"""Graphique du nombre de minifigs par personnage."""

from pathlib import Path
from typing import Dict, List

import matplotlib.pyplot as plt
from matplotlib.patches import Patch

from lib.filesystem import ensure_parent_dir
from lib.milestones import load_milestones
from lib.plots.gender_palette import GENDER_COLORS, GENDER_LABELS
from lib.rebrickable.stats import read_rows


def load_counts(path: Path) -> List[dict]:
    """Charge le CSV des comptes par personnage."""
    return read_rows(path)


def load_presence(path: Path) -> List[dict]:
    """Charge le CSV de présence par année/personnage."""
    return read_rows(path)


def load_new_characters(path: Path) -> List[dict]:
    """Charge le CSV des personnages introduits par année."""
    return read_rows(path)


def load_variations_and_totals(path: Path) -> List[dict]:
    """Charge le CSV comparatif variations/total par personnage."""
    return read_rows(path)


def plot_minifigs_per_character(counts_path: Path, destination_path: Path) -> None:
    """Trace un diagramme en barres horizontales du nombre de minifigs par personnage."""
    rows = load_counts(counts_path)
    characters = [row["known_character"] for row in rows]
    counts = [int(row["minifig_count"]) for row in rows]
    genders = [row.get("gender", "") for row in rows]
    colors = [GENDER_COLORS.get(gender.strip().lower(), GENDER_COLORS["unknown"]) for gender in genders]
    positions = list(range(len(rows)))
    height = max(6, len(rows) * 0.22)

    fig, ax = plt.subplots(figsize=(12, height))
    bars = ax.barh(positions, counts, color=colors, edgecolor="#0d0d0d", linewidth=0.6)
    ax.set_yticks(positions)
    ax.set_yticklabels(characters)
    ax.invert_yaxis()
    ax.set_xlabel("Nombre de minifigs distinctes")
    ax.set_title("Minifigs par personnage (thèmes filtrés)")
    ax.grid(True, axis="x", linestyle="--", alpha=0.25)
    max_value = max(counts) if counts else 0
    ax.set_xlim(0, max_value + 1)
    for index, bar in enumerate(bars):
        value = counts[index]
        ax.text(value + 0.1, bar.get_y() + bar.get_height() / 2, str(value), va="center", fontsize=8)
    legend_entries = []
    seen = set()
    for gender in genders:
        normalized = gender.strip().lower()
        if normalized in seen:
            continue
        seen.add(normalized)
        legend_entries.append(
            Patch(
                facecolor=GENDER_COLORS.get(normalized, GENDER_COLORS["unknown"]),
                edgecolor="#0d0d0d",
                linewidth=0.6,
                label=GENDER_LABELS.get(normalized, "Inconnu"),
            )
        )
    if legend_entries:
        ax.legend(handles=legend_entries, title="Genre", loc="lower right")

    ensure_parent_dir(destination_path)
    fig.tight_layout()
    fig.savefig(destination_path, dpi=160)
    plt.close(fig)


def plot_character_variations_vs_total(counts_path: Path, destination_path: Path) -> None:
    """Superpose le total de minifigs et leurs variations distinctes par personnage."""
    rows = load_variations_and_totals(counts_path)
    if not rows:
        return
    characters = [row["known_character"] for row in rows]
    variation_counts = [int(row["variation_count"]) for row in rows]
    total_counts = [int(row["total_minifigs"]) for row in rows]
    genders = [row.get("gender", "") for row in rows]
    gender_colors = [GENDER_COLORS.get(gender.strip().lower(), GENDER_COLORS["unknown"]) for gender in genders]
    positions = list(range(len(rows)))
    height = max(6, len(rows) * 0.24)
    background_color = "#d7d7e0"

    fig, ax = plt.subplots(figsize=(12.4, height))
    bars_total = ax.barh(
        positions,
        total_counts,
        color=background_color,
        edgecolor="#0d0d0d",
        linewidth=0.6,
        height=0.6,
        label="Total de minifigs",
    )
    bars_variations = ax.barh(
        positions,
        variation_counts,
        color=gender_colors,
        edgecolor="#0d0d0d",
        linewidth=0.8,
        height=0.36,
        label="Variations distinctes",
    )
    ax.set_yticks(positions)
    ax.set_yticklabels(characters)
    ax.invert_yaxis()
    ax.set_xlabel("Nombre de minifigs")
    ax.set_title("Variations et total de minifigs par personnage (hors figurants)")
    ax.grid(True, axis="x", linestyle="--", alpha=0.25)
    max_value = max(total_counts) if total_counts else 0
    ax.set_xlim(0, max_value + 1)

    for index, bar in enumerate(bars_total):
        value = total_counts[index]
        ax.text(value + 0.12, bar.get_y() + bar.get_height() / 2, str(value), va="center", fontsize=8, color="#1a1a1a")
    for index, bar in enumerate(bars_variations):
        value = variation_counts[index]
        ax.text(value + 0.12, bar.get_y() + bar.get_height() / 2, str(value), va="center", fontsize=8, color="#0d0d0d")

