"""
DEM (Digital Elevation Model) Service
Serves terrain data from Copernicus DEM GLO-30
"""
import os
import math
from typing import Optional, Tuple
import struct
import structlog
import numpy as np
from PIL import Image
from io import BytesIO

from config import settings

logger = structlog.get_logger(__name__)

# Germany bounding box
GERMANY_BOUNDS = {
    "west": 5.87,
    "south": 47.27,
    "east": 15.04,
    "north": 55.06,
}


def lat_lon_to_tile(lat: float, lon: float, zoom: int) -> Tuple[int, int]:
    """Convert latitude/longitude to tile coordinates."""
    n = 2 ** zoom
    x = int((lon + 180.0) / 360.0 * n)
    lat_rad = math.radians(lat)
    y = int((1.0 - math.asinh(math.tan(lat_rad)) / math.pi) / 2.0 * n)
    return x, y


def tile_to_bounds(z: int, x: int, y: int) -> Tuple[float, float, float, float]:
    """Convert tile coordinates to bounding box (west, south, east, north)."""
    n = 2 ** z
    west = x / n * 360.0 - 180.0
    east = (x + 1) / n * 360.0 - 180.0
    north_rad = math.atan(math.sinh(math.pi * (1 - 2 * y / n)))
    south_rad = math.atan(math.sinh(math.pi * (1 - 2 * (y + 1) / n)))
    north = math.degrees(north_rad)
    south = math.degrees(south_rad)
    return west, south, east, north


class DEMService:
    """
    Service for handling Digital Elevation Model data.

    Uses Copernicus DEM GLO-30 (30m resolution) as the data source.
    Generates terrain tiles in Mapbox Terrain-RGB format for MapLibre/Unity.
    """

    def __init__(self):
        self.dem_dir = settings.dem_data_dir
        self.tile_size = settings.terrain_tile_size
        self._dem_cache = {}  # Cache loaded DEM files

    def _get_dem_file_path(self, lat: int, lon: int) -> str:
        """
        Get the path to a Copernicus DEM file for the given coordinates.

        Copernicus DEM files are named like: Copernicus_DSM_COG_10_N47_00_E008_00_DEM.tif
        """
        lat_prefix = "N" if lat >= 0 else "S"
        lon_prefix = "E" if lon >= 0 else "W"

        # Format: N47E008
        filename = f"{lat_prefix}{abs(lat):02d}{lon_prefix}{abs(lon):03d}.tif"
        return os.path.join(self.dem_dir, filename)

    def _load_dem_tile(self, lat: int, lon: int) -> Optional[np.ndarray]:
        """Load a DEM tile from disk."""
        cache_key = f"{lat}_{lon}"
        if cache_key in self._dem_cache:
            return self._dem_cache[cache_key]

        filepath = self._get_dem_file_path(lat, lon)

        if not os.path.exists(filepath):
            logger.debug("DEM file not found", path=filepath)
            return None

        try:
            import rasterio

            with rasterio.open(filepath) as src:
                data = src.read(1)  # Read first band
                self._dem_cache[cache_key] = data
                return data

        except ImportError:
            logger.warning("rasterio not available, using fallback")
            return self._load_dem_fallback(filepath)
        except Exception as e:
            logger.error("Error loading DEM", path=filepath, error=str(e))
            return None

    def _load_dem_fallback(self, filepath: str) -> Optional[np.ndarray]:
        """Fallback DEM loader without rasterio (for development)."""
        # In development, return synthetic terrain
        return None

    async def get_heightmap_tile(self, z: int, x: int, y: int) -> Optional[bytes]:
        """
        Generate a heightmap tile in Mapbox Terrain-RGB format.

