Ajoute les agrégats et visualisations globales des couleurs de têtes

lib/plots/global_minifig_heads.py

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+"""Visualisation des couleurs de têtes de minifigs sur le catalogue complet."""
+
+from pathlib import Path
+from typing import Dict, Iterable, List, Tuple
+
+import matplotlib.pyplot as plt
+
+from lib.filesystem import ensure_parent_dir
+from lib.rebrickable.stats import read_rows
+
+
+def load_global_heads(heads_path: Path) -> List[dict]:
+    """Charge l'agrégat global des têtes par année."""
+    return read_rows(heads_path)
+
+
+def select_top_colors(rows: Iterable[dict], limit: int = 12) -> List[Tuple[str, str, str]]:
+    """Retourne les couleurs les plus fréquentes globalement (nom, rgb, is_translucent)."""
+    totals: Dict[Tuple[str, str, str], int] = {}
+    for row in rows:
+        key = (row["color_name"], row["color_rgb"], row["is_translucent"])
+        totals[key] = totals.get(key, 0) + int(row["quantity"])
+    sorted_colors = sorted(totals.items(), key=lambda item: (-item[1], item[0][0], item[0][1]))
+    return [color for color, _ in sorted_colors[:limit]]
+
+
+def build_share_matrix(
+    rows: Iterable[dict], top_colors: List[Tuple[str, str, str]]
+) -> Tuple[List[int], List[Tuple[str, str, str]], List[Dict[str, float]]]:
+    """Construit les parts par année en regroupant les couleurs hors top dans 'Autres'."""
+    years = sorted({int(row["year"]) for row in rows})
+    colors = top_colors + [("Autres", "444444", "false")]
+    shares_by_year: List[Dict[str, float]] = []
+    rows_by_year: Dict[int, List[dict]] = {year: [] for year in years}
+    for row in rows:
+        rows_by_year[int(row["year"])].append(row)
+    for year in years:
+        year_rows = rows_by_year[year]
+        total = sum(int(r["quantity"]) for r in year_rows)
+        shares: Dict[str, float] = {color[0]: 0.0 for color in colors}
+        for r in year_rows:
+            key = (r["color_name"], r["color_rgb"], r["is_translucent"])
+            quantity = int(r["quantity"])
+            target = "Autres" if key not in top_colors else r["color_name"]
+            shares[target] = shares.get(target, 0.0) + quantity / total if total > 0 else 0.0
+        shares_by_year.append(shares)
+    return years, colors, shares_by_year
+
+
+def plot_global_head_shares(
+    heads_path: Path,
+    destination_path: Path,
+    top_limit: int = 12,
+) -> None:
+    """Trace les parts des couleurs de têtes de minifigs par année (catalogue complet)."""
+    rows = load_global_heads(heads_path)
+    top_colors = select_top_colors(rows, limit=top_limit)
+    years, colors, shares_by_year = build_share_matrix(rows, top_colors)
+
+    fig, ax = plt.subplots(figsize=(14, 6))
+    bottoms = [0.0] * len(years)
+    y_positions = list(range(len(years)))
+    for name, color_rgb, is_trans in colors:
+        values = [shares[name] for shares in shares_by_year]
+        edge = "#f2f2f2" if is_trans == "true" else "#0d0d0d"
+        ax.bar(
+            years,
+            values,
+            bottom=bottoms,
+            color=f"#{color_rgb}",
+            edgecolor=edge,
+            label=name,
+            linewidth=0.7,
+        )
+        bottoms = [b + v for b, v in zip(bottoms, values)]
+    ax.set_ylim(0, 1.05)
+    ax.set_ylabel("Part des couleurs (têtes de minifigs, catalogue complet)")
+    ax.set_xlabel("Année")
+    if len(years) > 15:
+        step = max(1, len(years) // 10)
+        ax.set_xticks(years[::step])
+    else:
+        ax.set_xticks(years)
+    ax.set_title("Répartition des couleurs de têtes de minifigs par année (catalogue complet)")
+    ax.legend(loc="upper left", bbox_to_anchor=(1.02, 1), frameon=False)
+    ax.grid(True, axis="y", linestyle="--", alpha=0.25)
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=170)
+    plt.close(fig)

