# Copyright (c) 2019 University of Illinois and others. All rights reserved.
#
# This program and the accompanying materials are made available under the
# terms of the Mozilla Public License v2.0 which accompanies this distribution,
# and is available at https://www.mozilla.org/en-US/MPL/2.0/

import concurrent.futures
from itertools import repeat

from pyincore import (
    BaseAnalysis,
    HazardService,
    FragilityService,
    AnalysisUtil,
    GeoUtil,
)
from pyincore.models.dfr3curve import DFR3Curve


class RoadDamage(BaseAnalysis):
    """Road Damage Analysis calculates the probability of road damage based on an earthquake or tsunami hazard.

    Args:
        incore_client (IncoreClient): Service authentication.

    """

    DEFAULT_FRAGILITY_KEY = "Non-Retrofit Fragility ID Code"

    def __init__(self, incore_client):
        self.hazardsvc = HazardService(incore_client)
        self.fragilitysvc = FragilityService(incore_client)

        super(RoadDamage, self).__init__(incore_client)

    def run(self):
        """Executes road damage analysis."""
        # Road dataset
        road_set = self.get_input_dataset("roads").get_inventory_reader()

        # Get Fragility key
        fragility_key = self.get_parameter("fragility_key")
        if fragility_key is None:
            fragility_key = self.DEFAULT_FRAGILITY_KEY

        # get input hazard
        (
            hazard,
            hazard_type,
            hazard_dataset_id,
        ) = self.create_hazard_object_from_input_params()

        # Liquefaction
        use_liquefaction = False
        if self.get_parameter("use_liquefaction") is not None:
            use_liquefaction = self.get_parameter("use_liquefaction")

        # Get geology dataset for liquefaction
        geology_dataset_id = None
        if self.get_parameter("liquefaction_geology_dataset_id") is not None:
            geology_dataset_id = self.get_parameter("liquefaction_geology_dataset_id")

        # Hazard Uncertainty
        use_hazard_uncertainty = False
        if self.get_parameter("use_hazard_uncertainty") is not None:
            use_hazard_uncertainty = self.get_parameter("use_hazard_uncertainty")

        user_defined_cpu = 1
        if (
            self.get_parameter("num_cpu") is not None
            and self.get_parameter("num_cpu") > 0
        ):
            user_defined_cpu = self.get_parameter("num_cpu")

        num_workers = AnalysisUtil.determine_parallelism_locally(
            self, len(road_set), user_defined_cpu
        )

        avg_bulk_input_size = int(len(road_set) / num_workers)
        inventory_args = []
        count = 0
        inventory_list = list(road_set)
        while count < len(inventory_list):
            inventory_args.append(inventory_list[count : count + avg_bulk_input_size])
            count += avg_bulk_input_size

        (ds_results, damage_results) = self.road_damage_concurrent_future(
            self.road_damage_analysis_bulk_input,
            num_workers,
            inventory_args,
            repeat(hazard),
            repeat(hazard_type),
            repeat(hazard_dataset_id),
            repeat(use_hazard_uncertainty),
            repeat(geology_dataset_id),
            repeat(fragility_key),
            repeat(use_liquefaction),
        )

        self.set_result_csv_data(
            "result", ds_results, name=self.get_parameter("result_name")
        )
        self.set_result_json_data(
            "metadata",
            damage_results,
            name=self.get_parameter("result_name") + "_additional_info",
        )

        return True

    def road_damage_concurrent_future(self, function_name, num_workers, *args):
        """Utilizes concurrent.future module.

        Args:
            function_name (function): The function to be parallelized.
            num_workers (int): Number of workers in parallelization.
            *args: All the arguments in order to pass into parameter function_name.

        Returns:
            output_ds: A list of ordered dictionaries with road damage values
            output_dmg: A list of ordered dictionaries with other road data/metadata.

        """

        output_ds = []
        output_dmg = []
        with concurrent.futures.ProcessPoolExecutor(
            max_workers=num_workers
        ) as executor:
            for ret1, ret2 in executor.map(function_name, *args):
                output_ds.extend(ret1)
                output_dmg.extend(ret2)

        return output_ds, output_dmg

    def road_damage_analysis_bulk_input(
        self,
        roads,
        hazard,
        hazard_type,
        hazard_dataset_id,
        use_hazard_uncertainty,
        geology_dataset_id,
        fragility_key,
        use_liquefaction,
    ):
        """Run analysis for multiple roads.

