"""
Vector to Tilecode Module

This module provides functionality to convert vector geometries to Tilecode grid cells with flexible input and output formats.
Tilecodes are hierarchical spatial identifiers in the format 'z{x}x{y}y{z}' where z is the zoom level and x,y are tile coordinates.

Key Functions:
    point2tilecode: Convert point geometries to Tilecode cells
    polyline2tilecode: Convert line geometries to Tilecode cells
    polygon2tilecode: Convert polygon geometries to Tilecode cells with spatial predicates
    geodataframe2tilecode: Convert GeoDataFrame to Tilecode cells with topology support
    vector2tilecode: Main function for converting various input formats to Tilecode cells
    vector2tilecode_cli: Command-line interface for batch processing
"""

import sys
import os
import re
import argparse
from math import sqrt
from tqdm import tqdm
from shapely.geometry import Polygon, MultiPoint
import geopandas as gpd
from vgrid.dggs import tilecode
from vgrid.dggs import mercantile
from vgrid.utils.geometry import graticule_dggs_to_geoseries
from vgrid.conversion.dggscompact.tilecodecompact import tilecodecompact
from vgrid.utils.geometry import (
    check_predicate,
    shortest_point_distance,
)
from vgrid.utils.io import (
    validate_tilecode_resolution,
    process_input_data_vector,
    convert_to_output_format,
    DGGS_TYPES,
)
from vgrid.utils.constants import OUTPUT_FORMATS, STRUCTURED_FORMATS

min_res = DGGS_TYPES["tilecode"]["min_res"]
max_res = DGGS_TYPES["tilecode"]["max_res"]


def point2tilecode(
    feature,
    resolution,
    feature_properties=None,
    predicate=None,
    compact=False,
    topology=False,
    include_properties=True,
):
    """
    Convert a point geometry to Tilecode grid cells.

    Converts point or multipoint geometries to Tilecode grid cells at the specified resolution.
    Each point is assigned to its containing Tilecode cell.

    Parameters
    ----------
    feature : shapely.geometry.Point or shapely.geometry.MultiPoint
        Point geometry to convert to Tilecode cells.
    resolution : int
        Tilecode resolution level [0..29].
    feature_properties : dict, optional
        Properties to include in output features.
    predicate : str, optional
        Spatial predicate to apply (not used for points).
    compact : bool, optional
        Enable Tilecode compact mode (not used for points).
    topology : bool, optional
        Enable topology preserving mode (handled by geodataframe2tilecode).
    include_properties : bool, optional
        Whether to include properties in output.

    Returns
    -------
    list of dict
        List of dictionaries representing Tilecode cells containing the point(s).
        Each dictionary contains Tilecode cell properties and geometry.

    Examples
    --------
    >>> from shapely.geometry import Point
    >>> point = Point(-122.4194, 37.7749)  # San Francisco
    >>> cells = point2tilecode(point, 10, {"name": "SF"})
    >>> len(cells)
    1

    >>> from shapely.geometry import MultiPoint
    >>> points = MultiPoint([(-122.4194, 37.7749), (-74.0060, 40.7128)])
    >>> cells = point2tilecode(points, 8)
    >>> len(cells)
    2
    """
    tilecode_rows = []
    if feature.geom_type in ("Point"):
        points = [feature]
    elif feature.geom_type in ("MultiPoint"):
        points = list(feature.geoms)
    else:
        return []

    for point in points:
        tilecode_id = tilecode.latlon2tilecode(point.y, point.x, resolution)
        tilecode_cell = mercantile.tile(point.x, point.y, resolution)
        bounds = mercantile.bounds(tilecode_cell)
        if bounds:
            min_lat, min_lon = bounds.south, bounds.west
            max_lat, max_lon = bounds.north, bounds.east
            cell_polygon = Polygon(
                [
                    [min_lon, min_lat],
                    [max_lon, min_lat],
                    [max_lon, max_lat],
                    [min_lon, max_lat],
                    [min_lon, min_lat],
                ]
            )
            tilecode_row = graticule_dggs_to_geoseries(
                "tilecode", tilecode_id, resolution, cell_polygon
            )
            if include_properties and feature_properties:
                tilecode_row.update(feature_properties)
            tilecode_rows.append(tilecode_row)
    return tilecode_rows


def polyline2tilecode(
    feature,
    resolution,
    feature_properties=None,
    predicate=None,
    compact=False,
    topology=False,
    include_properties=True,
):
    """
    Convert a polyline geometry to Tilecode grid cells.

