"""Graphiques sur la taille moyenne des sets (pièces par set)."""

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.milestones import load_milestones
from lib.rebrickable.stats import read_rows


def compute_average_parts_per_set(rows: Iterable[dict]) -> List[Tuple[int, float]]:
    """Calcule la moyenne annuelle de pièces par set."""
    per_year: Dict[int, Dict[str, int]] = {}
    for row in rows:
        year = int(row["year"])
        per_year[year] = per_year.get(year, {"parts": 0, "sets": 0})
        per_year[year]["parts"] += int(row["num_parts"])
        per_year[year]["sets"] += 1
    results: List[Tuple[int, float]] = []
    for year in sorted(per_year):
        totals = per_year[year]
        results.append((year, totals["parts"] / totals["sets"]))
    return results


def compute_rolling_mean(series: List[Tuple[int, float]], window: int) -> List[Tuple[int, float]]:
    """Calcule la moyenne glissante sur une fenêtre donnée."""
    values = [value for _, value in series]
    years = [year for year, _ in series]
    rolling: List[Tuple[int, float]] = []
    for index in range(len(values)):
        if index + 1 < window:
            rolling.append((years[index], 0.0))
        else:
            window_values = values[index - window + 1 : index + 1]
            rolling.append((years[index], sum(window_values) / window))
    return rolling


def plot_parts_per_set(
    enriched_sets_path: Path,
    milestones_path: Path,
    destination_path: Path,
    rolling_window: int = 3,
) -> None:
    """Génère un graphique de la moyenne annuelle et glissante des pièces par set."""
    sets_rows = read_rows(enriched_sets_path)
    milestones = load_milestones(milestones_path)
    annual_series = compute_average_parts_per_set(sets_rows)
    rolling_series = compute_rolling_mean(annual_series, rolling_window)
    years = [year for year, _ in annual_series]
    annual_values = [value for _, value in annual_series]
    rolling_values = [value for _, value in rolling_series]

    fig, ax = plt.subplots(figsize=(12, 6))
    ax.plot(years, annual_values, marker="o", color="#2ca02c", label="Moyenne annuelle (pièces/set)")
    ax.plot(
        years,
        rolling_values,
        marker="^",
        color="#9467bd",
        label=f"Moyenne glissante {rolling_window} ans (pièces/set)",
    )
    ax.set_xlabel("Année")
    ax.set_ylabel("Pièces par set")
    ax.set_title("Évolution de la taille moyenne des sets (thèmes filtrés)")
    ax.grid(True, linestyle="--", alpha=0.3)
    ax.set_xlim(min(years) - 0.4, max(years) + 0.4)
    ax.set_xticks(list(range(min(years), max(years) + 1)))
    ax.tick_params(axis="x", labelrotation=45)

    peak = max(max(annual_values), max(rolling_values))
    top_limit = peak * 2
    milestones_in_range = sorted(
        [m for m in milestones if min(years) <= m["year"] <= max(years)],
        key=lambda m: (m["year"], m["description"]),
    )
    milestone_offsets: Dict[int, int] = {}
    offset_step = 0.4
    max_offset = 0
    for milestone in milestones_in_range:
        year = milestone["year"]
        count_for_year = milestone_offsets.get(year, 0)
        milestone_offsets[year] = count_for_year + 1
        horizontal_offset = offset_step * (count_for_year // 2 + 1)
        max_offset = max(max_offset, count_for_year)
        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)
        ax.text(
            text_x,
            top_limit,
            milestone["description"],
            rotation=90,
            verticalalignment="top",
            horizontalalignment="center",
            fontsize=8,
            color="#d62728",
        )

    ax.set_ylim(0, top_limit * (1 + max_offset * 0.02))
    ax.legend(loc="upper left", bbox_to_anchor=(1.12, 1))

    ensure_parent_dir(destination_path)
    fig.tight_layout()
    fig.savefig(destination_path, dpi=150)
    plt.close(fig)