        The encoding stores elevation as: height = -10000 + ((R * 256 * 256 + G * 256 + B) * 0.1)
        This allows for -10000m to +1677721.6m range with 0.1m precision.
        """
        # Get tile bounds
        west, south, east, north = tile_to_bounds(z, x, y)

        # Check if tile is within Germany
        if east < GERMANY_BOUNDS["west"] or west > GERMANY_BOUNDS["east"]:
            return None
        if north < GERMANY_BOUNDS["south"] or south > GERMANY_BOUNDS["north"]:
            return None

        # Try to load elevation data for this tile
        elevations = await self._get_elevations_for_bounds(west, south, east, north)

        if elevations is None:
            # No DEM data available - return placeholder or None
            return self._generate_placeholder_heightmap()

        # Convert to Terrain-RGB format
        return self._encode_terrain_rgb(elevations)

    async def _get_elevations_for_bounds(
        self, west: float, south: float, east: float, north: float
    ) -> Optional[np.ndarray]:
        """Get elevation data for a bounding box."""
        # Determine which DEM tiles we need
        lat_min = int(math.floor(south))
        lat_max = int(math.ceil(north))
        lon_min = int(math.floor(west))
        lon_max = int(math.ceil(east))

        # Load all required DEM tiles
        dem_tiles = []
        for lat in range(lat_min, lat_max + 1):
            for lon in range(lon_min, lon_max + 1):
                tile = self._load_dem_tile(lat, lon)
                if tile is not None:
                    dem_tiles.append((lat, lon, tile))

        if not dem_tiles:
            return None

        # Interpolate elevations for our tile grid
        elevations = np.zeros((self.tile_size, self.tile_size), dtype=np.float32)

        for py in range(self.tile_size):
            for px in range(self.tile_size):
                # Calculate lat/lon for this pixel
                lon = west + (east - west) * px / self.tile_size
                lat = north - (north - south) * py / self.tile_size

                # Get elevation (simplified - would need proper interpolation)
                elevation = self._sample_elevation(lat, lon, dem_tiles)
                elevations[py, px] = elevation if elevation is not None else 0

        return elevations

    def _sample_elevation(
        self, lat: float, lon: float, dem_tiles: list
    ) -> Optional[float]:
        """Sample elevation at a specific point from loaded DEM tiles."""
        tile_lat = int(math.floor(lat))
        tile_lon = int(math.floor(lon))

        for t_lat, t_lon, data in dem_tiles:
            if t_lat == tile_lat and t_lon == tile_lon:
                # Calculate pixel position within tile
                # Assuming 1 degree = 3600 pixels (1 arcsecond for 30m DEM)
                rows, cols = data.shape
                px = int((lon - tile_lon) * cols)
                py = int((t_lat + 1 - lat) * rows)

                px = max(0, min(cols - 1, px))
                py = max(0, min(rows - 1, py))

                return float(data[py, px])

        return None

    def _encode_terrain_rgb(self, elevations: np.ndarray) -> bytes:
        """
        Encode elevation data as Mapbox Terrain-RGB.

        Format: height = -10000 + ((R * 256 * 256 + G * 256 + B) * 0.1)
        """
        # Convert elevation to RGB values
        # encoded = (elevation + 10000) / 0.1
        encoded = ((elevations + 10000) / 0.1).astype(np.uint32)

        r = (encoded // (256 * 256)) % 256
        g = (encoded // 256) % 256
        b = encoded % 256

        # Create RGB image
        rgb = np.stack([r, g, b], axis=-1).astype(np.uint8)
        img = Image.fromarray(rgb, mode="RGB")

        # Save to bytes
        buffer = BytesIO()
        img.save(buffer, format="PNG")
        return buffer.getvalue()

    def _generate_placeholder_heightmap(self) -> bytes:
        """Generate a flat placeholder heightmap (sea level)."""
        # Sea level = 0m encoded as RGB
        # encoded = (0 + 10000) / 0.1 = 100000
        # R = 100000 // 65536 = 1
        # G = (100000 // 256) % 256 = 134
        # B = 100000 % 256 = 160

        img = Image.new("RGB", (self.tile_size, self.tile_size), (1, 134, 160))
        buffer = BytesIO()
        img.save(buffer, format="PNG")
        return buffer.getvalue()

    async def get_hillshade_tile(
        self, z: int, x: int, y: int, azimuth: float = 315, altitude: float = 45
    ) -> Optional[bytes]:
        """
        Generate a hillshade tile for terrain visualization.

