58:22,735 - C4,1 4*B4 -481127.0940 342.44 Axial coma(4th) +2026-06-24 06:58:22,735 - C4,3 4*D4 -401575.4690 112.95 3-lobe aberration +2026-06-24 06:58:22,735 - C4,5 A4 -145142.8750 105.24 5-fold astigmatism +2026-06-24 06:58:22,735 - C5,0 C5 -149249216.0000 - Spherical aberration (5th) +2026-06-24 06:58:22,735 - C5,2 6*S5 -9506572.0000 6.13 Axial star aberration(5th) +2026-06-24 06:58:22,735 - C5,4 6*R5 -19155148.0000 290.68 4-lobe aberration +2026-06-24 06:58:22,735 - C5,6 A5 -5630734.5000 117.03 6-fold astigmatism +2026-06-24 06:58:22,739 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:58:22,739 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:58:22,739 - Creating 5 new probe modes from the major mode +2026-06-24 06:58:22,739 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:58:23,026 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:58:23,027 - Orthogonalizing 6 pmodes +2026-06-24 06:58:23,030 - Sorting 6 pmodes by their intensities +2026-06-24 06:58:23,031 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:58:23,031 - sum(|probe_data|**2) = 763.84, while meas_total_ints (min, mean, max) = (753.8368, 763.8416, 768.8050) +2026-06-24 06:58:23,032 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:58:23,032 - +2026-06-24 06:58:23,032 - ### Initializing probe positions ### +2026-06-24 06:58:23,032 - Loading probe positions from source = 'simu' +2026-06-24 06:58:23,032 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:58:23,032 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.3740, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:58:23,032 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:58:23,034 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:58:23,034 - crop_pos 1st and last px coords (y,x) = ([16, 16], [44, 44]) +2026-06-24 06:58:23,034 - crop_pos extent (Ang) = [5.6 5.6] +2026-06-24 06:58:23,034 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:58:23,034 - +2026-06-24 06:58:23,034 - ### Initializing object ### +2026-06-24 06:58:23,034 - Loading object from source = 'simu' +2026-06-24 06:58:23,034 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:58:23,036 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:58:23,036 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 188, 188) +2026-06-24 06:58:23,036 - object extent (Z, Y, X) (Ang) = [20. 37.6 37.6] +2026-06-24 06:58:23,036 - +2026-06-24 06:58:23,036 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:58:23,036 - omode_occu (omode) = float32, (1,) +2026-06-24 06:58:23,036 - +2026-06-24 06:58:23,036 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:58:23,036 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 06:58:23,037 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:58:23,037 - +2026-06-24 06:58:23,037 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:58:23,037 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:58:23,037 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:58:23,037 - +2026-06-24 06:58:23,037 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:58:23,037 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:58:23,037 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:58:23,037 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:58:23,037 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:58:23,037 - crop positions (yx_min=[16 16], yx_max=[172 172]) are well contained inside object canvas (Ny,Nx) = (188, 188). +2026-06-24 06:58:23,037 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:58:23,037 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:58:23,037 - +2026-06-24 06:58:23,037 - ### Collecting reconstruction provenance ### +2026-06-24 06:58:23,038 - Reconstruction provenance is collected and initialized. +2026-06-24 06:58:23,038 - +2026-06-24 06:58:23,038 - ### Initializing loss function ### +2026-06-24 06:58:23,038 - Active loss types: +2026-06-24 06:58:23,038 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:58:23,038 - +2026-06-24 06:58:23,038 - ### Initializing constraint function ### +2026-06-24 06:58:23,038 - Active constraint types: +2026-06-24 06:58:23,038 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:58:23,038 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:58:23,038 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:58:23,038 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:58:23,038 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:58:23,038 - +2026-06-24 06:58:23,038 - ### Done initializing PtyRADSolver ### +2026-06-24 06:58:23,038 - +2026-06-24 06:58:23,167 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:58:23,167 - +2026-06-24 06:58:23,167 - ### Initializing PtychoModel model ### +2026-06-24 06:58:23,239 - ### PtychoModel optimizable variables ### +2026-06-24 06:58:23,239 - obja : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:58:23,239 - objp : torch.Size([1, 1, 188, 188]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:58:23,239 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:58:23,239 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:58:23,239 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:58:23,239 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:58:23,239 - +2026-06-24 06:58:23,239 - ### Optimizable variables statitsics ### +2026-06-24 06:58:23,239 - Total measurement values : 4,194,304 +2026-06-24 06:58:23,239 - Total optimizing variables: 267,808 +2026-06-24 06:58:23,239 - Overdetermined ratio : 15.66 +2026-06-24 06:58:23,239 - +2026-06-24 06:58:23,239 - ### Model behavior ### +2026-06-24 06:58:23,239 - Tilt propagator : False +2026-06-24 06:58:23,239 - Change slice thickness : False +2026-06-24 06:58:23,239 - Detector blur : False +2026-06-24 06:58:23,239 - Preload data : True +2026-06-24 06:58:23,239 - On-the-fly meas padding : False +2026-06-24 06:58:23,239 - On-the-fly meas resample : False +2026-06-24 06:58:23,239 - On-the-fly simu match mode: None +2026-06-24 06:58:23,239 - +2026-06-24 06:58:23,282 - ### Done initializing PtychoModel model ### +2026-06-24 06:58:23,282 - +2026-06-24 06:58:23,282 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:58:23,282 - +2026-06-24 06:58:23,282 - ### Generating indices, batches, and output_path ### +2026-06-24 06:58:23,284 - d90 = 61.000 px or 12.200 Ang +2026-06-24 06:58:23,284 - Selecting indices with the 'full' mode +2026-06-24 06:58:23,743 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:58:23,819 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:58:23,819 - Original recon_dir_affixes = ['default'] +2026-06-24 06:58:23,819 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:58:23,825 - Path corrected for compatibility: +2026-06-24 06:58:23,825 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C32_2.83e+03_phi32_352_C34_-5.43e+03_phi34_354_C41_-4.81e+05_phi41_342_C43_-4.02e+05_phi43_113_C45_-1.45e+05_phi45_105_C50_-1.49e+08_C52_-9.51e+06_phi52_6.13_C54_-1.92e+07_phi54_291_C56_-5.63e+06_phi56_117 +2026-06-24 06:58:23,825 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117 +2026-06-24 06:58:23,826 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117' is generated! +2026-06-24 06:58:23,978 - +2026-06-24 06:58:23,979 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/20260624_065823_ptyrad_log.txt ### +2026-06-24 06:58:23,979 - +2026-06-24 06:58:23,980 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:58:23,980 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:58:23,980 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:58:25,165 - Iter: 1, Total Loss: 0.8560, loss_single: 0.8560, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:58:25,202 - Iter: 2, Total Loss: 0.8354, loss_single: 0.8354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:58:25,237 - Iter: 3, Total Loss: 0.8194, loss_single: 0.8194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,272 - Iter: 4, Total Loss: 0.8057, loss_single: 0.8057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,311 - Iter: 5, Total Loss: 0.7925, loss_single: 0.7925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,346 - Iter: 6, Total Loss: 0.7796, loss_single: 0.7796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,381 - Iter: 7, Total Loss: 0.7654, loss_single: 0.7654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,416 - Iter: 8, Total Loss: 0.7496, loss_single: 0.7496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,451 - Iter: 9, Total Loss: 0.7332, loss_single: 0.7332, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,487 - Iter: 10, Total Loss: 0.7185, loss_single: 0.7185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:58:25,522 - Iter: 11, Total Loss: 0.7044, loss_single: 0.7044, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,557 - Iter: 12, Total Loss: 0.6895, loss_single: 0.6895, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,592 - Iter: 13, Total Loss: 0.6745, loss_single: 0.6745, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,627 - Iter: 14, Total Loss: 0.6598, loss_single: 0.6598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,662 - Iter: 15, Total Loss: 0.6456, loss_single: 0.6456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,697 - Iter: 16, Total Loss: 0.6336, loss_single: 0.6336, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,731 - Iter: 17, Total Loss: 0.6233, loss_single: 0.6233, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,766 - Iter: 18, Total Loss: 0.6121, loss_single: 0.6121, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,801 - Iter: 19, Total Loss: 0.6001, loss_single: 0.6001, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,836 - Iter: 20, Total Loss: 0.5885, loss_single: 0.5885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,871 - Iter: 21, Total Loss: 0.5772, loss_single: 0.5772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,906 - Iter: 22, Total Loss: 0.5653, loss_single: 0.5653, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:25,941 - Iter: 23, Total Loss: 0.5532, loss_single: 0.5532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:25,976 - Iter: 24, Total Loss: 0.5411, loss_single: 0.5411, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,010 - Iter: 25, Total Loss: 0.5290, loss_single: 0.5290, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,045 - Iter: 26, Total Loss: 0.5178, loss_single: 0.5178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,080 - Iter: 27, Total Loss: 0.5065, loss_single: 0.5065, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,115 - Iter: 28, Total Loss: 0.4946, loss_single: 0.4946, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,150 - Iter: 29, Total Loss: 0.4828, loss_single: 0.4828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,184 - Iter: 30, Total Loss: 0.4716, loss_single: 0.4716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,219 - Iter: 31, Total Loss: 0.4617, loss_single: 0.4617, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,254 - Iter: 32, Total Loss: 0.4524, loss_single: 0.4524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,289 - Iter: 33, Total Loss: 0.4424, loss_single: 0.4424, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,323 - Iter: 34, Total Loss: 0.4313, loss_single: 0.4313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,358 - Iter: 35, Total Loss: 0.4208, loss_single: 0.4208, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,393 - Iter: 36, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,428 - Iter: 37, Total Loss: 0.4020, loss_single: 0.4020, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,463 - Iter: 38, Total Loss: 0.3941, loss_single: 0.3941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,497 - Iter: 39, Total Loss: 0.3868, loss_single: 0.3868, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,532 - Iter: 40, Total Loss: 0.3795, loss_single: 0.3795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,568 - Iter: 41, Total Loss: 0.3730, loss_single: 0.3730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,603 - Iter: 42, Total Loss: 0.3657, loss_single: 0.3657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,638 - Iter: 43, Total Loss: 0.3606, loss_single: 0.3606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,673 - Iter: 44, Total Loss: 0.3559, loss_single: 0.3559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,707 - Iter: 45, Total Loss: 0.3497, loss_single: 0.3497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,750 - Iter: 46, Total Loss: 0.3442, loss_single: 0.3442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.042 sec +2026-06-24 06:58:26,785 - Iter: 47, Total Loss: 0.3393, loss_single: 0.3393, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,820 - Iter: 48, Total Loss: 0.3345, loss_single: 0.3345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,855 - Iter: 49, Total Loss: 0.3294, loss_single: 0.3294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,890 - Iter: 50, Total Loss: 0.3240, loss_single: 0.3240, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,925 - Iter: 51, Total Loss: 0.3192, loss_single: 0.3192, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:26,960 - Iter: 52, Total Loss: 0.3145, loss_single: 0.3145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:26,995 - Iter: 53, Total Loss: 0.3098, loss_single: 0.3098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:27,030 - Iter: 54, Total Loss: 0.3057, loss_single: 0.3057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:27,065 - Iter: 55, Total Loss: 0.3019, loss_single: 0.3019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:27,100 - Iter: 56, Total Loss: 0.2981, loss_single: 0.2981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:27,135 - Iter: 57, Total Loss: 0.2943, loss_single: 0.2943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:27,170 - Iter: 58, Total Loss: 0.2913, loss_single: 0.2913, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:27,205 - 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Iter: 95, Total Loss: 0.2500, loss_single: 0.2500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:28,506 - Iter: 96, Total Loss: 0.2497, loss_single: 0.2497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:28,541 - Iter: 97, Total Loss: 0.2495, loss_single: 0.2495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:58:28,576 - Iter: 98, Total Loss: 0.2493, loss_single: 0.2493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:28,610 - Iter: 99, Total Loss: 0.2491, loss_single: 0.2491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:28,645 - Iter: 100, Total Loss: 0.2489, loss_single: 0.2489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 06:58:28,756 - Saving summary figures for iter 100 +2026-06-24 06:58:32,677 - ### Finished 100 iterations, averaged iter_t = 0.03869 with std = 0.040 ### +2026-06-24 06:58:32,677 - +2026-06-24 06:58:32,677 - ### The PtyRADSolver is finished in 9.510 sec ### +2026-06-24 06:58:32,678 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..a3551d3aec7483e13e155dbfaabd176767a33d11 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/simulation_data_aug3__sample_000032.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/simulation_data_aug3__sample_000032.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d59551b201c1cf1b77860b7e255a6ee7fcf168cd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032/c30_small__simulation_data_aug3__sample_000032_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-630_C12_-8.8_phi12_95.7_C21_362_phi21_199_C23_-120_phi23_220_C30_1.12e+06_C3.63e+06_phi56_117/simulation_data_aug3__sample_000032.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 24.3415584564209 + probe_aberrations: + C10: -629.5191040039062 + C12: -8.801835060119629 + C21: 362.43817138671875 + C23: -120.14838409423828 + C30: 1122122.0 + C32: 2834.926025390625 + C34: -5432.22802734375 + C41: -481127.09375 + C43: -401575.46875 + C45: -145142.875 + C50: -149249216.0 + C52: -9506572.0 + C54: -19155148.0 + C56: -5630734.5 + phi12: 95.71914529277245 + phi21: 198.50895705585546 + phi23: 219.81130620912808 + phi32: 351.6584092676028 + phi34: 354.4861349047448 + phi41: 342.44180664310096 + phi43: 112.95211554987566 + phi45: 105.2437621280852 + phi52: 6.127299098281793 + phi54: 290.6776334142719 + phi56: 117.03156214488166 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.37401965260505676 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000032_measurement.h5 + key: measurement + random_seed: 20262186 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000032 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug3__sample_000032 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/20260624_065908_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/20260624_065908_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c90cfee0c047c6d1e95fa1b853cbf4cf187799d3 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/20260624_065908_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 06:59:06,657 - ### PtyRAD LoggingManager configuration ### +2026-06-24 06:59:06,657 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 06:59:06,657 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 06:59:06,657 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 06:59:06,657 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 06:59:06,657 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 06:59:06,657 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 06:59:06,657 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 06:59:06,657 - +2026-06-24 06:59:06,764 - ### Initializing HuggingFace accelerator ### +2026-06-24 06:59:06,764 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 06:59:06,764 - Accelerator.num_process = 1 +2026-06-24 06:59:06,764 - Accelerator.mixed_precision = no +2026-06-24 06:59:06,775 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 06:59:06,775 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 06:59:06,775 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 06:59:06,775 - +2026-06-24 06:59:06,775 - ### System information ### +2026-06-24 06:59:06,775 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 06:59:06,775 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 06:59:06,775 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 06:59:06,776 - Machine: x86_64 +2026-06-24 06:59:06,776 - Processor: x86_64 +2026-06-24 06:59:06,776 - Available CPU cores: 8 +2026-06-24 06:59:06,776 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 06:59:06,776 - +2026-06-24 06:59:06,776 - ### GPU information ### +2026-06-24 06:59:06,776 - CUDA Available: True +2026-06-24 06:59:06,776 - CUDA Version: 13.0 +2026-06-24 06:59:06,776 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 06:59:06,776 - CUDA Compute Capability: ['8.0'] +2026-06-24 06:59:06,776 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 06:59:06,776 - In addition, Triton does not directly support Windows. +2026-06-24 06:59:06,776 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 06:59:06,803 - MIG (Multi-Instance GPU) mode = False +2026-06-24 06:59:06,804 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 06:59:06,804 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 06:59:06,804 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 06:59:06,804 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 06:59:06,804 - +2026-06-24 06:59:06,804 - ### Python information ### +2026-06-24 06:59:06,806 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 06:59:06,806 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 06:59:06,806 - +2026-06-24 06:59:06,806 - ### Packages information ### +2026-06-24 06:59:06,807 - Numpy Version (metadata): 2.4.6 +2026-06-24 06:59:06,807 - PyTorch Version (metadata): 2.12.0 +2026-06-24 06:59:06,808 - Optuna Version (metadata): 4.9.0 +2026-06-24 06:59:06,809 - Accelerate Version (metadata): 1.13.0 +2026-06-24 06:59:06,809 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 06:59:06,809 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 06:59:06,809 - +2026-06-24 06:59:06,809 - ### Loading params file ### +2026-06-24 06:59:06,809 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000035.yaml +2026-06-24 06:59:06,816 - validate = True: Filling defaults and validating the params file... +2026-06-24 06:59:06,817 - Success! Params file validated and defaults applied. +2026-06-24 06:59:06,817 - +2026-06-24 06:59:06,817 - ### Setting GPU Device ### +2026-06-24 06:59:06,817 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 06:59:06,817 - +2026-06-24 06:59:06,817 - Random seed: 20262189 provided by params file +2026-06-24 06:59:06,817 - ### Initializing Initializer ### +2026-06-24 06:59:06,818 - init_params are displayed below: +2026-06-24 06:59:06,818 - random_seed: 20262189 +2026-06-24 06:59:06,818 - probe_illum_type: electron +2026-06-24 06:59:06,818 - probe_kv: 120.0 +2026-06-24 06:59:06,818 - probe_conv_angle: 20.964792251586914 +2026-06-24 06:59:06,818 - probe_aberrations: {'C10': -677.21, 'C12': 21.861, 'phi12': 172.928, 'C21': -393.688, 'phi21': 72.55, 'C23': -866.397, 'phi23': 219.375, 'C30': 2547562.75, 'C32': -9569.777, 'phi32': 330.806, 'C34': -5646.589, 'phi34': 140.15, 'C41': -15074.83, 'phi41': 111.536, 'C43': 396160.594, 'phi43': 143.437, 'C45': 993.643, 'phi45': 348.162, 'C50': -234957344.0, 'C52': -832321.125, 'phi52': 172.788, 'C54': 5693490.5, 'phi54': 309.659, 'C56': 5803275.0, 'phi56': 184.058} +2026-06-24 06:59:06,818 - beam_kev: None +2026-06-24 06:59:06,818 - probe_dRn: None +2026-06-24 06:59:06,818 - probe_Rn: None +2026-06-24 06:59:06,818 - probe_D_H: None +2026-06-24 06:59:06,818 - probe_D_FZP: None +2026-06-24 06:59:06,818 - probe_Ls: None +2026-06-24 06:59:06,818 - meas_Npix: 128 +2026-06-24 06:59:06,818 - pos_N_scans: 256 +2026-06-24 06:59:06,818 - pos_N_scan_slow: 16 +2026-06-24 06:59:06,818 - pos_N_scan_fast: 16 +2026-06-24 06:59:06,818 - pos_scan_step_size: 0.4174773693084717 +2026-06-24 06:59:06,818 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 06:59:06,818 - probe_pmode_max: 6 +2026-06-24 06:59:06,818 - probe_pmode_init_pows: [0.02] +2026-06-24 06:59:06,818 - obj_omode_max: 1 +2026-06-24 06:59:06,818 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 06:59:06,818 - obj_Nlayer: 1 +2026-06-24 06:59:06,818 - obj_slice_thickness: 20.0 +2026-06-24 06:59:06,818 - simu_Npix: None +2026-06-24 06:59:06,818 - simu_match_mode: None +2026-06-24 06:59:06,818 - meas_permute: None +2026-06-24 06:59:06,818 - meas_reshape: [256, 128, 128] +2026-06-24 06:59:06,818 - meas_flipT: [0, 0, 0] +2026-06-24 06:59:06,818 - meas_crop: None +2026-06-24 06:59:06,818 - meas_pad: None +2026-06-24 06:59:06,818 - meas_resample: None +2026-06-24 06:59:06,818 - meas_add_source_size: None +2026-06-24 06:59:06,818 - meas_add_detector_blur: None +2026-06-24 06:59:06,818 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 06:59:06,819 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 06:59:06,819 - meas_add_poisson_noise: None +2026-06-24 06:59:06,819 - meas_export: None +2026-06-24 06:59:06,819 - probe_permute: None +2026-06-24 06:59:06,819 - probe_z_shift: None +2026-06-24 06:59:06,819 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 06:59:06,819 - pos_scan_flipT: None +2026-06-24 06:59:06,819 - pos_scan_affine: None +2026-06-24 06:59:06,819 - pos_scan_rand_std: 0.15 +2026-06-24 06:59:06,819 - obj_z_crop: None +2026-06-24 06:59:06,819 - obj_z_pad: None +2026-06-24 06:59:06,819 - obj_z_resample: None +2026-06-24 06:59:06,819 - meas_source: file +2026-06-24 06:59:06,819 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000035_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 06:59:06,819 - probe_source: simu +2026-06-24 06:59:06,819 - probe_params: None +2026-06-24 06:59:06,819 - pos_source: simu +2026-06-24 06:59:06,819 - pos_params: None +2026-06-24 06:59:06,819 - obj_source: simu +2026-06-24 06:59:06,819 - obj_params: None +2026-06-24 06:59:06,819 - tilt_source: simu +2026-06-24 06:59:06,819 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 06:59:06,819 - +2026-06-24 06:59:06,819 - ### Initializing cache ### +2026-06-24 06:59:06,819 - use_cached_obj = False +2026-06-24 06:59:06,819 - use_cached_probe = False +2026-06-24 06:59:06,819 - use_cached_pos = False +2026-06-24 06:59:06,819 - +2026-06-24 06:59:06,819 - ### Initializing measurements ### +2026-06-24 06:59:06,819 - Loading measurements from source = 'file' +2026-06-24 06:59:06,819 - Detected measurement file type = '.h5' +2026-06-24 06:59:06,899 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 06:59:06,899 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 06:59:06,901 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0017) +2026-06-24 06:59:06,901 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 06:59:06,901 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 06:59:06,903 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:59:06,903 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 06:59:06,903 - Normalizing by max of the 2D mean pattern intensity: 0.0012223043 +2026-06-24 06:59:06,904 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 06:59:06,905 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0498, 1.3884) +2026-06-24 06:59:06,906 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 06:59:06,907 - Pattern total int. statistics (min, mean, max) = (812.2263, 816.6282, 821.4991), with min/max = 98.9% +2026-06-24 06:59:06,908 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0498, 1.3884) +2026-06-24 06:59:06,908 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 06:59:06,908 - +2026-06-24 06:59:06,908 - ### Setting up calibration ### +2026-06-24 06:59:06,908 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 06:59:06,908 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 06:59:06,909 - Radius of fitted bright field disk (RBF) = 15.94 px with meas_Npix = 128 +2026-06-24 06:59:06,909 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2490 +2026-06-24 06:59:06,909 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 06:59:06,909 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 06:59:07,130 - Initial guess: center=(63.63, 63.64), radius=15.94, Gaussian blur std=0.50 +2026-06-24 06:59:07,144 - Final fit: center=(63.63, 63.64), radius=15.94, Gaussian blur std=0.74 +2026-06-24 06:59:07,144 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 16.02 px with Npix = 128 +2026-06-24 06:59:07,144 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 06:59:07,144 - +2026-06-24 06:59:07,144 - ### Setting init_variables dict ### +2026-06-24 06:59:07,144 - Derived values given input init_params: +2026-06-24 06:59:07,144 - kv = 120.0 kV +2026-06-24 06:59:07,144 - wavelength = 0.0335 Ang +2026-06-24 06:59:07,144 - conv_angle = 20.964792251586914 mrad +2026-06-24 06:59:07,144 - Npix = 128 px +2026-06-24 06:59:07,144 - dk = 0.0391 Ang^-1 +2026-06-24 06:59:07,144 - kMax = 2.5000 Ang^-1 +2026-06-24 06:59:07,144 - da = 1.3083 mrad +2026-06-24 06:59:07,144 - angleMax = 83.7304 mrad +2026-06-24 06:59:07,144 - RBF = 16.0246 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 06:59:07,144 - n_alpha = 3.9939 (# conv_angle) +2026-06-24 06:59:07,145 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:59:07,145 - Rayleigh-limited resolution = 0.9745 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:59:07,145 - Real space probe extent = 25.6000 Ang +2026-06-24 06:59:07,145 - +2026-06-24 06:59:07,145 - ### Initializing probe ### +2026-06-24 06:59:07,145 - Loading probe from source = 'simu' +2026-06-24 06:59:07,145 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 06:59:07,145 - Start simulating STEM probe +2026-06-24 06:59:07,145 - kv = 120.0 kV +2026-06-24 06:59:07,145 - wavelength = 0.0335 Ang +2026-06-24 06:59:07,145 - conv_angle = 20.964792251586914 mrad +2026-06-24 06:59:07,145 - Npix = 128 px +2026-06-24 06:59:07,145 - dk = 0.0391 Ang^-1 +2026-06-24 06:59:07,145 - kMax = 2.5000 Ang^-1 +2026-06-24 06:59:07,145 - alpha_max = 83.7304 mrad +2026-06-24 06:59:07,145 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 06:59:07,145 - Rayleigh-limited resolution = 0.9745 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 06:59:07,145 - Real space probe extent = 25.6000 Ang +2026-06-24 06:59:07,145 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 06:59:07,145 - ------------------------------------------------------------------------------------- +2026-06-24 06:59:07,145 - C1,0 C1 -677.2100 - Defocus (C10 = -df) +2026-06-24 06:59:07,145 - C1,2 A1 21.8610 172.93 2-fold astigmatism +2026-06-24 06:59:07,145 - C2,1 3*B2 -393.6880 72.55 Axial coma +2026-06-24 06:59:07,145 - C2,3 A2 -866.3970 219.38 3-fold astigmatism +2026-06-24 06:59:07,145 - C3,0 C3 2547562.7500 - Spherical aberration +2026-06-24 06:59:07,146 - C3,2 4*S3 -9569.7770 330.81 Axial star aberration +2026-06-24 06:59:07,146 - C3,4 A3 -5646.5890 140.15 4-fold astigmatism +2026-06-24 06:59:07,146 - C4,1 4*B4 -15074.8300 111.54 Axial coma(4th) +2026-06-24 06:59:07,146 - C4,3 4*D4 396160.5940 143.44 3-lobe aberration +2026-06-24 06:59:07,146 - C4,5 A4 993.6430 348.16 5-fold astigmatism +2026-06-24 06:59:07,146 - C5,0 C5 -234957344.0000 - Spherical aberration (5th) +2026-06-24 06:59:07,146 - C5,2 6*S5 -832321.1250 172.79 Axial star aberration(5th) +2026-06-24 06:59:07,146 - C5,4 6*R5 5693490.5000 309.66 4-lobe aberration +2026-06-24 06:59:07,146 - C5,6 A5 5803275.0000 184.06 6-fold astigmatism +2026-06-24 06:59:07,148 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 06:59:07,149 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 06:59:07,149 - Creating 5 new probe modes from the major mode +2026-06-24 06:59:07,149 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 06:59:07,379 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 06:59:07,380 - Orthogonalizing 6 pmodes +2026-06-24 06:59:07,389 - Sorting 6 pmodes by their intensities +2026-06-24 06:59:07,389 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 06:59:07,390 - sum(|probe_data|**2) = 816.63, while meas_total_ints (min, mean, max) = (812.2263, 816.6282, 821.4991) +2026-06-24 06:59:07,390 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 06:59:07,390 - +2026-06-24 06:59:07,390 - ### Initializing probe positions ### +2026-06-24 06:59:07,390 - Loading probe positions from source = 'simu' +2026-06-24 06:59:07,390 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 06:59:07,390 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4175, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 06:59:07,390 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 06:59:07,392 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 06:59:07,392 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 06:59:07,392 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 06:59:07,392 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 06:59:07,392 - +2026-06-24 06:59:07,393 - ### Initializing object ### +2026-06-24 06:59:07,393 - Loading object from source = 'simu' +2026-06-24 06:59:07,393 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 06:59:07,394 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 06:59:07,394 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 192, 192) +2026-06-24 06:59:07,394 - object extent (Z, Y, X) (Ang) = [20. 38.4 38.4] +2026-06-24 06:59:07,394 - +2026-06-24 06:59:07,394 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 06:59:07,394 - omode_occu (omode) = float32, (1,) +2026-06-24 06:59:07,394 - +2026-06-24 06:59:07,394 - ### Initializing H (Fresnel propagator) ### +2026-06-24 06:59:07,394 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 06:59:07,395 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 06:59:07,395 - +2026-06-24 06:59:07,395 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 06:59:07,395 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 06:59:07,395 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 06:59:07,395 - +2026-06-24 06:59:07,395 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 06:59:07,395 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 06:59:07,395 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 06:59:07,395 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 06:59:07,395 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 06:59:07,396 - crop positions (yx_min=[16 16], yx_max=[176 176]) are well contained inside object canvas (Ny,Nx) = (192, 192). +2026-06-24 06:59:07,396 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 06:59:07,396 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 06:59:07,396 - +2026-06-24 06:59:07,396 - ### Collecting reconstruction provenance ### +2026-06-24 06:59:07,396 - Reconstruction provenance is collected and initialized. +2026-06-24 06:59:07,396 - +2026-06-24 06:59:07,396 - ### Initializing loss function ### +2026-06-24 06:59:07,396 - Active loss types: +2026-06-24 06:59:07,396 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 06:59:07,396 - +2026-06-24 06:59:07,396 - ### Initializing constraint function ### +2026-06-24 06:59:07,396 - Active constraint types: +2026-06-24 06:59:07,396 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:59:07,396 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 06:59:07,396 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 06:59:07,396 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 06:59:07,396 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 06:59:07,396 - +2026-06-24 06:59:07,396 - ### Done initializing PtyRADSolver ### +2026-06-24 06:59:07,396 - +2026-06-24 06:59:07,520 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 06:59:07,520 - +2026-06-24 06:59:07,521 - ### Initializing PtychoModel model ### +2026-06-24 06:59:07,591 - ### PtychoModel optimizable variables ### +2026-06-24 06:59:07,591 - obja : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:59:07,591 - objp : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:59:07,591 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:59:07,591 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 06:59:07,591 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 06:59:07,591 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 06:59:07,591 - +2026-06-24 06:59:07,591 - ### Optimizable variables statitsics ### +2026-06-24 06:59:07,592 - Total measurement values : 4,194,304 +2026-06-24 06:59:07,592 - Total optimizing variables: 270,848 +2026-06-24 06:59:07,592 - Overdetermined ratio : 15.49 +2026-06-24 06:59:07,592 - +2026-06-24 06:59:07,592 - ### Model behavior ### +2026-06-24 06:59:07,592 - Tilt propagator : False +2026-06-24 06:59:07,592 - Change slice thickness : False +2026-06-24 06:59:07,592 - Detector blur : False +2026-06-24 06:59:07,592 - Preload data : True +2026-06-24 06:59:07,592 - On-the-fly meas padding : False +2026-06-24 06:59:07,592 - On-the-fly meas resample : False +2026-06-24 06:59:07,592 - On-the-fly simu match mode: None +2026-06-24 06:59:07,592 - +2026-06-24 06:59:07,633 - ### Done initializing PtychoModel model ### +2026-06-24 06:59:07,634 - +2026-06-24 06:59:07,634 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 06:59:07,634 - +2026-06-24 06:59:07,634 - ### Generating indices, batches, and output_path ### +2026-06-24 06:59:07,635 - d90 = 55.000 px or 11.000 Ang +2026-06-24 06:59:07,635 - Selecting indices with the 'full' mode +2026-06-24 06:59:08,099 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 06:59:08,171 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 06:59:08,171 - Original recon_dir_affixes = ['default'] +2026-06-24 06:59:08,171 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 06:59:08,178 - Path corrected for compatibility: +2026-06-24 06:59:08,178 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C32_-9.57e+03_phi32_331_C34_-5.65e+03_phi34_140_C41_-1.51e+04_phi41_112_C43_3.96e+05_phi43_143_C45_994_phi45_348_C50_-2.35e+08_C52_-8.32e+05_phi52_173_C54_5.69e+06_phi54_310_C56_5.8e+06_phi56_184 +2026-06-24 06:59:08,178 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184 +2026-06-24 06:59:08,179 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184' is generated! +2026-06-24 06:59:08,325 - +2026-06-24 06:59:08,326 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/20260624_065908_ptyrad_log.txt ### +2026-06-24 06:59:08,326 - +2026-06-24 06:59:08,327 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 06:59:08,327 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 06:59:08,327 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 06:59:09,518 - Iter: 1, Total Loss: 0.6739, loss_single: 0.6739, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 06:59:09,556 - Iter: 2, Total Loss: 0.6496, loss_single: 0.6496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 06:59:09,592 - Iter: 3, Total Loss: 0.6300, loss_single: 0.6300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,628 - Iter: 4, Total Loss: 0.6114, loss_single: 0.6114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:09,663 - Iter: 5, Total Loss: 0.5954, loss_single: 0.5954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,699 - Iter: 6, Total Loss: 0.5807, loss_single: 0.5807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,735 - Iter: 7, Total Loss: 0.5632, loss_single: 0.5632, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:09,770 - Iter: 8, Total Loss: 0.5449, loss_single: 0.5449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,806 - Iter: 9, Total Loss: 0.5270, loss_single: 0.5270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,842 - Iter: 10, Total Loss: 0.5109, loss_single: 0.5109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:09,878 - Iter: 11, Total Loss: 0.4958, loss_single: 0.4958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,914 - Iter: 12, Total Loss: 0.4821, loss_single: 0.4821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,949 - Iter: 13, Total Loss: 0.4684, loss_single: 0.4684, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:09,985 - Iter: 14, Total Loss: 0.4539, loss_single: 0.4539, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,021 - Iter: 15, Total Loss: 0.4398, loss_single: 0.4398, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,057 - Iter: 16, Total Loss: 0.4252, loss_single: 0.4252, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,093 - Iter: 17, Total Loss: 0.4109, loss_single: 0.4109, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,129 - Iter: 18, Total Loss: 0.3979, loss_single: 0.3979, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,165 - Iter: 19, Total Loss: 0.3864, loss_single: 0.3864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,200 - Iter: 20, Total Loss: 0.3758, loss_single: 0.3758, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,236 - Iter: 21, Total Loss: 0.3666, loss_single: 0.3666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,272 - Iter: 22, Total Loss: 0.3565, loss_single: 0.3565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,307 - Iter: 23, Total Loss: 0.3474, loss_single: 0.3474, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,343 - Iter: 24, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,404 - Iter: 25, Total Loss: 0.3307, loss_single: 0.3307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,443 - Iter: 26, Total Loss: 0.3219, loss_single: 0.3219, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 06:59:10,479 - Iter: 27, Total Loss: 0.3140, loss_single: 0.3140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,515 - Iter: 28, Total Loss: 0.3057, loss_single: 0.3057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,550 - Iter: 29, Total Loss: 0.2971, loss_single: 0.2971, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,586 - Iter: 30, Total Loss: 0.2902, loss_single: 0.2902, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,622 - Iter: 31, Total Loss: 0.2843, loss_single: 0.2843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:10,657 - Iter: 32, Total Loss: 0.2779, loss_single: 0.2779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,693 - Iter: 33, Total Loss: 0.2719, loss_single: 0.2719, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,729 - Iter: 34, Total Loss: 0.2660, loss_single: 0.2660, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,764 - Iter: 35, Total Loss: 0.2603, loss_single: 0.2603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,800 - Iter: 36, Total Loss: 0.2550, loss_single: 0.2550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,835 - Iter: 37, Total Loss: 0.2498, loss_single: 0.2498, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,871 - Iter: 38, Total Loss: 0.2452, loss_single: 0.2452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,907 - Iter: 39, Total Loss: 0.2405, loss_single: 0.2405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,942 - Iter: 40, Total Loss: 0.2354, loss_single: 0.2354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:10,981 - Iter: 41, Total Loss: 0.2316, loss_single: 0.2316, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,017 - Iter: 42, Total Loss: 0.2293, loss_single: 0.2293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,053 - Iter: 43, Total Loss: 0.2277, loss_single: 0.2277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,089 - Iter: 44, Total Loss: 0.2262, loss_single: 0.2262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,124 - Iter: 45, Total Loss: 0.2242, loss_single: 0.2242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,160 - Iter: 46, Total Loss: 0.2221, loss_single: 0.2221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,195 - Iter: 47, Total Loss: 0.2202, loss_single: 0.2202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,231 - Iter: 48, Total Loss: 0.2187, loss_single: 0.2187, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,267 - Iter: 49, Total Loss: 0.2172, loss_single: 0.2172, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,302 - Iter: 50, Total Loss: 0.2159, loss_single: 0.2159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,338 - Iter: 51, Total Loss: 0.2148, loss_single: 0.2148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,373 - Iter: 52, Total Loss: 0.2137, loss_single: 0.2137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,409 - Iter: 53, Total Loss: 0.2129, loss_single: 0.2129, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,445 - Iter: 54, Total Loss: 0.2122, loss_single: 0.2122, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,480 - Iter: 55, Total Loss: 0.2115, loss_single: 0.2115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,517 - Iter: 56, Total Loss: 0.2110, loss_single: 0.2110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 06:59:11,552 - Iter: 57, Total Loss: 0.2105, loss_single: 0.2105, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 06:59:11,588 - Iter: 58, Total Loss: 0.2100, loss_single: 0.2100, loss_poissn: 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/simulation_data_aug3__sample_000035.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 20.964792251586914 + probe_aberrations: + C10: -677.21044921875 + C12: 21.861135482788086 + C21: -393.68829345703125 + C23: -866.3973388671875 + C30: 2547562.75 + C32: -9569.77734375 + C34: -5646.58935546875 + C41: -15074.830078125 + C43: 396160.59375 + C45: 993.6426391601562 + C50: -234957344.0 + C52: -832321.125 + C54: 5693490.5 + C56: 5803275.0 + phi12: 172.92768563286663 + phi21: 72.54960683552595 + phi23: 219.3750347060827 + phi32: 330.8061149391207 + phi34: 140.14968976824548 + phi41: 111.53613537266197 + phi43: 143.4374969478795 + phi45: 348.16198078995996 + phi52: 172.7879536228265 + phi54: 309.6588930422774 + phi56: 184.05790235713096 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4174773693084717 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000035_measurement.h5 + key: measurement + random_seed: 20262189 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug3__sample_000035 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000035/c30_small__simulation_data_aug3__sample_000035_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_21.9_phi12_173_C21_-394_phi21_72.5_C23_-866_phi23_219_C30_2.55e+06_C3.8e+06_phi56_184/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306/20260624_070022_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..da58c073ff9c0c8e8ba52bdc603a21e4fbc0b591 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306/20260624_070022_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 07:00:20,867 - ### PtyRAD LoggingManager configuration ### +2026-06-24 07:00:20,867 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 07:00:20,867 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 07:00:20,867 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 07:00:20,867 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 07:00:20,868 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 07:00:20,868 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 07:00:20,868 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 07:00:20,868 - +2026-06-24 07:00:20,974 - ### Initializing HuggingFace accelerator ### +2026-06-24 07:00:20,974 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 07:00:20,974 - Accelerator.num_process = 1 +2026-06-24 07:00:20,974 - Accelerator.mixed_precision = no +2026-06-24 07:00:20,985 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 07:00:20,985 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 07:00:20,985 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 07:00:20,985 - +2026-06-24 07:00:20,985 - ### System information ### +2026-06-24 07:00:20,985 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 07:00:20,985 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 07:00:20,985 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 07:00:20,985 - Machine: x86_64 +2026-06-24 07:00:20,985 - Processor: x86_64 +2026-06-24 07:00:20,985 - Available CPU cores: 8 +2026-06-24 07:00:20,985 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 07:00:20,985 - +2026-06-24 07:00:20,985 - ### GPU information ### +2026-06-24 07:00:20,985 - CUDA Available: True +2026-06-24 07:00:20,985 - CUDA Version: 13.0 +2026-06-24 07:00:20,986 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 07:00:20,986 - CUDA Compute Capability: ['8.0'] +2026-06-24 07:00:20,986 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 07:00:20,986 - In addition, Triton does not directly support Windows. +2026-06-24 07:00:20,986 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 07:00:21,001 - MIG (Multi-Instance GPU) mode = False +2026-06-24 07:00:21,001 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 07:00:21,001 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 07:00:21,001 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 07:00:21,001 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 07:00:21,001 - +2026-06-24 07:00:21,001 - ### Python information ### +2026-06-24 07:00:21,003 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 07:00:21,003 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 07:00:21,003 - +2026-06-24 07:00:21,003 - ### Packages information ### +2026-06-24 07:00:21,003 - Numpy Version (metadata): 2.4.6 +2026-06-24 07:00:21,004 - PyTorch Version (metadata): 2.12.0 +2026-06-24 07:00:21,005 - Optuna Version (metadata): 4.9.0 +2026-06-24 07:00:21,006 - Accelerate Version (metadata): 1.13.0 +2026-06-24 07:00:21,006 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 07:00:21,006 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 07:00:21,006 - +2026-06-24 07:00:21,007 - ### Loading params file ### +2026-06-24 07:00:21,007 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000040.yaml +2026-06-24 07:00:21,013 - validate = True: Filling defaults and validating the params file... +2026-06-24 07:00:21,014 - Success! Params file validated and defaults applied. +2026-06-24 07:00:21,014 - +2026-06-24 07:00:21,014 - ### Setting GPU Device ### +2026-06-24 07:00:21,015 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 07:00:21,015 - +2026-06-24 07:00:21,015 - Random seed: 20262194 provided by params file +2026-06-24 07:00:21,015 - ### Initializing Initializer ### +2026-06-24 07:00:21,015 - init_params are displayed below: +2026-06-24 07:00:21,015 - random_seed: 20262194 +2026-06-24 07:00:21,015 - probe_illum_type: electron +2026-06-24 07:00:21,015 - probe_kv: 80.0 +2026-06-24 07:00:21,015 - probe_conv_angle: 14.6714506149292 +2026-06-24 07:00:21,015 - probe_aberrations: {'C10': -353.53, 'C12': -22.922, 'phi12': 53.469, 'C21': -525.903, 'phi21': 58.762, 'C23': 962.106, 'phi23': 309.502, 'C30': 3766869.5, 'C32': 4294.09, 'phi32': 105.736, 'C34': -5434.264, 'phi34': 0.046, 'C41': 95421.344, 'phi41': 262.906, 'C43': -200856.5, 'phi43': 65.396, 'C45': 104123.375, 'phi45': 284.257, 'C50': -269852000.0, 'C52': -1606306.375, 'phi52': 252.336, 'C54': -8147864.0, 'phi54': 114.367, 'C56': -13579540.0, 'phi56': 305.55} +2026-06-24 07:00:21,015 - beam_kev: None +2026-06-24 07:00:21,015 - probe_dRn: None +2026-06-24 07:00:21,015 - probe_Rn: None +2026-06-24 07:00:21,015 - probe_D_H: None +2026-06-24 07:00:21,015 - probe_D_FZP: None +2026-06-24 07:00:21,015 - probe_Ls: None +2026-06-24 07:00:21,015 - meas_Npix: 128 +2026-06-24 07:00:21,015 - pos_N_scans: 256 +2026-06-24 07:00:21,015 - pos_N_scan_slow: 16 +2026-06-24 07:00:21,015 - pos_N_scan_fast: 16 +2026-06-24 07:00:21,016 - pos_scan_step_size: 0.43743759393692017 +2026-06-24 07:00:21,016 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 07:00:21,016 - probe_pmode_max: 6 +2026-06-24 07:00:21,016 - probe_pmode_init_pows: [0.02] +2026-06-24 07:00:21,016 - obj_omode_max: 1 +2026-06-24 07:00:21,016 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 07:00:21,016 - obj_Nlayer: 1 +2026-06-24 07:00:21,016 - obj_slice_thickness: 20.0 +2026-06-24 07:00:21,016 - simu_Npix: None +2026-06-24 07:00:21,016 - simu_match_mode: None +2026-06-24 07:00:21,016 - meas_permute: None +2026-06-24 07:00:21,016 - meas_reshape: [256, 128, 128] +2026-06-24 07:00:21,016 - meas_flipT: [0, 0, 0] +2026-06-24 07:00:21,016 - meas_crop: None +2026-06-24 07:00:21,016 - meas_pad: None +2026-06-24 07:00:21,016 - meas_resample: None +2026-06-24 07:00:21,016 - meas_add_source_size: None +2026-06-24 07:00:21,016 - meas_add_detector_blur: None +2026-06-24 07:00:21,016 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 07:00:21,016 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 07:00:21,016 - meas_add_poisson_noise: None +2026-06-24 07:00:21,016 - meas_export: None +2026-06-24 07:00:21,016 - probe_permute: None +2026-06-24 07:00:21,016 - probe_z_shift: None +2026-06-24 07:00:21,016 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 07:00:21,016 - pos_scan_flipT: None +2026-06-24 07:00:21,016 - pos_scan_affine: None +2026-06-24 07:00:21,016 - pos_scan_rand_std: 0.15 +2026-06-24 07:00:21,016 - obj_z_crop: None +2026-06-24 07:00:21,016 - obj_z_pad: None +2026-06-24 07:00:21,016 - obj_z_resample: None +2026-06-24 07:00:21,016 - meas_source: file +2026-06-24 07:00:21,016 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000040_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 07:00:21,016 - probe_source: simu +2026-06-24 07:00:21,016 - probe_params: None +2026-06-24 07:00:21,016 - pos_source: simu +2026-06-24 07:00:21,016 - pos_params: None +2026-06-24 07:00:21,016 - obj_source: simu +2026-06-24 07:00:21,016 - obj_params: None +2026-06-24 07:00:21,016 - tilt_source: simu +2026-06-24 07:00:21,017 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 07:00:21,017 - +2026-06-24 07:00:21,017 - ### Initializing cache ### +2026-06-24 07:00:21,017 - use_cached_obj = False +2026-06-24 07:00:21,017 - use_cached_probe = False +2026-06-24 07:00:21,017 - use_cached_pos = False +2026-06-24 07:00:21,017 - +2026-06-24 07:00:21,017 - ### Initializing measurements ### +2026-06-24 07:00:21,017 - Loading measurements from source = 'file' +2026-06-24 07:00:21,017 - Detected measurement file type = '.h5' +2026-06-24 07:00:21,093 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 07:00:21,093 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 07:00:21,094 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0052) +2026-06-24 07:00:21,094 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 07:00:21,094 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 07:00:21,096 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:00:21,096 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 07:00:21,097 - Normalizing by max of the 2D mean pattern intensity: 0.0038469494 +2026-06-24 07:00:21,097 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 07:00:21,099 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0159, 1.3600) +2026-06-24 07:00:21,099 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:00:21,100 - Pattern total int. statistics (min, mean, max) = (255.7592, 259.7429, 263.4906), with min/max = 97.1% +2026-06-24 07:00:21,102 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0159, 1.3600) +2026-06-24 07:00:21,102 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 07:00:21,102 - +2026-06-24 07:00:21,102 - ### Setting up calibration ### +2026-06-24 07:00:21,102 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 07:00:21,102 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 07:00:21,102 - Radius of fitted bright field disk (RBF) = 8.92 px with meas_Npix = 128 +2026-06-24 07:00:21,102 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1394 +2026-06-24 07:00:21,102 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 07:00:21,102 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 07:00:21,322 - Initial guess: center=(63.59, 63.60), radius=8.92, Gaussian blur std=0.50 +2026-06-24 07:00:21,335 - Final fit: center=(63.59, 63.60), radius=8.92, Gaussian blur std=0.68 +2026-06-24 07:00:21,335 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 8.99 px with Npix = 128 +2026-06-24 07:00:21,335 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 07:00:21,335 - +2026-06-24 07:00:21,335 - ### Setting init_variables dict ### +2026-06-24 07:00:21,335 - Derived values given input init_params: +2026-06-24 07:00:21,335 - kv = 80.0 kV +2026-06-24 07:00:21,335 - wavelength = 0.0418 Ang +2026-06-24 07:00:21,335 - conv_angle = 14.6714506149292 mrad +2026-06-24 07:00:21,335 - Npix = 128 px +2026-06-24 07:00:21,335 - dk = 0.0391 Ang^-1 +2026-06-24 07:00:21,335 - kMax = 2.5000 Ang^-1 +2026-06-24 07:00:21,335 - da = 1.6311 mrad +2026-06-24 07:00:21,335 - angleMax = 104.3929 mrad +2026-06-24 07:00:21,336 - RBF = 8.9946 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 07:00:21,336 - n_alpha = 7.1154 (# conv_angle) +2026-06-24 07:00:21,336 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:00:21,336 - Rayleigh-limited resolution = 1.7362 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:00:21,336 - Real space probe extent = 25.6000 Ang +2026-06-24 07:00:21,336 - +2026-06-24 07:00:21,336 - ### Initializing probe ### +2026-06-24 07:00:21,336 - Loading probe from source = 'simu' +2026-06-24 07:00:21,336 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 07:00:21,336 - Start simulating STEM probe +2026-06-24 07:00:21,336 - kv = 80.0 kV +2026-06-24 07:00:21,336 - wavelength = 0.0418 Ang +2026-06-24 07:00:21,336 - conv_angle = 14.6714506149292 mrad +2026-06-24 07:00:21,336 - Npix = 128 px +2026-06-24 07:00:21,336 - dk = 0.0391 Ang^-1 +2026-06-24 07:00:21,336 - kMax = 2.5000 Ang^-1 +2026-06-24 07:00:21,336 - alpha_max = 104.3929 mrad +2026-06-24 07:00:21,336 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:00:21,336 - Rayleigh-limited resolution = 1.7362 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:00:21,336 - Real space probe extent = 25.6000 Ang +2026-06-24 07:00:21,336 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 07:00:21,336 - ------------------------------------------------------------------------------------- +2026-06-24 07:00:21,336 - C1,0 C1 -353.5300 - Defocus (C10 = -df) +2026-06-24 07:00:21,336 - C1,2 A1 -22.9220 53.47 2-fold astigmatism +2026-06-24 07:00:21,337 - C2,1 3*B2 -525.9030 58.76 Axial coma +2026-06-24 07:00:21,337 - C2,3 A2 962.1060 309.50 3-fold astigmatism +2026-06-24 07:00:21,337 - C3,0 C3 3766869.5000 - Spherical aberration +2026-06-24 07:00:21,337 - C3,2 4*S3 4294.0900 105.74 Axial star aberration +2026-06-24 07:00:21,337 - C3,4 A3 -5434.2640 0.05 4-fold astigmatism +2026-06-24 07:00:21,337 - C4,1 4*B4 95421.3440 262.91 Axial coma(4th) +2026-06-24 07:00:21,337 - C4,3 4*D4 -200856.5000 65.40 3-lobe aberration +2026-06-24 07:00:21,337 - C4,5 A4 104123.3750 284.26 5-fold astigmatism +2026-06-24 07:00:21,337 - C5,0 C5 -269852000.0000 - Spherical aberration (5th) +2026-06-24 07:00:21,337 - C5,2 6*S5 -1606306.3750 252.34 Axial star aberration(5th) +2026-06-24 07:00:21,337 - C5,4 6*R5 -8147864.0000 114.37 4-lobe aberration +2026-06-24 07:00:21,337 - C5,6 A5 -13579540.0000 305.55 6-fold astigmatism +2026-06-24 07:00:21,340 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 07:00:21,340 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 07:00:21,340 - Creating 5 new probe modes from the major mode +2026-06-24 07:00:21,340 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 07:00:21,442 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 07:00:21,443 - Orthogonalizing 6 pmodes +2026-06-24 07:00:21,445 - Sorting 6 pmodes by their intensities +2026-06-24 07:00:21,446 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 07:00:21,446 - sum(|probe_data|**2) = 259.74, while meas_total_ints (min, mean, max) = (255.7592, 259.7429, 263.4906) +2026-06-24 07:00:21,446 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 07:00:21,446 - +2026-06-24 07:00:21,446 - ### Initializing probe positions ### +2026-06-24 07:00:21,446 - Loading probe positions from source = 'simu' +2026-06-24 07:00:21,447 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 07:00:21,447 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4374, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 07:00:21,447 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 07:00:21,449 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 07:00:21,449 - crop_pos 1st and last px coords (y,x) = ([16, 16], [48, 48]) +2026-06-24 07:00:21,449 - crop_pos extent (Ang) = [6.8 6.8] +2026-06-24 07:00:21,449 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 07:00:21,449 - +2026-06-24 07:00:21,449 - ### Initializing object ### +2026-06-24 07:00:21,449 - Loading object from source = 'simu' +2026-06-24 07:00:21,449 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 07:00:21,451 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 07:00:21,451 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 194, 194) +2026-06-24 07:00:21,451 - object extent (Z, Y, X) (Ang) = [20. 38.8 38.8] +2026-06-24 07:00:21,451 - +2026-06-24 07:00:21,451 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 07:00:21,451 - omode_occu (omode) = float32, (1,) +2026-06-24 07:00:21,451 - +2026-06-24 07:00:21,451 - ### Initializing H (Fresnel propagator) ### +2026-06-24 07:00:21,451 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0418 Ang +2026-06-24 07:00:21,452 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 07:00:21,452 - +2026-06-24 07:00:21,452 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 07:00:21,452 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 07:00:21,452 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 07:00:21,452 - +2026-06-24 07:00:21,452 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 07:00:21,452 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 07:00:21,452 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 07:00:21,452 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 07:00:21,452 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 07:00:21,452 - crop positions (yx_min=[15 15], yx_max=[177 177]) are well contained inside object canvas (Ny,Nx) = (194, 194). +2026-06-24 07:00:21,452 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 07:00:21,452 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 07:00:21,452 - +2026-06-24 07:00:21,452 - ### Collecting reconstruction provenance ### +2026-06-24 07:00:21,452 - Reconstruction provenance is collected and initialized. +2026-06-24 07:00:21,452 - +2026-06-24 07:00:21,452 - ### Initializing loss function ### +2026-06-24 07:00:21,453 - Active loss types: +2026-06-24 07:00:21,453 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 07:00:21,453 - +2026-06-24 07:00:21,453 - ### Initializing constraint function ### +2026-06-24 07:00:21,453 - Active constraint types: +2026-06-24 07:00:21,453 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:00:21,453 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:00:21,453 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 07:00:21,453 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 07:00:21,453 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 07:00:21,453 - +2026-06-24 07:00:21,453 - ### Done initializing PtyRADSolver ### +2026-06-24 07:00:21,453 - +2026-06-24 07:00:21,577 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 07:00:21,577 - +2026-06-24 07:00:21,577 - ### Initializing PtychoModel model ### +2026-06-24 07:00:21,646 - ### PtychoModel optimizable variables ### +2026-06-24 07:00:21,647 - obja : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:21,647 - objp : torch.Size([1, 1, 194, 194]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:21,647 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:00:21,647 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:00:21,647 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 07:00:21,647 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:21,647 - +2026-06-24 07:00:21,647 - ### Optimizable variables statitsics ### +2026-06-24 07:00:21,647 - Total measurement values : 4,194,304 +2026-06-24 07:00:21,647 - Total optimizing variables: 272,392 +2026-06-24 07:00:21,647 - Overdetermined ratio : 15.40 +2026-06-24 07:00:21,647 - +2026-06-24 07:00:21,647 - ### Model behavior ### +2026-06-24 07:00:21,647 - Tilt propagator : False +2026-06-24 07:00:21,647 - Change slice thickness : False +2026-06-24 07:00:21,647 - Detector blur : False +2026-06-24 07:00:21,647 - Preload data : True +2026-06-24 07:00:21,647 - On-the-fly meas padding : False +2026-06-24 07:00:21,647 - On-the-fly meas resample : False +2026-06-24 07:00:21,647 - On-the-fly simu match mode: None +2026-06-24 07:00:21,647 - +2026-06-24 07:00:21,689 - ### Done initializing PtychoModel model ### +2026-06-24 07:00:21,689 - +2026-06-24 07:00:21,689 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 07:00:21,689 - +2026-06-24 07:00:21,689 - ### Generating indices, batches, and output_path ### +2026-06-24 07:00:21,690 - d90 = 51.000 px or 10.200 Ang +2026-06-24 07:00:21,690 - Selecting indices with the 'full' mode +2026-06-24 07:00:22,152 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 07:00:22,225 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 07:00:22,225 - Original recon_dir_affixes = ['default'] +2026-06-24 07:00:22,225 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 07:00:22,231 - Path corrected for compatibility: +2026-06-24 07:00:22,232 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_C32_4.29e+03_phi32_106_C34_-5.43e+03_phi34_0.046_C41_9.54e+04_phi41_263_C43_-2.01e+05_phi43_65.4_C45_1.04e+05_phi45_284_C50_-2.7e+08_C52_-1.61e+06_phi52_252_C54_-8.15e+06_phi54_114_C56_-1.36e+07_phi56_306 +2026-06-24 07:00:22,232 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306 +2026-06-24 07:00:22,233 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306' is generated! +2026-06-24 07:00:22,379 - +2026-06-24 07:00:22,380 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306/20260624_070022_ptyrad_log.txt ### +2026-06-24 07:00:22,380 - +2026-06-24 07:00:22,382 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 07:00:22,382 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 07:00:22,382 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 07:00:23,575 - Iter: 1, Total Loss: 1.0400, loss_single: 1.0400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 07:00:23,610 - Iter: 2, Total Loss: 0.9907, loss_single: 0.9907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,646 - Iter: 3, Total Loss: 0.9457, loss_single: 0.9457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,681 - Iter: 4, Total Loss: 0.8970, loss_single: 0.8970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,716 - Iter: 5, Total Loss: 0.8609, loss_single: 0.8609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:23,751 - Iter: 6, Total Loss: 0.8379, loss_single: 0.8379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,787 - Iter: 7, Total Loss: 0.8122, loss_single: 0.8122, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,822 - Iter: 8, Total Loss: 0.7829, loss_single: 0.7829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,857 - Iter: 9, Total Loss: 0.7565, loss_single: 0.7565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,893 - Iter: 10, Total Loss: 0.7313, loss_single: 0.7313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,927 - Iter: 11, Total Loss: 0.7057, loss_single: 0.7057, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,962 - Iter: 12, Total Loss: 0.6808, loss_single: 0.6808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:23,998 - Iter: 13, Total Loss: 0.6558, loss_single: 0.6558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,032 - Iter: 14, Total Loss: 0.6340, loss_single: 0.6340, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,067 - Iter: 15, Total Loss: 0.6137, loss_single: 0.6137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,103 - Iter: 16, Total Loss: 0.5958, loss_single: 0.5958, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,138 - Iter: 17, Total Loss: 0.5807, loss_single: 0.5807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,173 - Iter: 18, Total Loss: 0.5654, loss_single: 0.5654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,208 - Iter: 19, Total Loss: 0.5507, loss_single: 0.5507, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,243 - Iter: 20, Total Loss: 0.5389, loss_single: 0.5389, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,278 - Iter: 21, Total Loss: 0.5286, loss_single: 0.5286, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,313 - Iter: 22, Total Loss: 0.5189, loss_single: 0.5189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,348 - Iter: 23, Total Loss: 0.5096, loss_single: 0.5096, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,384 - Iter: 24, Total Loss: 0.5031, loss_single: 0.5031, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,419 - Iter: 25, Total Loss: 0.4981, loss_single: 0.4981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,454 - Iter: 26, Total Loss: 0.4911, loss_single: 0.4911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,489 - Iter: 27, Total Loss: 0.4848, loss_single: 0.4848, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,524 - Iter: 28, Total Loss: 0.4805, loss_single: 0.4805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,559 - Iter: 29, Total Loss: 0.4765, loss_single: 0.4765, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,595 - Iter: 30, Total Loss: 0.4715, loss_single: 0.4715, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,629 - Iter: 31, Total Loss: 0.4665, loss_single: 0.4665, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,668 - Iter: 32, Total Loss: 0.4626, loss_single: 0.4626, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 07:00:24,703 - Iter: 33, Total Loss: 0.4600, loss_single: 0.4600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,738 - Iter: 34, Total Loss: 0.4571, loss_single: 0.4571, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,773 - Iter: 35, Total Loss: 0.4541, loss_single: 0.4541, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,808 - Iter: 36, Total Loss: 0.4515, loss_single: 0.4515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,843 - Iter: 37, Total Loss: 0.4496, loss_single: 0.4496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,877 - Iter: 38, Total Loss: 0.4483, loss_single: 0.4483, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,912 - Iter: 39, Total Loss: 0.4473, loss_single: 0.4473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:24,947 - Iter: 40, Total Loss: 0.4465, loss_single: 0.4465, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:24,984 - Iter: 41, Total Loss: 0.4454, loss_single: 0.4454, 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Iter: 47, Total Loss: 0.4419, loss_single: 0.4419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:25,230 - Iter: 48, Total Loss: 0.4416, loss_single: 0.4416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,265 - Iter: 49, Total Loss: 0.4413, loss_single: 0.4413, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:25,300 - Iter: 50, Total Loss: 0.4411, loss_single: 0.4411, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,335 - Iter: 51, Total Loss: 0.4408, loss_single: 0.4408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,370 - Iter: 52, Total Loss: 0.4405, loss_single: 0.4405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,405 - Iter: 53, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,465 - Iter: 54, Total Loss: 0.4400, loss_single: 0.4400, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,500 - Iter: 55, Total Loss: 0.4397, loss_single: 0.4397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,535 - Iter: 56, Total Loss: 0.4396, loss_single: 0.4396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,570 - Iter: 57, Total Loss: 0.4394, loss_single: 0.4394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:25,606 - Iter: 58, Total Loss: 0.4392, loss_single: 0.4392, loss_poissn: 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in 0.035 sec +2026-06-24 07:00:26,026 - Iter: 70, Total Loss: 0.4373, loss_single: 0.4373, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,061 - Iter: 71, Total Loss: 0.4372, loss_single: 0.4372, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,096 - Iter: 72, Total Loss: 0.4371, loss_single: 0.4371, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,131 - Iter: 73, Total Loss: 0.4369, loss_single: 0.4369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,165 - Iter: 74, Total Loss: 0.4368, loss_single: 0.4368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,200 - Iter: 75, Total Loss: 0.4366, loss_single: 0.4366, loss_poissn: 0.0000, loss_pacbed: 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loss_single: 0.4358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,445 - Iter: 82, Total Loss: 0.4356, loss_single: 0.4356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,479 - Iter: 83, Total Loss: 0.4355, loss_single: 0.4355, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,514 - Iter: 84, Total Loss: 0.4354, loss_single: 0.4354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,549 - Iter: 85, Total Loss: 0.4353, loss_single: 0.4353, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,584 - Iter: 86, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,618 - Iter: 87, Total Loss: 0.4350, loss_single: 0.4350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:26,653 - Iter: 88, Total Loss: 0.4348, loss_single: 0.4348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,688 - Iter: 89, Total Loss: 0.4347, loss_single: 0.4347, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,723 - Iter: 90, Total Loss: 0.4345, loss_single: 0.4345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,758 - Iter: 91, Total Loss: 0.4343, loss_single: 0.4343, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:26,795 - Iter: 92, Total Loss: 0.4342, loss_single: 0.4342, loss_poissn: 0.0000, loss_pacbed: 0.0000, 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0.4333, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:27,040 - Iter: 99, Total Loss: 0.4331, loss_single: 0.4331, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:27,075 - Iter: 100, Total Loss: 0.4329, loss_single: 0.4329, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:27,187 - Saving summary figures for iter 100 +2026-06-24 07:00:30,754 - ### Finished 100 iterations, averaged iter_t = 0.038648 with std = 0.040 ### +2026-06-24 07:00:30,754 - +2026-06-24 07:00:30,754 - ### The PtyRADSolver is finished in 9.178 sec ### +2026-06-24 07:00:30,754 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040/c30_small__simulation_data_aug3__sample_000040_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-354_C12_-22.9_phi12_53.5_C21_-526_phi21_58.8_C23_962_phi23_310_C30_3.77e+06_.36e+07_phi56_306/simulation_data_aug3__sample_000040.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 80.0 + probe_conv_angle: 14.6714506149292 + probe_aberrations: + C10: -353.5296325683594 + C12: -22.92247200012207 + C21: -525.9033203125 + C23: 962.1060180664062 + C30: 3766869.5 + C32: 4294.08984375 + C34: -5434.263671875 + C41: 95421.34375 + C43: -200856.5 + C45: 104123.375 + C50: -269852000.0 + C52: -1606306.375 + C54: -8147864.0 + C56: -13579540.0 + phi12: 53.46935044569027 + phi21: 58.76181814672303 + phi23: 309.50160744607035 + phi32: 105.73574065400122 + phi34: 0.04628122841387417 + phi41: 262.90613889051343 + phi43: 65.39639752909578 + phi45: 284.25731023597325 + phi52: 252.33622990462192 + phi54: 114.36682531190371 + phi56: 305.5500698036512 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.43743759393692017 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000040_measurement.h5 + key: measurement + random_seed: 20262194 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000040 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/20260624_070051_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ea5c2ea1dd7f980761157dc611fd85bafdb44087 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/20260624_070051_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 07:00:50,171 - ### PtyRAD LoggingManager configuration ### +2026-06-24 07:00:50,171 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 07:00:50,171 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 07:00:50,171 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 07:00:50,171 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 07:00:50,171 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 07:00:50,171 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 07:00:50,171 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 07:00:50,171 - +2026-06-24 07:00:50,278 - ### Initializing HuggingFace accelerator ### +2026-06-24 07:00:50,278 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 07:00:50,278 - Accelerator.num_process = 1 +2026-06-24 07:00:50,278 - Accelerator.mixed_precision = no +2026-06-24 07:00:50,289 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 07:00:50,289 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 07:00:50,289 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 07:00:50,289 - +2026-06-24 07:00:50,289 - ### System information ### +2026-06-24 07:00:50,289 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 07:00:50,289 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 07:00:50,289 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 07:00:50,289 - Machine: x86_64 +2026-06-24 07:00:50,289 - Processor: x86_64 +2026-06-24 07:00:50,289 - Available CPU cores: 8 +2026-06-24 07:00:50,289 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 07:00:50,289 - +2026-06-24 07:00:50,289 - ### GPU information ### +2026-06-24 07:00:50,289 - CUDA Available: True +2026-06-24 07:00:50,289 - CUDA Version: 13.0 +2026-06-24 07:00:50,290 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 07:00:50,290 - CUDA Compute Capability: ['8.0'] +2026-06-24 07:00:50,290 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 07:00:50,290 - In addition, Triton does not directly support Windows. +2026-06-24 07:00:50,290 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 07:00:50,317 - MIG (Multi-Instance GPU) mode = False +2026-06-24 07:00:50,317 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 07:00:50,317 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 07:00:50,317 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 07:00:50,317 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 07:00:50,317 - +2026-06-24 07:00:50,317 - ### Python information ### +2026-06-24 07:00:50,319 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 07:00:50,319 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 07:00:50,319 - +2026-06-24 07:00:50,319 - ### Packages information ### +2026-06-24 07:00:50,320 - Numpy Version (metadata): 2.4.6 +2026-06-24 07:00:50,321 - PyTorch Version (metadata): 2.12.0 +2026-06-24 07:00:50,321 - Optuna Version (metadata): 4.9.0 +2026-06-24 07:00:50,322 - Accelerate Version (metadata): 1.13.0 +2026-06-24 07:00:50,323 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 07:00:50,323 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 07:00:50,323 - +2026-06-24 07:00:50,323 - ### Loading params file ### +2026-06-24 07:00:50,323 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000042.yaml +2026-06-24 07:00:50,329 - validate = True: Filling defaults and validating the params file... +2026-06-24 07:00:50,330 - Success! Params file validated and defaults applied. +2026-06-24 07:00:50,330 - +2026-06-24 07:00:50,330 - ### Setting GPU Device ### +2026-06-24 07:00:50,330 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 07:00:50,330 - +2026-06-24 07:00:50,330 - Random seed: 20262196 provided by params file +2026-06-24 07:00:50,331 - ### Initializing Initializer ### +2026-06-24 07:00:50,331 - init_params are displayed below: +2026-06-24 07:00:50,331 - random_seed: 20262196 +2026-06-24 07:00:50,331 - probe_illum_type: electron +2026-06-24 07:00:50,331 - probe_kv: 120.0 +2026-06-24 07:00:50,331 - probe_conv_angle: 12.160144805908203 +2026-06-24 07:00:50,331 - probe_aberrations: {'C10': -677.112, 'C12': 41.083, 'phi12': 38.408, 'C21': -400.336, 'phi21': 306.994, 'C23': -727.643, 'phi23': 217.164, 'C30': 3627635.5, 'C32': 11294.394, 'phi32': 211.404, 'C34': 2029.126, 'phi34': 270.168, 'C41': -177012.281, 'phi41': 135.088, 'C43': 473864.719, 'phi43': 116.488, 'C45': -349908.469, 'phi45': 252.729, 'C50': 373299552.0, 'C52': 17618454.0, 'phi52': 356.893, 'C54': -17341056.0, 'phi54': 53.201, 'C56': -14740456.0, 'phi56': 102.232} +2026-06-24 07:00:50,331 - beam_kev: None +2026-06-24 07:00:50,331 - probe_dRn: None +2026-06-24 07:00:50,331 - probe_Rn: None +2026-06-24 07:00:50,331 - probe_D_H: None +2026-06-24 07:00:50,331 - probe_D_FZP: None +2026-06-24 07:00:50,331 - probe_Ls: None +2026-06-24 07:00:50,331 - meas_Npix: 128 +2026-06-24 07:00:50,331 - pos_N_scans: 256 +2026-06-24 07:00:50,331 - pos_N_scan_slow: 16 +2026-06-24 07:00:50,331 - pos_N_scan_fast: 16 +2026-06-24 07:00:50,331 - pos_scan_step_size: 0.5009142160415649 +2026-06-24 07:00:50,331 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 07:00:50,331 - probe_pmode_max: 6 +2026-06-24 07:00:50,331 - probe_pmode_init_pows: [0.02] +2026-06-24 07:00:50,331 - obj_omode_max: 1 +2026-06-24 07:00:50,331 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 07:00:50,331 - obj_Nlayer: 1 +2026-06-24 07:00:50,331 - obj_slice_thickness: 20.0 +2026-06-24 07:00:50,332 - simu_Npix: None +2026-06-24 07:00:50,332 - simu_match_mode: None +2026-06-24 07:00:50,332 - meas_permute: None +2026-06-24 07:00:50,332 - meas_reshape: [256, 128, 128] +2026-06-24 07:00:50,332 - meas_flipT: [0, 0, 0] +2026-06-24 07:00:50,332 - meas_crop: None +2026-06-24 07:00:50,332 - meas_pad: None +2026-06-24 07:00:50,332 - meas_resample: None +2026-06-24 07:00:50,332 - meas_add_source_size: None +2026-06-24 07:00:50,332 - meas_add_detector_blur: None +2026-06-24 07:00:50,332 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 07:00:50,332 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 07:00:50,332 - meas_add_poisson_noise: None +2026-06-24 07:00:50,332 - meas_export: None +2026-06-24 07:00:50,332 - probe_permute: None +2026-06-24 07:00:50,332 - probe_z_shift: None +2026-06-24 07:00:50,332 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 07:00:50,332 - pos_scan_flipT: None +2026-06-24 07:00:50,332 - pos_scan_affine: None +2026-06-24 07:00:50,332 - pos_scan_rand_std: 0.15 +2026-06-24 07:00:50,332 - obj_z_crop: None +2026-06-24 07:00:50,332 - obj_z_pad: None +2026-06-24 07:00:50,332 - obj_z_resample: None +2026-06-24 07:00:50,332 - meas_source: file +2026-06-24 07:00:50,332 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000042_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 07:00:50,332 - probe_source: simu +2026-06-24 07:00:50,332 - probe_params: None +2026-06-24 07:00:50,332 - pos_source: simu +2026-06-24 07:00:50,332 - pos_params: None +2026-06-24 07:00:50,332 - obj_source: simu +2026-06-24 07:00:50,332 - obj_params: None +2026-06-24 07:00:50,332 - tilt_source: simu +2026-06-24 07:00:50,332 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 07:00:50,332 - +2026-06-24 07:00:50,332 - ### Initializing cache ### +2026-06-24 07:00:50,332 - use_cached_obj = False +2026-06-24 07:00:50,332 - use_cached_probe = False +2026-06-24 07:00:50,333 - use_cached_pos = False +2026-06-24 07:00:50,333 - +2026-06-24 07:00:50,333 - ### Initializing measurements ### +2026-06-24 07:00:50,333 - Loading measurements from source = 'file' +2026-06-24 07:00:50,333 - Detected measurement file type = '.h5' +2026-06-24 07:00:50,413 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 07:00:50,413 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 07:00:50,415 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0046) +2026-06-24 07:00:50,415 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 07:00:50,415 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 07:00:50,417 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:00:50,417 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 07:00:50,418 - Normalizing by max of the 2D mean pattern intensity: 0.0034894578 +2026-06-24 07:00:50,418 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 07:00:50,419 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0174, 1.3295) +2026-06-24 07:00:50,420 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:00:50,421 - Pattern total int. statistics (min, mean, max) = (283.5066, 285.7718, 287.9973), with min/max = 98.4% +2026-06-24 07:00:50,423 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0174, 1.3295) +2026-06-24 07:00:50,423 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 07:00:50,423 - +2026-06-24 07:00:50,423 - ### Setting up calibration ### +2026-06-24 07:00:50,423 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 07:00:50,423 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 07:00:50,423 - Radius of fitted bright field disk (RBF) = 9.15 px with meas_Npix = 128 +2026-06-24 07:00:50,423 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1430 +2026-06-24 07:00:50,423 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 07:00:50,423 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 07:00:50,647 - Initial guess: center=(63.63, 63.63), radius=9.15, Gaussian blur std=0.50 +2026-06-24 07:00:50,659 - Final fit: center=(63.63, 63.63), radius=9.15, Gaussian blur std=0.70 +2026-06-24 07:00:50,659 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.29 px with Npix = 128 +2026-06-24 07:00:50,660 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 07:00:50,660 - +2026-06-24 07:00:50,660 - ### Setting init_variables dict ### +2026-06-24 07:00:50,660 - Derived values given input init_params: +2026-06-24 07:00:50,660 - kv = 120.0 kV +2026-06-24 07:00:50,660 - wavelength = 0.0335 Ang +2026-06-24 07:00:50,660 - conv_angle = 12.160144805908203 mrad +2026-06-24 07:00:50,660 - Npix = 128 px +2026-06-24 07:00:50,660 - dk = 0.0391 Ang^-1 +2026-06-24 07:00:50,660 - kMax = 2.5000 Ang^-1 +2026-06-24 07:00:50,660 - da = 1.3083 mrad +2026-06-24 07:00:50,660 - angleMax = 83.7304 mrad +2026-06-24 07:00:50,660 - RBF = 9.2947 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 07:00:50,660 - n_alpha = 6.8856 (# conv_angle) +2026-06-24 07:00:50,660 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:00:50,660 - Rayleigh-limited resolution = 1.6801 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:00:50,660 - Real space probe extent = 25.6000 Ang +2026-06-24 07:00:50,660 - +2026-06-24 07:00:50,660 - ### Initializing probe ### +2026-06-24 07:00:50,660 - Loading probe from source = 'simu' +2026-06-24 07:00:50,660 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 07:00:50,660 - Start simulating STEM probe +2026-06-24 07:00:50,660 - kv = 120.0 kV +2026-06-24 07:00:50,660 - wavelength = 0.0335 Ang +2026-06-24 07:00:50,660 - conv_angle = 12.160144805908203 mrad +2026-06-24 07:00:50,661 - Npix = 128 px +2026-06-24 07:00:50,661 - dk = 0.0391 Ang^-1 +2026-06-24 07:00:50,661 - kMax = 2.5000 Ang^-1 +2026-06-24 07:00:50,661 - alpha_max = 83.7304 mrad +2026-06-24 07:00:50,661 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:00:50,661 - Rayleigh-limited resolution = 1.6801 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:00:50,661 - Real space probe extent = 25.6000 Ang +2026-06-24 07:00:50,661 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 07:00:50,661 - ------------------------------------------------------------------------------------ +2026-06-24 07:00:50,661 - C1,0 C1 -677.1120 - Defocus (C10 = -df) +2026-06-24 07:00:50,661 - C1,2 A1 41.0830 38.41 2-fold astigmatism +2026-06-24 07:00:50,661 - C2,1 3*B2 -400.3360 306.99 Axial coma +2026-06-24 07:00:50,661 - C2,3 A2 -727.6430 217.16 3-fold astigmatism +2026-06-24 07:00:50,661 - C3,0 C3 3627635.5000 - Spherical aberration +2026-06-24 07:00:50,661 - C3,2 4*S3 11294.3940 211.40 Axial star aberration +2026-06-24 07:00:50,661 - C3,4 A3 2029.1260 270.17 4-fold astigmatism +2026-06-24 07:00:50,661 - C4,1 4*B4 -177012.2810 135.09 Axial coma(4th) +2026-06-24 07:00:50,661 - C4,3 4*D4 473864.7190 116.49 3-lobe aberration +2026-06-24 07:00:50,661 - C4,5 A4 -349908.4690 252.73 5-fold astigmatism +2026-06-24 07:00:50,661 - C5,0 C5 373299552.0000 - Spherical aberration (5th) +2026-06-24 07:00:50,661 - C5,2 6*S5 17618454.0000 356.89 Axial star aberration(5th) +2026-06-24 07:00:50,661 - C5,4 6*R5 -17341056.0000 53.20 4-lobe aberration +2026-06-24 07:00:50,661 - C5,6 A5 -14740456.0000 102.23 6-fold astigmatism +2026-06-24 07:00:50,664 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 07:00:50,664 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 07:00:50,664 - Creating 5 new probe modes from the major mode +2026-06-24 07:00:50,664 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 07:00:50,763 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 07:00:50,764 - Orthogonalizing 6 pmodes +2026-06-24 07:00:50,766 - Sorting 6 pmodes by their intensities +2026-06-24 07:00:50,767 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 07:00:50,768 - sum(|probe_data|**2) = 285.77, while meas_total_ints (min, mean, max) = (283.5066, 285.7718, 287.9973) +2026-06-24 07:00:50,768 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 07:00:50,768 - +2026-06-24 07:00:50,768 - ### Initializing probe positions ### +2026-06-24 07:00:50,768 - Loading probe positions from source = 'simu' +2026-06-24 07:00:50,768 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 07:00:50,768 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5009, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 07:00:50,768 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 07:00:50,770 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 07:00:50,770 - crop_pos 1st and last px coords (y,x) = ([16, 16], [54, 54]) +2026-06-24 07:00:50,770 - crop_pos extent (Ang) = [7.6 7.6] +2026-06-24 07:00:50,770 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 07:00:50,770 - +2026-06-24 07:00:50,770 - ### Initializing object ### +2026-06-24 07:00:50,770 - Loading object from source = 'simu' +2026-06-24 07:00:50,771 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 07:00:50,772 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 07:00:50,772 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 200, 200) +2026-06-24 07:00:50,772 - object extent (Z, Y, X) (Ang) = [20. 40. 40.] +2026-06-24 07:00:50,772 - +2026-06-24 07:00:50,772 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 07:00:50,772 - omode_occu (omode) = float32, (1,) +2026-06-24 07:00:50,773 - +2026-06-24 07:00:50,773 - ### Initializing H (Fresnel propagator) ### +2026-06-24 07:00:50,773 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0335 Ang +2026-06-24 07:00:50,773 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 07:00:50,773 - +2026-06-24 07:00:50,773 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 07:00:50,773 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 07:00:50,773 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 07:00:50,773 - +2026-06-24 07:00:50,773 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 07:00:50,773 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 07:00:50,773 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 07:00:50,774 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 07:00:50,774 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 07:00:50,774 - crop positions (yx_min=[16 16], yx_max=[182 182]) are well contained inside object canvas (Ny,Nx) = (200, 200). +2026-06-24 07:00:50,774 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 07:00:50,774 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 07:00:50,774 - +2026-06-24 07:00:50,774 - ### Collecting reconstruction provenance ### +2026-06-24 07:00:50,774 - Reconstruction provenance is collected and initialized. +2026-06-24 07:00:50,774 - +2026-06-24 07:00:50,774 - ### Initializing loss function ### +2026-06-24 07:00:50,774 - Active loss types: +2026-06-24 07:00:50,774 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 07:00:50,774 - +2026-06-24 07:00:50,774 - ### Initializing constraint function ### +2026-06-24 07:00:50,774 - Active constraint types: +2026-06-24 07:00:50,774 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:00:50,774 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:00:50,774 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 07:00:50,774 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 07:00:50,774 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 07:00:50,774 - +2026-06-24 07:00:50,775 - ### Done initializing PtyRADSolver ### +2026-06-24 07:00:50,775 - +2026-06-24 07:00:50,905 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 07:00:50,905 - +2026-06-24 07:00:50,905 - ### Initializing PtychoModel model ### +2026-06-24 07:00:50,988 - ### PtychoModel optimizable variables ### +2026-06-24 07:00:50,988 - obja : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:50,988 - objp : torch.Size([1, 1, 200, 200]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:50,988 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:00:50,988 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:00:50,988 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 07:00:50,988 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:00:50,988 - +2026-06-24 07:00:50,988 - ### Optimizable variables statitsics ### +2026-06-24 07:00:50,988 - Total measurement values : 4,194,304 +2026-06-24 07:00:50,988 - Total optimizing variables: 277,120 +2026-06-24 07:00:50,988 - Overdetermined ratio : 15.14 +2026-06-24 07:00:50,988 - +2026-06-24 07:00:50,988 - ### Model behavior ### +2026-06-24 07:00:50,988 - Tilt propagator : False +2026-06-24 07:00:50,988 - Change slice thickness : False +2026-06-24 07:00:50,989 - Detector blur : False +2026-06-24 07:00:50,989 - Preload data : True +2026-06-24 07:00:50,989 - On-the-fly meas padding : False +2026-06-24 07:00:50,989 - On-the-fly meas resample : False +2026-06-24 07:00:50,989 - On-the-fly simu match mode: None +2026-06-24 07:00:50,989 - +2026-06-24 07:00:51,030 - ### Done initializing PtychoModel model ### +2026-06-24 07:00:51,030 - +2026-06-24 07:00:51,030 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 07:00:51,030 - +2026-06-24 07:00:51,030 - ### Generating indices, batches, and output_path ### +2026-06-24 07:00:51,031 - d90 = 51.000 px or 10.200 Ang +2026-06-24 07:00:51,031 - Selecting indices with the 'full' mode +2026-06-24 07:00:51,489 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 07:00:51,564 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 07:00:51,564 - Original recon_dir_affixes = ['default'] +2026-06-24 07:00:51,564 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 07:00:51,571 - Path corrected for compatibility: +2026-06-24 07:00:51,571 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C32_1.13e+04_phi32_211_C34_2.03e+03_phi34_270_C41_-1.77e+05_phi41_135_C43_4.74e+05_phi43_116_C45_-3.5e+05_phi45_253_C50_3.73e+08_C52_1.76e+07_phi52_357_C54_-1.73e+07_phi54_53.2_C56_-1.47e+07_phi56_102 +2026-06-24 07:00:51,571 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102 +2026-06-24 07:00:51,572 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102' is generated! +2026-06-24 07:00:51,723 - +2026-06-24 07:00:51,724 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/20260624_070051_ptyrad_log.txt ### +2026-06-24 07:00:51,724 - +2026-06-24 07:00:51,726 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 07:00:51,726 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 07:00:51,726 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 07:00:52,913 - Iter: 1, Total Loss: 1.0085, loss_single: 1.0085, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 07:00:52,950 - Iter: 2, Total Loss: 0.9637, loss_single: 0.9637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 07:00:52,985 - Iter: 3, Total Loss: 0.9327, loss_single: 0.9327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,020 - Iter: 4, Total Loss: 0.9073, loss_single: 0.9073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,056 - Iter: 5, Total Loss: 0.8785, loss_single: 0.8785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,090 - Iter: 6, Total Loss: 0.8446, loss_single: 0.8446, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:53,125 - Iter: 7, Total Loss: 0.8144, loss_single: 0.8144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:53,160 - Iter: 8, Total Loss: 0.7902, loss_single: 0.7902, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,195 - Iter: 9, Total Loss: 0.7636, loss_single: 0.7636, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,231 - Iter: 10, Total Loss: 0.7318, loss_single: 0.7318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,266 - Iter: 11, Total Loss: 0.6995, loss_single: 0.6995, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:00:53,301 - Iter: 12, Total Loss: 0.6696, loss_single: 0.6696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,336 - Iter: 13, Total Loss: 0.6412, loss_single: 0.6412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,371 - Iter: 14, Total Loss: 0.6103, loss_single: 0.6103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,406 - Iter: 15, Total Loss: 0.5798, loss_single: 0.5798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,441 - Iter: 16, Total Loss: 0.5532, loss_single: 0.5532, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,477 - Iter: 17, Total Loss: 0.5264, loss_single: 0.5264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,512 - Iter: 18, Total Loss: 0.5041, loss_single: 0.5041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,547 - Iter: 19, Total Loss: 0.4828, loss_single: 0.4828, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,582 - Iter: 20, Total Loss: 0.4598, loss_single: 0.4598, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,618 - Iter: 21, Total Loss: 0.4392, loss_single: 0.4392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,653 - Iter: 22, Total Loss: 0.4197, loss_single: 0.4197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,689 - Iter: 23, Total Loss: 0.4028, loss_single: 0.4028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:00:53,724 - Iter: 24, Total Loss: 0.3886, loss_single: 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a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/simulation_data_aug3__sample_000042.