    Args:
        feature (shapely.geometry.LineString or shapely.geometry.MultiLineString): Polyline geometry to convert
        resolution (int): Tilecode resolution level [0..29]
        feature_properties (dict, optional): Properties to include in output features
        predicate (str, optional): Spatial predicate to apply (not used for polylines)
        compact (bool, optional): Enable Tilecode compact mode (not used for polylines)
        topology (bool, optional): Enable topology preserving mode (handled by geodataframe2tilecode)
        include_properties (bool, optional): Whether to include properties in output

    Returns:
        list: List of dictionaries representing Tilecode cells intersecting the polyline

    Example:
        >>> from shapely.geometry import LineString
        >>> line = LineString([(-122.4194, 37.7749), (-122.4000, 37.7800)])
        >>> cells = polyline2tilecode(line, 10, {"name": "route"})
        >>> len(cells) > 0
        True
    """
    tilecode_rows = []
    if feature.geom_type in ("LineString"):
        polylines = [feature]
    elif feature.geom_type in ("MultiLineString"):
        polylines = list(feature.geoms)
    else:
        return []

    for polyline in polylines:
        min_lon, min_lat, max_lon, max_lat = polyline.bounds
        tilecodes = mercantile.tiles(min_lon, min_lat, max_lon, max_lat, resolution)
        tilecode_ids = []
        for tile in tilecodes:
            tilecode_id = f"z{tile.z}x{tile.x}y{tile.y}"
            tilecode_ids.append(tilecode_id)
        for tilecode_id in tilecode_ids:
            match = re.match(r"z(\d+)x(\d+)y(\d+)", tilecode_id)
            if not match:
                raise ValueError(
                    "Invalid tilecode output_format. Expected output_format: 'zXxYyZ'"
                )
            cell_resolution = int(match.group(1))
            z = int(match.group(1))
            x = int(match.group(2))
            y = int(match.group(3))
            bounds = mercantile.bounds(x, y, z)
            if bounds:
                min_lat, min_lon = bounds.south, bounds.west
                max_lat, max_lon = bounds.north, bounds.east
                cell_polygon = Polygon(
                    [
                        [min_lon, min_lat],
                        [max_lon, min_lat],
                        [max_lon, max_lat],
                        [min_lon, max_lat],
                        [min_lon, min_lat],
                    ]
                )
                if cell_polygon.intersects(polyline):
                    tilecode_row = graticule_dggs_to_geoseries(
                        "tilecode", tilecode_id, cell_resolution, cell_polygon
                    )
                    if feature_properties:
                        tilecode_row.update(feature_properties)
                    tilecode_rows.append(tilecode_row)
    return tilecode_rows


def polygon2tilecode(
    feature,
    resolution,
    feature_properties=None,
    predicate=None,
    compact=False,
    topology=False,
    include_properties=True,
):
    """
    Convert a polygon geometry to Tilecode grid cells.

    Args:
        feature (shapely.geometry.Polygon or shapely.geometry.MultiPolygon): Polygon geometry to convert
        resolution (int): Tilecode resolution level [0..29]
        feature_properties (dict, optional): Properties to include in output features
        predicate (str, optional): Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact (bool, optional): Enable Tilecode compact mode to reduce cell count
        topology (bool, optional): Enable topology preserving mode (handled by geodataframe2tilecode)
        include_properties (bool, optional): Whether to include properties in output

    Returns:
        list: List of dictionaries representing Tilecode cells based on predicate

    Example:
        >>> from shapely.geometry import Polygon
        >>> poly = Polygon([(-122.5, 37.7), (-122.3, 37.7), (-122.3, 37.9), (-122.5, 37.9)])
        >>> cells = polygon2tilecode(poly, 10, {"name": "area"}, predicate="intersect")
        >>> len(cells) > 0
        True
    """
    tilecode_rows = []
    if feature.geom_type in ("Polygon"):
        polygons = [feature]
    elif feature.geom_type in ("MultiPolygon"):
        polygons = list(feature.geoms)
    else:
        return []

    for polygon in polygons:
        min_lon, min_lat, max_lon, max_lat = polygon.bounds
        tilecodes = mercantile.tiles(min_lon, min_lat, max_lon, max_lat, resolution)
        tilecode_ids = []
        for tile in tilecodes:
            tilecode_id = f"z{tile.z}x{tile.x}y{tile.y}"
            tilecode_ids.append(tilecode_id)
        for tilecode_id in tilecode_ids:
            match = re.match(r"z(\d+)x(\d+)y(\d+)", tilecode_id)
            if not match:
                raise ValueError(
                    "Invalid tilecode output_format. Expected output_format: 'zXxYyZ'"
                )
            cell_resolution = int(match.group(1))
            z = int(match.group(1))
            x = int(match.group(2))
            y = int(match.group(3))
            bounds = mercantile.bounds(x, y, z)
            if bounds:
                min_lat, min_lon = bounds.south, bounds.west
                max_lat, max_lon = bounds.north, bounds.east
                cell_polygon = Polygon(
                    [
                        [min_lon, min_lat],
                        [max_lon, min_lat],
                        [max_lon, max_lat],
                        [min_lon, max_lat],
                        [min_lon, min_lat],
                    ]
                )
                if check_predicate(cell_polygon, polygon, predicate):
                    tilecode_row = graticule_dggs_to_geoseries(
                        "tilecode", tilecode_id, cell_resolution, cell_polygon
                    )
                    if include_properties and feature_properties:
                        tilecode_row.update(feature_properties)
                    tilecode_rows.append(tilecode_row)

