Ajoute la heatmap annuelle des personnages
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@ -240,3 +240,10 @@ Le script relit `data/intermediate/sets_enriched.csv`, `data/intermediate/parts_
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2. `python -m scripts.plot_minifig_characters`
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Le script lit `data/intermediate/minifigs_by_set.csv`, compte le nombre de minifigs distinctes par personnage (`known_character` + `fig_num`), écrit `data/intermediate/minifig_characters_counts.csv`, puis trace `figures/step22/minifig_characters.png` (barres horizontales triées).
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### Étape 23 : présence annuelle des personnages
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1. `source .venv/bin/activate`
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2. `python -m scripts.plot_minifig_characters_timeline`
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Le script lit `data/intermediate/minifigs_by_set.csv` et `data/intermediate/sets_enriched.csv`, construit une matrice binaire personnage × année (hors figurants) enregistrée dans `data/intermediate/minifig_characters_year_presence.csv`, puis trace `figures/step22/minifig_characters_timeline.png` (heatmap binaire).
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@ -14,6 +14,11 @@ def load_counts(path: Path) -> List[dict]:
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return read_rows(path)
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def load_presence(path: Path) -> List[dict]:
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"""Charge le CSV de présence par année/personnage."""
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return read_rows(path)
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def plot_minifigs_per_character(counts_path: Path, destination_path: Path) -> None:
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"""Trace un diagramme en barres horizontales du nombre de minifigs par personnage."""
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rows = load_counts(counts_path)
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@ -40,3 +45,49 @@ def plot_minifigs_per_character(counts_path: Path, destination_path: Path) -> No
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fig.tight_layout()
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fig.savefig(destination_path, dpi=160)
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plt.close(fig)
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def plot_character_year_presence(presence_path: Path, destination_path: Path) -> None:
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"""Trace une heatmap binaire indiquant la présence d'un personnage par année."""
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rows = load_presence(presence_path)
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if not rows:
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return
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years = sorted({int(row["year"]) for row in rows})
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characters = sorted(
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{row["known_character"] for row in rows},
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key=lambda name: (
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-sum(1 for r in rows if r["known_character"] == name and r["present"] == "1"),
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name,
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),
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)
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matrix = []
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for character in characters:
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row_values = []
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for year in years:
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present = next(
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(r["present"] for r in rows if r["known_character"] == character and int(r["year"]) == year),
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"0",
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)
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row_values.append(int(present))
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matrix.append(row_values)
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height = max(5, len(characters) * 0.35)
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fig, ax = plt.subplots(figsize=(12, height))
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cax = ax.imshow(matrix, aspect="auto", cmap="Greens", interpolation="nearest")
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ax.set_xticks(range(len(years)))
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ax.set_xticklabels(years, rotation=45, ha="right")
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ax.set_yticks(range(len(characters)))
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ax.set_yticklabels(characters)
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ax.set_xlabel("Année")
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ax.set_ylabel("Personnage")
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ax.set_title("Présence des personnages par année (hors figurants)")
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for i, character in enumerate(characters):
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for j, year in enumerate(years):
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value = matrix[i][j]
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if value == 1:
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ax.text(j, i, "●", ha="center", va="center", color="#0d0d0d", fontsize=7)
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fig.colorbar(cax, ax=ax, fraction=0.046, pad=0.04, label="Présence (1 si minifig)")
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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=160)
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plt.close(fig)
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@ -39,3 +39,59 @@ def write_character_counts(path: Path, rows: Sequence[dict]) -> None:
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writer.writeheader()
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for row in rows:
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writer.writerow(row)
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def load_sets_enriched(path: Path) -> Dict[str, str]:
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"""Indexe les années par set_num."""
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lookup: Dict[str, str] = {}
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with path.open() as sets_file:
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reader = csv.DictReader(sets_file)
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for row in reader:
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lookup[row["set_num"]] = row["year"]
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return lookup
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def aggregate_presence_by_year(
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minifigs_rows: Iterable[dict],
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sets_years: Dict[str, str],
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excluded_characters: Sequence[str] | None = None,
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) -> List[dict]:
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"""Construit la présence binaire des personnages par année (hors figurants)."""
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excluded = set(excluded_characters or [])
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presence: set[tuple[str, int]] = set()
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years_all = {int(year) for year in sets_years.values()}
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for row in minifigs_rows:
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character = row["known_character"].strip()
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fig_num = row["fig_num"].strip()
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if character == "" or fig_num == "":
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continue
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if character in excluded:
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continue
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year = sets_years.get(row["set_num"])
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if year is None:
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continue
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presence.add((character, int(year)))
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years = sorted(years_all)
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characters = sorted({character for character, _ in presence})
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results: List[dict] = []
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for character in characters:
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for year in years:
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results.append(
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{
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"known_character": character,
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"year": str(year),
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"present": "1" if (character, year) in presence else "0",
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}
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)
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return results
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def write_presence_by_year(path: Path, rows: Sequence[dict]) -> None:
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"""Écrit la matrice présence binaire année/personnage."""