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/simulation_data_aug3__sample_000042.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ba7d48f31b3cde8549517f4433e485dbff5ccd8d --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/simulation_data_aug3__sample_000042.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 120.0 + probe_conv_angle: 12.160144805908203 + probe_aberrations: + C10: -677.1116943359375 + C12: 41.0830078125 + C21: -400.3356628417969 + C23: -727.6427612304688 + C30: 3627635.5 + C32: 11294.3935546875 + C34: 2029.1263427734375 + C41: -177012.28125 + C43: 473864.71875 + C45: -349908.46875 + C50: 373299552.0 + C52: 17618454.0 + C54: -17341056.0 + C56: -14740456.0 + phi12: 38.40832570313776 + phi21: 306.9941630394886 + phi23: 217.16429371704632 + phi32: 211.40443617110958 + phi34: 270.1681052990977 + phi41: 135.08797317813242 + phi43: 116.48815229451544 + phi45: 252.72852864979077 + phi52: 356.89282036069045 + phi54: 53.20112550188929 + phi56: 102.23236587397243 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5009142160415649 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000042_measurement.h5 + key: measurement + random_seed: 20262196 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: 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0000000000000000000000000000000000000000..43fe4b5a46fc6706127e87c0795263173b32e342 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/summary_probe_modes_real_amp_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:26a282277d42fb3e7efcb7f0dbe7b434d6dd6749ecac5f11062bf1b08d1f9f1c +size 1380776 diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000042/c30_small__simulation_data_aug3__sample_000042_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-677_C12_41.1_phi12_38.4_C21_-400_phi21_307_C23_-728_phi23_217_C30_3.63e+06_C.47e+07_phi56_102/summary_scan_pos_iter0100.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f47d176e3fb902e68ec4d930ff3e316ae77fb3963bf4863fdccc66117b6d6e32 +size 47431 diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/20260624_070106_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/20260624_070106_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..96a8a9dbc89ab108d3bcd035703a8138f0f6f45f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/20260624_070106_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 07:01:04,825 - ### PtyRAD LoggingManager configuration ### +2026-06-24 07:01:04,825 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 07:01:04,825 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 07:01:04,825 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 07:01:04,825 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 07:01:04,825 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 07:01:04,825 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 07:01:04,825 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 07:01:04,825 - +2026-06-24 07:01:04,933 - ### Initializing HuggingFace accelerator ### +2026-06-24 07:01:04,933 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 07:01:04,933 - Accelerator.num_process = 1 +2026-06-24 07:01:04,933 - Accelerator.mixed_precision = no +2026-06-24 07:01:04,944 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 07:01:04,944 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 07:01:04,944 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 07:01:04,944 - +2026-06-24 07:01:04,944 - ### System information ### +2026-06-24 07:01:04,944 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 07:01:04,944 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 07:01:04,944 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 07:01:04,944 - Machine: x86_64 +2026-06-24 07:01:04,944 - Processor: x86_64 +2026-06-24 07:01:04,944 - Available CPU cores: 8 +2026-06-24 07:01:04,944 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 07:01:04,944 - +2026-06-24 07:01:04,944 - ### GPU information ### +2026-06-24 07:01:04,945 - CUDA Available: True +2026-06-24 07:01:04,945 - CUDA Version: 13.0 +2026-06-24 07:01:04,945 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 07:01:04,945 - CUDA Compute Capability: ['8.0'] +2026-06-24 07:01:04,945 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 07:01:04,945 - In addition, Triton does not directly support Windows. +2026-06-24 07:01:04,945 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 07:01:04,972 - MIG (Multi-Instance GPU) mode = False +2026-06-24 07:01:04,972 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 07:01:04,972 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 07:01:04,972 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 07:01:04,972 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 07:01:04,972 - +2026-06-24 07:01:04,972 - ### Python information ### +2026-06-24 07:01:04,974 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 07:01:04,974 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 07:01:04,974 - +2026-06-24 07:01:04,974 - ### Packages information ### +2026-06-24 07:01:04,975 - Numpy Version (metadata): 2.4.6 +2026-06-24 07:01:04,975 - PyTorch Version (metadata): 2.12.0 +2026-06-24 07:01:04,976 - Optuna Version (metadata): 4.9.0 +2026-06-24 07:01:04,977 - Accelerate Version (metadata): 1.13.0 +2026-06-24 07:01:04,977 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 07:01:04,977 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 07:01:04,977 - +2026-06-24 07:01:04,977 - ### Loading params file ### +2026-06-24 07:01:04,977 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/c30_small/simulation_data_aug3__sample_000043.yaml +2026-06-24 07:01:04,984 - validate = True: Filling defaults and validating the params file... +2026-06-24 07:01:04,985 - Success! Params file validated and defaults applied. +2026-06-24 07:01:04,985 - +2026-06-24 07:01:04,985 - ### Setting GPU Device ### +2026-06-24 07:01:04,985 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 07:01:04,985 - +2026-06-24 07:01:04,985 - Random seed: 20262197 provided by params file +2026-06-24 07:01:04,986 - ### Initializing Initializer ### +2026-06-24 07:01:04,986 - init_params are displayed below: +2026-06-24 07:01:04,986 - random_seed: 20262197 +2026-06-24 07:01:04,986 - probe_illum_type: electron +2026-06-24 07:01:04,986 - probe_kv: 200.0 +2026-06-24 07:01:04,986 - probe_conv_angle: 13.721831321716309 +2026-06-24 07:01:04,986 - probe_aberrations: {'C10': -503.185, 'C12': 4.457, 'phi12': 291.952, 'C21': -941.907, 'phi21': 250.997, 'C23': 596.08, 'phi23': 146.016, 'C30': 503309.469, 'C32': 7726.867, 'phi32': 71.236, 'C34': -830.371, 'phi34': 328.483, 'C41': -414928.562, 'phi41': 340.407, 'C43': 445750.688, 'phi43': 316.87, 'C45': -307469.75, 'phi45': 281.239, 'C50': -132780944.0, 'C52': -19836824.0, 'phi52': 241.254, 'C54': -10198138.0, 'phi54': 56.585, 'C56': 15413882.0, 'phi56': 317.063} +2026-06-24 07:01:04,986 - beam_kev: None +2026-06-24 07:01:04,986 - probe_dRn: None +2026-06-24 07:01:04,986 - probe_Rn: None +2026-06-24 07:01:04,986 - probe_D_H: None +2026-06-24 07:01:04,986 - probe_D_FZP: None +2026-06-24 07:01:04,986 - probe_Ls: None +2026-06-24 07:01:04,986 - meas_Npix: 128 +2026-06-24 07:01:04,986 - pos_N_scans: 256 +2026-06-24 07:01:04,986 - pos_N_scan_slow: 16 +2026-06-24 07:01:04,986 - pos_N_scan_fast: 16 +2026-06-24 07:01:04,986 - pos_scan_step_size: 0.4075760543346405 +2026-06-24 07:01:04,986 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 07:01:04,986 - probe_pmode_max: 6 +2026-06-24 07:01:04,986 - probe_pmode_init_pows: [0.02] +2026-06-24 07:01:04,986 - obj_omode_max: 1 +2026-06-24 07:01:04,986 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 07:01:04,986 - obj_Nlayer: 1 +2026-06-24 07:01:04,986 - obj_slice_thickness: 20.0 +2026-06-24 07:01:04,986 - simu_Npix: None +2026-06-24 07:01:04,986 - simu_match_mode: None +2026-06-24 07:01:04,986 - meas_permute: None +2026-06-24 07:01:04,986 - meas_reshape: [256, 128, 128] +2026-06-24 07:01:04,986 - meas_flipT: [0, 0, 0] +2026-06-24 07:01:04,986 - meas_crop: None +2026-06-24 07:01:04,986 - meas_pad: None +2026-06-24 07:01:04,986 - meas_resample: None +2026-06-24 07:01:04,987 - meas_add_source_size: None +2026-06-24 07:01:04,987 - meas_add_detector_blur: None +2026-06-24 07:01:04,987 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 07:01:04,987 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 07:01:04,987 - meas_add_poisson_noise: None +2026-06-24 07:01:04,987 - meas_export: None +2026-06-24 07:01:04,987 - probe_permute: None +2026-06-24 07:01:04,987 - probe_z_shift: None +2026-06-24 07:01:04,987 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 07:01:04,987 - pos_scan_flipT: None +2026-06-24 07:01:04,987 - pos_scan_affine: None +2026-06-24 07:01:04,987 - pos_scan_rand_std: 0.15 +2026-06-24 07:01:04,987 - obj_z_crop: None +2026-06-24 07:01:04,987 - obj_z_pad: None +2026-06-24 07:01:04,987 - obj_z_resample: None +2026-06-24 07:01:04,987 - meas_source: file +2026-06-24 07:01:04,987 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000043_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 07:01:04,987 - probe_source: simu +2026-06-24 07:01:04,987 - probe_params: None +2026-06-24 07:01:04,987 - pos_source: simu +2026-06-24 07:01:04,987 - pos_params: None +2026-06-24 07:01:04,987 - obj_source: simu +2026-06-24 07:01:04,987 - obj_params: None +2026-06-24 07:01:04,987 - tilt_source: simu +2026-06-24 07:01:04,987 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 07:01:04,987 - +2026-06-24 07:01:04,987 - ### Initializing cache ### +2026-06-24 07:01:04,987 - use_cached_obj = False +2026-06-24 07:01:04,987 - use_cached_probe = False +2026-06-24 07:01:04,987 - use_cached_pos = False +2026-06-24 07:01:04,987 - +2026-06-24 07:01:04,987 - ### Initializing measurements ### +2026-06-24 07:01:04,987 - Loading measurements from source = 'file' +2026-06-24 07:01:04,987 - Detected measurement file type = '.h5' +2026-06-24 07:01:05,066 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 07:01:05,066 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 07:01:05,067 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0023) +2026-06-24 07:01:05,067 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 07:01:05,067 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 07:01:05,069 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:01:05,069 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 07:01:05,069 - Normalizing by max of the 2D mean pattern intensity: 0.001639335 +2026-06-24 07:01:05,070 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 07:01:05,072 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0372, 1.4143) +2026-06-24 07:01:05,072 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 07:01:05,073 - Pattern total int. statistics (min, mean, max) = (605.6042, 609.4741, 613.1958), with min/max = 98.8% +2026-06-24 07:01:05,075 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0372, 1.4143) +2026-06-24 07:01:05,075 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 07:01:05,075 - +2026-06-24 07:01:05,075 - ### Setting up calibration ### +2026-06-24 07:01:05,075 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 07:01:05,075 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 07:01:05,075 - Radius of fitted bright field disk (RBF) = 13.91 px with meas_Npix = 128 +2026-06-24 07:01:05,075 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2174 +2026-06-24 07:01:05,075 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 07:01:05,075 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 07:01:05,297 - Initial guess: center=(63.63, 63.62), radius=13.91, Gaussian blur std=0.50 +2026-06-24 07:01:05,307 - Final fit: center=(63.63, 63.62), radius=13.91, Gaussian blur std=0.59 +2026-06-24 07:01:05,307 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 14.01 px with Npix = 128 +2026-06-24 07:01:05,307 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 07:01:05,307 - +2026-06-24 07:01:05,307 - ### Setting init_variables dict ### +2026-06-24 07:01:05,308 - Derived values given input init_params: +2026-06-24 07:01:05,308 - kv = 200.0 kV +2026-06-24 07:01:05,308 - wavelength = 0.0251 Ang +2026-06-24 07:01:05,308 - conv_angle = 13.721831321716309 mrad +2026-06-24 07:01:05,308 - Npix = 128 px +2026-06-24 07:01:05,308 - dk = 0.0391 Ang^-1 +2026-06-24 07:01:05,308 - kMax = 2.5000 Ang^-1 +2026-06-24 07:01:05,308 - da = 0.9797 mrad +2026-06-24 07:01:05,308 - angleMax = 62.6984 mrad +2026-06-24 07:01:05,308 - RBF = 14.0067 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 07:01:05,308 - n_alpha = 4.5692 (# conv_angle) +2026-06-24 07:01:05,308 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:01:05,308 - Rayleigh-limited resolution = 1.1149 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:01:05,308 - Real space probe extent = 25.6000 Ang +2026-06-24 07:01:05,308 - +2026-06-24 07:01:05,308 - ### Initializing probe ### +2026-06-24 07:01:05,308 - Loading probe from source = 'simu' +2026-06-24 07:01:05,308 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 07:01:05,308 - Start simulating STEM probe +2026-06-24 07:01:05,308 - kv = 200.0 kV +2026-06-24 07:01:05,308 - wavelength = 0.0251 Ang +2026-06-24 07:01:05,308 - conv_angle = 13.721831321716309 mrad +2026-06-24 07:01:05,308 - Npix = 128 px +2026-06-24 07:01:05,308 - dk = 0.0391 Ang^-1 +2026-06-24 07:01:05,309 - kMax = 2.5000 Ang^-1 +2026-06-24 07:01:05,309 - alpha_max = 62.6984 mrad +2026-06-24 07:01:05,309 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 07:01:05,309 - Rayleigh-limited resolution = 1.1149 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 07:01:05,309 - Real space probe extent = 25.6000 Ang +2026-06-24 07:01:05,309 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 07:01:05,309 - ------------------------------------------------------------------------------------- +2026-06-24 07:01:05,309 - C1,0 C1 -503.1850 - Defocus (C10 = -df) +2026-06-24 07:01:05,309 - C1,2 A1 4.4570 291.95 2-fold astigmatism +2026-06-24 07:01:05,309 - C2,1 3*B2 -941.9070 251.00 Axial coma +2026-06-24 07:01:05,309 - C2,3 A2 596.0800 146.02 3-fold astigmatism +2026-06-24 07:01:05,309 - C3,0 C3 503309.4690 - Spherical aberration +2026-06-24 07:01:05,309 - C3,2 4*S3 7726.8670 71.24 Axial star aberration +2026-06-24 07:01:05,309 - C3,4 A3 -830.3710 328.48 4-fold astigmatism +2026-06-24 07:01:05,309 - C4,1 4*B4 -414928.5620 340.41 Axial coma(4th) +2026-06-24 07:01:05,309 - C4,3 4*D4 445750.6880 316.87 3-lobe aberration +2026-06-24 07:01:05,309 - C4,5 A4 -307469.7500 281.24 5-fold astigmatism +2026-06-24 07:01:05,309 - C5,0 C5 -132780944.0000 - Spherical aberration (5th) +2026-06-24 07:01:05,309 - C5,2 6*S5 -19836824.0000 241.25 Axial star aberration(5th) +2026-06-24 07:01:05,309 - C5,4 6*R5 -10198138.0000 56.59 4-lobe aberration +2026-06-24 07:01:05,309 - C5,6 A5 15413882.0000 317.06 6-fold astigmatism +2026-06-24 07:01:05,312 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 07:01:05,312 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 07:01:05,312 - Creating 5 new probe modes from the major mode +2026-06-24 07:01:05,312 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 07:01:05,415 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 07:01:05,416 - Orthogonalizing 6 pmodes +2026-06-24 07:01:05,419 - Sorting 6 pmodes by their intensities +2026-06-24 07:01:05,419 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 07:01:05,420 - sum(|probe_data|**2) = 609.47, while meas_total_ints (min, mean, max) = (605.6042, 609.4741, 613.1958) +2026-06-24 07:01:05,420 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 07:01:05,420 - +2026-06-24 07:01:05,420 - ### Initializing probe positions ### +2026-06-24 07:01:05,420 - Loading probe positions from source = 'simu' +2026-06-24 07:01:05,420 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 07:01:05,420 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4076, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 07:01:05,421 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 07:01:05,423 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 07:01:05,423 - crop_pos 1st and last px coords (y,x) = ([16, 16], [46, 46]) +2026-06-24 07:01:05,423 - crop_pos extent (Ang) = [6.4 6.4] +2026-06-24 07:01:05,423 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 07:01:05,423 - +2026-06-24 07:01:05,423 - ### Initializing object ### +2026-06-24 07:01:05,423 - Loading object from source = 'simu' +2026-06-24 07:01:05,423 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 07:01:05,424 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 07:01:05,424 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 192, 192) +2026-06-24 07:01:05,425 - object extent (Z, Y, X) (Ang) = [20. 38.4 38.4] +2026-06-24 07:01:05,425 - +2026-06-24 07:01:05,425 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 07:01:05,425 - omode_occu (omode) = float32, (1,) +2026-06-24 07:01:05,425 - +2026-06-24 07:01:05,425 - ### Initializing H (Fresnel propagator) ### +2026-06-24 07:01:05,425 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 07:01:05,425 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 07:01:05,426 - +2026-06-24 07:01:05,426 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 07:01:05,426 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 07:01:05,426 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 07:01:05,426 - +2026-06-24 07:01:05,426 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 07:01:05,426 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 07:01:05,426 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 07:01:05,426 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 07:01:05,426 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 07:01:05,426 - crop positions (yx_min=[15 15], yx_max=[175 175]) are well contained inside object canvas (Ny,Nx) = (192, 192). +2026-06-24 07:01:05,426 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 07:01:05,426 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 07:01:05,426 - +2026-06-24 07:01:05,426 - ### Collecting reconstruction provenance ### +2026-06-24 07:01:05,426 - Reconstruction provenance is collected and initialized. +2026-06-24 07:01:05,426 - +2026-06-24 07:01:05,426 - ### Initializing loss function ### +2026-06-24 07:01:05,426 - Active loss types: +2026-06-24 07:01:05,426 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 07:01:05,427 - +2026-06-24 07:01:05,427 - ### Initializing constraint function ### +2026-06-24 07:01:05,427 - Active constraint types: +2026-06-24 07:01:05,427 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:01:05,427 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 07:01:05,427 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 07:01:05,427 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 07:01:05,427 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 07:01:05,427 - +2026-06-24 07:01:05,427 - ### Done initializing PtyRADSolver ### +2026-06-24 07:01:05,427 - +2026-06-24 07:01:05,556 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 07:01:05,556 - +2026-06-24 07:01:05,556 - ### Initializing PtychoModel model ### +2026-06-24 07:01:05,627 - ### PtychoModel optimizable variables ### +2026-06-24 07:01:05,627 - obja : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:01:05,627 - objp : torch.Size([1, 1, 192, 192]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:01:05,627 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:01:05,627 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 07:01:05,627 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 07:01:05,627 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 07:01:05,627 - +2026-06-24 07:01:05,627 - ### Optimizable variables statitsics ### +2026-06-24 07:01:05,627 - Total measurement values : 4,194,304 +2026-06-24 07:01:05,627 - Total optimizing variables: 270,848 +2026-06-24 07:01:05,627 - Overdetermined ratio : 15.49 +2026-06-24 07:01:05,628 - +2026-06-24 07:01:05,628 - ### Model behavior ### +2026-06-24 07:01:05,628 - Tilt propagator : False +2026-06-24 07:01:05,628 - Change slice thickness : False +2026-06-24 07:01:05,628 - Detector blur : False +2026-06-24 07:01:05,628 - Preload data : True +2026-06-24 07:01:05,628 - On-the-fly meas padding : False +2026-06-24 07:01:05,628 - On-the-fly meas resample : False +2026-06-24 07:01:05,628 - On-the-fly simu match mode: None +2026-06-24 07:01:05,628 - +2026-06-24 07:01:05,669 - ### Done initializing PtychoModel model ### +2026-06-24 07:01:05,670 - +2026-06-24 07:01:05,670 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 07:01:05,670 - +2026-06-24 07:01:05,670 - ### Generating indices, batches, and output_path ### +2026-06-24 07:01:05,671 - d90 = 63.000 px or 12.600 Ang +2026-06-24 07:01:05,671 - Selecting indices with the 'full' mode +2026-06-24 07:01:06,138 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 07:01:06,213 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 07:01:06,213 - Original recon_dir_affixes = ['default'] +2026-06-24 07:01:06,213 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 07:01:06,219 - Path corrected for compatibility: +2026-06-24 07:01:06,219 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32_7.73e+03_phi32_71.2_C34_-830_phi34_328_C41_-4.15e+05_phi41_340_C43_4.46e+05_phi43_317_C45_-3.07e+05_phi45_281_C50_-1.33e+08_C52_-1.98e+07_phi52_241_C54_-1.02e+07_phi54_56.6_C56_1.54e+07_phi56_317 +2026-06-24 07:01:06,219 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317 +2026-06-24 07:01:06,221 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317' is generated! +2026-06-24 07:01:06,372 - +2026-06-24 07:01:06,373 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/20260624_070106_ptyrad_log.txt ### +2026-06-24 07:01:06,373 - +2026-06-24 07:01:06,375 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 07:01:06,375 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 07:01:06,375 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 07:01:07,579 - Iter: 1, Total Loss: 0.7176, loss_single: 0.7176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 07:01:07,615 - Iter: 2, Total Loss: 0.6825, loss_single: 0.6825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 07:01:07,651 - Iter: 3, Total Loss: 0.6534, loss_single: 0.6534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,686 - Iter: 4, Total Loss: 0.6269, loss_single: 0.6269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,721 - Iter: 5, Total Loss: 0.6042, loss_single: 0.6042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:07,755 - Iter: 6, Total Loss: 0.5832, loss_single: 0.5832, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:07,790 - Iter: 7, Total Loss: 0.5631, loss_single: 0.5631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,825 - Iter: 8, Total Loss: 0.5430, loss_single: 0.5430, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,860 - Iter: 9, Total Loss: 0.5197, loss_single: 0.5197, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:07,896 - Iter: 10, Total Loss: 0.4929, loss_single: 0.4929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,931 - Iter: 11, Total Loss: 0.4687, loss_single: 0.4687, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:07,966 - Iter: 12, Total Loss: 0.4480, loss_single: 0.4480, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,001 - Iter: 13, Total Loss: 0.4273, loss_single: 0.4273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,036 - Iter: 14, Total Loss: 0.4078, loss_single: 0.4078, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,071 - Iter: 15, Total Loss: 0.3917, loss_single: 0.3917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,106 - Iter: 16, Total Loss: 0.3768, loss_single: 0.3768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,141 - Iter: 17, Total Loss: 0.3644, loss_single: 0.3644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,176 - Iter: 18, Total Loss: 0.3522, loss_single: 0.3522, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,211 - Iter: 19, Total Loss: 0.3407, loss_single: 0.3407, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,246 - Iter: 20, Total Loss: 0.3322, loss_single: 0.3322, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,280 - Iter: 21, Total Loss: 0.3232, loss_single: 0.3232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,315 - Iter: 22, Total Loss: 0.3147, loss_single: 0.3147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,350 - Iter: 23, Total Loss: 0.3089, loss_single: 0.3089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,384 - Iter: 24, Total Loss: 0.3035, loss_single: 0.3035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,419 - Iter: 25, Total Loss: 0.2978, loss_single: 0.2978, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,454 - Iter: 26, Total Loss: 0.2928, loss_single: 0.2928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,489 - Iter: 27, Total Loss: 0.2881, loss_single: 0.2881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,523 - Iter: 28, Total Loss: 0.2839, loss_single: 0.2839, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,559 - Iter: 29, Total Loss: 0.2807, loss_single: 0.2807, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,597 - Iter: 30, Total Loss: 0.2779, loss_single: 0.2779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 07:01:08,632 - Iter: 31, Total Loss: 0.2748, loss_single: 0.2748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,667 - Iter: 32, Total Loss: 0.2721, loss_single: 0.2721, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,702 - Iter: 33, Total Loss: 0.2697, loss_single: 0.2697, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,737 - Iter: 34, Total Loss: 0.2676, loss_single: 0.2676, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,771 - Iter: 35, Total Loss: 0.2657, loss_single: 0.2657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,806 - Iter: 36, Total Loss: 0.2639, loss_single: 0.2639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,841 - Iter: 37, Total Loss: 0.2623, loss_single: 0.2623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,876 - Iter: 38, Total Loss: 0.2611, loss_single: 0.2611, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,911 - Iter: 39, Total Loss: 0.2602, loss_single: 0.2602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:08,946 - Iter: 40, Total Loss: 0.2594, loss_single: 0.2594, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:08,984 - Iter: 41, Total Loss: 0.2587, loss_single: 0.2587, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,018 - Iter: 42, Total Loss: 0.2582, loss_single: 0.2582, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,052 - Iter: 43, Total Loss: 0.2576, loss_single: 0.2576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,087 - Iter: 44, Total Loss: 0.2571, loss_single: 0.2571, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,122 - Iter: 45, Total Loss: 0.2567, loss_single: 0.2567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:09,156 - Iter: 46, Total Loss: 0.2562, loss_single: 0.2562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,191 - Iter: 47, Total Loss: 0.2558, loss_single: 0.2558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,225 - Iter: 48, Total Loss: 0.2553, loss_single: 0.2553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,260 - Iter: 49, Total Loss: 0.2549, loss_single: 0.2549, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,295 - Iter: 50, Total Loss: 0.2545, loss_single: 0.2545, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,329 - Iter: 51, Total Loss: 0.2542, loss_single: 0.2542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,365 - Iter: 52, Total Loss: 0.2538, loss_single: 0.2538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:09,399 - Iter: 53, Total Loss: 0.2534, loss_single: 0.2534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,434 - Iter: 54, Total Loss: 0.2531, loss_single: 0.2531, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:09,470 - Iter: 55, Total Loss: 0.2528, loss_single: 0.2528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:09,504 - Iter: 56, Total Loss: 0.2524, loss_single: 0.2524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:09,540 - Iter: 57, Total Loss: 0.2521, loss_single: 0.2521, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:09,575 - Iter: 58, Total Loss: 0.2518, loss_single: 0.2518, loss_poissn: 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0.2437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 07:01:11,034 - Iter: 99, Total Loss: 0.2436, loss_single: 0.2436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:11,069 - Iter: 100, Total Loss: 0.2434, loss_single: 0.2434, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 07:01:11,182 - Saving summary figures for iter 100 +2026-06-24 07:01:14,868 - ### Finished 100 iterations, averaged iter_t = 0.038621 with std = 0.040 ### +2026-06-24 07:01:14,868 - +2026-06-24 07:01:14,868 - ### The PtyRADSolver is finished in 9.313 sec ### +2026-06-24 07:01:14,869 - diff --git 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/simulation_data_aug3__sample_000043.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 13.721831321716309 + probe_aberrations: + C10: -503.1854248046875 + C12: 4.456521511077881 + C21: -941.9065551757812 + C23: 596.0798950195312 + C30: 503309.46875 + C32: 7726.86669921875 + C34: -830.37060546875 + C41: -414928.5625 + C43: 445750.6875 + C45: -307469.75 + C50: -132780944.0 + C52: -19836824.0 + C54: -10198138.0 + C56: 15413882.0 + phi12: 291.9519554680995 + phi21: 250.99729426124597 + phi23: 146.01594800107267 + phi32: 71.23616828832166 + phi34: 328.4826485080224 + phi41: 340.4073118554076 + phi43: 316.8701521264635 + phi45: 281.23888571720454 + phi52: 241.25389280643938 + phi54: 56.58541251864432 + phi56: 317.06311863089473 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4075760543346405 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/c30_small/simulation_data_aug3__sample_000043_measurement.h5 + key: measurement + random_seed: 20262197 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043 + recon_dir_affixes: + - default + prefix: c30_small__simulation_data_aug3__sample_000043 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/c30_small/simulation_data_aug3__sample_000043/c30_small__simulation_data_aug3__sample_000043_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-503_C12_4.46_phi12_292_C21_-942_phi21_251_C23_596_phi23_146_C30_5.03e+05_C32.54e+07_phi56_317/summary_convergence_iter0100.png 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b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/20260623_234219_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..70a0dee4960ff1b09746a22afb060cf99ad06884 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/20260623_234219_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-23 23:42:18,317 - ### PtyRAD LoggingManager configuration ### +2026-06-23 23:42:18,318 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-23 23:42:18,318 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-23 23:42:18,318 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-23 23:42:18,318 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-23 23:42:18,318 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-23 23:42:18,318 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-23 23:42:18,318 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-23 23:42:18,318 - +2026-06-23 23:42:18,427 - ### Initializing HuggingFace accelerator ### +2026-06-23 23:42:18,427 - Accelerator.distributed_type = DistributedType.NO +2026-06-23 23:42:18,427 - Accelerator.num_process = 1 +2026-06-23 23:42:18,428 - Accelerator.mixed_precision = no +2026-06-23 23:42:18,450 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-23 23:42:18,450 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-23 23:42:18,450 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-23 23:42:18,450 - +2026-06-23 23:42:18,450 - ### System information ### +2026-06-23 23:42:18,450 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-23 23:42:18,450 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-23 23:42:18,450 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-23 23:42:18,450 - Machine: x86_64 +2026-06-23 23:42:18,450 - Processor: x86_64 +2026-06-23 23:42:18,450 - Available CPU cores: 8 +2026-06-23 23:42:18,450 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-23 23:42:18,450 - +2026-06-23 23:42:18,450 - ### GPU information ### +2026-06-23 23:42:18,450 - CUDA Available: True +2026-06-23 23:42:18,450 - CUDA Version: 13.0 +2026-06-23 23:42:18,451 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-23 23:42:18,451 - CUDA Compute Capability: ['8.0'] +2026-06-23 23:42:18,451 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-23 23:42:18,451 - In addition, Triton does not directly support Windows. +2026-06-23 23:42:18,451 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-23 23:42:18,466 - MIG (Multi-Instance GPU) mode = False +2026-06-23 23:42:18,466 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-23 23:42:18,466 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-23 23:42:18,466 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-23 23:42:18,466 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-23 23:42:18,466 - +2026-06-23 23:42:18,466 - ### Python information ### +2026-06-23 23:42:18,468 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-23 23:42:18,468 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-23 23:42:18,468 - +2026-06-23 23:42:18,468 - ### Packages information ### +2026-06-23 23:42:18,469 - Numpy Version (metadata): 2.4.6 +2026-06-23 23:42:18,469 - PyTorch Version (metadata): 2.12.0 +2026-06-23 23:42:18,470 - Optuna Version (metadata): 4.9.0 +2026-06-23 23:42:18,471 - Accelerate Version (metadata): 1.13.0 +2026-06-23 23:42:18,471 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-23 23:42:18,471 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-23 23:42:18,471 - +2026-06-23 23:42:18,471 - ### Loading params file ### +2026-06-23 23:42:18,471 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/f005_simulation_data6_b0cc2a63__sample_000013.yaml +2026-06-23 23:42:18,478 - validate = True: Filling defaults and validating the params file... +2026-06-23 23:42:18,479 - Success! Params file validated and defaults applied. +2026-06-23 23:42:18,479 - +2026-06-23 23:42:18,479 - ### Setting GPU Device ### +2026-06-23 23:42:18,479 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-23 23:42:18,479 - +2026-06-23 23:42:18,479 - Random seed: 20260626 provided by params file +2026-06-23 23:42:18,480 - ### Initializing Initializer ### +2026-06-23 23:42:18,480 - init_params are displayed below: +2026-06-23 23:42:18,480 - random_seed: 20260626 +2026-06-23 23:42:18,480 - probe_illum_type: electron +2026-06-23 23:42:18,480 - probe_kv: 200.0 +2026-06-23 23:42:18,480 - probe_conv_angle: 9.91810131072998 +2026-06-23 23:42:18,480 - probe_aberrations: {'C10': -401.252, 'C12': -13.184, 'phi12': 72.353, 'C21': 187.379, 'phi21': 351.034, 'C23': -814.688, 'phi23': 252.041, 'C30': 10371734.0, 'C32': 10346.336, 'phi32': 336.446, 'C34': -11791.021, 'phi34': 116.397, 'C41': -443766.781, 'phi41': 331.936, 'C43': 234443.188, 'phi43': 56.552, 'C45': -299696.406, 'phi45': 128.453, 'C50': 12290260.0, 'C52': -17827392.0, 'phi52': 330.065, 'C54': 1032114.562, 'phi54': 356.457, 'C56': -15998074.0, 'phi56': 75.251} +2026-06-23 23:42:18,480 - beam_kev: None +2026-06-23 23:42:18,480 - probe_dRn: None +2026-06-23 23:42:18,480 - probe_Rn: None +2026-06-23 23:42:18,480 - probe_D_H: None +2026-06-23 23:42:18,480 - probe_D_FZP: None +2026-06-23 23:42:18,480 - probe_Ls: None +2026-06-23 23:42:18,480 - meas_Npix: 128 +2026-06-23 23:42:18,480 - pos_N_scans: 256 +2026-06-23 23:42:18,480 - pos_N_scan_slow: 16 +2026-06-23 23:42:18,480 - pos_N_scan_fast: 16 +2026-06-23 23:42:18,480 - pos_scan_step_size: 0.5299999713897705 +2026-06-23 23:42:18,480 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-23 23:42:18,480 - probe_pmode_max: 6 +2026-06-23 23:42:18,480 - probe_pmode_init_pows: [0.02] +2026-06-23 23:42:18,480 - obj_omode_max: 1 +2026-06-23 23:42:18,480 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-23 23:42:18,480 - obj_Nlayer: 1 +2026-06-23 23:42:18,480 - obj_slice_thickness: 20.0 +2026-06-23 23:42:18,480 - simu_Npix: None +2026-06-23 23:42:18,480 - simu_match_mode: None +2026-06-23 23:42:18,480 - meas_permute: None +2026-06-23 23:42:18,480 - meas_reshape: [256, 128, 128] +2026-06-23 23:42:18,480 - meas_flipT: [0, 0, 0] +2026-06-23 23:42:18,481 - meas_crop: None +2026-06-23 23:42:18,481 - meas_pad: None +2026-06-23 23:42:18,481 - meas_resample: None +2026-06-23 23:42:18,481 - meas_add_source_size: None +2026-06-23 23:42:18,481 - meas_add_detector_blur: None +2026-06-23 23:42:18,481 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-23 23:42:18,481 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-23 23:42:18,481 - meas_add_poisson_noise: None +2026-06-23 23:42:18,481 - meas_export: None +2026-06-23 23:42:18,481 - probe_permute: None +2026-06-23 23:42:18,481 - probe_z_shift: None +2026-06-23 23:42:18,481 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-23 23:42:18,481 - pos_scan_flipT: None +2026-06-23 23:42:18,481 - pos_scan_affine: None +2026-06-23 23:42:18,481 - pos_scan_rand_std: 0.15 +2026-06-23 23:42:18,481 - obj_z_crop: None +2026-06-23 23:42:18,481 - obj_z_pad: None +2026-06-23 23:42:18,481 - obj_z_resample: None +2026-06-23 23:42:18,481 - meas_source: file +2026-06-23 23:42:18,481 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/f005_simulation_data6_b0cc2a63__sample_000013_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-23 23:42:18,481 - probe_source: simu +2026-06-23 23:42:18,481 - probe_params: None +2026-06-23 23:42:18,481 - pos_source: simu +2026-06-23 23:42:18,481 - pos_params: None +2026-06-23 23:42:18,481 - obj_source: simu +2026-06-23 23:42:18,481 - obj_params: None +2026-06-23 23:42:18,481 - tilt_source: simu +2026-06-23 23:42:18,481 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-23 23:42:18,481 - +2026-06-23 23:42:18,481 - ### Initializing cache ### +2026-06-23 23:42:18,481 - use_cached_obj = False +2026-06-23 23:42:18,481 - use_cached_probe = False +2026-06-23 23:42:18,481 - use_cached_pos = False +2026-06-23 23:42:18,481 - +2026-06-23 23:42:18,481 - ### Initializing measurements ### +2026-06-23 23:42:18,481 - Loading measurements from source = 'file' +2026-06-23 23:42:18,481 - Detected measurement file type = '.h5' +2026-06-23 23:42:18,560 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-23 23:42:18,560 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-23 23:42:18,562 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0044) +2026-06-23 23:42:18,562 - Reshaping measurements to shape = [256, 128, 128] +2026-06-23 23:42:18,562 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-23 23:42:18,564 - No negative values found in measurements. Skipping non-neg correction. +2026-06-23 23:42:18,564 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-23 23:42:18,565 - Normalizing by max of the 2D mean pattern intensity: 0.0030127415 +2026-06-23 23:42:18,566 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-23 23:42:18,567 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.4464) +2026-06-23 23:42:18,568 - No negative values found in measurements. Skipping non-neg correction. +2026-06-23 23:42:18,569 - Pattern total int. statistics (min, mean, max) = (328.6686, 331.1643, 333.0232), with min/max = 98.7% +2026-06-23 23:42:18,570 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.4464) +2026-06-23 23:42:18,570 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-23 23:42:18,570 - +2026-06-23 23:42:18,570 - ### Setting up calibration ### +2026-06-23 23:42:18,570 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-23 23:42:18,571 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-23 23:42:18,571 - Radius of fitted bright field disk (RBF) = 10.06 px with meas_Npix = 128 +2026-06-23 23:42:18,571 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1572 +2026-06-23 23:42:18,571 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-23 23:42:18,571 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-23 23:42:18,798 - Initial guess: center=(63.65, 63.61), radius=10.06, Gaussian blur std=0.50 +2026-06-23 23:42:18,807 - Final fit: center=(63.65, 63.61), radius=10.06, Gaussian blur std=0.54 +2026-06-23 23:42:18,807 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.12 px with Npix = 128 +2026-06-23 23:42:18,807 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-23 23:42:18,807 - +2026-06-23 23:42:18,807 - ### Setting init_variables dict ### +2026-06-23 23:42:18,807 - Derived values given input init_params: +2026-06-23 23:42:18,807 - kv = 200.0 kV +2026-06-23 23:42:18,807 - wavelength = 0.0251 Ang +2026-06-23 23:42:18,807 - conv_angle = 9.91810131072998 mrad +2026-06-23 23:42:18,807 - Npix = 128 px +2026-06-23 23:42:18,807 - dk = 0.0391 Ang^-1 +2026-06-23 23:42:18,807 - kMax = 2.5000 Ang^-1 +2026-06-23 23:42:18,807 - da = 0.9797 mrad +2026-06-23 23:42:18,807 - angleMax = 62.6984 mrad +2026-06-23 23:42:18,807 - RBF = 10.1240 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-23 23:42:18,807 - n_alpha = 6.3216 (# conv_angle) +2026-06-23 23:42:18,807 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-23 23:42:18,807 - Rayleigh-limited resolution = 1.5425 Ang (0.61*lambda/alpha for focused probe ) +2026-06-23 23:42:18,807 - Real space probe extent = 25.6000 Ang +2026-06-23 23:42:18,808 - +2026-06-23 23:42:18,808 - ### Initializing probe ### +2026-06-23 23:42:18,808 - Loading probe from source = 'simu' +2026-06-23 23:42:18,808 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-23 23:42:18,808 - Start simulating STEM probe +2026-06-23 23:42:18,808 - kv = 200.0 kV +2026-06-23 23:42:18,808 - wavelength = 0.0251 Ang +2026-06-23 23:42:18,808 - conv_angle = 9.91810131072998 mrad +2026-06-23 23:42:18,808 - Npix = 128 px +2026-06-23 23:42:18,808 - dk = 0.0391 Ang^-1 +2026-06-23 23:42:18,808 - kMax = 2.5000 Ang^-1 +2026-06-23 23:42:18,808 - alpha_max = 62.6984 mrad +2026-06-23 23:42:18,808 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-23 23:42:18,808 - Rayleigh-limited resolution = 1.5425 Ang (0.61*lambda/alpha for focused probe ) +2026-06-23 23:42:18,808 - Real space probe extent = 25.6000 Ang +2026-06-23 23:42:18,808 - Krivanek Haider Magnitude Angle (°) Description +2026-06-23 23:42:18,808 - ------------------------------------------------------------------------------------ +2026-06-23 23:42:18,808 - C1,0 C1 -401.2520 - Defocus (C10 = -df) +2026-06-23 23:42:18,808 - C1,2 A1 -13.1840 72.35 2-fold astigmatism +2026-06-23 23:42:18,808 - C2,1 3*B2 187.3790 351.03 Axial coma +2026-06-23 23:42:18,808 - C2,3 A2 -814.6880 252.04 3-fold astigmatism +2026-06-23 23:42:18,808 - C3,0 C3 10371734.0000 - Spherical aberration +2026-06-23 23:42:18,808 - C3,2 4*S3 10346.3360 336.45 Axial star aberration +2026-06-23 23:42:18,808 - C3,4 A3 -11791.0210 116.40 4-fold astigmatism +2026-06-23 23:42:18,808 - C4,1 4*B4 -443766.7810 331.94 Axial coma(4th) +2026-06-23 23:42:18,809 - C4,3 4*D4 234443.1880 56.55 3-lobe aberration +2026-06-23 23:42:18,809 - C4,5 A4 -299696.4060 128.45 5-fold astigmatism +2026-06-23 23:42:18,809 - C5,0 C5 12290260.0000 - Spherical aberration (5th) +2026-06-23 23:42:18,809 - C5,2 6*S5 -17827392.0000 330.06 Axial star aberration(5th) +2026-06-23 23:42:18,809 - C5,4 6*R5 1032114.5620 356.46 4-lobe aberration +2026-06-23 23:42:18,809 - C5,6 A5 -15998074.0000 75.25 6-fold astigmatism +2026-06-23 23:42:18,812 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-23 23:42:18,812 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-23 23:42:18,812 - Creating 5 new probe modes from the major mode +2026-06-23 23:42:18,812 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-23 23:42:18,909 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-23 23:42:18,911 - Orthogonalizing 6 pmodes +2026-06-23 23:42:18,914 - Sorting 6 pmodes by their intensities +2026-06-23 23:42:18,914 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-23 23:42:18,915 - sum(|probe_data|**2) = 331.16, while meas_total_ints (min, mean, max) = (328.6686, 331.1643, 333.0232) +2026-06-23 23:42:18,915 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-23 23:42:18,915 - +2026-06-23 23:42:18,915 - ### Initializing probe positions ### +2026-06-23 23:42:18,915 - Loading probe positions from source = 'simu' +2026-06-23 23:42:18,915 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-23 23:42:18,915 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-23 23:42:18,915 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-23 23:42:18,917 - crop_pos (N,2) = int16, (256, 2) +2026-06-23 23:42:18,917 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-23 23:42:18,918 - crop_pos extent (Ang) = [8. 8.] +2026-06-23 23:42:18,918 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-23 23:42:18,918 - +2026-06-23 23:42:18,918 - ### Initializing object ### +2026-06-23 23:42:18,918 - Loading object from source = 'simu' +2026-06-23 23:42:18,918 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-23 23:42:18,919 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-23 23:42:18,919 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-23 23:42:18,920 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-23 23:42:18,920 - +2026-06-23 23:42:18,920 - ### Initializing omode_occu from 'uniform' ### +2026-06-23 23:42:18,920 - omode_occu (omode) = float32, (1,) +2026-06-23 23:42:18,920 - +2026-06-23 23:42:18,920 - ### Initializing H (Fresnel propagator) ### +2026-06-23 23:42:18,920 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-23 23:42:18,920 - H (Ky, Kx) = complex64, (128, 128) +2026-06-23 23:42:18,920 - +2026-06-23 23:42:18,921 - ### Initializing obj tilts from = 'simu' ### +2026-06-23 23:42:18,921 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-23 23:42:18,921 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-23 23:42:18,921 - +2026-06-23 23:42:18,921 - ### Checking consistency between input params with the initialized variables ### +2026-06-23 23:42:18,921 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-23 23:42:18,921 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-23 23:42:18,921 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-23 23:42:18,921 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-23 23:42:18,921 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-23 23:42:18,921 - obj_tilts is consistent with either 1 or N_scans +2026-06-23 23:42:18,921 - Pass the consistency check of initialized variables, initialization is done! +2026-06-23 23:42:18,921 - +2026-06-23 23:42:18,921 - ### Collecting reconstruction provenance ### +2026-06-23 23:42:18,921 - Reconstruction provenance is collected and initialized. +2026-06-23 23:42:18,921 - +2026-06-23 23:42:18,921 - ### Initializing loss function ### +2026-06-23 23:42:18,921 - Active loss types: +2026-06-23 23:42:18,921 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-23 23:42:18,921 - +2026-06-23 23:42:18,921 - ### Initializing constraint function ### +2026-06-23 23:42:18,922 - Active constraint types: +2026-06-23 23:42:18,922 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-23 23:42:18,922 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-23 23:42:18,922 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-23 23:42:18,922 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-23 23:42:18,922 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-23 23:42:18,922 - +2026-06-23 23:42:18,922 - ### Done initializing PtyRADSolver ### +2026-06-23 23:42:18,922 - +2026-06-23 23:42:19,046 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-23 23:42:19,046 - +2026-06-23 23:42:19,046 - ### Initializing PtychoModel model ### +2026-06-23 23:42:19,117 - ### PtychoModel optimizable variables ### +2026-06-23 23:42:19,117 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:42:19,117 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:42:19,117 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-23 23:42:19,117 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-23 23:42:19,117 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-23 23:42:19,117 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:42:19,117 - +2026-06-23 23:42:19,117 - ### Optimizable variables statitsics ### +2026-06-23 23:42:19,117 - Total measurement values : 4,194,304 +2026-06-23 23:42:19,117 - Total optimizing variables: 278,728 +2026-06-23 23:42:19,118 - Overdetermined ratio : 15.05 +2026-06-23 23:42:19,118 - +2026-06-23 23:42:19,118 - ### Model behavior ### +2026-06-23 23:42:19,118 - Tilt propagator : False +2026-06-23 23:42:19,118 - Change slice thickness : False +2026-06-23 23:42:19,118 - Detector blur : False +2026-06-23 23:42:19,118 - Preload data : True +2026-06-23 23:42:19,118 - On-the-fly meas padding : False +2026-06-23 23:42:19,118 - On-the-fly meas resample : False +2026-06-23 23:42:19,118 - On-the-fly simu match mode: None +2026-06-23 23:42:19,118 - +2026-06-23 23:42:19,160 - ### Done initializing PtychoModel model ### +2026-06-23 23:42:19,160 - +2026-06-23 23:42:19,160 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-23 23:42:19,160 - +2026-06-23 23:42:19,160 - ### Generating indices, batches, and output_path ### +2026-06-23 23:42:19,162 - d90 = 51.000 px or 10.200 Ang +2026-06-23 23:42:19,162 - Selecting indices with the 'full' mode +2026-06-23 23:42:19,620 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-23 23:42:19,695 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-23 23:42:19,695 - Original recon_dir_affixes = ['default'] +2026-06-23 23:42:19,695 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-23 23:42:19,702 - Path corrected for compatibility: +2026-06-23 23:42:19,702 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi32_336_C34_-1.18e+04_phi34_116_C41_-4.44e+05_phi41_332_C43_2.34e+05_phi43_56.6_C45_-3e+05_phi45_128_C50_1.23e+07_C52_-1.78e+07_phi52_330_C54_1.03e+06_phi54_356_C56_-1.6e+07_phi56_75.3 +2026-06-23 23:42:19,702 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3 +2026-06-23 23:42:19,703 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3' is generated! +2026-06-23 23:42:19,856 - +2026-06-23 23:42:19,857 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/20260623_234219_ptyrad_log.txt ### +2026-06-23 23:42:19,857 - +2026-06-23 23:42:19,859 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-23 23:42:19,859 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-23 23:42:19,859 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-23 23:42:21,039 - Iter: 1, Total Loss: 1.0180, loss_single: 1.0180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.432 sec +2026-06-23 23:42:21,077 - Iter: 2, Total Loss: 0.9724, loss_single: 0.9724, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-23 23:42:21,114 - Iter: 3, Total Loss: 0.9346, loss_single: 0.9346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:42:21,150 - Iter: 4, Total Loss: 0.9055, loss_single: 0.9055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,186 - Iter: 5, Total Loss: 0.8820, loss_single: 0.8820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,221 - Iter: 6, Total Loss: 0.8534, loss_single: 0.8534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,256 - Iter: 7, Total Loss: 0.8190, loss_single: 0.8190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,292 - Iter: 8, Total Loss: 0.7906, loss_single: 0.7906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,327 - Iter: 9, Total Loss: 0.7642, loss_single: 0.7642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,362 - Iter: 10, Total Loss: 0.7377, loss_single: 0.7377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,398 - Iter: 11, Total Loss: 0.7158, loss_single: 0.7158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,467 - Iter: 12, Total Loss: 0.6924, loss_single: 0.6924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,502 - Iter: 13, Total Loss: 0.6651, loss_single: 0.6651, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,537 - Iter: 14, Total Loss: 0.6349, loss_single: 0.6349, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,573 - Iter: 15, Total Loss: 0.6029, loss_single: 0.6029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,608 - Iter: 16, Total Loss: 0.5762, loss_single: 0.5762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,644 - Iter: 17, Total Loss: 0.5576, loss_single: 0.5576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,682 - Iter: 18, Total Loss: 0.5393, loss_single: 0.5393, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-23 23:42:21,718 - Iter: 19, Total Loss: 0.5207, loss_single: 0.5207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,753 - Iter: 20, Total Loss: 0.5062, loss_single: 0.5062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,789 - Iter: 21, Total Loss: 0.4934, loss_single: 0.4934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,824 - Iter: 22, Total Loss: 0.4823, loss_single: 0.4823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,859 - Iter: 23, Total Loss: 0.4735, loss_single: 0.4735, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,895 - Iter: 24, Total Loss: 0.4633, loss_single: 0.4633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:42:21,930 - Iter: 25, Total Loss: 0.4534, loss_single: 0.4534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:21,965 - Iter: 26, Total Loss: 0.4456, loss_single: 0.4456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,001 - Iter: 27, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,036 - Iter: 28, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,071 - Iter: 29, Total Loss: 0.4296, loss_single: 0.4296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,107 - Iter: 30, Total Loss: 0.4246, loss_single: 0.4246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,143 - Iter: 31, Total Loss: 0.4207, loss_single: 0.4207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,181 - Iter: 32, Total Loss: 0.4175, loss_single: 0.4175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-23 23:42:22,217 - Iter: 33, Total Loss: 0.4143, loss_single: 0.4143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,253 - Iter: 34, Total Loss: 0.4110, loss_single: 0.4110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,288 - Iter: 35, Total Loss: 0.4077, loss_single: 0.4077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,324 - Iter: 36, Total Loss: 0.4049, loss_single: 0.4049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,359 - Iter: 37, Total Loss: 0.4024, loss_single: 0.4024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,394 - Iter: 38, Total Loss: 0.4000, loss_single: 0.4000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,430 - Iter: 39, Total Loss: 0.3980, loss_single: 0.3980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,465 - Iter: 40, Total Loss: 0.3961, loss_single: 0.3961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,504 - Iter: 41, Total Loss: 0.3947, loss_single: 0.3947, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,539 - Iter: 42, Total Loss: 0.3935, loss_single: 0.3935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,575 - Iter: 43, Total Loss: 0.3922, loss_single: 0.3922, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,610 - Iter: 44, Total Loss: 0.3910, loss_single: 0.3910, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,646 - Iter: 45, Total Loss: 0.3900, loss_single: 0.3900, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,681 - Iter: 46, Total Loss: 0.3891, loss_single: 0.3891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,717 - Iter: 47, Total Loss: 0.3880, loss_single: 0.3880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,755 - Iter: 48, Total Loss: 0.3869, loss_single: 0.3869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-23 23:42:22,791 - Iter: 49, Total Loss: 0.3858, loss_single: 0.3858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,826 - Iter: 50, Total Loss: 0.3847, loss_single: 0.3847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,862 - Iter: 51, Total Loss: 0.3837, loss_single: 0.3837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,898 - Iter: 52, Total Loss: 0.3827, loss_single: 0.3827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,933 - Iter: 53, Total Loss: 0.3817, loss_single: 0.3817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:22,968 - Iter: 54, Total Loss: 0.3809, loss_single: 0.3809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,004 - Iter: 55, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,039 - Iter: 56, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,074 - Iter: 57, Total Loss: 0.3784, loss_single: 0.3784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,110 - Iter: 58, Total Loss: 0.3777, loss_single: 0.3777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,145 - Iter: 59, Total Loss: 0.3769, loss_single: 0.3769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,180 - Iter: 60, Total Loss: 0.3760, loss_single: 0.3760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,215 - Iter: 61, Total Loss: 0.3752, loss_single: 0.3752, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,253 - Iter: 62, Total Loss: 0.3744, loss_single: 0.3744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-23 23:42:23,289 - Iter: 63, Total Loss: 0.3738, loss_single: 0.3738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:42:23,325 - Iter: 64, Total Loss: 0.3730, loss_single: 0.3730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,360 - Iter: 65, Total Loss: 0.3723, loss_single: 0.3723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,395 - Iter: 66, Total Loss: 0.3716, loss_single: 0.3716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,431 - Iter: 67, Total Loss: 0.3708, loss_single: 0.3708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,466 - Iter: 68, Total Loss: 0.3701, loss_single: 0.3701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,501 - Iter: 69, Total Loss: 0.3694, loss_single: 0.3694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,536 - Iter: 70, Total Loss: 0.3688, loss_single: 0.3688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,571 - Iter: 71, Total Loss: 0.3681, loss_single: 0.3681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,606 - Iter: 72, Total Loss: 0.3673, loss_single: 0.3673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,642 - Iter: 73, Total Loss: 0.3667, loss_single: 0.3667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,677 - Iter: 74, Total Loss: 0.3661, loss_single: 0.3661, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,712 - Iter: 75, Total Loss: 0.3654, loss_single: 0.3654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,747 - Iter: 76, Total Loss: 0.3646, loss_single: 0.3646, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,783 - Iter: 77, Total Loss: 0.3639, loss_single: 0.3639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,821 - Iter: 78, Total Loss: 0.3633, loss_single: 0.3633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-23 23:42:23,856 - Iter: 79, Total Loss: 0.3627, loss_single: 0.3627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:42:23,891 - Iter: 80, Total Loss: 0.3621, loss_single: 0.3621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,926 - Iter: 81, Total Loss: 0.3615, loss_single: 0.3615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,961 - Iter: 82, Total Loss: 0.3609, loss_single: 0.3609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:23,996 - Iter: 83, Total Loss: 0.3603, loss_single: 0.3603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,031 - Iter: 84, Total Loss: 0.3597, loss_single: 0.3597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,067 - Iter: 85, Total Loss: 0.3592, loss_single: 0.3592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,103 - Iter: 86, Total Loss: 0.3586, loss_single: 0.3586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,138 - Iter: 87, Total Loss: 0.3580, loss_single: 0.3580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,173 - Iter: 88, Total Loss: 0.3574, loss_single: 0.3574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,209 - Iter: 89, Total Loss: 0.3567, loss_single: 0.3567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,244 - Iter: 90, Total Loss: 0.3563, loss_single: 0.3563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,280 - Iter: 91, Total Loss: 0.3558, loss_single: 0.3558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,315 - Iter: 92, Total Loss: 0.3553, loss_single: 0.3553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,351 - Iter: 93, Total Loss: 0.3548, loss_single: 0.3548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:42:24,386 - Iter: 94, Total Loss: 0.3544, loss_single: 0.3544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,422 - Iter: 95, Total Loss: 0.3539, loss_single: 0.3539, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,457 - Iter: 96, Total Loss: 0.3535, loss_single: 0.3535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,492 - Iter: 97, Total Loss: 0.3530, loss_single: 0.3530, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,528 - Iter: 98, Total Loss: 0.3525, loss_single: 0.3525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,563 - Iter: 99, Total Loss: 0.3519, loss_single: 0.3519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,599 - Iter: 100, Total Loss: 0.3515, loss_single: 0.3515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:42:24,714 - Saving summary figures for iter 100 +2026-06-23 23:42:28,376 - ### Finished 100 iterations, averaged iter_t = 0.039138 with std = 0.039 ### +2026-06-23 23:42:28,376 - +2026-06-23 23:42:28,376 - ### The PtyRADSolver is finished in 9.330 sec ### +2026-06-23 23:42:28,376 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/f005_simulation_data6_b0cc2a63__sample_000013.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/f005_simulation_data6_b0cc2a63__sample_000013.yaml new file mode 100644 index 0000000000000000000000000000000000000000..896f2c32e1e6266ab6113c7adb1184f775ee1f80 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/f005_simulation_data6_b0cc2a63__sample_000013.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.91810131072998 + probe_aberrations: + C10: -401.2518310546875 + C12: -13.184317588806152 + C21: 187.379150390625 + C23: -814.6881713867188 + C30: 10371734.0 + C32: 10346.3359375 + C34: -11791.021484375 + C41: -443766.78125 + C43: 234443.1875 + C45: -299696.40625 + C50: 12290260.0 + C52: -17827392.0 + C54: 1032114.5625 + C56: -15998074.0 + phi12: 72.35294519875377 + phi21: 351.03355624157336 + phi23: 252.04127501550408 + phi32: 336.4461573066371 + phi34: 116.39699658985245 + phi41: 331.93601947313755 + phi43: 56.5521153464405 + phi45: 128.45260832400513 + phi52: 330.0651760179577 + phi54: 356.4568630463469 + phi56: 75.25121302964362 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/f005_simulation_data6_b0cc2a63__sample_000013_measurement.h5 + key: measurement + random_seed: 20260626 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013 + recon_dir_affixes: + - default + prefix: f005_simulation_data6_b0cc2a63__sample_000013 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..082b3ee3e7956f47514666da5d48963fabf66c25 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/20260623_234333_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/20260623_234333_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..226a81fe059da858f24cf326fb0e02391bc95598 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/20260623_234333_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-23 23:43:31,525 - ### PtyRAD LoggingManager configuration ### +2026-06-23 23:43:31,526 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-23 23:43:31,526 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-23 23:43:31,526 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-23 23:43:31,526 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-23 23:43:31,526 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-23 23:43:31,526 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-23 23:43:31,526 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-23 23:43:31,526 - +2026-06-23 23:43:31,633 - ### Initializing HuggingFace accelerator ### +2026-06-23 23:43:31,633 - Accelerator.distributed_type = DistributedType.NO +2026-06-23 23:43:31,633 - Accelerator.num_process = 1 +2026-06-23 23:43:31,633 - Accelerator.mixed_precision = no +2026-06-23 23:43:31,644 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-23 23:43:31,644 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-23 23:43:31,644 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-23 23:43:31,644 - +2026-06-23 23:43:31,645 - ### System information ### +2026-06-23 23:43:31,645 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-23 23:43:31,645 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-23 23:43:31,645 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-23 23:43:31,645 - Machine: x86_64 +2026-06-23 23:43:31,645 - Processor: x86_64 +2026-06-23 23:43:31,645 - Available CPU cores: 8 +2026-06-23 23:43:31,645 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-23 23:43:31,645 - +2026-06-23 23:43:31,645 - ### GPU information ### +2026-06-23 23:43:31,645 - CUDA Available: True +2026-06-23 23:43:31,645 - CUDA Version: 13.0 +2026-06-23 23:43:31,645 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-23 23:43:31,646 - CUDA Compute Capability: ['8.0'] +2026-06-23 23:43:31,646 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-23 23:43:31,646 - In addition, Triton does not directly support Windows. +2026-06-23 23:43:31,646 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-23 23:43:31,674 - MIG (Multi-Instance GPU) mode = False +2026-06-23 23:43:31,674 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-23 23:43:31,674 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-23 23:43:31,674 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-23 23:43:31,674 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-23 23:43:31,674 - +2026-06-23 23:43:31,674 - ### Python information ### +2026-06-23 23:43:31,675 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-23 23:43:31,675 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-23 23:43:31,675 - +2026-06-23 23:43:31,675 - ### Packages information ### +2026-06-23 23:43:31,675 - Numpy Version (metadata): 2.4.6 +2026-06-23 23:43:31,676 - PyTorch Version (metadata): 2.12.0 +2026-06-23 23:43:31,677 - Optuna Version (metadata): 4.9.0 +2026-06-23 23:43:31,677 - Accelerate Version (metadata): 1.13.0 +2026-06-23 23:43:31,678 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-23 23:43:31,678 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-23 23:43:31,678 - +2026-06-23 23:43:31,678 - ### Loading params file ### +2026-06-23 23:43:31,678 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/f035_simulation_data3_a89912d8__sample_000044.yaml +2026-06-23 23:43:31,684 - validate = True: Filling defaults and validating the params file... +2026-06-23 23:43:31,685 - Success! Params file validated and defaults applied. +2026-06-23 23:43:31,685 - +2026-06-23 23:43:31,686 - ### Setting GPU Device ### +2026-06-23 23:43:31,686 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-23 23:43:31,686 - +2026-06-23 23:43:31,686 - Random seed: 20260631 provided by params file +2026-06-23 23:43:31,686 - ### Initializing Initializer ### +2026-06-23 23:43:31,686 - init_params are displayed below: +2026-06-23 23:43:31,686 - random_seed: 20260631 +2026-06-23 23:43:31,686 - probe_illum_type: electron +2026-06-23 23:43:31,686 - probe_kv: 200.0 +2026-06-23 23:43:31,686 - probe_conv_angle: 16.78782081604004 +2026-06-23 23:43:31,686 - probe_aberrations: {'C10': -301.797, 'C12': 20.759, 'phi12': 132.233, 'C21': -175.547, 'phi21': 259.946, 'C23': 585.258, 'phi23': 37.068, 'C30': 2725116.5, 'C32': 10432.408, 'phi32': 247.103, 'C34': -9645.538, 'phi34': 242.124, 'C41': -415219.781, 'phi41': 337.211, 'C43': -216888.578, 'phi43': 48.101, 'C45': -219386.953, 'phi45': 275.992, 'C50': -44661052.0, 'C52': -19655062.0, 'phi52': 186.777, 'C54': -10497457.0, 'phi54': 122.675, 'C56': -6877892.0, 'phi56': 244.984} +2026-06-23 23:43:31,686 - beam_kev: None +2026-06-23 23:43:31,686 - probe_dRn: None +2026-06-23 23:43:31,686 - probe_Rn: None +2026-06-23 23:43:31,686 - probe_D_H: None +2026-06-23 23:43:31,687 - probe_D_FZP: None +2026-06-23 23:43:31,687 - probe_Ls: None +2026-06-23 23:43:31,687 - meas_Npix: 128 +2026-06-23 23:43:31,687 - pos_N_scans: 256 +2026-06-23 23:43:31,687 - pos_N_scan_slow: 16 +2026-06-23 23:43:31,687 - pos_N_scan_fast: 16 +2026-06-23 23:43:31,687 - pos_scan_step_size: 0.4053440988063812 +2026-06-23 23:43:31,687 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-23 23:43:31,687 - probe_pmode_max: 6 +2026-06-23 23:43:31,687 - probe_pmode_init_pows: [0.02] +2026-06-23 23:43:31,687 - obj_omode_max: 1 +2026-06-23 23:43:31,687 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-23 23:43:31,687 - obj_Nlayer: 1 +2026-06-23 23:43:31,687 - obj_slice_thickness: 20.0 +2026-06-23 23:43:31,687 - simu_Npix: None +2026-06-23 23:43:31,687 - simu_match_mode: None +2026-06-23 23:43:31,687 - meas_permute: None +2026-06-23 23:43:31,687 - meas_reshape: [256, 128, 128] +2026-06-23 23:43:31,687 - meas_flipT: [0, 0, 0] +2026-06-23 23:43:31,687 - meas_crop: None +2026-06-23 23:43:31,687 - meas_pad: None +2026-06-23 23:43:31,687 - meas_resample: None +2026-06-23 23:43:31,687 - meas_add_source_size: None +2026-06-23 23:43:31,687 - meas_add_detector_blur: None +2026-06-23 23:43:31,687 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-23 23:43:31,687 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-23 23:43:31,687 - meas_add_poisson_noise: None +2026-06-23 23:43:31,687 - meas_export: None +2026-06-23 23:43:31,687 - probe_permute: None +2026-06-23 23:43:31,687 - probe_z_shift: None +2026-06-23 23:43:31,687 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-23 23:43:31,687 - pos_scan_flipT: None +2026-06-23 23:43:31,687 - pos_scan_affine: None +2026-06-23 23:43:31,687 - pos_scan_rand_std: 0.15 +2026-06-23 23:43:31,687 - obj_z_crop: None +2026-06-23 23:43:31,687 - obj_z_pad: None +2026-06-23 23:43:31,687 - obj_z_resample: None +2026-06-23 23:43:31,687 - meas_source: file +2026-06-23 23:43:31,687 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/f035_simulation_data3_a89912d8__sample_000044_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-23 23:43:31,688 - probe_source: simu +2026-06-23 23:43:31,688 - probe_params: None +2026-06-23 23:43:31,688 - pos_source: simu +2026-06-23 23:43:31,688 - pos_params: None +2026-06-23 23:43:31,688 - obj_source: simu +2026-06-23 23:43:31,688 - obj_params: None +2026-06-23 23:43:31,688 - tilt_source: simu +2026-06-23 23:43:31,688 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-23 23:43:31,688 - +2026-06-23 23:43:31,688 - ### Initializing cache ### +2026-06-23 23:43:31,688 - use_cached_obj = False +2026-06-23 23:43:31,688 - use_cached_probe = False +2026-06-23 23:43:31,688 - use_cached_pos = False +2026-06-23 23:43:31,688 - +2026-06-23 23:43:31,688 - ### Initializing measurements ### +2026-06-23 23:43:31,688 - Loading measurements from source = 'file' +2026-06-23 23:43:31,688 - Detected measurement file type = '.h5' +2026-06-23 23:43:31,763 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-23 23:43:31,763 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-23 23:43:31,764 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0016) +2026-06-23 23:43:31,764 - Reshaping measurements to shape = [256, 128, 128] +2026-06-23 23:43:31,764 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-23 23:43:31,766 - No negative values found in measurements. Skipping non-neg correction. +2026-06-23 23:43:31,766 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-23 23:43:31,767 - Normalizing by max of the 2D mean pattern intensity: 0.001095339 +2026-06-23 23:43:31,768 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-23 23:43:31,769 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0558, 1.4853) +2026-06-23 23:43:31,770 - No negative values found in measurements. Skipping non-neg correction. +2026-06-23 23:43:31,771 - Pattern total int. statistics (min, mean, max) = (905.4617, 913.5955, 921.2964), with min/max = 98.3% +2026-06-23 23:43:31,772 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0558, 1.4853) +2026-06-23 23:43:31,772 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-23 23:43:31,772 - +2026-06-23 23:43:31,772 - ### Setting up calibration ### +2026-06-23 23:43:31,772 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-23 23:43:31,772 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-23 23:43:31,772 - Radius of fitted bright field disk (RBF) = 17.00 px with meas_Npix = 128 +2026-06-23 23:43:31,772 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.2656 +2026-06-23 23:43:31,773 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-23 23:43:31,773 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-23 23:43:32,005 - Initial guess: center=(63.62, 63.63), radius=17.00, Gaussian blur std=0.50 +2026-06-23 23:43:32,015 - Final fit: center=(63.62, 63.63), radius=17.00, Gaussian blur std=0.59 +2026-06-23 23:43:32,015 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 17.14 px with Npix = 128 +2026-06-23 23:43:32,015 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-23 23:43:32,015 - +2026-06-23 23:43:32,015 - ### Setting init_variables dict ### +2026-06-23 23:43:32,015 - Derived values given input init_params: +2026-06-23 23:43:32,015 - kv = 200.0 kV +2026-06-23 23:43:32,015 - wavelength = 0.0251 Ang +2026-06-23 23:43:32,015 - conv_angle = 16.78782081604004 mrad +2026-06-23 23:43:32,015 - Npix = 128 px +2026-06-23 23:43:32,015 - dk = 0.0391 Ang^-1 +2026-06-23 23:43:32,015 - kMax = 2.5000 Ang^-1 +2026-06-23 23:43:32,015 - da = 0.9797 mrad +2026-06-23 23:43:32,015 - angleMax = 62.6984 mrad +2026-06-23 23:43:32,015 - RBF = 17.1363 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-23 23:43:32,015 - n_alpha = 3.7348 (# conv_angle) +2026-06-23 23:43:32,015 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-23 23:43:32,015 - Rayleigh-limited resolution = 0.9113 Ang (0.61*lambda/alpha for focused probe ) +2026-06-23 23:43:32,015 - Real space probe extent = 25.6000 Ang +2026-06-23 23:43:32,016 - +2026-06-23 23:43:32,016 - ### Initializing probe ### +2026-06-23 23:43:32,016 - Loading probe from source = 'simu' +2026-06-23 23:43:32,016 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-23 23:43:32,016 - Start simulating STEM probe +2026-06-23 23:43:32,016 - kv = 200.0 kV +2026-06-23 23:43:32,016 - wavelength = 0.0251 Ang +2026-06-23 23:43:32,016 - conv_angle = 16.78782081604004 mrad +2026-06-23 23:43:32,016 - Npix = 128 px +2026-06-23 23:43:32,016 - dk = 0.0391 Ang^-1 +2026-06-23 23:43:32,016 - kMax = 2.5000 Ang^-1 +2026-06-23 23:43:32,016 - alpha_max = 62.6984 mrad +2026-06-23 23:43:32,016 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-23 23:43:32,016 - Rayleigh-limited resolution = 0.9113 Ang (0.61*lambda/alpha for focused probe ) +2026-06-23 23:43:32,016 - Real space probe extent = 25.6000 Ang +2026-06-23 23:43:32,016 - Krivanek Haider Magnitude Angle (°) Description +2026-06-23 23:43:32,016 - ------------------------------------------------------------------------------------ +2026-06-23 23:43:32,016 - C1,0 C1 -301.7970 - Defocus (C10 = -df) +2026-06-23 23:43:32,016 - C1,2 A1 20.7590 132.23 2-fold astigmatism +2026-06-23 23:43:32,016 - C2,1 3*B2 -175.5470 259.95 Axial coma +2026-06-23 23:43:32,016 - C2,3 A2 585.2580 37.07 3-fold astigmatism +2026-06-23 23:43:32,016 - C3,0 C3 2725116.5000 - Spherical aberration +2026-06-23 23:43:32,016 - C3,2 4*S3 10432.4080 247.10 Axial star aberration +2026-06-23 23:43:32,016 - C3,4 A3 -9645.5380 242.12 4-fold astigmatism +2026-06-23 23:43:32,017 - C4,1 4*B4 -415219.7810 337.21 Axial coma(4th) +2026-06-23 23:43:32,017 - C4,3 4*D4 -216888.5780 48.10 3-lobe aberration +2026-06-23 23:43:32,017 - C4,5 A4 -219386.9530 275.99 5-fold astigmatism +2026-06-23 23:43:32,017 - C5,0 C5 -44661052.0000 - Spherical aberration (5th) +2026-06-23 23:43:32,017 - C5,2 6*S5 -19655062.0000 186.78 Axial star aberration(5th) +2026-06-23 23:43:32,017 - C5,4 6*R5 -10497457.0000 122.67 4-lobe aberration +2026-06-23 23:43:32,017 - C5,6 A5 -6877892.0000 244.98 6-fold astigmatism +2026-06-23 23:43:32,020 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-23 23:43:32,020 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-23 23:43:32,020 - Creating 5 new probe modes from the major mode +2026-06-23 23:43:32,020 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-23 23:43:32,116 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-23 23:43:32,118 - Orthogonalizing 6 pmodes +2026-06-23 23:43:32,121 - Sorting 6 pmodes by their intensities +2026-06-23 23:43:32,121 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-23 23:43:32,122 - sum(|probe_data|**2) = 913.60, while meas_total_ints (min, mean, max) = (905.4617, 913.5955, 921.2964) +2026-06-23 23:43:32,122 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-23 23:43:32,122 - +2026-06-23 23:43:32,122 - ### Initializing probe positions ### +2026-06-23 23:43:32,122 - Loading probe positions from source = 'simu' +2026-06-23 23:43:32,122 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-23 23:43:32,122 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.4053, N_scan_fast = 16, N_scan_slow = 16 +2026-06-23 23:43:32,122 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-23 23:43:32,124 - crop_pos (N,2) = int16, (256, 2) +2026-06-23 23:43:32,124 - crop_pos 1st and last px coords (y,x) = ([16, 16], [46, 46]) +2026-06-23 23:43:32,125 - crop_pos extent (Ang) = [6. 6.] +2026-06-23 23:43:32,125 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-23 23:43:32,125 - +2026-06-23 23:43:32,125 - ### Initializing object ### +2026-06-23 23:43:32,125 - Loading object from source = 'simu' +2026-06-23 23:43:32,125 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-23 23:43:32,126 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-23 23:43:32,126 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 190, 190) +2026-06-23 23:43:32,126 - object extent (Z, Y, X) (Ang) = [20. 38. 38.] +2026-06-23 23:43:32,126 - +2026-06-23 23:43:32,126 - ### Initializing omode_occu from 'uniform' ### +2026-06-23 23:43:32,126 - omode_occu (omode) = float32, (1,) +2026-06-23 23:43:32,127 - +2026-06-23 23:43:32,127 - ### Initializing H (Fresnel propagator) ### +2026-06-23 23:43:32,127 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-23 23:43:32,127 - H (Ky, Kx) = complex64, (128, 128) +2026-06-23 23:43:32,127 - +2026-06-23 23:43:32,127 - ### Initializing obj tilts from = 'simu' ### +2026-06-23 23:43:32,127 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-23 23:43:32,127 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-23 23:43:32,127 - +2026-06-23 23:43:32,127 - ### Checking consistency between input params with the initialized variables ### +2026-06-23 23:43:32,128 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-23 23:43:32,128 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-23 23:43:32,128 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-23 23:43:32,128 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-23 23:43:32,128 - crop positions (yx_min=[16 16], yx_max=[174 174]) are well contained inside object canvas (Ny,Nx) = (190, 190). +2026-06-23 23:43:32,128 - obj_tilts is consistent with either 1 or N_scans +2026-06-23 23:43:32,128 - Pass the consistency check of initialized variables, initialization is done! +2026-06-23 23:43:32,128 - +2026-06-23 23:43:32,128 - ### Collecting reconstruction provenance ### +2026-06-23 23:43:32,128 - Reconstruction provenance is collected and initialized. +2026-06-23 23:43:32,128 - +2026-06-23 23:43:32,128 - ### Initializing loss function ### +2026-06-23 23:43:32,128 - Active loss types: +2026-06-23 23:43:32,128 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-23 23:43:32,128 - +2026-06-23 23:43:32,128 - ### Initializing constraint function ### +2026-06-23 23:43:32,128 - Active constraint types: +2026-06-23 23:43:32,128 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-23 23:43:32,128 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-23 23:43:32,128 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-23 23:43:32,128 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-23 23:43:32,129 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-23 23:43:32,129 - +2026-06-23 23:43:32,129 - ### Done initializing PtyRADSolver ### +2026-06-23 23:43:32,129 - +2026-06-23 23:43:32,254 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-23 23:43:32,254 - +2026-06-23 23:43:32,254 - ### Initializing PtychoModel model ### +2026-06-23 23:43:32,324 - ### PtychoModel optimizable variables ### +2026-06-23 23:43:32,324 - obja : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:43:32,324 - objp : torch.Size([1, 1, 190, 190]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:43:32,324 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-23 23:43:32,324 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-23 23:43:32,324 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-23 23:43:32,324 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-23 23:43:32,324 - +2026-06-23 23:43:32,324 - ### Optimizable variables statitsics ### +2026-06-23 23:43:32,324 - Total measurement values : 4,194,304 +2026-06-23 23:43:32,324 - Total optimizing variables: 269,320 +2026-06-23 23:43:32,324 - Overdetermined ratio : 15.57 +2026-06-23 23:43:32,325 - +2026-06-23 23:43:32,325 - ### Model behavior ### +2026-06-23 23:43:32,325 - Tilt propagator : False +2026-06-23 23:43:32,325 - Change slice thickness : False +2026-06-23 23:43:32,325 - Detector blur : False +2026-06-23 23:43:32,325 - Preload data : True +2026-06-23 23:43:32,325 - On-the-fly meas padding : False +2026-06-23 23:43:32,325 - On-the-fly meas resample : False +2026-06-23 23:43:32,325 - On-the-fly simu match mode: None +2026-06-23 23:43:32,325 - +2026-06-23 23:43:32,367 - ### Done initializing PtychoModel model ### +2026-06-23 23:43:32,367 - +2026-06-23 23:43:32,367 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-23 23:43:32,367 - +2026-06-23 23:43:32,367 - ### Generating indices, batches, and output_path ### +2026-06-23 23:43:32,369 - d90 = 57.000 px or 11.400 Ang +2026-06-23 23:43:32,369 - Selecting indices with the 'full' mode +2026-06-23 23:43:32,827 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-23 23:43:32,900 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-23 23:43:32,900 - Original recon_dir_affixes = ['default'] +2026-06-23 23:43:32,900 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-23 23:43:32,906 - Path corrected for compatibility: +2026-06-23 23:43:32,906 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32_1.04e+04_phi32_247_C34_-9.65e+03_phi34_242_C41_-4.15e+05_phi41_337_C43_-2.17e+05_phi43_48.1_C45_-2.19e+05_phi45_276_C50_-4.47e+07_C52_-1.97e+07_phi52_187_C54_-1.05e+07_phi54_123_C56_-6.88e+06_phi56_245 +2026-06-23 23:43:32,906 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245 +2026-06-23 23:43:32,907 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245' is generated! +2026-06-23 23:43:33,057 - +2026-06-23 23:43:33,058 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/20260623_234333_ptyrad_log.txt ### +2026-06-23 23:43:33,058 - +2026-06-23 23:43:33,059 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-23 23:43:33,059 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-23 23:43:33,059 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-23 23:43:34,245 - Iter: 1, Total Loss: 0.6212, loss_single: 0.6212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-23 23:43:34,282 - Iter: 2, Total Loss: 0.5980, loss_single: 0.5980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:43:34,318 - Iter: 3, Total Loss: 0.5787, loss_single: 0.5787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,354 - Iter: 4, Total Loss: 0.5607, loss_single: 0.5607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,389 - Iter: 5, Total Loss: 0.5421, loss_single: 0.5421, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,424 - Iter: 6, Total Loss: 0.5228, loss_single: 0.5228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,459 - Iter: 7, Total Loss: 0.5034, loss_single: 0.5034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:43:34,495 - Iter: 8, Total Loss: 0.4850, loss_single: 0.4850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,529 - Iter: 9, Total Loss: 0.4687, loss_single: 0.4687, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:43:34,564 - Iter: 10, Total Loss: 0.4547, loss_single: 0.4547, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,600 - Iter: 11, Total Loss: 0.4415, loss_single: 0.4415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,635 - Iter: 12, Total Loss: 0.4299, loss_single: 0.4299, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,670 - Iter: 13, Total Loss: 0.4196, loss_single: 0.4196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,705 - Iter: 14, Total Loss: 0.4098, loss_single: 0.4098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,741 - Iter: 15, Total Loss: 0.4003, loss_single: 0.4003, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-23 23:43:34,776 - Iter: 16, Total Loss: 0.3908, loss_single: 0.3908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,812 - Iter: 17, Total Loss: 0.3821, loss_single: 0.3821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,847 - Iter: 18, Total Loss: 0.3742, loss_single: 0.3742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,882 - Iter: 19, Total Loss: 0.3670, loss_single: 0.3670, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,917 - Iter: 20, Total Loss: 0.3601, loss_single: 0.3601, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:43:34,952 - Iter: 21, Total Loss: 0.3542, loss_single: 0.3542, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:34,988 - Iter: 22, Total Loss: 0.3505, loss_single: 0.3505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,022 - Iter: 23, Total Loss: 0.3475, loss_single: 0.3475, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:43:35,057 - Iter: 24, Total Loss: 0.3447, loss_single: 0.3447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,092 - Iter: 25, Total Loss: 0.3420, loss_single: 0.3420, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,127 - Iter: 26, Total Loss: 0.3388, loss_single: 0.3388, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,163 - Iter: 27, Total Loss: 0.3356, loss_single: 0.3356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,198 - Iter: 28, Total Loss: 0.3336, loss_single: 0.3336, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,233 - Iter: 29, Total Loss: 0.3318, loss_single: 0.3318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,268 - Iter: 30, Total Loss: 0.3301, loss_single: 0.3301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,303 - Iter: 31, Total Loss: 0.3287, loss_single: 0.3287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,338 - Iter: 32, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,373 - Iter: 33, Total Loss: 0.3253, loss_single: 0.3253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,408 - Iter: 34, Total Loss: 0.3239, loss_single: 0.3239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,443 - Iter: 35, Total Loss: 0.3225, loss_single: 0.3225, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,478 - Iter: 36, Total Loss: 0.3214, loss_single: 0.3214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,513 - Iter: 37, Total Loss: 0.3207, loss_single: 0.3207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,549 - Iter: 38, Total Loss: 0.3201, loss_single: 0.3201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,585 - Iter: 39, Total Loss: 0.3195, loss_single: 0.3195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,620 - Iter: 40, Total Loss: 0.3189, loss_single: 0.3189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,658 - Iter: 41, Total Loss: 0.3183, loss_single: 0.3183, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,693 - Iter: 42, Total Loss: 0.3178, loss_single: 0.3178, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-23 23:43:35,728 - Iter: 43, Total Loss: 0.3173, loss_single: 0.3173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,763 - Iter: 44, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,799 - Iter: 45, Total Loss: 0.3165, loss_single: 0.3165, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,834 - Iter: 46, Total Loss: 0.3162, loss_single: 0.3162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,869 - Iter: 47, Total Loss: 0.3159, loss_single: 0.3159, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,904 - Iter: 48, Total Loss: 0.3156, loss_single: 0.3156, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,939 - Iter: 49, Total Loss: 0.3154, loss_single: 0.3154, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:35,974 - Iter: 50, Total Loss: 0.3151, loss_single: 0.3151, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,010 - Iter: 51, Total Loss: 0.3149, loss_single: 0.3149, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,045 - Iter: 52, Total Loss: 0.3148, loss_single: 0.3148, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,081 - Iter: 53, Total Loss: 0.3146, loss_single: 0.3146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,116 - Iter: 54, Total Loss: 0.3144, loss_single: 0.3144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,152 - Iter: 55, Total Loss: 0.3143, loss_single: 0.3143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,187 - Iter: 56, Total Loss: 0.3142, loss_single: 0.3142, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,222 - Iter: 57, Total Loss: 0.3140, loss_single: 0.3140, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,257 - Iter: 58, Total Loss: 0.3139, loss_single: 0.3139, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:36,292 - 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Iter: 95, Total Loss: 0.3116, loss_single: 0.3116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,640 - Iter: 96, Total Loss: 0.3115, loss_single: 0.3115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,675 - Iter: 97, Total Loss: 0.3115, loss_single: 0.3115, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,710 - Iter: 98, Total Loss: 0.3114, loss_single: 0.3114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,745 - Iter: 99, Total Loss: 0.3114, loss_single: 0.3114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,780 - Iter: 100, Total Loss: 0.3114, loss_single: 0.3114, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-23 23:43:37,904 - Saving summary figures for iter 100 +2026-06-23 23:43:41,539 - ### Finished 100 iterations, averaged iter_t = 0.038844 with std = 0.040 ### +2026-06-23 23:43:41,539 - +2026-06-23 23:43:41,539 - ### The PtyRADSolver is finished in 9.286 sec ### +2026-06-23 23:43:41,539 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/f035_simulation_data3_a89912d8__sample_000044.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/f035_simulation_data3_a89912d8__sample_000044.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d41fa171317d7a7fb8148ef05891985a84bee520 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/f035_simulation_data3_a89912d8__sample_000044.