Download scripts/validate_era5_dataset.py from OneScience-Group/ERA5: direct link, hf CLI and curl.
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https://huggingface.co/datasets/OneScience-Group/ERA5/resolve/main/scripts/validate_era5_dataset.py
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curl -L -o validate_era5_dataset.py https://huggingface.co/datasets/OneScience-Group/ERA5/resolve/main/scripts/validate_era5_dataset.py
3.4 kB
| #!/usr/bin/env python3 | |
| """Validate the standardized ERA5 HDF5 dataset package.""" | |
| from __future__ import annotations | |
| import argparse | |
| from pathlib import Path | |
| import h5py | |
| def read_variables(fields) -> list[str]: | |
| return [ | |
| v.decode() if isinstance(v, bytes) else str(v) | |
| for v in fields.attrs.get("variables", []) | |
| ] | |
| def check_file(path: Path, expected_variables: list[str] | None) -> list[str]: | |
| with h5py.File(path, "r") as f: | |
| for name in ("fields", "global_means", "global_stds"): | |
| if name not in f: | |
| raise RuntimeError(f"{path}: missing dataset {name}") | |
| fields = f["fields"] | |
| if fields.dtype.name != "float32": | |
| raise RuntimeError(f"{path}: fields dtype is {fields.dtype}, expected float32") | |
| if len(fields.shape) != 4: | |
| raise RuntimeError(f"{path}: fields shape is {fields.shape}, expected [T, C, H, W]") | |
| if fields.shape[1:] != (243, 721, 1440): | |
| raise RuntimeError(f"{path}: fields shape {fields.shape}, expected [T, 243, 721, 1440]") | |
| if f["global_means"].shape != (1, 243, 1, 1): | |
| raise RuntimeError(f"{path}: global_means shape is {f['global_means'].shape}") | |
| if f["global_stds"].shape != (1, 243, 1, 1): | |
| raise RuntimeError(f"{path}: global_stds shape is {f['global_stds'].shape}") | |
| variables = read_variables(fields) | |
| if len(variables) != 243: | |
| raise RuntimeError(f"{path}: variables length is {len(variables)}, expected 243") | |
| if expected_variables is not None and variables != expected_variables: | |
| raise RuntimeError(f"{path}: variables attr differs from first checked file") | |
| if int(fields.attrs.get("time_step", -1)) != 6: | |
| raise RuntimeError(f"{path}: time_step is {fields.attrs.get('time_step')}, expected 6") | |
| _ = fields[0, 0, 0, 0] | |
| _ = f["global_means"][0, 0, 0, 0] | |
| _ = f["global_stds"][0, 0, 0, 0] | |
| return variables | |
| def main() -> int: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--data-dir", default="data", help="directory containing yearly *.h5 files") | |
| parser.add_argument("--expected-start-year", type=int, default=1979) | |
| parser.add_argument("--expected-end-year", type=int, default=2025) | |
| parser.add_argument("--check-all", action="store_true", help="inspect every yearly file") | |
| args = parser.parse_args() | |
| data_dir = Path(args.data_dir).resolve() | |
| files = sorted(data_dir.glob("*.h5")) | |
| if not files: | |
| raise FileNotFoundError(f"no HDF5 files found under {data_dir}") | |
| expected_names = [f"{year}.h5" for year in range(args.expected_start_year, args.expected_end_year + 1)] | |
| actual_names = [p.name for p in files] | |
| missing = [name for name in expected_names if name not in actual_names] | |
| if missing: | |
| raise FileNotFoundError(f"missing expected yearly files: {missing[:10]}") | |
| to_check = files if args.check_all else [data_dir / expected_names[0], data_dir / expected_names[-1]] | |
| variables = None | |
| for path in to_check: | |
| variables = check_file(path, variables) | |
| print("ERA5 dataset validation passed") | |
| print(f"data_dir: {data_dir}") | |
| print(f"files: {len(files)}") | |
| print(f"checked_files: {len(to_check)}") | |
| print(f"variables: {len(variables or [])}") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |