197 lines
6.6 KiB
Python
197 lines
6.6 KiB
Python
"""Graphiques montrant le nombre de sets sortis par année."""
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from pathlib import Path
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from typing import Dict, Iterable, List, Tuple
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import matplotlib.pyplot as plt
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from lib.filesystem import ensure_parent_dir
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from lib.milestones import load_milestones
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from lib.rebrickable.stats import read_rows
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def compute_sets_per_year(rows: Iterable[dict]) -> List[Tuple[int, int]]:
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"""Retourne la liste (année, nombre de sets) triée chronologiquement."""
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counts: Dict[int, int] = {}
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for row in rows:
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year = int(row["year"])
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counts[year] = counts.get(year, 0) + 1
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return sorted(counts.items(), key=lambda item: item[0])
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def compute_parts_per_year(rows: Iterable[dict]) -> List[Tuple[int, int]]:
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"""Retourne la liste (année, total de pièces) triée chronologiquement."""
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totals: Dict[int, int] = {}
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for row in rows:
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year = int(row["year"])
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totals[year] = totals.get(year, 0) + int(row["num_parts"])
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return sorted(totals.items(), key=lambda item: item[0])
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def plot_sets_per_year(
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enriched_sets_path: Path,
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milestones_path: Path,
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destination_path: Path,
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) -> None:
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"""Génère un histogramme annuel avec la moyenne cumulative et les jalons."""
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sets_rows = read_rows(enriched_sets_path)
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milestones = load_milestones(milestones_path)
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raw_series = compute_sets_per_year(sets_rows)
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raw_parts_series = compute_parts_per_year(sets_rows)
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min_year = min(year for year, _ in raw_series)
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max_year = max(year for year, _ in raw_series)
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series = [(year, dict(raw_series).get(year, 0)) for year in range(min_year, max_year + 1)]
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parts_series = [(year, dict(raw_parts_series).get(year, 0)) for year in range(min_year, max_year + 1)]
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years = [year for year, _ in series]
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counts = [count for _, count in series]
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parts_totals = [total for _, total in parts_series]
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owned_counts_map: Dict[int, int] = {}
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owned_parts_map: Dict[int, int] = {}
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for row in sets_rows:
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year = int(row["year"])
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if row["in_collection"] == "true":
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owned_counts_map[year] = owned_counts_map.get(year, 0) + 1
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owned_parts_map[year] = owned_parts_map.get(year, 0) + int(row["num_parts"])
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owned_counts = [owned_counts_map.get(year, 0) for year in years]
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missing_counts = [total - owned for total, owned in zip(counts, owned_counts)]
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owned_parts = [owned_parts_map.get(year, 0) for year in years]
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missing_parts = [total - owned for total, owned in zip(parts_totals, owned_parts)]
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first_non_zero_index = next(index for index, value in enumerate(counts) if value > 0)
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cumulative_mean = []
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total = 0
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for index, count in enumerate(counts):
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total += count
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cumulative_mean.append(total / (index + 1))
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cumulative_parts_mean = []
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rolling_sets = 0
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rolling_parts = 0
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for index, (count, parts) in enumerate(zip(counts, parts_totals)):
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rolling_sets += count
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rolling_parts += parts
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if index < first_non_zero_index:
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cumulative_parts_mean.append(0)
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else:
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cumulative_parts_mean.append(rolling_parts / rolling_sets)
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milestones_in_range = sorted(
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[m for m in milestones if min_year <= m["year"] <= max_year],
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key=lambda m: (m["year"], m["description"]),
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)
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fig, ax = plt.subplots(figsize=(14, 6))
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bar_width = 0.35
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x_sets = [year - bar_width / 2 for year in years]
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bars_owned_sets = ax.bar(
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x_sets,
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owned_counts,
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width=bar_width,
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color="#1f77b4",
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alpha=0.9,
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label="Sets possédés",
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zorder=2,
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)
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bars_missing_sets = ax.bar(
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x_sets,
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missing_counts,
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width=bar_width,
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bottom=owned_counts,
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color="#9ecae1",
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alpha=0.8,
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label="Sets non possédés",
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)
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set_mean_line = ax.plot(
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years,
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cumulative_mean,
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color="#ff7f0e",
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marker="o",
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label="Moyenne cumulative (sets)",
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zorder=5,
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)
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ax2 = ax.twinx()
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x_parts = [year + bar_width / 2 for year in years]
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parts_bars_owned = ax2.bar(
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x_parts,
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owned_parts,
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width=bar_width,
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color="#2ca02c",
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alpha=0.9,
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label="Pièces (sets possédés)",
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zorder=2,
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)
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parts_bars_missing = ax2.bar(
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x_parts,
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missing_parts,
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width=bar_width,
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bottom=owned_parts,
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color="#c7e9c0",
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alpha=0.85,
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label="Pièces (sets non possédés)",
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)
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parts_mean_line = ax2.plot(
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years,
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cumulative_parts_mean,
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color="#9467bd",
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marker="^",
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label="Moyenne cumulative (pièces/set)",
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zorder=6,
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)
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parts_peak = max(parts_totals + [1])
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ax2.set_ylim(0, parts_peak * 1.1)
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ax.set_xlabel("Année")
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ax.set_ylabel("Nombre de sets")
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ax2.set_ylabel("Nombre de pièces")
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ax.set_title("Nombre de sets par année (thèmes filtrés)")
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ax.grid(True, linestyle="--", alpha=0.3)
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ax.set_xlim(min_year - 1, max_year + 0.4)
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ax.set_xticks(list(range(min_year, max_year + 1)))
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ax.tick_params(axis="x", labelrotation=45)
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peak = max(max(counts), max(cumulative_mean))
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top_limit = peak * 2
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milestone_offsets: Dict[int, int] = {}
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offset_step = 0.3
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max_offset = 0
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for milestone in milestones_in_range:
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year = milestone["year"]
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count_for_year = milestone_offsets.get(year, 0)
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milestone_offsets[year] = count_for_year + 1
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max_offset = max(max_offset, count_for_year)
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horizontal_offset = offset_step * (count_for_year // 2 + 1)
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if count_for_year % 2 == 1:
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horizontal_offset *= -1
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text_x = year + horizontal_offset
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ax.axvline(year, color="#d62728", linestyle="--", linewidth=1, alpha=0.65)
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ax.text(
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text_x,
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top_limit,
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milestone["description"],
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rotation=90,
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verticalalignment="top",
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horizontalalignment="center",
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fontsize=8,
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color="#d62728",
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)
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ax.set_ylim(0, top_limit * (1 + max_offset * 0.02))
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handles = [
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bars_owned_sets,
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bars_missing_sets,
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parts_bars_owned,
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parts_bars_missing,
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set_mean_line[0],
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parts_mean_line[0],
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]
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labels = [
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"Sets possédés",
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"Sets non possédés",
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"Pièces (sets possédés)",
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"Pièces (sets non possédés)",
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"Moyenne cumulative (sets)",
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"Moyenne cumulative (pièces/set)",
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]
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ax.legend(handles, labels, loc="upper left", bbox_to_anchor=(1.12, 1))
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ensure_parent_dir(destination_path)
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fig.tight_layout()
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fig.savefig(destination_path, dpi=150)
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plt.close(fig)
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