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 16.78782081604004 + probe_aberrations: + C10: -301.79681396484375 + C12: 20.759498596191406 + C21: -175.54718017578125 + C23: 585.2575073242188 + C30: 2725116.5 + C32: 10432.408203125 + C34: -9645.5380859375 + C41: -415219.78125 + C43: -216888.578125 + C45: -219386.953125 + C50: -44661052.0 + C52: -19655062.0 + C54: -10497457.0 + C56: -6877892.0 + phi12: 132.23272187863532 + phi21: 259.94612614952666 + phi23: 37.06752541811841 + phi32: 247.10323949088163 + phi34: 242.12370373686218 + phi41: 337.210837965355 + phi43: 48.10075345616855 + phi45: 275.99248081193434 + phi52: 186.77735583554986 + phi54: 122.67477372017292 + phi56: 244.9843235650469 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.4053440988063812 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/f035_simulation_data3_a89912d8__sample_000044_measurement.h5 + key: measurement + random_seed: 20260631 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044 + recon_dir_affixes: + - default + prefix: f035_simulation_data3_a89912d8__sample_000044 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..3c630b1e6db3090e7100538337c0e87bbbc21b5f Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f035_simulation_data3_a89912d8__sample_000044/f035_simulation_data3_a89912d8__sample_000044_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-302_C12_20.8_phi12_132_C21_-176_phi21_260_C23_585_phi23_37.1_C30_2.73e+06_C32.88e+06_phi56_245/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/20260624_041930_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/20260624_041930_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..04fa509182dafd0e69046c2059feadb720c03cc7 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/20260624_041930_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:19:29,025 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:19:29,025 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:19:29,025 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:19:29,025 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:19:29,025 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:19:29,025 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:19:29,025 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:19:29,025 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:19:29,025 - +2026-06-24 04:19:29,133 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:19:29,133 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:19:29,133 - Accelerator.num_process = 1 +2026-06-24 04:19:29,133 - Accelerator.mixed_precision = no +2026-06-24 04:19:29,144 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:19:29,144 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:19:29,144 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:19:29,144 - +2026-06-24 04:19:29,144 - ### System information ### +2026-06-24 04:19:29,144 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:19:29,144 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:19:29,144 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:19:29,144 - Machine: x86_64 +2026-06-24 04:19:29,144 - Processor: x86_64 +2026-06-24 04:19:29,144 - Available CPU cores: 8 +2026-06-24 04:19:29,144 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:19:29,144 - +2026-06-24 04:19:29,144 - ### GPU information ### +2026-06-24 04:19:29,144 - CUDA Available: True +2026-06-24 04:19:29,144 - CUDA Version: 13.0 +2026-06-24 04:19:29,145 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:19:29,145 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:19:29,145 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:19:29,145 - In addition, Triton does not directly support Windows. +2026-06-24 04:19:29,145 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:19:29,161 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:19:29,161 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:19:29,161 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:19:29,161 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:19:29,161 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:19:29,161 - +2026-06-24 04:19:29,161 - ### Python information ### +2026-06-24 04:19:29,163 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:19:29,163 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:19:29,163 - +2026-06-24 04:19:29,163 - ### Packages information ### +2026-06-24 04:19:29,164 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:19:29,165 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:19:29,165 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:19:29,166 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:19:29,166 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:19:29,167 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:19:29,167 - +2026-06-24 04:19:29,167 - ### Loading params file ### +2026-06-24 04:19:29,167 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data10__sample_000007.yaml +2026-06-24 04:19:29,173 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:19:29,174 - Success! Params file validated and defaults applied. +2026-06-24 04:19:29,174 - +2026-06-24 04:19:29,174 - ### Setting GPU Device ### +2026-06-24 04:19:29,174 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:19:29,174 - +2026-06-24 04:19:29,174 - Random seed: 20261540 provided by params file +2026-06-24 04:19:29,175 - ### Initializing Initializer ### +2026-06-24 04:19:29,175 - init_params are displayed below: +2026-06-24 04:19:29,175 - random_seed: 20261540 +2026-06-24 04:19:29,175 - probe_illum_type: electron +2026-06-24 04:19:29,175 - probe_kv: 200.0 +2026-06-24 04:19:29,175 - probe_conv_angle: 9.433828353881836 +2026-06-24 04:19:29,175 - probe_aberrations: {'C10': -277.176, 'C12': -29.01, 'phi12': 227.839, 'C21': -299.118, 'phi21': 1.174, 'C23': -867.568, 'phi23': 157.803, 'C30': 12124196.0, 'C32': 10093.291, 'phi32': 331.191, 'C34': 3699.338, 'phi34': 306.201, 'C41': -72286.469, 'phi41': 308.534, 'C43': 380508.781, 'phi43': 3.869, 'C45': 243064.125, 'phi45': 116.57, 'C50': 16352149.0, 'C52': -11788933.0, 'phi52': 324.305, 'C54': 6396052.5, 'phi54': 173.131, 'C56': -7504720.0, 'phi56': 187.227} +2026-06-24 04:19:29,175 - beam_kev: None +2026-06-24 04:19:29,175 - probe_dRn: None +2026-06-24 04:19:29,175 - probe_Rn: None +2026-06-24 04:19:29,175 - probe_D_H: None +2026-06-24 04:19:29,175 - probe_D_FZP: None +2026-06-24 04:19:29,175 - probe_Ls: None +2026-06-24 04:19:29,175 - meas_Npix: 128 +2026-06-24 04:19:29,175 - pos_N_scans: 256 +2026-06-24 04:19:29,175 - pos_N_scan_slow: 16 +2026-06-24 04:19:29,175 - pos_N_scan_fast: 16 +2026-06-24 04:19:29,175 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:19:29,175 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:19:29,175 - probe_pmode_max: 6 +2026-06-24 04:19:29,175 - probe_pmode_init_pows: [0.02] +2026-06-24 04:19:29,175 - obj_omode_max: 1 +2026-06-24 04:19:29,175 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:19:29,175 - obj_Nlayer: 1 +2026-06-24 04:19:29,175 - obj_slice_thickness: 20.0 +2026-06-24 04:19:29,176 - simu_Npix: None +2026-06-24 04:19:29,176 - simu_match_mode: None +2026-06-24 04:19:29,176 - meas_permute: None +2026-06-24 04:19:29,176 - meas_reshape: [256, 128, 128] +2026-06-24 04:19:29,176 - meas_flipT: [0, 0, 0] +2026-06-24 04:19:29,176 - meas_crop: None +2026-06-24 04:19:29,176 - meas_pad: None +2026-06-24 04:19:29,176 - meas_resample: None +2026-06-24 04:19:29,176 - meas_add_source_size: None +2026-06-24 04:19:29,176 - meas_add_detector_blur: None +2026-06-24 04:19:29,176 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:19:29,176 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:19:29,176 - meas_add_poisson_noise: None +2026-06-24 04:19:29,176 - meas_export: None +2026-06-24 04:19:29,176 - probe_permute: None +2026-06-24 04:19:29,176 - probe_z_shift: None +2026-06-24 04:19:29,176 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:19:29,176 - pos_scan_flipT: None +2026-06-24 04:19:29,176 - pos_scan_affine: None +2026-06-24 04:19:29,176 - pos_scan_rand_std: 0.15 +2026-06-24 04:19:29,176 - obj_z_crop: None +2026-06-24 04:19:29,176 - obj_z_pad: None +2026-06-24 04:19:29,176 - obj_z_resample: None +2026-06-24 04:19:29,176 - meas_source: file +2026-06-24 04:19:29,176 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data10__sample_000007_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:19:29,176 - probe_source: simu +2026-06-24 04:19:29,176 - probe_params: None +2026-06-24 04:19:29,176 - pos_source: simu +2026-06-24 04:19:29,176 - pos_params: None +2026-06-24 04:19:29,176 - obj_source: simu +2026-06-24 04:19:29,176 - obj_params: None +2026-06-24 04:19:29,176 - tilt_source: simu +2026-06-24 04:19:29,176 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:19:29,176 - +2026-06-24 04:19:29,176 - ### Initializing cache ### +2026-06-24 04:19:29,176 - use_cached_obj = False +2026-06-24 04:19:29,176 - use_cached_probe = False +2026-06-24 04:19:29,176 - use_cached_pos = False +2026-06-24 04:19:29,176 - +2026-06-24 04:19:29,176 - ### Initializing measurements ### +2026-06-24 04:19:29,177 - Loading measurements from source = 'file' +2026-06-24 04:19:29,177 - Detected measurement file type = '.h5' +2026-06-24 04:19:29,249 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:19:29,249 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:19:29,250 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0043) +2026-06-24 04:19:29,250 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:19:29,251 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:19:29,251 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:19:29,251 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:19:29,252 - Normalizing by max of the 2D mean pattern intensity: 0.0034941647 +2026-06-24 04:19:29,253 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:19:29,254 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0175, 1.2429) +2026-06-24 04:19:29,254 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:19:29,256 - Pattern total int. statistics (min, mean, max) = (283.7774, 286.9723, 289.5375), with min/max = 98.0% +2026-06-24 04:19:29,257 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0175, 1.2429) +2026-06-24 04:19:29,257 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:19:29,257 - +2026-06-24 04:19:29,257 - ### Setting up calibration ### +2026-06-24 04:19:29,257 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:19:29,257 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:19:29,257 - Radius of fitted bright field disk (RBF) = 9.52 px with meas_Npix = 128 +2026-06-24 04:19:29,257 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1488 +2026-06-24 04:19:29,257 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:19:29,257 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:19:29,478 - Initial guess: center=(63.63, 63.63), radius=9.52, Gaussian blur std=0.50 +2026-06-24 04:19:29,488 - Final fit: center=(63.63, 63.63), radius=9.52, Gaussian blur std=0.60 +2026-06-24 04:19:29,488 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.63 px with Npix = 128 +2026-06-24 04:19:29,488 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:19:29,488 - +2026-06-24 04:19:29,488 - ### Setting init_variables dict ### +2026-06-24 04:19:29,488 - Derived values given input init_params: +2026-06-24 04:19:29,488 - kv = 200.0 kV +2026-06-24 04:19:29,488 - wavelength = 0.0251 Ang +2026-06-24 04:19:29,488 - conv_angle = 9.433828353881836 mrad +2026-06-24 04:19:29,488 - Npix = 128 px +2026-06-24 04:19:29,488 - dk = 0.0391 Ang^-1 +2026-06-24 04:19:29,488 - kMax = 2.5000 Ang^-1 +2026-06-24 04:19:29,488 - da = 0.9797 mrad +2026-06-24 04:19:29,488 - angleMax = 62.6984 mrad +2026-06-24 04:19:29,488 - RBF = 9.6297 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:19:29,488 - n_alpha = 6.6461 (# conv_angle) +2026-06-24 04:19:29,489 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:19:29,489 - Rayleigh-limited resolution = 1.6217 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:19:29,489 - Real space probe extent = 25.6000 Ang +2026-06-24 04:19:29,489 - +2026-06-24 04:19:29,489 - ### Initializing probe ### +2026-06-24 04:19:29,489 - Loading probe from source = 'simu' +2026-06-24 04:19:29,489 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:19:29,489 - Start simulating STEM probe +2026-06-24 04:19:29,489 - kv = 200.0 kV +2026-06-24 04:19:29,489 - wavelength = 0.0251 Ang +2026-06-24 04:19:29,489 - conv_angle = 9.433828353881836 mrad +2026-06-24 04:19:29,489 - Npix = 128 px +2026-06-24 04:19:29,489 - dk = 0.0391 Ang^-1 +2026-06-24 04:19:29,489 - kMax = 2.5000 Ang^-1 +2026-06-24 04:19:29,489 - alpha_max = 62.6984 mrad +2026-06-24 04:19:29,489 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:19:29,489 - Rayleigh-limited resolution = 1.6217 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:19:29,489 - Real space probe extent = 25.6000 Ang +2026-06-24 04:19:29,489 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:19:29,489 - ------------------------------------------------------------------------------------ +2026-06-24 04:19:29,489 - C1,0 C1 -277.1760 - Defocus (C10 = -df) +2026-06-24 04:19:29,489 - C1,2 A1 -29.0100 227.84 2-fold astigmatism +2026-06-24 04:19:29,489 - C2,1 3*B2 -299.1180 1.17 Axial coma +2026-06-24 04:19:29,489 - C2,3 A2 -867.5680 157.80 3-fold astigmatism +2026-06-24 04:19:29,490 - C3,0 C3 12124196.0000 - Spherical aberration +2026-06-24 04:19:29,490 - C3,2 4*S3 10093.2910 331.19 Axial star aberration +2026-06-24 04:19:29,490 - C3,4 A3 3699.3380 306.20 4-fold astigmatism +2026-06-24 04:19:29,490 - C4,1 4*B4 -72286.4690 308.53 Axial coma(4th) +2026-06-24 04:19:29,490 - C4,3 4*D4 380508.7810 3.87 3-lobe aberration +2026-06-24 04:19:29,490 - C4,5 A4 243064.1250 116.57 5-fold astigmatism +2026-06-24 04:19:29,490 - C5,0 C5 16352149.0000 - Spherical aberration (5th) +2026-06-24 04:19:29,490 - C5,2 6*S5 -11788933.0000 324.31 Axial star aberration(5th) +2026-06-24 04:19:29,490 - C5,4 6*R5 6396052.5000 173.13 4-lobe aberration +2026-06-24 04:19:29,490 - C5,6 A5 -7504720.0000 187.23 6-fold astigmatism +2026-06-24 04:19:29,492 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:19:29,493 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:19:29,493 - Creating 5 new probe modes from the major mode +2026-06-24 04:19:29,493 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:19:29,499 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:19:29,501 - Orthogonalizing 6 pmodes +2026-06-24 04:19:29,503 - Sorting 6 pmodes by their intensities +2026-06-24 04:19:29,504 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:19:29,505 - sum(|probe_data|**2) = 286.97, while meas_total_ints (min, mean, max) = (283.7774, 286.9723, 289.5375) +2026-06-24 04:19:29,505 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:19:29,505 - +2026-06-24 04:19:29,505 - ### Initializing probe positions ### +2026-06-24 04:19:29,505 - Loading probe positions from source = 'simu' +2026-06-24 04:19:29,505 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:19:29,505 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:19:29,505 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:19:29,507 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:19:29,507 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:19:29,507 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:19:29,507 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:19:29,507 - +2026-06-24 04:19:29,507 - ### Initializing object ### +2026-06-24 04:19:29,507 - Loading object from source = 'simu' +2026-06-24 04:19:29,507 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:19:29,509 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:19:29,509 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:19:29,509 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:19:29,509 - +2026-06-24 04:19:29,509 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:19:29,509 - omode_occu (omode) = float32, (1,) +2026-06-24 04:19:29,509 - +2026-06-24 04:19:29,509 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:19:29,509 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:19:29,510 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:19:29,510 - +2026-06-24 04:19:29,510 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:19:29,510 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:19:29,510 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:19:29,510 - +2026-06-24 04:19:29,510 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:19:29,510 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:19:29,510 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:19:29,510 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:19:29,510 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:19:29,511 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:19:29,511 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:19:29,511 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:19:29,511 - +2026-06-24 04:19:29,511 - ### Collecting reconstruction provenance ### +2026-06-24 04:19:29,511 - Reconstruction provenance is collected and initialized. +2026-06-24 04:19:29,511 - +2026-06-24 04:19:29,511 - ### Initializing loss function ### +2026-06-24 04:19:29,511 - Active loss types: +2026-06-24 04:19:29,511 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:19:29,511 - +2026-06-24 04:19:29,511 - ### Initializing constraint function ### +2026-06-24 04:19:29,511 - Active constraint types: +2026-06-24 04:19:29,511 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:19:29,511 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:19:29,511 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:19:29,511 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:19:29,511 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:19:29,511 - +2026-06-24 04:19:29,511 - ### Done initializing PtyRADSolver ### +2026-06-24 04:19:29,511 - +2026-06-24 04:19:29,637 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:19:29,638 - +2026-06-24 04:19:29,638 - ### Initializing PtychoModel model ### +2026-06-24 04:19:29,708 - ### PtychoModel optimizable variables ### +2026-06-24 04:19:29,708 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:19:29,709 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:19:29,709 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:19:29,709 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:19:29,709 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:19:29,709 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:19:29,709 - +2026-06-24 04:19:29,709 - ### Optimizable variables statitsics ### +2026-06-24 04:19:29,709 - Total measurement values : 4,194,304 +2026-06-24 04:19:29,709 - Total optimizing variables: 278,728 +2026-06-24 04:19:29,709 - Overdetermined ratio : 15.05 +2026-06-24 04:19:29,709 - +2026-06-24 04:19:29,709 - ### Model behavior ### +2026-06-24 04:19:29,709 - Tilt propagator : False +2026-06-24 04:19:29,709 - Change slice thickness : False +2026-06-24 04:19:29,709 - Detector blur : False +2026-06-24 04:19:29,709 - Preload data : True +2026-06-24 04:19:29,709 - On-the-fly meas padding : False +2026-06-24 04:19:29,709 - On-the-fly meas resample : False +2026-06-24 04:19:29,709 - On-the-fly simu match mode: None +2026-06-24 04:19:29,709 - +2026-06-24 04:19:29,751 - ### Done initializing PtychoModel model ### +2026-06-24 04:19:29,751 - +2026-06-24 04:19:29,751 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:19:29,751 - +2026-06-24 04:19:29,751 - ### Generating indices, batches, and output_path ### +2026-06-24 04:19:29,753 - d90 = 63.000 px or 12.600 Ang +2026-06-24 04:19:29,753 - Selecting indices with the 'full' mode +2026-06-24 04:19:30,214 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:19:30,294 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:19:30,294 - Original recon_dir_affixes = ['default'] +2026-06-24 04:19:30,294 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:19:30,300 - Path corrected for compatibility: +2026-06-24 04:19:30,300 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_C32_1.01e+04_phi32_331_C34_3.7e+03_phi34_306_C41_-7.23e+04_phi41_309_C43_3.81e+05_phi43_3.87_C45_2.43e+05_phi45_117_C50_1.64e+07_C52_-1.18e+07_phi52_324_C54_6.4e+06_phi54_173_C56_-7.5e+06_phi56_187 +2026-06-24 04:19:30,300 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187 +2026-06-24 04:19:30,302 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187' is generated! +2026-06-24 04:19:30,457 - +2026-06-24 04:19:30,458 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/20260624_041930_ptyrad_log.txt ### +2026-06-24 04:19:30,458 - +2026-06-24 04:19:30,460 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:19:30,460 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:19:30,460 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:19:31,659 - Iter: 1, Total Loss: 0.9551, loss_single: 0.9551, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 04:19:31,696 - Iter: 2, Total Loss: 0.8929, loss_single: 0.8929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:19:31,732 - Iter: 3, Total Loss: 0.8492, loss_single: 0.8492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:31,768 - Iter: 4, Total Loss: 0.8103, loss_single: 0.8103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:31,804 - Iter: 5, Total Loss: 0.7700, loss_single: 0.7700, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:31,840 - Iter: 6, Total Loss: 0.7315, loss_single: 0.7315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:31,875 - Iter: 7, Total Loss: 0.6954, loss_single: 0.6954, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:31,911 - Iter: 8, Total Loss: 0.6649, loss_single: 0.6649, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:31,947 - Iter: 9, Total Loss: 0.6363, loss_single: 0.6363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:31,983 - Iter: 10, Total Loss: 0.6075, loss_single: 0.6075, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,019 - Iter: 11, Total Loss: 0.5867, loss_single: 0.5867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,054 - Iter: 12, Total Loss: 0.5699, loss_single: 0.5699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,090 - Iter: 13, Total Loss: 0.5538, loss_single: 0.5538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,126 - Iter: 14, Total Loss: 0.5359, loss_single: 0.5359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,162 - Iter: 15, Total Loss: 0.5170, loss_single: 0.5170, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,198 - Iter: 16, Total Loss: 0.5039, loss_single: 0.5039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,234 - Iter: 17, Total Loss: 0.4929, loss_single: 0.4929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,269 - Iter: 18, Total Loss: 0.4846, loss_single: 0.4846, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,304 - Iter: 19, Total Loss: 0.4763, loss_single: 0.4763, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,340 - Iter: 20, Total Loss: 0.4658, loss_single: 0.4658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,375 - Iter: 21, Total Loss: 0.4581, loss_single: 0.4581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,412 - Iter: 22, Total Loss: 0.4528, loss_single: 0.4528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,447 - Iter: 23, Total Loss: 0.4492, loss_single: 0.4492, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,483 - Iter: 24, Total Loss: 0.4467, loss_single: 0.4467, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,519 - Iter: 25, Total Loss: 0.4437, loss_single: 0.4437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,555 - Iter: 26, Total Loss: 0.4415, loss_single: 0.4415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,590 - Iter: 27, Total Loss: 0.4399, loss_single: 0.4399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,626 - Iter: 28, Total Loss: 0.4383, loss_single: 0.4383, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,661 - Iter: 29, Total Loss: 0.4368, loss_single: 0.4368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,698 - Iter: 30, Total Loss: 0.4354, loss_single: 0.4354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:32,733 - Iter: 31, Total Loss: 0.4343, loss_single: 0.4343, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,768 - Iter: 32, Total Loss: 0.4334, loss_single: 0.4334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,807 - Iter: 33, Total Loss: 0.4327, loss_single: 0.4327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 04:19:32,843 - Iter: 34, Total Loss: 0.4319, loss_single: 0.4319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,879 - Iter: 35, Total Loss: 0.4312, loss_single: 0.4312, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,915 - Iter: 36, Total Loss: 0.4306, loss_single: 0.4306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,950 - Iter: 37, Total Loss: 0.4300, loss_single: 0.4300, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:32,986 - Iter: 38, Total Loss: 0.4296, loss_single: 0.4296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,021 - Iter: 39, Total Loss: 0.4293, loss_single: 0.4293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,057 - Iter: 40, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,094 - Iter: 41, Total Loss: 0.4286, loss_single: 0.4286, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,130 - Iter: 42, Total Loss: 0.4284, loss_single: 0.4284, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,166 - Iter: 43, Total Loss: 0.4281, loss_single: 0.4281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,201 - Iter: 44, Total Loss: 0.4279, loss_single: 0.4279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,237 - Iter: 45, Total Loss: 0.4277, loss_single: 0.4277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,273 - Iter: 46, Total Loss: 0.4275, loss_single: 0.4275, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:33,308 - Iter: 47, Total Loss: 0.4274, loss_single: 0.4274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,343 - Iter: 48, Total Loss: 0.4272, loss_single: 0.4272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,379 - Iter: 49, Total Loss: 0.4270, loss_single: 0.4270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,414 - Iter: 50, Total Loss: 0.4269, loss_single: 0.4269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,450 - Iter: 51, Total Loss: 0.4268, loss_single: 0.4268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,485 - Iter: 52, Total Loss: 0.4267, loss_single: 0.4267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,521 - Iter: 53, Total Loss: 0.4266, loss_single: 0.4266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,556 - Iter: 54, Total Loss: 0.4265, loss_single: 0.4265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,592 - Iter: 55, Total Loss: 0.4263, loss_single: 0.4263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,629 - Iter: 56, Total Loss: 0.4262, loss_single: 0.4262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:33,664 - Iter: 57, Total Loss: 0.4261, loss_single: 0.4261, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:33,700 - Iter: 58, Total Loss: 0.4260, loss_single: 0.4260, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:33,736 - 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Iter: 95, Total Loss: 0.4234, loss_single: 0.4234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:35,057 - Iter: 96, Total Loss: 0.4232, loss_single: 0.4232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:19:35,093 - Iter: 97, Total Loss: 0.4231, loss_single: 0.4231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:35,128 - Iter: 98, Total Loss: 0.4231, loss_single: 0.4231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:35,163 - Iter: 99, Total Loss: 0.4231, loss_single: 0.4231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:35,199 - Iter: 100, Total Loss: 0.4231, loss_single: 0.4231, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:19:35,312 - Saving summary figures for iter 100 +2026-06-24 04:19:38,972 - ### Finished 100 iterations, averaged iter_t = 0.039291 with std = 0.040 ### +2026-06-24 04:19:38,972 - +2026-06-24 04:19:38,972 - ### The PtyRADSolver is finished in 9.335 sec ### +2026-06-24 04:19:38,973 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..3e586027c9011a5cfdccef90dfb509910c72d226 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/simulation_data10__sample_000007.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/simulation_data10__sample_000007.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cabef96dee33011fcd014e156e4237e38f596566 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007/gendata3_std_02__simulation_data10__sample_000007_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-277_C12_-29_phi12_228_C21_-299_phi21_1.17_C23_-868_phi23_158_C30_1.21e+07_.5e+06_phi56_187/simulation_data10__sample_000007.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.433828353881836 + probe_aberrations: + C10: -277.1755676269531 + C12: -29.009902954101562 + C21: -299.1177673339844 + C23: -867.5684204101562 + C30: 12124196.0 + C32: 10093.291015625 + C34: 3699.337890625 + C41: -72286.46875 + C43: 380508.78125 + C45: 243064.125 + C50: 16352149.0 + C52: -11788933.0 + C54: 6396052.5 + C56: -7504720.0 + phi12: 227.83858165383396 + phi21: 1.1741826226936523 + phi23: 157.80280545176367 + phi32: 331.1907911931758 + phi34: 306.2005770202032 + phi41: 308.53363303689616 + phi43: 3.869344853494536 + phi45: 116.57003260228556 + phi52: 324.3050589248325 + phi54: 173.13076081726945 + phi56: 187.22670032066665 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data10__sample_000007_measurement.h5 + key: measurement + random_seed: 20261540 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data10__sample_000007 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data10__sample_000007 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/20260624_042553_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/20260624_042553_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..0183f50503762dab4d1039ee2c9ef2c0f97e7abd --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/20260624_042553_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:25:51,681 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:25:51,681 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:25:51,681 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:25:51,681 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:25:51,682 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:25:51,682 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:25:51,682 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:25:51,682 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:25:51,682 - +2026-06-24 04:25:51,789 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:25:51,789 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:25:51,789 - Accelerator.num_process = 1 +2026-06-24 04:25:51,789 - Accelerator.mixed_precision = no +2026-06-24 04:25:51,812 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:25:51,812 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:25:51,812 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:25:51,812 - +2026-06-24 04:25:51,812 - ### System information ### +2026-06-24 04:25:51,812 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:25:51,812 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:25:51,812 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:25:51,812 - Machine: x86_64 +2026-06-24 04:25:51,812 - Processor: x86_64 +2026-06-24 04:25:51,812 - Available CPU cores: 8 +2026-06-24 04:25:51,812 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:25:51,812 - +2026-06-24 04:25:51,812 - ### GPU information ### +2026-06-24 04:25:51,812 - CUDA Available: True +2026-06-24 04:25:51,812 - CUDA Version: 13.0 +2026-06-24 04:25:51,813 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:25:51,813 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:25:51,813 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:25:51,813 - In addition, Triton does not directly support Windows. +2026-06-24 04:25:51,813 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:25:51,839 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:25:51,839 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:25:51,839 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:25:51,839 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:25:51,839 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:25:51,839 - +2026-06-24 04:25:51,839 - ### Python information ### +2026-06-24 04:25:51,840 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:25:51,840 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:25:51,840 - +2026-06-24 04:25:51,840 - ### Packages information ### +2026-06-24 04:25:51,841 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:25:51,841 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:25:51,842 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:25:51,843 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:25:51,843 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:25:51,843 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:25:51,843 - +2026-06-24 04:25:51,843 - ### Loading params file ### +2026-06-24 04:25:51,843 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data11__sample_000011.yaml +2026-06-24 04:25:51,850 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:25:51,851 - Success! Params file validated and defaults applied. +2026-06-24 04:25:51,851 - +2026-06-24 04:25:51,851 - ### Setting GPU Device ### +2026-06-24 04:25:51,851 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:25:51,851 - +2026-06-24 04:25:51,851 - Random seed: 20261566 provided by params file +2026-06-24 04:25:51,851 - ### Initializing Initializer ### +2026-06-24 04:25:51,852 - init_params are displayed below: +2026-06-24 04:25:51,852 - random_seed: 20261566 +2026-06-24 04:25:51,852 - probe_illum_type: electron +2026-06-24 04:25:51,852 - probe_kv: 200.0 +2026-06-24 04:25:51,852 - probe_conv_angle: 9.036358833312988 +2026-06-24 04:25:51,852 - probe_aberrations: {'C10': -451.632, 'C12': -47.698, 'phi12': 100.686, 'C21': -901.807, 'phi21': 268.468, 'C23': -494.205, 'phi23': 302.659, 'C30': 12122050.0, 'C32': -10077.271, 'phi32': 183.725, 'C34': -8481.195, 'phi34': 279.583, 'C41': 413543.0, 'phi41': 46.242, 'C43': 409496.469, 'phi43': 343.472, 'C45': 423289.281, 'phi45': 109.391, 'C50': -9593891.0, 'C52': -10229413.0, 'phi52': 105.672, 'C54': -7431282.5, 'phi54': 18.06, 'C56': 12966203.0, 'phi56': 231.171} +2026-06-24 04:25:51,852 - beam_kev: None +2026-06-24 04:25:51,852 - probe_dRn: None +2026-06-24 04:25:51,852 - probe_Rn: None +2026-06-24 04:25:51,852 - probe_D_H: None +2026-06-24 04:25:51,852 - probe_D_FZP: None +2026-06-24 04:25:51,852 - probe_Ls: None +2026-06-24 04:25:51,852 - meas_Npix: 128 +2026-06-24 04:25:51,852 - pos_N_scans: 256 +2026-06-24 04:25:51,852 - pos_N_scan_slow: 16 +2026-06-24 04:25:51,852 - pos_N_scan_fast: 16 +2026-06-24 04:25:51,852 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:25:51,852 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:25:51,852 - probe_pmode_max: 6 +2026-06-24 04:25:51,852 - probe_pmode_init_pows: [0.02] +2026-06-24 04:25:51,852 - obj_omode_max: 1 +2026-06-24 04:25:51,852 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:25:51,852 - obj_Nlayer: 1 +2026-06-24 04:25:51,852 - obj_slice_thickness: 20.0 +2026-06-24 04:25:51,852 - simu_Npix: None +2026-06-24 04:25:51,852 - simu_match_mode: None +2026-06-24 04:25:51,852 - meas_permute: None +2026-06-24 04:25:51,852 - meas_reshape: [256, 128, 128] +2026-06-24 04:25:51,852 - meas_flipT: [0, 0, 0] +2026-06-24 04:25:51,852 - meas_crop: None +2026-06-24 04:25:51,852 - meas_pad: None +2026-06-24 04:25:51,852 - meas_resample: None +2026-06-24 04:25:51,852 - meas_add_source_size: None +2026-06-24 04:25:51,852 - meas_add_detector_blur: None +2026-06-24 04:25:51,853 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:25:51,853 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:25:51,853 - meas_add_poisson_noise: None +2026-06-24 04:25:51,853 - meas_export: None +2026-06-24 04:25:51,853 - probe_permute: None +2026-06-24 04:25:51,853 - probe_z_shift: None +2026-06-24 04:25:51,853 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:25:51,853 - pos_scan_flipT: None +2026-06-24 04:25:51,853 - pos_scan_affine: None +2026-06-24 04:25:51,853 - pos_scan_rand_std: 0.15 +2026-06-24 04:25:51,853 - obj_z_crop: None +2026-06-24 04:25:51,853 - obj_z_pad: None +2026-06-24 04:25:51,853 - obj_z_resample: None +2026-06-24 04:25:51,853 - meas_source: file +2026-06-24 04:25:51,853 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data11__sample_000011_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:25:51,853 - probe_source: simu +2026-06-24 04:25:51,853 - probe_params: None +2026-06-24 04:25:51,853 - pos_source: simu +2026-06-24 04:25:51,853 - pos_params: None +2026-06-24 04:25:51,853 - obj_source: simu +2026-06-24 04:25:51,853 - obj_params: None +2026-06-24 04:25:51,853 - tilt_source: simu +2026-06-24 04:25:51,853 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:25:51,853 - +2026-06-24 04:25:51,853 - ### Initializing cache ### +2026-06-24 04:25:51,853 - use_cached_obj = False +2026-06-24 04:25:51,853 - use_cached_probe = False +2026-06-24 04:25:51,853 - use_cached_pos = False +2026-06-24 04:25:51,853 - +2026-06-24 04:25:51,853 - ### Initializing measurements ### +2026-06-24 04:25:51,853 - Loading measurements from source = 'file' +2026-06-24 04:25:51,853 - Detected measurement file type = '.h5' +2026-06-24 04:25:51,931 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:25:51,932 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:25:51,933 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0052) +2026-06-24 04:25:51,933 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:25:51,933 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:25:51,935 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:25:51,935 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:25:51,935 - Normalizing by max of the 2D mean pattern intensity: 0.0037308421 +2026-06-24 04:25:51,936 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:25:51,937 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0164, 1.3844) +2026-06-24 04:25:51,938 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:25:51,939 - Pattern total int. statistics (min, mean, max) = (266.2330, 268.0637, 269.9359), with min/max = 98.6% +2026-06-24 04:25:51,940 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0164, 1.3844) +2026-06-24 04:25:51,940 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:25:51,940 - +2026-06-24 04:25:51,940 - ### Setting up calibration ### +2026-06-24 04:25:51,940 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:25:51,941 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:25:51,941 - Radius of fitted bright field disk (RBF) = 9.08 px with meas_Npix = 128 +2026-06-24 04:25:51,941 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1419 +2026-06-24 04:25:51,941 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:25:51,941 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:25:52,165 - Initial guess: center=(63.62, 63.63), radius=9.08, Gaussian blur std=0.50 +2026-06-24 04:25:52,175 - Final fit: center=(63.62, 63.63), radius=9.08, Gaussian blur std=0.61 +2026-06-24 04:25:52,175 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.22 px with Npix = 128 +2026-06-24 04:25:52,175 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:25:52,175 - +2026-06-24 04:25:52,175 - ### Setting init_variables dict ### +2026-06-24 04:25:52,176 - Derived values given input init_params: +2026-06-24 04:25:52,176 - kv = 200.0 kV +2026-06-24 04:25:52,176 - wavelength = 0.0251 Ang +2026-06-24 04:25:52,176 - conv_angle = 9.036358833312988 mrad +2026-06-24 04:25:52,176 - Npix = 128 px +2026-06-24 04:25:52,176 - dk = 0.0391 Ang^-1 +2026-06-24 04:25:52,176 - kMax = 2.5000 Ang^-1 +2026-06-24 04:25:52,176 - da = 0.9797 mrad +2026-06-24 04:25:52,176 - angleMax = 62.6984 mrad +2026-06-24 04:25:52,176 - RBF = 9.2240 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:25:52,176 - n_alpha = 6.9385 (# conv_angle) +2026-06-24 04:25:52,176 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:25:52,176 - Rayleigh-limited resolution = 1.6930 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:25:52,176 - Real space probe extent = 25.6000 Ang +2026-06-24 04:25:52,176 - +2026-06-24 04:25:52,176 - ### Initializing probe ### +2026-06-24 04:25:52,176 - Loading probe from source = 'simu' +2026-06-24 04:25:52,176 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:25:52,176 - Start simulating STEM probe +2026-06-24 04:25:52,176 - kv = 200.0 kV +2026-06-24 04:25:52,176 - wavelength = 0.0251 Ang +2026-06-24 04:25:52,176 - conv_angle = 9.036358833312988 mrad +2026-06-24 04:25:52,176 - Npix = 128 px +2026-06-24 04:25:52,176 - dk = 0.0391 Ang^-1 +2026-06-24 04:25:52,176 - kMax = 2.5000 Ang^-1 +2026-06-24 04:25:52,176 - alpha_max = 62.6984 mrad +2026-06-24 04:25:52,177 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:25:52,177 - Rayleigh-limited resolution = 1.6930 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:25:52,177 - Real space probe extent = 25.6000 Ang +2026-06-24 04:25:52,177 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:25:52,177 - ------------------------------------------------------------------------------------ +2026-06-24 04:25:52,177 - C1,0 C1 -451.6320 - Defocus (C10 = -df) +2026-06-24 04:25:52,177 - C1,2 A1 -47.6980 100.69 2-fold astigmatism +2026-06-24 04:25:52,177 - C2,1 3*B2 -901.8070 268.47 Axial coma +2026-06-24 04:25:52,177 - C2,3 A2 -494.2050 302.66 3-fold astigmatism +2026-06-24 04:25:52,177 - C3,0 C3 12122050.0000 - Spherical aberration +2026-06-24 04:25:52,177 - C3,2 4*S3 -10077.2710 183.72 Axial star aberration +2026-06-24 04:25:52,177 - C3,4 A3 -8481.1950 279.58 4-fold astigmatism +2026-06-24 04:25:52,177 - C4,1 4*B4 413543.0000 46.24 Axial coma(4th) +2026-06-24 04:25:52,177 - C4,3 4*D4 409496.4690 343.47 3-lobe aberration +2026-06-24 04:25:52,177 - C4,5 A4 423289.2810 109.39 5-fold astigmatism +2026-06-24 04:25:52,177 - C5,0 C5 -9593891.0000 - Spherical aberration (5th) +2026-06-24 04:25:52,177 - C5,2 6*S5 -10229413.0000 105.67 Axial star aberration(5th) +2026-06-24 04:25:52,177 - C5,4 6*R5 -7431282.5000 18.06 4-lobe aberration +2026-06-24 04:25:52,177 - C5,6 A5 12966203.0000 231.17 6-fold astigmatism +2026-06-24 04:25:52,180 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:25:52,180 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:25:52,180 - Creating 5 new probe modes from the major mode +2026-06-24 04:25:52,180 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:25:52,283 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:25:52,284 - Orthogonalizing 6 pmodes +2026-06-24 04:25:52,286 - Sorting 6 pmodes by their intensities +2026-06-24 04:25:52,287 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:25:52,287 - sum(|probe_data|**2) = 268.06, while meas_total_ints (min, mean, max) = (266.2330, 268.0637, 269.9359) +2026-06-24 04:25:52,288 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:25:52,288 - +2026-06-24 04:25:52,288 - ### Initializing probe positions ### +2026-06-24 04:25:52,288 - Loading probe positions from source = 'simu' +2026-06-24 04:25:52,288 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:25:52,288 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:25:52,288 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:25:52,290 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:25:52,290 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:25:52,290 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:25:52,290 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:25:52,290 - +2026-06-24 04:25:52,290 - ### Initializing object ### +2026-06-24 04:25:52,290 - Loading object from source = 'simu' +2026-06-24 04:25:52,290 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:25:52,292 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:25:52,292 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:25:52,292 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:25:52,292 - +2026-06-24 04:25:52,292 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:25:52,292 - omode_occu (omode) = float32, (1,) +2026-06-24 04:25:52,292 - +2026-06-24 04:25:52,292 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:25:52,293 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:25:52,293 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:25:52,293 - +2026-06-24 04:25:52,293 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:25:52,293 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:25:52,293 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:25:52,293 - +2026-06-24 04:25:52,293 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:25:52,293 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:25:52,293 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:25:52,293 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:25:52,293 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:25:52,294 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:25:52,294 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:25:52,294 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:25:52,294 - +2026-06-24 04:25:52,294 - ### Collecting reconstruction provenance ### +2026-06-24 04:25:52,294 - Reconstruction provenance is collected and initialized. +2026-06-24 04:25:52,294 - +2026-06-24 04:25:52,294 - ### Initializing loss function ### +2026-06-24 04:25:52,294 - Active loss types: +2026-06-24 04:25:52,294 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:25:52,294 - +2026-06-24 04:25:52,294 - ### Initializing constraint function ### +2026-06-24 04:25:52,294 - Active constraint types: +2026-06-24 04:25:52,294 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:25:52,294 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:25:52,294 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:25:52,294 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:25:52,294 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:25:52,294 - +2026-06-24 04:25:52,294 - ### Done initializing PtyRADSolver ### +2026-06-24 04:25:52,294 - +2026-06-24 04:25:52,424 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:25:52,424 - +2026-06-24 04:25:52,424 - ### Initializing PtychoModel model ### +2026-06-24 04:25:52,495 - ### PtychoModel optimizable variables ### +2026-06-24 04:25:52,495 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:25:52,495 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:25:52,495 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:25:52,495 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:25:52,495 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:25:52,495 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:25:52,495 - +2026-06-24 04:25:52,495 - ### Optimizable variables statitsics ### +2026-06-24 04:25:52,495 - Total measurement values : 4,194,304 +2026-06-24 04:25:52,495 - Total optimizing variables: 278,728 +2026-06-24 04:25:52,496 - Overdetermined ratio : 15.05 +2026-06-24 04:25:52,496 - +2026-06-24 04:25:52,496 - ### Model behavior ### +2026-06-24 04:25:52,496 - Tilt propagator : False +2026-06-24 04:25:52,496 - Change slice thickness : False +2026-06-24 04:25:52,496 - Detector blur : False +2026-06-24 04:25:52,496 - Preload data : True +2026-06-24 04:25:52,496 - On-the-fly meas padding : False +2026-06-24 04:25:52,496 - On-the-fly meas resample : False +2026-06-24 04:25:52,496 - On-the-fly simu match mode: None +2026-06-24 04:25:52,496 - +2026-06-24 04:25:52,536 - ### Done initializing PtychoModel model ### +2026-06-24 04:25:52,536 - +2026-06-24 04:25:52,536 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:25:52,536 - +2026-06-24 04:25:52,537 - ### Generating indices, batches, and output_path ### +2026-06-24 04:25:52,538 - d90 = 47.000 px or 9.400 Ang +2026-06-24 04:25:52,538 - Selecting indices with the 'full' mode +2026-06-24 04:25:52,994 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:25:53,070 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:25:53,070 - Original recon_dir_affixes = ['default'] +2026-06-24 04:25:53,070 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:25:53,076 - Path corrected for compatibility: +2026-06-24 04:25:53,076 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07_C32_-1.01e+04_phi32_184_C34_-8.48e+03_phi34_280_C41_4.14e+05_phi41_46.2_C43_4.09e+05_phi43_343_C45_4.23e+05_phi45_109_C50_-9.59e+06_C52_-1.02e+07_phi52_106_C54_-7.43e+06_phi54_18.1_C56_1.3e+07_phi56_231 +2026-06-24 04:25:53,076 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231 +2026-06-24 04:25:53,077 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231' is generated! +2026-06-24 04:25:53,230 - +2026-06-24 04:25:53,231 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/20260624_042553_ptyrad_log.txt ### +2026-06-24 04:25:53,231 - +2026-06-24 04:25:53,232 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:25:53,232 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:25:53,232 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:25:54,413 - Iter: 1, Total Loss: 1.0736, loss_single: 1.0736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 04:25:54,450 - Iter: 2, Total Loss: 1.0117, loss_single: 1.0117, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:25:54,486 - Iter: 3, Total Loss: 0.9584, loss_single: 0.9584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,522 - Iter: 4, Total Loss: 0.9022, loss_single: 0.9022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:25:54,557 - Iter: 5, Total Loss: 0.8459, loss_single: 0.8459, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,593 - Iter: 6, Total Loss: 0.7957, loss_single: 0.7957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,628 - Iter: 7, Total Loss: 0.7527, loss_single: 0.7527, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,664 - Iter: 8, Total Loss: 0.7174, loss_single: 0.7174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,699 - Iter: 9, Total Loss: 0.6891, loss_single: 0.6891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,734 - Iter: 10, Total Loss: 0.6604, loss_single: 0.6604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,770 - Iter: 11, Total Loss: 0.6321, loss_single: 0.6321, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,805 - Iter: 12, Total Loss: 0.6044, loss_single: 0.6044, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,841 - Iter: 13, Total Loss: 0.5785, loss_single: 0.5785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,876 - Iter: 14, Total Loss: 0.5565, loss_single: 0.5565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:54,914 - Iter: 15, Total Loss: 0.5366, loss_single: 0.5366, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:25:54,950 - Iter: 16, Total Loss: 0.5228, loss_single: 0.5228, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:25:54,985 - Iter: 17, Total Loss: 0.5116, loss_single: 0.5116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,021 - Iter: 18, Total Loss: 0.4997, loss_single: 0.4997, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,057 - Iter: 19, Total Loss: 0.4889, loss_single: 0.4889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:25:55,092 - Iter: 20, Total Loss: 0.4790, loss_single: 0.4790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,127 - Iter: 21, Total Loss: 0.4695, loss_single: 0.4695, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,162 - Iter: 22, Total Loss: 0.4612, loss_single: 0.4612, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,197 - Iter: 23, Total Loss: 0.4546, loss_single: 0.4546, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,232 - Iter: 24, Total Loss: 0.4496, loss_single: 0.4496, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,268 - Iter: 25, Total Loss: 0.4452, loss_single: 0.4452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,303 - Iter: 26, Total Loss: 0.4409, loss_single: 0.4409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,339 - Iter: 27, Total Loss: 0.4369, loss_single: 0.4369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,374 - Iter: 28, Total Loss: 0.4334, loss_single: 0.4334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,413 - Iter: 29, Total Loss: 0.4299, loss_single: 0.4299, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 04:25:55,449 - Iter: 30, Total Loss: 0.4265, loss_single: 0.4265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,485 - Iter: 31, Total Loss: 0.4233, loss_single: 0.4233, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,520 - Iter: 32, Total Loss: 0.4206, loss_single: 0.4206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,556 - Iter: 33, Total Loss: 0.4185, loss_single: 0.4185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,591 - Iter: 34, Total Loss: 0.4168, loss_single: 0.4168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,627 - Iter: 35, Total Loss: 0.4150, loss_single: 0.4150, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,662 - Iter: 36, Total Loss: 0.4133, loss_single: 0.4133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,697 - Iter: 37, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,732 - Iter: 38, Total Loss: 0.4104, loss_single: 0.4104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,768 - Iter: 39, Total Loss: 0.4091, loss_single: 0.4091, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,803 - Iter: 40, Total Loss: 0.4080, loss_single: 0.4080, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,840 - Iter: 41, Total Loss: 0.4067, loss_single: 0.4067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,876 - Iter: 42, Total Loss: 0.4056, loss_single: 0.4056, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,912 - Iter: 43, Total Loss: 0.4046, loss_single: 0.4046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,947 - Iter: 44, Total Loss: 0.4037, loss_single: 0.4037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:55,986 - Iter: 45, Total Loss: 0.4028, loss_single: 0.4028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 04:25:56,022 - Iter: 46, Total Loss: 0.4018, loss_single: 0.4018, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,057 - Iter: 47, Total Loss: 0.4008, loss_single: 0.4008, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,093 - Iter: 48, Total Loss: 0.4000, loss_single: 0.4000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,129 - Iter: 49, Total Loss: 0.3991, loss_single: 0.3991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,164 - Iter: 50, Total Loss: 0.3982, loss_single: 0.3982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,200 - Iter: 51, Total Loss: 0.3973, loss_single: 0.3973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,235 - Iter: 52, Total Loss: 0.3964, loss_single: 0.3964, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,270 - Iter: 53, Total Loss: 0.3957, loss_single: 0.3957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,305 - Iter: 54, Total Loss: 0.3949, loss_single: 0.3949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,341 - Iter: 55, Total Loss: 0.3941, loss_single: 0.3941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,376 - Iter: 56, Total Loss: 0.3935, loss_single: 0.3935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,412 - Iter: 57, Total Loss: 0.3927, loss_single: 0.3927, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,448 - Iter: 58, Total Loss: 0.3920, loss_single: 0.3920, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,486 - Iter: 59, Total Loss: 0.3912, loss_single: 0.3912, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 04:25:56,522 - Iter: 60, Total Loss: 0.3905, loss_single: 0.3905, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,557 - Iter: 61, Total Loss: 0.3898, loss_single: 0.3898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,592 - Iter: 62, Total Loss: 0.3890, loss_single: 0.3890, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,628 - Iter: 63, Total Loss: 0.3884, loss_single: 0.3884, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,663 - Iter: 64, Total Loss: 0.3877, loss_single: 0.3877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:56,698 - 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Iter: 77, Total Loss: 0.3797, loss_single: 0.3797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,161 - Iter: 78, Total Loss: 0.3791, loss_single: 0.3791, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,197 - Iter: 79, Total Loss: 0.3786, loss_single: 0.3786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,232 - Iter: 80, Total Loss: 0.3782, loss_single: 0.3782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,267 - Iter: 81, Total Loss: 0.3776, loss_single: 0.3776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,302 - Iter: 82, Total Loss: 0.3770, loss_single: 0.3770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,338 - 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Iter: 95, Total Loss: 0.3710, loss_single: 0.3710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,800 - Iter: 96, Total Loss: 0.3706, loss_single: 0.3706, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,836 - Iter: 97, Total Loss: 0.3702, loss_single: 0.3702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,871 - Iter: 98, Total Loss: 0.3697, loss_single: 0.3697, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,907 - Iter: 99, Total Loss: 0.3692, loss_single: 0.3692, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:57,943 - Iter: 100, Total Loss: 0.3689, loss_single: 0.3689, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:25:58,054 - Saving summary figures for iter 100 +2026-06-24 04:26:01,632 - ### Finished 100 iterations, averaged iter_t = 0.039236 with std = 0.040 ### +2026-06-24 04:26:01,632 - +2026-06-24 04:26:01,632 - ### The PtyRADSolver is finished in 9.208 sec ### +2026-06-24 04:26:01,633 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..a4cd74eb28cdb073644b6488ffb70fa2e17c8693 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/simulation_data11__sample_000011.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/simulation_data11__sample_000011.yaml new file mode 100644 index 0000000000000000000000000000000000000000..77912cf823a3096ab566707c681764eb422a388e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011/gendata3_std_02__simulation_data11__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-452_C12_-47.7_phi12_101_C21_-902_phi21_268_C23_-494_phi23_303_C30_1.21e+07.3e+07_phi56_231/simulation_data11__sample_000011.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.036358833312988 + probe_aberrations: + C10: -451.63165283203125 + C12: -47.697837829589844 + C21: -901.8069458007812 + C23: -494.20452880859375 + C30: 12122050.0 + C32: -10077.2705078125 + C34: -8481.1953125 + C41: 413543.0 + C43: 409496.46875 + C45: 423289.28125 + C50: -9593891.0 + C52: -10229413.0 + C54: -7431282.5 + C56: 12966203.0 + phi12: 100.68623644212414 + phi21: 268.4680985354382 + phi23: 302.658659482688 + phi32: 183.72463010676935 + phi34: 279.5826468057465 + phi41: 46.242371681129384 + phi43: 343.4721816605324 + phi45: 109.3909915204144 + phi52: 105.67245895134104 + phi54: 18.059547797627097 + phi56: 231.17108559139652 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data11__sample_000011_measurement.h5 + key: measurement + random_seed: 20261566 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data11__sample_000011 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data11__sample_000011 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/20260624_043200_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/20260624_043200_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f470363a88caeb6511a4221e0caf8cc72729532f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/20260624_043200_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:31:59,152 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:31:59,152 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:31:59,152 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:31:59,152 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:31:59,152 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:31:59,152 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:31:59,152 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:31:59,152 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:31:59,153 - +2026-06-24 04:31:59,260 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:31:59,260 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:31:59,260 - Accelerator.num_process = 1 +2026-06-24 04:31:59,260 - Accelerator.mixed_precision = no +2026-06-24 04:31:59,271 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:31:59,271 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:31:59,271 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:31:59,271 - +2026-06-24 04:31:59,271 - ### System information ### +2026-06-24 04:31:59,271 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:31:59,271 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:31:59,271 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:31:59,271 - Machine: x86_64 +2026-06-24 04:31:59,271 - Processor: x86_64 +2026-06-24 04:31:59,271 - Available CPU cores: 8 +2026-06-24 04:31:59,271 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:31:59,271 - +2026-06-24 04:31:59,271 - ### GPU information ### +2026-06-24 04:31:59,271 - CUDA Available: True +2026-06-24 04:31:59,271 - CUDA Version: 13.0 +2026-06-24 04:31:59,272 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:31:59,272 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:31:59,272 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:31:59,272 - In addition, Triton does not directly support Windows. +2026-06-24 04:31:59,272 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:31:59,287 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:31:59,287 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:31:59,287 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:31:59,287 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:31:59,287 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:31:59,287 - +2026-06-24 04:31:59,287 - ### Python information ### +2026-06-24 04:31:59,289 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:31:59,289 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:31:59,289 - +2026-06-24 04:31:59,289 - ### Packages information ### +2026-06-24 04:31:59,289 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:31:59,290 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:31:59,291 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:31:59,291 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:31:59,292 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:31:59,292 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:31:59,292 - +2026-06-24 04:31:59,292 - ### Loading params file ### +2026-06-24 04:31:59,292 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data7__sample_000016.yaml +2026-06-24 04:31:59,299 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:31:59,300 - Success! Params file validated and defaults applied. +2026-06-24 04:31:59,300 - +2026-06-24 04:31:59,300 - ### Setting GPU Device ### +2026-06-24 04:31:59,300 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:31:59,300 - +2026-06-24 04:31:59,300 - Random seed: 20261591 provided by params file +2026-06-24 04:31:59,300 - ### Initializing Initializer ### +2026-06-24 04:31:59,300 - init_params are displayed below: +2026-06-24 04:31:59,300 - random_seed: 20261591 +2026-06-24 04:31:59,300 - probe_illum_type: electron +2026-06-24 04:31:59,301 - probe_kv: 200.0 +2026-06-24 04:31:59,301 - probe_conv_angle: 9.859851837158203 +2026-06-24 04:31:59,301 - probe_aberrations: {'C10': -426.455, 'C12': 28.205, 'phi12': 132.185, 'C21': -685.645, 'phi21': 32.522, 'C23': 120.887, 'phi23': 109.278, 'C30': 10527491.0, 'C32': 5969.845, 'phi32': 273.525, 'C34': -4954.933, 'phi34': 254.645, 'C41': -483082.812, 'phi41': 248.011, 'C43': 144335.859, 'phi43': 297.243, 'C45': 37773.699, 'phi45': 237.506, 'C50': 2607385.0, 'C52': -16625273.0, 'phi52': 60.181, 'C54': 14834470.0, 'phi54': 227.651, 'C56': 4067612.0, 'phi56': 233.888} +2026-06-24 04:31:59,301 - beam_kev: None +2026-06-24 04:31:59,301 - probe_dRn: None +2026-06-24 04:31:59,301 - probe_Rn: None +2026-06-24 04:31:59,301 - probe_D_H: None +2026-06-24 04:31:59,301 - probe_D_FZP: None +2026-06-24 04:31:59,301 - probe_Ls: None +2026-06-24 04:31:59,301 - meas_Npix: 128 +2026-06-24 04:31:59,301 - pos_N_scans: 256 +2026-06-24 04:31:59,301 - pos_N_scan_slow: 16 +2026-06-24 04:31:59,301 - pos_N_scan_fast: 16 +2026-06-24 04:31:59,301 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:31:59,301 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:31:59,301 - probe_pmode_max: 6 +2026-06-24 04:31:59,301 - probe_pmode_init_pows: [0.02] +2026-06-24 04:31:59,301 - obj_omode_max: 1 +2026-06-24 04:31:59,301 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:31:59,301 - obj_Nlayer: 1 +2026-06-24 04:31:59,301 - obj_slice_thickness: 20.0 +2026-06-24 04:31:59,301 - simu_Npix: None +2026-06-24 04:31:59,301 - simu_match_mode: None +2026-06-24 04:31:59,301 - meas_permute: None +2026-06-24 04:31:59,301 - meas_reshape: [256, 128, 128] +2026-06-24 04:31:59,301 - meas_flipT: [0, 0, 0] +2026-06-24 04:31:59,301 - meas_crop: None +2026-06-24 04:31:59,301 - meas_pad: None +2026-06-24 04:31:59,301 - meas_resample: None +2026-06-24 04:31:59,301 - meas_add_source_size: None +2026-06-24 04:31:59,301 - meas_add_detector_blur: None +2026-06-24 04:31:59,301 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:31:59,301 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:31:59,301 - meas_add_poisson_noise: None +2026-06-24 04:31:59,301 - meas_export: None +2026-06-24 04:31:59,301 - probe_permute: None +2026-06-24 04:31:59,301 - probe_z_shift: None +2026-06-24 04:31:59,301 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:31:59,302 - pos_scan_flipT: None +2026-06-24 04:31:59,302 - pos_scan_affine: None +2026-06-24 04:31:59,302 - pos_scan_rand_std: 0.15 +2026-06-24 04:31:59,302 - obj_z_crop: None +2026-06-24 04:31:59,302 - obj_z_pad: None +2026-06-24 04:31:59,302 - obj_z_resample: None +2026-06-24 04:31:59,302 - meas_source: file +2026-06-24 04:31:59,302 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000016_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:31:59,302 - probe_source: simu +2026-06-24 04:31:59,302 - probe_params: None +2026-06-24 04:31:59,302 - pos_source: simu +2026-06-24 04:31:59,302 - pos_params: None +2026-06-24 04:31:59,302 - obj_source: simu +2026-06-24 04:31:59,302 - obj_params: None +2026-06-24 04:31:59,302 - tilt_source: simu +2026-06-24 04:31:59,302 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:31:59,302 - +2026-06-24 04:31:59,302 - ### Initializing cache ### +2026-06-24 04:31:59,302 - use_cached_obj = False +2026-06-24 04:31:59,302 - use_cached_probe = False +2026-06-24 04:31:59,302 - use_cached_pos = False +2026-06-24 04:31:59,302 - +2026-06-24 04:31:59,302 - ### Initializing measurements ### +2026-06-24 04:31:59,302 - Loading measurements from source = 'file' +2026-06-24 04:31:59,302 - Detected measurement file type = '.h5' +2026-06-24 04:31:59,380 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:31:59,380 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:31:59,382 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0039) +2026-06-24 04:31:59,382 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:31:59,382 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:31:59,385 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:31:59,385 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:31:59,385 - Normalizing by max of the 2D mean pattern intensity: 0.0030235467 +2026-06-24 04:31:59,386 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:31:59,387 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.3050) +2026-06-24 04:31:59,388 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:31:59,389 - Pattern total int. statistics (min, mean, max) = (328.6080, 330.5558, 332.9915), with min/max = 98.7% +2026-06-24 04:31:59,390 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.3050) +2026-06-24 04:31:59,390 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:31:59,390 - +2026-06-24 04:31:59,390 - ### Setting up calibration ### +2026-06-24 04:31:59,391 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:31:59,391 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:31:59,391 - Radius of fitted bright field disk (RBF) = 10.00 px with meas_Npix = 128 +2026-06-24 04:31:59,391 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1562 +2026-06-24 04:31:59,391 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:31:59,391 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:31:59,621 - Initial guess: center=(63.62, 63.62), radius=10.00, Gaussian blur std=0.50 +2026-06-24 04:31:59,631 - Final fit: center=(63.62, 63.62), radius=10.00, Gaussian blur std=0.59 +2026-06-24 04:31:59,631 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.06 px with Npix = 128 +2026-06-24 04:31:59,631 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:31:59,631 - +2026-06-24 04:31:59,631 - ### Setting init_variables dict ### +2026-06-24 04:31:59,631 - Derived values given input init_params: +2026-06-24 04:31:59,631 - kv = 200.0 kV +2026-06-24 04:31:59,632 - wavelength = 0.0251 Ang +2026-06-24 04:31:59,632 - conv_angle = 9.859851837158203 mrad +2026-06-24 04:31:59,632 - Npix = 128 px +2026-06-24 04:31:59,632 - dk = 0.0391 Ang^-1 +2026-06-24 04:31:59,632 - kMax = 2.5000 Ang^-1 +2026-06-24 04:31:59,632 - da = 0.9797 mrad +2026-06-24 04:31:59,632 - angleMax = 62.6984 mrad +2026-06-24 04:31:59,632 - RBF = 10.0645 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:31:59,632 - n_alpha = 6.3590 (# conv_angle) +2026-06-24 04:31:59,632 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:31:59,632 - Rayleigh-limited resolution = 1.5516 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:31:59,632 - Real space probe extent = 25.6000 Ang +2026-06-24 04:31:59,632 - +2026-06-24 04:31:59,632 - ### Initializing probe ### +2026-06-24 04:31:59,632 - Loading probe from source = 'simu' +2026-06-24 04:31:59,632 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:31:59,632 - Start simulating STEM probe +2026-06-24 04:31:59,632 - kv = 200.0 kV +2026-06-24 04:31:59,632 - wavelength = 0.0251 Ang +2026-06-24 04:31:59,632 - conv_angle = 9.859851837158203 mrad +2026-06-24 04:31:59,632 - Npix = 128 px +2026-06-24 04:31:59,632 - dk = 0.0391 Ang^-1 +2026-06-24 04:31:59,632 - kMax = 2.5000 Ang^-1 +2026-06-24 04:31:59,632 - alpha_max = 62.6984 mrad +2026-06-24 04:31:59,632 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:31:59,632 - Rayleigh-limited resolution = 1.5516 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:31:59,633 - Real space probe extent = 25.6000 Ang +2026-06-24 04:31:59,633 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:31:59,633 - ------------------------------------------------------------------------------------ +2026-06-24 04:31:59,633 - C1,0 C1 -426.4550 - Defocus (C10 = -df) +2026-06-24 04:31:59,633 - C1,2 A1 28.2050 132.19 2-fold astigmatism +2026-06-24 04:31:59,633 - C2,1 3*B2 -685.6450 32.52 Axial coma +2026-06-24 04:31:59,633 - C2,3 A2 120.8870 109.28 3-fold astigmatism +2026-06-24 04:31:59,633 - C3,0 C3 10527491.0000 - Spherical aberration +2026-06-24 04:31:59,633 - C3,2 4*S3 5969.8450 273.52 Axial star aberration +2026-06-24 04:31:59,633 - C3,4 A3 -4954.9330 254.65 4-fold astigmatism +2026-06-24 04:31:59,633 - C4,1 4*B4 -483082.8120 248.01 Axial coma(4th) +2026-06-24 04:31:59,633 - C4,3 4*D4 144335.8590 297.24 3-lobe aberration +2026-06-24 04:31:59,633 - C4,5 A4 37773.6990 237.51 5-fold astigmatism +2026-06-24 04:31:59,633 - C5,0 C5 2607385.0000 - Spherical aberration (5th) +2026-06-24 04:31:59,633 - C5,2 6*S5 -16625273.0000 60.18 Axial star aberration(5th) +2026-06-24 04:31:59,633 - C5,4 6*R5 14834470.0000 227.65 4-lobe aberration +2026-06-24 04:31:59,633 - C5,6 A5 4067612.0000 233.89 6-fold astigmatism +2026-06-24 04:31:59,636 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:31:59,636 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:31:59,636 - Creating 5 new probe modes from the major mode +2026-06-24 04:31:59,637 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:31:59,833 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:31:59,834 - Orthogonalizing 6 pmodes +2026-06-24 04:31:59,847 - Sorting 6 pmodes by their intensities +2026-06-24 04:31:59,847 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:31:59,848 - sum(|probe_data|**2) = 330.56, while meas_total_ints (min, mean, max) = (328.6080, 330.5558, 332.9915) +2026-06-24 04:31:59,848 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:31:59,848 - +2026-06-24 04:31:59,848 - ### Initializing probe positions ### +2026-06-24 04:31:59,848 - Loading probe positions from source = 'simu' +2026-06-24 04:31:59,848 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:31:59,848 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:31:59,848 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:31:59,850 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:31:59,851 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:31:59,851 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:31:59,851 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:31:59,851 - +2026-06-24 04:31:59,851 - ### Initializing object ### +2026-06-24 04:31:59,851 - Loading object from source = 'simu' +2026-06-24 04:31:59,851 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:31:59,852 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:31:59,852 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:31:59,853 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:31:59,853 - +2026-06-24 04:31:59,853 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:31:59,853 - omode_occu (omode) = float32, (1,) +2026-06-24 04:31:59,853 - +2026-06-24 04:31:59,853 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:31:59,853 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:31:59,853 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:31:59,854 - +2026-06-24 04:31:59,854 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:31:59,854 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:31:59,854 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:31:59,854 - +2026-06-24 04:31:59,854 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:31:59,854 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:31:59,854 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:31:59,854 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:31:59,854 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:31:59,854 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:31:59,854 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:31:59,854 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:31:59,854 - +2026-06-24 04:31:59,854 - ### Collecting reconstruction provenance ### +2026-06-24 04:31:59,854 - Reconstruction provenance is collected and initialized. +2026-06-24 04:31:59,854 - +2026-06-24 04:31:59,854 - ### Initializing loss function ### +2026-06-24 04:31:59,854 - Active loss types: +2026-06-24 04:31:59,854 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:31:59,854 - +2026-06-24 04:31:59,855 - ### Initializing constraint function ### +2026-06-24 04:31:59,855 - Active constraint types: +2026-06-24 04:31:59,855 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:31:59,855 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:31:59,855 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:31:59,855 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:31:59,855 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:31:59,855 - +2026-06-24 04:31:59,855 - ### Done initializing PtyRADSolver ### +2026-06-24 04:31:59,855 - +2026-06-24 04:31:59,977 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:31:59,977 - +2026-06-24 04:31:59,977 - ### Initializing PtychoModel model ### +2026-06-24 04:32:00,050 - ### PtychoModel optimizable variables ### +2026-06-24 04:32:00,050 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:00,050 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:00,050 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:32:00,050 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:32:00,050 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:32:00,050 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:00,050 - +2026-06-24 04:32:00,050 - ### Optimizable variables statitsics ### +2026-06-24 04:32:00,050 - Total measurement values : 4,194,304 +2026-06-24 04:32:00,050 - Total optimizing variables: 278,728 +2026-06-24 04:32:00,051 - Overdetermined ratio : 15.05 +2026-06-24 04:32:00,051 - +2026-06-24 04:32:00,051 - ### Model behavior ### +2026-06-24 04:32:00,051 - Tilt propagator : False +2026-06-24 04:32:00,051 - Change slice thickness : False +2026-06-24 04:32:00,051 - Detector blur : False +2026-06-24 04:32:00,051 - Preload data : True +2026-06-24 04:32:00,051 - On-the-fly meas padding : False +2026-06-24 04:32:00,051 - On-the-fly meas resample : False +2026-06-24 04:32:00,051 - On-the-fly simu match mode: None +2026-06-24 04:32:00,051 - +2026-06-24 04:32:00,092 - ### Done initializing PtychoModel model ### +2026-06-24 04:32:00,092 - +2026-06-24 04:32:00,092 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:32:00,092 - +2026-06-24 04:32:00,092 - ### Generating indices, batches, and output_path ### +2026-06-24 04:32:00,094 - d90 = 51.000 px or 10.200 Ang +2026-06-24 04:32:00,094 - Selecting indices with the 'full' mode +2026-06-24 04:32:00,554 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:32:00,629 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:32:00,629 - Original recon_dir_affixes = ['default'] +2026-06-24 04:32:00,629 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:32:00,636 - Path corrected for compatibility: +2026-06-24 04:32:00,636 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_C32_5.97e+03_phi32_274_C34_-4.95e+03_phi34_255_C41_-4.83e+05_phi41_248_C43_1.44e+05_phi43_297_C45_3.78e+04_phi45_238_C50_2.61e+06_C52_-1.66e+07_phi52_60.2_C54_1.48e+07_phi54_228_C56_4.07e+06_phi56_234 +2026-06-24 04:32:00,636 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234 +2026-06-24 04:32:00,637 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234' is generated! +2026-06-24 04:32:00,789 - +2026-06-24 04:32:00,790 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/20260624_043200_ptyrad_log.txt ### +2026-06-24 04:32:00,790 - +2026-06-24 04:32:00,792 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:32:00,792 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:32:00,792 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:32:01,980 - Iter: 1, Total Loss: 1.0303, loss_single: 1.0303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.439 sec +2026-06-24 04:32:02,018 - Iter: 2, Total Loss: 0.9812, loss_single: 0.9812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:32:02,054 - Iter: 3, Total Loss: 0.9408, loss_single: 0.9408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,091 - Iter: 4, Total Loss: 0.9039, loss_single: 0.9039, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,127 - Iter: 5, Total Loss: 0.8769, loss_single: 0.8769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,163 - Iter: 6, Total Loss: 0.8526, loss_single: 0.8526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,200 - Iter: 7, Total Loss: 0.8227, loss_single: 0.8227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,235 - Iter: 8, Total Loss: 0.7930, loss_single: 0.7930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,271 - Iter: 9, Total Loss: 0.7673, loss_single: 0.7673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,341 - Iter: 10, Total Loss: 0.7402, loss_single: 0.7402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,377 - Iter: 11, Total Loss: 0.7097, loss_single: 0.7097, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,413 - Iter: 12, Total Loss: 0.6865, loss_single: 0.6865, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,449 - Iter: 13, Total Loss: 0.6654, loss_single: 0.6654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,485 - Iter: 14, Total Loss: 0.6402, loss_single: 0.6402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,521 - Iter: 15, Total Loss: 0.6180, loss_single: 0.6180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,557 - Iter: 16, Total Loss: 0.5941, loss_single: 0.5941, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,593 - Iter: 17, Total Loss: 0.5666, loss_single: 0.5666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,629 - Iter: 18, Total Loss: 0.5444, loss_single: 0.5444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,665 - Iter: 19, Total Loss: 0.5211, loss_single: 0.5211, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,701 - Iter: 20, Total Loss: 0.4978, loss_single: 0.4978, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,738 - Iter: 21, Total Loss: 0.4783, loss_single: 0.4783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,773 - Iter: 22, Total Loss: 0.4607, loss_single: 0.4607, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,809 - Iter: 23, Total Loss: 0.4462, loss_single: 0.4462, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,845 - Iter: 24, Total Loss: 0.4312, loss_single: 0.4312, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,881 - Iter: 25, Total Loss: 0.4166, loss_single: 0.4166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:02,917 - Iter: 26, Total Loss: 0.4061, loss_single: 0.4061, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,953 - Iter: 27, Total Loss: 0.3969, loss_single: 0.3969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:02,989 - Iter: 28, Total Loss: 0.3888, loss_single: 0.3888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,025 - Iter: 29, Total Loss: 0.3817, loss_single: 0.3817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,061 - Iter: 30, Total Loss: 0.3750, loss_single: 0.3750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,096 - Iter: 31, Total Loss: 0.3691, loss_single: 0.3691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,132 - Iter: 32, Total Loss: 0.3645, loss_single: 0.3645, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,168 - Iter: 33, Total Loss: 0.3600, loss_single: 0.3600, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,204 - Iter: 34, Total Loss: 0.3555, loss_single: 0.3555, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,239 - Iter: 35, Total Loss: 0.3518, loss_single: 0.3518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,275 - Iter: 36, Total Loss: 0.3485, loss_single: 0.3485, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,311 - Iter: 37, Total Loss: 0.3458, loss_single: 0.3458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,347 - Iter: 38, Total Loss: 0.3441, loss_single: 0.3441, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,383 - Iter: 39, Total Loss: 0.3427, loss_single: 0.3427, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,419 - Iter: 40, Total Loss: 0.3409, loss_single: 0.3409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,457 - Iter: 41, Total Loss: 0.3392, loss_single: 0.3392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,493 - Iter: 42, Total Loss: 0.3377, loss_single: 0.3377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,529 - Iter: 43, Total Loss: 0.3359, loss_single: 0.3359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,565 - Iter: 44, Total Loss: 0.3343, loss_single: 0.3343, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,601 - Iter: 45, Total Loss: 0.3334, loss_single: 0.3334, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,636 - Iter: 46, Total Loss: 0.3326, loss_single: 0.3326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,672 - Iter: 47, Total Loss: 0.3317, loss_single: 0.3317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,708 - Iter: 48, Total Loss: 0.3309, loss_single: 0.3309, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,744 - Iter: 49, Total Loss: 0.3302, loss_single: 0.3302, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,779 - Iter: 50, Total Loss: 0.3294, loss_single: 0.3294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,815 - Iter: 51, Total Loss: 0.3286, loss_single: 0.3286, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,852 - Iter: 52, Total Loss: 0.3281, loss_single: 0.3281, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,887 - Iter: 53, Total Loss: 0.3276, loss_single: 0.3276, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:03,923 - Iter: 54, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,960 - Iter: 55, Total Loss: 0.3265, loss_single: 0.3265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:03,996 - Iter: 56, Total Loss: 0.3259, loss_single: 0.3259, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:04,032 - Iter: 57, Total Loss: 0.3253, loss_single: 0.3253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:04,068 - Iter: 58, Total Loss: 0.3248, loss_single: 0.3248, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:04,104 - 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Iter: 95, Total Loss: 0.3093, loss_single: 0.3093, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:05,441 - Iter: 96, Total Loss: 0.3090, loss_single: 0.3090, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:05,477 - Iter: 97, Total Loss: 0.3087, loss_single: 0.3087, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:05,514 - Iter: 98, Total Loss: 0.3084, loss_single: 0.3084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:05,550 - Iter: 99, Total Loss: 0.3081, loss_single: 0.3081, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:05,586 - Iter: 100, Total Loss: 0.3079, loss_single: 0.3079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:05,698 - Saving summary figures for iter 100 +2026-06-24 04:32:09,273 - ### Finished 100 iterations, averaged iter_t = 0.039676 with std = 0.040 ### +2026-06-24 04:32:09,273 - +2026-06-24 04:32:09,273 - ### The PtyRADSolver is finished in 9.296 sec ### +2026-06-24 04:32:09,273 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..8929abafaf5e77d5fccd5daf24222e6a6de7be78 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/simulation_data7__sample_000016.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/simulation_data7__sample_000016.yaml new file mode 100644 index 0000000000000000000000000000000000000000..80054722eec581a23d14061fff44613c13bd4218 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016/gendata3_std_02__simulation_data7__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-426_C12_28.2_phi12_132_C21_-686_phi21_32.5_C23_121_phi23_109_C30_1.05e+07_.07e+06_phi56_234/simulation_data7__sample_000016.