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ensure_parent_dir(path)
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fieldnames = ["known_character", "year", "present"]
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with path.open("w", newline="") as csv_file:
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writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
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writer.writeheader()
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for row in rows:
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writer.writerow(row)
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31
scripts/plot_minifig_characters_timeline.py
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31
scripts/plot_minifig_characters_timeline.py
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@ -0,0 +1,31 @@
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"""Trace la présence annuelle des personnages représentés par les minifigs (hors figurants)."""
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from pathlib import Path
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from lib.plots.minifig_characters import plot_character_year_presence
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from lib.rebrickable.minifig_characters import (
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aggregate_presence_by_year,
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load_minifigs_by_set,
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load_sets_enriched,
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write_presence_by_year,
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)
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MINIFIGS_BY_SET_PATH = Path("data/intermediate/minifigs_by_set.csv")
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SETS_ENRICHED_PATH = Path("data/intermediate/sets_enriched.csv")
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PRESENCE_PATH = Path("data/intermediate/minifig_characters_year_presence.csv")
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DESTINATION_PATH = Path("figures/step22/minifig_characters_timeline.png")
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EXCLUDED_CHARACTERS = ["Figurant"]
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def main() -> None:
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"""Construit la présence par année et trace la heatmap binaire."""
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minifigs = load_minifigs_by_set(MINIFIGS_BY_SET_PATH)
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sets_years = load_sets_enriched(SETS_ENRICHED_PATH)
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presence = aggregate_presence_by_year(minifigs, sets_years, excluded_characters=EXCLUDED_CHARACTERS)
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write_presence_by_year(PRESENCE_PATH, presence)
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plot_character_year_presence(PRESENCE_PATH, DESTINATION_PATH)
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if __name__ == "__main__":
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main()
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@ -3,6 +3,7 @@
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from pathlib import Path
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from lib.rebrickable.minifig_characters import aggregate_by_character, write_character_counts
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from lib.rebrickable.minifig_characters import aggregate_presence_by_year, write_presence_by_year, load_sets_enriched
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def test_aggregate_by_character_counts_unique_figs() -> None:
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@ -35,3 +36,25 @@ def test_write_character_counts_outputs_csv(tmp_path: Path) -> None:
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write_character_counts(destination, rows)
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assert destination.read_text() == "known_character,minifig_count\nA,2\nB,1\n"
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def test_aggregate_presence_by_year_excludes_figurants(tmp_path: Path) -> None:
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"""Calcule la présence annuelle en excluant les figurants."""
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sets_path = tmp_path / "sets_enriched.csv"
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sets_path.write_text(
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"set_num,year\n"
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"123-1,2020\n"
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"124-1,2021\n"
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)
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minifigs_rows = [
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{"set_num": "123-1", "known_character": "Owen Grady", "fig_num": "fig-owen", "part_num": "head-a"},
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{"set_num": "124-1", "known_character": "Figurant", "fig_num": "fig-guard", "part_num": "head-b"},
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]
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sets_years = load_sets_enriched(sets_path)
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presence = aggregate_presence_by_year(minifigs_rows, sets_years, excluded_characters=["Figurant"])
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assert presence == [
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{"known_character": "Owen Grady", "year": "2020", "present": "1"},
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{"known_character": "Owen Grady", "year": "2021", "present": "0"},
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]
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26
tests/test_minifig_characters_timeline_plot.py
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tests/test_minifig_characters_timeline_plot.py
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"""Tests du graphique de présence annuelle des personnages."""
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import matplotlib
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from pathlib import Path
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from lib.plots.minifig_characters import plot_character_year_presence
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matplotlib.use("Agg")
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def test_plot_character_year_presence(tmp_path: Path) -> None:
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"""Génère la heatmap binaire personnage × année."""
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presence_path = tmp_path / "minifig_characters_year_presence.csv"
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destination = tmp_path / "figures" / "step22" / "minifig_characters_timeline.png"
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presence_path.write_text(
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"known_character,year,present\n"
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"Owen Grady,2020,1\n"
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"Owen Grady,2021,0\n"
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"Figurant,2020,1\n"
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)
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plot_character_year_presence(presence_path, destination)
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assert destination.exists()
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assert destination.stat().st_size > 0
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