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import argparse
import shutil
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
def main(args):
path = Path(args.path)
root = Path(__file__).parent
df_all = pd.read_csv(root / "metadata_all.csv", index_col=0)
df = pd.read_csv(root / "metadata.csv", index_col=0)
missing_files = np.array(list(set(df_all.index) - set(df.index)))
exists = np.array([(path / f"{f}.h5ad").exists() for f in missing_files])
print(f"Found {exists.sum()} missing files out of {len(exists)}")
existing_files = missing_files[exists]
if args.dry_run:
print(f"Files will be copied inside {root}/<species>/<tissue>")
else:
for name in tqdm(existing_files, desc="Copying files"):
species, tissue = df_all.loc[name, ["species", "tissue"]].values
src = path / f"{name}.h5ad"
dst_dir: Path = root / species / tissue
dst = dst_dir / f"{name}.h5ad"
dst_dir.mkdir(parents=True, exist_ok=True)
shutil.copyfile(src, dst)
if not args.dry_run:
print(f"Appending {len(existing_files)} files to metadata.csv")
df_all.loc[existing_files].to_csv(root / "metadata.csv", mode="a", header=False)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"-p",
"--path",
type=str,
required=True,
help="Path to the data directories containing h5ad files to add",
)
parser.add_argument(
"--dry-run",
action="store_true",
help="Perform a dry run without copying files",
)
main(parser.parse_args())
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