| 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()) |
|
|