    # Apply compact mode if enabled
    if compact and tilecode_rows:
        # Create a GeoDataFrame from the current results
        temp_gdf = gpd.GeoDataFrame(tilecode_rows, geometry="geometry", crs="EPSG:4326")

        # Use tilecodecompact function directly
        compacted_gdf = tilecodecompact(
            temp_gdf, tilecode_id="tilecode", output_format="gpd"
        )

        if compacted_gdf is not None:
            # Convert back to list of dictionaries
            tilecode_rows = compacted_gdf.to_dict("records")
        # If compaction failed, keep original results

    return tilecode_rows


def geodataframe2tilecode(
    gdf,
    resolution=None,
    predicate=None,
    compact=False,
    topology=False,
    include_properties=True,
):
    """
    Convert a GeoDataFrame to Tilecode grid cells.

    Args:
        gdf (geopandas.GeoDataFrame): GeoDataFrame to convert
        resolution (int, optional): Tilecode resolution level [0..29]. Required when topology=False, auto-calculated when topology=True
        predicate (str, optional): Spatial predicate to apply for polygons ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact (bool, optional): Enable Tilecode compact mode for polygons
        topology (bool, optional): Enable topology preserving mode to ensure disjoint features have disjoint Tilecode cells
        include_properties (bool, optional): Whether to include properties in output

    Returns:
        geopandas.GeoDataFrame: GeoDataFrame with Tilecode grid cells

    Example:
        >>> import geopandas as gpd
        >>> from shapely.geometry import Point
        >>> gdf = gpd.GeoDataFrame({
        ...     'name': ['San Francisco'],
        ...     'geometry': [Point(-122.4194, 37.7749)]
        ... })
        >>> result = geodataframe2tilecode(gdf, 10)
        >>> len(result) > 0
        True
    """
    # Process topology for points and multipoints if enabled
    if topology:
        estimated_resolution = resolution
        # Collect all points for topology preservation
        points_list = []
        for _, row in gdf.iterrows():
            geom = row.geometry
            if geom is None:
                continue
            if geom.geom_type == "Point":
                points_list.append(geom)
            elif geom.geom_type == "MultiPoint":
                points_list.extend(list(geom.geoms))

        if points_list:
            all_points = MultiPoint(points_list)

            # Calculate the shortest distance between all points
            shortest_distance = shortest_point_distance(all_points)

            # Find resolution where Tilecode cell size is smaller than shortest distance
            # This ensures disjoint points have disjoint Tilecode cells
            if shortest_distance > 0:
                tilecode_cell_sizes = [
                    40075016.68557849 / (2**z) for z in range(min_res, max_res + 1)
                ]
                for res in range(min_res, max_res + 1):
                    cell_diameter = tilecode_cell_sizes[res] * sqrt(2) * 2
                    if cell_diameter < shortest_distance:
                        estimated_resolution = res
                        break
        resolution = estimated_resolution

    resolution = validate_tilecode_resolution(resolution)

    tilecode_rows = []

    for _, row in tqdm(gdf.iterrows(), desc="Processing features", total=len(gdf)):
        geom = row.geometry
        if geom is None:
            continue

        props = row.to_dict()
        if "geometry" in props:
            del props["geometry"]

        if not include_properties:
            props = {}

        if geom.geom_type == "Point" or geom.geom_type == "MultiPoint":
            tilecode_rows.extend(
                point2tilecode(
                    feature=geom,
                    resolution=resolution,
                    feature_properties=props,
                    predicate=predicate,
                    compact=compact,
                    topology=topology,  # Topology already processed above
                    include_properties=include_properties,
                )
            )

        elif geom.geom_type in ("LineString", "MultiLineString"):
            tilecode_rows.extend(
                polyline2tilecode(
                    feature=geom,
                    resolution=resolution,
                    feature_properties=props,
                    predicate=predicate,
                    compact=compact,
                    include_properties=include_properties,
                )
            )
        elif geom.geom_type in ("Polygon", "MultiPolygon"):
            tilecode_rows.extend(
                polygon2tilecode(
                    feature=geom,
                    resolution=resolution,
                    feature_properties=props,
                    predicate=predicate,
                    compact=compact,
                    include_properties=include_properties,
                )
            )
    return gpd.GeoDataFrame(tilecode_rows, geometry="geometry", crs="EPSG:4326")


# --- Main vector2tilecode function ---
def vector2tilecode(
    vector_data,
    resolution=None,
    predicate=None,
    compact=False,
    topology=False,
    output_format="gpd",
    include_properties=True,
    **kwargs,
):
    """
    Convert vector data to Tilecode grid cells from various input formats.