    legend_entries = [
        Patch(facecolor=background_color, edgecolor="#0d0d0d", linewidth=0.6, label="Total de minifigs"),
        Patch(
            facecolor=GENDER_COLORS["unknown"],
            edgecolor="#0d0d0d",
            linewidth=0.8,
            label="Variations distinctes (couleur = genre)",
        ),
    ]
    seen = set()
    for gender, color in zip(genders, gender_colors):
        normalized = gender.strip().lower()
        if normalized in seen:
            continue
        seen.add(normalized)
        legend_entries.append(
            Patch(
                facecolor=color,
                edgecolor="#0d0d0d",
                linewidth=0.6,
                label=GENDER_LABELS.get(normalized, "Inconnu"),
            )
        )
    ax.legend(handles=legend_entries, loc="lower right")

    ensure_parent_dir(destination_path)
    fig.tight_layout()
    fig.savefig(destination_path, dpi=160)
    plt.close(fig)


def plot_character_year_presence(presence_path: Path, destination_path: Path) -> None:
    """Trace une heatmap indiquant le nombre de minifigs par personnage et par année."""
    rows = load_presence(presence_path)
    if not rows:
        return
    years = sorted({int(row["year"]) for row in rows})
    characters = sorted(
        {row["known_character"] for row in rows},
        key=lambda name: (
            -sum(int(r["minifig_count"]) for r in rows if r["known_character"] == name),
            name,
        ),
    )
    matrix = []
    for character in characters:
        row_values = []
        for year in years:
            count = next(
                (r["minifig_count"] for r in rows if r["known_character"] == character and int(r["year"]) == year),
                "0",
            )
            row_values.append(int(count))
        matrix.append(row_values)

    height = max(5, len(characters) * 0.35)
    fig, ax = plt.subplots(figsize=(12, height))
    cax = ax.imshow(matrix, aspect="auto", cmap="Greens", interpolation="nearest")
    ax.set_xticks(range(len(years)))
    ax.set_xticklabels(years, rotation=45, ha="right")
    ax.set_yticks(range(len(characters)))
    ax.set_yticklabels(characters)
    ax.set_xlabel("Année")
    ax.set_ylabel("Personnage")
    ax.set_title("Nombre de minifigs par personnage et par année (hors figurants)")
    for i, character in enumerate(characters):
        for j, year in enumerate(years):
            value = matrix[i][j]
            if value == 1:
                ax.text(j, i, "●", ha="center", va="center", color="#0d0d0d", fontsize=7)
            elif value > 1:
                ax.text(j, i, str(value), ha="center", va="center", color="#0d0d0d", fontsize=7)
    fig.colorbar(cax, ax=ax, fraction=0.046, pad=0.04, label="Nombre de minifigs")
    ensure_parent_dir(destination_path)
    fig.tight_layout()
    fig.savefig(destination_path, dpi=160)
    plt.close(fig)


def plot_new_characters_per_year(
    counts_path: Path,
    milestones_path: Path,
    destination_path: Path,
    start_year: int,
    end_year: int,
) -> None:
    """Trace un diagramme en barres du nombre de nouveaux personnages introduits par an."""
    rows = load_new_characters(counts_path)
    if not rows:
        return
    counts = {int(row["year"]): int(row["new_characters"]) for row in rows}
    years = list(range(start_year, end_year + 1))
    values = [counts.get(year, 0) for year in years]

    fig_width = max(8.5, len(years) * 0.45 + 2.5)
    fig, ax = plt.subplots(figsize=(fig_width, 5.4))
    bars = ax.bar(years, values, color="#1f77b4", edgecolor="#0d0d0d", linewidth=0.7)
    ax.set_xlabel("Année")
    ax.set_ylabel("Nouveaux personnages")
    ax.set_title("Personnages introduits par an (hors figurants)")
    ax.grid(axis="y", linestyle="--", alpha=0.3)
    ax.set_xticks(years)
    ax.set_xticklabels(years, rotation=45, ha="right")
    ax.set_xlim(start_year - 0.6, end_year + 0.6)
    y_max = max(values) if values else 0
    upper_limit = 20
    ax.set_ylim(0, upper_limit)

    for bar, value in zip(bars, values):
        if value == 0:
            continue
        ax.text(bar.get_x() + bar.get_width() / 2, value + 0.05, str(value), ha="center", va="bottom", fontsize=8)

    milestones = load_milestones(milestones_path)
    if milestones:
        milestones_in_range = sorted(
            [m for m in milestones if start_year <= m["year"] <= end_year],
            key=lambda m: (m["year"], m["description"]),
        )
        offset_step = 0.25
        offset_map: Dict[int, int] = {}
        top_limit = ax.get_ylim()[1]
        label_y = top_limit * 0.96
        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,
                label_y,
                milestone["description"],
                rotation=90,
                verticalalignment="top",
                horizontalalignment="center",
                fontsize=8,
                color="#d62728",
            )

    ensure_parent_dir(destination_path)
    fig.tight_layout()
    fig.savefig(destination_path, dpi=160)
    plt.close(fig)