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.859851837158203 + probe_aberrations: + C10: -426.4550476074219 + C12: 28.204883575439453 + C21: -685.645263671875 + C23: 120.88688659667969 + C30: 10527491.0 + C32: 5969.8447265625 + C34: -4954.93310546875 + C41: -483082.8125 + C43: 144335.859375 + C45: 37773.69921875 + C50: 2607385.0 + C52: -16625273.0 + C54: 14834470.0 + C56: 4067612.0 + phi12: 132.18526572428206 + phi21: 32.5224033556901 + phi23: 109.2781567953258 + phi32: 273.5249520308622 + phi34: 254.64494312711295 + phi41: 248.01094431081964 + phi43: 297.2431390935683 + phi45: 237.5058948012866 + phi52: 60.18141832419682 + phi54: 227.65098367809037 + phi56: 233.88767039036404 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000016_measurement.h5 + key: measurement + random_seed: 20261591 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000016 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data7__sample_000016 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/20260624_043230_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/20260624_043230_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9f9648af643c5d43cd06202389b5c8370cc05100 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/20260624_043230_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:32:28,375 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:32:28,375 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:32:28,375 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:32:28,375 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:32:28,375 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:32:28,375 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:32:28,375 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:32:28,375 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:32:28,375 - +2026-06-24 04:32:28,483 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:32:28,483 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:32:28,483 - Accelerator.num_process = 1 +2026-06-24 04:32:28,483 - Accelerator.mixed_precision = no +2026-06-24 04:32:28,494 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:32:28,494 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:32:28,494 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:32:28,494 - +2026-06-24 04:32:28,494 - ### System information ### +2026-06-24 04:32:28,494 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:32:28,494 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:32:28,494 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:32:28,494 - Machine: x86_64 +2026-06-24 04:32:28,494 - Processor: x86_64 +2026-06-24 04:32:28,494 - Available CPU cores: 8 +2026-06-24 04:32:28,494 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:32:28,494 - +2026-06-24 04:32:28,494 - ### GPU information ### +2026-06-24 04:32:28,494 - CUDA Available: True +2026-06-24 04:32:28,494 - CUDA Version: 13.0 +2026-06-24 04:32:28,495 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:32:28,495 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:32:28,495 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:32:28,495 - In addition, Triton does not directly support Windows. +2026-06-24 04:32:28,495 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:32:28,522 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:32:28,522 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:32:28,522 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:32:28,522 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:32:28,522 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:32:28,522 - +2026-06-24 04:32:28,522 - ### Python information ### +2026-06-24 04:32:28,524 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:32:28,524 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:32:28,524 - +2026-06-24 04:32:28,524 - ### Packages information ### +2026-06-24 04:32:28,525 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:32:28,526 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:32:28,526 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:32:28,527 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:32:28,528 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:32:28,528 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:32:28,528 - +2026-06-24 04:32:28,528 - ### Loading params file ### +2026-06-24 04:32:28,528 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data7__sample_000018.yaml +2026-06-24 04:32:28,534 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:32:28,535 - Success! Params file validated and defaults applied. +2026-06-24 04:32:28,535 - +2026-06-24 04:32:28,535 - ### Setting GPU Device ### +2026-06-24 04:32:28,535 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:32:28,535 - +2026-06-24 04:32:28,535 - Random seed: 20261593 provided by params file +2026-06-24 04:32:28,536 - ### Initializing Initializer ### +2026-06-24 04:32:28,536 - init_params are displayed below: +2026-06-24 04:32:28,536 - random_seed: 20261593 +2026-06-24 04:32:28,536 - probe_illum_type: electron +2026-06-24 04:32:28,536 - probe_kv: 200.0 +2026-06-24 04:32:28,536 - probe_conv_angle: 9.35141372680664 +2026-06-24 04:32:28,536 - probe_aberrations: {'C10': -265.493, 'C12': -30.984, 'phi12': 317.258, 'C21': -972.332, 'phi21': 340.597, 'C23': 46.215, 'phi23': 144.348, 'C30': 10134859.0, 'C32': -4167.753, 'phi32': 5.856, 'C34': 8201.533, 'phi34': 219.256, 'C41': -14974.071, 'phi41': 338.736, 'C43': -140066.031, 'phi43': 96.652, 'C45': -16976.01, 'phi45': 297.448, 'C50': -7715912.5, 'C52': -2944906.5, 'phi52': 182.959, 'C54': -7187390.0, 'phi54': 186.78, 'C56': 10144350.0, 'phi56': 217.533} +2026-06-24 04:32:28,536 - beam_kev: None +2026-06-24 04:32:28,536 - probe_dRn: None +2026-06-24 04:32:28,536 - probe_Rn: None +2026-06-24 04:32:28,536 - probe_D_H: None +2026-06-24 04:32:28,536 - probe_D_FZP: None +2026-06-24 04:32:28,536 - probe_Ls: None +2026-06-24 04:32:28,536 - meas_Npix: 128 +2026-06-24 04:32:28,536 - pos_N_scans: 256 +2026-06-24 04:32:28,536 - pos_N_scan_slow: 16 +2026-06-24 04:32:28,536 - pos_N_scan_fast: 16 +2026-06-24 04:32:28,536 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:32:28,536 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:32:28,536 - probe_pmode_max: 6 +2026-06-24 04:32:28,536 - probe_pmode_init_pows: [0.02] +2026-06-24 04:32:28,537 - obj_omode_max: 1 +2026-06-24 04:32:28,537 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:32:28,537 - obj_Nlayer: 1 +2026-06-24 04:32:28,537 - obj_slice_thickness: 20.0 +2026-06-24 04:32:28,537 - simu_Npix: None +2026-06-24 04:32:28,537 - simu_match_mode: None +2026-06-24 04:32:28,537 - meas_permute: None +2026-06-24 04:32:28,537 - meas_reshape: [256, 128, 128] +2026-06-24 04:32:28,537 - meas_flipT: [0, 0, 0] +2026-06-24 04:32:28,537 - meas_crop: None +2026-06-24 04:32:28,537 - meas_pad: None +2026-06-24 04:32:28,537 - meas_resample: None +2026-06-24 04:32:28,537 - meas_add_source_size: None +2026-06-24 04:32:28,537 - meas_add_detector_blur: None +2026-06-24 04:32:28,537 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:32:28,537 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:32:28,537 - meas_add_poisson_noise: None +2026-06-24 04:32:28,537 - meas_export: None +2026-06-24 04:32:28,537 - probe_permute: None +2026-06-24 04:32:28,537 - probe_z_shift: None +2026-06-24 04:32:28,537 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:32:28,537 - pos_scan_flipT: None +2026-06-24 04:32:28,537 - pos_scan_affine: None +2026-06-24 04:32:28,537 - pos_scan_rand_std: 0.15 +2026-06-24 04:32:28,537 - obj_z_crop: None +2026-06-24 04:32:28,537 - obj_z_pad: None +2026-06-24 04:32:28,537 - obj_z_resample: None +2026-06-24 04:32:28,537 - meas_source: file +2026-06-24 04:32:28,537 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000018_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:32:28,537 - probe_source: simu +2026-06-24 04:32:28,537 - probe_params: None +2026-06-24 04:32:28,537 - pos_source: simu +2026-06-24 04:32:28,537 - pos_params: None +2026-06-24 04:32:28,537 - obj_source: simu +2026-06-24 04:32:28,537 - obj_params: None +2026-06-24 04:32:28,537 - tilt_source: simu +2026-06-24 04:32:28,537 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:32:28,537 - +2026-06-24 04:32:28,537 - ### Initializing cache ### +2026-06-24 04:32:28,537 - use_cached_obj = False +2026-06-24 04:32:28,537 - use_cached_probe = False +2026-06-24 04:32:28,538 - use_cached_pos = False +2026-06-24 04:32:28,538 - +2026-06-24 04:32:28,538 - ### Initializing measurements ### +2026-06-24 04:32:28,538 - Loading measurements from source = 'file' +2026-06-24 04:32:28,538 - Detected measurement file type = '.h5' +2026-06-24 04:32:28,610 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:32:28,610 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:32:28,612 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0045) +2026-06-24 04:32:28,612 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:32:28,612 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:32:28,613 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:32:28,613 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:32:28,614 - Normalizing by max of the 2D mean pattern intensity: 0.0035403683 +2026-06-24 04:32:28,614 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:32:28,616 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.2849) +2026-06-24 04:32:28,616 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:32:28,617 - Pattern total int. statistics (min, mean, max) = (279.6346, 283.0591, 286.3806), with min/max = 97.6% +2026-06-24 04:32:28,619 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.2849) +2026-06-24 04:32:28,619 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:32:28,619 - +2026-06-24 04:32:28,619 - ### Setting up calibration ### +2026-06-24 04:32:28,619 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:32:28,619 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:32:28,619 - Radius of fitted bright field disk (RBF) = 9.41 px with meas_Npix = 128 +2026-06-24 04:32:28,619 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1470 +2026-06-24 04:32:28,619 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:32:28,619 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:32:28,842 - Initial guess: center=(63.63, 63.63), radius=9.41, Gaussian blur std=0.50 +2026-06-24 04:32:28,854 - Final fit: center=(63.63, 63.63), radius=9.41, Gaussian blur std=0.62 +2026-06-24 04:32:28,854 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.55 px with Npix = 128 +2026-06-24 04:32:28,854 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:32:28,855 - +2026-06-24 04:32:28,855 - ### Setting init_variables dict ### +2026-06-24 04:32:28,855 - Derived values given input init_params: +2026-06-24 04:32:28,855 - kv = 200.0 kV +2026-06-24 04:32:28,855 - wavelength = 0.0251 Ang +2026-06-24 04:32:28,855 - conv_angle = 9.35141372680664 mrad +2026-06-24 04:32:28,855 - Npix = 128 px +2026-06-24 04:32:28,855 - dk = 0.0391 Ang^-1 +2026-06-24 04:32:28,855 - kMax = 2.5000 Ang^-1 +2026-06-24 04:32:28,855 - da = 0.9797 mrad +2026-06-24 04:32:28,855 - angleMax = 62.6984 mrad +2026-06-24 04:32:28,855 - RBF = 9.5456 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:32:28,855 - n_alpha = 6.7047 (# conv_angle) +2026-06-24 04:32:28,855 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:32:28,855 - Rayleigh-limited resolution = 1.6359 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:32:28,855 - Real space probe extent = 25.6000 Ang +2026-06-24 04:32:28,855 - +2026-06-24 04:32:28,855 - ### Initializing probe ### +2026-06-24 04:32:28,855 - Loading probe from source = 'simu' +2026-06-24 04:32:28,855 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:32:28,855 - Start simulating STEM probe +2026-06-24 04:32:28,855 - kv = 200.0 kV +2026-06-24 04:32:28,855 - wavelength = 0.0251 Ang +2026-06-24 04:32:28,855 - conv_angle = 9.35141372680664 mrad +2026-06-24 04:32:28,855 - Npix = 128 px +2026-06-24 04:32:28,856 - dk = 0.0391 Ang^-1 +2026-06-24 04:32:28,856 - kMax = 2.5000 Ang^-1 +2026-06-24 04:32:28,856 - alpha_max = 62.6984 mrad +2026-06-24 04:32:28,856 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:32:28,856 - Rayleigh-limited resolution = 1.6359 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:32:28,856 - Real space probe extent = 25.6000 Ang +2026-06-24 04:32:28,856 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:32:28,856 - ----------------------------------------------------------------------------------- +2026-06-24 04:32:28,856 - C1,0 C1 -265.4930 - Defocus (C10 = -df) +2026-06-24 04:32:28,856 - C1,2 A1 -30.9840 317.26 2-fold astigmatism +2026-06-24 04:32:28,856 - C2,1 3*B2 -972.3320 340.60 Axial coma +2026-06-24 04:32:28,856 - C2,3 A2 46.2150 144.35 3-fold astigmatism +2026-06-24 04:32:28,856 - C3,0 C3 10134859.0000 - Spherical aberration +2026-06-24 04:32:28,856 - C3,2 4*S3 -4167.7530 5.86 Axial star aberration +2026-06-24 04:32:28,856 - C3,4 A3 8201.5330 219.26 4-fold astigmatism +2026-06-24 04:32:28,856 - C4,1 4*B4 -14974.0710 338.74 Axial coma(4th) +2026-06-24 04:32:28,856 - C4,3 4*D4 -140066.0310 96.65 3-lobe aberration +2026-06-24 04:32:28,856 - C4,5 A4 -16976.0100 297.45 5-fold astigmatism +2026-06-24 04:32:28,856 - C5,0 C5 -7715912.5000 - Spherical aberration (5th) +2026-06-24 04:32:28,856 - C5,2 6*S5 -2944906.5000 182.96 Axial star aberration(5th) +2026-06-24 04:32:28,856 - C5,4 6*R5 -7187390.0000 186.78 4-lobe aberration +2026-06-24 04:32:28,856 - C5,6 A5 10144350.0000 217.53 6-fold astigmatism +2026-06-24 04:32:28,859 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:32:28,859 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:32:28,859 - Creating 5 new probe modes from the major mode +2026-06-24 04:32:28,859 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:32:29,075 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:32:29,076 - Orthogonalizing 6 pmodes +2026-06-24 04:32:29,079 - Sorting 6 pmodes by their intensities +2026-06-24 04:32:29,079 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:32:29,080 - sum(|probe_data|**2) = 283.06, while meas_total_ints (min, mean, max) = (279.6346, 283.0591, 286.3806) +2026-06-24 04:32:29,080 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:32:29,080 - +2026-06-24 04:32:29,080 - ### Initializing probe positions ### +2026-06-24 04:32:29,080 - Loading probe positions from source = 'simu' +2026-06-24 04:32:29,080 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:32:29,080 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:32:29,080 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:32:29,082 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:32:29,083 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:32:29,083 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:32:29,083 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:32:29,083 - +2026-06-24 04:32:29,083 - ### Initializing object ### +2026-06-24 04:32:29,083 - Loading object from source = 'simu' +2026-06-24 04:32:29,083 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:32:29,084 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:32:29,084 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:32:29,085 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:32:29,085 - +2026-06-24 04:32:29,085 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:32:29,085 - omode_occu (omode) = float32, (1,) +2026-06-24 04:32:29,085 - +2026-06-24 04:32:29,085 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:32:29,085 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:32:29,085 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:32:29,086 - +2026-06-24 04:32:29,086 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:32:29,086 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:32:29,086 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:32:29,086 - +2026-06-24 04:32:29,086 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:32:29,086 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:32:29,086 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:32:29,086 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:32:29,086 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:32:29,086 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:32:29,086 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:32:29,086 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:32:29,086 - +2026-06-24 04:32:29,086 - ### Collecting reconstruction provenance ### +2026-06-24 04:32:29,086 - Reconstruction provenance is collected and initialized. +2026-06-24 04:32:29,086 - +2026-06-24 04:32:29,086 - ### Initializing loss function ### +2026-06-24 04:32:29,086 - Active loss types: +2026-06-24 04:32:29,086 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:32:29,087 - +2026-06-24 04:32:29,087 - ### Initializing constraint function ### +2026-06-24 04:32:29,087 - Active constraint types: +2026-06-24 04:32:29,087 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:32:29,087 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:32:29,087 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:32:29,087 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:32:29,087 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:32:29,087 - +2026-06-24 04:32:29,087 - ### Done initializing PtyRADSolver ### +2026-06-24 04:32:29,087 - +2026-06-24 04:32:29,218 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:32:29,219 - +2026-06-24 04:32:29,219 - ### Initializing PtychoModel model ### +2026-06-24 04:32:29,289 - ### PtychoModel optimizable variables ### +2026-06-24 04:32:29,289 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:29,289 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:29,290 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:32:29,290 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:32:29,290 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:32:29,290 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:32:29,290 - +2026-06-24 04:32:29,290 - ### Optimizable variables statitsics ### +2026-06-24 04:32:29,290 - Total measurement values : 4,194,304 +2026-06-24 04:32:29,290 - Total optimizing variables: 278,728 +2026-06-24 04:32:29,290 - Overdetermined ratio : 15.05 +2026-06-24 04:32:29,290 - +2026-06-24 04:32:29,290 - ### Model behavior ### +2026-06-24 04:32:29,290 - Tilt propagator : False +2026-06-24 04:32:29,290 - Change slice thickness : False +2026-06-24 04:32:29,290 - Detector blur : False +2026-06-24 04:32:29,290 - Preload data : True +2026-06-24 04:32:29,290 - On-the-fly meas padding : False +2026-06-24 04:32:29,290 - On-the-fly meas resample : False +2026-06-24 04:32:29,290 - On-the-fly simu match mode: None +2026-06-24 04:32:29,290 - +2026-06-24 04:32:29,332 - ### Done initializing PtychoModel model ### +2026-06-24 04:32:29,332 - +2026-06-24 04:32:29,332 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:32:29,332 - +2026-06-24 04:32:29,332 - ### Generating indices, batches, and output_path ### +2026-06-24 04:32:29,333 - d90 = 51.000 px or 10.200 Ang +2026-06-24 04:32:29,333 - Selecting indices with the 'full' mode +2026-06-24 04:32:29,798 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:32:29,875 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:32:29,875 - Original recon_dir_affixes = ['default'] +2026-06-24 04:32:29,875 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:32:29,882 - Path corrected for compatibility: +2026-06-24 04:32:29,882 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C32_-4.17e+03_phi32_5.86_C34_8.2e+03_phi34_219_C41_-1.5e+04_phi41_339_C43_-1.4e+05_phi43_96.7_C45_-1.7e+04_phi45_297_C50_-7.72e+06_C52_-2.94e+06_phi52_183_C54_-7.19e+06_phi54_187_C56_1.01e+07_phi56_218 +2026-06-24 04:32:29,882 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218 +2026-06-24 04:32:29,883 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218' is generated! +2026-06-24 04:32:30,036 - +2026-06-24 04:32:30,037 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/20260624_043230_ptyrad_log.txt ### +2026-06-24 04:32:30,037 - +2026-06-24 04:32:30,038 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:32:30,038 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:32:30,038 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:32:31,239 - Iter: 1, Total Loss: 0.9957, loss_single: 0.9957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.437 sec +2026-06-24 04:32:31,276 - Iter: 2, Total Loss: 0.9356, loss_single: 0.9356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:32:31,311 - Iter: 3, Total Loss: 0.8897, loss_single: 0.8897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,346 - Iter: 4, Total Loss: 0.8533, loss_single: 0.8533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,382 - Iter: 5, Total Loss: 0.8164, loss_single: 0.8164, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,417 - Iter: 6, Total Loss: 0.7814, loss_single: 0.7814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,452 - Iter: 7, Total Loss: 0.7514, loss_single: 0.7514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,488 - Iter: 8, Total Loss: 0.7154, loss_single: 0.7154, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,523 - Iter: 9, Total Loss: 0.6896, loss_single: 0.6896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,559 - Iter: 10, Total Loss: 0.6688, loss_single: 0.6688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,594 - Iter: 11, Total Loss: 0.6452, loss_single: 0.6452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,629 - Iter: 12, Total Loss: 0.6242, loss_single: 0.6242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,665 - Iter: 13, Total Loss: 0.6064, loss_single: 0.6064, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,700 - Iter: 14, Total Loss: 0.5898, loss_single: 0.5898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,736 - Iter: 15, Total Loss: 0.5746, loss_single: 0.5746, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,771 - Iter: 16, Total Loss: 0.5609, loss_single: 0.5609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,806 - Iter: 17, Total Loss: 0.5472, loss_single: 0.5472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,842 - Iter: 18, Total Loss: 0.5358, loss_single: 0.5358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,877 - Iter: 19, Total Loss: 0.5230, loss_single: 0.5230, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,912 - Iter: 20, Total Loss: 0.5119, loss_single: 0.5119, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,948 - Iter: 21, Total Loss: 0.5028, loss_single: 0.5028, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:31,983 - Iter: 22, Total Loss: 0.4924, loss_single: 0.4924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,018 - Iter: 23, Total Loss: 0.4841, loss_single: 0.4841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,054 - Iter: 24, Total Loss: 0.4788, loss_single: 0.4788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,089 - Iter: 25, Total Loss: 0.4757, loss_single: 0.4757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,124 - Iter: 26, Total Loss: 0.4723, loss_single: 0.4723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,163 - Iter: 27, Total Loss: 0.4686, loss_single: 0.4686, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 04:32:32,198 - Iter: 28, Total Loss: 0.4657, loss_single: 0.4657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,233 - Iter: 29, Total Loss: 0.4627, loss_single: 0.4627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,268 - Iter: 30, Total Loss: 0.4602, loss_single: 0.4602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,303 - Iter: 31, Total Loss: 0.4581, loss_single: 0.4581, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,339 - Iter: 32, Total Loss: 0.4567, loss_single: 0.4567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:32,375 - Iter: 33, Total Loss: 0.4548, loss_single: 0.4548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,427 - Iter: 34, Total Loss: 0.4526, loss_single: 0.4526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:32:32,462 - Iter: 35, Total Loss: 0.4506, loss_single: 0.4506, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,497 - Iter: 36, Total Loss: 0.4490, loss_single: 0.4490, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,533 - Iter: 37, Total Loss: 0.4477, loss_single: 0.4477, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,568 - Iter: 38, Total Loss: 0.4466, loss_single: 0.4466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,604 - Iter: 39, Total Loss: 0.4453, loss_single: 0.4453, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,638 - Iter: 40, Total Loss: 0.4439, loss_single: 0.4439, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,675 - Iter: 41, Total Loss: 0.4429, loss_single: 0.4429, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,710 - Iter: 42, Total Loss: 0.4422, loss_single: 0.4422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,746 - Iter: 43, Total Loss: 0.4416, loss_single: 0.4416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,781 - Iter: 44, Total Loss: 0.4409, loss_single: 0.4409, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,816 - Iter: 45, Total Loss: 0.4399, loss_single: 0.4399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,852 - Iter: 46, Total Loss: 0.4391, loss_single: 0.4391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,887 - Iter: 47, Total Loss: 0.4384, loss_single: 0.4384, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,922 - Iter: 48, Total Loss: 0.4379, loss_single: 0.4379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,958 - Iter: 49, Total Loss: 0.4375, loss_single: 0.4375, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:32,993 - Iter: 50, Total Loss: 0.4369, loss_single: 0.4369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,028 - Iter: 51, Total Loss: 0.4362, loss_single: 0.4362, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,064 - Iter: 52, Total Loss: 0.4358, loss_single: 0.4358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,099 - Iter: 53, Total Loss: 0.4355, loss_single: 0.4355, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,135 - Iter: 54, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,170 - Iter: 55, Total Loss: 0.4348, loss_single: 0.4348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,205 - Iter: 56, Total Loss: 0.4345, loss_single: 0.4345, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,240 - Iter: 57, Total Loss: 0.4342, loss_single: 0.4342, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,275 - Iter: 58, Total Loss: 0.4340, loss_single: 0.4340, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:33,311 - 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Iter: 95, Total Loss: 0.4268, loss_single: 0.4268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:34,620 - Iter: 96, Total Loss: 0.4268, loss_single: 0.4268, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:34,655 - Iter: 97, Total Loss: 0.4266, loss_single: 0.4266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:34,690 - Iter: 98, Total Loss: 0.4265, loss_single: 0.4265, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:34,726 - Iter: 99, Total Loss: 0.4264, loss_single: 0.4264, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:32:34,761 - Iter: 100, Total Loss: 0.4263, loss_single: 0.4263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:32:34,872 - Saving summary figures for iter 100 +2026-06-24 04:32:38,433 - ### Finished 100 iterations, averaged iter_t = 0.038995 with std = 0.040 ### +2026-06-24 04:32:38,433 - +2026-06-24 04:32:38,433 - ### The PtyRADSolver is finished in 9.215 sec ### +2026-06-24 04:32:38,433 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..2163d9f22506277128f81b2d3ebffd0e406f8e77 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/simulation_data7__sample_000018.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/simulation_data7__sample_000018.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f91dc14252003e54fb81d0a1e7a4a1434574f10a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018/gendata3_std_02__simulation_data7__sample_000018_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_-31_phi12_317_C21_-972_phi21_341_C23_46.2_phi23_144_C30_1.01e+07_C.01e+07_phi56_218/simulation_data7__sample_000018.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.35141372680664 + probe_aberrations: + C10: -265.4933166503906 + C12: -30.98445701599121 + C21: -972.3320922851562 + C23: 46.21458435058594 + C30: 10134859.0 + C32: -4167.75341796875 + C34: 8201.533203125 + C41: -14974.0712890625 + C43: -140066.03125 + C45: -16976.009765625 + C50: -7715912.5 + C52: -2944906.5 + C54: -7187390.0 + C56: 10144350.0 + phi12: 317.25824347510365 + phi21: 340.5968359444971 + phi23: 144.34751037175698 + phi32: 5.855852866513501 + phi34: 219.2564079805779 + phi41: 338.73550011264194 + phi43: 96.65178030318101 + phi45: 297.44820869320876 + phi52: 182.9594303536745 + phi54: 186.7795141753276 + phi56: 217.53270046049846 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000018_measurement.h5 + key: measurement + random_seed: 20261593 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000018 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data7__sample_000018 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/20260624_043527_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/20260624_043527_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c1d4b433dda2afabf7f7b890b22802594478b867 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/20260624_043527_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:35:26,035 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:35:26,036 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:35:26,036 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:35:26,036 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:35:26,036 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:35:26,036 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:35:26,036 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:35:26,036 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:35:26,036 - +2026-06-24 04:35:26,142 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:35:26,142 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:35:26,142 - Accelerator.num_process = 1 +2026-06-24 04:35:26,142 - Accelerator.mixed_precision = no +2026-06-24 04:35:26,153 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:35:26,153 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:35:26,153 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:35:26,153 - +2026-06-24 04:35:26,153 - ### System information ### +2026-06-24 04:35:26,153 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:35:26,153 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:35:26,153 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:35:26,153 - Machine: x86_64 +2026-06-24 04:35:26,153 - Processor: x86_64 +2026-06-24 04:35:26,153 - Available CPU cores: 8 +2026-06-24 04:35:26,153 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:35:26,153 - +2026-06-24 04:35:26,153 - ### GPU information ### +2026-06-24 04:35:26,153 - CUDA Available: True +2026-06-24 04:35:26,153 - CUDA Version: 13.0 +2026-06-24 04:35:26,154 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:35:26,154 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:35:26,154 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:35:26,154 - In addition, Triton does not directly support Windows. +2026-06-24 04:35:26,154 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:35:26,181 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:35:26,181 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:35:26,181 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:35:26,181 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:35:26,181 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:35:26,181 - +2026-06-24 04:35:26,181 - ### Python information ### +2026-06-24 04:35:26,183 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:35:26,183 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:35:26,183 - +2026-06-24 04:35:26,183 - ### Packages information ### +2026-06-24 04:35:26,183 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:35:26,184 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:35:26,185 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:35:26,185 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:35:26,186 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:35:26,186 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:35:26,186 - +2026-06-24 04:35:26,186 - ### Loading params file ### +2026-06-24 04:35:26,186 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data7__sample_000030.yaml +2026-06-24 04:35:26,192 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:35:26,193 - Success! Params file validated and defaults applied. +2026-06-24 04:35:26,193 - +2026-06-24 04:35:26,193 - ### Setting GPU Device ### +2026-06-24 04:35:26,194 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:35:26,194 - +2026-06-24 04:35:26,194 - Random seed: 20261605 provided by params file +2026-06-24 04:35:26,194 - ### Initializing Initializer ### +2026-06-24 04:35:26,194 - init_params are displayed below: +2026-06-24 04:35:26,194 - random_seed: 20261605 +2026-06-24 04:35:26,194 - probe_illum_type: electron +2026-06-24 04:35:26,194 - probe_kv: 200.0 +2026-06-24 04:35:26,194 - probe_conv_angle: 9.487207412719727 +2026-06-24 04:35:26,194 - probe_aberrations: {'C10': -321.237, 'C12': 36.513, 'phi12': 212.572, 'C21': -269.003, 'phi21': 96.055, 'C23': 715.233, 'phi23': 21.623, 'C30': 11070396.0, 'C32': -5687.701, 'phi32': 284.893, 'C34': 9261.953, 'phi34': 300.237, 'C41': 92159.977, 'phi41': 199.522, 'C43': 403354.031, 'phi43': 66.096, 'C45': 416371.906, 'phi45': 355.457, 'C50': -9298595.0, 'C52': 1324881.625, 'phi52': 5.098, 'C54': -4890564.5, 'phi54': 30.006, 'C56': -9115431.0, 'phi56': 330.216} +2026-06-24 04:35:26,194 - beam_kev: None +2026-06-24 04:35:26,194 - probe_dRn: None +2026-06-24 04:35:26,194 - probe_Rn: None +2026-06-24 04:35:26,194 - probe_D_H: None +2026-06-24 04:35:26,194 - probe_D_FZP: None +2026-06-24 04:35:26,194 - probe_Ls: None +2026-06-24 04:35:26,194 - meas_Npix: 128 +2026-06-24 04:35:26,194 - pos_N_scans: 256 +2026-06-24 04:35:26,195 - pos_N_scan_slow: 16 +2026-06-24 04:35:26,195 - pos_N_scan_fast: 16 +2026-06-24 04:35:26,195 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:35:26,195 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:35:26,195 - probe_pmode_max: 6 +2026-06-24 04:35:26,195 - probe_pmode_init_pows: [0.02] +2026-06-24 04:35:26,195 - obj_omode_max: 1 +2026-06-24 04:35:26,195 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:35:26,195 - obj_Nlayer: 1 +2026-06-24 04:35:26,195 - obj_slice_thickness: 20.0 +2026-06-24 04:35:26,195 - simu_Npix: None +2026-06-24 04:35:26,195 - simu_match_mode: None +2026-06-24 04:35:26,195 - meas_permute: None +2026-06-24 04:35:26,195 - meas_reshape: [256, 128, 128] +2026-06-24 04:35:26,195 - meas_flipT: [0, 0, 0] +2026-06-24 04:35:26,195 - meas_crop: None +2026-06-24 04:35:26,195 - meas_pad: None +2026-06-24 04:35:26,195 - meas_resample: None +2026-06-24 04:35:26,195 - meas_add_source_size: None +2026-06-24 04:35:26,195 - meas_add_detector_blur: None +2026-06-24 04:35:26,195 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:35:26,195 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:35:26,195 - meas_add_poisson_noise: None +2026-06-24 04:35:26,195 - meas_export: None +2026-06-24 04:35:26,195 - probe_permute: None +2026-06-24 04:35:26,195 - probe_z_shift: None +2026-06-24 04:35:26,195 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:35:26,195 - pos_scan_flipT: None +2026-06-24 04:35:26,195 - pos_scan_affine: None +2026-06-24 04:35:26,195 - pos_scan_rand_std: 0.15 +2026-06-24 04:35:26,195 - obj_z_crop: None +2026-06-24 04:35:26,195 - obj_z_pad: None +2026-06-24 04:35:26,195 - obj_z_resample: None +2026-06-24 04:35:26,195 - meas_source: file +2026-06-24 04:35:26,195 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000030_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:35:26,195 - probe_source: simu +2026-06-24 04:35:26,195 - probe_params: None +2026-06-24 04:35:26,195 - pos_source: simu +2026-06-24 04:35:26,195 - pos_params: None +2026-06-24 04:35:26,195 - obj_source: simu +2026-06-24 04:35:26,195 - obj_params: None +2026-06-24 04:35:26,196 - tilt_source: simu +2026-06-24 04:35:26,196 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:35:26,196 - +2026-06-24 04:35:26,196 - ### Initializing cache ### +2026-06-24 04:35:26,196 - use_cached_obj = False +2026-06-24 04:35:26,196 - use_cached_probe = False +2026-06-24 04:35:26,196 - use_cached_pos = False +2026-06-24 04:35:26,196 - +2026-06-24 04:35:26,196 - ### Initializing measurements ### +2026-06-24 04:35:26,196 - Loading measurements from source = 'file' +2026-06-24 04:35:26,196 - Detected measurement file type = '.h5' +2026-06-24 04:35:26,271 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:35:26,271 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:35:26,272 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0038) +2026-06-24 04:35:26,272 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:35:26,272 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:35:26,274 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:35:26,274 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:35:26,274 - Normalizing by max of the 2D mean pattern intensity: 0.003147441 +2026-06-24 04:35:26,275 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:35:26,276 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0194, 1.2128) +2026-06-24 04:35:26,277 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:35:26,278 - Pattern total int. statistics (min, mean, max) = (315.3701, 317.0888, 319.2206), with min/max = 98.8% +2026-06-24 04:35:26,279 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0194, 1.2128) +2026-06-24 04:35:26,279 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:35:26,279 - +2026-06-24 04:35:26,279 - ### Setting up calibration ### +2026-06-24 04:35:26,279 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:35:26,279 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:35:26,279 - Radius of fitted bright field disk (RBF) = 9.57 px with meas_Npix = 128 +2026-06-24 04:35:26,280 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1496 +2026-06-24 04:35:26,280 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:35:26,280 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:35:26,502 - Initial guess: center=(63.65, 63.62), radius=9.57, Gaussian blur std=0.50 +2026-06-24 04:35:26,512 - Final fit: center=(63.65, 63.62), radius=9.57, Gaussian blur std=0.57 +2026-06-24 04:35:26,512 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.68 px with Npix = 128 +2026-06-24 04:35:26,512 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:35:26,512 - +2026-06-24 04:35:26,513 - ### Setting init_variables dict ### +2026-06-24 04:35:26,513 - Derived values given input init_params: +2026-06-24 04:35:26,513 - kv = 200.0 kV +2026-06-24 04:35:26,513 - wavelength = 0.0251 Ang +2026-06-24 04:35:26,513 - conv_angle = 9.487207412719727 mrad +2026-06-24 04:35:26,513 - Npix = 128 px +2026-06-24 04:35:26,513 - dk = 0.0391 Ang^-1 +2026-06-24 04:35:26,513 - kMax = 2.5000 Ang^-1 +2026-06-24 04:35:26,513 - da = 0.9797 mrad +2026-06-24 04:35:26,513 - angleMax = 62.6984 mrad +2026-06-24 04:35:26,513 - RBF = 9.6842 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:35:26,513 - n_alpha = 6.6087 (# conv_angle) +2026-06-24 04:35:26,513 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:35:26,513 - Rayleigh-limited resolution = 1.6125 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:35:26,513 - Real space probe extent = 25.6000 Ang +2026-06-24 04:35:26,513 - +2026-06-24 04:35:26,513 - ### Initializing probe ### +2026-06-24 04:35:26,513 - Loading probe from source = 'simu' +2026-06-24 04:35:26,513 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:35:26,513 - Start simulating STEM probe +2026-06-24 04:35:26,513 - kv = 200.0 kV +2026-06-24 04:35:26,513 - wavelength = 0.0251 Ang +2026-06-24 04:35:26,513 - conv_angle = 9.487207412719727 mrad +2026-06-24 04:35:26,513 - Npix = 128 px +2026-06-24 04:35:26,513 - dk = 0.0391 Ang^-1 +2026-06-24 04:35:26,514 - kMax = 2.5000 Ang^-1 +2026-06-24 04:35:26,514 - alpha_max = 62.6984 mrad +2026-06-24 04:35:26,514 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:35:26,514 - Rayleigh-limited resolution = 1.6125 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:35:26,514 - Real space probe extent = 25.6000 Ang +2026-06-24 04:35:26,514 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:35:26,514 - ----------------------------------------------------------------------------------- +2026-06-24 04:35:26,514 - C1,0 C1 -321.2370 - Defocus (C10 = -df) +2026-06-24 04:35:26,514 - C1,2 A1 36.5130 212.57 2-fold astigmatism +2026-06-24 04:35:26,514 - C2,1 3*B2 -269.0030 96.06 Axial coma +2026-06-24 04:35:26,514 - C2,3 A2 715.2330 21.62 3-fold astigmatism +2026-06-24 04:35:26,514 - C3,0 C3 11070396.0000 - Spherical aberration +2026-06-24 04:35:26,514 - C3,2 4*S3 -5687.7010 284.89 Axial star aberration +2026-06-24 04:35:26,514 - C3,4 A3 9261.9530 300.24 4-fold astigmatism +2026-06-24 04:35:26,514 - C4,1 4*B4 92159.9770 199.52 Axial coma(4th) +2026-06-24 04:35:26,514 - C4,3 4*D4 403354.0310 66.10 3-lobe aberration +2026-06-24 04:35:26,514 - C4,5 A4 416371.9060 355.46 5-fold astigmatism +2026-06-24 04:35:26,514 - C5,0 C5 -9298595.0000 - Spherical aberration (5th) +2026-06-24 04:35:26,514 - C5,2 6*S5 1324881.6250 5.10 Axial star aberration(5th) +2026-06-24 04:35:26,514 - C5,4 6*R5 -4890564.5000 30.01 4-lobe aberration +2026-06-24 04:35:26,514 - C5,6 A5 -9115431.0000 330.22 6-fold astigmatism +2026-06-24 04:35:26,517 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:35:26,517 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:35:26,517 - Creating 5 new probe modes from the major mode +2026-06-24 04:35:26,517 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:35:26,734 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:35:26,735 - Orthogonalizing 6 pmodes +2026-06-24 04:35:26,738 - Sorting 6 pmodes by their intensities +2026-06-24 04:35:26,739 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:35:26,739 - sum(|probe_data|**2) = 317.09, while meas_total_ints (min, mean, max) = (315.3701, 317.0888, 319.2206) +2026-06-24 04:35:26,739 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:35:26,739 - +2026-06-24 04:35:26,739 - ### Initializing probe positions ### +2026-06-24 04:35:26,739 - Loading probe positions from source = 'simu' +2026-06-24 04:35:26,739 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:35:26,739 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:35:26,740 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:35:26,742 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:35:26,742 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:35:26,742 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:35:26,742 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:35:26,742 - +2026-06-24 04:35:26,742 - ### Initializing object ### +2026-06-24 04:35:26,742 - Loading object from source = 'simu' +2026-06-24 04:35:26,742 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:35:26,744 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:35:26,744 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:35:26,744 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:35:26,744 - +2026-06-24 04:35:26,744 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:35:26,744 - omode_occu (omode) = float32, (1,) +2026-06-24 04:35:26,744 - +2026-06-24 04:35:26,744 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:35:26,744 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:35:26,745 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:35:26,745 - +2026-06-24 04:35:26,745 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:35:26,745 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:35:26,745 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:35:26,745 - +2026-06-24 04:35:26,745 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:35:26,745 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:35:26,745 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:35:26,745 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:35:26,745 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:35:26,745 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:35:26,745 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:35:26,745 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:35:26,745 - +2026-06-24 04:35:26,745 - ### Collecting reconstruction provenance ### +2026-06-24 04:35:26,746 - Reconstruction provenance is collected and initialized. +2026-06-24 04:35:26,746 - +2026-06-24 04:35:26,746 - ### Initializing loss function ### +2026-06-24 04:35:26,746 - Active loss types: +2026-06-24 04:35:26,746 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:35:26,746 - +2026-06-24 04:35:26,746 - ### Initializing constraint function ### +2026-06-24 04:35:26,746 - Active constraint types: +2026-06-24 04:35:26,746 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:35:26,746 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:35:26,746 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:35:26,746 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:35:26,746 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:35:26,746 - +2026-06-24 04:35:26,746 - ### Done initializing PtyRADSolver ### +2026-06-24 04:35:26,746 - +2026-06-24 04:35:26,872 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:35:26,872 - +2026-06-24 04:35:26,872 - ### Initializing PtychoModel model ### +2026-06-24 04:35:26,943 - ### PtychoModel optimizable variables ### +2026-06-24 04:35:26,943 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:35:26,943 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:35:26,943 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:35:26,943 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:35:26,944 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:35:26,944 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:35:26,944 - +2026-06-24 04:35:26,944 - ### Optimizable variables statitsics ### +2026-06-24 04:35:26,944 - Total measurement values : 4,194,304 +2026-06-24 04:35:26,944 - Total optimizing variables: 278,728 +2026-06-24 04:35:26,944 - Overdetermined ratio : 15.05 +2026-06-24 04:35:26,944 - +2026-06-24 04:35:26,944 - ### Model behavior ### +2026-06-24 04:35:26,944 - Tilt propagator : False +2026-06-24 04:35:26,944 - Change slice thickness : False +2026-06-24 04:35:26,944 - Detector blur : False +2026-06-24 04:35:26,944 - Preload data : True +2026-06-24 04:35:26,944 - On-the-fly meas padding : False +2026-06-24 04:35:26,944 - On-the-fly meas resample : False +2026-06-24 04:35:26,944 - On-the-fly simu match mode: None +2026-06-24 04:35:26,944 - +2026-06-24 04:35:26,986 - ### Done initializing PtychoModel model ### +2026-06-24 04:35:26,986 - +2026-06-24 04:35:26,987 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:35:26,987 - +2026-06-24 04:35:26,987 - ### Generating indices, batches, and output_path ### +2026-06-24 04:35:26,988 - d90 = 53.000 px or 10.600 Ang +2026-06-24 04:35:26,988 - Selecting indices with the 'full' mode +2026-06-24 04:35:27,449 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:35:27,526 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:35:27,526 - Original recon_dir_affixes = ['default'] +2026-06-24 04:35:27,527 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:35:27,533 - Path corrected for compatibility: +2026-06-24 04:35:27,533 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07_C32_-5.69e+03_phi32_285_C34_9.26e+03_phi34_300_C41_9.22e+04_phi41_200_C43_4.03e+05_phi43_66.1_C45_4.16e+05_phi45_355_C50_-9.3e+06_C52_1.32e+06_phi52_5.1_C54_-4.89e+06_phi54_30_C56_-9.12e+06_phi56_330 +2026-06-24 04:35:27,533 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330 +2026-06-24 04:35:27,534 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330' is generated! +2026-06-24 04:35:27,685 - +2026-06-24 04:35:27,686 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/20260624_043527_ptyrad_log.txt ### +2026-06-24 04:35:27,686 - +2026-06-24 04:35:27,688 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:35:27,688 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:35:27,688 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:35:28,915 - Iter: 1, Total Loss: 1.0634, loss_single: 1.0634, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.445 sec +2026-06-24 04:35:28,952 - Iter: 2, Total Loss: 1.0210, loss_single: 1.0210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:35:28,989 - Iter: 3, Total Loss: 0.9846, loss_single: 0.9846, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,025 - Iter: 4, Total Loss: 0.9457, loss_single: 0.9457, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,061 - Iter: 5, Total Loss: 0.9101, loss_single: 0.9101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,097 - Iter: 6, Total Loss: 0.8827, loss_single: 0.8827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,132 - Iter: 7, Total Loss: 0.8546, loss_single: 0.8546, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,168 - Iter: 8, Total Loss: 0.8257, loss_single: 0.8257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,204 - Iter: 9, Total Loss: 0.7967, loss_single: 0.7967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,240 - Iter: 10, Total Loss: 0.7633, loss_single: 0.7633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,275 - Iter: 11, Total Loss: 0.7346, loss_single: 0.7346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,311 - Iter: 12, Total Loss: 0.7075, loss_single: 0.7075, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,347 - Iter: 13, Total Loss: 0.6829, loss_single: 0.6829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,382 - Iter: 14, Total Loss: 0.6606, loss_single: 0.6606, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,418 - Iter: 15, Total Loss: 0.6362, loss_single: 0.6362, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,454 - Iter: 16, Total Loss: 0.6131, loss_single: 0.6131, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,490 - Iter: 17, Total Loss: 0.5887, loss_single: 0.5887, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,525 - Iter: 18, Total Loss: 0.5666, loss_single: 0.5666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,561 - Iter: 19, Total Loss: 0.5470, loss_single: 0.5470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,597 - Iter: 20, Total Loss: 0.5297, loss_single: 0.5297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,633 - Iter: 21, Total Loss: 0.5098, loss_single: 0.5098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,669 - Iter: 22, Total Loss: 0.4871, loss_single: 0.4871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,708 - Iter: 23, Total Loss: 0.4647, loss_single: 0.4647, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 04:35:29,744 - Iter: 24, Total Loss: 0.4470, loss_single: 0.4470, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,780 - Iter: 25, Total Loss: 0.4312, loss_single: 0.4312, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,815 - Iter: 26, Total Loss: 0.4132, loss_single: 0.4132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,851 - Iter: 27, Total Loss: 0.3965, loss_single: 0.3965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,886 - Iter: 28, Total Loss: 0.3787, loss_single: 0.3787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,923 - Iter: 29, Total Loss: 0.3631, loss_single: 0.3631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:29,958 - Iter: 30, Total Loss: 0.3497, loss_single: 0.3497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:29,994 - Iter: 31, Total Loss: 0.3390, loss_single: 0.3390, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,029 - Iter: 32, Total Loss: 0.3287, loss_single: 0.3287, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,066 - Iter: 33, Total Loss: 0.3169, loss_single: 0.3169, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,102 - Iter: 34, Total Loss: 0.3102, loss_single: 0.3102, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,138 - Iter: 35, Total Loss: 0.3041, loss_single: 0.3041, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,174 - Iter: 36, Total Loss: 0.2973, loss_single: 0.2973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,210 - Iter: 37, Total Loss: 0.2925, loss_single: 0.2925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,246 - Iter: 38, Total Loss: 0.2878, loss_single: 0.2878, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,282 - Iter: 39, Total Loss: 0.2830, loss_single: 0.2830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,317 - Iter: 40, Total Loss: 0.2794, loss_single: 0.2794, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,355 - Iter: 41, Total Loss: 0.2764, loss_single: 0.2764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,390 - Iter: 42, Total Loss: 0.2743, loss_single: 0.2743, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,425 - Iter: 43, Total Loss: 0.2727, loss_single: 0.2727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,461 - Iter: 44, Total Loss: 0.2711, loss_single: 0.2711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,497 - Iter: 45, Total Loss: 0.2698, loss_single: 0.2698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,532 - Iter: 46, Total Loss: 0.2688, loss_single: 0.2688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,568 - Iter: 47, Total Loss: 0.2679, loss_single: 0.2679, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,605 - Iter: 48, Total Loss: 0.2670, loss_single: 0.2670, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,640 - Iter: 49, Total Loss: 0.2663, loss_single: 0.2663, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,676 - Iter: 50, Total Loss: 0.2657, loss_single: 0.2657, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,711 - Iter: 51, Total Loss: 0.2652, loss_single: 0.2652, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,747 - Iter: 52, Total Loss: 0.2648, loss_single: 0.2648, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:30,782 - Iter: 53, Total Loss: 0.2643, loss_single: 0.2643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,818 - Iter: 54, Total Loss: 0.2640, loss_single: 0.2640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,853 - Iter: 55, Total Loss: 0.2637, loss_single: 0.2637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,889 - Iter: 56, Total Loss: 0.2634, loss_single: 0.2634, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,924 - Iter: 57, Total Loss: 0.2631, loss_single: 0.2631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,960 - Iter: 58, Total Loss: 0.2629, loss_single: 0.2629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:30,996 - 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Iter: 95, Total Loss: 0.2604, loss_single: 0.2604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:32,318 - Iter: 96, Total Loss: 0.2603, loss_single: 0.2603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:32,354 - Iter: 97, Total Loss: 0.2603, loss_single: 0.2603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:35:32,390 - Iter: 98, Total Loss: 0.2603, loss_single: 0.2603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:32,426 - Iter: 99, Total Loss: 0.2602, loss_single: 0.2602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:32,461 - Iter: 100, Total Loss: 0.2602, loss_single: 0.2602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:35:32,590 - Saving summary figures for iter 100 +2026-06-24 04:35:36,243 - ### Finished 100 iterations, averaged iter_t = 0.039474 with std = 0.041 ### +2026-06-24 04:35:36,243 - +2026-06-24 04:35:36,243 - ### The PtyRADSolver is finished in 9.371 sec ### +2026-06-24 04:35:36,243 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..8be10572d65abc99b888bf68a09a5dfd02c9b2cc Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/simulation_data7__sample_000030.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/simulation_data7__sample_000030.yaml new file mode 100644 index 0000000000000000000000000000000000000000..42bd3b1011582a1c6a78fa8de50a6baf534d0626 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030/gendata3_std_02__simulation_data7__sample_000030_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-321_C12_36.5_phi12_213_C21_-269_phi21_96.1_C23_715_phi23_21.6_C30_1.11e+07.12e+06_phi56_330/simulation_data7__sample_000030.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.487207412719727 + probe_aberrations: + C10: -321.23681640625 + C12: 36.51311492919922 + C21: -269.0029296875 + C23: 715.232666015625 + C30: 11070396.0 + C32: -5687.701171875 + C34: 9261.953125 + C41: 92159.9765625 + C43: 403354.03125 + C45: 416371.90625 + C50: -9298595.0 + C52: 1324881.625 + C54: -4890564.5 + C56: -9115431.0 + phi12: 212.5718657644265 + phi21: 96.05474663764103 + phi23: 21.623217780101466 + phi32: 284.89265443256784 + phi34: 300.23686564829825 + phi41: 199.52233856263192 + phi43: 66.09552886234913 + phi45: 355.4572238801805 + phi52: 5.098147538485428 + phi54: 30.006322174902902 + phi56: 330.216205160885 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000030_measurement.h5 + key: measurement + random_seed: 20261605 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000030 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data7__sample_000030 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/20260624_043655_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/20260624_043655_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d8dc7efd68a3f70c7c59a8e46281d6d182794c7b --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/20260624_043655_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:36:53,932 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:36:53,932 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:36:53,932 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:36:53,932 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:36:53,932 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:36:53,932 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:36:53,932 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:36:53,932 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:36:53,932 - +2026-06-24 04:36:54,040 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:36:54,040 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:36:54,040 - Accelerator.num_process = 1 +2026-06-24 04:36:54,040 - Accelerator.mixed_precision = no +2026-06-24 04:36:54,051 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:36:54,051 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:36:54,051 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:36:54,051 - +2026-06-24 04:36:54,051 - ### System information ### +2026-06-24 04:36:54,051 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:36:54,051 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:36:54,051 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:36:54,051 - Machine: x86_64 +2026-06-24 04:36:54,051 - Processor: x86_64 +2026-06-24 04:36:54,051 - Available CPU cores: 8 +2026-06-24 04:36:54,051 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:36:54,051 - +2026-06-24 04:36:54,051 - ### GPU information ### +2026-06-24 04:36:54,051 - CUDA Available: True +2026-06-24 04:36:54,051 - CUDA Version: 13.0 +2026-06-24 04:36:54,052 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:36:54,052 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:36:54,052 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:36:54,052 - In addition, Triton does not directly support Windows. +2026-06-24 04:36:54,052 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:36:54,067 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:36:54,067 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:36:54,067 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:36:54,067 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:36:54,067 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:36:54,067 - +2026-06-24 04:36:54,067 - ### Python information ### +2026-06-24 04:36:54,069 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:36:54,069 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:36:54,069 - +2026-06-24 04:36:54,069 - ### Packages information ### +2026-06-24 04:36:54,070 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:36:54,071 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:36:54,072 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:36:54,072 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:36:54,073 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:36:54,073 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:36:54,073 - +2026-06-24 04:36:54,073 - ### Loading params file ### +2026-06-24 04:36:54,073 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data7__sample_000036.yaml +2026-06-24 04:36:54,079 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:36:54,080 - Success! Params file validated and defaults applied. +2026-06-24 04:36:54,081 - +2026-06-24 04:36:54,081 - ### Setting GPU Device ### +2026-06-24 04:36:54,081 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:36:54,081 - +2026-06-24 04:36:54,081 - Random seed: 20261611 provided by params file +2026-06-24 04:36:54,081 - ### Initializing Initializer ### +2026-06-24 04:36:54,081 - init_params are displayed below: +2026-06-24 04:36:54,081 - random_seed: 20261611 +2026-06-24 04:36:54,081 - probe_illum_type: electron +2026-06-24 04:36:54,081 - probe_kv: 200.0 +2026-06-24 04:36:54,081 - probe_conv_angle: 9.916728019714355 +2026-06-24 04:36:54,081 - probe_aberrations: {'C10': -441.691, 'C12': -3.771, 'phi12': 333.017, 'C21': -597.488, 'phi21': 270.851, 'C23': 233.399, 'phi23': 267.151, 'C30': 12557186.0, 'C32': 11475.828, 'phi32': 130.636, 'C34': 11417.139, 'phi34': 170.673, 'C41': 466071.781, 'phi41': 185.235, 'C43': 261530.578, 'phi43': 274.633, 'C45': 258355.656, 'phi45': 165.317, 'C50': 13830564.0, 'C52': 3855807.75, 'phi52': 354.263, 'C54': 1574878.625, 'phi54': 85.336, 'C56': 13555013.0, 'phi56': 258.44} +2026-06-24 04:36:54,081 - beam_kev: None +2026-06-24 04:36:54,081 - probe_dRn: None +2026-06-24 04:36:54,081 - probe_Rn: None +2026-06-24 04:36:54,082 - probe_D_H: None +2026-06-24 04:36:54,082 - probe_D_FZP: None +2026-06-24 04:36:54,082 - probe_Ls: None +2026-06-24 04:36:54,082 - meas_Npix: 128 +2026-06-24 04:36:54,082 - pos_N_scans: 256 +2026-06-24 04:36:54,082 - pos_N_scan_slow: 16 +2026-06-24 04:36:54,082 - pos_N_scan_fast: 16 +2026-06-24 04:36:54,082 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:36:54,082 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:36:54,082 - probe_pmode_max: 6 +2026-06-24 04:36:54,082 - probe_pmode_init_pows: [0.02] +2026-06-24 04:36:54,082 - obj_omode_max: 1 +2026-06-24 04:36:54,082 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:36:54,082 - obj_Nlayer: 1 +2026-06-24 04:36:54,082 - obj_slice_thickness: 20.0 +2026-06-24 04:36:54,082 - simu_Npix: None +2026-06-24 04:36:54,082 - simu_match_mode: None +2026-06-24 04:36:54,082 - meas_permute: None +2026-06-24 04:36:54,082 - meas_reshape: [256, 128, 128] +2026-06-24 04:36:54,082 - meas_flipT: [0, 0, 0] +2026-06-24 04:36:54,082 - meas_crop: None +2026-06-24 04:36:54,082 - meas_pad: None +2026-06-24 04:36:54,082 - meas_resample: None +2026-06-24 04:36:54,082 - meas_add_source_size: None +2026-06-24 04:36:54,082 - meas_add_detector_blur: None +2026-06-24 04:36:54,082 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:36:54,082 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:36:54,082 - meas_add_poisson_noise: None +2026-06-24 04:36:54,082 - meas_export: None +2026-06-24 04:36:54,082 - probe_permute: None +2026-06-24 04:36:54,082 - probe_z_shift: None +2026-06-24 04:36:54,082 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:36:54,082 - pos_scan_flipT: None +2026-06-24 04:36:54,082 - pos_scan_affine: None +2026-06-24 04:36:54,082 - pos_scan_rand_std: 0.15 +2026-06-24 04:36:54,082 - obj_z_crop: None +2026-06-24 04:36:54,082 - obj_z_pad: None +2026-06-24 04:36:54,082 - obj_z_resample: None +2026-06-24 04:36:54,082 - meas_source: file +2026-06-24 04:36:54,082 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000036_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:36:54,083 - probe_source: simu +2026-06-24 04:36:54,083 - probe_params: None +2026-06-24 04:36:54,083 - pos_source: simu +2026-06-24 04:36:54,083 - pos_params: None +2026-06-24 04:36:54,083 - obj_source: simu +2026-06-24 04:36:54,083 - obj_params: None +2026-06-24 04:36:54,083 - tilt_source: simu +2026-06-24 04:36:54,083 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:36:54,083 - +2026-06-24 04:36:54,083 - ### Initializing cache ### +2026-06-24 04:36:54,083 - use_cached_obj = False +2026-06-24 04:36:54,083 - use_cached_probe = False +2026-06-24 04:36:54,083 - use_cached_pos = False +2026-06-24 04:36:54,083 - +2026-06-24 04:36:54,083 - ### Initializing measurements ### +2026-06-24 04:36:54,083 - Loading measurements from source = 'file' +2026-06-24 04:36:54,083 - Detected measurement file type = '.h5' +2026-06-24 04:36:54,160 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:36:54,160 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:36:54,162 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0041) +2026-06-24 04:36:54,162 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:36:54,162 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:36:54,163 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:36:54,163 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:36:54,164 - Normalizing by max of the 2D mean pattern intensity: 0.003162066 +2026-06-24 04:36:54,164 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:36:54,166 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0193, 1.2936) +2026-06-24 04:36:54,166 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:36:54,168 - Pattern total int. statistics (min, mean, max) = (314.2636, 316.2426, 317.8652), with min/max = 98.9% +2026-06-24 04:36:54,169 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0193, 1.2936) +2026-06-24 04:36:54,169 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:36:54,169 - +2026-06-24 04:36:54,169 - ### Setting up calibration ### +2026-06-24 04:36:54,169 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:36:54,169 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:36:54,169 - Radius of fitted bright field disk (RBF) = 10.06 px with meas_Npix = 128 +2026-06-24 04:36:54,169 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1572 +2026-06-24 04:36:54,169 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:36:54,169 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:36:54,392 - Initial guess: center=(63.64, 63.62), radius=10.06, Gaussian blur std=0.50 +2026-06-24 04:36:54,406 - Final fit: center=(63.64, 63.62), radius=10.06, Gaussian blur std=0.71 +2026-06-24 04:36:54,407 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.12 px with Npix = 128 +2026-06-24 04:36:54,407 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:36:54,407 - +2026-06-24 04:36:54,407 - ### Setting init_variables dict ### +2026-06-24 04:36:54,407 - Derived values given input init_params: +2026-06-24 04:36:54,407 - kv = 200.0 kV +2026-06-24 04:36:54,407 - wavelength = 0.0251 Ang +2026-06-24 04:36:54,407 - conv_angle = 9.916728019714355 mrad +2026-06-24 04:36:54,407 - Npix = 128 px +2026-06-24 04:36:54,407 - dk = 0.0391 Ang^-1 +2026-06-24 04:36:54,407 - kMax = 2.5000 Ang^-1 +2026-06-24 04:36:54,407 - da = 0.9797 mrad +2026-06-24 04:36:54,407 - angleMax = 62.6984 mrad +2026-06-24 04:36:54,407 - RBF = 10.1226 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:36:54,407 - n_alpha = 6.3225 (# conv_angle) +2026-06-24 04:36:54,407 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:36:54,407 - Rayleigh-limited resolution = 1.5427 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:36:54,407 - Real space probe extent = 25.6000 Ang +2026-06-24 04:36:54,407 - +2026-06-24 04:36:54,407 - ### Initializing probe ### +2026-06-24 04:36:54,407 - Loading probe from source = 'simu' +2026-06-24 04:36:54,407 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:36:54,407 - Start simulating STEM probe +2026-06-24 04:36:54,407 - kv = 200.0 kV +2026-06-24 04:36:54,407 - wavelength = 0.0251 Ang +2026-06-24 04:36:54,408 - conv_angle = 9.916728019714355 mrad +2026-06-24 04:36:54,408 - Npix = 128 px +2026-06-24 04:36:54,408 - dk = 0.0391 Ang^-1 +2026-06-24 04:36:54,408 - kMax = 2.5000 Ang^-1 +2026-06-24 04:36:54,408 - alpha_max = 62.6984 mrad +2026-06-24 04:36:54,408 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:36:54,408 - Rayleigh-limited resolution = 1.5427 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:36:54,408 - Real space probe extent = 25.6000 Ang +2026-06-24 04:36:54,408 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:36:54,408 - ----------------------------------------------------------------------------------- +2026-06-24 04:36:54,408 - C1,0 C1 -441.6910 - Defocus (C10 = -df) +2026-06-24 04:36:54,408 - C1,2 A1 -3.7710 333.02 2-fold astigmatism +2026-06-24 04:36:54,408 - C2,1 3*B2 -597.4880 270.85 Axial coma +2026-06-24 04:36:54,408 - C2,3 A2 233.3990 267.15 3-fold astigmatism +2026-06-24 04:36:54,408 - C3,0 C3 12557186.0000 - Spherical aberration +2026-06-24 04:36:54,408 - C3,2 4*S3 11475.8280 130.64 Axial star aberration +2026-06-24 04:36:54,408 - C3,4 A3 11417.1390 170.67 4-fold astigmatism +2026-06-24 04:36:54,408 - C4,1 4*B4 466071.7810 185.24 Axial coma(4th) +2026-06-24 04:36:54,408 - C4,3 4*D4 261530.5780 274.63 3-lobe aberration +2026-06-24 04:36:54,408 - C4,5 A4 258355.6560 165.32 5-fold astigmatism +2026-06-24 04:36:54,408 - C5,0 C5 13830564.0000 - Spherical aberration (5th) +2026-06-24 04:36:54,408 - C5,2 6*S5 3855807.7500 354.26 Axial star aberration(5th) +2026-06-24 04:36:54,408 - C5,4 6*R5 1574878.6250 85.34 4-lobe aberration +2026-06-24 04:36:54,408 - C5,6 A5 13555013.0000 258.44 6-fold astigmatism +2026-06-24 04:36:54,411 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:36:54,411 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:36:54,411 - Creating 5 new probe modes from the major mode +2026-06-24 04:36:54,411 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:36:54,514 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:36:54,515 - Orthogonalizing 6 pmodes +2026-06-24 04:36:54,518 - Sorting 6 pmodes by their intensities +2026-06-24 04:36:54,518 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:36:54,519 - sum(|probe_data|**2) = 316.24, while meas_total_ints (min, mean, max) = (314.2636, 316.2426, 317.8652) +2026-06-24 04:36:54,519 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:36:54,519 - +2026-06-24 04:36:54,519 - ### Initializing probe positions ### +2026-06-24 04:36:54,519 - Loading probe positions from source = 'simu' +2026-06-24 04:36:54,519 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:36:54,519 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:36:54,519 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:36:54,521 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:36:54,521 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:36:54,521 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:36:54,522 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:36:54,522 - +2026-06-24 04:36:54,522 - ### Initializing object ### +2026-06-24 04:36:54,522 - Loading object from source = 'simu' +2026-06-24 04:36:54,522 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:36:54,523 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:36:54,523 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:36:54,523 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:36:54,523 - +2026-06-24 04:36:54,523 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:36:54,524 - omode_occu (omode) = float32, (1,) +2026-06-24 04:36:54,524 - +2026-06-24 04:36:54,524 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:36:54,524 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:36:54,524 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:36:54,524 - +2026-06-24 04:36:54,524 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:36:54,524 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:36:54,524 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:36:54,524 - +2026-06-24 04:36:54,525 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:36:54,525 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:36:54,525 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:36:54,525 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:36:54,525 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:36:54,525 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:36:54,525 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:36:54,525 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:36:54,525 - +2026-06-24 04:36:54,525 - ### Collecting reconstruction provenance ### +2026-06-24 04:36:54,525 - Reconstruction provenance is collected and initialized. +2026-06-24 04:36:54,525 - +2026-06-24 04:36:54,525 - ### Initializing loss function ### +2026-06-24 04:36:54,525 - Active loss types: +2026-06-24 04:36:54,525 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:36:54,525 - +2026-06-24 04:36:54,525 - ### Initializing constraint function ### +2026-06-24 04:36:54,525 - Active constraint types: +2026-06-24 04:36:54,525 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:36:54,525 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:36:54,525 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:36:54,525 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:36:54,526 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:36:54,526 - +2026-06-24 04:36:54,526 - ### Done initializing PtyRADSolver ### +2026-06-24 04:36:54,526 - +2026-06-24 04:36:54,653 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:36:54,653 - +2026-06-24 04:36:54,653 - ### Initializing PtychoModel model ### +2026-06-24 04:36:54,725 - ### PtychoModel optimizable variables ### +2026-06-24 04:36:54,725 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:36:54,725 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:36:54,725 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:36:54,725 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:36:54,725 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:36:54,725 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:36:54,725 - +2026-06-24 04:36:54,725 - ### Optimizable variables statitsics ### +2026-06-24 04:36:54,725 - Total measurement values : 4,194,304 +2026-06-24 04:36:54,725 - Total optimizing variables: 278,728 +2026-06-24 04:36:54,725 - Overdetermined ratio : 15.05 +2026-06-24 04:36:54,725 - +2026-06-24 04:36:54,726 - ### Model behavior ### +2026-06-24 04:36:54,726 - Tilt propagator : False +2026-06-24 04:36:54,726 - Change slice thickness : False +2026-06-24 04:36:54,726 - Detector blur : False +2026-06-24 04:36:54,726 - Preload data : True +2026-06-24 04:36:54,726 - On-the-fly meas padding : False +2026-06-24 04:36:54,726 - On-the-fly meas resample : False +2026-06-24 04:36:54,726 - On-the-fly simu match mode: None +2026-06-24 04:36:54,726 - +2026-06-24 04:36:54,767 - ### Done initializing PtychoModel model ### +2026-06-24 04:36:54,767 - +2026-06-24 04:36:54,767 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:36:54,767 - +2026-06-24 04:36:54,767 - ### Generating indices, batches, and output_path ### +2026-06-24 04:36:54,769 - d90 = 63.000 px or 12.600 Ang +2026-06-24 04:36:54,769 - Selecting indices with the 'full' mode +2026-06-24 04:36:55,233 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:36:55,310 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:36:55,310 - Original recon_dir_affixes = ['default'] +2026-06-24 04:36:55,310 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:36:55,316 - Path corrected for compatibility: +2026-06-24 04:36:55,316 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_C32_1.15e+04_phi32_131_C34_1.14e+04_phi34_171_C41_4.66e+05_phi41_185_C43_2.62e+05_phi43_275_C45_2.58e+05_phi45_165_C50_1.38e+07_C52_3.86e+06_phi52_354_C54_1.57e+06_phi54_85.3_C56_1.36e+07_phi56_258 +2026-06-24 04:36:55,316 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258 +2026-06-24 04:36:55,318 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258' is generated! +2026-06-24 04:36:55,472 - +2026-06-24 04:36:55,473 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/20260624_043655_ptyrad_log.txt ### +2026-06-24 04:36:55,473 - +2026-06-24 04:36:55,475 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:36:55,475 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:36:55,475 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:36:56,675 - Iter: 1, Total Loss: 0.9244, loss_single: 0.9244, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 04:36:56,713 - Iter: 2, Total Loss: 0.8640, loss_single: 0.8640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:36:56,749 - Iter: 3, Total Loss: 0.8195, loss_single: 0.8195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,784 - Iter: 4, Total Loss: 0.7845, loss_single: 0.7845, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,819 - Iter: 5, Total Loss: 0.7491, loss_single: 0.7491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,855 - Iter: 6, Total Loss: 0.7100, loss_single: 0.7100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,890 - Iter: 7, Total Loss: 0.6703, loss_single: 0.6703, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,926 - Iter: 8, Total Loss: 0.6238, loss_single: 0.6238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,961 - Iter: 9, Total Loss: 0.5717, loss_single: 0.5717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:56,996 - Iter: 10, Total Loss: 0.5201, loss_single: 0.5201, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,032 - Iter: 11, Total Loss: 0.4778, loss_single: 0.4778, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,067 - Iter: 12, Total Loss: 0.4479, loss_single: 0.4479, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,102 - Iter: 13, Total Loss: 0.4289, loss_single: 0.4289, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,137 - Iter: 14, Total Loss: 0.4118, loss_single: 0.4118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,173 - Iter: 15, Total Loss: 0.3948, loss_single: 0.3948, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,207 - Iter: 16, Total Loss: 0.3787, loss_single: 0.3787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:57,243 - Iter: 17, Total Loss: 0.3631, loss_single: 0.3631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,278 - Iter: 18, Total Loss: 0.3500, loss_single: 0.3500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,314 - Iter: 19, Total Loss: 0.3370, loss_single: 0.3370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,349 - Iter: 20, Total Loss: 0.3273, loss_single: 0.3273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,384 - Iter: 21, Total Loss: 0.3194, loss_single: 0.3194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:57,420 - Iter: 22, Total Loss: 0.3118, loss_single: 0.3118, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:36:57,455 - Iter: 23, Total Loss: 0.3068, loss_single: 0.3068, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,491 - Iter: 24, Total Loss: 0.3027, loss_single: 0.3027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,526 - Iter: 25, Total Loss: 0.2991, loss_single: 0.2991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,561 - Iter: 26, Total Loss: 0.2959, loss_single: 0.2959, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,596 - Iter: 27, Total Loss: 0.2930, loss_single: 0.2930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,631 - Iter: 28, Total Loss: 0.2908, loss_single: 0.2908, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,666 - Iter: 29, Total Loss: 0.2891, loss_single: 0.2891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,706 - Iter: 30, Total Loss: 0.2879, loss_single: 0.2879, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 04:36:57,741 - Iter: 31, Total Loss: 0.2869, loss_single: 0.2869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,776 - Iter: 32, Total Loss: 0.2857, loss_single: 0.2857, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,811 - Iter: 33, Total Loss: 0.2845, loss_single: 0.2845, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,847 - Iter: 34, Total Loss: 0.2834, loss_single: 0.2834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,882 - Iter: 35, Total Loss: 0.2822, loss_single: 0.2822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,917 - Iter: 36, Total Loss: 0.2813, loss_single: 0.2813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,952 - Iter: 37, Total Loss: 0.2805, loss_single: 0.2805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:57,987 - Iter: 38, Total Loss: 0.2796, loss_single: 0.2796, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,022 - Iter: 39, Total Loss: 0.2786, loss_single: 0.2786, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,057 - Iter: 40, Total Loss: 0.2777, loss_single: 0.2777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,093 - Iter: 41, Total Loss: 0.2768, loss_single: 0.2768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,128 - Iter: 42, Total Loss: 0.2759, loss_single: 0.2759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,163 - Iter: 43, Total Loss: 0.2750, loss_single: 0.2750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,198 - Iter: 44, Total Loss: 0.2742, loss_single: 0.2742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,234 - Iter: 45, Total Loss: 0.2733, loss_single: 0.2733, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,268 - Iter: 46, Total Loss: 0.2725, loss_single: 0.2725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:58,303 - Iter: 47, Total Loss: 0.2718, loss_single: 0.2718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,338 - Iter: 48, Total Loss: 0.2710, loss_single: 0.2710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:58,372 - Iter: 49, Total Loss: 0.2702, loss_single: 0.2702, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:58,407 - Iter: 50, Total Loss: 0.2695, loss_single: 0.2695, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:36:58,442 - Iter: 51, Total Loss: 0.2688, loss_single: 0.2688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,478 - Iter: 52, Total Loss: 0.2681, loss_single: 0.2681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,513 - Iter: 53, Total Loss: 0.2675, loss_single: 0.2675, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,549 - Iter: 54, Total Loss: 0.2668, loss_single: 0.2668, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,584 - Iter: 55, Total Loss: 0.2662, loss_single: 0.2662, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,619 - Iter: 56, Total Loss: 0.2656, loss_single: 0.2656, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,654 - Iter: 57, Total Loss: 0.2650, loss_single: 0.2650, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,689 - Iter: 58, Total Loss: 0.2644, loss_single: 0.2644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:36:58,724 - 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Iter: 95, Total Loss: 0.2525, loss_single: 0.2525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:37:00,040 - Iter: 96, Total Loss: 0.2523, loss_single: 0.2523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:37:00,075 - Iter: 97, Total Loss: 0.2519, loss_single: 0.2519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:37:00,110 - Iter: 98, Total Loss: 0.2517, loss_single: 0.2517, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:37:00,146 - Iter: 99, Total Loss: 0.2516, loss_single: 0.2516, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:37:00,181 - Iter: 100, Total Loss: 0.2513, loss_single: 0.2513, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:37:00,293 - Saving summary figures for iter 100 +2026-06-24 04:37:03,835 - ### Finished 100 iterations, averaged iter_t = 0.038978 with std = 0.040 ### +2026-06-24 04:37:03,835 - +2026-06-24 04:37:03,836 - ### The PtyRADSolver is finished in 9.183 sec ### +2026-06-24 04:37:03,836 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..c54ecd54c9dedc0502fe03b861193b21dd727594 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/simulation_data7__sample_000036.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/simulation_data7__sample_000036.yaml new file mode 100644 index 0000000000000000000000000000000000000000..38140e62d6386545a855df46094752cb362ec458 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036/gendata3_std_02__simulation_data7__sample_000036_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-442_C12_-3.77_phi12_333_C21_-597_phi21_271_C23_233_phi23_267_C30_1.26e+07_.36e+07_phi56_258/simulation_data7__sample_000036.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.916728019714355 + probe_aberrations: + C10: -441.691162109375 + C12: -3.7706847190856934 + C21: -597.4882202148438 + C23: 233.3985595703125 + C30: 12557186.0 + C32: 11475.828125 + C34: 11417.138671875 + C41: 466071.78125 + C43: 261530.578125 + C45: 258355.65625 + C50: 13830564.0 + C52: 3855807.75 + C54: 1574878.625 + C56: 13555013.0 + phi12: 333.0172930602639 + phi21: 270.8509876123156 + phi23: 267.1512927049731 + phi32: 130.63616516014483 + phi34: 170.67295822557537 + phi41: 185.23460734734076 + phi43: 274.6333004878585 + phi45: 165.31698342563985 + phi52: 354.262815039642 + phi54: 85.3363629995718 + phi56: 258.44017872056554 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data7__sample_000036_measurement.h5 + key: measurement + random_seed: 20261611 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data7__sample_000036 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data7__sample_000036 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/20260624_043823_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/20260624_043823_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..1e95e20e0ae191f6fb12f011f85cae29872fa342 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/20260624_043823_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:38:21,985 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:38:21,986 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:38:21,986 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:38:21,986 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:38:21,986 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:38:21,986 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:38:21,986 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:38:21,986 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:38:21,986 - +2026-06-24 04:38:22,094 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:38:22,094 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:38:22,094 - Accelerator.num_process = 1 +2026-06-24 04:38:22,094 - Accelerator.mixed_precision = no +2026-06-24 04:38:22,104 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:38:22,104 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:38:22,105 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:38:22,105 - +2026-06-24 04:38:22,105 - ### System information ### +2026-06-24 04:38:22,105 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:38:22,105 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:38:22,105 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:38:22,105 - Machine: x86_64 +2026-06-24 04:38:22,105 - Processor: x86_64 +2026-06-24 04:38:22,105 - Available CPU cores: 8 +2026-06-24 04:38:22,105 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:38:22,105 - +2026-06-24 04:38:22,105 - ### GPU information ### +2026-06-24 04:38:22,105 - CUDA Available: True +2026-06-24 04:38:22,105 - CUDA Version: 13.0 +2026-06-24 04:38:22,106 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:38:22,106 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:38:22,106 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:38:22,106 - In addition, Triton does not directly support Windows. +2026-06-24 04:38:22,106 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:38:22,120 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:38:22,120 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:38:22,120 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:38:22,120 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:38:22,120 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:38:22,120 - +2026-06-24 04:38:22,120 - ### Python information ### +2026-06-24 04:38:22,122 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:38:22,122 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:38:22,122 - +2026-06-24 04:38:22,122 - ### Packages information ### +2026-06-24 04:38:22,123 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:38:22,124 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:38:22,124 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:38:22,125 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:38:22,126 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:38:22,126 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:38:22,126 - +2026-06-24 04:38:22,126 - ### Loading params file ### +2026-06-24 04:38:22,126 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data8__sample_000002.yaml +2026-06-24 04:38:22,132 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:38:22,133 - Success! Params file validated and defaults applied. +2026-06-24 04:38:22,134 - +2026-06-24 04:38:22,134 - ### Setting GPU Device ### +2026-06-24 04:38:22,134 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:38:22,134 - +2026-06-24 04:38:22,134 - Random seed: 20261617 provided by params file +2026-06-24 04:38:22,134 - ### Initializing Initializer ### +2026-06-24 04:38:22,134 - init_params are displayed below: +2026-06-24 04:38:22,134 - random_seed: 20261617 +2026-06-24 04:38:22,134 - probe_illum_type: electron +2026-06-24 04:38:22,134 - probe_kv: 200.0 +2026-06-24 04:38:22,134 - probe_conv_angle: 10.053448677062988 +2026-06-24 04:38:22,134 - probe_aberrations: {'C10': -383.736, 'C12': 18.235, 'phi12': 62.764, 'C21': -96.93, 'phi21': 331.258, 'C23': -912.001, 'phi23': 355.913, 'C30': 10434008.0, 'C32': -3099.316, 'phi32': 237.489, 'C34': -10574.333, 'phi34': 126.7, 'C41': 443529.031, 'phi41': 212.621, 'C43': 124879.367, 'phi43': 0.194, 'C45': 475732.531, 'phi45': 201.743, 'C50': 13609200.0, 'C52': -6313372.0, 'phi52': 207.431, 'C54': 3497176.0, 'phi54': 338.324, 'C56': -11651816.0, 'phi56': 12.547} +2026-06-24 04:38:22,134 - beam_kev: None +2026-06-24 04:38:22,134 - probe_dRn: None +2026-06-24 04:38:22,134 - probe_Rn: None +2026-06-24 04:38:22,135 - probe_D_H: None +2026-06-24 04:38:22,135 - probe_D_FZP: None +2026-06-24 04:38:22,135 - probe_Ls: None +2026-06-24 04:38:22,135 - meas_Npix: 128 +2026-06-24 04:38:22,135 - pos_N_scans: 256 +2026-06-24 04:38:22,135 - pos_N_scan_slow: 16 +2026-06-24 04:38:22,135 - pos_N_scan_fast: 16 +2026-06-24 04:38:22,135 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:38:22,135 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:38:22,135 - probe_pmode_max: 6 +2026-06-24 04:38:22,135 - probe_pmode_init_pows: [0.02] +2026-06-24 04:38:22,135 - obj_omode_max: 1 +2026-06-24 04:38:22,135 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:38:22,135 - obj_Nlayer: 1 +2026-06-24 04:38:22,135 - obj_slice_thickness: 20.0 +2026-06-24 04:38:22,135 - simu_Npix: None +2026-06-24 04:38:22,135 - simu_match_mode: None +2026-06-24 04:38:22,135 - meas_permute: None +2026-06-24 04:38:22,135 - meas_reshape: [256, 128, 128] +2026-06-24 04:38:22,135 - meas_flipT: [0, 0, 0] +2026-06-24 04:38:22,135 - meas_crop: None +2026-06-24 04:38:22,135 - meas_pad: None +2026-06-24 04:38:22,135 - meas_resample: None +2026-06-24 04:38:22,135 - meas_add_source_size: None +2026-06-24 04:38:22,135 - meas_add_detector_blur: None +2026-06-24 04:38:22,135 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:38:22,135 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:38:22,135 - meas_add_poisson_noise: None +2026-06-24 04:38:22,135 - meas_export: None +2026-06-24 04:38:22,135 - probe_permute: None +2026-06-24 04:38:22,135 - probe_z_shift: None +2026-06-24 04:38:22,135 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:38:22,135 - pos_scan_flipT: None +2026-06-24 04:38:22,135 - pos_scan_affine: None +2026-06-24 04:38:22,135 - pos_scan_rand_std: 0.15 +2026-06-24 04:38:22,135 - obj_z_crop: None +2026-06-24 04:38:22,135 - obj_z_pad: None +2026-06-24 04:38:22,135 - obj_z_resample: None +2026-06-24 04:38:22,135 - meas_source: file +2026-06-24 04:38:22,135 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data8__sample_000002_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:38:22,136 - probe_source: simu +2026-06-24 04:38:22,136 - probe_params: None +2026-06-24 04:38:22,136 - pos_source: simu +2026-06-24 04:38:22,136 - pos_params: None +2026-06-24 04:38:22,136 - obj_source: simu +2026-06-24 04:38:22,136 - obj_params: None +2026-06-24 04:38:22,136 - tilt_source: simu +2026-06-24 04:38:22,136 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:38:22,136 - +2026-06-24 04:38:22,136 - ### Initializing cache ### +2026-06-24 04:38:22,136 - use_cached_obj = False +2026-06-24 04:38:22,136 - use_cached_probe = False +2026-06-24 04:38:22,136 - use_cached_pos = False +2026-06-24 04:38:22,136 - +2026-06-24 04:38:22,136 - ### Initializing measurements ### +2026-06-24 04:38:22,136 - Loading measurements from source = 'file' +2026-06-24 04:38:22,136 - Detected measurement file type = '.h5' +2026-06-24 04:38:22,210 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:38:22,211 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:38:22,212 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0040) +2026-06-24 04:38:22,212 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:38:22,212 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:38:22,214 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:38:22,214 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:38:22,214 - Normalizing by max of the 2D mean pattern intensity: 0.0030731724 +2026-06-24 04:38:22,215 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:38:22,217 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0199, 1.2864) +2026-06-24 04:38:22,217 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:38:22,218 - Pattern total int. statistics (min, mean, max) = (323.7697, 325.5735, 328.0749), with min/max = 98.7% +2026-06-24 04:38:22,220 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0199, 1.2864) +2026-06-24 04:38:22,220 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:38:22,220 - +2026-06-24 04:38:22,220 - ### Setting up calibration ### +2026-06-24 04:38:22,220 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:38:22,220 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:38:22,220 - Radius of fitted bright field disk (RBF) = 10.16 px with meas_Npix = 128 +2026-06-24 04:38:22,220 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1587 +2026-06-24 04:38:22,220 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:38:22,220 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:38:22,454 - Initial guess: center=(63.62, 63.63), radius=10.16, Gaussian blur std=0.50 +2026-06-24 04:38:22,462 - Final fit: center=(63.62, 63.63), radius=10.16, Gaussian blur std=0.54 +2026-06-24 04:38:22,463 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.26 px with Npix = 128 +2026-06-24 04:38:22,463 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:38:22,463 - +2026-06-24 04:38:22,463 - ### Setting init_variables dict ### +2026-06-24 04:38:22,463 - Derived values given input init_params: +2026-06-24 04:38:22,463 - kv = 200.0 kV +2026-06-24 04:38:22,463 - wavelength = 0.0251 Ang +2026-06-24 04:38:22,463 - conv_angle = 10.053448677062988 mrad +2026-06-24 04:38:22,463 - Npix = 128 px +2026-06-24 04:38:22,463 - dk = 0.0391 Ang^-1 +2026-06-24 04:38:22,463 - kMax = 2.5000 Ang^-1 +2026-06-24 04:38:22,463 - da = 0.9797 mrad +2026-06-24 04:38:22,463 - angleMax = 62.6984 mrad +2026-06-24 04:38:22,463 - RBF = 10.2622 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:38:22,463 - n_alpha = 6.2365 (# conv_angle) +2026-06-24 04:38:22,463 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:38:22,463 - Rayleigh-limited resolution = 1.5217 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:38:22,463 - Real space probe extent = 25.6000 Ang +2026-06-24 04:38:22,463 - +2026-06-24 04:38:22,463 - ### Initializing probe ### +2026-06-24 04:38:22,463 - Loading probe from source = 'simu' +2026-06-24 04:38:22,463 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:38:22,463 - Start simulating STEM probe +2026-06-24 04:38:22,464 - kv = 200.0 kV +2026-06-24 04:38:22,464 - wavelength = 0.0251 Ang +2026-06-24 04:38:22,464 - conv_angle = 10.053448677062988 mrad +2026-06-24 04:38:22,464 - Npix = 128 px +2026-06-24 04:38:22,464 - dk = 0.0391 Ang^-1 +2026-06-24 04:38:22,464 - kMax = 2.5000 Ang^-1 +2026-06-24 04:38:22,464 - alpha_max = 62.6984 mrad +2026-06-24 04:38:22,464 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:38:22,464 - Rayleigh-limited resolution = 1.5217 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:38:22,464 - Real space probe extent = 25.6000 Ang +2026-06-24 04:38:22,464 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:38:22,464 - ------------------------------------------------------------------------------------ +2026-06-24 04:38:22,464 - C1,0 C1 -383.7360 - Defocus (C10 = -df) +2026-06-24 04:38:22,464 - C1,2 A1 18.2350 62.76 2-fold astigmatism +2026-06-24 04:38:22,464 - C2,1 3*B2 -96.9300 331.26 Axial coma +2026-06-24 04:38:22,464 - C2,3 A2 -912.0010 355.91 3-fold astigmatism +2026-06-24 04:38:22,464 - C3,0 C3 10434008.0000 - Spherical aberration +2026-06-24 04:38:22,464 - C3,2 4*S3 -3099.3160 237.49 Axial star aberration +2026-06-24 04:38:22,464 - C3,4 A3 -10574.3330 126.70 4-fold astigmatism +2026-06-24 04:38:22,464 - C4,1 4*B4 443529.0310 212.62 Axial coma(4th) +2026-06-24 04:38:22,464 - C4,3 4*D4 124879.3670 0.19 3-lobe aberration +2026-06-24 04:38:22,464 - C4,5 A4 475732.5310 201.74 5-fold astigmatism +2026-06-24 04:38:22,464 - C5,0 C5 13609200.0000 - Spherical aberration (5th) +2026-06-24 04:38:22,464 - C5,2 6*S5 -6313372.0000 207.43 Axial star aberration(5th) +2026-06-24 04:38:22,464 - C5,4 6*R5 3497176.0000 338.32 4-lobe aberration +2026-06-24 04:38:22,464 - C5,6 A5 -11651816.0000 12.55 6-fold astigmatism +2026-06-24 04:38:22,467 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:38:22,468 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:38:22,468 - Creating 5 new probe modes from the major mode +2026-06-24 04:38:22,468 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:38:22,474 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:38:22,475 - Orthogonalizing 6 pmodes +2026-06-24 04:38:22,477 - Sorting 6 pmodes by their intensities +2026-06-24 04:38:22,478 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:38:22,478 - sum(|probe_data|**2) = 325.57, while meas_total_ints (min, mean, max) = (323.7697, 325.5735, 328.0749) +2026-06-24 04:38:22,479 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:38:22,479 - +2026-06-24 04:38:22,479 - ### Initializing probe positions ### +2026-06-24 04:38:22,479 - Loading probe positions from source = 'simu' +2026-06-24 04:38:22,479 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:38:22,479 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:38:22,479 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:38:22,481 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:38:22,481 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:38:22,481 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:38:22,481 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:38:22,481 - +2026-06-24 04:38:22,481 - ### Initializing object ### +2026-06-24 04:38:22,481 - Loading object from source = 'simu' +2026-06-24 04:38:22,481 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:38:22,483 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:38:22,483 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:38:22,483 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:38:22,483 - +2026-06-24 04:38:22,483 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:38:22,483 - omode_occu (omode) = float32, (1,) +2026-06-24 04:38:22,483 - +2026-06-24 04:38:22,483 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:38:22,483 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:38:22,484 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:38:22,484 - +2026-06-24 04:38:22,484 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:38:22,484 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:38:22,484 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:38:22,484 - +2026-06-24 04:38:22,484 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:38:22,484 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:38:22,484 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:38:22,484 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:38:22,484 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:38:22,484 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:38:22,484 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:38:22,484 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:38:22,485 - +2026-06-24 04:38:22,485 - ### Collecting reconstruction provenance ### +2026-06-24 04:38:22,485 - Reconstruction provenance is collected and initialized. +2026-06-24 04:38:22,485 - +2026-06-24 04:38:22,485 - ### Initializing loss function ### +2026-06-24 04:38:22,485 - Active loss types: +2026-06-24 04:38:22,485 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:38:22,485 - +2026-06-24 04:38:22,485 - ### Initializing constraint function ### +2026-06-24 04:38:22,485 - Active constraint types: +2026-06-24 04:38:22,485 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:38:22,485 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:38:22,485 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:38:22,485 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:38:22,485 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:38:22,485 - +2026-06-24 04:38:22,485 - ### Done initializing PtyRADSolver ### +2026-06-24 04:38:22,485 - +2026-06-24 04:38:22,621 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:38:22,621 - +2026-06-24 04:38:22,621 - ### Initializing PtychoModel model ### +2026-06-24 04:38:22,693 - ### PtychoModel optimizable variables ### +2026-06-24 04:38:22,693 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:38:22,693 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:38:22,693 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:38:22,693 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:38:22,693 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:38:22,693 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:38:22,693 - +2026-06-24 04:38:22,693 - ### Optimizable variables statitsics ### +2026-06-24 04:38:22,693 - Total measurement values : 4,194,304 +2026-06-24 04:38:22,693 - Total optimizing variables: 278,728 +2026-06-24 04:38:22,693 - Overdetermined ratio : 15.05 +2026-06-24 04:38:22,693 - +2026-06-24 04:38:22,693 - ### Model behavior ### +2026-06-24 04:38:22,693 - Tilt propagator : False +2026-06-24 04:38:22,693 - Change slice thickness : False +2026-06-24 04:38:22,693 - Detector blur : False +2026-06-24 04:38:22,693 - Preload data : True +2026-06-24 04:38:22,693 - On-the-fly meas padding : False +2026-06-24 04:38:22,693 - On-the-fly meas resample : False +2026-06-24 04:38:22,693 - On-the-fly simu match mode: None +2026-06-24 04:38:22,694 - +2026-06-24 04:38:22,734 - ### Done initializing PtychoModel model ### +2026-06-24 04:38:22,735 - +2026-06-24 04:38:22,735 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:38:22,735 - +2026-06-24 04:38:22,735 - ### Generating indices, batches, and output_path ### +2026-06-24 04:38:22,736 - d90 = 55.000 px or 11.000 Ang +2026-06-24 04:38:22,736 - Selecting indices with the 'full' mode +2026-06-24 04:38:23,197 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:38:23,272 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:38:23,273 - Original recon_dir_affixes = ['default'] +2026-06-24 04:38:23,273 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:38:23,279 - Path corrected for compatibility: +2026-06-24 04:38:23,279 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_phi32_237_C34_-1.06e+04_phi34_127_C41_4.44e+05_phi41_213_C43_1.25e+05_phi43_0.194_C45_4.76e+05_phi45_202_C50_1.36e+07_C52_-6.31e+06_phi52_207_C54_3.5e+06_phi54_338_C56_-1.17e+07_phi56_12.5 +2026-06-24 04:38:23,279 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5 +2026-06-24 04:38:23,280 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5' is generated! +2026-06-24 04:38:23,435 - +2026-06-24 04:38:23,436 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/20260624_043823_ptyrad_log.txt ### +2026-06-24 04:38:23,436 - +2026-06-24 04:38:23,437 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:38:23,437 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:38:23,437 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:38:24,624 - Iter: 1, Total Loss: 0.9688, loss_single: 0.9688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 04:38:24,662 - Iter: 2, Total Loss: 0.9088, loss_single: 0.9088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:38:24,697 - Iter: 3, Total Loss: 0.8608, loss_single: 0.8608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,733 - Iter: 4, Total Loss: 0.8185, loss_single: 0.8185, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,769 - Iter: 5, Total Loss: 0.7811, loss_single: 0.7811, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,804 - Iter: 6, Total Loss: 0.7463, loss_single: 0.7463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,841 - Iter: 7, Total Loss: 0.7104, loss_single: 0.7104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:24,876 - Iter: 8, Total Loss: 0.6731, loss_single: 0.6731, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,911 - Iter: 9, Total Loss: 0.6351, loss_single: 0.6351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:24,947 - Iter: 10, Total Loss: 0.6021, loss_single: 0.6021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:24,983 - Iter: 11, Total Loss: 0.5727, loss_single: 0.5727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,018 - Iter: 12, Total Loss: 0.5447, loss_single: 0.5447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,054 - Iter: 13, Total Loss: 0.5215, loss_single: 0.5215, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,090 - Iter: 14, Total Loss: 0.5010, loss_single: 0.5010, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:25,125 - Iter: 15, Total Loss: 0.4816, loss_single: 0.4816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,162 - Iter: 16, Total Loss: 0.4637, loss_single: 0.4637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:25,197 - Iter: 17, Total Loss: 0.4493, loss_single: 0.4493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,233 - Iter: 18, Total Loss: 0.4377, loss_single: 0.4377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,268 - Iter: 19, Total Loss: 0.4266, loss_single: 0.4266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,303 - Iter: 20, Total Loss: 0.4167, loss_single: 0.4167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,338 - Iter: 21, Total Loss: 0.4055, loss_single: 0.4055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,374 - Iter: 22, Total Loss: 0.3917, loss_single: 0.3917, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,409 - Iter: 23, Total Loss: 0.3829, loss_single: 0.3829, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,444 - Iter: 24, Total Loss: 0.3760, loss_single: 0.3760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,479 - Iter: 25, Total Loss: 0.3696, loss_single: 0.3696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:38:25,515 - Iter: 26, Total Loss: 0.3660, loss_single: 0.3660, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,550 - Iter: 27, Total Loss: 0.3603, loss_single: 0.3603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,586 - Iter: 28, Total Loss: 0.3554, loss_single: 0.3554, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,621 - Iter: 29, Total Loss: 0.3514, loss_single: 0.3514, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,656 - Iter: 30, Total Loss: 0.3466, loss_single: 0.3466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,692 - Iter: 31, Total Loss: 0.3426, loss_single: 0.3426, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,727 - Iter: 32, Total Loss: 0.3406, loss_single: 0.3406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,762 - Iter: 33, Total Loss: 0.3390, loss_single: 0.3390, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,797 - Iter: 34, Total Loss: 0.3364, loss_single: 0.3364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,832 - Iter: 35, Total Loss: 0.3339, loss_single: 0.3339, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:38:25,867 - Iter: 36, Total Loss: 0.3317, loss_single: 0.3317, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,902 - Iter: 37, Total Loss: 0.3294, loss_single: 0.3294, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,938 - Iter: 38, Total Loss: 0.3277, loss_single: 0.3277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:25,973 - Iter: 39, Total Loss: 0.3266, loss_single: 0.3266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,008 - Iter: 40, Total Loss: 0.3255, loss_single: 0.3255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,046 - Iter: 41, Total Loss: 0.3245, loss_single: 0.3245, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,081 - Iter: 42, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,117 - Iter: 43, Total Loss: 0.3224, loss_single: 0.3224, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:26,152 - Iter: 44, Total Loss: 0.3214, loss_single: 0.3214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,187 - Iter: 45, Total Loss: 0.3205, loss_single: 0.3205, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,223 - Iter: 46, Total Loss: 0.3196, loss_single: 0.3196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,258 - Iter: 47, Total Loss: 0.3189, loss_single: 0.3189, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,293 - Iter: 48, Total Loss: 0.3182, loss_single: 0.3182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,329 - Iter: 49, Total Loss: 0.3176, loss_single: 0.3176, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,365 - Iter: 50, Total Loss: 0.3168, loss_single: 0.3168, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,400 - Iter: 51, Total Loss: 0.3161, loss_single: 0.3161, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,436 - Iter: 52, Total Loss: 0.3157, loss_single: 0.3157, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,471 - Iter: 53, Total Loss: 0.3152, loss_single: 0.3152, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,507 - Iter: 54, Total Loss: 0.3144, loss_single: 0.3144, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,542 - Iter: 55, Total Loss: 0.3136, loss_single: 0.3136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,577 - Iter: 56, Total Loss: 0.3130, loss_single: 0.3130, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,613 - Iter: 57, Total Loss: 0.3125, loss_single: 0.3125, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,657 - Iter: 58, Total Loss: 0.3120, loss_single: 0.3120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,692 - Iter: 59, Total Loss: 0.3116, loss_single: 0.3116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,727 - Iter: 60, Total Loss: 0.3110, loss_single: 0.3110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,763 - Iter: 61, Total Loss: 0.3104, loss_single: 0.3104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,798 - Iter: 62, Total Loss: 0.3098, loss_single: 0.3098, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,833 - Iter: 63, Total Loss: 0.3094, loss_single: 0.3094, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,869 - Iter: 64, Total Loss: 0.3088, loss_single: 0.3088, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:26,904 - 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Iter: 95, Total Loss: 0.2972, loss_single: 0.2972, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:28,030 - Iter: 96, Total Loss: 0.2970, loss_single: 0.2970, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:28,066 - Iter: 97, Total Loss: 0.2968, loss_single: 0.2968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:38:28,102 - Iter: 98, Total Loss: 0.2965, loss_single: 0.2965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:28,137 - Iter: 99, Total Loss: 0.2963, loss_single: 0.2963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:28,172 - Iter: 100, Total Loss: 0.2961, loss_single: 0.2961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:38:28,283 - Saving summary figures for iter 100 +2026-06-24 04:38:31,850 - ### Finished 100 iterations, averaged iter_t = 0.038999 with std = 0.040 ### +2026-06-24 04:38:31,850 - +2026-06-24 04:38:31,850 - ### The PtyRADSolver is finished in 9.230 sec ### +2026-06-24 04:38:31,850 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..ef3e39c49cabccabfa07273da0964a48e524db44 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/simulation_data8__sample_000002.