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1aeffbb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | """Generate a small synthetic dataset description for local smoke tests."""
import argparse
import json
from pathlib import Path
import numpy as np
import yaml
try:
import h5py
except ImportError as exc:
raise SystemExit("fake_data.py requires h5py; install it in the active OneScience environment") from exc
ROOT = Path(__file__).resolve().parents[1]
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--config", default=str(ROOT / "conf/config.yaml"))
parser.add_argument("--output", default=None)
args = parser.parse_args()
with open(args.config, encoding="utf-8") as handle:
config = yaml.safe_load(handle)
metadata = {
"variables": config["data"]["channels"],
"grid": config["data"]["grid"],
"input_steps": config["data"]["input_steps"],
"output_steps": config["data"]["output_steps"],
"time_resolution": "1 day",
"source": "synthetic; not GLORYS12 values",
}
data_root = ROOT / config["data"]["data_dir"] / "data"
data_root.mkdir(parents=True, exist_ok=True)
fields = np.random.default_rng(config["project"]["seed"]).standard_normal(
(config["data"]["synthetic_samples"] + config["data"]["input_steps"],
len(config["data"]["channels"]), *config["data"]["grid"]), dtype=np.float32
)
with h5py.File(data_root / "2000.h5", "w") as handle:
dataset = handle.create_dataset("fields", data=fields)
dataset.attrs["variables"] = config["data"]["channels"]
dataset.attrs["time_step"] = 24
output = Path(args.output or ROOT / config["data"]["data_dir"] / "synthetic_metadata.json")
output.parent.mkdir(parents=True, exist_ok=True)
output.write_text(json.dumps(metadata, indent=2) + "\n", encoding="utf-8")
print(f"saved={output}")
if __name__ == "__main__":
main()
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