lib/plots/minifig_skin_tones.py

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+"""Visualisation de la part des têtes jaunes sur le catalogue global."""
+
+from pathlib import Path
+from typing import Dict, List
+
+import matplotlib.pyplot as plt
+
+from lib.filesystem import ensure_parent_dir
+from lib.milestones import load_milestones
+from lib.rebrickable.stats import read_rows
+
+
+def compute_yellow_share(rows: List[dict]) -> List[dict]:
+    """Calcule la part de la couleur Yellow par année."""
+    aggregated: Dict[str, Dict[str, int]] = {}
+    for row in rows:
+        year = row["year"]
+        if year not in aggregated:
+            aggregated[year] = {"yellow": 0, "total": 0}
+        aggregated[year]["total"] += int(row["quantity"])
+        if row["color_name"].lower() == "yellow" or row["color_rgb"].upper() == "FFFF00":
+            aggregated[year]["yellow"] += int(row["quantity"])
+    results = []
+    for year in sorted(aggregated.keys(), key=int):
+        total = aggregated[year]["total"]
+        yellow = aggregated[year]["yellow"]
+        share = yellow / total if total > 0 else 0
+        results.append({"year": int(year), "yellow_share": share, "total": total})
+    return results
+
+
+def plot_yellow_share(heads_path: Path, milestones_path: Path, destination_path: Path) -> None:
+    """Trace l'évolution de la part de têtes jaunes dans le catalogue complet."""
+    rows = read_rows(heads_path)
+    milestones = load_milestones(milestones_path)
+    series = compute_yellow_share(rows)
+    years = [item["year"] for item in series]
+    shares = [item["yellow_share"] for item in series]
+
+    fig, ax = plt.subplots(figsize=(13, 5.5))
+    ax.plot(years, shares, color="#f2c300", marker="o", linewidth=2.4, label="Part Yellow")
+    ax.fill_between(years, shares, color="#f2c300", alpha=0.18)
+    ax.set_ylim(0, min(1.0, max(shares + [0.01]) * 1.1))
+    ax.set_ylabel("Part de têtes Yellow")
+    ax.set_xlabel("Année")
+    if len(years) > 15:
+        step = max(1, len(years) // 10)
+        ax.set_xticks(years[::step])
+    else:
+        ax.set_xticks(years)
+    ax.set_title("Evolution de l'usage des têtes Yellow (catalogue complet)")
+    ax.grid(True, linestyle="--", alpha=0.3)
+    if milestones:
+        min_year = min(years)
+        max_year = max(years)
+        milestones_in_range = sorted(
+            [m for m in milestones if min_year <= m["year"] <= max_year],
+            key=lambda m: (m["year"], m["description"]),
+        )
+        offset_map: Dict[int, int] = {}
+        offset_step = 0.35
+        top_limit = ax.get_ylim()[1] * 1.05
+        for milestone in milestones_in_range:
+            year = milestone["year"]
+            count_for_year = offset_map.get(year, 0)
+            offset_map[year] = count_for_year + 1
+            horizontal_offset = offset_step * (count_for_year // 2 + 1)
+            if count_for_year % 2 == 1:
+                horizontal_offset *= -1
+            text_x = year + horizontal_offset
+            ax.axvline(year, color="#d62728", linestyle="--", linewidth=1, alpha=0.65, zorder=1)
+            ax.text(
+                text_x,
+                top_limit,
+                milestone["description"],
+                rotation=90,
+                verticalalignment="top",
+                horizontalalignment="center",
+                fontsize=8,
+                color="#d62728",
+            )
+        ax.set_ylim(ax.get_ylim()[0], top_limit * (1 + max(offset_map.values(), default=0) * 0.02))
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=170)
+    plt.close(fig)

