Download code/records/sqg/fid_adapter.json from coarse-grained-forecasting-benchmark/forecasting-models: direct link, hf CLI and curl.
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- Download file 1.1 kB
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https://huggingface.co/coarse-grained-forecasting-benchmark/forecasting-models/resolve/main/code/records/sqg/fid_adapter.json
- Command line
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hf download hf://coarse-grained-forecasting-benchmark/forecasting-models/code/records/sqg/fid_adapter.json
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curl -L -o fid_adapter.json https://huggingface.co/coarse-grained-forecasting-benchmark/forecasting-models/resolve/main/code/records/sqg/fid_adapter.json
1.1 kB
| { | |
| "adapter": "passive_scalar_coarse", | |
| "field_kind": "signed", | |
| "quantile": 0.9999, | |
| "clip_c": 1.1251138597965493, | |
| "range": [ | |
| -1.1251138597965493, | |
| 1.1251138597965493 | |
| ], | |
| "n_train_states": 65600, | |
| "field_shape": [ | |
| 128, | |
| 128 | |
| ], | |
| "pixel_stride": 4, | |
| "n_pixel_values": 67174400, | |
| "map": "uint8 = rint((clip(w,-c,c)+c)/(2c)*255)", | |
| "channels": "3 identical (grayscale scalar field), no colormap", | |
| "source": { | |
| "packaged_dataset_path": "<dataset>", | |
| "block": "vecs_train", | |
| "ics": "canonical rows 0..79", | |
| "members": "j < 20", | |
| "snapshots": "all", | |
| "pixel_stride": 4, | |
| "n_states": 65600, | |
| "rule": "training data only; validation, test and generated data never enter" | |
| }, | |
| "state": "196-D coarse spectral passive scalar (98 complex modes |k| <= 8, Hermitian half, theta_hat / N^2)", | |
| "reconstruction": "exact inverse FFT of the |k| <= 8 modes on a 128x128 grid (alias-free)", | |
| "n_disp": 128, | |
| "k_c": 8, | |
| "clip": "symmetric [-c, c], c = Q_q(|theta|) over the training pool", | |
| "physical_diagnostic": "scalar_variance_ratio = mean_gen sum|theta_hat_k|^2 / mean_truth sum|theta_hat_k|^2" | |
| } | |