    Args:
        vector_data (str, geopandas.GeoDataFrame, pandas.DataFrame, dict, or list): Input vector data
        resolution (int, optional): Tilecode resolution level [0..29]. Required when topology=False, auto-calculated when topology=True
        predicate (str, optional): Spatial predicate to apply for polygons ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact (bool, optional): Enable Tilecode compact mode for polygons
        topology (bool, optional): Enable topology preserving mode to ensure disjoint features have disjoint Tilecode cells
        output_format (str, optional): Output format ('gpd', 'geojson', 'csv', 'shapefile', 'gpkg', 'parquet', 'geoparquet')
        include_properties (bool, optional): Whether to include properties in output
        **kwargs: Additional arguments passed to process_input_data_vector

    Returns:
        geopandas.GeoDataFrame, dict, or str: Output in the specified format. If output_format is a file-based format,
        the output will be saved to a file in the current directory with a default name based on the input.
        Otherwise, returns a Python object (GeoDataFrame, dict, etc.) depending on output_format.

    Example:
        >>> result = vector2tilecode("data/points.geojson", resolution=10, output_format="geojson")
        >>> print(f"Output saved to: {result}")
    """
    # Validate resolution parameter
    if not topology and resolution is None:
        raise ValueError("resolution parameter is required when topology=False")

    # Only validate resolution if it's not None
    if resolution is not None:
        resolution = validate_tilecode_resolution(resolution)

    gdf = process_input_data_vector(vector_data, **kwargs)
    result = geodataframe2tilecode(
        gdf, resolution, predicate, compact, topology, include_properties
    )
    output_name = None
    if output_format in OUTPUT_FORMATS:
        if isinstance(vector_data, str):
            base = os.path.splitext(os.path.basename(vector_data))[0]
            output_name = f"{base}2tilecode"
        else:
            output_name = "tilecode"
    return convert_to_output_format(result, output_format, output_name)


# --- CLI ---
def vector2tilecode_cli():
    """
    Command-line interface for vector2tilecode conversion.

    This function provides a command-line interface for converting vector data to Tilecode grid cells.
    It supports various input formats and output formats, with options for resolution control,
    spatial predicates, compact mode, and topology preservation.

    Usage:
        python vector2tilecode.py -i input.geojson -r 10 -f geojson
        python vector2tilecode.py -i input.shp -r 8 -p intersect -c -t
    """
    parser = argparse.ArgumentParser(
        description="Convert vector data to Tilecode grid cells"
    )
    parser.add_argument("-i", "--input", help="Input file path, URL")

    parser.add_argument(
        "-r",
        "--resolution",
        type=int,
        choices=range(min_res, max_res + 1),
        help=f"Tilecode resolution [{min_res}..{max_res}]. Required when topology=False, auto-calculated when topology=True",
    )
    parser.add_argument(
        "-p",
        "--predicate",
        choices=["intersect", "within", "centroid_within", "largest_overlap"],
        help="Spatial predicate: intersect, within, centroid_within, largest_overlap for polygons",
    )
    parser.add_argument(
        "-c",
        "--compact",
        action="store_true",
        help="Enable Tilecode compact mode for polygons",
    )
    parser.add_argument(
        "-t", "--topology", action="store_true", help="Enable topology preserving mode"
    )
    parser.add_argument(
        "-np",
        "-no-props",
        dest="include_properties",
        action="store_false",
        help="Do not include original feature properties.",
    )
    parser.add_argument(
        "-f",
        "--output_format",
        type=str,
        choices=OUTPUT_FORMATS,
        default="gpd",
        help="Output format (default: gpd).",
    )
    args = parser.parse_args()

    try:
        result = vector2tilecode(
            vector_data=args.input,
            resolution=args.resolution,
            predicate=args.predicate,
            compact=args.compact,
            topology=args.topology,
            output_format=args.output_format,
            include_properties=args.include_properties,
        )
        if args.output_format in STRUCTURED_FORMATS:
            print(result)
        # For file outputs, the utility prints the saved path
    except Exception as e:
        print(f"Error: {str(e)}", file=sys.stderr)
        sys.exit(1)


if __name__ == "__main__":
    vector2tilecode_cli()