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/simulation_data8__sample_000002.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5b87a60980c20340baa23ea85f942bdd47e652d2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002/gendata3_std_02__simulation_data8__sample_000002_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-384_C12_18.2_phi12_62.8_C21_-96.9_phi21_331_C23_-912_phi23_356_C30_1.04e+07_C32_-3.1e+03_.5/simulation_data8__sample_000002.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 10.053448677062988 + probe_aberrations: + C10: -383.7359619140625 + C12: 18.234739303588867 + C21: -96.92977905273438 + C23: -912.0013427734375 + C30: 10434008.0 + C32: -3099.315673828125 + C34: -10574.3330078125 + C41: 443529.03125 + C43: 124879.3671875 + C45: 475732.53125 + C50: 13609200.0 + C52: -6313372.0 + C54: 3497176.0 + C56: -11651816.0 + phi12: 62.76447292489058 + phi21: 331.2584647074723 + phi23: 355.91255161101026 + phi32: 237.48851880003807 + phi34: 126.70044623584342 + phi41: 212.62052403207366 + phi43: 0.19418326527924099 + phi45: 201.742669137263 + phi52: 207.43108290448137 + phi54: 338.3241588000671 + phi56: 12.547239359100075 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data8__sample_000002_measurement.h5 + key: measurement + random_seed: 20261617 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data8__sample_000002 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data8__sample_000002 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/20260624_044924_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/20260624_044924_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..4e5640925476f39cea8b359a9fdc8e6bd72d8c1a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/20260624_044924_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:49:23,459 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:49:23,459 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:49:23,459 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:49:23,459 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:49:23,459 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:49:23,459 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:49:23,459 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:49:23,459 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:49:23,459 - +2026-06-24 04:49:23,542 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:49:23,542 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:49:23,542 - Accelerator.num_process = 1 +2026-06-24 04:49:23,542 - Accelerator.mixed_precision = no +2026-06-24 04:49:23,553 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:49:23,553 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:49:23,553 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:49:23,553 - +2026-06-24 04:49:23,553 - ### System information ### +2026-06-24 04:49:23,553 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:49:23,553 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:49:23,553 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:49:23,553 - Machine: x86_64 +2026-06-24 04:49:23,553 - Processor: x86_64 +2026-06-24 04:49:23,553 - Available CPU cores: 8 +2026-06-24 04:49:23,553 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:49:23,553 - +2026-06-24 04:49:23,553 - ### GPU information ### +2026-06-24 04:49:23,554 - CUDA Available: True +2026-06-24 04:49:23,554 - CUDA Version: 13.0 +2026-06-24 04:49:23,554 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:49:23,554 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:49:23,554 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:49:23,554 - In addition, Triton does not directly support Windows. +2026-06-24 04:49:23,554 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:49:23,569 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:49:23,569 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:49:23,569 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:49:23,569 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:49:23,569 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:49:23,569 - +2026-06-24 04:49:23,569 - ### Python information ### +2026-06-24 04:49:23,571 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:49:23,571 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:49:23,571 - +2026-06-24 04:49:23,571 - ### Packages information ### +2026-06-24 04:49:23,572 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:49:23,572 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:49:23,573 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:49:23,574 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:49:23,574 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:49:23,574 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:49:23,574 - +2026-06-24 04:49:23,574 - ### Loading params file ### +2026-06-24 04:49:23,574 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data9__sample_000011.yaml +2026-06-24 04:49:23,581 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:49:23,582 - Success! Params file validated and defaults applied. +2026-06-24 04:49:23,582 - +2026-06-24 04:49:23,582 - ### Setting GPU Device ### +2026-06-24 04:49:23,582 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:49:23,582 - +2026-06-24 04:49:23,582 - Random seed: 20261662 provided by params file +2026-06-24 04:49:23,582 - ### Initializing Initializer ### +2026-06-24 04:49:23,582 - init_params are displayed below: +2026-06-24 04:49:23,582 - random_seed: 20261662 +2026-06-24 04:49:23,582 - probe_illum_type: electron +2026-06-24 04:49:23,582 - probe_kv: 200.0 +2026-06-24 04:49:23,582 - probe_conv_angle: 9.135071754455566 +2026-06-24 04:49:23,583 - probe_aberrations: {'C10': -480.066, 'C12': -29.343, 'phi12': 234.266, 'C21': -596.802, 'phi21': 288.182, 'C23': 438.74, 'phi23': 143.647, 'C30': 12468925.0, 'C32': -7918.81, 'phi32': 303.163, 'C34': 3192.514, 'phi34': 61.524, 'C41': -275253.875, 'phi41': 243.711, 'C43': -467357.844, 'phi43': 350.645, 'C45': -367361.969, 'phi45': 193.231, 'C50': 16114874.0, 'C52': -11555331.0, 'phi52': 162.79, 'C54': 15583528.0, 'phi54': 191.479, 'C56': -3712321.25, 'phi56': 144.355} +2026-06-24 04:49:23,583 - beam_kev: None +2026-06-24 04:49:23,583 - probe_dRn: None +2026-06-24 04:49:23,583 - probe_Rn: None +2026-06-24 04:49:23,583 - probe_D_H: None +2026-06-24 04:49:23,583 - probe_D_FZP: None +2026-06-24 04:49:23,583 - probe_Ls: None +2026-06-24 04:49:23,583 - meas_Npix: 128 +2026-06-24 04:49:23,583 - pos_N_scans: 256 +2026-06-24 04:49:23,583 - pos_N_scan_slow: 16 +2026-06-24 04:49:23,583 - pos_N_scan_fast: 16 +2026-06-24 04:49:23,583 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:49:23,583 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:49:23,583 - probe_pmode_max: 6 +2026-06-24 04:49:23,583 - probe_pmode_init_pows: [0.02] +2026-06-24 04:49:23,583 - obj_omode_max: 1 +2026-06-24 04:49:23,583 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:49:23,583 - obj_Nlayer: 1 +2026-06-24 04:49:23,583 - obj_slice_thickness: 20.0 +2026-06-24 04:49:23,583 - simu_Npix: None +2026-06-24 04:49:23,583 - simu_match_mode: None +2026-06-24 04:49:23,583 - meas_permute: None +2026-06-24 04:49:23,583 - meas_reshape: [256, 128, 128] +2026-06-24 04:49:23,583 - meas_flipT: [0, 0, 0] +2026-06-24 04:49:23,583 - meas_crop: None +2026-06-24 04:49:23,583 - meas_pad: None +2026-06-24 04:49:23,583 - meas_resample: None +2026-06-24 04:49:23,583 - meas_add_source_size: None +2026-06-24 04:49:23,583 - meas_add_detector_blur: None +2026-06-24 04:49:23,583 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:49:23,583 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:49:23,583 - meas_add_poisson_noise: None +2026-06-24 04:49:23,583 - meas_export: None +2026-06-24 04:49:23,583 - probe_permute: None +2026-06-24 04:49:23,583 - probe_z_shift: None +2026-06-24 04:49:23,583 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:49:23,583 - pos_scan_flipT: None +2026-06-24 04:49:23,583 - pos_scan_affine: None +2026-06-24 04:49:23,583 - pos_scan_rand_std: 0.15 +2026-06-24 04:49:23,583 - obj_z_crop: None +2026-06-24 04:49:23,583 - obj_z_pad: None +2026-06-24 04:49:23,584 - obj_z_resample: None +2026-06-24 04:49:23,584 - meas_source: file +2026-06-24 04:49:23,584 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000011_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:49:23,584 - probe_source: simu +2026-06-24 04:49:23,584 - probe_params: None +2026-06-24 04:49:23,584 - pos_source: simu +2026-06-24 04:49:23,584 - pos_params: None +2026-06-24 04:49:23,584 - obj_source: simu +2026-06-24 04:49:23,584 - obj_params: None +2026-06-24 04:49:23,584 - tilt_source: simu +2026-06-24 04:49:23,584 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:49:23,584 - +2026-06-24 04:49:23,584 - ### Initializing cache ### +2026-06-24 04:49:23,584 - use_cached_obj = False +2026-06-24 04:49:23,584 - use_cached_probe = False +2026-06-24 04:49:23,584 - use_cached_pos = False +2026-06-24 04:49:23,584 - +2026-06-24 04:49:23,584 - ### Initializing measurements ### +2026-06-24 04:49:23,584 - Loading measurements from source = 'file' +2026-06-24 04:49:23,584 - Detected measurement file type = '.h5' +2026-06-24 04:49:23,661 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:49:23,661 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:49:23,662 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0048) +2026-06-24 04:49:23,662 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:49:23,663 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:49:23,664 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:49:23,664 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:49:23,665 - Normalizing by max of the 2D mean pattern intensity: 0.0034692138 +2026-06-24 04:49:23,665 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:49:23,667 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.3856) +2026-06-24 04:49:23,667 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:49:23,668 - Pattern total int. statistics (min, mean, max) = (284.8362, 287.6127, 291.2579), with min/max = 97.8% +2026-06-24 04:49:23,670 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0176, 1.3856) +2026-06-24 04:49:23,670 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:49:23,670 - +2026-06-24 04:49:23,670 - ### Setting up calibration ### +2026-06-24 04:49:23,670 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:49:23,670 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:49:23,670 - Radius of fitted bright field disk (RBF) = 9.18 px with meas_Npix = 128 +2026-06-24 04:49:23,670 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1435 +2026-06-24 04:49:23,670 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:49:23,670 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:49:23,887 - Initial guess: center=(63.63, 63.62), radius=9.18, Gaussian blur std=0.50 +2026-06-24 04:49:23,895 - Final fit: center=(63.63, 63.62), radius=9.18, Gaussian blur std=0.55 +2026-06-24 04:49:23,895 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.32 px with Npix = 128 +2026-06-24 04:49:23,895 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:49:23,895 - +2026-06-24 04:49:23,895 - ### Setting init_variables dict ### +2026-06-24 04:49:23,895 - Derived values given input init_params: +2026-06-24 04:49:23,895 - kv = 200.0 kV +2026-06-24 04:49:23,895 - wavelength = 0.0251 Ang +2026-06-24 04:49:23,895 - conv_angle = 9.135071754455566 mrad +2026-06-24 04:49:23,895 - Npix = 128 px +2026-06-24 04:49:23,895 - dk = 0.0391 Ang^-1 +2026-06-24 04:49:23,895 - kMax = 2.5000 Ang^-1 +2026-06-24 04:49:23,896 - da = 0.9797 mrad +2026-06-24 04:49:23,896 - angleMax = 62.6984 mrad +2026-06-24 04:49:23,896 - RBF = 9.3247 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:49:23,896 - n_alpha = 6.8635 (# conv_angle) +2026-06-24 04:49:23,896 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:49:23,896 - Rayleigh-limited resolution = 1.6747 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:49:23,896 - Real space probe extent = 25.6000 Ang +2026-06-24 04:49:23,896 - +2026-06-24 04:49:23,896 - ### Initializing probe ### +2026-06-24 04:49:23,896 - Loading probe from source = 'simu' +2026-06-24 04:49:23,896 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:49:23,896 - Start simulating STEM probe +2026-06-24 04:49:23,896 - kv = 200.0 kV +2026-06-24 04:49:23,896 - wavelength = 0.0251 Ang +2026-06-24 04:49:23,896 - conv_angle = 9.135071754455566 mrad +2026-06-24 04:49:23,896 - Npix = 128 px +2026-06-24 04:49:23,896 - dk = 0.0391 Ang^-1 +2026-06-24 04:49:23,896 - kMax = 2.5000 Ang^-1 +2026-06-24 04:49:23,896 - alpha_max = 62.6984 mrad +2026-06-24 04:49:23,896 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:49:23,896 - Rayleigh-limited resolution = 1.6747 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:49:23,896 - Real space probe extent = 25.6000 Ang +2026-06-24 04:49:23,896 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:49:23,896 - ------------------------------------------------------------------------------------ +2026-06-24 04:49:23,896 - C1,0 C1 -480.0660 - Defocus (C10 = -df) +2026-06-24 04:49:23,897 - C1,2 A1 -29.3430 234.27 2-fold astigmatism +2026-06-24 04:49:23,897 - C2,1 3*B2 -596.8020 288.18 Axial coma +2026-06-24 04:49:23,897 - C2,3 A2 438.7400 143.65 3-fold astigmatism +2026-06-24 04:49:23,897 - C3,0 C3 12468925.0000 - Spherical aberration +2026-06-24 04:49:23,897 - C3,2 4*S3 -7918.8100 303.16 Axial star aberration +2026-06-24 04:49:23,897 - C3,4 A3 3192.5140 61.52 4-fold astigmatism +2026-06-24 04:49:23,897 - C4,1 4*B4 -275253.8750 243.71 Axial coma(4th) +2026-06-24 04:49:23,897 - C4,3 4*D4 -467357.8440 350.64 3-lobe aberration +2026-06-24 04:49:23,897 - C4,5 A4 -367361.9690 193.23 5-fold astigmatism +2026-06-24 04:49:23,897 - C5,0 C5 16114874.0000 - Spherical aberration (5th) +2026-06-24 04:49:23,897 - C5,2 6*S5 -11555331.0000 162.79 Axial star aberration(5th) +2026-06-24 04:49:23,897 - C5,4 6*R5 15583528.0000 191.48 4-lobe aberration +2026-06-24 04:49:23,897 - C5,6 A5 -3712321.2500 144.35 6-fold astigmatism +2026-06-24 04:49:23,900 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:49:23,900 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:49:23,900 - Creating 5 new probe modes from the major mode +2026-06-24 04:49:23,900 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:49:24,003 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:49:24,004 - Orthogonalizing 6 pmodes +2026-06-24 04:49:24,006 - Sorting 6 pmodes by their intensities +2026-06-24 04:49:24,006 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:49:24,007 - sum(|probe_data|**2) = 287.61, while meas_total_ints (min, mean, max) = (284.8362, 287.6127, 291.2579) +2026-06-24 04:49:24,007 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:49:24,007 - +2026-06-24 04:49:24,007 - ### Initializing probe positions ### +2026-06-24 04:49:24,007 - Loading probe positions from source = 'simu' +2026-06-24 04:49:24,007 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:49:24,007 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:49:24,007 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:49:24,009 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:49:24,009 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:49:24,009 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:49:24,009 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:49:24,009 - +2026-06-24 04:49:24,009 - ### Initializing object ### +2026-06-24 04:49:24,009 - Loading object from source = 'simu' +2026-06-24 04:49:24,009 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:49:24,011 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:49:24,011 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:49:24,011 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:49:24,011 - +2026-06-24 04:49:24,011 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:49:24,011 - omode_occu (omode) = float32, (1,) +2026-06-24 04:49:24,011 - +2026-06-24 04:49:24,011 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:49:24,011 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:49:24,012 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:49:24,012 - +2026-06-24 04:49:24,012 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:49:24,012 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:49:24,012 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:49:24,012 - +2026-06-24 04:49:24,012 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:49:24,012 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:49:24,012 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:49:24,012 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:49:24,012 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:49:24,013 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:49:24,013 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:49:24,013 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:49:24,013 - +2026-06-24 04:49:24,013 - ### Collecting reconstruction provenance ### +2026-06-24 04:49:24,013 - Reconstruction provenance is collected and initialized. +2026-06-24 04:49:24,013 - +2026-06-24 04:49:24,013 - ### Initializing loss function ### +2026-06-24 04:49:24,013 - Active loss types: +2026-06-24 04:49:24,013 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:49:24,013 - +2026-06-24 04:49:24,013 - ### Initializing constraint function ### +2026-06-24 04:49:24,013 - Active constraint types: +2026-06-24 04:49:24,013 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:49:24,013 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:49:24,013 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:49:24,013 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:49:24,013 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:49:24,013 - +2026-06-24 04:49:24,013 - ### Done initializing PtyRADSolver ### +2026-06-24 04:49:24,013 - +2026-06-24 04:49:24,139 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:49:24,139 - +2026-06-24 04:49:24,139 - ### Initializing PtychoModel model ### +2026-06-24 04:49:24,209 - ### PtychoModel optimizable variables ### +2026-06-24 04:49:24,210 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:49:24,210 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:49:24,210 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:49:24,210 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:49:24,210 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:49:24,210 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:49:24,210 - +2026-06-24 04:49:24,210 - ### Optimizable variables statitsics ### +2026-06-24 04:49:24,210 - Total measurement values : 4,194,304 +2026-06-24 04:49:24,210 - Total optimizing variables: 278,728 +2026-06-24 04:49:24,210 - Overdetermined ratio : 15.05 +2026-06-24 04:49:24,210 - +2026-06-24 04:49:24,210 - ### Model behavior ### +2026-06-24 04:49:24,210 - Tilt propagator : False +2026-06-24 04:49:24,210 - Change slice thickness : False +2026-06-24 04:49:24,210 - Detector blur : False +2026-06-24 04:49:24,210 - Preload data : True +2026-06-24 04:49:24,210 - On-the-fly meas padding : False +2026-06-24 04:49:24,210 - On-the-fly meas resample : False +2026-06-24 04:49:24,210 - On-the-fly simu match mode: None +2026-06-24 04:49:24,210 - +2026-06-24 04:49:24,250 - ### Done initializing PtychoModel model ### +2026-06-24 04:49:24,251 - +2026-06-24 04:49:24,251 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:49:24,251 - +2026-06-24 04:49:24,251 - ### Generating indices, batches, and output_path ### +2026-06-24 04:49:24,252 - d90 = 47.000 px or 9.400 Ang +2026-06-24 04:49:24,252 - Selecting indices with the 'full' mode +2026-06-24 04:49:24,705 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:49:24,784 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:49:24,784 - Original recon_dir_affixes = ['default'] +2026-06-24 04:49:24,784 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:49:24,791 - Path corrected for compatibility: +2026-06-24 04:49:24,791 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_C32_-7.92e+03_phi32_303_C34_3.19e+03_phi34_61.5_C41_-2.75e+05_phi41_244_C43_-4.67e+05_phi43_351_C45_-3.67e+05_phi45_193_C50_1.61e+07_C52_-1.16e+07_phi52_163_C54_1.56e+07_phi54_191_C56_-3.71e+06_phi56_144 +2026-06-24 04:49:24,791 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144 +2026-06-24 04:49:24,792 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144' is generated! +2026-06-24 04:49:24,944 - +2026-06-24 04:49:24,945 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/20260624_044924_ptyrad_log.txt ### +2026-06-24 04:49:24,945 - +2026-06-24 04:49:24,947 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:49:24,947 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:49:24,947 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:49:26,134 - Iter: 1, Total Loss: 1.0412, loss_single: 1.0412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 04:49:26,171 - Iter: 2, Total Loss: 0.9965, loss_single: 0.9965, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:49:26,206 - Iter: 3, Total Loss: 0.9562, loss_single: 0.9562, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,242 - Iter: 4, Total Loss: 0.9158, loss_single: 0.9158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,277 - Iter: 5, Total Loss: 0.8759, loss_single: 0.8759, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,312 - Iter: 6, Total Loss: 0.8344, loss_single: 0.8344, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,348 - Iter: 7, Total Loss: 0.7942, loss_single: 0.7942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,383 - Iter: 8, Total Loss: 0.7625, loss_single: 0.7625, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,419 - Iter: 9, Total Loss: 0.7371, loss_single: 0.7371, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,454 - Iter: 10, Total Loss: 0.7116, loss_single: 0.7116, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,489 - Iter: 11, Total Loss: 0.6857, loss_single: 0.6857, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,524 - Iter: 12, Total Loss: 0.6608, loss_single: 0.6608, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,559 - Iter: 13, Total Loss: 0.6367, loss_single: 0.6367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,594 - Iter: 14, Total Loss: 0.6141, loss_single: 0.6141, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,630 - Iter: 15, Total Loss: 0.5930, loss_single: 0.5930, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,665 - Iter: 16, Total Loss: 0.5734, loss_single: 0.5734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,700 - Iter: 17, Total Loss: 0.5550, loss_single: 0.5550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,735 - Iter: 18, Total Loss: 0.5384, loss_single: 0.5384, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,770 - Iter: 19, Total Loss: 0.5236, loss_single: 0.5236, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,806 - Iter: 20, Total Loss: 0.5100, loss_single: 0.5100, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,841 - Iter: 21, Total Loss: 0.4988, loss_single: 0.4988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,876 - Iter: 22, Total Loss: 0.4892, loss_single: 0.4892, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,912 - Iter: 23, Total Loss: 0.4821, loss_single: 0.4821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,947 - Iter: 24, Total Loss: 0.4771, loss_single: 0.4771, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:26,982 - Iter: 25, Total Loss: 0.4733, loss_single: 0.4733, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,017 - Iter: 26, Total Loss: 0.4708, loss_single: 0.4708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,053 - Iter: 27, Total Loss: 0.4687, loss_single: 0.4687, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,088 - Iter: 28, Total Loss: 0.4666, loss_single: 0.4666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,123 - Iter: 29, Total Loss: 0.4642, loss_single: 0.4642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,158 - Iter: 30, Total Loss: 0.4621, loss_single: 0.4621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,193 - Iter: 31, Total Loss: 0.4605, loss_single: 0.4605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:49:27,228 - Iter: 32, Total Loss: 0.4592, loss_single: 0.4592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,267 - Iter: 33, Total Loss: 0.4578, loss_single: 0.4578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 04:49:27,302 - Iter: 34, Total Loss: 0.4565, loss_single: 0.4565, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,337 - Iter: 35, Total Loss: 0.4556, loss_single: 0.4556, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:49:27,373 - Iter: 36, Total Loss: 0.4548, loss_single: 0.4548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,408 - Iter: 37, Total Loss: 0.4540, loss_single: 0.4540, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,443 - Iter: 38, Total Loss: 0.4533, loss_single: 0.4533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,478 - Iter: 39, Total Loss: 0.4528, loss_single: 0.4528, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,514 - Iter: 40, Total Loss: 0.4523, loss_single: 0.4523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,551 - Iter: 41, Total Loss: 0.4518, loss_single: 0.4518, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,586 - Iter: 42, Total Loss: 0.4513, loss_single: 0.4513, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,621 - Iter: 43, Total Loss: 0.4509, loss_single: 0.4509, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,657 - Iter: 44, Total Loss: 0.4505, loss_single: 0.4505, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,692 - Iter: 45, Total Loss: 0.4501, loss_single: 0.4501, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,727 - Iter: 46, Total Loss: 0.4497, loss_single: 0.4497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,762 - Iter: 47, Total Loss: 0.4493, loss_single: 0.4493, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,797 - Iter: 48, Total Loss: 0.4488, loss_single: 0.4488, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,832 - Iter: 49, Total Loss: 0.4485, loss_single: 0.4485, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,867 - Iter: 50, Total Loss: 0.4482, loss_single: 0.4482, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:49:27,903 - Iter: 51, Total Loss: 0.4479, loss_single: 0.4479, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,938 - Iter: 52, Total Loss: 0.4476, loss_single: 0.4476, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:49:27,973 - 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Saving summary figures for iter 100 +2026-06-24 04:49:33,322 - ### Finished 100 iterations, averaged iter_t = 0.038865 with std = 0.040 ### +2026-06-24 04:49:33,322 - +2026-06-24 04:49:33,322 - ### The PtyRADSolver is finished in 9.183 sec ### +2026-06-24 04:49:33,322 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..648ed294bb734fb81e000078514f94fdd6ee2c0e Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/simulation_data9__sample_000011.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/simulation_data9__sample_000011.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1e66d94a437eb1fb44340e31ac870469735b65b6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011/gendata3_std_02__simulation_data9__sample_000011_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-480_C12_-29.3_phi12_234_C21_-597_phi21_288_C23_439_phi23_144_C30_1.25e+07_.71e+06_phi56_144/simulation_data9__sample_000011.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.135071754455566 + probe_aberrations: + C10: -480.0659484863281 + C12: -29.342788696289062 + C21: -596.801513671875 + C23: 438.7400817871094 + C30: 12468925.0 + C32: -7918.8095703125 + C34: 3192.513916015625 + C41: -275253.875 + C43: -467357.84375 + C45: -367361.96875 + C50: 16114874.0 + C52: -11555331.0 + C54: 15583528.0 + C56: -3712321.25 + phi12: 234.26589894584265 + phi21: 288.1821828198727 + phi23: 143.64671930253533 + phi32: 303.16346510386535 + phi34: 61.52385785461698 + phi41: 243.7106845301363 + phi43: 350.6448638362863 + phi45: 193.23069614829635 + phi52: 162.79048279127377 + phi54: 191.47905315451155 + phi56: 144.3549962590873 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000011_measurement.h5 + key: measurement + random_seed: 20261662 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000011 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data9__sample_000011 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/20260624_045235_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/20260624_045235_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..5b7a9b45a3b9cc9c6837eaf9a30d6f95c8f8dc85 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/20260624_045235_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:52:34,311 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:52:34,311 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:52:34,311 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:52:34,311 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:52:34,311 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:52:34,311 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:52:34,311 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:52:34,311 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:52:34,311 - +2026-06-24 04:52:34,417 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:52:34,417 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:52:34,417 - Accelerator.num_process = 1 +2026-06-24 04:52:34,417 - Accelerator.mixed_precision = no +2026-06-24 04:52:34,427 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:52:34,427 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:52:34,427 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:52:34,427 - +2026-06-24 04:52:34,427 - ### System information ### +2026-06-24 04:52:34,427 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:52:34,428 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:52:34,428 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:52:34,428 - Machine: x86_64 +2026-06-24 04:52:34,428 - Processor: x86_64 +2026-06-24 04:52:34,428 - Available CPU cores: 8 +2026-06-24 04:52:34,428 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:52:34,428 - +2026-06-24 04:52:34,428 - ### GPU information ### +2026-06-24 04:52:34,428 - CUDA Available: True +2026-06-24 04:52:34,428 - CUDA Version: 13.0 +2026-06-24 04:52:34,428 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:52:34,429 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:52:34,429 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:52:34,429 - In addition, Triton does not directly support Windows. +2026-06-24 04:52:34,429 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:52:34,443 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:52:34,443 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:52:34,443 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:52:34,443 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:52:34,444 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:52:34,444 - +2026-06-24 04:52:34,444 - ### Python information ### +2026-06-24 04:52:34,446 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:52:34,446 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:52:34,446 - +2026-06-24 04:52:34,446 - ### Packages information ### +2026-06-24 04:52:34,446 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:52:34,447 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:52:34,448 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:52:34,448 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:52:34,449 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:52:34,449 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:52:34,449 - +2026-06-24 04:52:34,449 - ### Loading params file ### +2026-06-24 04:52:34,449 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data9__sample_000024.yaml +2026-06-24 04:52:34,455 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:52:34,456 - Success! Params file validated and defaults applied. +2026-06-24 04:52:34,456 - +2026-06-24 04:52:34,456 - ### Setting GPU Device ### +2026-06-24 04:52:34,457 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:52:34,457 - +2026-06-24 04:52:34,457 - Random seed: 20261675 provided by params file +2026-06-24 04:52:34,457 - ### Initializing Initializer ### +2026-06-24 04:52:34,457 - init_params are displayed below: +2026-06-24 04:52:34,457 - random_seed: 20261675 +2026-06-24 04:52:34,457 - probe_illum_type: electron +2026-06-24 04:52:34,457 - probe_kv: 200.0 +2026-06-24 04:52:34,457 - probe_conv_angle: 9.626856803894043 +2026-06-24 04:52:34,457 - probe_aberrations: {'C10': -319.86, 'C12': -34.378, 'phi12': 260.919, 'C21': -11.527, 'phi21': 80.585, 'C23': -936.256, 'phi23': 74.59, 'C30': 11840959.0, 'C32': 445.095, 'phi32': 125.271, 'C34': 11534.697, 'phi34': 328.618, 'C41': -17684.365, 'phi41': 297.011, 'C43': 254354.453, 'phi43': 139.532, 'C45': 395319.531, 'phi45': 136.487, 'C50': -15404038.0, 'C52': 14131282.0, 'phi52': 302.936, 'C54': -4953916.5, 'phi54': 353.243, 'C56': -10474631.0, 'phi56': 188.381} +2026-06-24 04:52:34,457 - beam_kev: None +2026-06-24 04:52:34,457 - probe_dRn: None +2026-06-24 04:52:34,457 - probe_Rn: None +2026-06-24 04:52:34,457 - probe_D_H: None +2026-06-24 04:52:34,457 - probe_D_FZP: None +2026-06-24 04:52:34,457 - probe_Ls: None +2026-06-24 04:52:34,457 - meas_Npix: 128 +2026-06-24 04:52:34,458 - pos_N_scans: 256 +2026-06-24 04:52:34,458 - pos_N_scan_slow: 16 +2026-06-24 04:52:34,458 - pos_N_scan_fast: 16 +2026-06-24 04:52:34,458 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:52:34,458 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:52:34,458 - probe_pmode_max: 6 +2026-06-24 04:52:34,458 - probe_pmode_init_pows: [0.02] +2026-06-24 04:52:34,458 - obj_omode_max: 1 +2026-06-24 04:52:34,458 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:52:34,458 - obj_Nlayer: 1 +2026-06-24 04:52:34,458 - obj_slice_thickness: 20.0 +2026-06-24 04:52:34,458 - simu_Npix: None +2026-06-24 04:52:34,458 - simu_match_mode: None +2026-06-24 04:52:34,458 - meas_permute: None +2026-06-24 04:52:34,458 - meas_reshape: [256, 128, 128] +2026-06-24 04:52:34,458 - meas_flipT: [0, 0, 0] +2026-06-24 04:52:34,458 - meas_crop: None +2026-06-24 04:52:34,458 - meas_pad: None +2026-06-24 04:52:34,458 - meas_resample: None +2026-06-24 04:52:34,458 - meas_add_source_size: None +2026-06-24 04:52:34,458 - meas_add_detector_blur: None +2026-06-24 04:52:34,458 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:52:34,458 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:52:34,458 - meas_add_poisson_noise: None +2026-06-24 04:52:34,458 - meas_export: None +2026-06-24 04:52:34,458 - probe_permute: None +2026-06-24 04:52:34,458 - probe_z_shift: None +2026-06-24 04:52:34,458 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:52:34,458 - pos_scan_flipT: None +2026-06-24 04:52:34,458 - pos_scan_affine: None +2026-06-24 04:52:34,458 - pos_scan_rand_std: 0.15 +2026-06-24 04:52:34,458 - obj_z_crop: None +2026-06-24 04:52:34,458 - obj_z_pad: None +2026-06-24 04:52:34,458 - obj_z_resample: None +2026-06-24 04:52:34,458 - meas_source: file +2026-06-24 04:52:34,458 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000024_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:52:34,458 - probe_source: simu +2026-06-24 04:52:34,458 - probe_params: None +2026-06-24 04:52:34,458 - pos_source: simu +2026-06-24 04:52:34,458 - pos_params: None +2026-06-24 04:52:34,458 - obj_source: simu +2026-06-24 04:52:34,459 - obj_params: None +2026-06-24 04:52:34,459 - tilt_source: simu +2026-06-24 04:52:34,459 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:52:34,459 - +2026-06-24 04:52:34,459 - ### Initializing cache ### +2026-06-24 04:52:34,459 - use_cached_obj = False +2026-06-24 04:52:34,459 - use_cached_probe = False +2026-06-24 04:52:34,459 - use_cached_pos = False +2026-06-24 04:52:34,459 - +2026-06-24 04:52:34,459 - ### Initializing measurements ### +2026-06-24 04:52:34,459 - Loading measurements from source = 'file' +2026-06-24 04:52:34,459 - Detected measurement file type = '.h5' +2026-06-24 04:52:34,537 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:52:34,537 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:52:34,539 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0037) +2026-06-24 04:52:34,539 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:52:34,539 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:52:34,540 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:52:34,540 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:52:34,541 - Normalizing by max of the 2D mean pattern intensity: 0.0031936548 +2026-06-24 04:52:34,541 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:52:34,543 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0191, 1.1475) +2026-06-24 04:52:34,543 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:52:34,545 - Pattern total int. statistics (min, mean, max) = (311.7780, 312.8057, 314.0519), with min/max = 99.3% +2026-06-24 04:52:34,546 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0191, 1.1475) +2026-06-24 04:52:34,546 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:52:34,546 - +2026-06-24 04:52:34,546 - ### Setting up calibration ### +2026-06-24 04:52:34,546 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:52:34,546 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:52:34,546 - Radius of fitted bright field disk (RBF) = 9.71 px with meas_Npix = 128 +2026-06-24 04:52:34,546 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1517 +2026-06-24 04:52:34,546 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:52:34,546 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:52:34,770 - Initial guess: center=(63.62, 63.63), radius=9.71, Gaussian blur std=0.50 +2026-06-24 04:52:34,784 - Final fit: center=(63.62, 63.63), radius=9.71, Gaussian blur std=0.71 +2026-06-24 04:52:34,784 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.83 px with Npix = 128 +2026-06-24 04:52:34,784 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:52:34,784 - +2026-06-24 04:52:34,784 - ### Setting init_variables dict ### +2026-06-24 04:52:34,784 - Derived values given input init_params: +2026-06-24 04:52:34,784 - kv = 200.0 kV +2026-06-24 04:52:34,784 - wavelength = 0.0251 Ang +2026-06-24 04:52:34,784 - conv_angle = 9.626856803894043 mrad +2026-06-24 04:52:34,784 - Npix = 128 px +2026-06-24 04:52:34,784 - dk = 0.0391 Ang^-1 +2026-06-24 04:52:34,784 - kMax = 2.5000 Ang^-1 +2026-06-24 04:52:34,784 - da = 0.9797 mrad +2026-06-24 04:52:34,784 - angleMax = 62.6984 mrad +2026-06-24 04:52:34,784 - RBF = 9.8267 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:52:34,784 - n_alpha = 6.5129 (# conv_angle) +2026-06-24 04:52:34,784 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:52:34,784 - Rayleigh-limited resolution = 1.5891 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:52:34,784 - Real space probe extent = 25.6000 Ang +2026-06-24 04:52:34,784 - +2026-06-24 04:52:34,784 - ### Initializing probe ### +2026-06-24 04:52:34,784 - Loading probe from source = 'simu' +2026-06-24 04:52:34,784 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:52:34,785 - Start simulating STEM probe +2026-06-24 04:52:34,785 - kv = 200.0 kV +2026-06-24 04:52:34,785 - wavelength = 0.0251 Ang +2026-06-24 04:52:34,785 - conv_angle = 9.626856803894043 mrad +2026-06-24 04:52:34,785 - Npix = 128 px +2026-06-24 04:52:34,785 - dk = 0.0391 Ang^-1 +2026-06-24 04:52:34,785 - kMax = 2.5000 Ang^-1 +2026-06-24 04:52:34,785 - alpha_max = 62.6984 mrad +2026-06-24 04:52:34,785 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:52:34,785 - Rayleigh-limited resolution = 1.5891 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:52:34,785 - Real space probe extent = 25.6000 Ang +2026-06-24 04:52:34,785 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:52:34,785 - ------------------------------------------------------------------------------------ +2026-06-24 04:52:34,785 - C1,0 C1 -319.8600 - Defocus (C10 = -df) +2026-06-24 04:52:34,785 - C1,2 A1 -34.3780 260.92 2-fold astigmatism +2026-06-24 04:52:34,785 - C2,1 3*B2 -11.5270 80.58 Axial coma +2026-06-24 04:52:34,785 - C2,3 A2 -936.2560 74.59 3-fold astigmatism +2026-06-24 04:52:34,785 - C3,0 C3 11840959.0000 - Spherical aberration +2026-06-24 04:52:34,785 - C3,2 4*S3 445.0950 125.27 Axial star aberration +2026-06-24 04:52:34,785 - C3,4 A3 11534.6970 328.62 4-fold astigmatism +2026-06-24 04:52:34,785 - C4,1 4*B4 -17684.3650 297.01 Axial coma(4th) +2026-06-24 04:52:34,785 - C4,3 4*D4 254354.4530 139.53 3-lobe aberration +2026-06-24 04:52:34,785 - C4,5 A4 395319.5310 136.49 5-fold astigmatism +2026-06-24 04:52:34,785 - C5,0 C5 -15404038.0000 - Spherical aberration (5th) +2026-06-24 04:52:34,785 - C5,2 6*S5 14131282.0000 302.94 Axial star aberration(5th) +2026-06-24 04:52:34,785 - C5,4 6*R5 -4953916.5000 353.24 4-lobe aberration +2026-06-24 04:52:34,785 - C5,6 A5 -10474631.0000 188.38 6-fold astigmatism +2026-06-24 04:52:34,788 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:52:34,788 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:52:34,788 - Creating 5 new probe modes from the major mode +2026-06-24 04:52:34,788 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:52:34,955 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:52:34,956 - Orthogonalizing 6 pmodes +2026-06-24 04:52:34,959 - Sorting 6 pmodes by their intensities +2026-06-24 04:52:34,959 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:52:34,960 - sum(|probe_data|**2) = 312.81, while meas_total_ints (min, mean, max) = (311.7780, 312.8057, 314.0519) +2026-06-24 04:52:34,960 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:52:34,960 - +2026-06-24 04:52:34,960 - ### Initializing probe positions ### +2026-06-24 04:52:34,960 - Loading probe positions from source = 'simu' +2026-06-24 04:52:34,960 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:52:34,960 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:52:34,960 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:52:34,962 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:52:34,962 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:52:34,963 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:52:34,963 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:52:34,963 - +2026-06-24 04:52:34,963 - ### Initializing object ### +2026-06-24 04:52:34,963 - Loading object from source = 'simu' +2026-06-24 04:52:34,963 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:52:34,964 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:52:34,964 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:52:34,964 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:52:34,965 - +2026-06-24 04:52:34,965 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:52:34,965 - omode_occu (omode) = float32, (1,) +2026-06-24 04:52:34,965 - +2026-06-24 04:52:34,965 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:52:34,965 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:52:34,965 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:52:34,965 - +2026-06-24 04:52:34,965 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:52:34,966 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:52:34,966 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:52:34,966 - +2026-06-24 04:52:34,966 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:52:34,966 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:52:34,966 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:52:34,966 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:52:34,966 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:52:34,966 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:52:34,966 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:52:34,966 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:52:34,966 - +2026-06-24 04:52:34,966 - ### Collecting reconstruction provenance ### +2026-06-24 04:52:34,966 - Reconstruction provenance is collected and initialized. +2026-06-24 04:52:34,966 - +2026-06-24 04:52:34,966 - ### Initializing loss function ### +2026-06-24 04:52:34,966 - Active loss types: +2026-06-24 04:52:34,966 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:52:34,966 - +2026-06-24 04:52:34,966 - ### Initializing constraint function ### +2026-06-24 04:52:34,967 - Active constraint types: +2026-06-24 04:52:34,967 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:52:34,967 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:52:34,967 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:52:34,967 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:52:34,967 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:52:34,967 - +2026-06-24 04:52:34,967 - ### Done initializing PtyRADSolver ### +2026-06-24 04:52:34,967 - +2026-06-24 04:52:35,098 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:52:35,098 - +2026-06-24 04:52:35,098 - ### Initializing PtychoModel model ### +2026-06-24 04:52:35,170 - ### PtychoModel optimizable variables ### +2026-06-24 04:52:35,170 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:52:35,171 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:52:35,171 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:52:35,171 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:52:35,171 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:52:35,171 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:52:35,171 - +2026-06-24 04:52:35,171 - ### Optimizable variables statitsics ### +2026-06-24 04:52:35,171 - Total measurement values : 4,194,304 +2026-06-24 04:52:35,171 - Total optimizing variables: 278,728 +2026-06-24 04:52:35,171 - Overdetermined ratio : 15.05 +2026-06-24 04:52:35,171 - +2026-06-24 04:52:35,171 - ### Model behavior ### +2026-06-24 04:52:35,171 - Tilt propagator : False +2026-06-24 04:52:35,171 - Change slice thickness : False +2026-06-24 04:52:35,171 - Detector blur : False +2026-06-24 04:52:35,171 - Preload data : True +2026-06-24 04:52:35,171 - On-the-fly meas padding : False +2026-06-24 04:52:35,171 - On-the-fly meas resample : False +2026-06-24 04:52:35,171 - On-the-fly simu match mode: None +2026-06-24 04:52:35,171 - +2026-06-24 04:52:35,213 - ### Done initializing PtychoModel model ### +2026-06-24 04:52:35,213 - +2026-06-24 04:52:35,213 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:52:35,214 - +2026-06-24 04:52:35,214 - ### Generating indices, batches, and output_path ### +2026-06-24 04:52:35,215 - d90 = 59.000 px or 11.800 Ang +2026-06-24 04:52:35,215 - Selecting indices with the 'full' mode +2026-06-24 04:52:35,675 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:52:35,754 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:52:35,754 - Original recon_dir_affixes = ['default'] +2026-06-24 04:52:35,754 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:52:35,760 - Path corrected for compatibility: +2026-06-24 04:52:35,760 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e+07_C32_445_phi32_125_C34_1.15e+04_phi34_329_C41_-1.77e+04_phi41_297_C43_2.54e+05_phi43_140_C45_3.95e+05_phi45_136_C50_-1.54e+07_C52_1.41e+07_phi52_303_C54_-4.95e+06_phi54_353_C56_-1.05e+07_phi56_188 +2026-06-24 04:52:35,760 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188 +2026-06-24 04:52:35,761 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188' is generated! +2026-06-24 04:52:35,918 - +2026-06-24 04:52:35,919 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/20260624_045235_ptyrad_log.txt ### +2026-06-24 04:52:35,919 - +2026-06-24 04:52:35,921 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:52:35,921 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:52:35,921 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:52:37,142 - Iter: 1, Total Loss: 0.9660, loss_single: 0.9660, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.441 sec +2026-06-24 04:52:37,179 - Iter: 2, Total Loss: 0.9132, loss_single: 0.9132, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:52:37,214 - Iter: 3, Total Loss: 0.8766, loss_single: 0.8766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,259 - Iter: 4, Total Loss: 0.8417, loss_single: 0.8417, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.044 sec +2026-06-24 04:52:37,295 - Iter: 5, Total Loss: 0.8040, loss_single: 0.8040, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:52:37,330 - Iter: 6, Total Loss: 0.7681, loss_single: 0.7681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,365 - Iter: 7, Total Loss: 0.7326, loss_single: 0.7326, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,400 - Iter: 8, Total Loss: 0.6994, loss_single: 0.6994, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,436 - Iter: 9, Total Loss: 0.6644, loss_single: 0.6644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,471 - Iter: 10, Total Loss: 0.6272, loss_single: 0.6272, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,507 - Iter: 11, Total Loss: 0.5888, loss_single: 0.5888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,542 - Iter: 12, Total Loss: 0.5584, loss_single: 0.5584, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,577 - Iter: 13, Total Loss: 0.5315, loss_single: 0.5315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,613 - Iter: 14, Total Loss: 0.5046, loss_single: 0.5046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,648 - Iter: 15, Total Loss: 0.4824, loss_single: 0.4824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,684 - Iter: 16, Total Loss: 0.4586, loss_single: 0.4586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:52:37,719 - Iter: 17, Total Loss: 0.4327, loss_single: 0.4327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,754 - Iter: 18, Total Loss: 0.4102, loss_single: 0.4102, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,793 - Iter: 19, Total Loss: 0.3891, loss_single: 0.3891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 04:52:37,828 - Iter: 20, Total Loss: 0.3637, loss_single: 0.3637, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,864 - Iter: 21, Total Loss: 0.3405, loss_single: 0.3405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,900 - Iter: 22, Total Loss: 0.3179, loss_single: 0.3179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:52:37,936 - Iter: 23, Total Loss: 0.3004, loss_single: 0.3004, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:37,971 - Iter: 24, Total Loss: 0.2871, loss_single: 0.2871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,007 - Iter: 25, Total Loss: 0.2716, loss_single: 0.2716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,042 - Iter: 26, Total Loss: 0.2592, loss_single: 0.2592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,077 - Iter: 27, Total Loss: 0.2515, loss_single: 0.2515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,113 - Iter: 28, Total Loss: 0.2437, loss_single: 0.2437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,148 - Iter: 29, Total Loss: 0.2327, loss_single: 0.2327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,184 - Iter: 30, Total Loss: 0.2227, loss_single: 0.2227, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,219 - Iter: 31, Total Loss: 0.2166, loss_single: 0.2166, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,254 - Iter: 32, Total Loss: 0.2120, loss_single: 0.2120, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,289 - Iter: 33, Total Loss: 0.2079, loss_single: 0.2079, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,325 - Iter: 34, Total Loss: 0.2042, loss_single: 0.2042, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,360 - Iter: 35, Total Loss: 0.2011, loss_single: 0.2011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,396 - Iter: 36, Total Loss: 0.1993, loss_single: 0.1993, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:52:38,431 - Iter: 37, Total Loss: 0.1980, loss_single: 0.1980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 04:52:38,466 - Iter: 38, Total Loss: 0.1968, loss_single: 0.1968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,502 - Iter: 39, Total Loss: 0.1957, loss_single: 0.1957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,537 - Iter: 40, Total Loss: 0.1948, loss_single: 0.1948, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:52:38,575 - 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Saving summary figures for iter 100 +2026-06-24 04:52:44,407 - ### Finished 100 iterations, averaged iter_t = 0.039214 with std = 0.040 ### +2026-06-24 04:52:44,407 - +2026-06-24 04:52:44,407 - ### The PtyRADSolver is finished in 9.309 sec ### +2026-06-24 04:52:44,407 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..4e0e00068e5fa62e84409fe2d43d3c730555113e Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/simulation_data9__sample_000024.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/simulation_data9__sample_000024.yaml new file mode 100644 index 0000000000000000000000000000000000000000..de95ebedc5388e86e9d1139c230b647adeeb0041 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024/gendata3_std_02__simulation_data9__sample_000024_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-320_C12_-34.4_phi12_261_C21_-11.5_phi21_80.6_C23_-936_phi23_74.6_C30_1.18e.05e+07_phi56_188/simulation_data9__sample_000024.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.626856803894043 + probe_aberrations: + C10: -319.8601379394531 + C12: -34.37777328491211 + C21: -11.527031898498535 + C23: -936.255859375 + C30: 11840959.0 + C32: 445.0951843261719 + C34: 11534.697265625 + C41: -17684.365234375 + C43: 254354.453125 + C45: 395319.53125 + C50: -15404038.0 + C52: 14131282.0 + C54: -4953916.5 + C56: -10474631.0 + phi12: 260.9189363326332 + phi21: 80.58454575248057 + phi23: 74.58982532174377 + phi32: 125.27050515196622 + phi34: 328.6184053479656 + phi41: 297.0113224731381 + phi43: 139.53228164841136 + phi45: 136.48670029750267 + phi52: 302.9364022950974 + phi54: 353.2429858342891 + phi56: 188.3807973847237 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000024_measurement.h5 + key: measurement + random_seed: 20261675 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000024 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data9__sample_000024 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/20260624_045349_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/20260624_045349_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b3f9881c3917fdb07effc1e27d8f499bcca78e2f --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/20260624_045349_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 04:53:47,909 - ### PtyRAD LoggingManager configuration ### +2026-06-24 04:53:47,909 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 04:53:47,909 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 04:53:47,909 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 04:53:47,909 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 04:53:47,910 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 04:53:47,910 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 04:53:47,910 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 04:53:47,910 - +2026-06-24 04:53:48,018 - ### Initializing HuggingFace accelerator ### +2026-06-24 04:53:48,018 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 04:53:48,018 - Accelerator.num_process = 1 +2026-06-24 04:53:48,018 - Accelerator.mixed_precision = no +2026-06-24 04:53:48,040 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 04:53:48,040 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 04:53:48,040 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 04:53:48,040 - +2026-06-24 04:53:48,040 - ### System information ### +2026-06-24 04:53:48,040 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 04:53:48,040 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 04:53:48,040 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 04:53:48,040 - Machine: x86_64 +2026-06-24 04:53:48,041 - Processor: x86_64 +2026-06-24 04:53:48,041 - Available CPU cores: 8 +2026-06-24 04:53:48,041 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 04:53:48,041 - +2026-06-24 04:53:48,041 - ### GPU information ### +2026-06-24 04:53:48,041 - CUDA Available: True +2026-06-24 04:53:48,041 - CUDA Version: 13.0 +2026-06-24 04:53:48,041 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 04:53:48,041 - CUDA Compute Capability: ['8.0'] +2026-06-24 04:53:48,041 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 04:53:48,041 - In addition, Triton does not directly support Windows. +2026-06-24 04:53:48,041 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 04:53:48,056 - MIG (Multi-Instance GPU) mode = False +2026-06-24 04:53:48,057 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 04:53:48,057 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 04:53:48,057 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 04:53:48,057 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 04:53:48,057 - +2026-06-24 04:53:48,057 - ### Python information ### +2026-06-24 04:53:48,059 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 04:53:48,059 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 04:53:48,059 - +2026-06-24 04:53:48,059 - ### Packages information ### +2026-06-24 04:53:48,059 - Numpy Version (metadata): 2.4.6 +2026-06-24 04:53:48,060 - PyTorch Version (metadata): 2.12.0 +2026-06-24 04:53:48,061 - Optuna Version (metadata): 4.9.0 +2026-06-24 04:53:48,062 - Accelerate Version (metadata): 1.13.0 +2026-06-24 04:53:48,062 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 04:53:48,062 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 04:53:48,062 - +2026-06-24 04:53:48,062 - ### Loading params file ### +2026-06-24 04:53:48,062 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data9__sample_000029.yaml +2026-06-24 04:53:48,069 - validate = True: Filling defaults and validating the params file... +2026-06-24 04:53:48,070 - Success! Params file validated and defaults applied. +2026-06-24 04:53:48,070 - +2026-06-24 04:53:48,070 - ### Setting GPU Device ### +2026-06-24 04:53:48,070 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 04:53:48,070 - +2026-06-24 04:53:48,070 - Random seed: 20261680 provided by params file +2026-06-24 04:53:48,070 - ### Initializing Initializer ### +2026-06-24 04:53:48,071 - init_params are displayed below: +2026-06-24 04:53:48,071 - random_seed: 20261680 +2026-06-24 04:53:48,071 - probe_illum_type: electron +2026-06-24 04:53:48,071 - probe_kv: 200.0 +2026-06-24 04:53:48,071 - probe_conv_angle: 10.042913436889648 +2026-06-24 04:53:48,071 - probe_aberrations: {'C10': -424.149, 'C12': -48.226, 'phi12': 61.976, 'C21': -774.585, 'phi21': 102.367, 'C23': 946.593, 'phi23': 158.212, 'C30': 10673077.0, 'C32': 7044.538, 'phi32': 21.066, 'C34': -4829.787, 'phi34': 198.599, 'C41': 238209.125, 'phi41': 138.202, 'C43': 247782.438, 'phi43': 18.855, 'C45': 370824.75, 'phi45': 269.023, 'C50': 2281911.5, 'C52': -10411431.0, 'phi52': 49.757, 'C54': 2667136.25, 'phi54': 108.665, 'C56': -3126392.0, 'phi56': 48.1} +2026-06-24 04:53:48,071 - beam_kev: None +2026-06-24 04:53:48,071 - probe_dRn: None +2026-06-24 04:53:48,071 - probe_Rn: None +2026-06-24 04:53:48,071 - probe_D_H: None +2026-06-24 04:53:48,071 - probe_D_FZP: None +2026-06-24 04:53:48,071 - probe_Ls: None +2026-06-24 04:53:48,071 - meas_Npix: 128 +2026-06-24 04:53:48,071 - pos_N_scans: 256 +2026-06-24 04:53:48,071 - pos_N_scan_slow: 16 +2026-06-24 04:53:48,071 - pos_N_scan_fast: 16 +2026-06-24 04:53:48,071 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 04:53:48,071 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 04:53:48,071 - probe_pmode_max: 6 +2026-06-24 04:53:48,071 - probe_pmode_init_pows: [0.02] +2026-06-24 04:53:48,071 - obj_omode_max: 1 +2026-06-24 04:53:48,071 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 04:53:48,071 - obj_Nlayer: 1 +2026-06-24 04:53:48,071 - obj_slice_thickness: 20.0 +2026-06-24 04:53:48,071 - simu_Npix: None +2026-06-24 04:53:48,071 - simu_match_mode: None +2026-06-24 04:53:48,071 - meas_permute: None +2026-06-24 04:53:48,071 - meas_reshape: [256, 128, 128] +2026-06-24 04:53:48,071 - meas_flipT: [0, 0, 0] +2026-06-24 04:53:48,071 - meas_crop: None +2026-06-24 04:53:48,071 - meas_pad: None +2026-06-24 04:53:48,071 - meas_resample: None +2026-06-24 04:53:48,071 - meas_add_source_size: None +2026-06-24 04:53:48,071 - meas_add_detector_blur: None +2026-06-24 04:53:48,071 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 04:53:48,072 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 04:53:48,072 - meas_add_poisson_noise: None +2026-06-24 04:53:48,072 - meas_export: None +2026-06-24 04:53:48,072 - probe_permute: None +2026-06-24 04:53:48,072 - probe_z_shift: None +2026-06-24 04:53:48,072 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 04:53:48,072 - pos_scan_flipT: None +2026-06-24 04:53:48,072 - pos_scan_affine: None +2026-06-24 04:53:48,072 - pos_scan_rand_std: 0.15 +2026-06-24 04:53:48,072 - obj_z_crop: None +2026-06-24 04:53:48,072 - obj_z_pad: None +2026-06-24 04:53:48,072 - obj_z_resample: None +2026-06-24 04:53:48,072 - meas_source: file +2026-06-24 04:53:48,072 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000029_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 04:53:48,072 - probe_source: simu +2026-06-24 04:53:48,072 - probe_params: None +2026-06-24 04:53:48,072 - pos_source: simu +2026-06-24 04:53:48,072 - pos_params: None +2026-06-24 04:53:48,072 - obj_source: simu +2026-06-24 04:53:48,072 - obj_params: None +2026-06-24 04:53:48,072 - tilt_source: simu +2026-06-24 04:53:48,072 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 04:53:48,072 - +2026-06-24 04:53:48,072 - ### Initializing cache ### +2026-06-24 04:53:48,072 - use_cached_obj = False +2026-06-24 04:53:48,072 - use_cached_probe = False +2026-06-24 04:53:48,072 - use_cached_pos = False +2026-06-24 04:53:48,072 - +2026-06-24 04:53:48,072 - ### Initializing measurements ### +2026-06-24 04:53:48,072 - Loading measurements from source = 'file' +2026-06-24 04:53:48,072 - Detected measurement file type = '.h5' +2026-06-24 04:53:48,150 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 04:53:48,150 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 04:53:48,152 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0041) +2026-06-24 04:53:48,152 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 04:53:48,152 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 04:53:48,153 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:53:48,153 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 04:53:48,154 - Normalizing by max of the 2D mean pattern intensity: 0.003002 +2026-06-24 04:53:48,154 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 04:53:48,156 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0203, 1.3810) +2026-06-24 04:53:48,156 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 04:53:48,157 - Pattern total int. statistics (min, mean, max) = (330.8300, 332.7341, 334.6193), with min/max = 98.9% +2026-06-24 04:53:48,159 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0203, 1.3810) +2026-06-24 04:53:48,159 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 04:53:48,159 - +2026-06-24 04:53:48,159 - ### Setting up calibration ### +2026-06-24 04:53:48,159 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 04:53:48,159 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 04:53:48,159 - Radius of fitted bright field disk (RBF) = 10.16 px with meas_Npix = 128 +2026-06-24 04:53:48,159 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1587 +2026-06-24 04:53:48,159 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 04:53:48,159 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 04:53:48,381 - Initial guess: center=(63.63, 63.61), radius=10.16, Gaussian blur std=0.50 +2026-06-24 04:53:48,394 - Final fit: center=(63.63, 63.61), radius=10.16, Gaussian blur std=0.62 +2026-06-24 04:53:48,394 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.25 px with Npix = 128 +2026-06-24 04:53:48,394 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 04:53:48,394 - +2026-06-24 04:53:48,394 - ### Setting init_variables dict ### +2026-06-24 04:53:48,394 - Derived values given input init_params: +2026-06-24 04:53:48,394 - kv = 200.0 kV +2026-06-24 04:53:48,394 - wavelength = 0.0251 Ang +2026-06-24 04:53:48,394 - conv_angle = 10.042913436889648 mrad +2026-06-24 04:53:48,394 - Npix = 128 px +2026-06-24 04:53:48,394 - dk = 0.0391 Ang^-1 +2026-06-24 04:53:48,394 - kMax = 2.5000 Ang^-1 +2026-06-24 04:53:48,394 - da = 0.9797 mrad +2026-06-24 04:53:48,394 - angleMax = 62.6984 mrad +2026-06-24 04:53:48,394 - RBF = 10.2514 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 04:53:48,394 - n_alpha = 6.2430 (# conv_angle) +2026-06-24 04:53:48,394 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:53:48,394 - Rayleigh-limited resolution = 1.5233 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:53:48,394 - Real space probe extent = 25.6000 Ang +2026-06-24 04:53:48,394 - +2026-06-24 04:53:48,394 - ### Initializing probe ### +2026-06-24 04:53:48,394 - Loading probe from source = 'simu' +2026-06-24 04:53:48,394 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 04:53:48,395 - Start simulating STEM probe +2026-06-24 04:53:48,395 - kv = 200.0 kV +2026-06-24 04:53:48,395 - wavelength = 0.0251 Ang +2026-06-24 04:53:48,395 - conv_angle = 10.042913436889648 mrad +2026-06-24 04:53:48,395 - Npix = 128 px +2026-06-24 04:53:48,395 - dk = 0.0391 Ang^-1 +2026-06-24 04:53:48,395 - kMax = 2.5000 Ang^-1 +2026-06-24 04:53:48,395 - alpha_max = 62.6984 mrad +2026-06-24 04:53:48,395 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 04:53:48,395 - Rayleigh-limited resolution = 1.5233 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 04:53:48,395 - Real space probe extent = 25.6000 Ang +2026-06-24 04:53:48,395 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 04:53:48,395 - ------------------------------------------------------------------------------------ +2026-06-24 04:53:48,395 - C1,0 C1 -424.1490 - Defocus (C10 = -df) +2026-06-24 04:53:48,395 - C1,2 A1 -48.2260 61.98 2-fold astigmatism +2026-06-24 04:53:48,395 - C2,1 3*B2 -774.5850 102.37 Axial coma +2026-06-24 04:53:48,395 - C2,3 A2 946.5930 158.21 3-fold astigmatism +2026-06-24 04:53:48,395 - C3,0 C3 10673077.0000 - Spherical aberration +2026-06-24 04:53:48,395 - C3,2 4*S3 7044.5380 21.07 Axial star aberration +2026-06-24 04:53:48,395 - C3,4 A3 -4829.7870 198.60 4-fold astigmatism +2026-06-24 04:53:48,395 - C4,1 4*B4 238209.1250 138.20 Axial coma(4th) +2026-06-24 04:53:48,395 - C4,3 4*D4 247782.4380 18.86 3-lobe aberration +2026-06-24 04:53:48,395 - C4,5 A4 370824.7500 269.02 5-fold astigmatism +2026-06-24 04:53:48,395 - C5,0 C5 2281911.5000 - Spherical aberration (5th) +2026-06-24 04:53:48,395 - C5,2 6*S5 -10411431.0000 49.76 Axial star aberration(5th) +2026-06-24 04:53:48,395 - C5,4 6*R5 2667136.2500 108.67 4-lobe aberration +2026-06-24 04:53:48,395 - C5,6 A5 -3126392.0000 48.10 6-fold astigmatism +2026-06-24 04:53:48,398 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 04:53:48,398 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 04:53:48,398 - Creating 5 new probe modes from the major mode +2026-06-24 04:53:48,398 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 04:53:48,501 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 04:53:48,502 - Orthogonalizing 6 pmodes +2026-06-24 04:53:48,504 - Sorting 6 pmodes by their intensities +2026-06-24 04:53:48,504 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 04:53:48,505 - sum(|probe_data|**2) = 332.73, while meas_total_ints (min, mean, max) = (330.8300, 332.7341, 334.6193) +2026-06-24 04:53:48,505 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 04:53:48,505 - +2026-06-24 04:53:48,505 - ### Initializing probe positions ### +2026-06-24 04:53:48,505 - Loading probe positions from source = 'simu' +2026-06-24 04:53:48,505 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 04:53:48,505 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 04:53:48,506 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 04:53:48,508 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 04:53:48,508 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 04:53:48,508 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 04:53:48,508 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 04:53:48,508 - +2026-06-24 04:53:48,508 - ### Initializing object ### +2026-06-24 04:53:48,508 - Loading object from source = 'simu' +2026-06-24 04:53:48,508 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 04:53:48,509 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 04:53:48,510 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 04:53:48,510 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 04:53:48,510 - +2026-06-24 04:53:48,510 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 04:53:48,510 - omode_occu (omode) = float32, (1,) +2026-06-24 04:53:48,510 - +2026-06-24 04:53:48,510 - ### Initializing H (Fresnel propagator) ### +2026-06-24 04:53:48,510 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 04:53:48,511 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 04:53:48,511 - +2026-06-24 04:53:48,511 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 04:53:48,511 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 04:53:48,511 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 04:53:48,511 - +2026-06-24 04:53:48,511 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 04:53:48,511 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 04:53:48,511 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 04:53:48,511 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 04:53:48,511 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 04:53:48,511 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 04:53:48,511 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 04:53:48,511 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 04:53:48,511 - +2026-06-24 04:53:48,511 - ### Collecting reconstruction provenance ### +2026-06-24 04:53:48,511 - Reconstruction provenance is collected and initialized. +2026-06-24 04:53:48,511 - +2026-06-24 04:53:48,511 - ### Initializing loss function ### +2026-06-24 04:53:48,511 - Active loss types: +2026-06-24 04:53:48,511 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 04:53:48,512 - +2026-06-24 04:53:48,512 - ### Initializing constraint function ### +2026-06-24 04:53:48,512 - Active constraint types: +2026-06-24 04:53:48,512 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:53:48,512 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 04:53:48,512 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 04:53:48,512 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 04:53:48,512 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 04:53:48,512 - +2026-06-24 04:53:48,512 - ### Done initializing PtyRADSolver ### +2026-06-24 04:53:48,512 - +2026-06-24 04:53:48,641 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 04:53:48,641 - +2026-06-24 04:53:48,641 - ### Initializing PtychoModel model ### +2026-06-24 04:53:48,713 - ### PtychoModel optimizable variables ### +2026-06-24 04:53:48,713 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:53:48,713 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:53:48,713 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:53:48,713 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 04:53:48,713 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 04:53:48,713 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 04:53:48,713 - +2026-06-24 04:53:48,713 - ### Optimizable variables statitsics ### +2026-06-24 04:53:48,713 - Total measurement values : 4,194,304 +2026-06-24 04:53:48,713 - Total optimizing variables: 278,728 +2026-06-24 04:53:48,713 - Overdetermined ratio : 15.05 +2026-06-24 04:53:48,713 - +2026-06-24 04:53:48,713 - ### Model behavior ### +2026-06-24 04:53:48,713 - Tilt propagator : False +2026-06-24 04:53:48,713 - Change slice thickness : False +2026-06-24 04:53:48,713 - Detector blur : False +2026-06-24 04:53:48,713 - Preload data : True +2026-06-24 04:53:48,713 - On-the-fly meas padding : False +2026-06-24 04:53:48,713 - On-the-fly meas resample : False +2026-06-24 04:53:48,714 - On-the-fly simu match mode: None +2026-06-24 04:53:48,714 - +2026-06-24 04:53:48,755 - ### Done initializing PtychoModel model ### +2026-06-24 04:53:48,755 - +2026-06-24 04:53:48,755 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 04:53:48,756 - +2026-06-24 04:53:48,756 - ### Generating indices, batches, and output_path ### +2026-06-24 04:53:48,757 - d90 = 55.000 px or 11.000 Ang +2026-06-24 04:53:48,757 - Selecting indices with the 'full' mode +2026-06-24 04:53:49,218 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 04:53:49,295 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 04:53:49,295 - Original recon_dir_affixes = ['default'] +2026-06-24 04:53:49,295 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 04:53:49,302 - Path corrected for compatibility: +2026-06-24 04:53:49,302 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi32_21.1_C34_-4.83e+03_phi34_199_C41_2.38e+05_phi41_138_C43_2.48e+05_phi43_18.9_C45_3.71e+05_phi45_269_C50_2.28e+06_C52_-1.04e+07_phi52_49.8_C54_2.67e+06_phi54_109_C56_-3.13e+06_phi56_48.1 +2026-06-24 04:53:49,302 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1 +2026-06-24 04:53:49,303 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1' is generated! +2026-06-24 04:53:49,455 - +2026-06-24 04:53:49,456 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/20260624_045349_ptyrad_log.txt ### +2026-06-24 04:53:49,456 - +2026-06-24 04:53:49,458 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 04:53:49,458 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 04:53:49,458 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 04:53:50,655 - Iter: 1, Total Loss: 0.9173, loss_single: 0.9173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.436 sec +2026-06-24 04:53:50,691 - Iter: 2, Total Loss: 0.8652, loss_single: 0.8652, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:53:50,727 - Iter: 3, Total Loss: 0.8234, loss_single: 0.8234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,762 - Iter: 4, Total Loss: 0.7851, loss_single: 0.7851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,798 - Iter: 5, Total Loss: 0.7464, loss_single: 0.7464, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 04:53:50,833 - Iter: 6, Total Loss: 0.7174, loss_single: 0.7174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,869 - Iter: 7, Total Loss: 0.6919, loss_single: 0.6919, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,904 - Iter: 8, Total Loss: 0.6615, loss_single: 0.6615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,940 - Iter: 9, Total Loss: 0.6327, loss_single: 0.6327, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:50,976 - Iter: 10, Total Loss: 0.6013, loss_single: 0.6013, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,011 - Iter: 11, Total Loss: 0.5756, loss_single: 0.5756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,047 - Iter: 12, Total Loss: 0.5568, loss_single: 0.5568, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,082 - Iter: 13, Total Loss: 0.5377, loss_single: 0.5377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,118 - Iter: 14, Total Loss: 0.5173, loss_single: 0.5173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,153 - Iter: 15, Total Loss: 0.4969, loss_single: 0.4969, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,188 - Iter: 16, Total Loss: 0.4776, loss_single: 0.4776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:51,224 - 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Iter: 89, Total Loss: 0.3399, loss_single: 0.3399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:53,813 - Iter: 90, Total Loss: 0.3396, loss_single: 0.3396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:53,850 - Iter: 91, Total Loss: 0.3392, loss_single: 0.3392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 04:53:53,885 - Iter: 92, Total Loss: 0.3387, loss_single: 0.3387, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:53,921 - Iter: 93, Total Loss: 0.3383, loss_single: 0.3383, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:53,956 - Iter: 94, Total Loss: 0.3379, loss_single: 0.3379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:53,991 - Iter: 95, Total Loss: 0.3375, loss_single: 0.3375, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,027 - Iter: 96, Total Loss: 0.3371, loss_single: 0.3371, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,062 - Iter: 97, Total Loss: 0.3367, loss_single: 0.3367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,097 - Iter: 98, Total Loss: 0.3363, loss_single: 0.3363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,132 - Iter: 99, Total Loss: 0.3358, loss_single: 0.3358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,168 - Iter: 100, Total Loss: 0.3352, loss_single: 0.3352, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 04:53:54,280 - Saving summary figures for iter 100 +2026-06-24 04:53:57,841 - ### Finished 100 iterations, averaged iter_t = 0.038985 with std = 0.040 ### +2026-06-24 04:53:57,841 - +2026-06-24 04:53:57,841 - ### The PtyRADSolver is finished in 9.200 sec ### +2026-06-24 04:53:57,841 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..06d1465b11812f6f2ff9517100e0f254b066e9ee Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/simulation_data9__sample_000029.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/simulation_data9__sample_000029.yaml new file mode 100644 index 0000000000000000000000000000000000000000..00e0949ad2c6cf36e68df854a4ba1916b413643e --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029/gendata3_std_02__simulation_data9__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-424_C12_-48.2_phi12_62_C21_-775_phi21_102_C23_947_phi23_158_C30_1.07e+07_C32_7.04e+03_phi.1/simulation_data9__sample_000029.