You've already forked etude_lego_jurassic_world
Exclure les pièces de minifigs et intégrer les visuels de rareté
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86
lib/plots/part_rarity.py
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86
lib/plots/part_rarity.py
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"""Visualisation des pièces les plus rares observées dans les sets filtrés."""
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import csv
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from pathlib import Path
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from typing import List
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import matplotlib.pyplot as plt
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from matplotlib.offsetbox import AnnotationBbox, OffsetImage
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from PIL import Image
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from lib.filesystem import ensure_parent_dir
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def load_part_rarity(path: Path) -> List[dict]:
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"""Charge le CSV des pièces rares."""
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rows: List[dict] = []
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with path.open() as csv_file:
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reader = csv.DictReader(csv_file)
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for row in reader:
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rows.append(row)
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return rows
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def format_label(row: dict) -> str:
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"""Formate l’étiquette de l’axe vertical."""
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return f"{row['part_num']} — {row['part_name']}"
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def load_part_image(row: dict, resources_dir: Path) -> Image.Image | None:
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"""Charge l'image associée à une pièce si elle est disponible."""
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path = resources_dir / row["sample_set_id"] / "rare_parts" / f"{row['part_num']}.jpg"
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if not path.exists():
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return None
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return Image.open(path)
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def plot_part_rarity(
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path: Path,
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destination_path: Path,
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resources_dir: Path = Path("figures/rebrickable"),
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show_images: bool = True,
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) -> None:
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"""Trace un bar chart horizontal des pièces les plus rares avec leurs visuels."""
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rows = load_part_rarity(path)
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selected = rows
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labels = [format_label(row) for row in selected]
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filtered_counts = [int(row["filtered_quantity"]) for row in selected]
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other_counts = [int(row["other_sets_quantity"]) for row in selected]
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positions = list(range(len(selected)))
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fig, ax = plt.subplots(figsize=(13, 0.55 * len(selected) + 1.4))
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ax.barh(positions, filtered_counts, color="#1f78b4", label="Sets filtrés")
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ax.barh(positions, other_counts, left=filtered_counts, color="#b2df8a", label="Autres sets")
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ax.set_yticks(positions)
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ax.set_yticklabels(labels)
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ax.set_xlabel("Occurrences de la pièce (rechanges incluses)")
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ax.grid(axis="x", linestyle="--", alpha=0.4)
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ax.legend()
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if show_images:
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max_count = max((f + o) for f, o in zip(filtered_counts, other_counts)) if selected else 0
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pad = max_count * 0.15 if max_count > 0 else 1.0
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ax.set_xlim(left=-pad, right=max_count + pad * 0.3)
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for row, pos in zip(selected, positions):
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image = load_part_image(row, resources_dir)
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if image is None:
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continue
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target_height = 28
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ratio = target_height / image.height
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resized = image.resize((int(image.width * ratio), target_height))
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imagebox = OffsetImage(resized)
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ab = AnnotationBbox(
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imagebox,
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(-pad * 0.45, pos),
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xycoords=("data", "data"),
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box_alignment=(0.5, 0.5),
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frameon=False,
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)
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ax.add_artist(ab)
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fig.subplots_adjust(left=0.42)
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fig.tight_layout()
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ensure_parent_dir(destination_path)
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fig.savefig(destination_path, dpi=150)
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plt.close(fig)
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