"""在 mole 环境中运行：把数据集所有唯一 SMILES 编码成 MolE 表征缓存。

用法（工作目录 = lnp_ml 根，且已 pip install -e mole_public）:
    pyenv activate mole
    python scripts/precompute_mole.py --ckpt MolE_ckpt/model.pth \
        --out data/processed/mole_embeddings.npz

产物 .npz 含 "smiles" (N,) 与 "embeddings" (N, D=8000)。
"""
import argparse
from pathlib import Path
import numpy as np
import pandas as pd

DATA_FILES = ["data/interim/internal.csv", "data/external/all_data_LiON.csv"]
GLOB_FILES = ["data/external/all_amine_split_for_LiON/cv_*/train.csv",
              "data/external/all_amine_split_for_LiON/cv_*/test.csv"]

def collect_smiles(root: Path) -> list:
    seen = set()
    files = [root / f for f in DATA_FILES]
    for pat in GLOB_FILES:
        files += sorted(root.glob(pat))
    for f in files:
        if not f.exists():
            print(f"跳过不存在: {f}"); continue
        df = pd.read_csv(f, low_memory=False)
        if "smiles" in df.columns:
            seen.update(df["smiles"].dropna().astype(str).tolist())
    return sorted(seen)

def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--ckpt", default="MolE_ckpt/model.pth", help="MolE 权重(或权重目录)")
    ap.add_argument("--out", default="data/processed/mole_embeddings.npz")
    ap.add_argument("--root", default=".")
    ap.add_argument("--batch-size", type=int, default=32)
    ap.add_argument("--num-workers", type=int, default=4)
    args = ap.parse_args()

    from mole import mole_predict

    smiles = collect_smiles(Path(args.root))
    print(f"收集到 {len(smiles)} 个唯一 SMILES，开始 MolE 编码...")

    emb = mole_predict.encode(
        smiles=smiles, pretrained_model=args.ckpt,
        batch_size=args.batch_size, num_workers=args.num_workers,
    )
    emb = np.asarray(emb, dtype=np.float32)
    print(f"embeddings.shape = {emb.shape}")     # 期望 (N, 8000)
    assert emb.shape[0] == len(smiles), "encode 丢弃了部分 SMILES，需对齐后再存"

    out = Path(args.out); out.parent.mkdir(parents=True, exist_ok=True)
    np.savez_compressed(out, smiles=np.array(smiles), embeddings=emb)
    print(f"已保存 {emb.shape} 到 {out}")

if __name__ == "__main__":
    main()