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 10.042913436889648 + probe_aberrations: + C10: -424.1494445800781 + C12: -48.22585678100586 + C21: -774.585205078125 + C23: 946.5927734375 + C30: 10673077.0 + C32: 7044.5380859375 + C34: -4829.787109375 + C41: 238209.125 + C43: 247782.4375 + C45: 370824.75 + C50: 2281911.5 + C52: -10411431.0 + C54: 2667136.25 + C56: -3126392.0 + phi12: 61.97559290594328 + phi21: 102.36708452516176 + phi23: 158.21155129245392 + phi32: 21.065908494774277 + phi34: 198.5985554773877 + phi41: 138.2022115905781 + phi43: 18.855145307623108 + phi45: 269.0232836319335 + phi52: 49.757187028017945 + phi54: 108.66527026072221 + phi56: 48.100466588223405 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data9__sample_000029_measurement.h5 + key: measurement + random_seed: 20261680 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data9__sample_000029 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data9__sample_000029 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/20260624_050041_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/20260624_050041_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c120ea520d521db7299bcc5244daf66a4646f9a2 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/20260624_050041_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:00:40,133 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:00:40,133 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:00:40,133 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:00:40,133 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:00:40,133 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:00:40,133 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:00:40,133 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:00:40,133 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:00:40,133 - +2026-06-24 05:00:40,241 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:00:40,241 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:00:40,241 - Accelerator.num_process = 1 +2026-06-24 05:00:40,241 - Accelerator.mixed_precision = no +2026-06-24 05:00:40,251 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:00:40,251 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:00:40,251 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:00:40,251 - +2026-06-24 05:00:40,252 - ### System information ### +2026-06-24 05:00:40,252 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:00:40,252 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:00:40,252 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:00:40,252 - Machine: x86_64 +2026-06-24 05:00:40,252 - Processor: x86_64 +2026-06-24 05:00:40,252 - Available CPU cores: 8 +2026-06-24 05:00:40,252 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:00:40,252 - +2026-06-24 05:00:40,252 - ### GPU information ### +2026-06-24 05:00:40,252 - CUDA Available: True +2026-06-24 05:00:40,252 - CUDA Version: 13.0 +2026-06-24 05:00:40,252 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:00:40,253 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:00:40,253 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:00:40,253 - In addition, Triton does not directly support Windows. +2026-06-24 05:00:40,253 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:00:40,267 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:00:40,267 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:00:40,267 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:00:40,267 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:00:40,267 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:00:40,268 - +2026-06-24 05:00:40,268 - ### Python information ### +2026-06-24 05:00:40,269 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:00:40,269 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:00:40,269 - +2026-06-24 05:00:40,269 - ### Packages information ### +2026-06-24 05:00:40,269 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:00:40,270 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:00:40,271 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:00:40,271 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:00:40,272 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:00:40,272 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:00:40,272 - +2026-06-24 05:00:40,272 - ### Loading params file ### +2026-06-24 05:00:40,272 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug10__sample_000023.yaml +2026-06-24 05:00:40,279 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:00:40,280 - Success! Params file validated and defaults applied. +2026-06-24 05:00:40,280 - +2026-06-24 05:00:40,280 - ### Setting GPU Device ### +2026-06-24 05:00:40,280 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:00:40,280 - +2026-06-24 05:00:40,280 - Random seed: 20261708 provided by params file +2026-06-24 05:00:40,280 - ### Initializing Initializer ### +2026-06-24 05:00:40,280 - init_params are displayed below: +2026-06-24 05:00:40,281 - random_seed: 20261708 +2026-06-24 05:00:40,281 - probe_illum_type: electron +2026-06-24 05:00:40,281 - probe_kv: 200.0 +2026-06-24 05:00:40,281 - probe_conv_angle: 10.274909019470215 +2026-06-24 05:00:40,281 - probe_aberrations: {'C10': -375.293, 'C12': 3.026, 'phi12': 89.859, 'C21': -828.693, 'phi21': 8.159, 'C23': 777.267, 'phi23': 296.771, 'C30': 10915388.0, 'C32': 8852.924, 'phi32': 187.621, 'C34': 1545.814, 'phi34': 291.97, 'C41': 457526.969, 'phi41': 75.077, 'C43': -11435.985, 'phi43': 238.164, 'C45': 353617.875, 'phi45': 337.024, 'C50': 12157433.0, 'C52': 12110364.0, 'phi52': 338.54, 'C54': 17628498.0, 'phi54': 270.617, 'C56': 10617607.0, 'phi56': 195.02} +2026-06-24 05:00:40,281 - beam_kev: None +2026-06-24 05:00:40,281 - probe_dRn: None +2026-06-24 05:00:40,281 - probe_Rn: None +2026-06-24 05:00:40,281 - probe_D_H: None +2026-06-24 05:00:40,281 - probe_D_FZP: None +2026-06-24 05:00:40,281 - probe_Ls: None +2026-06-24 05:00:40,281 - meas_Npix: 128 +2026-06-24 05:00:40,281 - pos_N_scans: 256 +2026-06-24 05:00:40,281 - pos_N_scan_slow: 16 +2026-06-24 05:00:40,281 - pos_N_scan_fast: 16 +2026-06-24 05:00:40,281 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:00:40,281 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:00:40,281 - probe_pmode_max: 6 +2026-06-24 05:00:40,281 - probe_pmode_init_pows: [0.02] +2026-06-24 05:00:40,281 - obj_omode_max: 1 +2026-06-24 05:00:40,281 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:00:40,281 - obj_Nlayer: 1 +2026-06-24 05:00:40,281 - obj_slice_thickness: 20.0 +2026-06-24 05:00:40,281 - simu_Npix: None +2026-06-24 05:00:40,281 - simu_match_mode: None +2026-06-24 05:00:40,281 - meas_permute: None +2026-06-24 05:00:40,281 - meas_reshape: [256, 128, 128] +2026-06-24 05:00:40,281 - meas_flipT: [0, 0, 0] +2026-06-24 05:00:40,281 - meas_crop: None +2026-06-24 05:00:40,281 - meas_pad: None +2026-06-24 05:00:40,281 - meas_resample: None +2026-06-24 05:00:40,282 - meas_add_source_size: None +2026-06-24 05:00:40,282 - meas_add_detector_blur: None +2026-06-24 05:00:40,282 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:00:40,282 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:00:40,282 - meas_add_poisson_noise: None +2026-06-24 05:00:40,282 - meas_export: None +2026-06-24 05:00:40,282 - probe_permute: None +2026-06-24 05:00:40,282 - probe_z_shift: None +2026-06-24 05:00:40,282 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:00:40,282 - pos_scan_flipT: None +2026-06-24 05:00:40,282 - pos_scan_affine: None +2026-06-24 05:00:40,282 - pos_scan_rand_std: 0.15 +2026-06-24 05:00:40,282 - obj_z_crop: None +2026-06-24 05:00:40,282 - obj_z_pad: None +2026-06-24 05:00:40,282 - obj_z_resample: None +2026-06-24 05:00:40,282 - meas_source: file +2026-06-24 05:00:40,282 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug10__sample_000023_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:00:40,282 - probe_source: simu +2026-06-24 05:00:40,282 - probe_params: None +2026-06-24 05:00:40,282 - pos_source: simu +2026-06-24 05:00:40,282 - pos_params: None +2026-06-24 05:00:40,282 - obj_source: simu +2026-06-24 05:00:40,282 - obj_params: None +2026-06-24 05:00:40,282 - tilt_source: simu +2026-06-24 05:00:40,282 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:00:40,282 - +2026-06-24 05:00:40,282 - ### Initializing cache ### +2026-06-24 05:00:40,282 - use_cached_obj = False +2026-06-24 05:00:40,282 - use_cached_probe = False +2026-06-24 05:00:40,282 - use_cached_pos = False +2026-06-24 05:00:40,282 - +2026-06-24 05:00:40,282 - ### Initializing measurements ### +2026-06-24 05:00:40,282 - Loading measurements from source = 'file' +2026-06-24 05:00:40,282 - Detected measurement file type = '.h5' +2026-06-24 05:00:40,357 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:00:40,357 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:00:40,359 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0039) +2026-06-24 05:00:40,359 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:00:40,359 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:00:40,360 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:00:40,360 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:00:40,361 - Normalizing by max of the 2D mean pattern intensity: 0.0029488096 +2026-06-24 05:00:40,361 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:00:40,362 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0207, 1.3075) +2026-06-24 05:00:40,363 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:00:40,364 - Pattern total int. statistics (min, mean, max) = (337.5975, 339.1925, 341.0348), with min/max = 99.0% +2026-06-24 05:00:40,366 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0207, 1.3075) +2026-06-24 05:00:40,366 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:00:40,366 - +2026-06-24 05:00:40,366 - ### Setting up calibration ### +2026-06-24 05:00:40,366 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:00:40,366 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:00:40,366 - Radius of fitted bright field disk (RBF) = 10.36 px with meas_Npix = 128 +2026-06-24 05:00:40,366 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1618 +2026-06-24 05:00:40,366 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:00:40,366 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:00:40,587 - Initial guess: center=(63.63, 63.62), radius=10.36, Gaussian blur std=0.50 +2026-06-24 05:00:40,595 - Final fit: center=(63.63, 63.62), radius=10.36, Gaussian blur std=0.53 +2026-06-24 05:00:40,595 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.49 px with Npix = 128 +2026-06-24 05:00:40,595 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:00:40,595 - +2026-06-24 05:00:40,595 - ### Setting init_variables dict ### +2026-06-24 05:00:40,595 - Derived values given input init_params: +2026-06-24 05:00:40,595 - kv = 200.0 kV +2026-06-24 05:00:40,595 - wavelength = 0.0251 Ang +2026-06-24 05:00:40,595 - conv_angle = 10.274909019470215 mrad +2026-06-24 05:00:40,595 - Npix = 128 px +2026-06-24 05:00:40,596 - dk = 0.0391 Ang^-1 +2026-06-24 05:00:40,596 - kMax = 2.5000 Ang^-1 +2026-06-24 05:00:40,596 - da = 0.9797 mrad +2026-06-24 05:00:40,596 - angleMax = 62.6984 mrad +2026-06-24 05:00:40,596 - RBF = 10.4882 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:00:40,596 - n_alpha = 6.1021 (# conv_angle) +2026-06-24 05:00:40,596 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:00:40,596 - Rayleigh-limited resolution = 1.4889 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:00:40,596 - Real space probe extent = 25.6000 Ang +2026-06-24 05:00:40,596 - +2026-06-24 05:00:40,596 - ### Initializing probe ### +2026-06-24 05:00:40,596 - Loading probe from source = 'simu' +2026-06-24 05:00:40,596 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:00:40,596 - Start simulating STEM probe +2026-06-24 05:00:40,596 - kv = 200.0 kV +2026-06-24 05:00:40,596 - wavelength = 0.0251 Ang +2026-06-24 05:00:40,596 - conv_angle = 10.274909019470215 mrad +2026-06-24 05:00:40,596 - Npix = 128 px +2026-06-24 05:00:40,596 - dk = 0.0391 Ang^-1 +2026-06-24 05:00:40,596 - kMax = 2.5000 Ang^-1 +2026-06-24 05:00:40,596 - alpha_max = 62.6984 mrad +2026-06-24 05:00:40,596 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:00:40,596 - Rayleigh-limited resolution = 1.4889 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:00:40,596 - Real space probe extent = 25.6000 Ang +2026-06-24 05:00:40,597 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:00:40,597 - ----------------------------------------------------------------------------------- +2026-06-24 05:00:40,597 - C1,0 C1 -375.2930 - Defocus (C10 = -df) +2026-06-24 05:00:40,597 - C1,2 A1 3.0260 89.86 2-fold astigmatism +2026-06-24 05:00:40,597 - C2,1 3*B2 -828.6930 8.16 Axial coma +2026-06-24 05:00:40,597 - C2,3 A2 777.2670 296.77 3-fold astigmatism +2026-06-24 05:00:40,597 - C3,0 C3 10915388.0000 - Spherical aberration +2026-06-24 05:00:40,597 - C3,2 4*S3 8852.9240 187.62 Axial star aberration +2026-06-24 05:00:40,597 - C3,4 A3 1545.8140 291.97 4-fold astigmatism +2026-06-24 05:00:40,597 - C4,1 4*B4 457526.9690 75.08 Axial coma(4th) +2026-06-24 05:00:40,597 - C4,3 4*D4 -11435.9850 238.16 3-lobe aberration +2026-06-24 05:00:40,597 - C4,5 A4 353617.8750 337.02 5-fold astigmatism +2026-06-24 05:00:40,597 - C5,0 C5 12157433.0000 - Spherical aberration (5th) +2026-06-24 05:00:40,597 - C5,2 6*S5 12110364.0000 338.54 Axial star aberration(5th) +2026-06-24 05:00:40,597 - C5,4 6*R5 17628498.0000 270.62 4-lobe aberration +2026-06-24 05:00:40,597 - C5,6 A5 10617607.0000 195.02 6-fold astigmatism +2026-06-24 05:00:40,600 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:00:40,600 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:00:40,600 - Creating 5 new probe modes from the major mode +2026-06-24 05:00:40,600 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:00:40,696 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:00:40,697 - Orthogonalizing 6 pmodes +2026-06-24 05:00:40,700 - Sorting 6 pmodes by their intensities +2026-06-24 05:00:40,700 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:00:40,701 - sum(|probe_data|**2) = 339.19, while meas_total_ints (min, mean, max) = (337.5975, 339.1925, 341.0348) +2026-06-24 05:00:40,701 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:00:40,701 - +2026-06-24 05:00:40,701 - ### Initializing probe positions ### +2026-06-24 05:00:40,701 - Loading probe positions from source = 'simu' +2026-06-24 05:00:40,701 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:00:40,701 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:00:40,701 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:00:40,703 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:00:40,704 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:00:40,704 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:00:40,704 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:00:40,704 - +2026-06-24 05:00:40,704 - ### Initializing object ### +2026-06-24 05:00:40,704 - Loading object from source = 'simu' +2026-06-24 05:00:40,704 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:00:40,706 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:00:40,706 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:00:40,706 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:00:40,706 - +2026-06-24 05:00:40,706 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:00:40,706 - omode_occu (omode) = float32, (1,) +2026-06-24 05:00:40,706 - +2026-06-24 05:00:40,706 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:00:40,706 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:00:40,707 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:00:40,707 - +2026-06-24 05:00:40,707 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:00:40,707 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:00:40,707 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:00:40,707 - +2026-06-24 05:00:40,707 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:00:40,707 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:00:40,707 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:00:40,707 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:00:40,707 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:00:40,707 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:00:40,707 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:00:40,707 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:00:40,707 - +2026-06-24 05:00:40,707 - ### Collecting reconstruction provenance ### +2026-06-24 05:00:40,708 - Reconstruction provenance is collected and initialized. +2026-06-24 05:00:40,708 - +2026-06-24 05:00:40,708 - ### Initializing loss function ### +2026-06-24 05:00:40,708 - Active loss types: +2026-06-24 05:00:40,708 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:00:40,708 - +2026-06-24 05:00:40,708 - ### Initializing constraint function ### +2026-06-24 05:00:40,708 - Active constraint types: +2026-06-24 05:00:40,708 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:00:40,708 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:00:40,708 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:00:40,708 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:00:40,708 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:00:40,708 - +2026-06-24 05:00:40,708 - ### Done initializing PtyRADSolver ### +2026-06-24 05:00:40,708 - +2026-06-24 05:00:40,840 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:00:40,840 - +2026-06-24 05:00:40,840 - ### Initializing PtychoModel model ### +2026-06-24 05:00:40,912 - ### PtychoModel optimizable variables ### +2026-06-24 05:00:40,912 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:00:40,912 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:00:40,912 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:00:40,912 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:00:40,912 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:00:40,912 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:00:40,912 - +2026-06-24 05:00:40,912 - ### Optimizable variables statitsics ### +2026-06-24 05:00:40,912 - Total measurement values : 4,194,304 +2026-06-24 05:00:40,913 - Total optimizing variables: 278,728 +2026-06-24 05:00:40,913 - Overdetermined ratio : 15.05 +2026-06-24 05:00:40,913 - +2026-06-24 05:00:40,913 - ### Model behavior ### +2026-06-24 05:00:40,913 - Tilt propagator : False +2026-06-24 05:00:40,913 - Change slice thickness : False +2026-06-24 05:00:40,913 - Detector blur : False +2026-06-24 05:00:40,913 - Preload data : True +2026-06-24 05:00:40,913 - On-the-fly meas padding : False +2026-06-24 05:00:40,913 - On-the-fly meas resample : False +2026-06-24 05:00:40,913 - On-the-fly simu match mode: None +2026-06-24 05:00:40,913 - +2026-06-24 05:00:40,954 - ### Done initializing PtychoModel model ### +2026-06-24 05:00:40,955 - +2026-06-24 05:00:40,955 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:00:40,955 - +2026-06-24 05:00:40,955 - ### Generating indices, batches, and output_path ### +2026-06-24 05:00:40,956 - d90 = 63.000 px or 12.600 Ang +2026-06-24 05:00:40,956 - Selecting indices with the 'full' mode +2026-06-24 05:00:41,420 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:00:41,497 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:00:41,497 - Original recon_dir_affixes = ['default'] +2026-06-24 05:00:41,497 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:00:41,504 - Path corrected for compatibility: +2026-06-24 05:00:41,504 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.09e+07_C32_8.85e+03_phi32_188_C34_1.55e+03_phi34_292_C41_4.58e+05_phi41_75.1_C43_-1.14e+04_phi43_238_C45_3.54e+05_phi45_337_C50_1.22e+07_C52_1.21e+07_phi52_339_C54_1.76e+07_phi54_271_C56_1.06e+07_phi56_195 +2026-06-24 05:00:41,504 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195 +2026-06-24 05:00:41,505 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195' is generated! +2026-06-24 05:00:41,658 - +2026-06-24 05:00:41,659 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/20260624_050041_ptyrad_log.txt ### +2026-06-24 05:00:41,659 - +2026-06-24 05:00:41,661 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:00:41,661 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:00:41,661 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:00:42,889 - Iter: 1, Total Loss: 0.9337, loss_single: 0.9337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.444 sec +2026-06-24 05:00:42,926 - Iter: 2, Total Loss: 0.8756, loss_single: 0.8756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:42,962 - Iter: 3, Total Loss: 0.8335, loss_single: 0.8335, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:42,998 - Iter: 4, Total Loss: 0.7932, loss_single: 0.7932, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,034 - Iter: 5, Total Loss: 0.7563, loss_single: 0.7563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,070 - Iter: 6, Total Loss: 0.7226, loss_single: 0.7226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,105 - Iter: 7, Total Loss: 0.6846, loss_single: 0.6846, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,141 - Iter: 8, Total Loss: 0.6483, loss_single: 0.6483, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,177 - Iter: 9, Total Loss: 0.6147, loss_single: 0.6147, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,213 - Iter: 10, Total Loss: 0.5843, loss_single: 0.5843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,248 - Iter: 11, Total Loss: 0.5559, loss_single: 0.5559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,284 - Iter: 12, Total Loss: 0.5269, loss_single: 0.5269, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,320 - Iter: 13, Total Loss: 0.5034, loss_single: 0.5034, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,356 - Iter: 14, Total Loss: 0.4824, loss_single: 0.4824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,391 - Iter: 15, Total Loss: 0.4622, loss_single: 0.4622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,427 - Iter: 16, Total Loss: 0.4447, loss_single: 0.4447, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,463 - Iter: 17, Total Loss: 0.4303, loss_single: 0.4303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,499 - Iter: 18, Total Loss: 0.4179, loss_single: 0.4179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,535 - Iter: 19, Total Loss: 0.4050, loss_single: 0.4050, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,570 - Iter: 20, Total Loss: 0.3952, loss_single: 0.3952, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,605 - Iter: 21, Total Loss: 0.3862, loss_single: 0.3862, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,641 - Iter: 22, Total Loss: 0.3743, loss_single: 0.3743, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,676 - Iter: 23, Total Loss: 0.3642, loss_single: 0.3642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,712 - Iter: 24, Total Loss: 0.3578, loss_single: 0.3578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,748 - Iter: 25, Total Loss: 0.3524, loss_single: 0.3524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,787 - Iter: 26, Total Loss: 0.3466, loss_single: 0.3466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:00:43,823 - Iter: 27, Total Loss: 0.3419, loss_single: 0.3419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,859 - Iter: 28, Total Loss: 0.3370, loss_single: 0.3370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,895 - Iter: 29, Total Loss: 0.3329, loss_single: 0.3329, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:43,931 - Iter: 30, Total Loss: 0.3306, loss_single: 0.3306, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:43,967 - Iter: 31, Total Loss: 0.3274, loss_single: 0.3274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,003 - Iter: 32, Total Loss: 0.3232, loss_single: 0.3232, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,039 - Iter: 33, Total Loss: 0.3202, loss_single: 0.3202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,075 - Iter: 34, Total Loss: 0.3183, loss_single: 0.3183, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,111 - Iter: 35, Total Loss: 0.3162, loss_single: 0.3162, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,147 - Iter: 36, Total Loss: 0.3146, loss_single: 0.3146, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,183 - Iter: 37, Total Loss: 0.3127, loss_single: 0.3127, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,218 - Iter: 38, Total Loss: 0.3104, loss_single: 0.3104, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,254 - Iter: 39, Total Loss: 0.3091, loss_single: 0.3091, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,290 - Iter: 40, Total Loss: 0.3083, loss_single: 0.3083, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,328 - Iter: 41, Total Loss: 0.3073, loss_single: 0.3073, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,363 - Iter: 42, Total Loss: 0.3063, loss_single: 0.3063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,399 - Iter: 43, Total Loss: 0.3050, loss_single: 0.3050, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,435 - Iter: 44, Total Loss: 0.3035, loss_single: 0.3035, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,471 - Iter: 45, Total Loss: 0.3027, loss_single: 0.3027, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,507 - Iter: 46, Total Loss: 0.3019, loss_single: 0.3019, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:44,543 - Iter: 47, Total Loss: 0.3009, loss_single: 0.3009, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,578 - Iter: 48, Total Loss: 0.2998, loss_single: 0.2998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,614 - Iter: 49, Total Loss: 0.2988, loss_single: 0.2988, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,649 - Iter: 50, Total Loss: 0.2978, loss_single: 0.2978, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,685 - Iter: 51, Total Loss: 0.2973, loss_single: 0.2973, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,720 - Iter: 52, Total Loss: 0.2967, loss_single: 0.2967, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,756 - Iter: 53, Total Loss: 0.2961, loss_single: 0.2961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,792 - Iter: 54, Total Loss: 0.2956, loss_single: 0.2956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,827 - Iter: 55, Total Loss: 0.2951, loss_single: 0.2951, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,863 - Iter: 56, Total Loss: 0.2945, loss_single: 0.2945, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,898 - Iter: 57, Total Loss: 0.2938, loss_single: 0.2938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,933 - Iter: 58, Total Loss: 0.2931, loss_single: 0.2931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:44,969 - Iter: 59, Total Loss: 0.2925, loss_single: 0.2925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,005 - Iter: 60, Total Loss: 0.2920, loss_single: 0.2920, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:45,040 - Iter: 61, Total Loss: 0.2916, loss_single: 0.2916, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,076 - Iter: 62, Total Loss: 0.2911, loss_single: 0.2911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,111 - Iter: 63, Total Loss: 0.2907, loss_single: 0.2907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,147 - Iter: 64, Total Loss: 0.2903, loss_single: 0.2903, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,182 - Iter: 65, Total Loss: 0.2898, loss_single: 0.2898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,218 - Iter: 66, Total Loss: 0.2894, loss_single: 0.2894, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,253 - Iter: 67, Total Loss: 0.2889, loss_single: 0.2889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,289 - Iter: 68, Total Loss: 0.2885, loss_single: 0.2885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:45,325 - Iter: 69, Total Loss: 0.2880, loss_single: 0.2880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,360 - Iter: 70, Total Loss: 0.2875, loss_single: 0.2875, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,395 - Iter: 71, Total Loss: 0.2871, loss_single: 0.2871, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,431 - Iter: 72, Total Loss: 0.2867, loss_single: 0.2867, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,467 - Iter: 73, Total Loss: 0.2864, loss_single: 0.2864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,502 - Iter: 74, Total Loss: 0.2859, loss_single: 0.2859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,537 - Iter: 75, Total Loss: 0.2856, loss_single: 0.2856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,573 - Iter: 76, Total Loss: 0.2852, loss_single: 0.2852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,608 - Iter: 77, Total Loss: 0.2850, loss_single: 0.2850, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,644 - Iter: 78, Total Loss: 0.2844, loss_single: 0.2844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,680 - Iter: 79, Total Loss: 0.2842, loss_single: 0.2842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,723 - Iter: 80, Total Loss: 0.2838, loss_single: 0.2838, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.043 sec +2026-06-24 05:00:45,759 - Iter: 81, Total Loss: 0.2834, loss_single: 0.2834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,794 - Iter: 82, Total Loss: 0.2831, loss_single: 0.2831, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,830 - Iter: 83, Total Loss: 0.2827, loss_single: 0.2827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,865 - Iter: 84, Total Loss: 0.2824, loss_single: 0.2824, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,901 - Iter: 85, Total Loss: 0.2821, loss_single: 0.2821, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:45,937 - Iter: 86, Total Loss: 0.2818, loss_single: 0.2818, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:45,972 - Iter: 87, Total Loss: 0.2816, loss_single: 0.2816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,007 - Iter: 88, Total Loss: 0.2812, loss_single: 0.2812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,042 - Iter: 89, Total Loss: 0.2809, loss_single: 0.2809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,078 - Iter: 90, Total Loss: 0.2806, loss_single: 0.2806, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,116 - Iter: 91, Total Loss: 0.2803, loss_single: 0.2803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:00:46,152 - Iter: 92, Total Loss: 0.2799, loss_single: 0.2799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:46,188 - Iter: 93, Total Loss: 0.2798, loss_single: 0.2798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,223 - Iter: 94, Total Loss: 0.2795, loss_single: 0.2795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,259 - Iter: 95, Total Loss: 0.2793, loss_single: 0.2793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:46,295 - Iter: 96, Total Loss: 0.2789, loss_single: 0.2789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,330 - Iter: 97, Total Loss: 0.2787, loss_single: 0.2787, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,366 - Iter: 98, Total Loss: 0.2784, loss_single: 0.2784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:46,402 - Iter: 99, Total Loss: 0.2782, loss_single: 0.2782, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:00:46,438 - Iter: 100, Total Loss: 0.2779, loss_single: 0.2779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:00:46,551 - Saving summary figures for iter 100 +2026-06-24 05:00:50,150 - ### Finished 100 iterations, averaged iter_t = 0.039484 with std = 0.041 ### +2026-06-24 05:00:50,150 - +2026-06-24 05:00:50,150 - ### The PtyRADSolver is finished in 9.310 sec ### +2026-06-24 05:00:50,150 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..59469ab8310f9894a4e152750d71036e7832800e Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/simulation_data_aug10__sample_000023.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/simulation_data_aug10__sample_000023.yaml new file mode 100644 index 0000000000000000000000000000000000000000..815c15abc1e07ec44aaef5787ae1e2128589d083 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023/gendata3_std_02__simulation_data_aug10__sample_000023_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-375_C12_3.03_phi12_89.9_C21_-829_phi21_8.16_C23_777_phi23_297_C30_1.0.06e+07_phi56_195/simulation_data_aug10__sample_000023.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 10.274909019470215 + probe_aberrations: + C10: -375.2925720214844 + C12: 3.0262248516082764 + C21: -828.6934204101562 + C23: 777.2671508789062 + C30: 10915388.0 + C32: 8852.923828125 + C34: 1545.814208984375 + C41: 457526.96875 + C43: -11435.9853515625 + C45: 353617.875 + C50: 12157433.0 + C52: 12110364.0 + C54: 17628498.0 + C56: 10617607.0 + phi12: 89.85887030565819 + phi21: 8.158618274897918 + phi23: 296.7713369464605 + phi32: 187.62099348107316 + phi34: 291.97031501658853 + phi41: 75.07689294164656 + phi43: 238.1644616410592 + phi45: 337.0236361405833 + phi52: 338.53966492875935 + phi54: 270.6172585389177 + phi56: 195.0200417862996 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug10__sample_000023_measurement.h5 + key: measurement + random_seed: 20261708 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug10__sample_000023 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug10__sample_000023 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/20260624_050652_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/20260624_050652_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fd48a6f8723c43378f52e195945673e103b33ab9 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/20260624_050652_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:06:51,032 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:06:51,032 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:06:51,032 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:06:51,032 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:06:51,032 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:06:51,033 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:06:51,033 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:06:51,033 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:06:51,033 - +2026-06-24 05:06:51,141 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:06:51,141 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:06:51,141 - Accelerator.num_process = 1 +2026-06-24 05:06:51,141 - Accelerator.mixed_precision = no +2026-06-24 05:06:51,151 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:06:51,152 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:06:51,152 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:06:51,152 - +2026-06-24 05:06:51,152 - ### System information ### +2026-06-24 05:06:51,152 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:06:51,152 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:06:51,152 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:06:51,152 - Machine: x86_64 +2026-06-24 05:06:51,152 - Processor: x86_64 +2026-06-24 05:06:51,152 - Available CPU cores: 8 +2026-06-24 05:06:51,152 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:06:51,152 - +2026-06-24 05:06:51,152 - ### GPU information ### +2026-06-24 05:06:51,152 - CUDA Available: True +2026-06-24 05:06:51,152 - CUDA Version: 13.0 +2026-06-24 05:06:51,153 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:06:51,153 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:06:51,153 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:06:51,153 - In addition, Triton does not directly support Windows. +2026-06-24 05:06:51,153 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:06:51,167 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:06:51,168 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:06:51,168 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:06:51,168 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:06:51,168 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:06:51,168 - +2026-06-24 05:06:51,168 - ### Python information ### +2026-06-24 05:06:51,170 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:06:51,170 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:06:51,170 - +2026-06-24 05:06:51,170 - ### Packages information ### +2026-06-24 05:06:51,170 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:06:51,171 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:06:51,172 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:06:51,172 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:06:51,173 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:06:51,173 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:06:51,173 - +2026-06-24 05:06:51,173 - ### Loading params file ### +2026-06-24 05:06:51,173 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug11__sample_000012.yaml +2026-06-24 05:06:51,179 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:06:51,180 - Success! Params file validated and defaults applied. +2026-06-24 05:06:51,181 - +2026-06-24 05:06:51,181 - ### Setting GPU Device ### +2026-06-24 05:06:51,181 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:06:51,181 - +2026-06-24 05:06:51,181 - Random seed: 20261733 provided by params file +2026-06-24 05:06:51,181 - ### Initializing Initializer ### +2026-06-24 05:06:51,181 - init_params are displayed below: +2026-06-24 05:06:51,181 - random_seed: 20261733 +2026-06-24 05:06:51,181 - probe_illum_type: electron +2026-06-24 05:06:51,181 - probe_kv: 200.0 +2026-06-24 05:06:51,181 - probe_conv_angle: 9.115277290344238 +2026-06-24 05:06:51,181 - probe_aberrations: {'C10': -304.567, 'C12': -14.93, 'phi12': 300.456, 'C21': -342.567, 'phi21': 207.367, 'C23': 472.433, 'phi23': 21.681, 'C30': 10807051.0, 'C32': -6358.936, 'phi32': 320.791, 'C34': -3662.159, 'phi34': 125.33, 'C41': 13287.549, 'phi41': 209.858, 'C43': -373145.656, 'phi43': 201.351, 'C45': 367775.812, 'phi45': 158.395, 'C50': -7332149.0, 'C52': 191209.547, 'phi52': 141.28, 'C54': 11798943.0, 'phi54': 101.813, 'C56': -11482549.0, 'phi56': 50.268} +2026-06-24 05:06:51,181 - beam_kev: None +2026-06-24 05:06:51,181 - probe_dRn: None +2026-06-24 05:06:51,181 - probe_Rn: None +2026-06-24 05:06:51,181 - probe_D_H: None +2026-06-24 05:06:51,182 - probe_D_FZP: None +2026-06-24 05:06:51,182 - probe_Ls: None +2026-06-24 05:06:51,182 - meas_Npix: 128 +2026-06-24 05:06:51,182 - pos_N_scans: 256 +2026-06-24 05:06:51,182 - pos_N_scan_slow: 16 +2026-06-24 05:06:51,182 - pos_N_scan_fast: 16 +2026-06-24 05:06:51,182 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:06:51,182 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:06:51,182 - probe_pmode_max: 6 +2026-06-24 05:06:51,182 - probe_pmode_init_pows: [0.02] +2026-06-24 05:06:51,182 - obj_omode_max: 1 +2026-06-24 05:06:51,182 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:06:51,182 - obj_Nlayer: 1 +2026-06-24 05:06:51,182 - obj_slice_thickness: 20.0 +2026-06-24 05:06:51,182 - simu_Npix: None +2026-06-24 05:06:51,182 - simu_match_mode: None +2026-06-24 05:06:51,182 - meas_permute: None +2026-06-24 05:06:51,182 - meas_reshape: [256, 128, 128] +2026-06-24 05:06:51,182 - meas_flipT: [0, 0, 0] +2026-06-24 05:06:51,182 - meas_crop: None +2026-06-24 05:06:51,182 - meas_pad: None +2026-06-24 05:06:51,182 - meas_resample: None +2026-06-24 05:06:51,182 - meas_add_source_size: None +2026-06-24 05:06:51,182 - meas_add_detector_blur: None +2026-06-24 05:06:51,182 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:06:51,182 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:06:51,182 - meas_add_poisson_noise: None +2026-06-24 05:06:51,182 - meas_export: None +2026-06-24 05:06:51,182 - probe_permute: None +2026-06-24 05:06:51,182 - probe_z_shift: None +2026-06-24 05:06:51,182 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:06:51,182 - pos_scan_flipT: None +2026-06-24 05:06:51,182 - pos_scan_affine: None +2026-06-24 05:06:51,182 - pos_scan_rand_std: 0.15 +2026-06-24 05:06:51,182 - obj_z_crop: None +2026-06-24 05:06:51,182 - obj_z_pad: None +2026-06-24 05:06:51,183 - obj_z_resample: None +2026-06-24 05:06:51,183 - meas_source: file +2026-06-24 05:06:51,183 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000012_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:06:51,183 - probe_source: simu +2026-06-24 05:06:51,183 - probe_params: None +2026-06-24 05:06:51,183 - pos_source: simu +2026-06-24 05:06:51,183 - pos_params: None +2026-06-24 05:06:51,183 - obj_source: simu +2026-06-24 05:06:51,183 - obj_params: None +2026-06-24 05:06:51,183 - tilt_source: simu +2026-06-24 05:06:51,183 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:06:51,183 - +2026-06-24 05:06:51,183 - ### Initializing cache ### +2026-06-24 05:06:51,183 - use_cached_obj = False +2026-06-24 05:06:51,183 - use_cached_probe = False +2026-06-24 05:06:51,183 - use_cached_pos = False +2026-06-24 05:06:51,183 - +2026-06-24 05:06:51,183 - ### Initializing measurements ### +2026-06-24 05:06:51,183 - Loading measurements from source = 'file' +2026-06-24 05:06:51,183 - Detected measurement file type = '.h5' +2026-06-24 05:06:51,258 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:06:51,258 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:06:51,260 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0050) +2026-06-24 05:06:51,260 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:06:51,260 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:06:51,261 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:06:51,261 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:06:51,262 - Normalizing by max of the 2D mean pattern intensity: 0.0035243703 +2026-06-24 05:06:51,262 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:06:51,264 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.4182) +2026-06-24 05:06:51,264 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:06:51,266 - Pattern total int. statistics (min, mean, max) = (279.3644, 283.6967, 286.4525), with min/max = 97.5% +2026-06-24 05:06:51,267 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.4182) +2026-06-24 05:06:51,267 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:06:51,267 - +2026-06-24 05:06:51,267 - ### Setting up calibration ### +2026-06-24 05:06:51,267 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:06:51,267 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:06:51,267 - Radius of fitted bright field disk (RBF) = 9.15 px with meas_Npix = 128 +2026-06-24 05:06:51,267 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1430 +2026-06-24 05:06:51,267 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:06:51,267 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:06:51,488 - Initial guess: center=(63.62, 63.63), radius=9.15, Gaussian blur std=0.50 +2026-06-24 05:06:51,496 - Final fit: center=(63.62, 63.63), radius=9.15, Gaussian blur std=0.53 +2026-06-24 05:06:51,496 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.30 px with Npix = 128 +2026-06-24 05:06:51,497 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:06:51,497 - +2026-06-24 05:06:51,497 - ### Setting init_variables dict ### +2026-06-24 05:06:51,497 - Derived values given input init_params: +2026-06-24 05:06:51,497 - kv = 200.0 kV +2026-06-24 05:06:51,497 - wavelength = 0.0251 Ang +2026-06-24 05:06:51,497 - conv_angle = 9.115277290344238 mrad +2026-06-24 05:06:51,497 - Npix = 128 px +2026-06-24 05:06:51,497 - dk = 0.0391 Ang^-1 +2026-06-24 05:06:51,497 - kMax = 2.5000 Ang^-1 +2026-06-24 05:06:51,497 - da = 0.9797 mrad +2026-06-24 05:06:51,497 - angleMax = 62.6984 mrad +2026-06-24 05:06:51,497 - RBF = 9.3045 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:06:51,497 - n_alpha = 6.8784 (# conv_angle) +2026-06-24 05:06:51,497 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:06:51,497 - Rayleigh-limited resolution = 1.6783 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:06:51,497 - Real space probe extent = 25.6000 Ang +2026-06-24 05:06:51,497 - +2026-06-24 05:06:51,497 - ### Initializing probe ### +2026-06-24 05:06:51,497 - Loading probe from source = 'simu' +2026-06-24 05:06:51,497 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:06:51,497 - Start simulating STEM probe +2026-06-24 05:06:51,497 - kv = 200.0 kV +2026-06-24 05:06:51,497 - wavelength = 0.0251 Ang +2026-06-24 05:06:51,497 - conv_angle = 9.115277290344238 mrad +2026-06-24 05:06:51,498 - Npix = 128 px +2026-06-24 05:06:51,498 - dk = 0.0391 Ang^-1 +2026-06-24 05:06:51,498 - kMax = 2.5000 Ang^-1 +2026-06-24 05:06:51,498 - alpha_max = 62.6984 mrad +2026-06-24 05:06:51,498 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:06:51,498 - Rayleigh-limited resolution = 1.6783 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:06:51,498 - Real space probe extent = 25.6000 Ang +2026-06-24 05:06:51,498 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:06:51,498 - ------------------------------------------------------------------------------------ +2026-06-24 05:06:51,498 - C1,0 C1 -304.5670 - Defocus (C10 = -df) +2026-06-24 05:06:51,498 - C1,2 A1 -14.9300 300.46 2-fold astigmatism +2026-06-24 05:06:51,498 - C2,1 3*B2 -342.5670 207.37 Axial coma +2026-06-24 05:06:51,498 - C2,3 A2 472.4330 21.68 3-fold astigmatism +2026-06-24 05:06:51,498 - C3,0 C3 10807051.0000 - Spherical aberration +2026-06-24 05:06:51,498 - C3,2 4*S3 -6358.9360 320.79 Axial star aberration +2026-06-24 05:06:51,498 - C3,4 A3 -3662.1590 125.33 4-fold astigmatism +2026-06-24 05:06:51,498 - C4,1 4*B4 13287.5490 209.86 Axial coma(4th) +2026-06-24 05:06:51,498 - C4,3 4*D4 -373145.6560 201.35 3-lobe aberration +2026-06-24 05:06:51,498 - C4,5 A4 367775.8120 158.40 5-fold astigmatism +2026-06-24 05:06:51,498 - C5,0 C5 -7332149.0000 - Spherical aberration (5th) +2026-06-24 05:06:51,498 - C5,2 6*S5 191209.5470 141.28 Axial star aberration(5th) +2026-06-24 05:06:51,498 - C5,4 6*R5 11798943.0000 101.81 4-lobe aberration +2026-06-24 05:06:51,498 - C5,6 A5 -11482549.0000 50.27 6-fold astigmatism +2026-06-24 05:06:51,501 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:06:51,501 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:06:51,501 - Creating 5 new probe modes from the major mode +2026-06-24 05:06:51,501 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:06:51,604 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:06:51,605 - Orthogonalizing 6 pmodes +2026-06-24 05:06:51,609 - Sorting 6 pmodes by their intensities +2026-06-24 05:06:51,609 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:06:51,610 - sum(|probe_data|**2) = 283.70, while meas_total_ints (min, mean, max) = (279.3644, 283.6967, 286.4525) +2026-06-24 05:06:51,610 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:06:51,610 - +2026-06-24 05:06:51,610 - ### Initializing probe positions ### +2026-06-24 05:06:51,610 - Loading probe positions from source = 'simu' +2026-06-24 05:06:51,610 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:06:51,610 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:06:51,610 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:06:51,612 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:06:51,612 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:06:51,612 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:06:51,613 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:06:51,613 - +2026-06-24 05:06:51,613 - ### Initializing object ### +2026-06-24 05:06:51,613 - Loading object from source = 'simu' +2026-06-24 05:06:51,613 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:06:51,614 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:06:51,614 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:06:51,614 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:06:51,614 - +2026-06-24 05:06:51,614 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:06:51,614 - omode_occu (omode) = float32, (1,) +2026-06-24 05:06:51,615 - +2026-06-24 05:06:51,615 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:06:51,615 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:06:51,615 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:06:51,615 - +2026-06-24 05:06:51,615 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:06:51,615 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:06:51,615 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:06:51,615 - +2026-06-24 05:06:51,615 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:06:51,615 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:06:51,616 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:06:51,616 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:06:51,616 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:06:51,616 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:06:51,616 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:06:51,616 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:06:51,616 - +2026-06-24 05:06:51,616 - ### Collecting reconstruction provenance ### +2026-06-24 05:06:51,616 - Reconstruction provenance is collected and initialized. +2026-06-24 05:06:51,616 - +2026-06-24 05:06:51,616 - ### Initializing loss function ### +2026-06-24 05:06:51,616 - Active loss types: +2026-06-24 05:06:51,616 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:06:51,616 - +2026-06-24 05:06:51,616 - ### Initializing constraint function ### +2026-06-24 05:06:51,616 - Active constraint types: +2026-06-24 05:06:51,616 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:06:51,616 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:06:51,616 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:06:51,616 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:06:51,616 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:06:51,617 - +2026-06-24 05:06:51,617 - ### Done initializing PtyRADSolver ### +2026-06-24 05:06:51,617 - +2026-06-24 05:06:51,741 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:06:51,741 - +2026-06-24 05:06:51,742 - ### Initializing PtychoModel model ### +2026-06-24 05:06:51,813 - ### PtychoModel optimizable variables ### +2026-06-24 05:06:51,813 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:06:51,813 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:06:51,813 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:06:51,813 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:06:51,813 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:06:51,813 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:06:51,813 - +2026-06-24 05:06:51,813 - ### Optimizable variables statitsics ### +2026-06-24 05:06:51,813 - Total measurement values : 4,194,304 +2026-06-24 05:06:51,813 - Total optimizing variables: 278,728 +2026-06-24 05:06:51,813 - Overdetermined ratio : 15.05 +2026-06-24 05:06:51,813 - +2026-06-24 05:06:51,813 - ### Model behavior ### +2026-06-24 05:06:51,813 - Tilt propagator : False +2026-06-24 05:06:51,813 - Change slice thickness : False +2026-06-24 05:06:51,813 - Detector blur : False +2026-06-24 05:06:51,813 - Preload data : True +2026-06-24 05:06:51,813 - On-the-fly meas padding : False +2026-06-24 05:06:51,813 - On-the-fly meas resample : False +2026-06-24 05:06:51,814 - On-the-fly simu match mode: None +2026-06-24 05:06:51,814 - +2026-06-24 05:06:51,855 - ### Done initializing PtychoModel model ### +2026-06-24 05:06:51,855 - +2026-06-24 05:06:51,855 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:06:51,856 - +2026-06-24 05:06:51,856 - ### Generating indices, batches, and output_path ### +2026-06-24 05:06:51,857 - d90 = 51.000 px or 10.200 Ang +2026-06-24 05:06:51,857 - Selecting indices with the 'full' mode +2026-06-24 05:06:52,312 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:06:52,393 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:06:52,393 - Original recon_dir_affixes = ['default'] +2026-06-24 05:06:52,393 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:06:52,400 - Path corrected for compatibility: +2026-06-24 05:06:52,400 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36e+03_phi32_321_C34_-3.66e+03_phi34_125_C41_1.33e+04_phi41_210_C43_-3.73e+05_phi43_201_C45_3.68e+05_phi45_158_C50_-7.33e+06_C52_1.91e+05_phi52_141_C54_1.18e+07_phi54_102_C56_-1.15e+07_phi56_50.3 +2026-06-24 05:06:52,400 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3 +2026-06-24 05:06:52,401 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3' is generated! +2026-06-24 05:06:52,556 - +2026-06-24 05:06:52,557 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/20260624_050652_ptyrad_log.txt ### +2026-06-24 05:06:52,557 - +2026-06-24 05:06:52,559 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:06:52,559 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:06:52,559 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:06:53,759 - Iter: 1, Total Loss: 1.1203, loss_single: 1.1203, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.438 sec +2026-06-24 05:06:53,797 - Iter: 2, Total Loss: 1.0780, loss_single: 1.0780, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:06:53,833 - Iter: 3, Total Loss: 1.0392, loss_single: 1.0392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:53,868 - Iter: 4, Total Loss: 1.0008, loss_single: 1.0008, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:53,904 - Iter: 5, Total Loss: 0.9704, loss_single: 0.9704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:53,939 - Iter: 6, Total Loss: 0.9394, loss_single: 0.9394, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:53,975 - Iter: 7, Total Loss: 0.9037, loss_single: 0.9037, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:54,011 - Iter: 8, Total Loss: 0.8656, loss_single: 0.8656, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,046 - Iter: 9, Total Loss: 0.8318, loss_single: 0.8318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,081 - Iter: 10, Total Loss: 0.8045, loss_single: 0.8045, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,117 - Iter: 11, Total Loss: 0.7789, loss_single: 0.7789, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,152 - Iter: 12, Total Loss: 0.7527, loss_single: 0.7527, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,188 - Iter: 13, Total Loss: 0.7293, loss_single: 0.7293, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,225 - Iter: 14, Total Loss: 0.7089, loss_single: 0.7089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:54,260 - Iter: 15, Total Loss: 0.6894, loss_single: 0.6894, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,309 - Iter: 16, Total Loss: 0.6738, loss_single: 0.6738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,345 - Iter: 17, Total Loss: 0.6604, loss_single: 0.6604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:54,381 - Iter: 18, Total Loss: 0.6482, loss_single: 0.6482, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,417 - Iter: 19, Total Loss: 0.6374, loss_single: 0.6374, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:54,452 - Iter: 20, Total Loss: 0.6277, loss_single: 0.6277, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,487 - Iter: 21, Total Loss: 0.6196, loss_single: 0.6196, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,523 - Iter: 22, Total Loss: 0.6136, loss_single: 0.6136, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,558 - Iter: 23, Total Loss: 0.6089, loss_single: 0.6089, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,593 - Iter: 24, Total Loss: 0.6046, loss_single: 0.6046, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,629 - Iter: 25, Total Loss: 0.6005, loss_single: 0.6005, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,665 - Iter: 26, Total Loss: 0.5976, loss_single: 0.5976, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,700 - Iter: 27, Total Loss: 0.5957, loss_single: 0.5957, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,736 - Iter: 28, Total Loss: 0.5940, loss_single: 0.5940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:54,771 - Iter: 29, Total Loss: 0.5923, loss_single: 0.5923, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,806 - Iter: 30, Total Loss: 0.5909, loss_single: 0.5909, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,842 - Iter: 31, Total Loss: 0.5897, loss_single: 0.5897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,881 - Iter: 32, Total Loss: 0.5888, loss_single: 0.5888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:06:54,917 - Iter: 33, Total Loss: 0.5881, loss_single: 0.5881, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,952 - Iter: 34, Total Loss: 0.5873, loss_single: 0.5873, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:54,988 - Iter: 35, Total Loss: 0.5864, loss_single: 0.5864, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:55,023 - Iter: 36, Total Loss: 0.5859, loss_single: 0.5859, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,058 - Iter: 37, Total Loss: 0.5854, loss_single: 0.5854, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,094 - Iter: 38, Total Loss: 0.5849, loss_single: 0.5849, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,129 - Iter: 39, Total Loss: 0.5843, loss_single: 0.5843, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,164 - Iter: 40, Total Loss: 0.5839, loss_single: 0.5839, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,202 - Iter: 41, Total Loss: 0.5835, loss_single: 0.5835, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,237 - Iter: 42, Total Loss: 0.5830, loss_single: 0.5830, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,273 - Iter: 43, Total Loss: 0.5825, loss_single: 0.5825, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:55,308 - Iter: 44, Total Loss: 0.5822, loss_single: 0.5822, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,344 - Iter: 45, Total Loss: 0.5819, loss_single: 0.5819, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,379 - Iter: 46, Total Loss: 0.5815, loss_single: 0.5815, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,415 - Iter: 47, Total Loss: 0.5812, loss_single: 0.5812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:55,451 - Iter: 48, Total Loss: 0.5808, loss_single: 0.5808, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,487 - Iter: 49, Total Loss: 0.5805, loss_single: 0.5805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:55,522 - Iter: 50, Total Loss: 0.5802, loss_single: 0.5802, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,557 - Iter: 51, Total Loss: 0.5800, loss_single: 0.5800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,592 - Iter: 52, Total Loss: 0.5798, loss_single: 0.5798, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,628 - Iter: 53, Total Loss: 0.5795, loss_single: 0.5795, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:55,663 - Iter: 54, Total Loss: 0.5793, loss_single: 0.5793, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,698 - Iter: 55, Total Loss: 0.5790, loss_single: 0.5790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,733 - Iter: 56, Total Loss: 0.5788, loss_single: 0.5788, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,768 - Iter: 57, Total Loss: 0.5785, loss_single: 0.5785, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,803 - Iter: 58, Total Loss: 0.5783, loss_single: 0.5783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,839 - Iter: 59, Total Loss: 0.5781, loss_single: 0.5781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,874 - Iter: 60, Total Loss: 0.5779, loss_single: 0.5779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,910 - Iter: 61, Total Loss: 0.5777, loss_single: 0.5777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,945 - Iter: 62, Total Loss: 0.5775, loss_single: 0.5775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:55,980 - Iter: 63, Total Loss: 0.5772, loss_single: 0.5772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,016 - Iter: 64, Total Loss: 0.5770, loss_single: 0.5770, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,051 - Iter: 65, Total Loss: 0.5768, loss_single: 0.5768, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,086 - Iter: 66, Total Loss: 0.5766, loss_single: 0.5766, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,121 - Iter: 67, Total Loss: 0.5764, loss_single: 0.5764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,156 - Iter: 68, Total Loss: 0.5762, loss_single: 0.5762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,192 - Iter: 69, Total Loss: 0.5760, loss_single: 0.5760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,227 - Iter: 70, Total Loss: 0.5758, loss_single: 0.5758, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,262 - Iter: 71, Total Loss: 0.5756, loss_single: 0.5756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,297 - Iter: 72, Total Loss: 0.5754, loss_single: 0.5754, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,332 - Iter: 73, Total Loss: 0.5752, loss_single: 0.5752, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,368 - Iter: 74, Total Loss: 0.5750, loss_single: 0.5750, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,403 - Iter: 75, Total Loss: 0.5748, loss_single: 0.5748, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,438 - Iter: 76, Total Loss: 0.5746, loss_single: 0.5746, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,473 - Iter: 77, Total Loss: 0.5744, loss_single: 0.5744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,509 - Iter: 78, Total Loss: 0.5742, loss_single: 0.5742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,544 - Iter: 79, Total Loss: 0.5740, loss_single: 0.5740, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,580 - Iter: 80, Total Loss: 0.5738, loss_single: 0.5738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,616 - Iter: 81, Total Loss: 0.5736, loss_single: 0.5736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:56,651 - Iter: 82, Total Loss: 0.5734, loss_single: 0.5734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,686 - Iter: 83, Total Loss: 0.5731, loss_single: 0.5731, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,721 - Iter: 84, Total Loss: 0.5730, loss_single: 0.5730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,757 - Iter: 85, Total Loss: 0.5728, loss_single: 0.5728, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,792 - Iter: 86, Total Loss: 0.5727, loss_single: 0.5727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,828 - Iter: 87, Total Loss: 0.5725, loss_single: 0.5725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,863 - Iter: 88, Total Loss: 0.5723, loss_single: 0.5723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,899 - Iter: 89, Total Loss: 0.5720, loss_single: 0.5720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,934 - Iter: 90, Total Loss: 0.5718, loss_single: 0.5718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:56,970 - Iter: 91, Total Loss: 0.5717, loss_single: 0.5717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,006 - Iter: 92, Total Loss: 0.5715, loss_single: 0.5715, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:06:57,043 - Iter: 93, Total Loss: 0.5713, loss_single: 0.5713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:06:57,079 - Iter: 94, Total Loss: 0.5712, loss_single: 0.5712, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,114 - Iter: 95, Total Loss: 0.5710, loss_single: 0.5710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,149 - Iter: 96, Total Loss: 0.5708, loss_single: 0.5708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,185 - Iter: 97, Total Loss: 0.5707, loss_single: 0.5707, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,220 - Iter: 98, Total Loss: 0.5706, loss_single: 0.5706, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,255 - Iter: 99, Total Loss: 0.5703, loss_single: 0.5703, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,290 - Iter: 100, Total Loss: 0.5701, loss_single: 0.5701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:06:57,401 - Saving summary figures for iter 100 +2026-06-24 05:07:00,994 - ### Finished 100 iterations, averaged iter_t = 0.039117 with std = 0.040 ### +2026-06-24 05:07:00,994 - +2026-06-24 05:07:00,994 - ### The PtyRADSolver is finished in 9.253 sec ### +2026-06-24 05:07:00,994 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..aaabfeb793ae87e55a50c1452977ba4c0fe8b0d7 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/simulation_data_aug11__sample_000012.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/simulation_data_aug11__sample_000012.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bc580f70f519cc8ae95f104cc5dda88b7367309c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012/gendata3_std_02__simulation_data_aug11__sample_000012_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-305_C12_-14.9_phi12_300_C21_-343_phi21_207_C23_472_phi23_21.7_C30_1.08e+07_C32_-6.36.3/simulation_data_aug11__sample_000012.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.115277290344238 + probe_aberrations: + C10: -304.5665588378906 + C12: -14.93049430847168 + C21: -342.5669250488281 + C23: 472.4331359863281 + C30: 10807051.0 + C32: -6358.93603515625 + C34: -3662.158935546875 + C41: 13287.548828125 + C43: -373145.65625 + C45: 367775.8125 + C50: -7332149.0 + C52: 191209.546875 + C54: 11798943.0 + C56: -11482549.0 + phi12: 300.45638792822245 + phi21: 207.367029390445 + phi23: 21.680564048372894 + phi32: 320.7908719553476 + phi34: 125.33028296758218 + phi41: 209.85786277696525 + phi43: 201.35072556193097 + phi45: 158.3953653433973 + phi52: 141.28037294382773 + phi54: 101.8128215042044 + phi56: 50.26838570625838 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000012_measurement.h5 + key: measurement + random_seed: 20261733 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000012 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug11__sample_000012 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/20260624_050805_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/20260624_050805_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b344a8ec82da8c987865d4f5fc00ad97466bcafe --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/20260624_050805_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:08:04,353 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:08:04,353 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:08:04,353 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:08:04,353 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:08:04,353 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:08:04,353 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:08:04,353 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:08:04,353 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:08:04,353 - +2026-06-24 05:08:04,464 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:08:04,464 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:08:04,464 - Accelerator.num_process = 1 +2026-06-24 05:08:04,464 - Accelerator.mixed_precision = no +2026-06-24 05:08:04,474 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:08:04,475 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:08:04,475 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:08:04,475 - +2026-06-24 05:08:04,475 - ### System information ### +2026-06-24 05:08:04,475 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:08:04,475 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:08:04,475 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:08:04,475 - Machine: x86_64 +2026-06-24 05:08:04,475 - Processor: x86_64 +2026-06-24 05:08:04,475 - Available CPU cores: 8 +2026-06-24 05:08:04,475 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:08:04,475 - +2026-06-24 05:08:04,475 - ### GPU information ### +2026-06-24 05:08:04,475 - CUDA Available: True +2026-06-24 05:08:04,475 - CUDA Version: 13.0 +2026-06-24 05:08:04,476 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:08:04,476 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:08:04,476 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:08:04,476 - In addition, Triton does not directly support Windows. +2026-06-24 05:08:04,476 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:08:04,491 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:08:04,491 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:08:04,491 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:08:04,491 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:08:04,491 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:08:04,491 - +2026-06-24 05:08:04,491 - ### Python information ### +2026-06-24 05:08:04,493 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:08:04,493 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:08:04,493 - +2026-06-24 05:08:04,493 - ### Packages information ### +2026-06-24 05:08:04,494 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:08:04,495 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:08:04,495 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:08:04,496 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:08:04,496 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:08:04,496 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:08:04,496 - +2026-06-24 05:08:04,497 - ### Loading params file ### +2026-06-24 05:08:04,497 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug11__sample_000017.yaml +2026-06-24 05:08:04,503 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:08:04,504 - Success! Params file validated and defaults applied. +2026-06-24 05:08:04,504 - +2026-06-24 05:08:04,504 - ### Setting GPU Device ### +2026-06-24 05:08:04,504 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:08:04,504 - +2026-06-24 05:08:04,504 - Random seed: 20261738 provided by params file +2026-06-24 05:08:04,505 - ### Initializing Initializer ### +2026-06-24 05:08:04,505 - init_params are displayed below: +2026-06-24 05:08:04,505 - random_seed: 20261738 +2026-06-24 05:08:04,505 - probe_illum_type: electron +2026-06-24 05:08:04,505 - probe_kv: 200.0 +2026-06-24 05:08:04,505 - probe_conv_angle: 9.856125831604004 +2026-06-24 05:08:04,505 - probe_aberrations: {'C10': -264.626, 'C12': 4.425, 'phi12': 17.825, 'C21': 713.569, 'phi21': 31.119, 'C23': -375.252, 'phi23': 110.019, 'C30': 10131374.0, 'C32': 4611.994, 'phi32': 167.819, 'C34': 8771.155, 'phi34': 201.876, 'C41': 56336.906, 'phi41': 154.735, 'C43': 28428.518, 'phi43': 249.575, 'C45': 335352.125, 'phi45': 142.898, 'C50': 5736675.5, 'C52': -7180388.5, 'phi52': 13.026, 'C54': 5166542.0, 'phi54': 14.011, 'C56': 4801067.5, 'phi56': 216.672} +2026-06-24 05:08:04,505 - beam_kev: None +2026-06-24 05:08:04,505 - probe_dRn: None +2026-06-24 05:08:04,505 - probe_Rn: None +2026-06-24 05:08:04,505 - probe_D_H: None +2026-06-24 05:08:04,505 - probe_D_FZP: None +2026-06-24 05:08:04,505 - probe_Ls: None +2026-06-24 05:08:04,505 - meas_Npix: 128 +2026-06-24 05:08:04,505 - pos_N_scans: 256 +2026-06-24 05:08:04,505 - pos_N_scan_slow: 16 +2026-06-24 05:08:04,505 - pos_N_scan_fast: 16 +2026-06-24 05:08:04,505 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:08:04,505 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:08:04,505 - probe_pmode_max: 6 +2026-06-24 05:08:04,505 - probe_pmode_init_pows: [0.02] +2026-06-24 05:08:04,505 - obj_omode_max: 1 +2026-06-24 05:08:04,505 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:08:04,505 - obj_Nlayer: 1 +2026-06-24 05:08:04,505 - obj_slice_thickness: 20.0 +2026-06-24 05:08:04,505 - simu_Npix: None +2026-06-24 05:08:04,505 - simu_match_mode: None +2026-06-24 05:08:04,505 - meas_permute: None +2026-06-24 05:08:04,505 - meas_reshape: [256, 128, 128] +2026-06-24 05:08:04,505 - meas_flipT: [0, 0, 0] +2026-06-24 05:08:04,505 - meas_crop: None +2026-06-24 05:08:04,505 - meas_pad: None +2026-06-24 05:08:04,506 - meas_resample: None +2026-06-24 05:08:04,506 - meas_add_source_size: None +2026-06-24 05:08:04,506 - meas_add_detector_blur: None +2026-06-24 05:08:04,506 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:08:04,506 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:08:04,506 - meas_add_poisson_noise: None +2026-06-24 05:08:04,506 - meas_export: None +2026-06-24 05:08:04,506 - probe_permute: None +2026-06-24 05:08:04,506 - probe_z_shift: None +2026-06-24 05:08:04,506 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:08:04,506 - pos_scan_flipT: None +2026-06-24 05:08:04,506 - pos_scan_affine: None +2026-06-24 05:08:04,506 - pos_scan_rand_std: 0.15 +2026-06-24 05:08:04,506 - obj_z_crop: None +2026-06-24 05:08:04,506 - obj_z_pad: None +2026-06-24 05:08:04,506 - obj_z_resample: None +2026-06-24 05:08:04,506 - meas_source: file +2026-06-24 05:08:04,506 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000017_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:08:04,506 - probe_source: simu +2026-06-24 05:08:04,506 - probe_params: None +2026-06-24 05:08:04,506 - pos_source: simu +2026-06-24 05:08:04,506 - pos_params: None +2026-06-24 05:08:04,506 - obj_source: simu +2026-06-24 05:08:04,506 - obj_params: None +2026-06-24 05:08:04,506 - tilt_source: simu +2026-06-24 05:08:04,506 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:08:04,506 - +2026-06-24 05:08:04,506 - ### Initializing cache ### +2026-06-24 05:08:04,506 - use_cached_obj = False +2026-06-24 05:08:04,506 - use_cached_probe = False +2026-06-24 05:08:04,506 - use_cached_pos = False +2026-06-24 05:08:04,506 - +2026-06-24 05:08:04,506 - ### Initializing measurements ### +2026-06-24 05:08:04,506 - Loading measurements from source = 'file' +2026-06-24 05:08:04,506 - Detected measurement file type = '.h5' +2026-06-24 05:08:04,584 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:08:04,584 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:08:04,586 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0043) +2026-06-24 05:08:04,586 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:08:04,586 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:08:04,587 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:08:04,587 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:08:04,587 - Normalizing by max of the 2D mean pattern intensity: 0.0031029438 +2026-06-24 05:08:04,588 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:08:04,589 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0196, 1.3995) +2026-06-24 05:08:04,590 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:08:04,591 - Pattern total int. statistics (min, mean, max) = (319.0837, 321.9215, 324.7194), with min/max = 98.3% +2026-06-24 05:08:04,592 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0196, 1.3995) +2026-06-24 05:08:04,592 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:08:04,592 - +2026-06-24 05:08:04,592 - ### Setting up calibration ### +2026-06-24 05:08:04,592 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:08:04,593 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:08:04,593 - Radius of fitted bright field disk (RBF) = 9.95 px with meas_Npix = 128 +2026-06-24 05:08:04,593 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1555 +2026-06-24 05:08:04,593 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:08:04,593 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:08:04,822 - Initial guess: center=(63.62, 63.64), radius=9.95, Gaussian blur std=0.50 +2026-06-24 05:08:04,835 - Final fit: center=(63.62, 63.64), radius=9.95, Gaussian blur std=0.70 +2026-06-24 05:08:04,835 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.06 px with Npix = 128 +2026-06-24 05:08:04,835 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:08:04,835 - +2026-06-24 05:08:04,835 - ### Setting init_variables dict ### +2026-06-24 05:08:04,835 - Derived values given input init_params: +2026-06-24 05:08:04,836 - kv = 200.0 kV +2026-06-24 05:08:04,836 - wavelength = 0.0251 Ang +2026-06-24 05:08:04,836 - conv_angle = 9.856125831604004 mrad +2026-06-24 05:08:04,836 - Npix = 128 px +2026-06-24 05:08:04,836 - dk = 0.0391 Ang^-1 +2026-06-24 05:08:04,836 - kMax = 2.5000 Ang^-1 +2026-06-24 05:08:04,836 - da = 0.9797 mrad +2026-06-24 05:08:04,836 - angleMax = 62.6984 mrad +2026-06-24 05:08:04,836 - RBF = 10.0607 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:08:04,836 - n_alpha = 6.3614 (# conv_angle) +2026-06-24 05:08:04,836 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:08:04,836 - Rayleigh-limited resolution = 1.5522 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:08:04,836 - Real space probe extent = 25.6000 Ang +2026-06-24 05:08:04,836 - +2026-06-24 05:08:04,836 - ### Initializing probe ### +2026-06-24 05:08:04,836 - Loading probe from source = 'simu' +2026-06-24 05:08:04,836 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:08:04,836 - Start simulating STEM probe +2026-06-24 05:08:04,836 - kv = 200.0 kV +2026-06-24 05:08:04,836 - wavelength = 0.0251 Ang +2026-06-24 05:08:04,836 - conv_angle = 9.856125831604004 mrad +2026-06-24 05:08:04,836 - Npix = 128 px +2026-06-24 05:08:04,836 - dk = 0.0391 Ang^-1 +2026-06-24 05:08:04,836 - kMax = 2.5000 Ang^-1 +2026-06-24 05:08:04,836 - alpha_max = 62.6984 mrad +2026-06-24 05:08:04,837 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:08:04,837 - Rayleigh-limited resolution = 1.5522 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:08:04,837 - Real space probe extent = 25.6000 Ang +2026-06-24 05:08:04,837 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:08:04,837 - ----------------------------------------------------------------------------------- +2026-06-24 05:08:04,837 - C1,0 C1 -264.6260 - Defocus (C10 = -df) +2026-06-24 05:08:04,837 - C1,2 A1 4.4250 17.82 2-fold astigmatism +2026-06-24 05:08:04,837 - C2,1 3*B2 713.5690 31.12 Axial coma +2026-06-24 05:08:04,837 - C2,3 A2 -375.2520 110.02 3-fold astigmatism +2026-06-24 05:08:04,837 - C3,0 C3 10131374.0000 - Spherical aberration +2026-06-24 05:08:04,837 - C3,2 4*S3 4611.9940 167.82 Axial star aberration +2026-06-24 05:08:04,837 - C3,4 A3 8771.1550 201.88 4-fold astigmatism +2026-06-24 05:08:04,837 - C4,1 4*B4 56336.9060 154.74 Axial coma(4th) +2026-06-24 05:08:04,837 - C4,3 4*D4 28428.5180 249.57 3-lobe aberration +2026-06-24 05:08:04,837 - C4,5 A4 335352.1250 142.90 5-fold astigmatism +2026-06-24 05:08:04,837 - C5,0 C5 5736675.5000 - Spherical aberration (5th) +2026-06-24 05:08:04,837 - C5,2 6*S5 -7180388.5000 13.03 Axial star aberration(5th) +2026-06-24 05:08:04,837 - C5,4 6*R5 5166542.0000 14.01 4-lobe aberration +2026-06-24 05:08:04,837 - C5,6 A5 4801067.5000 216.67 6-fold astigmatism +2026-06-24 05:08:04,840 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:08:04,840 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:08:04,840 - Creating 5 new probe modes from the major mode +2026-06-24 05:08:04,840 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:08:04,943 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:08:04,945 - Orthogonalizing 6 pmodes +2026-06-24 05:08:04,948 - Sorting 6 pmodes by their intensities +2026-06-24 05:08:04,948 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:08:04,949 - sum(|probe_data|**2) = 321.92, while meas_total_ints (min, mean, max) = (319.0837, 321.9215, 324.7194) +2026-06-24 05:08:04,949 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:08:04,949 - +2026-06-24 05:08:04,949 - ### Initializing probe positions ### +2026-06-24 05:08:04,949 - Loading probe positions from source = 'simu' +2026-06-24 05:08:04,949 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:08:04,949 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:08:04,949 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:08:04,951 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:08:04,951 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:08:04,951 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:08:04,952 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:08:04,952 - +2026-06-24 05:08:04,952 - ### Initializing object ### +2026-06-24 05:08:04,952 - Loading object from source = 'simu' +2026-06-24 05:08:04,952 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:08:04,953 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:08:04,953 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:08:04,953 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:08:04,953 - +2026-06-24 05:08:04,953 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:08:04,953 - omode_occu (omode) = float32, (1,) +2026-06-24 05:08:04,954 - +2026-06-24 05:08:04,954 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:08:04,954 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:08:04,954 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:08:04,954 - +2026-06-24 05:08:04,954 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:08:04,954 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:08:04,954 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:08:04,954 - +2026-06-24 05:08:04,954 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:08:04,954 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:08:04,955 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:08:04,955 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:08:04,955 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:08:04,955 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:08:04,955 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:08:04,955 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:08:04,955 - +2026-06-24 05:08:04,955 - ### Collecting reconstruction provenance ### +2026-06-24 05:08:04,955 - Reconstruction provenance is collected and initialized. +2026-06-24 05:08:04,955 - +2026-06-24 05:08:04,955 - ### Initializing loss function ### +2026-06-24 05:08:04,955 - Active loss types: +2026-06-24 05:08:04,955 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:08:04,955 - +2026-06-24 05:08:04,955 - ### Initializing constraint function ### +2026-06-24 05:08:04,955 - Active constraint types: +2026-06-24 05:08:04,955 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:08:04,955 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:08:04,955 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:08:04,955 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:08:04,955 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:08:04,956 - +2026-06-24 05:08:04,956 - ### Done initializing PtyRADSolver ### +2026-06-24 05:08:04,956 - +2026-06-24 05:08:05,079 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:08:05,079 - +2026-06-24 05:08:05,079 - ### Initializing PtychoModel model ### +2026-06-24 05:08:05,151 - ### PtychoModel optimizable variables ### +2026-06-24 05:08:05,151 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:08:05,151 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:08:05,151 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:08:05,152 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:08:05,152 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:08:05,152 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:08:05,152 - +2026-06-24 05:08:05,152 - ### Optimizable variables statitsics ### +2026-06-24 05:08:05,152 - Total measurement values : 4,194,304 +2026-06-24 05:08:05,152 - Total optimizing variables: 278,728 +2026-06-24 05:08:05,152 - Overdetermined ratio : 15.05 +2026-06-24 05:08:05,152 - +2026-06-24 05:08:05,152 - ### Model behavior ### +2026-06-24 05:08:05,152 - Tilt propagator : False +2026-06-24 05:08:05,152 - Change slice thickness : False +2026-06-24 05:08:05,152 - Detector blur : False +2026-06-24 05:08:05,152 - Preload data : True +2026-06-24 05:08:05,152 - On-the-fly meas padding : False +2026-06-24 05:08:05,152 - On-the-fly meas resample : False +2026-06-24 05:08:05,152 - On-the-fly simu match mode: None +2026-06-24 05:08:05,152 - +2026-06-24 05:08:05,193 - ### Done initializing PtychoModel model ### +2026-06-24 05:08:05,193 - +2026-06-24 05:08:05,193 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:08:05,194 - +2026-06-24 05:08:05,194 - ### Generating indices, batches, and output_path ### +2026-06-24 05:08:05,195 - d90 = 61.000 px or 12.200 Ang +2026-06-24 05:08:05,195 - Selecting indices with the 'full' mode +2026-06-24 05:08:05,654 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:08:05,732 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:08:05,732 - Original recon_dir_affixes = ['default'] +2026-06-24 05:08:05,732 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:08:05,739 - Path corrected for compatibility: +2026-06-24 05:08:05,739 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01e+07_C32_4.61e+03_phi32_168_C34_8.77e+03_phi34_202_C41_5.63e+04_phi41_155_C43_2.84e+04_phi43_250_C45_3.35e+05_phi45_143_C50_5.74e+06_C52_-7.18e+06_phi52_13_C54_5.17e+06_phi54_14_C56_4.8e+06_phi56_217 +2026-06-24 05:08:05,739 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217 +2026-06-24 05:08:05,740 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217' is generated! +2026-06-24 05:08:05,893 - +2026-06-24 05:08:05,894 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/20260624_050805_ptyrad_log.txt ### +2026-06-24 05:08:05,894 - +2026-06-24 05:08:05,895 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:08:05,895 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:08:05,895 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:08:07,077 - Iter: 1, Total Loss: 0.9570, loss_single: 0.9570, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:08:07,114 - Iter: 2, Total Loss: 0.9087, loss_single: 0.9087, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:08:07,150 - Iter: 3, Total Loss: 0.8710, loss_single: 0.8710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,186 - Iter: 4, Total Loss: 0.8369, loss_single: 0.8369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,221 - Iter: 5, Total Loss: 0.8033, loss_single: 0.8033, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,256 - Iter: 6, Total Loss: 0.7713, loss_single: 0.7713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,292 - Iter: 7, Total Loss: 0.7369, loss_single: 0.7369, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,327 - Iter: 8, Total Loss: 0.7021, loss_single: 0.7021, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,363 - Iter: 9, Total Loss: 0.6730, loss_single: 0.6730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,398 - Iter: 10, Total Loss: 0.6491, loss_single: 0.6491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,434 - Iter: 11, Total Loss: 0.6253, loss_single: 0.6253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,469 - Iter: 12, Total Loss: 0.6030, loss_single: 0.6030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,506 - Iter: 13, Total Loss: 0.5820, loss_single: 0.5820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,542 - Iter: 14, Total Loss: 0.5623, loss_single: 0.5623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:08:07,578 - Iter: 15, Total Loss: 0.5432, loss_single: 0.5432, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:08:07,614 - Iter: 16, Total Loss: 0.5244, loss_single: 0.5244, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,650 - Iter: 17, Total Loss: 0.5063, loss_single: 0.5063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,685 - Iter: 18, Total Loss: 0.4883, loss_single: 0.4883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,721 - Iter: 19, Total Loss: 0.4725, loss_single: 0.4725, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,757 - Iter: 20, Total Loss: 0.4578, loss_single: 0.4578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:08:07,792 - Iter: 21, Total Loss: 0.4444, loss_single: 0.4444, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,828 - Iter: 22, Total Loss: 0.4325, loss_single: 0.4325, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,863 - Iter: 23, Total Loss: 0.4223, loss_single: 0.4223, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,899 - Iter: 24, Total Loss: 0.4145, loss_single: 0.4145, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,934 - Iter: 25, Total Loss: 0.4084, loss_single: 0.4084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:07,969 - Iter: 26, Total Loss: 0.4030, loss_single: 0.4030, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,005 - Iter: 27, Total Loss: 0.3991, loss_single: 0.3991, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:08:08,040 - Iter: 28, Total Loss: 0.3956, loss_single: 0.3956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,076 - Iter: 29, Total Loss: 0.3925, loss_single: 0.3925, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,111 - Iter: 30, Total Loss: 0.3899, loss_single: 0.3899, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,147 - Iter: 31, Total Loss: 0.3877, loss_single: 0.3877, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,183 - Iter: 32, Total Loss: 0.3861, loss_single: 0.3861, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,218 - Iter: 33, Total Loss: 0.3847, loss_single: 0.3847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,254 - Iter: 34, Total Loss: 0.3834, loss_single: 0.3834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,290 - Iter: 35, Total Loss: 0.3823, loss_single: 0.3823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,325 - Iter: 36, Total Loss: 0.3813, loss_single: 0.3813, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,361 - Iter: 37, Total Loss: 0.3803, loss_single: 0.3803, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,396 - Iter: 38, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,432 - Iter: 39, Total Loss: 0.3781, loss_single: 0.3781, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,467 - Iter: 40, Total Loss: 0.3772, loss_single: 0.3772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,506 - Iter: 41, Total Loss: 0.3764, loss_single: 0.3764, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,541 - Iter: 42, Total Loss: 0.3756, loss_single: 0.3756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,576 - Iter: 43, Total Loss: 0.3749, loss_single: 0.3749, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,612 - Iter: 44, Total Loss: 0.3741, loss_single: 0.3741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,647 - Iter: 45, Total Loss: 0.3734, loss_single: 0.3734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,683 - Iter: 46, Total Loss: 0.3727, loss_single: 0.3727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:08:08,719 - Iter: 47, Total Loss: 0.3720, loss_single: 0.3720, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,754 - Iter: 48, Total Loss: 0.3713, loss_single: 0.3713, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,789 - Iter: 49, Total Loss: 0.3705, loss_single: 0.3705, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,824 - Iter: 50, Total Loss: 0.3697, loss_single: 0.3697, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,860 - Iter: 51, Total Loss: 0.3691, loss_single: 0.3691, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,895 - Iter: 52, Total Loss: 0.3684, loss_single: 0.3684, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,931 - Iter: 53, Total Loss: 0.3678, loss_single: 0.3678, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:08,966 - Iter: 54, Total Loss: 0.3672, loss_single: 0.3672, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:09,002 - Iter: 55, Total Loss: 0.3665, loss_single: 0.3665, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:09,037 - Iter: 56, Total Loss: 0.3658, loss_single: 0.3658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:09,073 - Iter: 57, Total Loss: 0.3650, loss_single: 0.3650, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:09,108 - Iter: 58, Total Loss: 0.3643, loss_single: 0.3643, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:08:09,144 - 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Saving summary figures for iter 100 +2026-06-24 05:08:14,455 - ### Finished 100 iterations, averaged iter_t = 0.039142 with std = 0.040 ### +2026-06-24 05:08:14,455 - +2026-06-24 05:08:14,456 - ### The PtyRADSolver is finished in 9.376 sec ### +2026-06-24 05:08:14,456 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..9326aca34feaafd2240ed30a7d71b313e23f6ec3 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/simulation_data_aug11__sample_000017.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/simulation_data_aug11__sample_000017.yaml new file mode 100644 index 0000000000000000000000000000000000000000..37afc77714bcc104988957ece4e56fe96910d543 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017/gendata3_std_02__simulation_data_aug11__sample_000017_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-265_C12_4.42_phi12_17.8_C21_714_phi21_31.1_C23_-375_phi23_110_C30_1.01.8e+06_phi56_217/simulation_data_aug11__sample_000017.