Scripts et figures manquantes

docs/11 - Modèle Chronos/scripts/plot_chronos_errors_combined.py

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+# scripts/plot_chronos_errors_combined.py
+from __future__ import annotations
+
+from pathlib import Path
+import re
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+DOC_DIR = Path(__file__).resolve().parent.parent
+DATA_DIR = DOC_DIR / "data"
+FIG_DIR = DOC_DIR / "figures"
+
+
+def load_errors() -> pd.DataFrame:
+    pattern = re.compile(r"chronos_forecast_(amazon__chronos-t5-[a-z]+)\.csv")
+    records = []
+    for csv in DATA_DIR.glob("chronos_forecast_*.csv"):
+        m = pattern.match(csv.name)
+        if not m:
+            continue
+        model = m.group(1).replace("__", "/")
+        df = pd.read_csv(csv)
+        if not {"y_true", "y_pred"}.issubset(df.columns):
+            continue
+        err = (df["y_pred"] - df["y_true"]).abs()
+        for i, v in enumerate(err, start=1):
+            records.append({"model": model, "horizon_h": i, "abs_error": v})
+    return pd.DataFrame(records)
+
+
+def plot_errors(df: pd.DataFrame, output_path: Path) -> None:
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    fig, ax = plt.subplots(figsize=(8, 4))
+    for model, sub in df.groupby("model"):
+        sub_sorted = sub.sort_values("horizon_h")
+        ax.plot(sub_sorted["horizon_h"], sub_sorted["abs_error"], label=model, linewidth=2)
+    ax.set_xlabel("Horizon (heures)")
+    ax.set_ylabel("Erreur absolue (°C)")
+    ax.set_title("Chronos T5 – erreur absolue vs horizon")
+    ax.grid(True, linestyle=":", alpha=0.4)
+    ax.legend()
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=150)
+    plt.close(fig)
+
+
+def main() -> None:
+    df = load_errors()
+    if df.empty:
+        raise SystemExit("Aucun fichier chronos_forecast_*.csv trouvé ou colonnes manquantes.")
+    plot_errors(df, FIG_DIR / "chronos_errors_combined.png")
+    print("✔ Figure : figures/chronos_errors_combined.png")
+
+
+if __name__ == "__main__":
+    main()

docs/11 - Modèle Chronos/scripts/plot_chronos_multi_errors.py

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+# scripts/plot_chronos_multi_errors.py
+from __future__ import annotations
+
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+DOC_DIR = Path(__file__).resolve().parent.parent
+DATA_DIR = DOC_DIR / "data"
+FIG_DIR = DOC_DIR / "figures"
+
+
+def _plot_temp_wind(df: pd.DataFrame, output: Path) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    fig, ax = plt.subplots(figsize=(6, 4))
+    for target in ("temperature", "wind_speed"):
+        sub = df[(df["target"] == target) & (df["kind"] == "reg")].sort_values("horizon_h")
+        ax.plot(sub["horizon_h"], sub["mae"], marker="o", label=f"{target} – MAE")
+        ax.plot(sub["horizon_h"], sub["rmse"], marker="s", label=f"{target} – RMSE", linestyle="--")
+    ax.set_xlabel("Horizon (heures)")
+    ax.set_ylabel("Erreur")
+    ax.set_title("Chronos small – erreurs température / vent")
+    ax.grid(True, linestyle=":", alpha=0.4)
+    ax.legend()
+    fig.tight_layout()
+    fig.savefig(output, dpi=150)
+    plt.close(fig)
+
+
+def _plot_rain(df: pd.DataFrame, output: Path) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    sub = df[(df["target"] == "rain_rate") & (df["kind"] == "cls")].sort_values("horizon_h")
+    fig, ax1 = plt.subplots(figsize=(6, 4))
+    ax1.plot(sub["horizon_h"], sub["f1"], marker="o", color="tab:blue", label="F1")
+    ax1.set_ylabel("F1", color="tab:blue")
+    ax1.tick_params(axis="y", labelcolor="tab:blue")
+
+    ax2 = ax1.twinx()
+    ax2.plot(sub["horizon_h"], sub["brier"], marker="s", color="tab:red", linestyle="--", label="Brier")
+    ax2.set_ylabel("Brier", color="tab:red")
+    ax2.tick_params(axis="y", labelcolor="tab:red")
+
+    ax1.set_xlabel("Horizon (heures)")
+    ax1.set_title("Chronos small – pluie (F1/Brier)")
+    ax1.grid(True, linestyle=":", alpha=0.4)
+
+    # Combine legends
+    handles, labels = [], []
+    for ax in (ax1, ax2):
+        h, l = ax.get_legend_handles_labels()
+        handles += h
+        labels += l
+    ax1.legend(handles, labels, loc="upper right")
+
+    fig.tight_layout()
+    fig.savefig(output, dpi=150)
+    plt.close(fig)
+
+
+def main() -> None:
+    metrics_path = DATA_DIR / "chronos_multi_metrics.csv"
+    if not metrics_path.exists():
+        raise SystemExit("chronos_multi_metrics.csv introuvable. Lancez run_chronos_multi.py d'abord.")
+    df = pd.read_csv(metrics_path)
+    _plot_temp_wind(df, FIG_DIR / "chronos_multi_errors_temp_wind.png")
+    _plot_rain(df, FIG_DIR / "chronos_multi_errors_rain.png")
+    print("✔ Figures : chronos_multi_errors_temp_wind.png, chronos_multi_errors_rain.png")
+
+
+if __name__ == "__main__":
+    main()