# Copyright (C) 2026 Hector van der Aa <hector@h3cx.dev>
# Copyright (C) 2026 Pierre Barbier <pierrebarbier741@gmail.com>
# Copyright (C) 2026 Association Exergie <association.exergie@gmail.com>
# SPDX-License-Identifier: GPL-3.0-or-later

import argparse
from pathlib import Path

import pandas as pd
from tqdm import tqdm


def filter_data(file: Path) -> pd.DataFrame:
    df = pd.read_csv(file, usecols=["time_us", "crank", "cam"])

    crank_df = df.loc[df["crank"] == 1, ["time_us"]].copy()

    crank_df["d1"] = crank_df["time_us"].diff()
    crank_df["prev_d1"] = crank_df["d1"].shift(1)
    crank_df["d2"] = crank_df["d1"] - crank_df["prev_d1"]
    crank_df["ratio"] = crank_df["d2"] / crank_df["d1"]

    crank_df = crank_df.dropna(subset=["d1", "d2", "ratio"])

    return crank_df[["time_us", "d1", "d2", "ratio"]]


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("directory", type=Path, help="Source data directory")
    args = parser.parse_args()

    directory: Path = args.directory

    if not directory.is_dir():
        parser.error(f"{directory} is not a valid directory")

    print(f"Processing data in: {directory}")

    concat_files: list[Path] = []

    for path in directory.glob("*.csv"):
        stem = path.stem

        try:
            base_name, channel = stem.rsplit("_", 1)
        except ValueError:
            print(f"Skipping badly named file: {path}")
            continue

        if channel != "trimmed":
            print(f"Skipping unknown file: {path}")
            continue

        concat_files.append(path)

    for file in tqdm(concat_files, desc="Files"):
        base_name, _ = file.stem.rsplit("_", 1)
        output = file.parent / f"{base_name}_derivative.csv"

        out_df = filter_data(file)
        out_df.to_csv(output, index=False)


if __name__ == "__main__":
    main()