#!/usr/bin/env python3
"""Prepare vocab and normalization stats for HAI 21.03."""

import json
from typing import Optional

from data_utils import compute_cont_stats, build_vocab, load_split

DATA_PATH = "/home/anay/Dev/diffusion/dataset/hai/hai-21.03/train1.csv.gz"
SPLIT_PATH = "/home/anay/Dev/diffusion/mask-ddpm/example/feature_split.json"
OUT_STATS = "/home/anay/Dev/diffusion/mask-ddpm/example/results/cont_stats.json"
OUT_VOCAB = "/home/anay/Dev/diffusion/mask-ddpm/example/results/disc_vocab.json"


def main(max_rows: Optional[int] = None):
    split = load_split(SPLIT_PATH)
    cont_cols = split["continuous"]
    disc_cols = split["discrete"]

    mean, std = compute_cont_stats(DATA_PATH, cont_cols, max_rows=max_rows)
    vocab = build_vocab(DATA_PATH, disc_cols, max_rows=max_rows)

    with open(OUT_STATS, "w", encoding="ascii") as f:
        json.dump({"mean": mean, "std": std, "max_rows": max_rows}, f, indent=2)

    with open(OUT_VOCAB, "w", encoding="ascii") as f:
        json.dump({"vocab": vocab, "max_rows": max_rows}, f, indent=2)


if __name__ == "__main__":
    # Default: sample 50000 rows for speed. Set to None for full scan.
    main(max_rows=50000)