# -*- coding: utf-8 -*-
__author__ = "Thang Quach"
__date__ = "2024-11-20"
__copyright__ = "(L) 2024, Thang Quach"

import os

from qgis.core import (
    QgsProcessing,
    QgsProcessingParameterFeatureSource,
    QgsProcessingFeatureBasedAlgorithm,
    QgsProcessingParameterEnum,
    QgsProcessingParameterNumber,
    QgsProcessingParameterBoolean,
    QgsProcessingException,
    QgsWkbTypes,
)

from qgis.core import QgsApplication
from qgis.PyQt.QtGui import QIcon
from qgis.PyQt.QtCore import QCoreApplication, QVariant

import platform
from ...utils.help_footer import social_links_footer
from ...utils.conversion.qgsfeature2dggs import *
from ...utils.conversion.crs_helper import wgs84_transform_if_needed
from ...settings import settings


class Vector2DGGS(QgsProcessingFeatureBasedAlgorithm):
    """
    convert Vector Layer to H3, S2, rHEALPix, ISEA4T, ISEA3H, QTM, OLC, Geohash, MGRS, Tilecode, Maidenhead, GARS
    """

    INPUT = "INPUT"
    DGGS_TYPE = "DGGS_TYPE"
    RESOLUTION = "RESOLUTION"
    COMPACT = "COMPACT"
    PREDICATE = "PREDICATE"
    PREDICATES = ["intersects", "within", "centroid_within", "largest_overlap"]
    DGGS_TYPES = [
        "H3",
        "S2",
        "A5",
        "rHEALPix",
        "DGGAL_GNOSIS",
        "DGGAL_ISEA4R",
        "DGGAL_ISEA9R",
        "DGGAL_ISEA3H",
        "DGGAL_ISEA7H",
        "DGGAL_ISEA7H_Z7",
        "DGGAL_IVEA4R",
        "DGGAL_IVEA9R",
        "DGGAL_IVEA3H",
        "DGGAL_IVEA7H",
        "DGGAL_IVEA7H_Z7",
        "DGGAL_RTEA4R",
        "DGGAL_RTEA9R",
        "DGGAL_RTEA3H",
        "DGGAL_RTEA7H",
        "DGGAL_RTEA7H_Z7",
        "DGGAL_HEALPix",
        "DGGAL_rHEALPix",
        "DGGRID_SUPERFUND",
        "DGGRID_PLANETRISK",
        "DGGRID_ISEA3H",
        "DGGRID_ISEA4H",
        "DGGRID_ISEA4T",
        "DGGRID_ISEA4D",
        "DGGRID_ISEA43H",
        "DGGRID_ISEA7H",
        "DGGRID_IGEO7",
        "DGGRID_FULLER3H",
        "DGGRID_FULLER4H",
        "DGGRID_FULLER4T",
        "DGGRID_FULLER4D",
        "DGGRID_FULLER43H",
        "DGGRID_FULLER7H",
        "QTM",
        "OLC",
        "Geohash",
        "Tilecode",
        "Quadkey",
        "DIGIPIN",
    ]

    if platform.system() == "Windows":
        index = DGGS_TYPES.index("rHEALPix") + 1
        DGGS_TYPES[index:index] = ["ISEA4T", "ISEA3H"]

    OUTPUT = "OUTPUT"

    LOC = QgsApplication.locale()[:2]

    def translate(self, string):
        return QCoreApplication.translate("Processing", string)

    def tr(self, *string):
        # Translate to Vietnamese: arg[0] - English (translate), arg[1] - Vietnamese
        if self.LOC == "vi":
            if len(string) == 2:
                return string[1]
            else:
                return self.translate(string[0])
        else:
            return self.translate(string[0])

    def createInstance(self):
        return Vector2DGGS()

    def name(self):
        return "vector2dggs"

    def icon(self):
        return QIcon(
            os.path.join(
                os.path.dirname(os.path.dirname(__file__)),
                "../images/conversion/vector2dggs.png",
            )
        )

    def displayName(self):
        return self.tr("Vector to DGGS", "Vector to DGGS")

    def group(self):
        return self.tr("Conversion", "Conversion")

    def groupId(self):
        return "conversion"

    def tags(self):
        return self.tr(
            "vector, S2, H3, rHEALPix, ISEA4T, ISEA3H, EASE, DGGAL, OLC, OpenLocationCode, Google Plus Codes, MGRS, Geohash, GEOREF, Tilecode, Maidenhead, GARS"
        ).split(",")

    txt_en = "Vector to DGGS"
    txt_vi = "Vector to DGGS"
    figure = "../images/tutorial/vector2dggs.png"

    def shortHelpString(self):
        footer = (
            '''<div align="center">
                      <img src="'''
            + os.path.join(os.path.dirname(os.path.dirname(__file__)), self.figure)
            + """">
                    </div>
                    <div align="right">
                      <p align="right">
                      <b>"""
            + self.tr("Author: Thang Quach", "Author: Thang Quach")
            + """</b>
                      </p>"""
            + social_links_footer()
            + """
                    </div>
                    """
        )
        return self.tr(self.txt_en, self.txt_vi) + footer

    def inputLayerTypes(self):
        return [QgsProcessing.TypeVector]

    def outputName(self):
        return self.tr("Vector2DGGS")

    def outputWkbType(self, input_wkb_type):
        return QgsWkbTypes.Polygon

    def supportInPlaceEdit(self, layer):
        return False

    def initParameters(self, config=None):
        # Input vector layer
        self.addParameter(
            QgsProcessingParameterFeatureSource(
                self.INPUT, self.tr("Input vector layer"), [QgsProcessing.TypeVector]
            )
        )

        self.addParameter(
            QgsProcessingParameterEnum(
                self.DGGS_TYPE, "DGGS type", options=self.DGGS_TYPES, defaultValue=0
            )
        )