        Args:
            roads (list): Multiple roads from input inventory set.
            hazard (obj): A hazard object.
            hazard_type (str): A hazard type of the hazard exposure (earthquake or tsunami).
            hazard_dataset_id (str): An id of the hazard exposure.
            use_hazard_uncertainty(bool): Flag to indicate use uncertainty or not
            geology_dataset_id (str): An id of the geology for use in liquefaction.
            fragility_key (str): Fragility key describing the type of fragility.
            use_liquefaction (bool): Liquefaction. True for using liquefaction information to modify the damage,
                False otherwise.

        Returns:
            list: A list of ordered dictionaries with road damage values and other data/metadata.
            list: A list of ordered dictionaries with other road data/metadata.

        """
        fragility_sets = self.fragilitysvc.match_inventory(
            self.get_input_dataset("dfr3_mapping_set"), roads, fragility_key
        )

        values_payload = []
        mapped_roads = []
        unmapped_roads = []
        pgd_flag = True  # for liquefaction
        liquefaction_resp = None

        for road in roads:
            if road["id"] in fragility_sets.keys():
                fragility_set = fragility_sets[road["id"]]
                location = GeoUtil.get_location(road)
                loc = str(location.y) + "," + str(location.x)
                demands = fragility_set.demand_types
                # for liquefaction
                if any(demand.lower() != "pgd" for demand in demands):
                    pgd_flag = False
                units = fragility_set.demand_units
                value = {"demands": demands, "units": units, "loc": loc}
                values_payload.append(value)
                mapped_roads.append(road)
            else:
                unmapped_roads.append(road)
        del roads

        # get hazard and liquefaction values
        if hazard_type == "earthquake":
            hazard_resp = hazard.read_hazard_values(values_payload, self.hazardsvc)

            if pgd_flag and use_liquefaction and geology_dataset_id is not None:
                liquefaction_resp = self.hazardsvc.post_liquefaction_values(
                    hazard_dataset_id, geology_dataset_id, values_payload
                )

        elif hazard_type == "tsunami" or "hurricane":
            hazard_resp = hazard.read_hazard_values(values_payload, self.hazardsvc)
        else:
            raise ValueError(
                "The provided hazard type is not supported yet by this analysis"
            )

        # calculate LS and DS
        ds_results = []
        damage_results = []
        for i, road in enumerate(mapped_roads):
            dmg_probability = dict()
            dmg_interval = dict()
            demand_types_liq = None
            demand_units_liq = None
            liq_hazard_vals = None
            liquefaction_prob = None
            selected_fragility_set = fragility_sets[road["id"]]
            # hazard_std_dev = 0.0
            if use_hazard_uncertainty:
                raise ValueError("Uncertainty Not Implemented Yet.")

            if isinstance(selected_fragility_set.fragility_curves[0], DFR3Curve):
                hazard_vals = AnalysisUtil.update_precision_of_lists(
                    hazard_resp[i]["hazardValues"]
                )
                demand_types = hazard_resp[i]["demands"]
                demand_units = hazard_resp[i]["units"]
                hval_dict = dict()
                for j, d in enumerate(selected_fragility_set.demand_types):
                    hval_dict[d] = hazard_vals[j]

                if not AnalysisUtil.do_hazard_values_have_errors(
                    hazard_resp[i]["hazardValues"]
                ):
                    road_args = (
                        selected_fragility_set.construct_expression_args_from_inventory(
                            road
                        )
                    )
                    dmg_probability = selected_fragility_set.calculate_limit_state(
                        hval_dict, inventory_type="road", **road_args
                    )

                    # if there is liquefaction, overwrite the hazardval with liquefaction value
                    # recalculate dmg_probability and dmg_interval
                    if liquefaction_resp is not None and len(liquefaction_resp) > 0:
                        liq_hazard_vals = AnalysisUtil.update_precision_of_lists(
                            liquefaction_resp[i]["pgdValues"]
                        )
                        demand_types_liq = liquefaction_resp[i]["demands"]
                        demand_units_liq = liquefaction_resp[i]["units"]
                        liquefaction_prob = liquefaction_resp[i]["liqProbability"]
                        liq_hval_dict = dict()
                        for j, d in enumerate(liquefaction_resp[i]["demands"]):
                            liq_hval_dict[d] = liq_hazard_vals[j]
                        dmg_probability = selected_fragility_set.calculate_limit_state(
                            liq_hval_dict, inventory_type="road", **road_args
                        )

