"""Download and prepare the filtered K562 and RPE1 datasets used by CausalBench."""

import argparse
from pathlib import Path
import subprocess

import numpy as np
import pandas as pd

from upstream.preprocessing import preprocess_dataset

ROOT = Path(__file__).resolve().parent
RAW = ROOT / "data/raw"
DATASETS = {
    "k562": (35773219, "TabB_K562_day6_summary_stat"),
    "rpe1": (35775606, "TabC_RPE1_summary_statistic"),
}
SUMMARY_URL = "https://ars.els-cdn.com/content/image/1-s2.0-S0092867422005979-mmc2.xlsx"


def download(url, path):
    if path.exists():
        return path
    path.parent.mkdir(parents=True, exist_ok=True)
    partial = path.with_suffix(path.suffix + ".part")
    subprocess.run(
        ["curl", "--fail", "--location", "--retry", "3", "--continue-at", "-",
         "--output", str(partial), url],
        check=True,
    )
    partial.replace(path)
    return path


def prepare(name, output_dir):
    npz = output_dir / f"dataset_{name}_filtered.npz"
    tsv = output_dir / f"causalbench_{name}.tsv.gz"
    if npz.exists() and tsv.exists():
        print(f"{name}: using existing files in {output_dir}")
        return
    if npz.exists() or tsv.exists():
        raise FileExistsError("Output is incomplete. Choose a new --output-dir to rebuild.")

    _, sheet = DATASETS[name]
    summary = pd.read_excel(RAW / "summary_stats.xlsx", sheet_name=sheet)
    expression, genes, labels = preprocess_dataset(str(RAW / f"{name}.h5ad"), summary)
    output_dir.mkdir(parents=True, exist_ok=True)
    np.savez(npz, expression_matrix=expression, var_names=np.asarray(genes, dtype=str),
             interventions=np.asarray(labels, dtype=str))
    table = pd.DataFrame(expression, columns=genes)
    table["intervention"] = labels
    table.to_csv(tsv, sep="\t", index=False, compression="gzip")
    print(f"{name}: saved {expression.shape[0]:,} cells × {expression.shape[1]} genes")


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("dataset", choices=["k562", "rpe1", "all"], nargs="?", default="all")
    parser.add_argument("--download-only", action="store_true")
    parser.add_argument("--output-dir", type=Path, default=ROOT / "data/prepared")
    args = parser.parse_args()
    names = DATASETS if args.dataset == "all" else [args.dataset]
    download(SUMMARY_URL, RAW / "summary_stats.xlsx")
    for name in names:
        file_id, _ = DATASETS[name]
        download(f"https://ndownloader.figshare.com/files/{file_id}", RAW / f"{name}.h5ad")
        if args.download_only:
            print(f"{name}: raw data ready in {RAW}")
        else:
            prepare(name, args.output_dir)