        # Get default resolution from settings
        default_res = 2
        default_dggs = self.DGGS_TYPES[0]
        _, _, default_res = settings.getResolution(default_dggs)

        self.addParameter(
            QgsProcessingParameterNumber(
                self.RESOLUTION,
                "Resolution",
                QgsProcessingParameterNumber.Integer,
                default_res,
                minValue=0,
                maxValue=40,
            )
        )

        self.addParameter(
            QgsProcessingParameterEnum(
                self.PREDICATE,
                "Spatial predicate",
                options=self.PREDICATES,
                defaultValue=0,
            )
        )

        self.addParameter(
            QgsProcessingParameterBoolean(self.COMPACT, "Compact", defaultValue=False)
        )

    def checkParameterValues(self, parameters, context):
        """Dynamically update resolution limits before execution"""
        selected_dggs_index = self.parameterAsEnum(parameters, self.DGGS_TYPE, context)
        selected_dggs = self.DGGS_TYPES[selected_dggs_index]

        resolution_settings = settings.getResolution(selected_dggs)
        if resolution_settings is None:
            return (False, f"No resolution settings found for {selected_dggs}.")

        min_res, max_res, _ = resolution_settings
        res_value = self.parameterAsInt(parameters, self.RESOLUTION, context)

        if not (min_res <= res_value <= max_res):
            return (
                False,
                f"Resolution must be between {min_res} and {max_res} for {selected_dggs}.",
            )

        if selected_dggs == "OLC":
            if res_value not in (2, 4, 6, 8, 10, 11, 12, 13, 14, 15):
                return (
                    False,
                    f"Resolution must be in [2,4,6,8,10,11,12,13,14,15] for {selected_dggs}.",
                )
        return super().checkParameterValues(parameters, context)

    def outputFields(self, input_fields):
        output_fields = QgsFields()

        # Preserve all original input fields
        for field in input_fields:
            output_fields.append(field)

        # Function to generate a unique field name by adding a suffix if necessary
        def get_unique_name(base_name):
            existing_names = {field.name() for field in output_fields}
            if base_name not in existing_names:
                return base_name
            i = 1
            while f"{base_name}_{i}" in existing_names:
                i += 1
            return f"{base_name}_{i}"

        dggs_type = self.DGGS_TYPES[self.DGGS_TYPE_index].lower()

        # Fields to be added
        new_fields = [
            QgsField(get_unique_name(dggs_type), QVariant.String),
            QgsField(get_unique_name("resolution"), QVariant.Int),
            QgsField(get_unique_name("center_lat"), QVariant.Double),
            QgsField(get_unique_name("center_lon"), QVariant.Double),
            QgsField(
                get_unique_name(
                    "avg_edge_len"
                    if dggs_type
                    in ("h3", "s2", "a5", "rhealpix", "isea4t", "isea3h", "ease", "qtm")
                    or dggs_type.startswith("dggal_")
                    or dggs_type.startswith("dggrid_")
                    else "cell_width"
                ),
                QVariant.Double,
            ),
            QgsField(get_unique_name("cell_height"), QVariant.Double)
            if dggs_type
            not in ("h3", "s2", "a5", "rhealpix", "isea4t", "isea3h", "ease", "qtm")
            and not dggs_type.startswith("dggal_")
            and not dggs_type.startswith("dggrid_")
            else None,
            QgsField(get_unique_name("cell_area"), QVariant.Double),
            QgsField(get_unique_name("cell_perimeter"), QVariant.Double),
        ]

        # Append the fields to output_fields
        for field in new_fields:
            if field:
                output_fields.append(field)

        return output_fields

    def prepareAlgorithm(self, parameters, context, feedback):
        source = self.parameterAsSource(parameters, self.INPUT, context)
        crs = source.sourceCrs() if hasattr(source, "sourceCrs") else None
        try:
            self._to_wgs84 = wgs84_transform_if_needed(
                crs, context.transformContext(), feedback
            )
        except QgsProcessingException as exc:
            feedback.reportError(str(exc))
            return False

        self.resolution = self.parameterAsInt(parameters, self.RESOLUTION, context)
        self.compact = self.parameterAsBool(parameters, self.COMPACT, context)
        self.predicate = self.parameterAsEnum(parameters, self.PREDICATE, context)

