from __future__ import annotations

from pathlib import Path
import sys

import pandas as pd

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, Variable
from meteo.plots import plot_weekday_profiles


CSV_PATH = PROJECT_ROOT / "data" / "weather_minutely.csv"
DOC_DIR = Path(__file__).resolve().parent.parent
OUTPUT_PATH = DOC_DIR / "figures" / "weekday_profiles.png"

# On se concentre sur le ressenti "agréable" : température, humidité, lumière.
VARIABLE_KEYS = ["temperature", "humidity", "illuminance"]


def compute_weekday_means(df: pd.DataFrame, variables: list[Variable]) -> pd.DataFrame:
    """
    Calcule, pour chaque jour de semaine (0=lundi,…,6=dimanche),
    la moyenne des variables fournies.
    """
    if df.empty:
        return pd.DataFrame(index=range(7))

    weekday_index = df.index.dayofweek
    columns = [var.column for var in variables]
    weekday_means = df.groupby(weekday_index)[columns].mean()
    # S'assure que toutes les valeurs 0–6 sont présentes, même si certaines manquent.
    weekday_means = weekday_means.reindex(range(7))
    weekday_means.index.name = "weekday"
    return weekday_means


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()

    variables = [VARIABLES_BY_KEY[key] for key in VARIABLE_KEYS]
    weekday_means = compute_weekday_means(df, variables)

    output_path = plot_weekday_profiles(
        weekday_df=weekday_means,
        variables=variables,
        output_path=OUTPUT_PATH,
        title="Moyennes par jour de semaine",
    )

    print(f"✔ Profils hebdomadaires exportés : {output_path}")

    weekday_labels_long = ["lundi", "mardi", "mercredi", "jeudi", "vendredi", "samedi", "dimanche"]
    for var in variables:
        series = weekday_means[var.column]
        if series.isna().all():
            continue
        best_idx = int(series.idxmax())
        best_label = weekday_labels_long[best_idx]
        best_value = series.max()
        unit = f" {var.unit}" if var.unit else ""
        print(f"  → {var.label} maximale en moyenne le {best_label} (≈{best_value:.2f}{unit})")


if __name__ == "__main__":
    main()