                    dmg_interval = selected_fragility_set.calculate_damage_interval(
                        dmg_probability, hazard_type=hazard_type, inventory_type="road"
                    )
            else:
                raise ValueError(
                    "One of the fragilities is in deprecated format. This should not happen. If you are "
                    "seeing this please report the issue."
                )

            ds_result = dict()
            ds_result["guid"] = road["properties"]["guid"]
            ds_result.update(dmg_probability)
            ds_result.update(dmg_interval)
            ds_result["haz_expose"] = AnalysisUtil.get_exposure_from_hazard_values(
                hazard_vals, hazard_type
            )

            damage_result = dict()
            damage_result["guid"] = road["properties"]["guid"]
            damage_result["fragility_id"] = selected_fragility_set.id
            damage_result["demandtypes"] = demand_types
            damage_result["demandunits"] = demand_units
            damage_result["hazardtype"] = hazard_type
            damage_result["hazardvals"] = hazard_vals
            damage_result["liqdemandtypes"] = demand_types_liq
            damage_result["liqdemandunits"] = demand_units_liq
            damage_result["liqhazvals"] = liq_hazard_vals
            damage_result["liqprobability"] = liquefaction_prob

            ds_results.append(ds_result)
            damage_results.append(damage_result)

        for road in unmapped_roads:
            ds_result = dict()
            damage_result = dict()

            ds_result["guid"] = road["properties"]["guid"]

            damage_result["guid"] = road["properties"]["guid"]
            damage_result["fragility_id"] = None
            damage_result["demandtypes"] = None
            damage_result["demandunits"] = None
            damage_result["hazardtype"] = None
            damage_result["hazardvals"] = None
            damage_result["liqdemandtypes"] = None
            damage_result["liqdemandunits"] = None
            damage_result["liqhazvals"] = None
            damage_result["liqprobability"] = None

            ds_results.append(ds_result)
            damage_results.append(damage_result)

        return ds_results, damage_results

    def get_spec(self):
        """Get specifications of the road damage analysis.

        Returns:
            obj: A JSON object of specifications of the road damage analysis.

        """

        return {
            "name": "road-damage",
            "description": "road damage analysis",
            "input_parameters": [
                {
                    "id": "result_name",
                    "required": True,
                    "description": "result dataset name",
                    "type": str,
                },
                {
                    "id": "hazard_type",
                    "required": False,
                    "description": "Hazard Type (e.g. earthquake)",
                    "type": str,
                },
                {
                    "id": "hazard_id",
                    "required": False,
                    "description": "Hazard ID",
                    "type": str,
                },
                {
                    "id": "fragility_key",
                    "required": False,
                    "description": "Fragility key to use in mapping dataset",
                    "type": str,
                },
                {
                    "id": "use_liquefaction",
                    "required": False,
                    "description": "Use liquefaction",
                    "type": bool,
                },
                {
                    "id": "liquefaction_geology_dataset_id",
                    "required": False,
                    "description": "Liquefaction geology/susceptibility dataset id. "
                    "If not provided, liquefaction will be ignored",
                    "type": str,
                },
                {
                    "id": "use_hazard_uncertainty",
                    "required": False,
                    "description": "Use hazard uncertainty",
                    "type": bool,
                },
                {
                    "id": "num_cpu",
                    "required": False,
                    "description": "If using parallel execution, the number of cpus to request",
                    "type": int,
                },
            ],
            "input_hazards": [
                {
                    "id": "hazard",
                    "required": False,
                    "description": "Hazard object",
                    "type": ["earthquake", "hurricane", "tsunami"],
                },
            ],
            "input_datasets": [
                {
                    "id": "roads",
                    "required": True,
                    "description": "Road Inventory",
                    "type": [
                        "ergo:roadLinkTopo",
                        "incore:roads",
                        "ergo:roadLinkTopoVer2",
                    ],
                },
                {
                    "id": "dfr3_mapping_set",
                    "required": True,
                    "description": "DFR3 Mapping Set Object",
                    "type": ["incore:dfr3MappingSet"],
                },
            ],
            "output_datasets": [
                {
                    "id": "result",
                    "parent_type": "roads",
                    "description": "CSV file of road structural damage",
                    "type": "ergo:roadDamageVer3",
                },
                {
                    "id": "metadata",
                    "parent_type": "roads",
                    "description": "additional metadata in json file about applied hazard value and "
                    "fragility",
                    "type": "incore:roadDamageSupplement",
                },
            ],
        }