        self.total_features = source.featureCount()
        self.num_bad = 0

        self.DGGS_TYPE_index = self.parameterAsEnum(parameters, self.DGGS_TYPE, context)
        self.DGGS_TYPE_functions = {
            "h3": qgsfeature2h3,
            "s2": qgsfeature2s2,
            "a5": qgsfeature2a5,
            "rhealpix": qgsfeature2rhealpix,
            "isea4t": qgsfeature2isea4t,
            "isea3h": qgsfeature2isea3h,
            "qtm": qgsfeature2qtm,
            "olc": qgsfeature2olc,
            "geohash": qgsfeature2geohash,
            "tilecode": qgsfeature2tilecode,
            "quadkey": qgsfeature2quadkey,
            "digipin": qgsfeature2digipin,
            "dggal_gnosis": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "gnosis", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_isea4r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "isea4r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_isea9r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "isea9r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_isea3h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "isea3h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_isea7h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "isea7h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_isea7h_z7": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "isea7h_z7", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_ivea4r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "ivea4r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_ivea9r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "ivea9r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_ivea3h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "ivea3h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_ivea7h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "ivea7h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_ivea7h_z7": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "ivea7h_z7", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rtea4r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rtea4r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rtea9r": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rtea9r", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rtea3h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rtea3h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rtea7h": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rtea7h", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rtea7h_z7": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rtea7h_z7", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_healpix": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "healpix", feature, resolution, predicate, compact, feedback
                )
            ),
            "dggal_rhealpix": lambda feature, resolution, predicate, compact, feedback: (
                qgsfeature2dggal(
                    "rhealpix", feature, resolution, predicate, compact, feedback
                )
            ),
        }
        for dggrid_name in (
            "SUPERFUND",
            "PLANETRISK",
            "ISEA3H",
            "ISEA4H",
            "ISEA4T",
            "ISEA4D",
            "ISEA43H",
            "ISEA7H",
            "IGEO7",
            "FULLER3H",
            "FULLER4H",
            "FULLER4T",
            "FULLER4D",
            "FULLER43H",
            "FULLER7H",
        ):
            key = f"dggrid_{dggrid_name.lower()}"
            self.DGGS_TYPE_functions[key] = (
                lambda feature, resolution, predicate, compact, feedback, t=dggrid_name: (
                    qgsfeature2dggrid(
                        t, feature, resolution, predicate, compact, feedback
                    )
                )
            )
        return True

    def processFeature(self, feature, context, feedback):
        try:
            feature = prepare_feature_for_dggs_conversion(
                feature, getattr(self, "_to_wgs84", None)
            )
            self.dggs_type = self.DGGS_TYPES[self.DGGS_TYPE_index].lower()
            conversion_function = self.DGGS_TYPE_functions.get(self.dggs_type)

            if conversion_function is None:
                return []

            feature_geom = feature.geometry()
            flat_type = QgsWkbTypes.flatType(feature_geom.wkbType())

            cell_polygons = []
            multi_cell_polygons = []

            # Handle MultiPoint geometry
            if flat_type == QgsWkbTypes.MultiPoint:
                for point in feature_geom.asMultiPoint():
                    point_feature = QgsFeature(feature)
                    point_feature.setGeometry(QgsGeometry.fromPointXY(point))
                    cell_polygons = conversion_function(
                        point_feature,
                        self.resolution,
                        self.predicate,
                        self.compact,
                        feedback,
                    )
                    if cell_polygons:
                        multi_cell_polygons.extend(cell_polygons)
                return multi_cell_polygons

            # Handle MultiLineString geometry
            elif flat_type == QgsWkbTypes.MultiLineString:
                for line in feature_geom.asMultiPolyline():
                    line_feature = QgsFeature(feature)
                    line_feature.setGeometry(QgsGeometry.fromPolylineXY(line))
                    cell_polygons = conversion_function(
                        line_feature,
                        self.resolution,
                        self.predicate,
                        self.compact,
                        feedback,
                    )
                    if cell_polygons:
                        multi_cell_polygons.extend(cell_polygons)
                return multi_cell_polygons

            # Handle MultiPolygon geometry
            elif flat_type == QgsWkbTypes.MultiPolygon:
                for polygon in feature_geom.asMultiPolygon():
                    polygon_feature = QgsFeature(feature)
                    polygon_feature.setGeometry(QgsGeometry.fromPolygonXY(polygon))
                    cell_polygons = conversion_function(
                        polygon_feature,
                        self.resolution,
                        self.predicate,
                        self.compact,
                        feedback,
                    )
                    if cell_polygons:
                        multi_cell_polygons.extend(cell_polygons)
                return multi_cell_polygons

            else:  # Single part features
                result = conversion_function(
                    feature, self.resolution, self.predicate, self.compact, feedback
                )
                return result if result is not None else []

        except Exception as e:
            self.num_bad += 1
            feedback.reportError(f"Error processing feature {feature.id()}: {str(e)}")
            return []

    def postProcessAlgorithm(self, context, feedback):
        if self.num_bad:
            feedback.pushInfo(
                self.tr(
                    "{} out of {} features had invalid parameters and were ignored.".format(
                        self.num_bad, self.total_features
                    )
                )
            )
        return {}
