# scripts/plot_lagged_correlations.py
from __future__ import annotations

from pathlib import Path
import sys


PROJECT_ROOT = Path(__file__).resolve().parents[3]
if str(PROJECT_ROOT) not in sys.path:
    sys.path.insert(0, str(PROJECT_ROOT))

from meteo.dataset import load_raw_csv
from meteo.variables import VARIABLES_BY_KEY
from meteo.analysis import compute_lagged_correlation
from meteo.plots import plot_lagged_correlation
from meteo.correlation_presets import DEFAULT_LAGGED_PAIRS


CSV_PATH = Path("data/weather_minutely.csv")
DOC_DIR = Path(__file__).resolve().parent.parent
OUTPUT_DIR = DOC_DIR / "figures" / "lagged_correlations"


def main() -> None:
    if not CSV_PATH.exists():
        print(f"⚠ Fichier introuvable : {CSV_PATH}")
        return

    df = load_raw_csv(CSV_PATH)
    print(f"Dataset minuté chargé : {CSV_PATH}")
    print(f"  Lignes   : {len(df)}")
    print(f"  Colonnes : {list(df.columns)}")
    print()

    for key_x, key_y in DEFAULT_LAGGED_PAIRS:
        var_x = VARIABLES_BY_KEY[key_x]
        var_y = VARIABLES_BY_KEY[key_y]

        print(f"→ Corrélation décalée : {var_x.key} → {var_y.key}")

        lag_df = compute_lagged_correlation(
            df=df,
            var_x=var_x,
            var_y=var_y,
            max_lag_minutes=360,   # ± 6 heures
            step_minutes=10,       # pas de 10 minutes
            method="pearson",
        )

        filename = f"lagcorr_{var_x.key}_to_{var_y.key}.png"
        output_path = OUTPUT_DIR / filename

        plot_lagged_correlation(
            lag_df=lag_df,
            var_x=var_x,
            var_y=var_y,
            output_path=output_path,
        )

    print("✔ Graphiques de corrélation décalée générés.")


if __name__ == "__main__":
    main()
