Download scripts/fake_data.py from OneScience-Group/PrecipExtremes-GAN: direct link, hf CLI and curl.
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- Download file 775 Bytes
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https://huggingface.co/OneScience-Group/PrecipExtremes-GAN/resolve/main/scripts/fake_data.py
- Command line
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hf download hf://OneScience-Group/PrecipExtremes-GAN/scripts/fake_data.py
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curl -L -o fake_data.py https://huggingface.co/OneScience-Group/PrecipExtremes-GAN/resolve/main/scripts/fake_data.py
775 Bytes
| from pathlib import Path | |
| import sys,numpy as np | |
| ROOT=Path(__file__).resolve().parents[1];sys.path.insert(0,str(ROOT)) | |
| from model.precip_extremes_gan import load_config,make_data | |
| c=load_config(ROOT);d=c["data"];records=make_data(d["samples_per_period"],*d["high_grid"],*d["low_grid"],c["seed"]);x=np.stack([r[0] for r in records]);y=np.stack([r[1] for r in records]);period=np.array([r[2] for r in records]);split=np.array(["train" if i%d["samples_per_period"]<d["samples_per_period"]-4 else "test" for i in range(len(records))]);path=ROOT/d["path"];path.parent.mkdir(parents=True,exist_ok=True);np.savez_compressed(path,format_version=np.array(d["format_version"]),predictors=x,precipitation=y,period=period,split=split,unit=np.array("mm day-1"));print(path,x.shape,y.shape) | |