Ajoute les visualisations temporelles des palettes

lib/plots/colors_timeline.py

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+"""Visualisations temporelles des palettes de couleurs."""
+
+from pathlib import Path
+from typing import Dict, Iterable, List, Tuple
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from lib.filesystem import ensure_parent_dir
+from lib.rebrickable.stats import read_rows
+
+
+def load_rows(path: Path) -> List[dict]:
+    """Charge un CSV simple en mémoire sous forme de dictionnaires."""
+    return read_rows(path)
+
+
+def plot_translucent_share(timeline_path: Path, destination_path: Path) -> None:
+    """Trace l'évolution de la part de pièces translucides et du nombre de couleurs."""
+    rows = load_rows(timeline_path)
+    years = [int(row["year"]) for row in rows]
+    shares = [float(row["share_translucent"]) for row in rows]
+    distinct_counts = [int(row["colors_distinct"]) for row in rows]
+
+    fig, ax = plt.subplots(figsize=(12, 5))
+    ax.plot(years, shares, color="#1f77b4", marker="o", linewidth=2.2, label="Part des translucides")
+    ax.fill_between(years, shares, color="#1f77b4", alpha=0.15)
+    ax.set_ylabel("Part translucide")
+    ax.set_ylim(0, min(1.0, max(shares) * 1.1))
+    ax.set_xlabel("Année")
+    ax.grid(True, linestyle="--", alpha=0.3)
+    ax2 = ax.twinx()
+    ax2.plot(years, distinct_counts, color="#ff7f0e", marker="s", linewidth=1.8, label="Couleurs distinctes")
+    ax2.set_ylabel("Nombre de couleurs distinctes")
+    handles = [
+        plt.Line2D([0], [0], color="#1f77b4", marker="o", label="Part des translucides"),
+        plt.Line2D([0], [0], color="#ff7f0e", marker="s", label="Couleurs distinctes"),
+    ]
+    ax.legend(handles=handles, loc="upper left")
+    ax.set_title("Evolution des palettes : translucides vs. diversité des couleurs")
+    ax.set_xticks(years)
+    ax.tick_params(axis="x", labelrotation=45)
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=160)
+    plt.close(fig)
+
+
+def build_heatmap_data(rows: Iterable[dict]) -> Tuple[List[int], List[str], np.ndarray]:
+    """Construit les vecteurs année, labels de couleur et matrice de quantités."""
+    years = sorted({int(row["year"]) for row in rows})
+    color_totals: Dict[Tuple[str, str, str], int] = {}
+    for row in rows:
+        key = (row["color_name"], row["color_rgb"], row["is_translucent"])
+        color_totals[key] = color_totals.get(key, 0) + int(row["quantity_total"])
+    sorted_colors = sorted(
+        color_totals.items(),
+        key=lambda item: (-item[1], item[0][0], item[0][1]),
+    )
+    color_keys = [color for color, _ in sorted_colors]
+    labels = [f"{name} ({'trans' if is_trans == 'true' else 'opaque'})" for name, _, is_trans in color_keys]
+    matrix = np.zeros((len(color_keys), len(years)), dtype=float)
+    index_by_year = {year: idx for idx, year in enumerate(years)}
+    index_by_color = {color: idx for idx, color in enumerate(color_keys)}
+    for row in rows:
+        color_key = (row["color_name"], row["color_rgb"], row["is_translucent"])
+        y_index = index_by_color[color_key]
+        x_index = index_by_year[int(row["year"])]
+        matrix[y_index, x_index] += int(row["quantity_total"])
+    return years, labels, matrix
+
+
+def plot_colors_heatmap(matrix_path: Path, destination_path: Path) -> None:
+    """Génère une heatmap année × couleur basée sur les quantités totales."""
+    rows = load_rows(matrix_path)
+    years, labels, matrix = build_heatmap_data(rows)
+    values = np.log1p(matrix)
+
+    fig, ax = plt.subplots(figsize=(14, max(6, len(labels) * 0.24)))
+    heatmap = ax.imshow(values, aspect="auto", cmap="magma", origin="lower")
+    ax.set_xticks(range(len(years)))
+    ax.set_xticklabels(years, rotation=45)
+    ax.set_yticks(range(len(labels)))
+    ax.set_yticklabels(labels)
+    ax.set_xlabel("Année")
+    ax.set_title("Intensité des couleurs par année (log1p des quantités)")
+    cbar = fig.colorbar(heatmap, ax=ax, shrink=0.82)
+    cbar.set_label("log1p(quantité totale)")
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=170)
+    plt.close(fig)