Ajout des vues calendrier à l'étape 3

docs/03 - Premiers graphiques/scripts/plot_calendar_overview.py

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+# docs/03 - Premiers graphiques/scripts/plot_calendar_overview.py
+from __future__ import annotations
+
+from pathlib import Path
+import sys
+
+import calendar
+import numpy as np
+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.analysis import compute_daily_rainfall_totals
+from meteo.plots import export_plot_dataset, plot_calendar_heatmap, plot_weekday_profiles
+from meteo.variables import VARIABLES_BY_KEY
+
+
+DOC_DIR = Path(__file__).resolve().parent.parent
+CSV_PATH = PROJECT_ROOT / "data" / "weather_minutely.csv"
+OUTPUT_DIR = DOC_DIR / "figures" / "calendar"
+
+WEEKDAY_VARIABLE_KEYS = ["temperature", "humidity", "wind_speed", "illuminance"]
+
+
+def _format_calendar_matrix(series: pd.Series, year: int, agg_label: str) -> pd.DataFrame:
+    """
+    Transforme une série quotidienne en matrice mois x jours (1-31).
+    """
+    start = pd.Timestamp(year=year, month=1, day=1, tz=series.index.tz)
+    end = pd.Timestamp(year=year, month=12, day=31, tz=series.index.tz)
+    filtered = series.loc[(series.index >= start) & (series.index <= end)]
+
+    matrix = pd.DataFrame(
+        np.nan,
+        index=[calendar.month_name[m][:3] for m in range(1, 13)],
+        columns=list(range(1, 32)),
+    )
+
+    for timestamp, value in filtered.items():
+        month = timestamp.month
+        day = timestamp.day
+        matrix.at[calendar.month_name[month][:3], day] = value
+
+    matrix.index.name = f"{agg_label} ({year})"
+    return matrix
+
+
+def compute_daily_mean(df: pd.DataFrame, column: str) -> pd.Series:
+    return df[column].resample("1D").mean()
+
+
+def main() -> None:
+    if not CSV_PATH.exists():
+        print(f"⚠ Fichier introuvable : {CSV_PATH}")
+        return
+
+    df = load_raw_csv(CSV_PATH)
+    if df.empty:
+        print("⚠ Dataset vide.")
+        return
+
+    if not isinstance(df.index, pd.DatetimeIndex):
+        print("⚠ Le dataset doit avoir un index temporel.")
+        return
+
+    print(f"Dataset minuté chargé : {CSV_PATH}")
+    print(f"  Lignes   : {len(df)}")
+    print(f"  Colonnes : {list(df.columns)}")
+    print()
+
+    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+    latest_year = df.index.year.max()
+    print(f"Année retenue pour le calendrier : {latest_year}")
+
+    daily_totals = compute_daily_rainfall_totals(df=df)
+    daily_rain = daily_totals["daily_total"]
+    rain_matrix = _format_calendar_matrix(daily_rain, latest_year, "Pluie (mm)")
+    rain_matrix.attrs["cmap"] = "Blues"
+    rain_matrix.attrs["colorbar_label"] = "mm"
+    rain_path = OUTPUT_DIR / f"calendar_rain_{latest_year}.png"
+    plot_calendar_heatmap(
+        matrix=rain_matrix,
+        output_path=rain_path,
+        title=f"Pluie quotidienne - {latest_year}",
+        cmap="Blues",
+        colorbar_label="mm",
+    )
+    print(f"✔ Heatmap pluie {latest_year} : {rain_path}")
+
+    daily_temp = compute_daily_mean(df, "temperature")
+    temp_matrix = _format_calendar_matrix(daily_temp, latest_year, "Température (°C)")
+    temp_matrix.attrs["cmap"] = "coolwarm"
+    temp_matrix.attrs["colorbar_label"] = "°C"
+    temp_path = OUTPUT_DIR / f"calendar_temperature_{latest_year}.png"
+    plot_calendar_heatmap(
+        matrix=temp_matrix,
+        output_path=temp_path,
+        title=f"Température moyenne quotidienne - {latest_year}",
+        cmap="coolwarm",
+        colorbar_label="°C",
+    )
+    print(f"✔ Heatmap température {latest_year} : {temp_path}")
+
+    if "pressure" in df.columns:
+        daily_pressure = compute_daily_mean(df, "pressure")
+        pressure_matrix = _format_calendar_matrix(daily_pressure, latest_year, "Pression (hPa)")
+        pressure_matrix.attrs["cmap"] = "Greens"
+        pressure_matrix.attrs["colorbar_label"] = "hPa"
+        pressure_path = OUTPUT_DIR / f"calendar_pressure_{latest_year}.png"
+        plot_calendar_heatmap(
+            matrix=pressure_matrix,
+            output_path=pressure_path,
+            title=f"Pression moyenne quotidienne - {latest_year}",
+            cmap="Greens",
+            colorbar_label="hPa",
+        )
+        print(f"✔ Heatmap pression {latest_year} : {pressure_path}")
+
+    if "illuminance" in df.columns:
+        daily_lux = compute_daily_mean(df, "illuminance")
+        lux_matrix = _format_calendar_matrix(daily_lux, latest_year, "Illuminance (lux)")
+        lux_matrix.attrs["cmap"] = "YlOrBr"
+        lux_matrix.attrs["colorbar_label"] = "lux"
+        lux_path = OUTPUT_DIR / f"calendar_illuminance_{latest_year}.png"
+        plot_calendar_heatmap(
+            matrix=lux_matrix,
+            output_path=lux_path,
+            title=f"Illuminance moyenne quotidienne - {latest_year}",
+            cmap="YlOrBr",
+            colorbar_label="lux",
+        )
+        print(f"✔ Heatmap illuminance {latest_year} : {lux_path}")
+
+    if "wind_speed" in df.columns:
+        daily_wind = compute_daily_mean(df, "wind_speed")
+        wind_matrix = _format_calendar_matrix(daily_wind, latest_year, "Vent (km/h)")
+        wind_matrix.attrs["cmap"] = "Purples"
+        wind_matrix.attrs["colorbar_label"] = "km/h"
+        wind_path = OUTPUT_DIR / f"calendar_wind_{latest_year}.png"
+        plot_calendar_heatmap(
+            matrix=wind_matrix,
+            output_path=wind_path,
+            title=f"Vitesse moyenne du vent - {latest_year}",
+            cmap="Purples",
+            colorbar_label="km/h",
+        )
+        print(f"✔ Heatmap vent {latest_year} : {wind_path}")
+
+    hourly = df[WEEKDAY_VARIABLE_KEYS].resample("1h").mean()
+    weekday_stats = hourly.groupby(hourly.index.dayofweek).mean()
+    weekday_path = OUTPUT_DIR / "weekday_profiles.png"
+    variables = [VARIABLES_BY_KEY[key] for key in WEEKDAY_VARIABLE_KEYS]
+    plot_weekday_profiles(
+        weekday_df=weekday_stats,
+        variables=variables,
+        output_path=weekday_path,
+        title="Profils moyens par jour de semaine",
+    )
+    print(f"✔ Profils hebdomadaires : {weekday_path}")
+
+    print("✔ Graphiques calendrier générés.")
+
+
+if __name__ == "__main__":
+    main()