lib/rebrickable/global_minifig_heads.py

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+"""Extraction des couleurs de têtes de minifigs sur le catalogue complet."""
+
+import csv
+from pathlib import Path
+from typing import Dict, Iterable, List, Set, Tuple
+
+from lib.rebrickable.parts_inventory import normalize_boolean, select_latest_inventories
+
+
+HEAD_CATEGORIES = {"59"}
+
+
+def load_head_parts(parts_path: Path, head_categories: Set[str] | None = None) -> Set[str]:
+    """Construit l'ensemble des références de têtes via leur catégorie."""
+    categories = head_categories or HEAD_CATEGORIES
+    head_parts: Set[str] = set()
+    with parts_path.open() as parts_file:
+        reader = csv.DictReader(parts_file)
+        for row in reader:
+            if row["part_cat_id"] in categories:
+                head_parts.add(row["part_num"])
+    return head_parts
+
+
+def build_sets_year_lookup(sets_path: Path) -> Dict[str, str]:
+    """Indexe les années par set_num."""
+    lookup: Dict[str, str] = {}
+    with sets_path.open() as sets_file:
+        reader = csv.DictReader(sets_file)
+        for row in reader:
+            lookup[row["set_num"]] = row["year"]
+    return lookup
+
+
+def build_color_lookup(colors_path: Path) -> Dict[str, dict]:
+    """Construit un index des couleurs par identifiant."""
+    lookup: Dict[str, dict] = {}
+    with colors_path.open() as colors_file:
+        reader = csv.DictReader(colors_file)
+        for row in reader:
+            lookup[row["id"]] = {
+                "rgb": row["rgb"],
+                "is_translucent": row["is_trans"].lower(),
+                "name": row["name"],
+            }
+    return lookup
+
+
+def aggregate_global_heads_by_year(
+    inventories_path: Path,
+    inventory_parts_path: Path,
+    parts_path: Path,
+    colors_path: Path,
+    sets_path: Path,
+    head_categories: Set[str] | None = None,
+) -> List[dict]:
+    """Agrège les couleurs de têtes par année sur le catalogue complet."""
+    head_parts = load_head_parts(parts_path, head_categories)
+    latest_inventories = select_latest_inventories(inventories_path)
+    latest_inventory_ids = {data["id"]: set_num for set_num, data in latest_inventories.items()}
+    colors_lookup = build_color_lookup(colors_path)
+    sets_year = build_sets_year_lookup(sets_path)
+    aggregates: Dict[Tuple[str, str, str], dict] = {}
+    with inventory_parts_path.open() as parts_file:
+        reader = csv.DictReader(parts_file)
+        for row in reader:
+            inventory_id = row["inventory_id"]
+            if inventory_id not in latest_inventory_ids:
+                continue
+            if row["part_num"] not in head_parts:
+                continue
+            if normalize_boolean(row["is_spare"]) == "true":
+                continue
+            set_num = latest_inventory_ids[inventory_id]
+            year = sets_year.get(set_num)
+            if year is None:
+                continue
+            color = colors_lookup[row["color_id"]]
+            key = (year, color["rgb"], color["is_translucent"])
+            existing = aggregates.get(key)
+            if existing is None:
+                aggregates[key] = {
+                    "year": year,
+                    "color_rgb": color["rgb"],
+                    "is_translucent": color["is_translucent"],
+                    "color_name": color["name"],
+                    "quantity": 0,
+                }
+                existing = aggregates[key]
+            existing["quantity"] += int(row["quantity"])
+    results = list(aggregates.values())
+    results.sort(key=lambda r: (int(r["year"]), r["color_name"], r["is_translucent"]))
+    return results
+
+
+def write_global_heads_by_year(destination_path: Path, rows: Iterable[dict]) -> None:
+    """Sérialise l'agrégat global par année."""
+    fieldnames = ["year", "color_rgb", "is_translucent", "color_name", "quantity"]
+    with destination_path.open("w", newline="") as csv_file:
+        writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
+        writer.writeheader()
+        for row in rows:
+            writer.writerow(row)