from __future__ import annotations

from dataclasses import dataclass, field
from typing import Any, Sequence

import numpy as np
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
from PIL import Image


@dataclass(frozen=True)
class TopDownSceneElements:
    room_nodes: Sequence[Any]
    object_nodes: Sequence[Any] = field(default_factory=tuple)
    edges: Sequence[tuple[str, str]] = field(default_factory=tuple)


@dataclass(frozen=True)
class TopDownRenderStyle:
    room_color: str = "red"
    room_label_color: str = "yellow"
    room_marker_size: int = 50
    room_label_offset: int = 2
    figure_size: tuple[int, int] = (8, 8)
    map_cmap: str = "gray"
    title: str = "RoomNode Top-Down Map"


def render_topdown_scene_map(
    pathfinder: Any,
    elements: TopDownSceneElements,
    meters_per_pixel: float,
    style: TopDownRenderStyle | None = None,
) -> Image.Image:
    """Render a top-down scene map as a PIL Image.

    Uses matplotlib Agg backend (non-interactive) to draw room markers and
    labels on the habitat top-down occupancy map, then returns the result
    as a PIL Image.

    Args:
        pathfinder: Habitat pathfinder instance.
        elements: Scene elements containing room nodes to annotate.
        meters_per_pixel: Resolution for the top-down map.
        style: Visual style configuration.

    Returns:
        PIL.Image.Image: Rendered top-down map with annotations.

    Raises:
        ValueError: If room_nodes is empty or meters_per_pixel <= 0.
        NotImplementedError: If object_nodes or edges are provided.
    """
    if not elements.room_nodes:
        raise ValueError("room_nodes must not be empty")

    if meters_per_pixel <= 0:
        raise ValueError("meters_per_pixel must be greater than 0")

    if elements.object_nodes:
        raise NotImplementedError("object_nodes overlay is not implemented yet")

    if elements.edges:
        raise NotImplementedError("edge overlay is not implemented yet")

    if style is None:
        style = TopDownRenderStyle()

    # Import habitat maps internally — treated as required dependency.
    from habitat.utils.visualizations import maps

    # Generate raw top-down occupancy map.
    map_height = float(elements.room_nodes[0].center[1])
    top_down_map = maps.get_topdown_map(
        pathfinder,
        height=map_height,
        meters_per_pixel=meters_per_pixel,
    )

    # Render with matplotlib Agg backend (no GUI required).
    fig = Figure(figsize=style.figure_size)
    _ = FigureCanvasAgg(fig)
    ax = fig.add_subplot(111)
    ax.imshow(top_down_map, cmap=style.map_cmap)

    # Annotate room positions and labels.
    for room_node in elements.room_nodes:
        grid_y, grid_x = maps.to_grid(
            float(room_node.center[2]),
            float(room_node.center[0]),
            top_down_map.shape,
            pathfinder=pathfinder,
        )
        ax.scatter(grid_x, grid_y, c=style.room_color, s=style.room_marker_size)
        ax.text(
            grid_x + style.room_label_offset,
            grid_y + style.room_label_offset,
            room_node.room_id,
            color=style.room_label_color,
            fontsize=8,
        )

    ax.set_title(style.title)
    ax.axis("off")
    fig.canvas.draw()

    # Extract RGB pixels from the Agg canvas buffer.
    rgba = np.asarray(fig.canvas.buffer_rgba(), dtype=np.uint8)
    rgb = rgba[..., :3].copy()

    return Image.fromarray(rgb)