Ajouter la frise des top couleurs annuelles

lib/plots/colors_timeline.py

@@ -1,7 +1,7 @@
 """Visualisations temporelles des palettes de couleurs."""
 
 from pathlib import Path
-from typing import Dict, Iterable, List, Tuple
+from typing import Dict, Iterable, List, Sequence, Tuple
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -115,6 +115,80 @@ def build_heatmap_data(rows: Iterable[dict]) -> Tuple[List[int], List[str], np.n
     return years, labels, matrix, swatches
 
 
+def build_top_colors_by_year(rows: Iterable[dict], limit: int = 5) -> List[dict]:
+    """Extrait les principales couleurs par année avec leur part relative."""
+    totals_by_year: Dict[int, int] = {}
+    grouped: Dict[int, List[dict]] = {}
+    for row in rows:
+        year = int(row["year"])
+        quantity = int(row["quantity_total"])
+        totals_by_year[year] = totals_by_year.get(year, 0) + quantity
+        grouped.setdefault(year, []).append(row)
+    top_rows: List[dict] = []
+    for year in sorted(grouped.keys()):
+        entries = grouped[year]
+        entries.sort(key=lambda r: (-int(r["quantity_total"]), r["color_name"], r["color_rgb"]))
+        total = totals_by_year[year]
+        for rank, entry in enumerate(entries[:limit]):
+            quantity = int(entry["quantity_total"])
+            share = quantity / total if total > 0 else 0.0
+            top_rows.append(
+                {
+                    "year": year,
+                    "rank": rank,
+                    "color_name": entry["color_name"],
+                    "color_rgb": entry["color_rgb"],
+                    "is_translucent": entry["is_translucent"],
+                    "quantity_total": quantity,
+                    "share": share,
+                }
+            )
+    return top_rows
+
+
+def plot_top_colors_swatches(
+    matrix_path: Path,
+    destination_path: Path,
+    limit: int = 5,
+) -> None:
+    """Affiche une frise des top couleurs par année (5 pastilles empilées par année)."""
+    rows = load_rows(matrix_path)
+    if not rows:
+        return
+    top_rows = build_top_colors_by_year(rows, limit=limit)
+    years = sorted({row["year"] for row in top_rows})
+    year_positions = {year: idx for idx, year in enumerate(years)}
+    x_values = [year_positions[row["year"]] for row in top_rows]
+    y_values = [limit - row["rank"] - 1 for row in top_rows]
+    ordered_hex = sort_hex_colors_lab({row["color_rgb"] for row in top_rows})
+    hex_rank = {hex_value: idx for idx, hex_value in enumerate(ordered_hex)}
+    sorted_rows = sorted(
+        top_rows,
+        key=lambda r: (r["year"], hex_rank[r["color_rgb"]], r["is_translucent"], r["color_name"]),
+    )
+    x_values = [year_positions[row["year"]] for row in sorted_rows]
+    y_values = [sorted_rows[i]["rank"] * 0.6 for i in range(len(sorted_rows))]
+    colors = [f"#{row['color_rgb']}" for row in sorted_rows]
+    sizes = [620 for _ in sorted_rows]
+    edges = ["#f2f2f2" if row["is_translucent"] == "true" else "#111111" for row in sorted_rows]
+
+    fig, ax = plt.subplots(figsize=(0.75 * len(years) + 3.5, 0.75 * limit + 0.9))
+    ax.scatter(x_values, y_values, s=sizes, c=colors, edgecolors=edges, linewidths=1.05)
+    ax.set_xticks(list(year_positions.values()))
+    ax.set_xticklabels(years, rotation=45)
+    ax.set_yticks([])
+    ax.set_ylabel("")
+    ax.set_xlim(-0.6, len(years) - 0.4)
+    ax.set_ylim(-0.6, limit - 0.5)
+    ax.set_title(f"Top {limit} couleurs par année")
+    ax.grid(axis="x", linestyle="--", alpha=0.25)
+
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=160)
+    plt.close(fig)
+
+
 def plot_colors_heatmap(
     matrix_path: Path,
     destination_path: Path,