--- license: cc-by-4.0 tags: - physics-informed - spectroscopy - infrared - synthetic pretty_name: PIDU simulated datasets --- # PIDU simulated datasets Simulated infrared spectra (Transfer Matrix Method, random Drude-Lorentz layer and oscillator parameters) with their ground-truth parameters, used to train and test the models of **Physics-infused Deep Unfolding for Automated Material Parameter Extraction of Optical Data** (Koumans, Stevens, van Sloun, van Mechelen). Code: https://github.com/MKoumans/PIDU · Checkpoints: [`MKoumans/pidu-optical-parameter-extraction`](https://huggingface.co/MKoumans/pidu-optical-parameter-extraction) ## Contents | Path | Content | | --- | --- | | `data/datasets/usecase1/*.npz` | Use case 1: train / val / test sets | | `data/datasets/usecase2/*.npz` | Use case 2: train / val / test sets, with (`wsn`) and without (`nwsn`) the second system | | `data/labels/*.xlsx` | Label mappings used during dataset generation | | `outputs/case/outputs/loss_{CNN,DU,PIDU}__001/` | Test exports of the trained runs (8 seeds per model; use case 2 includes `test_exp`, the predictions on the measured spectra) | | `outputs/case/loss/loss_{CNN,DU,PIDU}__001/` | Per-epoch train / val / test loss of those runs | | `outputs/case/logs/train__.log` | Training logs of those runs | | `models/usecase/-t01-.pt` | Checkpoints of those runs (the Fig. 2 timings average over seeds) | | `outputs/case/outputs/loss_lma_{baseline,noisy,random}/` | TRF (LMA) baseline: use case 1 on the 1024 simulated test spectra, use case 2 on the 75 measured spectra | Each `.npz` holds the clean spectra (`data_y_*`), noised spectra (`data_y_noised_*`), initial and target parameters (`data_x_*`), and the wavenumber axis (`wn_*`). **Not included:** the experimental SrTiO₃ measurements themselves (the predictions and fits on them are). ## Usage ```bash pidu-hub download --usecase 1 2 # everything pidu-hub download --what data logs --usecase 1 # datasets and training logs only ``` ## Citation To be added.