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.856125831604004 + probe_aberrations: + C10: -264.6255798339844 + C12: 4.425314903259277 + C21: 713.5692138671875 + C23: -375.2522277832031 + C30: 10131374.0 + C32: 4611.994140625 + C34: 8771.1552734375 + C41: 56336.90625 + C43: 28428.517578125 + C45: 335352.125 + C50: 5736675.5 + C52: -7180388.5 + C54: 5166542.0 + C56: 4801067.5 + phi12: 17.82461148829346 + phi21: 31.118799481252484 + phi23: 110.01924598065052 + phi32: 167.81874511483213 + phi34: 201.87600809023996 + phi41: 154.73475277848564 + phi43: 249.57453853637563 + phi45: 142.8981578902586 + phi52: 13.026406157680443 + phi54: 14.011165756739956 + phi56: 216.67236983264365 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000017_measurement.h5 + key: measurement + random_seed: 20261738 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000017 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug11__sample_000017 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/20260624_051102_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/20260624_051102_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca7ba9395762911368c855a9a80e254c6944399c --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/20260624_051102_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:11:01,039 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:11:01,040 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:11:01,040 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:11:01,040 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:11:01,040 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:11:01,040 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:11:01,040 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:11:01,040 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:11:01,040 - +2026-06-24 05:11:01,146 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:11:01,146 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:11:01,147 - Accelerator.num_process = 1 +2026-06-24 05:11:01,147 - Accelerator.mixed_precision = no +2026-06-24 05:11:01,157 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:11:01,157 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:11:01,157 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:11:01,157 - +2026-06-24 05:11:01,157 - ### System information ### +2026-06-24 05:11:01,157 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:11:01,157 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:11:01,157 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:11:01,157 - Machine: x86_64 +2026-06-24 05:11:01,157 - Processor: x86_64 +2026-06-24 05:11:01,157 - Available CPU cores: 8 +2026-06-24 05:11:01,157 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:11:01,157 - +2026-06-24 05:11:01,157 - ### GPU information ### +2026-06-24 05:11:01,157 - CUDA Available: True +2026-06-24 05:11:01,157 - CUDA Version: 13.0 +2026-06-24 05:11:01,158 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:11:01,158 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:11:01,158 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:11:01,158 - In addition, Triton does not directly support Windows. +2026-06-24 05:11:01,158 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:11:01,185 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:11:01,185 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:11:01,185 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:11:01,185 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:11:01,185 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:11:01,185 - +2026-06-24 05:11:01,185 - ### Python information ### +2026-06-24 05:11:01,187 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:11:01,187 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:11:01,187 - +2026-06-24 05:11:01,187 - ### Packages information ### +2026-06-24 05:11:01,188 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:11:01,189 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:11:01,189 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:11:01,190 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:11:01,191 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:11:01,191 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:11:01,191 - +2026-06-24 05:11:01,191 - ### Loading params file ### +2026-06-24 05:11:01,191 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug11__sample_000029.yaml +2026-06-24 05:11:01,197 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:11:01,198 - Success! Params file validated and defaults applied. +2026-06-24 05:11:01,198 - +2026-06-24 05:11:01,198 - ### Setting GPU Device ### +2026-06-24 05:11:01,199 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:11:01,199 - +2026-06-24 05:11:01,199 - Random seed: 20261750 provided by params file +2026-06-24 05:11:01,199 - ### Initializing Initializer ### +2026-06-24 05:11:01,199 - init_params are displayed below: +2026-06-24 05:11:01,199 - random_seed: 20261750 +2026-06-24 05:11:01,199 - probe_illum_type: electron +2026-06-24 05:11:01,199 - probe_kv: 200.0 +2026-06-24 05:11:01,199 - probe_conv_angle: 9.35567855834961 +2026-06-24 05:11:01,199 - probe_aberrations: {'C10': -266.29, 'C12': 19.943, 'phi12': 52.466, 'C21': -574.509, 'phi21': 123.937, 'C23': 271.554, 'phi23': 287.157, 'C30': 10902072.0, 'C32': 4617.055, 'phi32': 37.477, 'C34': -3436.616, 'phi34': 117.84, 'C41': -256969.625, 'phi41': 172.755, 'C43': -44910.281, 'phi43': 99.282, 'C45': 185875.672, 'phi45': 330.465, 'C50': 14735584.0, 'C52': -17658376.0, 'phi52': 1.913, 'C54': 19552424.0, 'phi54': 341.799, 'C56': 14896195.0, 'phi56': 330.132} +2026-06-24 05:11:01,199 - beam_kev: None +2026-06-24 05:11:01,199 - probe_dRn: None +2026-06-24 05:11:01,199 - probe_Rn: None +2026-06-24 05:11:01,199 - probe_D_H: None +2026-06-24 05:11:01,199 - probe_D_FZP: None +2026-06-24 05:11:01,199 - probe_Ls: None +2026-06-24 05:11:01,200 - meas_Npix: 128 +2026-06-24 05:11:01,200 - pos_N_scans: 256 +2026-06-24 05:11:01,200 - pos_N_scan_slow: 16 +2026-06-24 05:11:01,200 - pos_N_scan_fast: 16 +2026-06-24 05:11:01,200 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:11:01,200 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:11:01,200 - probe_pmode_max: 6 +2026-06-24 05:11:01,200 - probe_pmode_init_pows: [0.02] +2026-06-24 05:11:01,200 - obj_omode_max: 1 +2026-06-24 05:11:01,200 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:11:01,200 - obj_Nlayer: 1 +2026-06-24 05:11:01,200 - obj_slice_thickness: 20.0 +2026-06-24 05:11:01,200 - simu_Npix: None +2026-06-24 05:11:01,200 - simu_match_mode: None +2026-06-24 05:11:01,200 - meas_permute: None +2026-06-24 05:11:01,200 - meas_reshape: [256, 128, 128] +2026-06-24 05:11:01,200 - meas_flipT: [0, 0, 0] +2026-06-24 05:11:01,200 - meas_crop: None +2026-06-24 05:11:01,200 - meas_pad: None +2026-06-24 05:11:01,200 - meas_resample: None +2026-06-24 05:11:01,200 - meas_add_source_size: None +2026-06-24 05:11:01,200 - meas_add_detector_blur: None +2026-06-24 05:11:01,200 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:11:01,200 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:11:01,200 - meas_add_poisson_noise: None +2026-06-24 05:11:01,200 - meas_export: None +2026-06-24 05:11:01,200 - probe_permute: None +2026-06-24 05:11:01,200 - probe_z_shift: None +2026-06-24 05:11:01,200 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:11:01,200 - pos_scan_flipT: None +2026-06-24 05:11:01,200 - pos_scan_affine: None +2026-06-24 05:11:01,200 - pos_scan_rand_std: 0.15 +2026-06-24 05:11:01,200 - obj_z_crop: None +2026-06-24 05:11:01,200 - obj_z_pad: None +2026-06-24 05:11:01,200 - obj_z_resample: None +2026-06-24 05:11:01,200 - meas_source: file +2026-06-24 05:11:01,200 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000029_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:11:01,200 - probe_source: simu +2026-06-24 05:11:01,200 - probe_params: None +2026-06-24 05:11:01,201 - pos_source: simu +2026-06-24 05:11:01,201 - pos_params: None +2026-06-24 05:11:01,201 - obj_source: simu +2026-06-24 05:11:01,201 - obj_params: None +2026-06-24 05:11:01,201 - tilt_source: simu +2026-06-24 05:11:01,201 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:11:01,201 - +2026-06-24 05:11:01,201 - ### Initializing cache ### +2026-06-24 05:11:01,201 - use_cached_obj = False +2026-06-24 05:11:01,201 - use_cached_probe = False +2026-06-24 05:11:01,201 - use_cached_pos = False +2026-06-24 05:11:01,201 - +2026-06-24 05:11:01,201 - ### Initializing measurements ### +2026-06-24 05:11:01,201 - Loading measurements from source = 'file' +2026-06-24 05:11:01,201 - Detected measurement file type = '.h5' +2026-06-24 05:11:01,277 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:11:01,277 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:11:01,279 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0047) +2026-06-24 05:11:01,279 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:11:01,279 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:11:01,280 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:11:01,280 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:11:01,281 - Normalizing by max of the 2D mean pattern intensity: 0.0035210282 +2026-06-24 05:11:01,281 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:11:01,283 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.3401) +2026-06-24 05:11:01,283 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:11:01,284 - Pattern total int. statistics (min, mean, max) = (282.3733, 284.0633, 285.5302), with min/max = 98.9% +2026-06-24 05:11:01,286 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0173, 1.3401) +2026-06-24 05:11:01,286 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:11:01,286 - +2026-06-24 05:11:01,286 - ### Setting up calibration ### +2026-06-24 05:11:01,286 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:11:01,286 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:11:01,286 - Radius of fitted bright field disk (RBF) = 9.41 px with meas_Npix = 128 +2026-06-24 05:11:01,286 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1470 +2026-06-24 05:11:01,286 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:11:01,286 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:11:01,505 - Initial guess: center=(63.63, 63.62), radius=9.41, Gaussian blur std=0.50 +2026-06-24 05:11:01,518 - Final fit: center=(63.63, 63.62), radius=9.41, Gaussian blur std=0.66 +2026-06-24 05:11:01,518 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.55 px with Npix = 128 +2026-06-24 05:11:01,518 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:11:01,518 - +2026-06-24 05:11:01,518 - ### Setting init_variables dict ### +2026-06-24 05:11:01,518 - Derived values given input init_params: +2026-06-24 05:11:01,518 - kv = 200.0 kV +2026-06-24 05:11:01,518 - wavelength = 0.0251 Ang +2026-06-24 05:11:01,518 - conv_angle = 9.35567855834961 mrad +2026-06-24 05:11:01,518 - Npix = 128 px +2026-06-24 05:11:01,518 - dk = 0.0391 Ang^-1 +2026-06-24 05:11:01,518 - kMax = 2.5000 Ang^-1 +2026-06-24 05:11:01,518 - da = 0.9797 mrad +2026-06-24 05:11:01,518 - angleMax = 62.6984 mrad +2026-06-24 05:11:01,518 - RBF = 9.5499 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:11:01,518 - n_alpha = 6.7016 (# conv_angle) +2026-06-24 05:11:01,518 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:11:01,518 - Rayleigh-limited resolution = 1.6352 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:11:01,518 - Real space probe extent = 25.6000 Ang +2026-06-24 05:11:01,518 - +2026-06-24 05:11:01,518 - ### Initializing probe ### +2026-06-24 05:11:01,518 - Loading probe from source = 'simu' +2026-06-24 05:11:01,518 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:11:01,519 - Start simulating STEM probe +2026-06-24 05:11:01,519 - kv = 200.0 kV +2026-06-24 05:11:01,519 - wavelength = 0.0251 Ang +2026-06-24 05:11:01,519 - conv_angle = 9.35567855834961 mrad +2026-06-24 05:11:01,519 - Npix = 128 px +2026-06-24 05:11:01,519 - dk = 0.0391 Ang^-1 +2026-06-24 05:11:01,519 - kMax = 2.5000 Ang^-1 +2026-06-24 05:11:01,519 - alpha_max = 62.6984 mrad +2026-06-24 05:11:01,519 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:11:01,519 - Rayleigh-limited resolution = 1.6352 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:11:01,519 - Real space probe extent = 25.6000 Ang +2026-06-24 05:11:01,519 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:11:01,519 - ------------------------------------------------------------------------------------ +2026-06-24 05:11:01,519 - C1,0 C1 -266.2900 - Defocus (C10 = -df) +2026-06-24 05:11:01,519 - C1,2 A1 19.9430 52.47 2-fold astigmatism +2026-06-24 05:11:01,519 - C2,1 3*B2 -574.5090 123.94 Axial coma +2026-06-24 05:11:01,519 - C2,3 A2 271.5540 287.16 3-fold astigmatism +2026-06-24 05:11:01,519 - C3,0 C3 10902072.0000 - Spherical aberration +2026-06-24 05:11:01,519 - C3,2 4*S3 4617.0550 37.48 Axial star aberration +2026-06-24 05:11:01,519 - C3,4 A3 -3436.6160 117.84 4-fold astigmatism +2026-06-24 05:11:01,519 - C4,1 4*B4 -256969.6250 172.75 Axial coma(4th) +2026-06-24 05:11:01,519 - C4,3 4*D4 -44910.2810 99.28 3-lobe aberration +2026-06-24 05:11:01,519 - C4,5 A4 185875.6720 330.46 5-fold astigmatism +2026-06-24 05:11:01,519 - C5,0 C5 14735584.0000 - Spherical aberration (5th) +2026-06-24 05:11:01,519 - C5,2 6*S5 -17658376.0000 1.91 Axial star aberration(5th) +2026-06-24 05:11:01,519 - C5,4 6*R5 19552424.0000 341.80 4-lobe aberration +2026-06-24 05:11:01,519 - C5,6 A5 14896195.0000 330.13 6-fold astigmatism +2026-06-24 05:11:01,522 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:11:01,522 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:11:01,522 - Creating 5 new probe modes from the major mode +2026-06-24 05:11:01,522 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:11:01,716 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:11:01,717 - Orthogonalizing 6 pmodes +2026-06-24 05:11:01,719 - Sorting 6 pmodes by their intensities +2026-06-24 05:11:01,720 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:11:01,721 - sum(|probe_data|**2) = 284.06, while meas_total_ints (min, mean, max) = (282.3733, 284.0633, 285.5302) +2026-06-24 05:11:01,721 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:11:01,721 - +2026-06-24 05:11:01,721 - ### Initializing probe positions ### +2026-06-24 05:11:01,721 - Loading probe positions from source = 'simu' +2026-06-24 05:11:01,721 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:11:01,721 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:11:01,721 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:11:01,723 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:11:01,723 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:11:01,723 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:11:01,723 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:11:01,723 - +2026-06-24 05:11:01,723 - ### Initializing object ### +2026-06-24 05:11:01,723 - Loading object from source = 'simu' +2026-06-24 05:11:01,723 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:11:01,725 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:11:01,725 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:11:01,725 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:11:01,725 - +2026-06-24 05:11:01,725 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:11:01,725 - omode_occu (omode) = float32, (1,) +2026-06-24 05:11:01,725 - +2026-06-24 05:11:01,725 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:11:01,725 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:11:01,726 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:11:01,726 - +2026-06-24 05:11:01,726 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:11:01,726 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:11:01,726 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:11:01,726 - +2026-06-24 05:11:01,726 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:11:01,726 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:11:01,726 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:11:01,726 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:11:01,726 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:11:01,727 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:11:01,727 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:11:01,727 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:11:01,727 - +2026-06-24 05:11:01,727 - ### Collecting reconstruction provenance ### +2026-06-24 05:11:01,727 - Reconstruction provenance is collected and initialized. +2026-06-24 05:11:01,727 - +2026-06-24 05:11:01,727 - ### Initializing loss function ### +2026-06-24 05:11:01,727 - Active loss types: +2026-06-24 05:11:01,727 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:11:01,727 - +2026-06-24 05:11:01,727 - ### Initializing constraint function ### +2026-06-24 05:11:01,727 - Active constraint types: +2026-06-24 05:11:01,727 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:11:01,727 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:11:01,727 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:11:01,727 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:11:01,727 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:11:01,727 - +2026-06-24 05:11:01,727 - ### Done initializing PtyRADSolver ### +2026-06-24 05:11:01,727 - +2026-06-24 05:11:01,851 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:11:01,851 - +2026-06-24 05:11:01,851 - ### Initializing PtychoModel model ### +2026-06-24 05:11:01,923 - ### PtychoModel optimizable variables ### +2026-06-24 05:11:01,923 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:01,923 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:01,923 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:11:01,923 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:11:01,923 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:11:01,923 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:01,923 - +2026-06-24 05:11:01,923 - ### Optimizable variables statitsics ### +2026-06-24 05:11:01,923 - Total measurement values : 4,194,304 +2026-06-24 05:11:01,923 - Total optimizing variables: 278,728 +2026-06-24 05:11:01,923 - Overdetermined ratio : 15.05 +2026-06-24 05:11:01,923 - +2026-06-24 05:11:01,923 - ### Model behavior ### +2026-06-24 05:11:01,923 - Tilt propagator : False +2026-06-24 05:11:01,923 - Change slice thickness : False +2026-06-24 05:11:01,923 - Detector blur : False +2026-06-24 05:11:01,923 - Preload data : True +2026-06-24 05:11:01,923 - On-the-fly meas padding : False +2026-06-24 05:11:01,923 - On-the-fly meas resample : False +2026-06-24 05:11:01,923 - On-the-fly simu match mode: None +2026-06-24 05:11:01,923 - +2026-06-24 05:11:01,964 - ### Done initializing PtychoModel model ### +2026-06-24 05:11:01,965 - +2026-06-24 05:11:01,965 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:11:01,965 - +2026-06-24 05:11:01,965 - ### Generating indices, batches, and output_path ### +2026-06-24 05:11:01,966 - d90 = 57.000 px or 11.400 Ang +2026-06-24 05:11:01,966 - Selecting indices with the 'full' mode +2026-06-24 05:11:02,429 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:11:02,505 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:11:02,505 - Original recon_dir_affixes = ['default'] +2026-06-24 05:11:02,506 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:11:02,511 - Path corrected for compatibility: +2026-06-24 05:11:02,511 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09e+07_C32_4.62e+03_phi32_37.5_C34_-3.44e+03_phi34_118_C41_-2.57e+05_phi41_173_C43_-4.49e+04_phi43_99.3_C45_1.86e+05_phi45_330_C50_1.47e+07_C52_-1.77e+07_phi52_1.91_C54_1.96e+07_phi54_342_C56_1.49e+07_phi56_330 +2026-06-24 05:11:02,512 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330 +2026-06-24 05:11:02,513 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330' is generated! +2026-06-24 05:11:02,668 - +2026-06-24 05:11:02,669 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/20260624_051102_ptyrad_log.txt ### +2026-06-24 05:11:02,669 - +2026-06-24 05:11:02,670 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:11:02,670 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:11:02,670 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:11:03,867 - Iter: 1, Total Loss: 0.9491, loss_single: 0.9491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:11:03,904 - Iter: 2, Total Loss: 0.8889, loss_single: 0.8889, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:11:03,939 - Iter: 3, Total Loss: 0.8358, loss_single: 0.8358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:03,975 - Iter: 4, Total Loss: 0.7911, loss_single: 0.7911, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,010 - Iter: 5, Total Loss: 0.7569, loss_single: 0.7569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,045 - Iter: 6, Total Loss: 0.7194, loss_single: 0.7194, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,080 - Iter: 7, Total Loss: 0.6775, loss_single: 0.6775, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,116 - Iter: 8, Total Loss: 0.6464, loss_single: 0.6464, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,151 - Iter: 9, Total Loss: 0.6212, loss_single: 0.6212, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,186 - Iter: 10, Total Loss: 0.5898, loss_single: 0.5898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,221 - Iter: 11, Total Loss: 0.5622, loss_single: 0.5622, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,257 - Iter: 12, Total Loss: 0.5358, loss_single: 0.5358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,292 - Iter: 13, Total Loss: 0.5107, loss_single: 0.5107, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,327 - Iter: 14, Total Loss: 0.4907, loss_single: 0.4907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,362 - Iter: 15, Total Loss: 0.4699, loss_single: 0.4699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,397 - Iter: 16, Total Loss: 0.4546, loss_single: 0.4546, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,436 - Iter: 17, Total Loss: 0.4428, loss_single: 0.4428, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,471 - Iter: 18, Total Loss: 0.4273, loss_single: 0.4273, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,507 - Iter: 19, Total Loss: 0.4160, loss_single: 0.4160, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,542 - Iter: 20, Total Loss: 0.4063, loss_single: 0.4063, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,577 - Iter: 21, Total Loss: 0.3953, loss_single: 0.3953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,612 - Iter: 22, Total Loss: 0.3872, loss_single: 0.3872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,647 - Iter: 23, Total Loss: 0.3814, loss_single: 0.3814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,683 - Iter: 24, Total Loss: 0.3756, loss_single: 0.3756, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,718 - Iter: 25, Total Loss: 0.3696, loss_single: 0.3696, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,753 - Iter: 26, Total Loss: 0.3644, loss_single: 0.3644, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,792 - Iter: 27, Total Loss: 0.3613, loss_single: 0.3613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.039 sec +2026-06-24 05:11:04,828 - Iter: 28, Total Loss: 0.3591, loss_single: 0.3591, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,863 - Iter: 29, Total Loss: 0.3569, loss_single: 0.3569, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,898 - Iter: 30, Total Loss: 0.3550, loss_single: 0.3550, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,934 - Iter: 31, Total Loss: 0.3531, loss_single: 0.3531, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:04,969 - Iter: 32, Total Loss: 0.3513, loss_single: 0.3513, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,004 - Iter: 33, Total Loss: 0.3494, loss_single: 0.3494, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,040 - Iter: 34, Total Loss: 0.3473, loss_single: 0.3473, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,075 - Iter: 35, Total Loss: 0.3453, loss_single: 0.3453, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,110 - Iter: 36, Total Loss: 0.3434, loss_single: 0.3434, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,145 - Iter: 37, Total Loss: 0.3420, loss_single: 0.3420, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,180 - Iter: 38, Total Loss: 0.3410, loss_single: 0.3410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,216 - Iter: 39, Total Loss: 0.3398, loss_single: 0.3398, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,250 - Iter: 40, Total Loss: 0.3388, loss_single: 0.3388, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:11:05,286 - Iter: 41, Total Loss: 0.3378, loss_single: 0.3378, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:11:05,321 - Iter: 42, Total Loss: 0.3368, loss_single: 0.3368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,357 - Iter: 43, Total Loss: 0.3359, loss_single: 0.3359, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,392 - Iter: 44, Total Loss: 0.3348, loss_single: 0.3348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,427 - Iter: 45, Total Loss: 0.3338, loss_single: 0.3338, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,463 - Iter: 46, Total Loss: 0.3328, loss_single: 0.3328, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,498 - Iter: 47, Total Loss: 0.3320, loss_single: 0.3320, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,533 - Iter: 48, Total Loss: 0.3313, loss_single: 0.3313, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:11:05,568 - Iter: 49, Total Loss: 0.3305, loss_single: 0.3305, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,603 - Iter: 50, Total Loss: 0.3297, loss_single: 0.3297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,639 - Iter: 51, Total Loss: 0.3288, loss_single: 0.3288, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,674 - Iter: 52, Total Loss: 0.3279, loss_single: 0.3279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,709 - Iter: 53, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,745 - Iter: 54, Total Loss: 0.3261, loss_single: 0.3261, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,779 - Iter: 55, Total Loss: 0.3251, loss_single: 0.3251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:11:05,815 - Iter: 56, Total Loss: 0.3242, loss_single: 0.3242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,850 - Iter: 57, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,885 - Iter: 58, Total Loss: 0.3229, loss_single: 0.3229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:05,920 - 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Iter: 95, Total Loss: 0.3022, loss_single: 0.3022, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,224 - Iter: 96, Total Loss: 0.3017, loss_single: 0.3017, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,259 - Iter: 97, Total Loss: 0.3012, loss_single: 0.3012, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,295 - Iter: 98, Total Loss: 0.3007, loss_single: 0.3007, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,330 - Iter: 99, Total Loss: 0.3003, loss_single: 0.3003, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,365 - Iter: 100, Total Loss: 0.2999, loss_single: 0.2999, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:07,474 - Saving summary figures for iter 100 +2026-06-24 05:11:11,030 - ### Finished 100 iterations, averaged iter_t = 0.038868 with std = 0.040 ### +2026-06-24 05:11:11,030 - +2026-06-24 05:11:11,030 - ### The PtyRADSolver is finished in 9.180 sec ### +2026-06-24 05:11:11,030 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..c29a2bf362714cb2b500bf7ff438ff96eb3e77c5 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/simulation_data_aug11__sample_000029.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/simulation_data_aug11__sample_000029.yaml new file mode 100644 index 0000000000000000000000000000000000000000..42a48769949847f68a0c6edce6d96834a2b05627 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029/gendata3_std_02__simulation_data_aug11__sample_000029_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-266_C12_19.9_phi12_52.5_C21_-575_phi21_124_C23_272_phi23_287_C30_1.09.49e+07_phi56_330/simulation_data_aug11__sample_000029.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.35567855834961 + probe_aberrations: + C10: -266.2903137207031 + C12: 19.94328498840332 + C21: -574.5088500976562 + C23: 271.55389404296875 + C30: 10902072.0 + C32: 4617.05517578125 + C34: -3436.616455078125 + C41: -256969.625 + C43: -44910.28125 + C45: 185875.671875 + C50: 14735584.0 + C52: -17658376.0 + C54: 19552424.0 + C56: 14896195.0 + phi12: 52.4658351471699 + phi21: 123.93671947122448 + phi23: 287.1569714254538 + phi32: 37.476715221104705 + phi34: 117.83988771239599 + phi41: 172.75500479027036 + phi43: 99.28236619030889 + phi45: 330.46528849953705 + phi52: 1.9131357730771599 + phi54: 341.7990312006894 + phi56: 330.132439720904 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000029_measurement.h5 + key: measurement + random_seed: 20261750 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000029 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug11__sample_000029 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/20260624_051132_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/20260624_051132_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9d34951bab2aa45da8c75d393df03773acb2c0d5 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/20260624_051132_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:11:30,430 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:11:30,430 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:11:30,431 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:11:30,431 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:11:30,431 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:11:30,431 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:11:30,431 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:11:30,431 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:11:30,431 - +2026-06-24 05:11:30,538 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:11:30,538 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:11:30,538 - Accelerator.num_process = 1 +2026-06-24 05:11:30,538 - Accelerator.mixed_precision = no +2026-06-24 05:11:30,549 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:11:30,549 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:11:30,549 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:11:30,549 - +2026-06-24 05:11:30,549 - ### System information ### +2026-06-24 05:11:30,549 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:11:30,549 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:11:30,549 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:11:30,549 - Machine: x86_64 +2026-06-24 05:11:30,549 - Processor: x86_64 +2026-06-24 05:11:30,549 - Available CPU cores: 8 +2026-06-24 05:11:30,549 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:11:30,549 - +2026-06-24 05:11:30,549 - ### GPU information ### +2026-06-24 05:11:30,549 - CUDA Available: True +2026-06-24 05:11:30,549 - CUDA Version: 13.0 +2026-06-24 05:11:30,550 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:11:30,550 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:11:30,550 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:11:30,550 - In addition, Triton does not directly support Windows. +2026-06-24 05:11:30,550 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:11:30,577 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:11:30,577 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:11:30,577 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:11:30,577 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:11:30,578 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:11:30,578 - +2026-06-24 05:11:30,578 - ### Python information ### +2026-06-24 05:11:30,580 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:11:30,580 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:11:30,580 - +2026-06-24 05:11:30,580 - ### Packages information ### +2026-06-24 05:11:30,580 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:11:30,581 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:11:30,582 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:11:30,582 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:11:30,583 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:11:30,583 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:11:30,583 - +2026-06-24 05:11:30,583 - ### Loading params file ### +2026-06-24 05:11:30,583 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug11__sample_000031.yaml +2026-06-24 05:11:30,589 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:11:30,590 - Success! Params file validated and defaults applied. +2026-06-24 05:11:30,590 - +2026-06-24 05:11:30,590 - ### Setting GPU Device ### +2026-06-24 05:11:30,591 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:11:30,591 - +2026-06-24 05:11:30,591 - Random seed: 20261752 provided by params file +2026-06-24 05:11:30,591 - ### Initializing Initializer ### +2026-06-24 05:11:30,591 - init_params are displayed below: +2026-06-24 05:11:30,591 - random_seed: 20261752 +2026-06-24 05:11:30,591 - probe_illum_type: electron +2026-06-24 05:11:30,591 - probe_kv: 200.0 +2026-06-24 05:11:30,591 - probe_conv_angle: 9.658795356750488 +2026-06-24 05:11:30,591 - probe_aberrations: {'C10': -295.334, 'C12': -39.026, 'phi12': 75.97, 'C21': -729.526, 'phi21': 3.071, 'C23': 682.724, 'phi23': 22.314, 'C30': 11903337.0, 'C32': 9783.469, 'phi32': 9.535, 'C34': 742.591, 'phi34': 189.967, 'C41': -491153.719, 'phi41': 358.036, 'C43': -196840.797, 'phi43': 36.861, 'C45': 216352.0, 'phi45': 99.029, 'C50': -3310598.5, 'C52': -16387224.0, 'phi52': 218.379, 'C54': -5878874.5, 'phi54': 59.317, 'C56': -10303529.0, 'phi56': 250.342} +2026-06-24 05:11:30,591 - beam_kev: None +2026-06-24 05:11:30,591 - probe_dRn: None +2026-06-24 05:11:30,591 - probe_Rn: None +2026-06-24 05:11:30,591 - probe_D_H: None +2026-06-24 05:11:30,591 - probe_D_FZP: None +2026-06-24 05:11:30,591 - probe_Ls: None +2026-06-24 05:11:30,591 - meas_Npix: 128 +2026-06-24 05:11:30,592 - pos_N_scans: 256 +2026-06-24 05:11:30,592 - pos_N_scan_slow: 16 +2026-06-24 05:11:30,592 - pos_N_scan_fast: 16 +2026-06-24 05:11:30,592 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:11:30,592 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:11:30,592 - probe_pmode_max: 6 +2026-06-24 05:11:30,592 - probe_pmode_init_pows: [0.02] +2026-06-24 05:11:30,592 - obj_omode_max: 1 +2026-06-24 05:11:30,592 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:11:30,592 - obj_Nlayer: 1 +2026-06-24 05:11:30,592 - obj_slice_thickness: 20.0 +2026-06-24 05:11:30,592 - simu_Npix: None +2026-06-24 05:11:30,592 - simu_match_mode: None +2026-06-24 05:11:30,592 - meas_permute: None +2026-06-24 05:11:30,592 - meas_reshape: [256, 128, 128] +2026-06-24 05:11:30,592 - meas_flipT: [0, 0, 0] +2026-06-24 05:11:30,592 - meas_crop: None +2026-06-24 05:11:30,592 - meas_pad: None +2026-06-24 05:11:30,592 - meas_resample: None +2026-06-24 05:11:30,592 - meas_add_source_size: None +2026-06-24 05:11:30,592 - meas_add_detector_blur: None +2026-06-24 05:11:30,592 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:11:30,592 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:11:30,592 - meas_add_poisson_noise: None +2026-06-24 05:11:30,592 - meas_export: None +2026-06-24 05:11:30,592 - probe_permute: None +2026-06-24 05:11:30,592 - probe_z_shift: None +2026-06-24 05:11:30,592 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:11:30,592 - pos_scan_flipT: None +2026-06-24 05:11:30,592 - pos_scan_affine: None +2026-06-24 05:11:30,592 - pos_scan_rand_std: 0.15 +2026-06-24 05:11:30,592 - obj_z_crop: None +2026-06-24 05:11:30,592 - obj_z_pad: None +2026-06-24 05:11:30,592 - obj_z_resample: None +2026-06-24 05:11:30,592 - meas_source: file +2026-06-24 05:11:30,592 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000031_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:11:30,592 - probe_source: simu +2026-06-24 05:11:30,592 - probe_params: None +2026-06-24 05:11:30,592 - pos_source: simu +2026-06-24 05:11:30,593 - pos_params: None +2026-06-24 05:11:30,593 - obj_source: simu +2026-06-24 05:11:30,593 - obj_params: None +2026-06-24 05:11:30,593 - tilt_source: simu +2026-06-24 05:11:30,593 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:11:30,593 - +2026-06-24 05:11:30,593 - ### Initializing cache ### +2026-06-24 05:11:30,593 - use_cached_obj = False +2026-06-24 05:11:30,593 - use_cached_probe = False +2026-06-24 05:11:30,593 - use_cached_pos = False +2026-06-24 05:11:30,593 - +2026-06-24 05:11:30,593 - ### Initializing measurements ### +2026-06-24 05:11:30,593 - Loading measurements from source = 'file' +2026-06-24 05:11:30,593 - Detected measurement file type = '.h5' +2026-06-24 05:11:30,671 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:11:30,671 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:11:30,673 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0042) +2026-06-24 05:11:30,673 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:11:30,673 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:11:30,675 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:11:30,675 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:11:30,675 - Normalizing by max of the 2D mean pattern intensity: 0.0032419532 +2026-06-24 05:11:30,676 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:11:30,677 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0188, 1.2828) +2026-06-24 05:11:30,678 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:11:30,679 - Pattern total int. statistics (min, mean, max) = (306.0709, 307.8103, 309.8402), with min/max = 98.8% +2026-06-24 05:11:30,680 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0188, 1.2828) +2026-06-24 05:11:30,680 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:11:30,680 - +2026-06-24 05:11:30,680 - ### Setting up calibration ### +2026-06-24 05:11:30,680 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:11:30,680 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:11:30,680 - Radius of fitted bright field disk (RBF) = 9.77 px with meas_Npix = 128 +2026-06-24 05:11:30,680 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1527 +2026-06-24 05:11:30,680 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:11:30,681 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:11:30,901 - Initial guess: center=(63.63, 63.61), radius=9.77, Gaussian blur std=0.50 +2026-06-24 05:11:30,911 - Final fit: center=(63.63, 63.61), radius=9.77, Gaussian blur std=0.60 +2026-06-24 05:11:30,911 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.86 px with Npix = 128 +2026-06-24 05:11:30,911 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:11:30,911 - +2026-06-24 05:11:30,911 - ### Setting init_variables dict ### +2026-06-24 05:11:30,911 - Derived values given input init_params: +2026-06-24 05:11:30,911 - kv = 200.0 kV +2026-06-24 05:11:30,911 - wavelength = 0.0251 Ang +2026-06-24 05:11:30,911 - conv_angle = 9.658795356750488 mrad +2026-06-24 05:11:30,911 - Npix = 128 px +2026-06-24 05:11:30,911 - dk = 0.0391 Ang^-1 +2026-06-24 05:11:30,911 - kMax = 2.5000 Ang^-1 +2026-06-24 05:11:30,911 - da = 0.9797 mrad +2026-06-24 05:11:30,911 - angleMax = 62.6984 mrad +2026-06-24 05:11:30,911 - RBF = 9.8593 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:11:30,911 - n_alpha = 6.4913 (# conv_angle) +2026-06-24 05:11:30,911 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:11:30,911 - Rayleigh-limited resolution = 1.5839 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:11:30,911 - Real space probe extent = 25.6000 Ang +2026-06-24 05:11:30,912 - +2026-06-24 05:11:30,912 - ### Initializing probe ### +2026-06-24 05:11:30,912 - Loading probe from source = 'simu' +2026-06-24 05:11:30,912 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:11:30,912 - Start simulating STEM probe +2026-06-24 05:11:30,912 - kv = 200.0 kV +2026-06-24 05:11:30,912 - wavelength = 0.0251 Ang +2026-06-24 05:11:30,912 - conv_angle = 9.658795356750488 mrad +2026-06-24 05:11:30,912 - Npix = 128 px +2026-06-24 05:11:30,912 - dk = 0.0391 Ang^-1 +2026-06-24 05:11:30,912 - kMax = 2.5000 Ang^-1 +2026-06-24 05:11:30,912 - alpha_max = 62.6984 mrad +2026-06-24 05:11:30,912 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:11:30,912 - Rayleigh-limited resolution = 1.5839 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:11:30,912 - Real space probe extent = 25.6000 Ang +2026-06-24 05:11:30,912 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:11:30,912 - ------------------------------------------------------------------------------------ +2026-06-24 05:11:30,912 - C1,0 C1 -295.3340 - Defocus (C10 = -df) +2026-06-24 05:11:30,912 - C1,2 A1 -39.0260 75.97 2-fold astigmatism +2026-06-24 05:11:30,912 - C2,1 3*B2 -729.5260 3.07 Axial coma +2026-06-24 05:11:30,912 - C2,3 A2 682.7240 22.31 3-fold astigmatism +2026-06-24 05:11:30,912 - C3,0 C3 11903337.0000 - Spherical aberration +2026-06-24 05:11:30,912 - C3,2 4*S3 9783.4690 9.54 Axial star aberration +2026-06-24 05:11:30,912 - C3,4 A3 742.5910 189.97 4-fold astigmatism +2026-06-24 05:11:30,912 - C4,1 4*B4 -491153.7190 358.04 Axial coma(4th) +2026-06-24 05:11:30,913 - C4,3 4*D4 -196840.7970 36.86 3-lobe aberration +2026-06-24 05:11:30,913 - C4,5 A4 216352.0000 99.03 5-fold astigmatism +2026-06-24 05:11:30,913 - C5,0 C5 -3310598.5000 - Spherical aberration (5th) +2026-06-24 05:11:30,913 - C5,2 6*S5 -16387224.0000 218.38 Axial star aberration(5th) +2026-06-24 05:11:30,913 - C5,4 6*R5 -5878874.5000 59.32 4-lobe aberration +2026-06-24 05:11:30,913 - C5,6 A5 -10303529.0000 250.34 6-fold astigmatism +2026-06-24 05:11:30,915 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:11:30,916 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:11:30,916 - Creating 5 new probe modes from the major mode +2026-06-24 05:11:30,916 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:11:31,109 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:11:31,110 - Orthogonalizing 6 pmodes +2026-06-24 05:11:31,112 - Sorting 6 pmodes by their intensities +2026-06-24 05:11:31,112 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:11:31,113 - sum(|probe_data|**2) = 307.81, while meas_total_ints (min, mean, max) = (306.0709, 307.8103, 309.8402) +2026-06-24 05:11:31,113 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:11:31,113 - +2026-06-24 05:11:31,113 - ### Initializing probe positions ### +2026-06-24 05:11:31,113 - Loading probe positions from source = 'simu' +2026-06-24 05:11:31,113 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:11:31,113 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:11:31,113 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:11:31,115 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:11:31,116 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:11:31,116 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:11:31,116 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:11:31,116 - +2026-06-24 05:11:31,116 - ### Initializing object ### +2026-06-24 05:11:31,116 - Loading object from source = 'simu' +2026-06-24 05:11:31,116 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:11:31,117 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:11:31,117 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:11:31,118 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:11:31,118 - +2026-06-24 05:11:31,118 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:11:31,118 - omode_occu (omode) = float32, (1,) +2026-06-24 05:11:31,118 - +2026-06-24 05:11:31,118 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:11:31,118 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:11:31,119 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:11:31,119 - +2026-06-24 05:11:31,119 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:11:31,119 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:11:31,119 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:11:31,119 - +2026-06-24 05:11:31,119 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:11:31,119 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:11:31,119 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:11:31,119 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:11:31,119 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:11:31,119 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:11:31,119 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:11:31,119 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:11:31,119 - +2026-06-24 05:11:31,119 - ### Collecting reconstruction provenance ### +2026-06-24 05:11:31,119 - Reconstruction provenance is collected and initialized. +2026-06-24 05:11:31,119 - +2026-06-24 05:11:31,119 - ### Initializing loss function ### +2026-06-24 05:11:31,119 - Active loss types: +2026-06-24 05:11:31,119 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:11:31,120 - +2026-06-24 05:11:31,120 - ### Initializing constraint function ### +2026-06-24 05:11:31,120 - Active constraint types: +2026-06-24 05:11:31,120 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:11:31,120 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:11:31,120 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:11:31,120 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:11:31,120 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:11:31,120 - +2026-06-24 05:11:31,120 - ### Done initializing PtyRADSolver ### +2026-06-24 05:11:31,120 - +2026-06-24 05:11:31,249 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:11:31,249 - +2026-06-24 05:11:31,249 - ### Initializing PtychoModel model ### +2026-06-24 05:11:31,321 - ### PtychoModel optimizable variables ### +2026-06-24 05:11:31,321 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:31,321 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:31,321 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:11:31,321 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:11:31,321 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:11:31,322 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:11:31,322 - +2026-06-24 05:11:31,322 - ### Optimizable variables statitsics ### +2026-06-24 05:11:31,322 - Total measurement values : 4,194,304 +2026-06-24 05:11:31,322 - Total optimizing variables: 278,728 +2026-06-24 05:11:31,322 - Overdetermined ratio : 15.05 +2026-06-24 05:11:31,322 - +2026-06-24 05:11:31,322 - ### Model behavior ### +2026-06-24 05:11:31,322 - Tilt propagator : False +2026-06-24 05:11:31,322 - Change slice thickness : False +2026-06-24 05:11:31,322 - Detector blur : False +2026-06-24 05:11:31,322 - Preload data : True +2026-06-24 05:11:31,322 - On-the-fly meas padding : False +2026-06-24 05:11:31,322 - On-the-fly meas resample : False +2026-06-24 05:11:31,322 - On-the-fly simu match mode: None +2026-06-24 05:11:31,322 - +2026-06-24 05:11:31,362 - ### Done initializing PtychoModel model ### +2026-06-24 05:11:31,363 - +2026-06-24 05:11:31,363 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:11:31,363 - +2026-06-24 05:11:31,363 - ### Generating indices, batches, and output_path ### +2026-06-24 05:11:31,364 - d90 = 61.000 px or 12.200 Ang +2026-06-24 05:11:31,364 - Selecting indices with the 'full' mode +2026-06-24 05:11:31,828 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:11:31,904 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:11:31,904 - Original recon_dir_affixes = ['default'] +2026-06-24 05:11:31,904 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:11:31,910 - Path corrected for compatibility: +2026-06-24 05:11:31,910 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e+07_C32_9.78e+03_phi32_9.54_C34_743_phi34_190_C41_-4.91e+05_phi41_358_C43_-1.97e+05_phi43_36.9_C45_2.16e+05_phi45_99_C50_-3.31e+06_C52_-1.64e+07_phi52_218_C54_-5.88e+06_phi54_59.3_C56_-1.03e+07_phi56_250 +2026-06-24 05:11:31,910 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250 +2026-06-24 05:11:31,911 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250' is generated! +2026-06-24 05:11:32,065 - +2026-06-24 05:11:32,067 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/20260624_051132_ptyrad_log.txt ### +2026-06-24 05:11:32,067 - +2026-06-24 05:11:32,068 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:11:32,068 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:11:32,068 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:11:33,260 - Iter: 1, Total Loss: 0.9508, loss_single: 0.9508, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:11:33,297 - Iter: 2, Total Loss: 0.9017, loss_single: 0.9017, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:11:33,333 - Iter: 3, Total Loss: 0.8620, loss_single: 0.8620, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,369 - Iter: 4, Total Loss: 0.8258, loss_single: 0.8258, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,404 - Iter: 5, Total Loss: 0.7883, loss_single: 0.7883, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,439 - Iter: 6, Total Loss: 0.7495, loss_single: 0.7495, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,475 - Iter: 7, Total Loss: 0.7165, loss_single: 0.7165, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,511 - Iter: 8, Total Loss: 0.6860, loss_single: 0.6860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,546 - Iter: 9, Total Loss: 0.6519, loss_single: 0.6519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,581 - Iter: 10, Total Loss: 0.6214, loss_single: 0.6214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,616 - Iter: 11, Total Loss: 0.6011, loss_single: 0.6011, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,651 - Iter: 12, Total Loss: 0.5792, loss_single: 0.5792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,687 - Iter: 13, Total Loss: 0.5523, loss_single: 0.5523, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,722 - Iter: 14, Total Loss: 0.5330, loss_single: 0.5330, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,757 - Iter: 15, Total Loss: 0.5141, loss_single: 0.5141, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,793 - Iter: 16, Total Loss: 0.4929, loss_single: 0.4929, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,827 - Iter: 17, Total Loss: 0.4737, loss_single: 0.4737, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:11:33,862 - Iter: 18, Total Loss: 0.4576, loss_single: 0.4576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,898 - Iter: 19, Total Loss: 0.4452, loss_single: 0.4452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,933 - Iter: 20, Total Loss: 0.4337, loss_single: 0.4337, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:33,968 - Iter: 21, Total Loss: 0.4221, loss_single: 0.4221, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,003 - Iter: 22, Total Loss: 0.4086, loss_single: 0.4086, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,039 - Iter: 23, Total Loss: 0.3975, loss_single: 0.3975, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,074 - Iter: 24, Total Loss: 0.3897, loss_single: 0.3897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,109 - Iter: 25, Total Loss: 0.3799, loss_single: 0.3799, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,144 - Iter: 26, Total Loss: 0.3693, loss_single: 0.3693, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,183 - Iter: 27, Total Loss: 0.3623, loss_single: 0.3623, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:11:34,219 - Iter: 28, Total Loss: 0.3570, loss_single: 0.3570, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,254 - Iter: 29, Total Loss: 0.3524, loss_single: 0.3524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,289 - Iter: 30, Total Loss: 0.3490, loss_single: 0.3490, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,325 - Iter: 31, Total Loss: 0.3458, loss_single: 0.3458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,360 - Iter: 32, Total Loss: 0.3437, loss_single: 0.3437, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,396 - Iter: 33, Total Loss: 0.3417, loss_single: 0.3417, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,431 - Iter: 34, Total Loss: 0.3390, loss_single: 0.3390, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,466 - Iter: 35, Total Loss: 0.3367, loss_single: 0.3367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,502 - Iter: 36, Total Loss: 0.3347, loss_single: 0.3347, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,537 - Iter: 37, Total Loss: 0.3331, loss_single: 0.3331, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,573 - Iter: 38, Total Loss: 0.3318, loss_single: 0.3318, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,608 - Iter: 39, Total Loss: 0.3309, loss_single: 0.3309, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,643 - Iter: 40, Total Loss: 0.3303, loss_single: 0.3303, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,680 - Iter: 41, Total Loss: 0.3297, loss_single: 0.3297, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,715 - Iter: 42, Total Loss: 0.3291, loss_single: 0.3291, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,751 - Iter: 43, Total Loss: 0.3283, loss_single: 0.3283, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,786 - Iter: 44, Total Loss: 0.3278, loss_single: 0.3278, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,821 - Iter: 45, Total Loss: 0.3274, loss_single: 0.3274, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,857 - Iter: 46, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,892 - Iter: 47, Total Loss: 0.3267, loss_single: 0.3267, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,927 - Iter: 48, Total Loss: 0.3263, loss_single: 0.3263, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,963 - Iter: 49, Total Loss: 0.3259, loss_single: 0.3259, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:34,998 - Iter: 50, Total Loss: 0.3256, loss_single: 0.3256, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,033 - Iter: 51, Total Loss: 0.3253, loss_single: 0.3253, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,069 - Iter: 52, Total Loss: 0.3250, loss_single: 0.3250, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:11:35,104 - Iter: 53, Total Loss: 0.3247, loss_single: 0.3247, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,139 - Iter: 54, Total Loss: 0.3244, loss_single: 0.3244, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,174 - Iter: 55, Total Loss: 0.3241, loss_single: 0.3241, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,210 - Iter: 56, Total Loss: 0.3239, loss_single: 0.3239, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,245 - Iter: 57, Total Loss: 0.3237, loss_single: 0.3237, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:11:35,281 - Iter: 58, Total Loss: 0.3235, loss_single: 0.3235, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:11:35,316 - 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Saving summary figures for iter 100 +2026-06-24 05:11:40,493 - ### Finished 100 iterations, averaged iter_t = 0.038971 with std = 0.040 ### +2026-06-24 05:11:40,493 - +2026-06-24 05:11:40,493 - ### The PtyRADSolver is finished in 9.244 sec ### +2026-06-24 05:11:40,493 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..627b8d212a021acd6e1279efb09dc7eb832b50fa Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/simulation_data_aug11__sample_000031.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/simulation_data_aug11__sample_000031.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2b76c841b098bf45d52d2199ceb22b67f74ff57a --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031/gendata3_std_02__simulation_data_aug11__sample_000031_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-295_C12_-39_phi12_76_C21_-730_phi21_3.07_C23_683_phi23_22.3_C30_1.19e.03e+07_phi56_250/simulation_data_aug11__sample_000031.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.658795356750488 + probe_aberrations: + C10: -295.333984375 + C12: -39.02643585205078 + C21: -729.5256958007812 + C23: 682.7236938476562 + C30: 11903337.0 + C32: 9783.46875 + C34: 742.5911865234375 + C41: -491153.71875 + C43: -196840.796875 + C45: 216352.0 + C50: -3310598.5 + C52: -16387224.0 + C54: -5878874.5 + C56: -10303529.0 + phi12: 75.97006311903078 + phi21: 3.0709023562658038 + phi23: 22.314164839181835 + phi32: 9.534888586050794 + phi34: 189.96746398929602 + phi41: 358.0363579522907 + phi43: 36.86086438440133 + phi45: 99.02932817212744 + phi52: 218.3790565213114 + phi54: 59.31702373378586 + phi56: 250.34156878016807 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug11__sample_000031_measurement.h5 + key: measurement + random_seed: 20261752 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug11__sample_000031 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug11__sample_000031 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/20260624_051414_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/20260624_051414_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..88a463c9602a27d034aa20165fcbd1fa75db9e47 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/20260624_051414_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:14:12,670 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:14:12,670 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:14:12,670 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:14:12,670 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:14:12,670 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:14:12,670 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:14:12,670 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:14:12,670 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:14:12,670 - +2026-06-24 05:14:12,781 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:14:12,781 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:14:12,781 - Accelerator.num_process = 1 +2026-06-24 05:14:12,781 - Accelerator.mixed_precision = no +2026-06-24 05:14:12,791 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:14:12,791 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:14:12,791 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:14:12,791 - +2026-06-24 05:14:12,791 - ### System information ### +2026-06-24 05:14:12,791 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:14:12,791 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:14:12,791 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:14:12,791 - Machine: x86_64 +2026-06-24 05:14:12,792 - Processor: x86_64 +2026-06-24 05:14:12,792 - Available CPU cores: 8 +2026-06-24 05:14:12,792 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:14:12,792 - +2026-06-24 05:14:12,792 - ### GPU information ### +2026-06-24 05:14:12,792 - CUDA Available: True +2026-06-24 05:14:12,792 - CUDA Version: 13.0 +2026-06-24 05:14:12,792 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:14:12,792 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:14:12,792 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:14:12,792 - In addition, Triton does not directly support Windows. +2026-06-24 05:14:12,792 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:14:12,833 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:14:12,833 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:14:12,833 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:14:12,833 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:14:12,833 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:14:12,833 - +2026-06-24 05:14:12,833 - ### Python information ### +2026-06-24 05:14:12,835 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:14:12,835 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:14:12,835 - +2026-06-24 05:14:12,835 - ### Packages information ### +2026-06-24 05:14:12,835 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:14:12,836 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:14:12,837 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:14:12,838 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:14:12,838 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:14:12,838 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:14:12,838 - +2026-06-24 05:14:12,838 - ### Loading params file ### +2026-06-24 05:14:12,838 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug7__sample_000010.yaml +2026-06-24 05:14:12,845 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:14:12,846 - Success! Params file validated and defaults applied. +2026-06-24 05:14:12,846 - +2026-06-24 05:14:12,846 - ### Setting GPU Device ### +2026-06-24 05:14:12,846 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:14:12,846 - +2026-06-24 05:14:12,846 - Random seed: 20261763 provided by params file +2026-06-24 05:14:12,846 - ### Initializing Initializer ### +2026-06-24 05:14:12,847 - init_params are displayed below: +2026-06-24 05:14:12,847 - random_seed: 20261763 +2026-06-24 05:14:12,847 - probe_illum_type: electron +2026-06-24 05:14:12,847 - probe_kv: 200.0 +2026-06-24 05:14:12,847 - probe_conv_angle: 9.07798957824707 +2026-06-24 05:14:12,847 - probe_aberrations: {'C10': -285.31, 'C12': -1.172, 'phi12': 295.148, 'C21': -161.361, 'phi21': 295.641, 'C23': -352.725, 'phi23': 41.725, 'C30': 11467017.0, 'C32': -843.171, 'phi32': 209.682, 'C34': 9674.205, 'phi34': 230.839, 'C41': 467392.062, 'phi41': 17.634, 'C43': 140097.594, 'phi43': 323.459, 'C45': 227238.562, 'phi45': 303.427, 'C50': 13855129.0, 'C52': -8144325.0, 'phi52': 12.766, 'C54': -11617440.0, 'phi54': 16.812, 'C56': -1245309.25, 'phi56': 189.216} +2026-06-24 05:14:12,847 - beam_kev: None +2026-06-24 05:14:12,847 - probe_dRn: None +2026-06-24 05:14:12,847 - probe_Rn: None +2026-06-24 05:14:12,847 - probe_D_H: None +2026-06-24 05:14:12,847 - probe_D_FZP: None +2026-06-24 05:14:12,847 - probe_Ls: None +2026-06-24 05:14:12,847 - meas_Npix: 128 +2026-06-24 05:14:12,847 - pos_N_scans: 256 +2026-06-24 05:14:12,847 - pos_N_scan_slow: 16 +2026-06-24 05:14:12,847 - pos_N_scan_fast: 16 +2026-06-24 05:14:12,847 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:14:12,847 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:14:12,847 - probe_pmode_max: 6 +2026-06-24 05:14:12,847 - probe_pmode_init_pows: [0.02] +2026-06-24 05:14:12,847 - obj_omode_max: 1 +2026-06-24 05:14:12,847 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:14:12,847 - obj_Nlayer: 1 +2026-06-24 05:14:12,847 - obj_slice_thickness: 20.0 +2026-06-24 05:14:12,847 - simu_Npix: None +2026-06-24 05:14:12,847 - simu_match_mode: None +2026-06-24 05:14:12,847 - meas_permute: None +2026-06-24 05:14:12,847 - meas_reshape: [256, 128, 128] +2026-06-24 05:14:12,847 - meas_flipT: [0, 0, 0] +2026-06-24 05:14:12,847 - meas_crop: None +2026-06-24 05:14:12,847 - meas_pad: None +2026-06-24 05:14:12,847 - meas_resample: None +2026-06-24 05:14:12,847 - meas_add_source_size: None +2026-06-24 05:14:12,848 - meas_add_detector_blur: None +2026-06-24 05:14:12,848 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:14:12,848 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:14:12,848 - meas_add_poisson_noise: None +2026-06-24 05:14:12,848 - meas_export: None +2026-06-24 05:14:12,848 - probe_permute: None +2026-06-24 05:14:12,848 - probe_z_shift: None +2026-06-24 05:14:12,848 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:14:12,848 - pos_scan_flipT: None +2026-06-24 05:14:12,848 - pos_scan_affine: None +2026-06-24 05:14:12,848 - pos_scan_rand_std: 0.15 +2026-06-24 05:14:12,848 - obj_z_crop: None +2026-06-24 05:14:12,848 - obj_z_pad: None +2026-06-24 05:14:12,848 - obj_z_resample: None +2026-06-24 05:14:12,848 - meas_source: file +2026-06-24 05:14:12,848 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug7__sample_000010_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:14:12,848 - probe_source: simu +2026-06-24 05:14:12,848 - probe_params: None +2026-06-24 05:14:12,848 - pos_source: simu +2026-06-24 05:14:12,848 - pos_params: None +2026-06-24 05:14:12,848 - obj_source: simu +2026-06-24 05:14:12,848 - obj_params: None +2026-06-24 05:14:12,848 - tilt_source: simu +2026-06-24 05:14:12,848 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:14:12,848 - +2026-06-24 05:14:12,848 - ### Initializing cache ### +2026-06-24 05:14:12,848 - use_cached_obj = False +2026-06-24 05:14:12,848 - use_cached_probe = False +2026-06-24 05:14:12,848 - use_cached_pos = False +2026-06-24 05:14:12,848 - +2026-06-24 05:14:12,848 - ### Initializing measurements ### +2026-06-24 05:14:12,848 - Loading measurements from source = 'file' +2026-06-24 05:14:12,848 - Detected measurement file type = '.h5' +2026-06-24 05:14:12,927 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:14:12,927 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:14:12,929 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0048) +2026-06-24 05:14:12,929 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:14:12,929 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:14:12,931 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:14:12,931 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:14:12,932 - Normalizing by max of the 2D mean pattern intensity: 0.0037145331 +2026-06-24 05:14:12,932 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:14:12,934 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0164, 1.2878) +2026-06-24 05:14:12,934 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:14:12,935 - Pattern total int. statistics (min, mean, max) = (267.8049, 269.0427, 270.3538), with min/max = 99.1% +2026-06-24 05:14:12,938 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0164, 1.2878) +2026-06-24 05:14:12,938 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:14:12,938 - +2026-06-24 05:14:12,938 - ### Setting up calibration ### +2026-06-24 05:14:12,938 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:14:12,938 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:14:12,938 - Radius of fitted bright field disk (RBF) = 9.15 px with meas_Npix = 128 +2026-06-24 05:14:12,938 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1430 +2026-06-24 05:14:12,938 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:14:12,938 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:14:13,170 - Initial guess: center=(63.62, 63.62), radius=9.15, Gaussian blur std=0.50 +2026-06-24 05:14:13,182 - Final fit: center=(63.62, 63.62), radius=9.15, Gaussian blur std=0.69 +2026-06-24 05:14:13,183 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.27 px with Npix = 128 +2026-06-24 05:14:13,183 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:14:13,183 - +2026-06-24 05:14:13,183 - ### Setting init_variables dict ### +2026-06-24 05:14:13,183 - Derived values given input init_params: +2026-06-24 05:14:13,183 - kv = 200.0 kV +2026-06-24 05:14:13,183 - wavelength = 0.0251 Ang +2026-06-24 05:14:13,183 - conv_angle = 9.07798957824707 mrad +2026-06-24 05:14:13,183 - Npix = 128 px +2026-06-24 05:14:13,183 - dk = 0.0391 Ang^-1 +2026-06-24 05:14:13,183 - kMax = 2.5000 Ang^-1 +2026-06-24 05:14:13,183 - da = 0.9797 mrad +2026-06-24 05:14:13,183 - angleMax = 62.6984 mrad +2026-06-24 05:14:13,183 - RBF = 9.2665 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:14:13,183 - n_alpha = 6.9066 (# conv_angle) +2026-06-24 05:14:13,183 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:14:13,183 - Rayleigh-limited resolution = 1.6852 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:14:13,183 - Real space probe extent = 25.6000 Ang +2026-06-24 05:14:13,183 - +2026-06-24 05:14:13,183 - ### Initializing probe ### +2026-06-24 05:14:13,183 - Loading probe from source = 'simu' +2026-06-24 05:14:13,183 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:14:13,183 - Start simulating STEM probe +2026-06-24 05:14:13,184 - kv = 200.0 kV +2026-06-24 05:14:13,184 - wavelength = 0.0251 Ang +2026-06-24 05:14:13,184 - conv_angle = 9.07798957824707 mrad +2026-06-24 05:14:13,184 - Npix = 128 px +2026-06-24 05:14:13,184 - dk = 0.0391 Ang^-1 +2026-06-24 05:14:13,184 - kMax = 2.5000 Ang^-1 +2026-06-24 05:14:13,184 - alpha_max = 62.6984 mrad +2026-06-24 05:14:13,184 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:14:13,184 - Rayleigh-limited resolution = 1.6852 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:14:13,184 - Real space probe extent = 25.6000 Ang +2026-06-24 05:14:13,184 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:14:13,184 - ------------------------------------------------------------------------------------ +2026-06-24 05:14:13,184 - C1,0 C1 -285.3100 - Defocus (C10 = -df) +2026-06-24 05:14:13,184 - C1,2 A1 -1.1720 295.15 2-fold astigmatism +2026-06-24 05:14:13,184 - C2,1 3*B2 -161.3610 295.64 Axial coma +2026-06-24 05:14:13,184 - C2,3 A2 -352.7250 41.73 3-fold astigmatism +2026-06-24 05:14:13,184 - C3,0 C3 11467017.0000 - Spherical aberration +2026-06-24 05:14:13,184 - C3,2 4*S3 -843.1710 209.68 Axial star aberration +2026-06-24 05:14:13,184 - C3,4 A3 9674.2050 230.84 4-fold astigmatism +2026-06-24 05:14:13,184 - C4,1 4*B4 467392.0620 17.63 Axial coma(4th) +2026-06-24 05:14:13,184 - C4,3 4*D4 140097.5940 323.46 3-lobe aberration +2026-06-24 05:14:13,184 - C4,5 A4 227238.5620 303.43 5-fold astigmatism +2026-06-24 05:14:13,184 - C5,0 C5 13855129.0000 - Spherical aberration (5th) +2026-06-24 05:14:13,184 - C5,2 6*S5 -8144325.0000 12.77 Axial star aberration(5th) +2026-06-24 05:14:13,184 - C5,4 6*R5 -11617440.0000 16.81 4-lobe aberration +2026-06-24 05:14:13,184 - C5,6 A5 -1245309.2500 189.22 6-fold astigmatism +2026-06-24 05:14:13,187 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:14:13,187 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:14:13,188 - Creating 5 new probe modes from the major mode +2026-06-24 05:14:13,188 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:14:13,355 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:14:13,357 - Orthogonalizing 6 pmodes +2026-06-24 05:14:13,359 - Sorting 6 pmodes by their intensities +2026-06-24 05:14:13,360 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:14:13,361 - sum(|probe_data|**2) = 269.04, while meas_total_ints (min, mean, max) = (267.8049, 269.0427, 270.3538) +2026-06-24 05:14:13,361 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:14:13,361 - +2026-06-24 05:14:13,361 - ### Initializing probe positions ### +2026-06-24 05:14:13,361 - Loading probe positions from source = 'simu' +2026-06-24 05:14:13,361 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:14:13,361 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:14:13,361 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:14:13,363 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:14:13,363 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:14:13,363 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:14:13,363 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:14:13,363 - +2026-06-24 05:14:13,363 - ### Initializing object ### +2026-06-24 05:14:13,363 - Loading object from source = 'simu' +2026-06-24 05:14:13,364 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:14:13,365 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:14:13,365 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:14:13,365 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:14:13,365 - +2026-06-24 05:14:13,365 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:14:13,365 - omode_occu (omode) = float32, (1,) +2026-06-24 05:14:13,365 - +2026-06-24 05:14:13,366 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:14:13,366 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:14:13,366 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:14:13,366 - +2026-06-24 05:14:13,366 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:14:13,366 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:14:13,366 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:14:13,366 - +2026-06-24 05:14:13,366 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:14:13,366 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:14:13,366 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:14:13,367 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:14:13,367 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:14:13,367 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:14:13,367 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:14:13,367 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:14:13,367 - +2026-06-24 05:14:13,367 - ### Collecting reconstruction provenance ### +2026-06-24 05:14:13,367 - Reconstruction provenance is collected and initialized. +2026-06-24 05:14:13,367 - +2026-06-24 05:14:13,367 - ### Initializing loss function ### +2026-06-24 05:14:13,367 - Active loss types: +2026-06-24 05:14:13,367 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:14:13,367 - +2026-06-24 05:14:13,367 - ### Initializing constraint function ### +2026-06-24 05:14:13,367 - Active constraint types: +2026-06-24 05:14:13,367 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:14:13,367 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:14:13,367 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:14:13,367 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:14:13,367 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:14:13,367 - +2026-06-24 05:14:13,368 - ### Done initializing PtyRADSolver ### +2026-06-24 05:14:13,368 - +2026-06-24 05:14:13,491 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:14:13,491 - +2026-06-24 05:14:13,491 - ### Initializing PtychoModel model ### +2026-06-24 05:14:13,562 - ### PtychoModel optimizable variables ### +2026-06-24 05:14:13,562 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:14:13,562 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:14:13,562 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:14:13,562 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:14:13,562 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:14:13,562 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:14:13,562 - +2026-06-24 05:14:13,562 - ### Optimizable variables statitsics ### +2026-06-24 05:14:13,562 - Total measurement values : 4,194,304 +2026-06-24 05:14:13,562 - Total optimizing variables: 278,728 +2026-06-24 05:14:13,562 - Overdetermined ratio : 15.05 +2026-06-24 05:14:13,562 - +2026-06-24 05:14:13,562 - ### Model behavior ### +2026-06-24 05:14:13,562 - Tilt propagator : False +2026-06-24 05:14:13,563 - Change slice thickness : False +2026-06-24 05:14:13,563 - Detector blur : False +2026-06-24 05:14:13,563 - Preload data : True +2026-06-24 05:14:13,563 - On-the-fly meas padding : False +2026-06-24 05:14:13,563 - On-the-fly meas resample : False +2026-06-24 05:14:13,563 - On-the-fly simu match mode: None +2026-06-24 05:14:13,563 - +2026-06-24 05:14:13,604 - ### Done initializing PtychoModel model ### +2026-06-24 05:14:13,604 - +2026-06-24 05:14:13,604 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:14:13,604 - +2026-06-24 05:14:13,604 - ### Generating indices, batches, and output_path ### +2026-06-24 05:14:13,605 - d90 = 53.000 px or 10.600 Ang +2026-06-24 05:14:13,605 - Selecting indices with the 'full' mode +2026-06-24 05:14:14,067 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:14:14,146 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:14:14,146 - Original recon_dir_affixes = ['default'] +2026-06-24 05:14:14,146 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:14:14,152 - Path corrected for compatibility: +2026-06-24 05:14:14,152 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.15e+07_C32_-843_phi32_210_C34_9.67e+03_phi34_231_C41_4.67e+05_phi41_17.6_C43_1.4e+05_phi43_323_C45_2.27e+05_phi45_303_C50_1.39e+07_C52_-8.14e+06_phi52_12.8_C54_-1.16e+07_phi54_16.8_C56_-1.25e+06_phi56_189 +2026-06-24 05:14:14,152 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189 +2026-06-24 05:14:14,154 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189' is generated! +2026-06-24 05:14:14,311 - +2026-06-24 05:14:14,312 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/20260624_051414_ptyrad_log.txt ### +2026-06-24 05:14:14,312 - +2026-06-24 05:14:14,313 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:14:14,313 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:14:14,313 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:14:15,495 - Iter: 1, Total Loss: 0.9463, loss_single: 0.9463, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.434 sec +2026-06-24 05:14:15,533 - Iter: 2, Total Loss: 0.8856, loss_single: 0.8856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:14:15,568 - Iter: 3, Total Loss: 0.8336, loss_single: 0.8336, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,603 - Iter: 4, Total Loss: 0.7797, loss_single: 0.7797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,638 - Iter: 5, Total Loss: 0.7229, loss_single: 0.7229, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,674 - Iter: 6, Total Loss: 0.6669, loss_single: 0.6669, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:14:15,709 - Iter: 7, Total Loss: 0.6158, loss_single: 0.6158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,745 - Iter: 8, Total Loss: 0.5658, loss_single: 0.5658, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:14:15,782 - Iter: 9, Total Loss: 0.5282, loss_single: 0.5282, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:14:15,818 - Iter: 10, Total Loss: 0.4992, loss_single: 0.4992, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,853 - Iter: 11, Total Loss: 0.4684, loss_single: 0.4684, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,888 - Iter: 12, Total Loss: 0.4414, loss_single: 0.4414, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,924 - Iter: 13, Total Loss: 0.4167, loss_single: 0.4167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,959 - Iter: 14, Total Loss: 0.3943, loss_single: 0.3943, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:15,994 - Iter: 15, Total Loss: 0.3772, loss_single: 0.3772, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,029 - Iter: 16, Total Loss: 0.3635, loss_single: 0.3635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,063 - Iter: 17, Total Loss: 0.3524, loss_single: 0.3524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,099 - Iter: 18, Total Loss: 0.3438, loss_single: 0.3438, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,134 - Iter: 19, Total Loss: 0.3363, loss_single: 0.3363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,169 - Iter: 20, Total Loss: 0.3301, loss_single: 0.3301, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,204 - Iter: 21, Total Loss: 0.3251, loss_single: 0.3251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,240 - Iter: 22, Total Loss: 0.3204, loss_single: 0.3204, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,275 - Iter: 23, Total Loss: 0.3167, loss_single: 0.3167, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,310 - Iter: 24, Total Loss: 0.3138, loss_single: 0.3138, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,345 - Iter: 25, Total Loss: 0.3103, loss_single: 0.3103, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,380 - Iter: 26, Total Loss: 0.3067, loss_single: 0.3067, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,415 - Iter: 27, Total Loss: 0.3033, loss_single: 0.3033, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,450 - Iter: 28, Total Loss: 0.3014, loss_single: 0.3014, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,485 - Iter: 29, Total Loss: 0.3001, loss_single: 0.3001, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,520 - Iter: 30, Total Loss: 0.2982, loss_single: 0.2982, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,555 - Iter: 31, Total Loss: 0.2968, loss_single: 0.2968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,590 - Iter: 32, Total Loss: 0.2955, loss_single: 0.2955, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,626 - Iter: 33, Total Loss: 0.2939, loss_single: 0.2939, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,661 - Iter: 34, Total Loss: 0.2928, loss_single: 0.2928, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,696 - Iter: 35, Total Loss: 0.2918, loss_single: 0.2918, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,731 - Iter: 36, Total Loss: 0.2907, loss_single: 0.2907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,766 - Iter: 37, Total Loss: 0.2897, loss_single: 0.2897, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,801 - Iter: 38, Total Loss: 0.2885, loss_single: 0.2885, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,836 - Iter: 39, Total Loss: 0.2872, loss_single: 0.2872, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,871 - Iter: 40, Total Loss: 0.2860, loss_single: 0.2860, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,909 - Iter: 41, Total Loss: 0.2851, loss_single: 0.2851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:16,944 - Iter: 42, Total Loss: 0.2844, loss_single: 0.2844, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:14:16,979 - Iter: 43, Total Loss: 0.2834, loss_single: 0.2834, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,014 - Iter: 44, Total Loss: 0.2827, loss_single: 0.2827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,053 - Iter: 45, Total Loss: 0.2820, loss_single: 0.2820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:14:17,093 - Iter: 46, Total Loss: 0.2812, loss_single: 0.2812, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.040 sec +2026-06-24 05:14:17,128 - Iter: 47, Total Loss: 0.2805, loss_single: 0.2805, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,164 - Iter: 48, Total Loss: 0.2797, loss_single: 0.2797, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,199 - Iter: 49, Total Loss: 0.2790, loss_single: 0.2790, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,234 - Iter: 50, Total Loss: 0.2783, loss_single: 0.2783, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,269 - Iter: 51, Total Loss: 0.2776, loss_single: 0.2776, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,304 - Iter: 52, Total Loss: 0.2767, loss_single: 0.2767, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:14:17,339 - 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Saving summary figures for iter 100 +2026-06-24 05:14:22,691 - ### Finished 100 iterations, averaged iter_t = 0.03913 with std = 0.040 ### +2026-06-24 05:14:22,692 - +2026-06-24 05:14:22,692 - ### The PtyRADSolver is finished in 9.201 sec ### +2026-06-24 05:14:22,692 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..e255b3032494889097f6a7b27d48d14215acfecb Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/simulation_data_aug7__sample_000010.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/simulation_data_aug7__sample_000010.yaml new file mode 100644 index 0000000000000000000000000000000000000000..425b78beee73ddb1ea64072f94813a5a34d689e6 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010/gendata3_std_02__simulation_data_aug7__sample_000010_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-285_C12_-1.17_phi12_295_C21_-161_phi21_296_C23_-353_phi23_41.7_C30_1.1.25e+06_phi56_189/simulation_data_aug7__sample_000010.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.07798957824707 + probe_aberrations: + C10: -285.3104248046875 + C12: -1.1724512577056885 + C21: -161.36068725585938 + C23: -352.72454833984375 + C30: 11467017.0 + C32: -843.1707153320312 + C34: 9674.205078125 + C41: 467392.0625 + C43: 140097.59375 + C45: 227238.5625 + C50: 13855129.0 + C52: -8144325.0 + C54: -11617440.0 + C56: -1245309.25 + phi12: 295.1484566789088 + phi21: 295.6406947520133 + phi23: 41.72530803581149 + phi32: 209.68178050016232 + phi34: 230.83932964303065 + phi41: 17.633634276458025 + phi43: 323.45877116591123 + phi45: 303.4273016511246 + phi52: 12.766377440883472 + phi54: 16.812310858953165 + phi56: 189.21567872773105 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug7__sample_000010_measurement.h5 + key: measurement + random_seed: 20261763 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug7__sample_000010 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug7__sample_000010 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/20260624_052235_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/20260624_052235_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..8a3ede5b23cacaee9403b61870673a32f66aea30 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/20260624_052235_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:22:34,126 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:22:34,126 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:22:34,126 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:22:34,126 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:22:34,126 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:22:34,126 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:22:34,126 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:22:34,126 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:22:34,126 - +2026-06-24 05:22:34,235 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:22:34,235 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:22:34,235 - Accelerator.num_process = 1 +2026-06-24 05:22:34,235 - Accelerator.mixed_precision = no +2026-06-24 05:22:34,246 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:22:34,246 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:22:34,246 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:22:34,246 - +2026-06-24 05:22:34,246 - ### System information ### +2026-06-24 05:22:34,246 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:22:34,246 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:22:34,246 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:22:34,246 - Machine: x86_64 +2026-06-24 05:22:34,246 - Processor: x86_64 +2026-06-24 05:22:34,246 - Available CPU cores: 8 +2026-06-24 05:22:34,246 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:22:34,246 - +2026-06-24 05:22:34,246 - ### GPU information ### +2026-06-24 05:22:34,246 - CUDA Available: True +2026-06-24 05:22:34,246 - CUDA Version: 13.0 +2026-06-24 05:22:34,247 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:22:34,247 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:22:34,247 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:22:34,247 - In addition, Triton does not directly support Windows. +2026-06-24 05:22:34,247 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:22:34,262 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:22:34,262 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:22:34,262 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:22:34,262 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:22:34,262 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:22:34,262 - +2026-06-24 05:22:34,262 - ### Python information ### +2026-06-24 05:22:34,264 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:22:34,264 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:22:34,264 - +2026-06-24 05:22:34,264 - ### Packages information ### +2026-06-24 05:22:34,264 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:22:34,265 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:22:34,266 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:22:34,267 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:22:34,267 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:22:34,267 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:22:34,267 - +2026-06-24 05:22:34,267 - ### Loading params file ### +2026-06-24 05:22:34,267 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug8__sample_000016.yaml +2026-06-24 05:22:34,274 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:22:34,275 - Success! Params file validated and defaults applied. +2026-06-24 05:22:34,275 - +2026-06-24 05:22:34,275 - ### Setting GPU Device ### +2026-06-24 05:22:34,275 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:22:34,275 - +2026-06-24 05:22:34,275 - Random seed: 20261797 provided by params file +2026-06-24 05:22:34,275 - ### Initializing Initializer ### +2026-06-24 05:22:34,276 - init_params are displayed below: +2026-06-24 05:22:34,276 - random_seed: 20261797 +2026-06-24 05:22:34,276 - probe_illum_type: electron +2026-06-24 05:22:34,276 - probe_kv: 200.0 +2026-06-24 05:22:34,276 - probe_conv_angle: 9.134933471679688 +2026-06-24 05:22:34,276 - probe_aberrations: {'C10': -166.121, 'C12': 24.775, 'phi12': 49.88, 'C21': 186.499, 'phi21': 221.461, 'C23': 604.681, 'phi23': 131.992, 'C30': 10997134.0, 'C32': 10262.223, 'phi32': 48.091, 'C34': -10677.344, 'phi34': 134.074, 'C41': 384850.75, 'phi41': 157.819, 'C43': 2604.924, 'phi43': 230.187, 'C45': -130559.484, 'phi45': 279.591, 'C50': 15187763.0, 'C52': -3592998.0, 'phi52': 254.765, 'C54': -9284125.0, 'phi54': 99.31, 'C56': 5250988.0, 'phi56': 293.549} +2026-06-24 05:22:34,276 - beam_kev: None +2026-06-24 05:22:34,276 - probe_dRn: None +2026-06-24 05:22:34,276 - probe_Rn: None +2026-06-24 05:22:34,276 - probe_D_H: None +2026-06-24 05:22:34,276 - probe_D_FZP: None +2026-06-24 05:22:34,276 - probe_Ls: None +2026-06-24 05:22:34,276 - meas_Npix: 128 +2026-06-24 05:22:34,276 - pos_N_scans: 256 +2026-06-24 05:22:34,276 - pos_N_scan_slow: 16 +2026-06-24 05:22:34,276 - pos_N_scan_fast: 16 +2026-06-24 05:22:34,276 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:22:34,276 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:22:34,276 - probe_pmode_max: 6 +2026-06-24 05:22:34,276 - probe_pmode_init_pows: [0.02] +2026-06-24 05:22:34,276 - obj_omode_max: 1 +2026-06-24 05:22:34,276 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:22:34,276 - obj_Nlayer: 1 +2026-06-24 05:22:34,276 - obj_slice_thickness: 20.0 +2026-06-24 05:22:34,276 - simu_Npix: None +2026-06-24 05:22:34,276 - simu_match_mode: None +2026-06-24 05:22:34,276 - meas_permute: None +2026-06-24 05:22:34,276 - meas_reshape: [256, 128, 128] +2026-06-24 05:22:34,276 - meas_flipT: [0, 0, 0] +2026-06-24 05:22:34,276 - meas_crop: None +2026-06-24 05:22:34,276 - meas_pad: None +2026-06-24 05:22:34,276 - meas_resample: None +2026-06-24 05:22:34,276 - meas_add_source_size: None +2026-06-24 05:22:34,276 - meas_add_detector_blur: None +2026-06-24 05:22:34,276 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:22:34,277 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:22:34,277 - meas_add_poisson_noise: None +2026-06-24 05:22:34,277 - meas_export: None +2026-06-24 05:22:34,277 - probe_permute: None +2026-06-24 05:22:34,277 - probe_z_shift: None +2026-06-24 05:22:34,277 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:22:34,277 - pos_scan_flipT: None +2026-06-24 05:22:34,277 - pos_scan_affine: None +2026-06-24 05:22:34,277 - pos_scan_rand_std: 0.15 +2026-06-24 05:22:34,277 - obj_z_crop: None +2026-06-24 05:22:34,277 - obj_z_pad: None +2026-06-24 05:22:34,277 - obj_z_resample: None +2026-06-24 05:22:34,277 - meas_source: file +2026-06-24 05:22:34,277 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug8__sample_000016_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:22:34,277 - probe_source: simu +2026-06-24 05:22:34,277 - probe_params: None +2026-06-24 05:22:34,277 - pos_source: simu +2026-06-24 05:22:34,277 - pos_params: None +2026-06-24 05:22:34,277 - obj_source: simu +2026-06-24 05:22:34,277 - obj_params: None +2026-06-24 05:22:34,277 - tilt_source: simu +2026-06-24 05:22:34,277 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:22:34,277 - +2026-06-24 05:22:34,277 - ### Initializing cache ### +2026-06-24 05:22:34,277 - use_cached_obj = False +2026-06-24 05:22:34,277 - use_cached_probe = False +2026-06-24 05:22:34,277 - use_cached_pos = False +2026-06-24 05:22:34,277 - +2026-06-24 05:22:34,277 - ### Initializing measurements ### +2026-06-24 05:22:34,277 - Loading measurements from source = 'file' +2026-06-24 05:22:34,277 - Detected measurement file type = '.h5' +2026-06-24 05:22:34,356 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:22:34,356 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:22:34,358 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0043) +2026-06-24 05:22:34,358 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:22:34,358 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:22:34,359 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:22:34,359 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:22:34,360 - Normalizing by max of the 2D mean pattern intensity: 0.0036450145 +2026-06-24 05:22:34,361 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:22:34,362 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0167, 1.1772) +2026-06-24 05:22:34,363 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:22:34,364 - Pattern total int. statistics (min, mean, max) = (272.9092, 274.0356, 275.3064), with min/max = 99.1% +2026-06-24 05:22:34,365 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0167, 1.1772) +2026-06-24 05:22:34,365 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:22:34,365 - +2026-06-24 05:22:34,365 - ### Setting up calibration ### +2026-06-24 05:22:34,365 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:22:34,365 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:22:34,365 - Radius of fitted bright field disk (RBF) = 9.18 px with meas_Npix = 128 +2026-06-24 05:22:34,365 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1435 +2026-06-24 05:22:34,365 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:22:34,365 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:22:34,582 - Initial guess: center=(63.64, 63.62), radius=9.18, Gaussian blur std=0.50 +2026-06-24 05:22:34,592 - Final fit: center=(63.64, 63.62), radius=9.18, Gaussian blur std=0.60 +2026-06-24 05:22:34,592 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.32 px with Npix = 128 +2026-06-24 05:22:34,592 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:22:34,593 - +2026-06-24 05:22:34,593 - ### Setting init_variables dict ### +2026-06-24 05:22:34,593 - Derived values given input init_params: +2026-06-24 05:22:34,593 - kv = 200.0 kV +2026-06-24 05:22:34,593 - wavelength = 0.0251 Ang +2026-06-24 05:22:34,593 - conv_angle = 9.134933471679688 mrad +2026-06-24 05:22:34,593 - Npix = 128 px +2026-06-24 05:22:34,593 - dk = 0.0391 Ang^-1 +2026-06-24 05:22:34,593 - kMax = 2.5000 Ang^-1 +2026-06-24 05:22:34,593 - da = 0.9797 mrad +2026-06-24 05:22:34,593 - angleMax = 62.6984 mrad +2026-06-24 05:22:34,593 - RBF = 9.3246 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:22:34,593 - n_alpha = 6.8636 (# conv_angle) +2026-06-24 05:22:34,593 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:22:34,593 - Rayleigh-limited resolution = 1.6747 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:22:34,593 - Real space probe extent = 25.6000 Ang +2026-06-24 05:22:34,593 - +2026-06-24 05:22:34,593 - ### Initializing probe ### +2026-06-24 05:22:34,593 - Loading probe from source = 'simu' +2026-06-24 05:22:34,593 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:22:34,593 - Start simulating STEM probe +2026-06-24 05:22:34,593 - kv = 200.0 kV +2026-06-24 05:22:34,593 - wavelength = 0.0251 Ang +2026-06-24 05:22:34,593 - conv_angle = 9.134933471679688 mrad +2026-06-24 05:22:34,593 - Npix = 128 px +2026-06-24 05:22:34,593 - dk = 0.0391 Ang^-1 +2026-06-24 05:22:34,594 - kMax = 2.5000 Ang^-1 +2026-06-24 05:22:34,594 - alpha_max = 62.6984 mrad +2026-06-24 05:22:34,594 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:22:34,594 - Rayleigh-limited resolution = 1.6747 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:22:34,594 - Real space probe extent = 25.6000 Ang +2026-06-24 05:22:34,594 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:22:34,594 - ----------------------------------------------------------------------------------- +2026-06-24 05:22:34,594 - C1,0 C1 -166.1210 - Defocus (C10 = -df) +2026-06-24 05:22:34,594 - C1,2 A1 24.7750 49.88 2-fold astigmatism +2026-06-24 05:22:34,594 - C2,1 3*B2 186.4990 221.46 Axial coma +2026-06-24 05:22:34,594 - C2,3 A2 604.6810 131.99 3-fold astigmatism +2026-06-24 05:22:34,594 - C3,0 C3 10997134.0000 - Spherical aberration +2026-06-24 05:22:34,594 - C3,2 4*S3 10262.2230 48.09 Axial star aberration +2026-06-24 05:22:34,594 - C3,4 A3 -10677.3440 134.07 4-fold astigmatism +2026-06-24 05:22:34,594 - C4,1 4*B4 384850.7500 157.82 Axial coma(4th) +2026-06-24 05:22:34,594 - C4,3 4*D4 2604.9240 230.19 3-lobe aberration +2026-06-24 05:22:34,594 - C4,5 A4 -130559.4840 279.59 5-fold astigmatism +2026-06-24 05:22:34,594 - C5,0 C5 15187763.0000 - Spherical aberration (5th) +2026-06-24 05:22:34,594 - C5,2 6*S5 -3592998.0000 254.76 Axial star aberration(5th) +2026-06-24 05:22:34,594 - C5,4 6*R5 -9284125.0000 99.31 4-lobe aberration +2026-06-24 05:22:34,594 - C5,6 A5 5250988.0000 293.55 6-fold astigmatism +2026-06-24 05:22:34,597 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:22:34,597 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:22:34,597 - Creating 5 new probe modes from the major mode +2026-06-24 05:22:34,597 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:22:34,703 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:22:34,704 - Orthogonalizing 6 pmodes +2026-06-24 05:22:34,707 - Sorting 6 pmodes by their intensities +2026-06-24 05:22:34,707 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:22:34,708 - sum(|probe_data|**2) = 274.04, while meas_total_ints (min, mean, max) = (272.9092, 274.0356, 275.3064) +2026-06-24 05:22:34,708 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:22:34,708 - +2026-06-24 05:22:34,708 - ### Initializing probe positions ### +2026-06-24 05:22:34,708 - Loading probe positions from source = 'simu' +2026-06-24 05:22:34,708 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:22:34,708 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:22:34,708 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:22:34,710 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:22:34,710 - crop_pos 1st and last px coords (y,x) = ([16, 16], [55, 56]) +2026-06-24 05:22:34,711 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:22:34,711 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:22:34,711 - +2026-06-24 05:22:34,711 - ### Initializing object ### +2026-06-24 05:22:34,711 - Loading object from source = 'simu' +2026-06-24 05:22:34,711 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:22:34,712 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:22:34,712 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:22:34,713 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:22:34,713 - +2026-06-24 05:22:34,713 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:22:34,713 - omode_occu (omode) = float32, (1,) +2026-06-24 05:22:34,713 - +2026-06-24 05:22:34,713 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:22:34,713 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:22:34,713 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:22:34,713 - +2026-06-24 05:22:34,714 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:22:34,714 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:22:34,714 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:22:34,714 - +2026-06-24 05:22:34,714 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:22:34,714 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:22:34,714 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:22:34,714 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:22:34,714 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:22:34,714 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:22:34,714 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:22:34,714 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:22:34,714 - +2026-06-24 05:22:34,714 - ### Collecting reconstruction provenance ### +2026-06-24 05:22:34,714 - Reconstruction provenance is collected and initialized. +2026-06-24 05:22:34,714 - +2026-06-24 05:22:34,714 - ### Initializing loss function ### +2026-06-24 05:22:34,714 - Active loss types: +2026-06-24 05:22:34,714 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:22:34,714 - +2026-06-24 05:22:34,715 - ### Initializing constraint function ### +2026-06-24 05:22:34,715 - Active constraint types: +2026-06-24 05:22:34,715 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:22:34,715 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:22:34,715 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:22:34,715 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:22:34,715 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:22:34,715 - +2026-06-24 05:22:34,715 - ### Done initializing PtyRADSolver ### +2026-06-24 05:22:34,715 - +2026-06-24 05:22:34,840 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:22:34,840 - +2026-06-24 05:22:34,841 - ### Initializing PtychoModel model ### +2026-06-24 05:22:34,912 - ### PtychoModel optimizable variables ### +2026-06-24 05:22:34,912 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:22:34,912 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:22:34,912 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:22:34,912 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:22:34,912 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:22:34,912 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:22:34,913 - +2026-06-24 05:22:34,913 - ### Optimizable variables statitsics ### +2026-06-24 05:22:34,913 - Total measurement values : 4,194,304 +2026-06-24 05:22:34,913 - Total optimizing variables: 278,728 +2026-06-24 05:22:34,913 - Overdetermined ratio : 15.05 +2026-06-24 05:22:34,913 - +2026-06-24 05:22:34,913 - ### Model behavior ### +2026-06-24 05:22:34,913 - Tilt propagator : False +2026-06-24 05:22:34,913 - Change slice thickness : False +2026-06-24 05:22:34,913 - Detector blur : False +2026-06-24 05:22:34,913 - Preload data : True +2026-06-24 05:22:34,913 - On-the-fly meas padding : False +2026-06-24 05:22:34,913 - On-the-fly meas resample : False +2026-06-24 05:22:34,913 - On-the-fly simu match mode: None +2026-06-24 05:22:34,913 - +2026-06-24 05:22:34,954 - ### Done initializing PtychoModel model ### +2026-06-24 05:22:34,954 - +2026-06-24 05:22:34,954 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:22:34,954 - +2026-06-24 05:22:34,954 - ### Generating indices, batches, and output_path ### +2026-06-24 05:22:34,956 - d90 = 61.000 px or 12.200 Ang +2026-06-24 05:22:34,956 - Selecting indices with the 'full' mode +2026-06-24 05:22:35,421 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:22:35,498 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:22:35,498 - Original recon_dir_affixes = ['default'] +2026-06-24 05:22:35,498 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:22:35,505 - Path corrected for compatibility: +2026-06-24 05:22:35,505 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+07_C32_1.03e+04_phi32_48.1_C34_-1.07e+04_phi34_134_C41_3.85e+05_phi41_158_C43_2.6e+03_phi43_230_C45_-1.31e+05_phi45_280_C50_1.52e+07_C52_-3.59e+06_phi52_255_C54_-9.28e+06_phi54_99.3_C56_5.25e+06_phi56_294 +2026-06-24 05:22:35,505 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294 +2026-06-24 05:22:35,506 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294' is generated! +2026-06-24 05:22:35,662 - +2026-06-24 05:22:35,663 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/20260624_052235_ptyrad_log.txt ### +2026-06-24 05:22:35,663 - +2026-06-24 05:22:35,665 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:22:35,665 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:22:35,665 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:22:36,922 - Iter: 1, Total Loss: 0.9415, loss_single: 0.9415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.458 sec +2026-06-24 05:22:36,959 - Iter: 2, Total Loss: 0.8851, loss_single: 0.8851, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:22:36,995 - Iter: 3, Total Loss: 0.8408, loss_single: 0.8408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:22:37,031 - Iter: 4, Total Loss: 0.7974, loss_single: 0.7974, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,067 - Iter: 5, Total Loss: 0.7559, loss_single: 0.7559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,103 - Iter: 6, Total Loss: 0.7133, loss_single: 0.7133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,138 - Iter: 7, Total Loss: 0.6710, loss_single: 0.6710, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,173 - Iter: 8, Total Loss: 0.6314, loss_single: 0.6314, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,209 - Iter: 9, Total Loss: 0.5896, loss_single: 0.5896, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,244 - Iter: 10, Total Loss: 0.5478, loss_single: 0.5478, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,280 - Iter: 11, Total Loss: 0.5084, loss_single: 0.5084, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,316 - Iter: 12, Total Loss: 0.4717, loss_single: 0.4717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:22:37,353 - Iter: 13, Total Loss: 0.4328, loss_single: 0.4328, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:22:37,389 - Iter: 14, Total Loss: 0.3979, loss_single: 0.3979, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,425 - Iter: 15, Total Loss: 0.3726, loss_single: 0.3726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,460 - Iter: 16, Total Loss: 0.3566, loss_single: 0.3566, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,495 - Iter: 17, Total Loss: 0.3411, loss_single: 0.3411, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,531 - Iter: 18, Total Loss: 0.3249, loss_single: 0.3249, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,567 - Iter: 19, Total Loss: 0.3137, loss_single: 0.3137, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,602 - Iter: 20, Total Loss: 0.3043, loss_single: 0.3043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,637 - Iter: 21, Total Loss: 0.2968, loss_single: 0.2968, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,674 - Iter: 22, Total Loss: 0.2893, loss_single: 0.2893, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:22:37,709 - Iter: 23, Total Loss: 0.2842, loss_single: 0.2842, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,745 - Iter: 24, Total Loss: 0.2814, loss_single: 0.2814, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,780 - Iter: 25, Total Loss: 0.2777, loss_single: 0.2777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,815 - Iter: 26, Total Loss: 0.2742, loss_single: 0.2742, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,851 - Iter: 27, Total Loss: 0.2718, loss_single: 0.2718, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,887 - Iter: 28, Total Loss: 0.2698, loss_single: 0.2698, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,922 - Iter: 29, Total Loss: 0.2680, loss_single: 0.2680, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,958 - Iter: 30, Total Loss: 0.2666, loss_single: 0.2666, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:37,994 - Iter: 31, Total Loss: 0.2652, loss_single: 0.2652, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,032 - Iter: 32, Total Loss: 0.2640, loss_single: 0.2640, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec +2026-06-24 05:22:38,067 - Iter: 33, Total Loss: 0.2631, loss_single: 0.2631, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,103 - Iter: 34, Total Loss: 0.2624, loss_single: 0.2624, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,139 - Iter: 35, Total Loss: 0.2618, loss_single: 0.2618, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,174 - Iter: 36, Total Loss: 0.2613, loss_single: 0.2613, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,210 - Iter: 37, Total Loss: 0.2609, loss_single: 0.2609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:22:38,246 - Iter: 38, Total Loss: 0.2605, loss_single: 0.2605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,281 - Iter: 39, Total Loss: 0.2602, loss_single: 0.2602, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,317 - Iter: 40, Total Loss: 0.2599, loss_single: 0.2599, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:22:38,355 - 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Saving summary figures for iter 100 +2026-06-24 05:22:44,257 - ### Finished 100 iterations, averaged iter_t = 0.039545 with std = 0.042 ### +2026-06-24 05:22:44,257 - +2026-06-24 05:22:44,258 - ### The PtyRADSolver is finished in 9.417 sec ### +2026-06-24 05:22:44,258 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..a2ac6ce88e6af96dfeacd87afbeb3923d97c2c34 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/simulation_data_aug8__sample_000016.