        Args:
            z, x, y: Tile coordinates
            azimuth: Light direction in degrees (0=N, 90=E, 180=S, 270=W)
            altitude: Light altitude in degrees above horizon
        """
        west, south, east, north = tile_to_bounds(z, x, y)
        elevations = await self._get_elevations_for_bounds(west, south, east, north)

        if elevations is None:
            return None

        # Calculate hillshade using numpy
        hillshade = self._calculate_hillshade(elevations, azimuth, altitude)

        # Create grayscale image
        img = Image.fromarray((hillshade * 255).astype(np.uint8), mode="L")

        buffer = BytesIO()
        img.save(buffer, format="PNG")
        return buffer.getvalue()

    def _calculate_hillshade(
        self, dem: np.ndarray, azimuth: float, altitude: float
    ) -> np.ndarray:
        """Calculate hillshade from DEM array."""
        # Convert angles to radians
        azimuth_rad = math.radians(360 - azimuth + 90)
        altitude_rad = math.radians(altitude)

        # Calculate gradient
        dy, dx = np.gradient(dem)

        # Calculate slope and aspect
        slope = np.arctan(np.sqrt(dx**2 + dy**2))
        aspect = np.arctan2(-dy, dx)

        # Calculate hillshade
        hillshade = (
            np.sin(altitude_rad) * np.cos(slope)
            + np.cos(altitude_rad) * np.sin(slope) * np.cos(azimuth_rad - aspect)
        )

        # Normalize to 0-1
        hillshade = np.clip(hillshade, 0, 1)

        return hillshade

    async def get_contour_tile(
        self, z: int, x: int, y: int, interval: int = 20
    ) -> Optional[bytes]:
        """Generate contour lines as vector tile (stub - requires more complex implementation)."""
        # This would require generating contour lines from DEM and encoding as MVT
        # For now, return None
        logger.warning("Contour tiles not yet implemented")
        return None

    async def get_elevation(self, lat: float, lon: float) -> Optional[float]:
        """Get elevation at a specific point."""
        tile_lat = int(math.floor(lat))
        tile_lon = int(math.floor(lon))

        dem_data = self._load_dem_tile(tile_lat, tile_lon)
        if dem_data is None:
            return None

        return self._sample_elevation(lat, lon, [(tile_lat, tile_lon, dem_data)])

    async def get_elevation_profile(
        self, coordinates: list[list[float]], samples: int = 100
    ) -> list[dict]:
        """Get elevation profile along a path."""
        from shapely.geometry import LineString
        from shapely.ops import substring

        # Create line from coordinates
        line = LineString(coordinates)
        total_length = line.length

        # Sample points along line
        profile = []
        for i in range(samples):
            fraction = i / (samples - 1)
            point = line.interpolate(fraction, normalized=True)

            elevation = await self.get_elevation(point.y, point.x)

            profile.append({
                "distance_m": fraction * total_length * 111320,  # Approximate meters
                "longitude": point.x,
                "latitude": point.y,
                "elevation_m": elevation,
            })

        return profile

    async def get_metadata(self) -> dict:
        """Get metadata about available DEM data."""
        dem_files = []
        if os.path.exists(self.dem_dir):
            dem_files = [f for f in os.listdir(self.dem_dir) if f.endswith(".tif")]

        return {
            "data_available": len(dem_files) > 0,
            "tiles_generated": len(dem_files),
            "resolution_m": 30,
            "source": "Copernicus DEM GLO-30",
        }