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/simulation_data_aug8__sample_000016.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3292e9db4dcaa38e1ad4adc3f0f8ced6ec73eedb --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016/gendata3_std_02__simulation_data_aug8__sample_000016_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-166_C12_24.8_phi12_49.9_C21_186_phi21_221_C23_605_phi23_132_C30_1.1e+0.25e+06_phi56_294/simulation_data_aug8__sample_000016.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.134933471679688 + probe_aberrations: + C10: -166.12142944335938 + C12: 24.775285720825195 + C21: 186.498779296875 + C23: 604.6806640625 + C30: 10997134.0 + C32: 10262.22265625 + C34: -10677.34375 + C41: 384850.75 + C43: 2604.923583984375 + C45: -130559.484375 + C50: 15187763.0 + C52: -3592998.0 + C54: -9284125.0 + C56: 5250988.0 + phi12: 49.87972403682256 + phi21: 221.46120670503635 + phi23: 131.99176646509562 + phi32: 48.09136877624895 + phi34: 134.0740179354657 + phi41: 157.81852854723306 + phi43: 230.1871285395645 + phi45: 279.5913074856141 + phi52: 254.7652637395319 + phi54: 99.31005577720413 + phi56: 293.54871709226506 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug8__sample_000016_measurement.h5 + key: measurement + random_seed: 20261797 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug8__sample_000016 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug8__sample_000016 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/20260624_053156_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/20260624_053156_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..581b5d2a67c0ab3f72c63e3d58db6995222c4c76 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/20260624_053156_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:31:55,416 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:31:55,416 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:31:55,416 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:31:55,416 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:31:55,416 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:31:55,416 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:31:55,416 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:31:55,416 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:31:55,416 - +2026-06-24 05:31:55,523 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:31:55,523 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:31:55,523 - Accelerator.num_process = 1 +2026-06-24 05:31:55,523 - Accelerator.mixed_precision = no +2026-06-24 05:31:55,534 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:31:55,534 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:31:55,534 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:31:55,534 - +2026-06-24 05:31:55,534 - ### System information ### +2026-06-24 05:31:55,534 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:31:55,534 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:31:55,534 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:31:55,534 - Machine: x86_64 +2026-06-24 05:31:55,534 - Processor: x86_64 +2026-06-24 05:31:55,534 - Available CPU cores: 8 +2026-06-24 05:31:55,534 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:31:55,534 - +2026-06-24 05:31:55,534 - ### GPU information ### +2026-06-24 05:31:55,534 - CUDA Available: True +2026-06-24 05:31:55,534 - CUDA Version: 13.0 +2026-06-24 05:31:55,535 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:31:55,535 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:31:55,535 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:31:55,535 - In addition, Triton does not directly support Windows. +2026-06-24 05:31:55,535 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:31:55,549 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:31:55,549 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:31:55,550 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:31:55,550 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:31:55,550 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:31:55,550 - +2026-06-24 05:31:55,550 - ### Python information ### +2026-06-24 05:31:55,552 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:31:55,552 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:31:55,552 - +2026-06-24 05:31:55,552 - ### Packages information ### +2026-06-24 05:31:55,552 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:31:55,553 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:31:55,554 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:31:55,555 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:31:55,555 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:31:55,555 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:31:55,555 - +2026-06-24 05:31:55,555 - ### Loading params file ### +2026-06-24 05:31:55,555 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug9__sample_000025.yaml +2026-06-24 05:31:55,562 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:31:55,563 - Success! Params file validated and defaults applied. +2026-06-24 05:31:55,563 - +2026-06-24 05:31:55,563 - ### Setting GPU Device ### +2026-06-24 05:31:55,563 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:31:55,563 - +2026-06-24 05:31:55,563 - Random seed: 20261835 provided by params file +2026-06-24 05:31:55,564 - ### Initializing Initializer ### +2026-06-24 05:31:55,564 - init_params are displayed below: +2026-06-24 05:31:55,564 - random_seed: 20261835 +2026-06-24 05:31:55,564 - probe_illum_type: electron +2026-06-24 05:31:55,564 - probe_kv: 200.0 +2026-06-24 05:31:55,564 - probe_conv_angle: 9.48544979095459 +2026-06-24 05:31:55,564 - probe_aberrations: {'C10': -453.509, 'C12': -31.05, 'phi12': 288.556, 'C21': 912.854, 'phi21': 189.971, 'C23': -457.985, 'phi23': 359.048, 'C30': 12621951.0, 'C32': 2460.501, 'phi32': 213.188, 'C34': -5030.215, 'phi34': 265.654, 'C41': -50887.551, 'phi41': 81.716, 'C43': 122482.523, 'phi43': 201.053, 'C45': -452649.5, 'phi45': 146.956, 'C50': 14640464.0, 'C52': -5129790.0, 'phi52': 99.133, 'C54': 16033307.0, 'phi54': 257.35, 'C56': 10793937.0, 'phi56': 128.103} +2026-06-24 05:31:55,564 - beam_kev: None +2026-06-24 05:31:55,564 - probe_dRn: None +2026-06-24 05:31:55,564 - probe_Rn: None +2026-06-24 05:31:55,564 - probe_D_H: None +2026-06-24 05:31:55,564 - probe_D_FZP: None +2026-06-24 05:31:55,564 - probe_Ls: None +2026-06-24 05:31:55,564 - meas_Npix: 128 +2026-06-24 05:31:55,564 - pos_N_scans: 256 +2026-06-24 05:31:55,564 - pos_N_scan_slow: 16 +2026-06-24 05:31:55,564 - pos_N_scan_fast: 16 +2026-06-24 05:31:55,564 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:31:55,564 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:31:55,564 - probe_pmode_max: 6 +2026-06-24 05:31:55,564 - probe_pmode_init_pows: [0.02] +2026-06-24 05:31:55,564 - obj_omode_max: 1 +2026-06-24 05:31:55,564 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:31:55,564 - obj_Nlayer: 1 +2026-06-24 05:31:55,564 - obj_slice_thickness: 20.0 +2026-06-24 05:31:55,564 - simu_Npix: None +2026-06-24 05:31:55,564 - simu_match_mode: None +2026-06-24 05:31:55,564 - meas_permute: None +2026-06-24 05:31:55,564 - meas_reshape: [256, 128, 128] +2026-06-24 05:31:55,564 - meas_flipT: [0, 0, 0] +2026-06-24 05:31:55,564 - meas_crop: None +2026-06-24 05:31:55,564 - meas_pad: None +2026-06-24 05:31:55,565 - meas_resample: None +2026-06-24 05:31:55,565 - meas_add_source_size: None +2026-06-24 05:31:55,565 - meas_add_detector_blur: None +2026-06-24 05:31:55,565 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:31:55,565 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:31:55,565 - meas_add_poisson_noise: None +2026-06-24 05:31:55,565 - meas_export: None +2026-06-24 05:31:55,565 - probe_permute: None +2026-06-24 05:31:55,565 - probe_z_shift: None +2026-06-24 05:31:55,565 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:31:55,565 - pos_scan_flipT: None +2026-06-24 05:31:55,565 - pos_scan_affine: None +2026-06-24 05:31:55,565 - pos_scan_rand_std: 0.15 +2026-06-24 05:31:55,565 - obj_z_crop: None +2026-06-24 05:31:55,565 - obj_z_pad: None +2026-06-24 05:31:55,565 - obj_z_resample: None +2026-06-24 05:31:55,565 - meas_source: file +2026-06-24 05:31:55,565 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000025_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:31:55,565 - probe_source: simu +2026-06-24 05:31:55,565 - probe_params: None +2026-06-24 05:31:55,565 - pos_source: simu +2026-06-24 05:31:55,565 - pos_params: None +2026-06-24 05:31:55,565 - obj_source: simu +2026-06-24 05:31:55,565 - obj_params: None +2026-06-24 05:31:55,565 - tilt_source: simu +2026-06-24 05:31:55,565 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:31:55,565 - +2026-06-24 05:31:55,565 - ### Initializing cache ### +2026-06-24 05:31:55,565 - use_cached_obj = False +2026-06-24 05:31:55,565 - use_cached_probe = False +2026-06-24 05:31:55,565 - use_cached_pos = False +2026-06-24 05:31:55,565 - +2026-06-24 05:31:55,565 - ### Initializing measurements ### +2026-06-24 05:31:55,565 - Loading measurements from source = 'file' +2026-06-24 05:31:55,565 - Detected measurement file type = '.h5' +2026-06-24 05:31:55,642 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:31:55,643 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:31:55,644 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0044) +2026-06-24 05:31:55,644 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:31:55,644 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:31:55,646 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:31:55,646 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:31:55,647 - Normalizing by max of the 2D mean pattern intensity: 0.0033868325 +2026-06-24 05:31:55,648 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:31:55,649 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0180, 1.2985) +2026-06-24 05:31:55,649 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:31:55,651 - Pattern total int. statistics (min, mean, max) = (292.3333, 294.9029, 297.0320), with min/max = 98.4% +2026-06-24 05:31:55,652 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0180, 1.2985) +2026-06-24 05:31:55,652 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:31:55,652 - +2026-06-24 05:31:55,652 - ### Setting up calibration ### +2026-06-24 05:31:55,652 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:31:55,652 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:31:55,652 - Radius of fitted bright field disk (RBF) = 9.57 px with meas_Npix = 128 +2026-06-24 05:31:55,652 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1496 +2026-06-24 05:31:55,652 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:31:55,652 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:31:55,875 - Initial guess: center=(63.63, 63.61), radius=9.57, Gaussian blur std=0.50 +2026-06-24 05:31:55,886 - Final fit: center=(63.63, 63.61), radius=9.57, Gaussian blur std=0.58 +2026-06-24 05:31:55,886 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.68 px with Npix = 128 +2026-06-24 05:31:55,886 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:31:55,886 - +2026-06-24 05:31:55,886 - ### Setting init_variables dict ### +2026-06-24 05:31:55,886 - Derived values given input init_params: +2026-06-24 05:31:55,886 - kv = 200.0 kV +2026-06-24 05:31:55,886 - wavelength = 0.0251 Ang +2026-06-24 05:31:55,886 - conv_angle = 9.48544979095459 mrad +2026-06-24 05:31:55,886 - Npix = 128 px +2026-06-24 05:31:55,886 - dk = 0.0391 Ang^-1 +2026-06-24 05:31:55,886 - kMax = 2.5000 Ang^-1 +2026-06-24 05:31:55,886 - da = 0.9797 mrad +2026-06-24 05:31:55,886 - angleMax = 62.6984 mrad +2026-06-24 05:31:55,886 - RBF = 9.6824 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:31:55,886 - n_alpha = 6.6100 (# conv_angle) +2026-06-24 05:31:55,886 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:31:55,886 - Rayleigh-limited resolution = 1.6128 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:31:55,886 - Real space probe extent = 25.6000 Ang +2026-06-24 05:31:55,886 - +2026-06-24 05:31:55,886 - ### Initializing probe ### +2026-06-24 05:31:55,887 - Loading probe from source = 'simu' +2026-06-24 05:31:55,887 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:31:55,887 - Start simulating STEM probe +2026-06-24 05:31:55,887 - kv = 200.0 kV +2026-06-24 05:31:55,887 - wavelength = 0.0251 Ang +2026-06-24 05:31:55,887 - conv_angle = 9.48544979095459 mrad +2026-06-24 05:31:55,887 - Npix = 128 px +2026-06-24 05:31:55,887 - dk = 0.0391 Ang^-1 +2026-06-24 05:31:55,887 - kMax = 2.5000 Ang^-1 +2026-06-24 05:31:55,887 - alpha_max = 62.6984 mrad +2026-06-24 05:31:55,887 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:31:55,887 - Rayleigh-limited resolution = 1.6128 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:31:55,887 - Real space probe extent = 25.6000 Ang +2026-06-24 05:31:55,887 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:31:55,887 - ----------------------------------------------------------------------------------- +2026-06-24 05:31:55,887 - C1,0 C1 -453.5090 - Defocus (C10 = -df) +2026-06-24 05:31:55,887 - C1,2 A1 -31.0500 288.56 2-fold astigmatism +2026-06-24 05:31:55,887 - C2,1 3*B2 912.8540 189.97 Axial coma +2026-06-24 05:31:55,887 - C2,3 A2 -457.9850 359.05 3-fold astigmatism +2026-06-24 05:31:55,887 - C3,0 C3 12621951.0000 - Spherical aberration +2026-06-24 05:31:55,887 - C3,2 4*S3 2460.5010 213.19 Axial star aberration +2026-06-24 05:31:55,887 - C3,4 A3 -5030.2150 265.65 4-fold astigmatism +2026-06-24 05:31:55,887 - C4,1 4*B4 -50887.5510 81.72 Axial coma(4th) +2026-06-24 05:31:55,887 - C4,3 4*D4 122482.5230 201.05 3-lobe aberration +2026-06-24 05:31:55,888 - C4,5 A4 -452649.5000 146.96 5-fold astigmatism +2026-06-24 05:31:55,888 - C5,0 C5 14640464.0000 - Spherical aberration (5th) +2026-06-24 05:31:55,888 - C5,2 6*S5 -5129790.0000 99.13 Axial star aberration(5th) +2026-06-24 05:31:55,888 - C5,4 6*R5 16033307.0000 257.35 4-lobe aberration +2026-06-24 05:31:55,888 - C5,6 A5 10793937.0000 128.10 6-fold astigmatism +2026-06-24 05:31:55,890 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:31:55,890 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:31:55,891 - Creating 5 new probe modes from the major mode +2026-06-24 05:31:55,891 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:31:55,994 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:31:55,995 - Orthogonalizing 6 pmodes +2026-06-24 05:31:55,997 - Sorting 6 pmodes by their intensities +2026-06-24 05:31:55,997 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:31:55,998 - sum(|probe_data|**2) = 294.90, while meas_total_ints (min, mean, max) = (292.3333, 294.9029, 297.0320) +2026-06-24 05:31:55,998 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:31:55,998 - +2026-06-24 05:31:55,998 - ### Initializing probe positions ### +2026-06-24 05:31:55,998 - Loading probe positions from source = 'simu' +2026-06-24 05:31:55,998 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:31:55,998 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:31:55,998 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:31:56,001 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:31:56,001 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:31:56,001 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:31:56,001 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:31:56,001 - +2026-06-24 05:31:56,001 - ### Initializing object ### +2026-06-24 05:31:56,001 - Loading object from source = 'simu' +2026-06-24 05:31:56,001 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:31:56,002 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:31:56,002 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:31:56,003 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:31:56,003 - +2026-06-24 05:31:56,003 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:31:56,003 - omode_occu (omode) = float32, (1,) +2026-06-24 05:31:56,003 - +2026-06-24 05:31:56,003 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:31:56,003 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:31:56,004 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:31:56,004 - +2026-06-24 05:31:56,004 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:31:56,004 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:31:56,004 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:31:56,004 - +2026-06-24 05:31:56,004 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:31:56,004 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:31:56,004 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:31:56,004 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:31:56,004 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:31:56,004 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:31:56,004 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:31:56,004 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:31:56,004 - +2026-06-24 05:31:56,004 - ### Collecting reconstruction provenance ### +2026-06-24 05:31:56,004 - Reconstruction provenance is collected and initialized. +2026-06-24 05:31:56,004 - +2026-06-24 05:31:56,004 - ### Initializing loss function ### +2026-06-24 05:31:56,004 - Active loss types: +2026-06-24 05:31:56,004 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:31:56,005 - +2026-06-24 05:31:56,005 - ### Initializing constraint function ### +2026-06-24 05:31:56,005 - Active constraint types: +2026-06-24 05:31:56,005 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:31:56,005 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:31:56,005 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:31:56,005 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:31:56,005 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:31:56,005 - +2026-06-24 05:31:56,005 - ### Done initializing PtyRADSolver ### +2026-06-24 05:31:56,005 - +2026-06-24 05:31:56,131 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:31:56,131 - +2026-06-24 05:31:56,131 - ### Initializing PtychoModel model ### +2026-06-24 05:31:56,202 - ### PtychoModel optimizable variables ### +2026-06-24 05:31:56,203 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:31:56,203 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:31:56,203 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:31:56,203 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:31:56,203 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:31:56,203 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:31:56,203 - +2026-06-24 05:31:56,203 - ### Optimizable variables statitsics ### +2026-06-24 05:31:56,203 - Total measurement values : 4,194,304 +2026-06-24 05:31:56,203 - Total optimizing variables: 278,728 +2026-06-24 05:31:56,203 - Overdetermined ratio : 15.05 +2026-06-24 05:31:56,203 - +2026-06-24 05:31:56,203 - ### Model behavior ### +2026-06-24 05:31:56,203 - Tilt propagator : False +2026-06-24 05:31:56,203 - Change slice thickness : False +2026-06-24 05:31:56,203 - Detector blur : False +2026-06-24 05:31:56,203 - Preload data : True +2026-06-24 05:31:56,203 - On-the-fly meas padding : False +2026-06-24 05:31:56,203 - On-the-fly meas resample : False +2026-06-24 05:31:56,203 - On-the-fly simu match mode: None +2026-06-24 05:31:56,203 - +2026-06-24 05:31:56,245 - ### Done initializing PtychoModel model ### +2026-06-24 05:31:56,245 - +2026-06-24 05:31:56,245 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:31:56,245 - +2026-06-24 05:31:56,245 - ### Generating indices, batches, and output_path ### +2026-06-24 05:31:56,246 - d90 = 51.000 px or 10.200 Ang +2026-06-24 05:31:56,246 - Selecting indices with the 'full' mode +2026-06-24 05:31:56,710 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:31:56,786 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:31:56,786 - Original recon_dir_affixes = ['default'] +2026-06-24 05:31:56,786 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:31:56,792 - Path corrected for compatibility: +2026-06-24 05:31:56,792 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e+07_C32_2.46e+03_phi32_213_C34_-5.03e+03_phi34_266_C41_-5.09e+04_phi41_81.7_C43_1.22e+05_phi43_201_C45_-4.53e+05_phi45_147_C50_1.46e+07_C52_-5.13e+06_phi52_99.1_C54_1.6e+07_phi54_257_C56_1.08e+07_phi56_128 +2026-06-24 05:31:56,792 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128 +2026-06-24 05:31:56,793 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128' is generated! +2026-06-24 05:31:56,944 - +2026-06-24 05:31:56,945 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/20260624_053156_ptyrad_log.txt ### +2026-06-24 05:31:56,945 - +2026-06-24 05:31:56,947 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:31:56,947 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:31:56,947 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:31:58,143 - Iter: 1, Total Loss: 0.9497, loss_single: 0.9497, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:31:58,180 - Iter: 2, Total Loss: 0.8981, loss_single: 0.8981, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:31:58,215 - Iter: 3, Total Loss: 0.8561, loss_single: 0.8561, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:31:58,250 - Iter: 4, Total Loss: 0.8173, loss_single: 0.8173, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:31:58,286 - Iter: 5, Total Loss: 0.7907, loss_single: 0.7907, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,321 - Iter: 6, Total Loss: 0.7654, loss_single: 0.7654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,355 - Iter: 7, Total Loss: 0.7342, loss_single: 0.7342, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:31:58,391 - Iter: 8, Total Loss: 0.7003, loss_single: 0.7003, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,426 - Iter: 9, Total Loss: 0.6736, loss_single: 0.6736, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,461 - Iter: 10, Total Loss: 0.6526, loss_single: 0.6526, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,496 - Iter: 11, Total Loss: 0.6279, loss_single: 0.6279, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,531 - Iter: 12, Total Loss: 0.6072, loss_single: 0.6072, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:31:58,566 - Iter: 13, Total Loss: 0.5852, loss_single: 0.5852, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,601 - Iter: 14, Total Loss: 0.5635, loss_single: 0.5635, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,636 - Iter: 15, Total Loss: 0.5458, loss_single: 0.5458, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,671 - Iter: 16, Total Loss: 0.5285, loss_single: 0.5285, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:31:58,706 - 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Iter: 89, Total Loss: 0.3956, loss_single: 0.3956, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:32:01,311 - Iter: 90, Total Loss: 0.3953, loss_single: 0.3953, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,347 - Iter: 91, Total Loss: 0.3951, loss_single: 0.3951, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,384 - Iter: 92, Total Loss: 0.3949, loss_single: 0.3949, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:32:01,418 - Iter: 93, Total Loss: 0.3946, loss_single: 0.3946, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:32:01,453 - Iter: 94, Total Loss: 0.3944, loss_single: 0.3944, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:32:01,489 - Iter: 95, Total Loss: 0.3942, loss_single: 0.3942, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,524 - Iter: 96, Total Loss: 0.3940, loss_single: 0.3940, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,559 - Iter: 97, Total Loss: 0.3938, loss_single: 0.3938, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:32:01,594 - Iter: 98, Total Loss: 0.3936, loss_single: 0.3936, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:32:01,629 - Iter: 99, Total Loss: 0.3933, loss_single: 0.3933, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,664 - Iter: 100, Total Loss: 0.3931, loss_single: 0.3931, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:01,776 - Saving summary figures for iter 100 +2026-06-24 05:32:05,346 - ### Finished 100 iterations, averaged iter_t = 0.038728 with std = 0.040 ### +2026-06-24 05:32:05,347 - +2026-06-24 05:32:05,347 - ### The PtyRADSolver is finished in 9.216 sec ### +2026-06-24 05:32:05,347 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..e2ad82add80e7563e86371b2dad095aad1806b8a Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/simulation_data_aug9__sample_000025.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/simulation_data_aug9__sample_000025.yaml new file mode 100644 index 0000000000000000000000000000000000000000..79d2ee9f973d041f6fa5fa385cf2629322eea36b --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025/gendata3_std_02__simulation_data_aug9__sample_000025_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-454_C12_-31.1_phi12_289_C21_913_phi21_190_C23_-458_phi23_359_C30_1.26e.08e+07_phi56_128/simulation_data_aug9__sample_000025.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.48544979095459 + probe_aberrations: + C10: -453.5085144042969 + C12: -31.049604415893555 + C21: 912.8538208007812 + C23: -457.9848327636719 + C30: 12621951.0 + C32: 2460.500732421875 + C34: -5030.21484375 + C41: -50887.55078125 + C43: 122482.5234375 + C45: -452649.5 + C50: 14640464.0 + C52: -5129790.0 + C54: 16033307.0 + C56: 10793937.0 + phi12: 288.556258620336 + phi21: 189.9710430084211 + phi23: 359.04826413820643 + phi32: 213.18829033702016 + phi34: 265.6542791634464 + phi41: 81.71557726771049 + phi43: 201.05347572925203 + phi45: 146.95565908746136 + phi52: 99.13287383994482 + phi54: 257.3497253591947 + phi56: 128.10317584606727 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000025_measurement.h5 + key: measurement + random_seed: 20261835 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000025 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug9__sample_000025 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/20260624_053226_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/20260624_053226_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c5ac888e6f5d8e93489d985d2f475f9da5f94099 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/20260624_053226_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:32:24,659 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:32:24,659 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:32:24,659 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:32:24,659 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:32:24,659 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:32:24,659 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:32:24,659 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:32:24,659 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:32:24,659 - +2026-06-24 05:32:24,766 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:32:24,766 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:32:24,766 - Accelerator.num_process = 1 +2026-06-24 05:32:24,766 - Accelerator.mixed_precision = no +2026-06-24 05:32:24,777 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:32:24,777 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:32:24,777 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:32:24,777 - +2026-06-24 05:32:24,777 - ### System information ### +2026-06-24 05:32:24,777 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:32:24,777 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:32:24,777 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:32:24,777 - Machine: x86_64 +2026-06-24 05:32:24,777 - Processor: x86_64 +2026-06-24 05:32:24,777 - Available CPU cores: 8 +2026-06-24 05:32:24,777 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:32:24,777 - +2026-06-24 05:32:24,777 - ### GPU information ### +2026-06-24 05:32:24,778 - CUDA Available: True +2026-06-24 05:32:24,778 - CUDA Version: 13.0 +2026-06-24 05:32:24,778 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:32:24,778 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:32:24,778 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:32:24,778 - In addition, Triton does not directly support Windows. +2026-06-24 05:32:24,778 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:32:24,793 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:32:24,793 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:32:24,793 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:32:24,793 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:32:24,793 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:32:24,793 - +2026-06-24 05:32:24,793 - ### Python information ### +2026-06-24 05:32:24,795 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:32:24,795 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:32:24,795 - +2026-06-24 05:32:24,795 - ### Packages information ### +2026-06-24 05:32:24,796 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:32:24,797 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:32:24,798 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:32:24,798 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:32:24,799 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:32:24,799 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:32:24,799 - +2026-06-24 05:32:24,799 - ### Loading params file ### +2026-06-24 05:32:24,799 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug9__sample_000027.yaml +2026-06-24 05:32:24,805 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:32:24,806 - Success! Params file validated and defaults applied. +2026-06-24 05:32:24,807 - +2026-06-24 05:32:24,807 - ### Setting GPU Device ### +2026-06-24 05:32:24,807 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:32:24,807 - +2026-06-24 05:32:24,807 - Random seed: 20261837 provided by params file +2026-06-24 05:32:24,807 - ### Initializing Initializer ### +2026-06-24 05:32:24,807 - init_params are displayed below: +2026-06-24 05:32:24,807 - random_seed: 20261837 +2026-06-24 05:32:24,807 - probe_illum_type: electron +2026-06-24 05:32:24,807 - probe_kv: 200.0 +2026-06-24 05:32:24,807 - probe_conv_angle: 9.263802528381348 +2026-06-24 05:32:24,807 - probe_aberrations: {'C10': -137.029, 'C12': -0.534, 'phi12': 107.292, 'C21': -259.241, 'phi21': 164.583, 'C23': -681.792, 'phi23': 320.733, 'C30': 10790793.0, 'C32': -11464.351, 'phi32': 241.687, 'C34': -7516.821, 'phi34': 272.944, 'C41': 490368.094, 'phi41': 156.889, 'C43': -86848.625, 'phi43': 52.944, 'C45': -394552.438, 'phi45': 43.702, 'C50': 1594635.0, 'C52': 19246890.0, 'phi52': 121.216, 'C54': 1495991.875, 'phi54': 283.149, 'C56': 3230448.25, 'phi56': 50.692} +2026-06-24 05:32:24,807 - beam_kev: None +2026-06-24 05:32:24,807 - probe_dRn: None +2026-06-24 05:32:24,807 - probe_Rn: None +2026-06-24 05:32:24,808 - probe_D_H: None +2026-06-24 05:32:24,808 - probe_D_FZP: None +2026-06-24 05:32:24,808 - probe_Ls: None +2026-06-24 05:32:24,808 - meas_Npix: 128 +2026-06-24 05:32:24,808 - pos_N_scans: 256 +2026-06-24 05:32:24,808 - pos_N_scan_slow: 16 +2026-06-24 05:32:24,808 - pos_N_scan_fast: 16 +2026-06-24 05:32:24,808 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:32:24,808 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:32:24,808 - probe_pmode_max: 6 +2026-06-24 05:32:24,808 - probe_pmode_init_pows: [0.02] +2026-06-24 05:32:24,808 - obj_omode_max: 1 +2026-06-24 05:32:24,808 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:32:24,808 - obj_Nlayer: 1 +2026-06-24 05:32:24,808 - obj_slice_thickness: 20.0 +2026-06-24 05:32:24,808 - simu_Npix: None +2026-06-24 05:32:24,808 - simu_match_mode: None +2026-06-24 05:32:24,808 - meas_permute: None +2026-06-24 05:32:24,808 - meas_reshape: [256, 128, 128] +2026-06-24 05:32:24,808 - meas_flipT: [0, 0, 0] +2026-06-24 05:32:24,808 - meas_crop: None +2026-06-24 05:32:24,808 - meas_pad: None +2026-06-24 05:32:24,808 - meas_resample: None +2026-06-24 05:32:24,808 - meas_add_source_size: None +2026-06-24 05:32:24,808 - meas_add_detector_blur: None +2026-06-24 05:32:24,808 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:32:24,808 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:32:24,808 - meas_add_poisson_noise: None +2026-06-24 05:32:24,808 - meas_export: None +2026-06-24 05:32:24,808 - probe_permute: None +2026-06-24 05:32:24,808 - probe_z_shift: None +2026-06-24 05:32:24,808 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:32:24,808 - pos_scan_flipT: None +2026-06-24 05:32:24,808 - pos_scan_affine: None +2026-06-24 05:32:24,808 - pos_scan_rand_std: 0.15 +2026-06-24 05:32:24,808 - obj_z_crop: None +2026-06-24 05:32:24,808 - obj_z_pad: None +2026-06-24 05:32:24,808 - obj_z_resample: None +2026-06-24 05:32:24,808 - meas_source: file +2026-06-24 05:32:24,808 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000027_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:32:24,809 - probe_source: simu +2026-06-24 05:32:24,809 - probe_params: None +2026-06-24 05:32:24,809 - pos_source: simu +2026-06-24 05:32:24,809 - pos_params: None +2026-06-24 05:32:24,809 - obj_source: simu +2026-06-24 05:32:24,809 - obj_params: None +2026-06-24 05:32:24,809 - tilt_source: simu +2026-06-24 05:32:24,809 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:32:24,809 - +2026-06-24 05:32:24,809 - ### Initializing cache ### +2026-06-24 05:32:24,809 - use_cached_obj = False +2026-06-24 05:32:24,809 - use_cached_probe = False +2026-06-24 05:32:24,809 - use_cached_pos = False +2026-06-24 05:32:24,809 - +2026-06-24 05:32:24,809 - ### Initializing measurements ### +2026-06-24 05:32:24,809 - Loading measurements from source = 'file' +2026-06-24 05:32:24,809 - Detected measurement file type = '.h5' +2026-06-24 05:32:24,888 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:32:24,888 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:32:24,890 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0048) +2026-06-24 05:32:24,890 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:32:24,890 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:32:24,891 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:32:24,891 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:32:24,892 - Normalizing by max of the 2D mean pattern intensity: 0.0034008981 +2026-06-24 05:32:24,892 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:32:24,893 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0179, 1.4181) +2026-06-24 05:32:24,894 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:32:24,895 - Pattern total int. statistics (min, mean, max) = (291.6960, 293.1398, 294.4084), with min/max = 99.1% +2026-06-24 05:32:24,897 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0179, 1.4181) +2026-06-24 05:32:24,897 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:32:24,897 - +2026-06-24 05:32:24,897 - ### Setting up calibration ### +2026-06-24 05:32:24,897 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:32:24,897 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:32:24,897 - Radius of fitted bright field disk (RBF) = 9.30 px with meas_Npix = 128 +2026-06-24 05:32:24,897 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1454 +2026-06-24 05:32:24,897 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:32:24,897 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:32:25,129 - Initial guess: center=(63.63, 63.62), radius=9.30, Gaussian blur std=0.50 +2026-06-24 05:32:25,139 - Final fit: center=(63.63, 63.62), radius=9.30, Gaussian blur std=0.56 +2026-06-24 05:32:25,139 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.46 px with Npix = 128 +2026-06-24 05:32:25,139 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:32:25,139 - +2026-06-24 05:32:25,139 - ### Setting init_variables dict ### +2026-06-24 05:32:25,139 - Derived values given input init_params: +2026-06-24 05:32:25,139 - kv = 200.0 kV +2026-06-24 05:32:25,139 - wavelength = 0.0251 Ang +2026-06-24 05:32:25,139 - conv_angle = 9.263802528381348 mrad +2026-06-24 05:32:25,139 - Npix = 128 px +2026-06-24 05:32:25,139 - dk = 0.0391 Ang^-1 +2026-06-24 05:32:25,139 - kMax = 2.5000 Ang^-1 +2026-06-24 05:32:25,139 - da = 0.9797 mrad +2026-06-24 05:32:25,139 - angleMax = 62.6984 mrad +2026-06-24 05:32:25,139 - RBF = 9.4561 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:32:25,139 - n_alpha = 6.7681 (# conv_angle) +2026-06-24 05:32:25,139 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:32:25,139 - Rayleigh-limited resolution = 1.6514 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:32:25,139 - Real space probe extent = 25.6000 Ang +2026-06-24 05:32:25,139 - +2026-06-24 05:32:25,139 - ### Initializing probe ### +2026-06-24 05:32:25,139 - Loading probe from source = 'simu' +2026-06-24 05:32:25,140 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:32:25,140 - Start simulating STEM probe +2026-06-24 05:32:25,140 - kv = 200.0 kV +2026-06-24 05:32:25,140 - wavelength = 0.0251 Ang +2026-06-24 05:32:25,140 - conv_angle = 9.263802528381348 mrad +2026-06-24 05:32:25,140 - Npix = 128 px +2026-06-24 05:32:25,140 - dk = 0.0391 Ang^-1 +2026-06-24 05:32:25,140 - kMax = 2.5000 Ang^-1 +2026-06-24 05:32:25,140 - alpha_max = 62.6984 mrad +2026-06-24 05:32:25,140 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:32:25,140 - Rayleigh-limited resolution = 1.6514 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:32:25,140 - Real space probe extent = 25.6000 Ang +2026-06-24 05:32:25,140 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:32:25,140 - ----------------------------------------------------------------------------------- +2026-06-24 05:32:25,140 - C1,0 C1 -137.0290 - Defocus (C10 = -df) +2026-06-24 05:32:25,140 - C1,2 A1 -0.5340 107.29 2-fold astigmatism +2026-06-24 05:32:25,140 - C2,1 3*B2 -259.2410 164.58 Axial coma +2026-06-24 05:32:25,140 - C2,3 A2 -681.7920 320.73 3-fold astigmatism +2026-06-24 05:32:25,140 - C3,0 C3 10790793.0000 - Spherical aberration +2026-06-24 05:32:25,140 - C3,2 4*S3 -11464.3510 241.69 Axial star aberration +2026-06-24 05:32:25,140 - C3,4 A3 -7516.8210 272.94 4-fold astigmatism +2026-06-24 05:32:25,140 - C4,1 4*B4 490368.0940 156.89 Axial coma(4th) +2026-06-24 05:32:25,140 - C4,3 4*D4 -86848.6250 52.94 3-lobe aberration +2026-06-24 05:32:25,140 - C4,5 A4 -394552.4380 43.70 5-fold astigmatism +2026-06-24 05:32:25,140 - C5,0 C5 1594635.0000 - Spherical aberration (5th) +2026-06-24 05:32:25,141 - C5,2 6*S5 19246890.0000 121.22 Axial star aberration(5th) +2026-06-24 05:32:25,141 - C5,4 6*R5 1495991.8750 283.15 4-lobe aberration +2026-06-24 05:32:25,141 - C5,6 A5 3230448.2500 50.69 6-fold astigmatism +2026-06-24 05:32:25,144 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:32:25,144 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:32:25,144 - Creating 5 new probe modes from the major mode +2026-06-24 05:32:25,144 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:32:25,240 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:32:25,242 - Orthogonalizing 6 pmodes +2026-06-24 05:32:25,245 - Sorting 6 pmodes by their intensities +2026-06-24 05:32:25,245 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:32:25,246 - sum(|probe_data|**2) = 293.14, while meas_total_ints (min, mean, max) = (291.6960, 293.1398, 294.4084) +2026-06-24 05:32:25,246 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:32:25,246 - +2026-06-24 05:32:25,246 - ### Initializing probe positions ### +2026-06-24 05:32:25,246 - Loading probe positions from source = 'simu' +2026-06-24 05:32:25,246 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:32:25,246 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:32:25,246 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:32:25,248 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:32:25,248 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:32:25,248 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:32:25,248 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:32:25,248 - +2026-06-24 05:32:25,248 - ### Initializing object ### +2026-06-24 05:32:25,248 - Loading object from source = 'simu' +2026-06-24 05:32:25,248 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:32:25,250 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:32:25,250 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:32:25,250 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:32:25,250 - +2026-06-24 05:32:25,250 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:32:25,250 - omode_occu (omode) = float32, (1,) +2026-06-24 05:32:25,250 - +2026-06-24 05:32:25,250 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:32:25,250 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:32:25,251 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:32:25,251 - +2026-06-24 05:32:25,251 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:32:25,251 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:32:25,251 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:32:25,251 - +2026-06-24 05:32:25,251 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:32:25,251 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:32:25,251 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:32:25,251 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:32:25,251 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:32:25,252 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:32:25,252 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:32:25,252 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:32:25,252 - +2026-06-24 05:32:25,252 - ### Collecting reconstruction provenance ### +2026-06-24 05:32:25,252 - Reconstruction provenance is collected and initialized. +2026-06-24 05:32:25,252 - +2026-06-24 05:32:25,252 - ### Initializing loss function ### +2026-06-24 05:32:25,252 - Active loss types: +2026-06-24 05:32:25,252 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:32:25,252 - +2026-06-24 05:32:25,252 - ### Initializing constraint function ### +2026-06-24 05:32:25,252 - Active constraint types: +2026-06-24 05:32:25,252 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:32:25,252 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:32:25,252 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:32:25,252 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:32:25,252 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:32:25,252 - +2026-06-24 05:32:25,252 - ### Done initializing PtyRADSolver ### +2026-06-24 05:32:25,252 - +2026-06-24 05:32:25,382 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:32:25,382 - +2026-06-24 05:32:25,383 - ### Initializing PtychoModel model ### +2026-06-24 05:32:25,454 - ### PtychoModel optimizable variables ### +2026-06-24 05:32:25,454 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:32:25,454 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:32:25,454 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:32:25,454 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:32:25,454 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:32:25,454 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:32:25,454 - +2026-06-24 05:32:25,454 - ### Optimizable variables statitsics ### +2026-06-24 05:32:25,454 - Total measurement values : 4,194,304 +2026-06-24 05:32:25,454 - Total optimizing variables: 278,728 +2026-06-24 05:32:25,454 - Overdetermined ratio : 15.05 +2026-06-24 05:32:25,454 - +2026-06-24 05:32:25,454 - ### Model behavior ### +2026-06-24 05:32:25,454 - Tilt propagator : False +2026-06-24 05:32:25,454 - Change slice thickness : False +2026-06-24 05:32:25,454 - Detector blur : False +2026-06-24 05:32:25,454 - Preload data : True +2026-06-24 05:32:25,454 - On-the-fly meas padding : False +2026-06-24 05:32:25,454 - On-the-fly meas resample : False +2026-06-24 05:32:25,455 - On-the-fly simu match mode: None +2026-06-24 05:32:25,455 - +2026-06-24 05:32:25,496 - ### Done initializing PtychoModel model ### +2026-06-24 05:32:25,496 - +2026-06-24 05:32:25,496 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:32:25,496 - +2026-06-24 05:32:25,496 - ### Generating indices, batches, and output_path ### +2026-06-24 05:32:25,497 - d90 = 63.000 px or 12.600 Ang +2026-06-24 05:32:25,497 - Selecting indices with the 'full' mode +2026-06-24 05:32:25,955 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:32:26,030 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:32:26,030 - Original recon_dir_affixes = ['default'] +2026-06-24 05:32:26,030 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:32:26,036 - Path corrected for compatibility: +2026-06-24 05:32:26,036 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15e+04_phi32_242_C34_-7.52e+03_phi34_273_C41_4.9e+05_phi41_157_C43_-8.68e+04_phi43_52.9_C45_-3.95e+05_phi45_43.7_C50_1.59e+06_C52_1.92e+07_phi52_121_C54_1.5e+06_phi54_283_C56_3.23e+06_phi56_50.7 +2026-06-24 05:32:26,036 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7 +2026-06-24 05:32:26,038 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7' is generated! +2026-06-24 05:32:26,190 - +2026-06-24 05:32:26,191 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/20260624_053226_ptyrad_log.txt ### +2026-06-24 05:32:26,191 - +2026-06-24 05:32:26,192 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:32:26,192 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:32:26,192 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:32:27,372 - Iter: 1, Total Loss: 1.0218, loss_single: 1.0218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.435 sec +2026-06-24 05:32:27,410 - Iter: 2, Total Loss: 0.9741, loss_single: 0.9741, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:32:27,445 - Iter: 3, Total Loss: 0.9354, loss_single: 0.9354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,481 - Iter: 4, Total Loss: 0.9025, loss_single: 0.9025, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,517 - Iter: 5, Total Loss: 0.8704, loss_single: 0.8704, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,553 - Iter: 6, Total Loss: 0.8348, loss_single: 0.8348, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:27,588 - Iter: 7, Total Loss: 0.7960, loss_single: 0.7960, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,624 - Iter: 8, Total Loss: 0.7535, loss_single: 0.7535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,659 - Iter: 9, Total Loss: 0.7112, loss_single: 0.7112, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,695 - Iter: 10, Total Loss: 0.6734, loss_single: 0.6734, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:27,731 - Iter: 11, Total Loss: 0.6406, loss_single: 0.6406, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,767 - Iter: 12, Total Loss: 0.6179, loss_single: 0.6179, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,804 - Iter: 13, Total Loss: 0.5963, loss_single: 0.5963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:32:27,840 - Iter: 14, Total Loss: 0.5711, loss_single: 0.5711, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,875 - Iter: 15, Total Loss: 0.5467, loss_single: 0.5467, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,911 - Iter: 16, Total Loss: 0.5182, loss_single: 0.5182, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,946 - Iter: 17, Total Loss: 0.4898, loss_single: 0.4898, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:27,982 - Iter: 18, Total Loss: 0.4727, loss_single: 0.4727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,017 - Iter: 19, Total Loss: 0.4580, loss_single: 0.4580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,053 - Iter: 20, Total Loss: 0.4404, loss_single: 0.4404, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:28,089 - Iter: 21, Total Loss: 0.4257, loss_single: 0.4257, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,125 - Iter: 22, Total Loss: 0.4101, loss_single: 0.4101, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:28,160 - Iter: 23, Total Loss: 0.3998, loss_single: 0.3998, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,195 - Iter: 24, Total Loss: 0.3934, loss_single: 0.3934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,230 - Iter: 25, Total Loss: 0.3856, loss_single: 0.3856, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,266 - Iter: 26, Total Loss: 0.3779, loss_single: 0.3779, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,302 - Iter: 27, Total Loss: 0.3717, loss_single: 0.3717, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:28,337 - Iter: 28, Total Loss: 0.3667, loss_single: 0.3667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,373 - Iter: 29, Total Loss: 0.3629, loss_single: 0.3629, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,408 - Iter: 30, Total Loss: 0.3604, loss_single: 0.3604, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,444 - Iter: 31, Total Loss: 0.3578, loss_single: 0.3578, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,479 - Iter: 32, Total Loss: 0.3553, loss_single: 0.3553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,515 - Iter: 33, Total Loss: 0.3533, loss_single: 0.3533, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,550 - Iter: 34, Total Loss: 0.3517, loss_single: 0.3517, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,585 - Iter: 35, Total Loss: 0.3502, loss_single: 0.3502, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,621 - Iter: 36, Total Loss: 0.3489, loss_single: 0.3489, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,656 - Iter: 37, Total Loss: 0.3478, loss_single: 0.3478, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,692 - Iter: 38, Total Loss: 0.3468, loss_single: 0.3468, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,728 - Iter: 39, Total Loss: 0.3459, loss_single: 0.3459, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,762 - Iter: 40, Total Loss: 0.3450, loss_single: 0.3450, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,800 - Iter: 41, Total Loss: 0.3442, loss_single: 0.3442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,835 - Iter: 42, Total Loss: 0.3435, loss_single: 0.3435, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,871 - Iter: 43, Total Loss: 0.3428, loss_single: 0.3428, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,906 - Iter: 44, Total Loss: 0.3421, loss_single: 0.3421, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,942 - Iter: 45, Total Loss: 0.3415, loss_single: 0.3415, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:28,978 - Iter: 46, Total Loss: 0.3408, loss_single: 0.3408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:29,014 - Iter: 47, Total Loss: 0.3403, loss_single: 0.3403, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:29,049 - Iter: 48, Total Loss: 0.3397, loss_single: 0.3397, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,086 - Iter: 49, Total Loss: 0.3392, loss_single: 0.3392, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:29,122 - Iter: 50, Total Loss: 0.3386, loss_single: 0.3386, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:29,157 - Iter: 51, Total Loss: 0.3381, loss_single: 0.3381, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,193 - Iter: 52, Total Loss: 0.3377, loss_single: 0.3377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,228 - Iter: 53, Total Loss: 0.3372, loss_single: 0.3372, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,264 - Iter: 54, Total Loss: 0.3368, loss_single: 0.3368, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,299 - Iter: 55, Total Loss: 0.3363, loss_single: 0.3363, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,335 - Iter: 56, Total Loss: 0.3358, loss_single: 0.3358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,370 - Iter: 57, Total Loss: 0.3354, loss_single: 0.3354, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,406 - Iter: 58, Total Loss: 0.3350, loss_single: 0.3350, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,441 - 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Iter: 65, Total Loss: 0.3319, loss_single: 0.3319, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,690 - Iter: 66, Total Loss: 0.3315, loss_single: 0.3315, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,726 - Iter: 67, Total Loss: 0.3311, loss_single: 0.3311, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,761 - Iter: 68, Total Loss: 0.3307, loss_single: 0.3307, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,797 - Iter: 69, Total Loss: 0.3302, loss_single: 0.3302, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,832 - Iter: 70, Total Loss: 0.3298, loss_single: 0.3298, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:29,868 - 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Iter: 77, Total Loss: 0.3270, loss_single: 0.3270, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:30,118 - Iter: 78, Total Loss: 0.3266, loss_single: 0.3266, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:30,153 - Iter: 79, Total Loss: 0.3262, loss_single: 0.3262, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,189 - Iter: 80, Total Loss: 0.3259, loss_single: 0.3259, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,225 - Iter: 81, Total Loss: 0.3255, loss_single: 0.3255, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:30,260 - Iter: 82, Total Loss: 0.3251, loss_single: 0.3251, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,295 - Iter: 83, Total Loss: 0.3246, loss_single: 0.3246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,331 - Iter: 84, Total Loss: 0.3242, loss_single: 0.3242, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,367 - Iter: 85, Total Loss: 0.3238, loss_single: 0.3238, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,402 - Iter: 86, Total Loss: 0.3234, loss_single: 0.3234, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,438 - Iter: 87, Total Loss: 0.3230, loss_single: 0.3230, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,474 - Iter: 88, Total Loss: 0.3226, loss_single: 0.3226, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,509 - Iter: 89, Total Loss: 0.3222, loss_single: 0.3222, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:30,545 - Iter: 90, Total Loss: 0.3218, loss_single: 0.3218, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,582 - Iter: 91, Total Loss: 0.3214, loss_single: 0.3214, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:32:30,618 - Iter: 92, Total Loss: 0.3210, loss_single: 0.3210, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,654 - Iter: 93, Total Loss: 0.3206, loss_single: 0.3206, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,689 - Iter: 94, Total Loss: 0.3202, loss_single: 0.3202, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,724 - Iter: 95, Total Loss: 0.3199, loss_single: 0.3199, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,760 - Iter: 96, Total Loss: 0.3195, loss_single: 0.3195, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,795 - Iter: 97, Total Loss: 0.3191, loss_single: 0.3191, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,831 - Iter: 98, Total Loss: 0.3188, loss_single: 0.3188, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:30,867 - Iter: 99, Total Loss: 0.3184, loss_single: 0.3184, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:32:30,903 - Iter: 100, Total Loss: 0.3181, loss_single: 0.3181, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:32:31,013 - Saving summary figures for iter 100 +2026-06-24 05:32:34,596 - ### Finished 100 iterations, averaged iter_t = 0.039207 with std = 0.040 ### +2026-06-24 05:32:34,596 - +2026-06-24 05:32:34,596 - ### The PtyRADSolver is finished in 9.214 sec ### +2026-06-24 05:32:34,596 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..069b8cf3c37f2b99230af9e137d69b59359fef91 Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/simulation_data_aug9__sample_000027.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/simulation_data_aug9__sample_000027.yaml new file mode 100644 index 0000000000000000000000000000000000000000..61a28b50347c50b7f9a5ed3d2360e69518cd77f9 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027/gendata3_std_02__simulation_data_aug9__sample_000027_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-137_C12_-0.534_phi12_107_C21_-259_phi21_165_C23_-682_phi23_321_C30_1.08e+07_C32_-1.15.7/simulation_data_aug9__sample_000027.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.263802528381348 + probe_aberrations: + C10: -137.02932739257812 + C12: -0.5336474776268005 + C21: -259.24078369140625 + C23: -681.792236328125 + C30: 10790793.0 + C32: -11464.3505859375 + C34: -7516.82080078125 + C41: 490368.09375 + C43: -86848.625 + C45: -394552.4375 + C50: 1594635.0 + C52: 19246890.0 + C54: 1495991.875 + C56: 3230448.25 + phi12: 107.29184216203771 + phi21: 164.58317522197035 + phi23: 320.73273338513246 + phi32: 241.68668091300808 + phi34: 272.94419470611433 + phi41: 156.88906274459936 + phi43: 52.943856181517 + phi45: 43.701899894816066 + phi52: 121.21613218140334 + phi54: 283.1489890997336 + phi56: 50.69199403858257 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000027_measurement.h5 + key: measurement + random_seed: 20261837 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000027 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug9__sample_000027 + postfix: '' + compiler_configs: + enable: false + prefix_time: false diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/20260624_053355_ptyrad_log.txt b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/20260624_053355_ptyrad_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..12256862e2fdded2eeac97fe2f56ea05a7cd38b5 --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/20260624_053355_ptyrad_log.txt @@ -0,0 +1,417 @@ +2026-06-24 05:33:53,635 - ### PtyRAD LoggingManager configuration ### +2026-06-24 05:33:53,635 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. +2026-06-24 05:33:53,635 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. +2026-06-24 05:33:53,635 - flush_file = True. Automatically set to True if `log_file is not None` +2026-06-24 05:33:53,635 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. +2026-06-24 05:33:53,635 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. +2026-06-24 05:33:53,635 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. +2026-06-24 05:33:53,635 - show_timestamp = True. If true, the printed information will contain a timestamp. +2026-06-24 05:33:53,635 - +2026-06-24 05:33:53,720 - ### Initializing HuggingFace accelerator ### +2026-06-24 05:33:53,720 - Accelerator.distributed_type = DistributedType.NO +2026-06-24 05:33:53,720 - Accelerator.num_process = 1 +2026-06-24 05:33:53,720 - Accelerator.mixed_precision = no +2026-06-24 05:33:53,731 - 'accelerate' is available but NOT using distributed mode or mixed precision +2026-06-24 05:33:53,731 - If you want to utilize 'accelerate' for multiGPU or mixed precision, +2026-06-24 05:33:53,731 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run --gpuid 'acc'` in your terminal +2026-06-24 05:33:53,731 - +2026-06-24 05:33:53,731 - ### System information ### +2026-06-24 05:33:53,731 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 +2026-06-24 05:33:53,731 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 +2026-06-24 05:33:53,731 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 +2026-06-24 05:33:53,731 - Machine: x86_64 +2026-06-24 05:33:53,731 - Processor: x86_64 +2026-06-24 05:33:53,731 - Available CPU cores: 8 +2026-06-24 05:33:53,731 - SLURM-Allocated Total Memory: 78.12 GB +2026-06-24 05:33:53,731 - +2026-06-24 05:33:53,731 - ### GPU information ### +2026-06-24 05:33:53,731 - CUDA Available: True +2026-06-24 05:33:53,731 - CUDA Version: 13.0 +2026-06-24 05:33:53,732 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] +2026-06-24 05:33:53,732 - CUDA Compute Capability: ['8.0'] +2026-06-24 05:33:53,732 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. +2026-06-24 05:33:53,732 - In addition, Triton does not directly support Windows. +2026-06-24 05:33:53,732 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. +2026-06-24 05:33:53,747 - MIG (Multi-Instance GPU) mode = False +2026-06-24 05:33:53,747 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. +2026-06-24 05:33:53,747 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. +2026-06-24 05:33:53,747 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. +2026-06-24 05:33:53,747 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. +2026-06-24 05:33:53,747 - +2026-06-24 05:33:53,747 - ### Python information ### +2026-06-24 05:33:53,748 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 +2026-06-24 05:33:53,748 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] +2026-06-24 05:33:53,748 - +2026-06-24 05:33:53,748 - ### Packages information ### +2026-06-24 05:33:53,749 - Numpy Version (metadata): 2.4.6 +2026-06-24 05:33:53,749 - PyTorch Version (metadata): 2.12.0 +2026-06-24 05:33:53,750 - Optuna Version (metadata): 4.9.0 +2026-06-24 05:33:53,751 - Accelerate Version (metadata): 1.13.0 +2026-06-24 05:33:53,751 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 +2026-06-24 05:33:53,751 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py +2026-06-24 05:33:53,751 - +2026-06-24 05:33:53,751 - ### Loading params file ### +2026-06-24 05:33:53,751 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/gendata3_std_02/simulation_data_aug9__sample_000033.yaml +2026-06-24 05:33:53,758 - validate = True: Filling defaults and validating the params file... +2026-06-24 05:33:53,759 - Success! Params file validated and defaults applied. +2026-06-24 05:33:53,759 - +2026-06-24 05:33:53,759 - ### Setting GPU Device ### +2026-06-24 05:33:53,759 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) +2026-06-24 05:33:53,759 - +2026-06-24 05:33:53,759 - Random seed: 20261843 provided by params file +2026-06-24 05:33:53,760 - ### Initializing Initializer ### +2026-06-24 05:33:53,760 - init_params are displayed below: +2026-06-24 05:33:53,760 - random_seed: 20261843 +2026-06-24 05:33:53,760 - probe_illum_type: electron +2026-06-24 05:33:53,760 - probe_kv: 200.0 +2026-06-24 05:33:53,760 - probe_conv_angle: 9.665002822875977 +2026-06-24 05:33:53,760 - probe_aberrations: {'C10': -347.649, 'C12': 19.715, 'phi12': 268.427, 'C21': 922.235, 'phi21': 297.61, 'C23': 78.352, 'phi23': 328.62, 'C30': 11504695.0, 'C32': -4888.126, 'phi32': 17.087, 'C34': -7394.75, 'phi34': 194.153, 'C41': 174677.156, 'phi41': 145.356, 'C43': 320952.75, 'phi43': 133.031, 'C45': 408759.406, 'phi45': 243.345, 'C50': -1316927.5, 'C52': -8313144.0, 'phi52': 357.473, 'C54': -733252.438, 'phi54': 242.331, 'C56': 10132429.0, 'phi56': 126.589} +2026-06-24 05:33:53,760 - beam_kev: None +2026-06-24 05:33:53,760 - probe_dRn: None +2026-06-24 05:33:53,760 - probe_Rn: None +2026-06-24 05:33:53,760 - probe_D_H: None +2026-06-24 05:33:53,760 - probe_D_FZP: None +2026-06-24 05:33:53,760 - probe_Ls: None +2026-06-24 05:33:53,760 - meas_Npix: 128 +2026-06-24 05:33:53,760 - pos_N_scans: 256 +2026-06-24 05:33:53,760 - pos_N_scan_slow: 16 +2026-06-24 05:33:53,760 - pos_N_scan_fast: 16 +2026-06-24 05:33:53,760 - pos_scan_step_size: 0.5299999713897705 +2026-06-24 05:33:53,760 - meas_calibration: {'mode': 'kMax', 'value': 2.5} +2026-06-24 05:33:53,760 - probe_pmode_max: 6 +2026-06-24 05:33:53,761 - probe_pmode_init_pows: [0.02] +2026-06-24 05:33:53,761 - obj_omode_max: 1 +2026-06-24 05:33:53,761 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} +2026-06-24 05:33:53,761 - obj_Nlayer: 1 +2026-06-24 05:33:53,761 - obj_slice_thickness: 20.0 +2026-06-24 05:33:53,761 - simu_Npix: None +2026-06-24 05:33:53,761 - simu_match_mode: None +2026-06-24 05:33:53,761 - meas_permute: None +2026-06-24 05:33:53,761 - meas_reshape: [256, 128, 128] +2026-06-24 05:33:53,761 - meas_flipT: [0, 0, 0] +2026-06-24 05:33:53,761 - meas_crop: None +2026-06-24 05:33:53,761 - meas_pad: None +2026-06-24 05:33:53,761 - meas_resample: None +2026-06-24 05:33:53,761 - meas_add_source_size: None +2026-06-24 05:33:53,761 - meas_add_detector_blur: None +2026-06-24 05:33:53,761 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} +2026-06-24 05:33:53,761 - meas_normalization: {'mode': 'max_at_one', 'value': None} +2026-06-24 05:33:53,761 - meas_add_poisson_noise: None +2026-06-24 05:33:53,761 - meas_export: None +2026-06-24 05:33:53,761 - probe_permute: None +2026-06-24 05:33:53,761 - probe_z_shift: None +2026-06-24 05:33:53,761 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} +2026-06-24 05:33:53,761 - pos_scan_flipT: None +2026-06-24 05:33:53,761 - pos_scan_affine: None +2026-06-24 05:33:53,761 - pos_scan_rand_std: 0.15 +2026-06-24 05:33:53,761 - obj_z_crop: None +2026-06-24 05:33:53,761 - obj_z_pad: None +2026-06-24 05:33:53,761 - obj_z_resample: None +2026-06-24 05:33:53,761 - meas_source: file +2026-06-24 05:33:53,761 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000033_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} +2026-06-24 05:33:53,761 - probe_source: simu +2026-06-24 05:33:53,761 - probe_params: None +2026-06-24 05:33:53,761 - pos_source: simu +2026-06-24 05:33:53,761 - pos_params: None +2026-06-24 05:33:53,761 - obj_source: simu +2026-06-24 05:33:53,761 - obj_params: None +2026-06-24 05:33:53,761 - tilt_source: simu +2026-06-24 05:33:53,761 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} +2026-06-24 05:33:53,761 - +2026-06-24 05:33:53,762 - ### Initializing cache ### +2026-06-24 05:33:53,762 - use_cached_obj = False +2026-06-24 05:33:53,762 - use_cached_probe = False +2026-06-24 05:33:53,762 - use_cached_pos = False +2026-06-24 05:33:53,762 - +2026-06-24 05:33:53,762 - ### Initializing measurements ### +2026-06-24 05:33:53,762 - Loading measurements from source = 'file' +2026-06-24 05:33:53,762 - Detected measurement file type = '.h5' +2026-06-24 05:33:53,836 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. +2026-06-24 05:33:53,837 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 +2026-06-24 05:33:53,838 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0045) +2026-06-24 05:33:53,838 - Reshaping measurements to shape = [256, 128, 128] +2026-06-24 05:33:53,838 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] +2026-06-24 05:33:53,841 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:33:53,841 - Normalizing measurements with mode = 'max_at_one' and value = 'None' +2026-06-24 05:33:53,841 - Normalizing by max of the 2D mean pattern intensity: 0.0032360393 +2026-06-24 05:33:53,842 - meausrements shape / dtype = (256, 128, 128), dtype = float32 +2026-06-24 05:33:53,843 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0189, 1.4022) +2026-06-24 05:33:53,844 - No negative values found in measurements. Skipping non-neg correction. +2026-06-24 05:33:53,845 - Pattern total int. statistics (min, mean, max) = (305.8210, 309.7647, 313.1124), with min/max = 97.7% +2026-06-24 05:33:53,847 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0189, 1.4022) +2026-06-24 05:33:53,847 - measurements (N, Ky, Kx) = float32, (256, 128, 128) +2026-06-24 05:33:53,847 - +2026-06-24 05:33:53,847 - ### Setting up calibration ### +2026-06-24 05:33:53,847 - meas_calibration mode = 'kMax', value = 2.5 +2026-06-24 05:33:53,847 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration +2026-06-24 05:33:53,847 - Radius of fitted bright field disk (RBF) = 9.80 px with meas_Npix = 128 +2026-06-24 05:33:53,847 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1532 +2026-06-24 05:33:53,847 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check +2026-06-24 05:33:53,847 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks +2026-06-24 05:33:54,079 - Initial guess: center=(63.62, 63.62), radius=9.80, Gaussian blur std=0.50 +2026-06-24 05:33:54,091 - Final fit: center=(63.62, 63.62), radius=9.80, Gaussian blur std=0.67 +2026-06-24 05:33:54,092 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 9.87 px with Npix = 128 +2026-06-24 05:33:54,092 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 +2026-06-24 05:33:54,092 - +2026-06-24 05:33:54,092 - ### Setting init_variables dict ### +2026-06-24 05:33:54,092 - Derived values given input init_params: +2026-06-24 05:33:54,092 - kv = 200.0 kV +2026-06-24 05:33:54,092 - wavelength = 0.0251 Ang +2026-06-24 05:33:54,092 - conv_angle = 9.665002822875977 mrad +2026-06-24 05:33:54,092 - Npix = 128 px +2026-06-24 05:33:54,092 - dk = 0.0391 Ang^-1 +2026-06-24 05:33:54,092 - kMax = 2.5000 Ang^-1 +2026-06-24 05:33:54,092 - da = 0.9797 mrad +2026-06-24 05:33:54,092 - angleMax = 62.6984 mrad +2026-06-24 05:33:54,092 - RBF = 9.8657 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) +2026-06-24 05:33:54,092 - n_alpha = 6.4872 (# conv_angle) +2026-06-24 05:33:54,092 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:33:54,092 - Rayleigh-limited resolution = 1.5829 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:33:54,092 - Real space probe extent = 25.6000 Ang +2026-06-24 05:33:54,092 - +2026-06-24 05:33:54,092 - ### Initializing probe ### +2026-06-24 05:33:54,092 - Loading probe from source = 'simu' +2026-06-24 05:33:54,092 - Using experimental parameters specified by 'init_params' for initial probe simulation. +2026-06-24 05:33:54,092 - Start simulating STEM probe +2026-06-24 05:33:54,093 - kv = 200.0 kV +2026-06-24 05:33:54,093 - wavelength = 0.0251 Ang +2026-06-24 05:33:54,093 - conv_angle = 9.665002822875977 mrad +2026-06-24 05:33:54,093 - Npix = 128 px +2026-06-24 05:33:54,093 - dk = 0.0391 Ang^-1 +2026-06-24 05:33:54,093 - kMax = 2.5000 Ang^-1 +2026-06-24 05:33:54,093 - alpha_max = 62.6984 mrad +2026-06-24 05:33:54,093 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang +2026-06-24 05:33:54,093 - Rayleigh-limited resolution = 1.5829 Ang (0.61*lambda/alpha for focused probe ) +2026-06-24 05:33:54,093 - Real space probe extent = 25.6000 Ang +2026-06-24 05:33:54,093 - Krivanek Haider Magnitude Angle (°) Description +2026-06-24 05:33:54,093 - ----------------------------------------------------------------------------------- +2026-06-24 05:33:54,093 - C1,0 C1 -347.6490 - Defocus (C10 = -df) +2026-06-24 05:33:54,093 - C1,2 A1 19.7150 268.43 2-fold astigmatism +2026-06-24 05:33:54,093 - C2,1 3*B2 922.2350 297.61 Axial coma +2026-06-24 05:33:54,093 - C2,3 A2 78.3520 328.62 3-fold astigmatism +2026-06-24 05:33:54,093 - C3,0 C3 11504695.0000 - Spherical aberration +2026-06-24 05:33:54,093 - C3,2 4*S3 -4888.1260 17.09 Axial star aberration +2026-06-24 05:33:54,093 - C3,4 A3 -7394.7500 194.15 4-fold astigmatism +2026-06-24 05:33:54,093 - C4,1 4*B4 174677.1560 145.36 Axial coma(4th) +2026-06-24 05:33:54,093 - C4,3 4*D4 320952.7500 133.03 3-lobe aberration +2026-06-24 05:33:54,093 - C4,5 A4 408759.4060 243.34 5-fold astigmatism +2026-06-24 05:33:54,093 - C5,0 C5 -1316927.5000 - Spherical aberration (5th) +2026-06-24 05:33:54,093 - C5,2 6*S5 -8313144.0000 357.47 Axial star aberration(5th) +2026-06-24 05:33:54,093 - C5,4 6*R5 -733252.4380 242.33 4-lobe aberration +2026-06-24 05:33:54,093 - C5,6 A5 10132429.0000 126.59 6-fold astigmatism +2026-06-24 05:33:54,096 - Loaded probe shape = (1, 128, 128), dtype = complex128 +2026-06-24 05:33:54,096 - pmode_now: 1 and pmode_max: 6, padding the pmode. +2026-06-24 05:33:54,096 - Creating 5 new probe modes from the major mode +2026-06-24 05:33:54,096 - Start making mixed-state STEM probe with 6 incoherent probe modes +2026-06-24 05:33:54,241 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] +2026-06-24 05:33:54,242 - Orthogonalizing 6 pmodes +2026-06-24 05:33:54,245 - Sorting 6 pmodes by their intensities +2026-06-24 05:33:54,245 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' +2026-06-24 05:33:54,246 - sum(|probe_data|**2) = 309.76, while meas_total_ints (min, mean, max) = (305.8210, 309.7647, 313.1124) +2026-06-24 05:33:54,246 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) +2026-06-24 05:33:54,246 - +2026-06-24 05:33:54,246 - ### Initializing probe positions ### +2026-06-24 05:33:54,246 - Loading probe positions from source = 'simu' +2026-06-24 05:33:54,246 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. +2026-06-24 05:33:54,246 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 +2026-06-24 05:33:54,246 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions +2026-06-24 05:33:54,248 - crop_pos (N,2) = int16, (256, 2) +2026-06-24 05:33:54,248 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) +2026-06-24 05:33:54,249 - crop_pos extent (Ang) = [8. 8.] +2026-06-24 05:33:54,249 - probe_pos_shifts (N,2) = float32, (256, 2) +2026-06-24 05:33:54,249 - +2026-06-24 05:33:54,249 - ### Initializing object ### +2026-06-24 05:33:54,249 - Loading object from source = 'simu' +2026-06-24 05:33:54,249 - Using experimental parameters specified by 'init_params' for initial object simulation. +2026-06-24 05:33:54,250 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. +2026-06-24 05:33:54,250 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) +2026-06-24 05:33:54,251 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] +2026-06-24 05:33:54,251 - +2026-06-24 05:33:54,251 - ### Initializing omode_occu from 'uniform' ### +2026-06-24 05:33:54,251 - omode_occu (omode) = float32, (1,) +2026-06-24 05:33:54,251 - +2026-06-24 05:33:54,251 - ### Initializing H (Fresnel propagator) ### +2026-06-24 05:33:54,251 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang +2026-06-24 05:33:54,251 - H (Ky, Kx) = complex64, (128, 128) +2026-06-24 05:33:54,251 - +2026-06-24 05:33:54,252 - ### Initializing obj tilts from = 'simu' ### +2026-06-24 05:33:54,252 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad +2026-06-24 05:33:54,252 - obj_tilts (N, 2) = float32, (1, 2) +2026-06-24 05:33:54,252 - +2026-06-24 05:33:54,252 - ### Checking consistency between input params with the initialized variables ### +2026-06-24 05:33:54,252 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' +2026-06-24 05:33:54,252 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' +2026-06-24 05:33:54,252 - obj.shape[0] is consistent with len(omode_occu) as '1' +2026-06-24 05:33:54,252 - obj.shape[1] is consistent with Nlayer as '1' +2026-06-24 05:33:54,252 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). +2026-06-24 05:33:54,252 - obj_tilts is consistent with either 1 or N_scans +2026-06-24 05:33:54,252 - Pass the consistency check of initialized variables, initialization is done! +2026-06-24 05:33:54,252 - +2026-06-24 05:33:54,252 - ### Collecting reconstruction provenance ### +2026-06-24 05:33:54,252 - Reconstruction provenance is collected and initialized. +2026-06-24 05:33:54,252 - +2026-06-24 05:33:54,252 - ### Initializing loss function ### +2026-06-24 05:33:54,252 - Active loss types: +2026-06-24 05:33:54,252 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} +2026-06-24 05:33:54,252 - +2026-06-24 05:33:54,253 - ### Initializing constraint function ### +2026-06-24 05:33:54,253 - Active constraint types: +2026-06-24 05:33:54,253 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:33:54,253 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} +2026-06-24 05:33:54,253 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} +2026-06-24 05:33:54,253 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} +2026-06-24 05:33:54,253 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} +2026-06-24 05:33:54,253 - +2026-06-24 05:33:54,253 - ### Done initializing PtyRADSolver ### +2026-06-24 05:33:54,253 - +2026-06-24 05:33:54,380 - ### Starting the PtyRADSolver in reconstruct mode ### +2026-06-24 05:33:54,380 - +2026-06-24 05:33:54,380 - ### Initializing PtychoModel model ### +2026-06-24 05:33:54,451 - ### PtychoModel optimizable variables ### +2026-06-24 05:33:54,452 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:33:54,452 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:33:54,452 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:33:54,452 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 +2026-06-24 05:33:54,452 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 +2026-06-24 05:33:54,452 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 +2026-06-24 05:33:54,452 - +2026-06-24 05:33:54,452 - ### Optimizable variables statitsics ### +2026-06-24 05:33:54,452 - Total measurement values : 4,194,304 +2026-06-24 05:33:54,452 - Total optimizing variables: 278,728 +2026-06-24 05:33:54,452 - Overdetermined ratio : 15.05 +2026-06-24 05:33:54,452 - +2026-06-24 05:33:54,452 - ### Model behavior ### +2026-06-24 05:33:54,452 - Tilt propagator : False +2026-06-24 05:33:54,452 - Change slice thickness : False +2026-06-24 05:33:54,452 - Detector blur : False +2026-06-24 05:33:54,452 - Preload data : True +2026-06-24 05:33:54,452 - On-the-fly meas padding : False +2026-06-24 05:33:54,452 - On-the-fly meas resample : False +2026-06-24 05:33:54,452 - On-the-fly simu match mode: None +2026-06-24 05:33:54,452 - +2026-06-24 05:33:54,493 - ### Done initializing PtychoModel model ### +2026-06-24 05:33:54,493 - +2026-06-24 05:33:54,493 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### +2026-06-24 05:33:54,494 - +2026-06-24 05:33:54,494 - ### Generating indices, batches, and output_path ### +2026-06-24 05:33:54,495 - d90 = 57.000 px or 11.400 Ang +2026-06-24 05:33:54,495 - Selecting indices with the 'full' mode +2026-06-24 05:33:54,961 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec +2026-06-24 05:33:55,038 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 +2026-06-24 05:33:55,038 - Original recon_dir_affixes = ['default'] +2026-06-24 05:33:55,038 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] +2026-06-24 05:33:55,045 - Path corrected for compatibility: +2026-06-24 05:33:55,045 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+07_C32_-4.89e+03_phi32_17.1_C34_-7.39e+03_phi34_194_C41_1.75e+05_phi41_145_C43_3.21e+05_phi43_133_C45_4.09e+05_phi45_243_C50_-1.32e+06_C52_-8.31e+06_phi52_357_C54_-7.33e+05_phi54_242_C56_1.01e+07_phi56_127 +2026-06-24 05:33:55,045 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127 +2026-06-24 05:33:55,046 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127' is generated! +2026-06-24 05:33:55,201 - +2026-06-24 05:33:55,202 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/20260624_053355_ptyrad_log.txt ### +2026-06-24 05:33:55,202 - +2026-06-24 05:33:55,203 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### +2026-06-24 05:33:55,203 - ### Start the PtyRAD iterative ptycho reconstruction ### +2026-06-24 05:33:55,203 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} +2026-06-24 05:33:56,389 - Iter: 1, Total Loss: 0.9654, loss_single: 0.9654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.433 sec +2026-06-24 05:33:56,427 - Iter: 2, Total Loss: 0.9192, loss_single: 0.9192, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:33:56,463 - Iter: 3, Total Loss: 0.8809, loss_single: 0.8809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,498 - Iter: 4, Total Loss: 0.8419, loss_single: 0.8419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,534 - Iter: 5, Total Loss: 0.8043, loss_single: 0.8043, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,569 - Iter: 6, Total Loss: 0.7726, loss_single: 0.7726, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,605 - Iter: 7, Total Loss: 0.7412, loss_single: 0.7412, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,640 - Iter: 8, Total Loss: 0.7133, loss_single: 0.7133, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,676 - Iter: 9, Total Loss: 0.6884, loss_single: 0.6884, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,711 - Iter: 10, Total Loss: 0.6605, loss_single: 0.6605, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,748 - Iter: 11, Total Loss: 0.6364, loss_single: 0.6364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec +2026-06-24 05:33:56,784 - Iter: 12, Total Loss: 0.6180, loss_single: 0.6180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:56,820 - Iter: 13, Total Loss: 0.6012, loss_single: 0.6012, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,855 - Iter: 14, Total Loss: 0.5841, loss_single: 0.5841, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,890 - Iter: 15, Total Loss: 0.5679, loss_single: 0.5679, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,926 - Iter: 16, Total Loss: 0.5517, loss_single: 0.5517, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,962 - Iter: 17, Total Loss: 0.5399, loss_single: 0.5399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:56,997 - Iter: 18, Total Loss: 0.5302, loss_single: 0.5302, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,033 - Iter: 19, Total Loss: 0.5174, loss_single: 0.5174, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,068 - Iter: 20, Total Loss: 0.5054, loss_single: 0.5054, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,104 - Iter: 21, Total Loss: 0.4963, loss_single: 0.4963, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,140 - Iter: 22, Total Loss: 0.4888, loss_single: 0.4888, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,175 - Iter: 23, Total Loss: 0.4816, loss_single: 0.4816, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,210 - Iter: 24, Total Loss: 0.4757, loss_single: 0.4757, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,246 - Iter: 25, Total Loss: 0.4727, loss_single: 0.4727, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,281 - Iter: 26, Total Loss: 0.4699, loss_single: 0.4699, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,317 - Iter: 27, Total Loss: 0.4673, loss_single: 0.4673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,352 - Iter: 28, Total Loss: 0.4648, loss_single: 0.4648, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,387 - Iter: 29, Total Loss: 0.4614, loss_single: 0.4614, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,423 - Iter: 30, Total Loss: 0.4585, loss_single: 0.4585, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,459 - Iter: 31, Total Loss: 0.4559, loss_single: 0.4559, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,494 - Iter: 32, Total Loss: 0.4538, loss_single: 0.4538, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,529 - Iter: 33, Total Loss: 0.4524, loss_single: 0.4524, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,565 - Iter: 34, Total Loss: 0.4512, loss_single: 0.4512, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,601 - Iter: 35, Total Loss: 0.4500, loss_single: 0.4500, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,637 - Iter: 36, Total Loss: 0.4491, loss_single: 0.4491, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,672 - Iter: 37, Total Loss: 0.4484, loss_single: 0.4484, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,708 - Iter: 38, Total Loss: 0.4479, loss_single: 0.4479, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:57,743 - Iter: 39, Total Loss: 0.4472, loss_single: 0.4472, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,779 - Iter: 40, Total Loss: 0.4466, loss_single: 0.4466, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:57,817 - Iter: 41, Total Loss: 0.4461, loss_single: 0.4461, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,853 - Iter: 42, Total Loss: 0.4456, loss_single: 0.4456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,889 - Iter: 43, Total Loss: 0.4452, loss_single: 0.4452, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:57,924 - Iter: 44, Total Loss: 0.4449, loss_single: 0.4449, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:57,961 - Iter: 45, Total Loss: 0.4445, loss_single: 0.4445, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:57,996 - Iter: 46, Total Loss: 0.4442, loss_single: 0.4442, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,032 - Iter: 47, Total Loss: 0.4440, loss_single: 0.4440, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,067 - Iter: 48, Total Loss: 0.4436, loss_single: 0.4436, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,102 - Iter: 49, Total Loss: 0.4433, loss_single: 0.4433, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,138 - Iter: 50, Total Loss: 0.4431, loss_single: 0.4431, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,174 - Iter: 51, Total Loss: 0.4427, loss_single: 0.4427, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,209 - Iter: 52, Total Loss: 0.4425, loss_single: 0.4425, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,244 - Iter: 53, Total Loss: 0.4422, loss_single: 0.4422, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,279 - Iter: 54, Total Loss: 0.4419, loss_single: 0.4419, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,315 - Iter: 55, Total Loss: 0.4416, loss_single: 0.4416, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,350 - Iter: 56, Total Loss: 0.4413, loss_single: 0.4413, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,385 - Iter: 57, Total Loss: 0.4410, loss_single: 0.4410, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,420 - Iter: 58, Total Loss: 0.4408, loss_single: 0.4408, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,456 - Iter: 59, Total Loss: 0.4405, loss_single: 0.4405, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec +2026-06-24 05:33:58,492 - Iter: 60, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,527 - Iter: 61, Total Loss: 0.4399, loss_single: 0.4399, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,563 - Iter: 62, Total Loss: 0.4396, loss_single: 0.4396, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,597 - Iter: 63, Total Loss: 0.4393, loss_single: 0.4393, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec +2026-06-24 05:33:58,633 - Iter: 64, Total Loss: 0.4391, loss_single: 0.4391, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,668 - Iter: 65, Total Loss: 0.4388, loss_single: 0.4388, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,704 - Iter: 66, Total Loss: 0.4385, loss_single: 0.4385, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,739 - Iter: 67, Total Loss: 0.4382, loss_single: 0.4382, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,774 - Iter: 68, Total Loss: 0.4379, loss_single: 0.4379, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,810 - Iter: 69, Total Loss: 0.4376, loss_single: 0.4376, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,845 - Iter: 70, Total Loss: 0.4373, loss_single: 0.4373, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,880 - Iter: 71, Total Loss: 0.4370, loss_single: 0.4370, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,916 - Iter: 72, Total Loss: 0.4367, loss_single: 0.4367, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,951 - Iter: 73, Total Loss: 0.4364, loss_single: 0.4364, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:58,987 - Iter: 74, Total Loss: 0.4361, loss_single: 0.4361, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:59,022 - Iter: 75, Total Loss: 0.4358, loss_single: 0.4358, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:59,057 - Iter: 76, Total Loss: 0.4356, loss_single: 0.4356, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec +2026-06-24 05:33:59,092 - 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Saving summary figures for iter 100 +2026-06-24 05:34:03,624 - ### Finished 100 iterations, averaged iter_t = 0.039123 with std = 0.040 ### +2026-06-24 05:34:03,624 - +2026-06-24 05:34:03,625 - ### The PtyRADSolver is finished in 9.245 sec ### +2026-06-24 05:34:03,625 - diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/objp_crop_08bit_iter0100.tif b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/objp_crop_08bit_iter0100.tif new file mode 100644 index 0000000000000000000000000000000000000000..6e9e09da6a453cd7eb0107dce8492104acd2227c Binary files /dev/null and b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/objp_crop_08bit_iter0100.tif differ diff --git a/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/simulation_data_aug9__sample_000033.yaml b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/simulation_data_aug9__sample_000033.yaml new file mode 100644 index 0000000000000000000000000000000000000000..28a16e0ac89015fd07c63c6eabb989c288d0adec --- /dev/null +++ b/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033/gendata3_std_02__simulation_data_aug9__sample_000033_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-348_C12_19.7_phi12_268_C21_922_phi21_298_C23_78.4_phi23_329_C30_1.15e+.01e+07_phi56_127/simulation_data_aug9__sample_000033.yaml @@ -0,0 +1,140 @@ +init_params: + probe_kv: 200.0 + probe_conv_angle: 9.665002822875977 + probe_aberrations: + C10: -347.6485900878906 + C12: 19.71487808227539 + C21: 922.2353515625 + C23: 78.35189056396484 + C30: 11504695.0 + C32: -4888.12646484375 + C34: -7394.74951171875 + C41: 174677.15625 + C43: 320952.75 + C45: 408759.40625 + C50: -1316927.5 + C52: -8313144.0 + C54: -733252.4375 + C56: 10132429.0 + phi12: 268.4273086457149 + phi21: 297.61008417653807 + phi23: 328.6197167442862 + phi32: 17.086734199425937 + phi34: 194.15273070511304 + phi41: 145.3564795763296 + phi43: 133.030856803908 + phi45: 243.34507816424386 + phi52: 357.47259413819785 + phi54: 242.33147809141397 + phi56: 126.58925075615561 + meas_Npix: 128 + pos_N_scan_slow: 16 + pos_N_scan_fast: 16 + pos_scan_step_size: 0.5299999713897705 + probe_pmode_max: 6 + obj_Nlayer: 1 + obj_slice_thickness: 20.0 + meas_permute: null + meas_reshape: + - 256 + - 128 + - 128 + meas_flipT: + - 0 + - 0 + - 0 + meas_crop: null + meas_pad: null + meas_resample: null + pos_scan_affine: null + meas_params: + path: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/gendata3_std_02/simulation_data_aug9__sample_000033_measurement.h5 + key: measurement + random_seed: 20261843 + obj_omode_max: 1 + meas_calibration: + mode: kMax + value: 2.5 +model_params: + detector_blur_std: null + update_params: + obja: + start_iter: 1 + lr: 0.0005 + end_iter: null + objp: + start_iter: 1 + lr: 0.0005 + end_iter: null + probe: + start_iter: 1 + lr: 0.0001 + end_iter: null + probe_pos_shifts: + start_iter: 1 + lr: 0.0005 + end_iter: null +loss_params: + loss_single: + state: true + weight: 1.0 + dp_pow: 0.5 + loss_poissn: + state: false + weight: 1.0 + dp_pow: 1.0 + eps: 1.0e-06 + loss_sparse: + state: false + weight: 0.1 + ln_order: 1 +constraint_params: + ortho_pmode: + start_iter: 1 + step: 1 + end_iter: null + fix_probe_int: + start_iter: 1 + step: 1 + end_iter: null + obj_rblur: + start_iter: null + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 0.4 + obj_zblur: + start_iter: 1 + step: 1 + end_iter: null + obj_type: both + kernel_size: 5 + std: 1 + obja_thresh: + start_iter: 1 + step: 1 + end_iter: null + relax: 0 + thresh: + - 0.96 + - 1.04 + objp_postiv: + start_iter: null + step: 1 + end_iter: null + relax: 0 +recon_params: + NITER: 100 + BATCH_SIZE: + size: 32 + grad_accumulation: 1 + SAVE_ITERS: 100 + output_dir: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/gendata3_std_02/simulation_data_aug9__sample_000033 + recon_dir_affixes: + - default + prefix: gendata3_std_02__simulation_data_aug9__sample_000033 + postfix: '' + compiler_configs: + enable: false + prefix_time: false