import os
import random
import time

import networkx as nx
import numpy as np

import alfred_utils.gen.constants as constants
from alfred_utils.gen.utils import game_util

MAX_WEIGHT_IN_GRAPH = 1e5
PRED_WEIGHT_THRESH = 10
EPSILON = 1e-4

# Direction: 0: north, 1: east, 2: south, 3: west


class Graph(object):
    def __init__(self, use_gt=False, construct_graph=True, scene_id=None, debug=False):
        t_start = time.time()

        self.construct_graph = construct_graph
        '''
        event = env.step({'action': 'GetReachablePositions'})
        new_reachable_positions = event.metadata['reachablePositions']
        points = []
        for point in new_reachable_positions:
            xx = int(point['x'] / constants.AGENT_STEP_SIZE)
            yy = int(point['z'] / constants.AGENT_STEP_SIZE)
            points.append([xx, yy])

        self.points = np.array(points, dtype=np.int32)
        self.points = self.points[np.lexsort(self.points.T)]
        '''

        self.scene_id = scene_id
        self.points = np.load(os.path.join(
            os.path.dirname(__file__),
            os.pardir,
            'layouts',
            'FloorPlan%s-layout.npy' % self.scene_id))
        self.points /= constants.AGENT_STEP_SIZE
        self.points = np.round(self.points).astype(np.int32)
        self.xMin = self.points[:, 0].min() - constants.SCENE_PADDING * 2
        self.yMin = self.points[:, 1].min() - constants.SCENE_PADDING * 2
        self.xMax = self.points[:, 0].max() + constants.SCENE_PADDING * 2
        self.yMax = self.points[:, 1].max() + constants.SCENE_PADDING * 2
        self.memory = np.zeros((self.yMax - self.yMin + 1, self.xMax - self.xMin + 1), dtype=np.float32)
        self.gt_graph = None
        self.shortest_paths = {}
        self.shortest_paths_unweighted = {}
        self.use_gt = use_gt
        self.impossible_spots = set()
        self.updated_weights = {}
        self.prev_navigable_locations = None

        if self.use_gt:
            self.memory[:] = MAX_WEIGHT_IN_GRAPH
            self.memory[self.points[:, 1] - self.yMin, self.points[:, 0] - self.xMin] = 1 + EPSILON
        else:
            self.memory[:] = 1
            self.memory[:, :int(constants.SCENE_PADDING * 1.5)] = MAX_WEIGHT_IN_GRAPH
            self.memory[:int(constants.SCENE_PADDING * 1.5), :] = MAX_WEIGHT_IN_GRAPH
            self.memory[:, -int(constants.SCENE_PADDING * 1.5):] = MAX_WEIGHT_IN_GRAPH
            self.memory[-int(constants.SCENE_PADDING * 1.5):, :] = MAX_WEIGHT_IN_GRAPH

        if self.gt_graph is None:
            self.gt_graph = nx.DiGraph()
            if self.construct_graph:
                for yy in np.arange(self.yMin, self.yMax + 1):
                    for xx in np.arange(self.xMin, self.xMax + 1):
                        weight = self.memory[yy - self.yMin, xx - self.xMin]
                        for direction in range(4):
                            node = (xx, yy, direction)
                            back_direction = (direction + 2) % 4
                            back_node = (xx, yy, back_direction)
                            self.gt_graph.add_edge(node, (xx, yy, (direction + 1) % 4), weight=1)
                            self.gt_graph.add_edge(node, (xx, yy, (direction - 1) % 4), weight=1)
                            forward_node = None
                            if direction == 0 and yy != self.yMax:
                                forward_node = (xx, yy + 1, back_direction)
                            elif direction == 1 and xx != self.xMax:
                                forward_node = (xx + 1, yy, back_direction)
                            elif direction == 2 and yy != self.yMin:
                                forward_node = (xx, yy - 1, back_direction)
                            elif direction == 3 and xx != self.xMin:
                                forward_node = (xx - 1, yy, back_direction)
                            if forward_node is not None:
                                self.gt_graph.add_edge(forward_node, back_node, weight=weight)

        self.initial_memory = self.memory.copy()
        self.debug = debug
        if self.debug:
            print('Graph construction time %.3f' % (time.time() - t_start))

    def clear(self):
        self.shortest_paths = {}
        self.shortest_paths_unweighted = {}
        self.impossible_spots = set()
        self.prev_navigable_locations = None

        if self.use_gt:
            self.memory[:] = self.initial_memory
        else:
            self.memory[:] = 1
            self.memory[:, :int(constants.SCENE_PADDING * 1.5)] = MAX_WEIGHT_IN_GRAPH
            self.memory[:int(constants.SCENE_PADDING * 1.5), :] = MAX_WEIGHT_IN_GRAPH
            self.memory[:, -int(constants.SCENE_PADDING * 1.5):] = MAX_WEIGHT_IN_GRAPH
            self.memory[-int(constants.SCENE_PADDING * 1.5):, :] = MAX_WEIGHT_IN_GRAPH

        if self.construct_graph:
            for (nodea, nodeb), original_weight in self.updated_weights.items():
                self.gt_graph[nodea][nodeb]['weight'] = original_weight
        self.updated_weights = {}

    @property
    def image(self):
        return self.memory[:, :].astype(np.uint8)

    def check_graph_memory_correspondence(self):
        # graph sanity check
        if self.construct_graph:
            for yy in np.arange(self.yMin, self.yMax + 1):
                for xx in np.arange(self.xMin, self.xMax + 1):
                    for direction in range(4):
                        back_direction = (direction + 2) % 4
                        back_node = (xx, yy, back_direction)
                        if direction == 0 and yy != self.yMax:
                            assert(abs(self.gt_graph[(xx, yy + 1, back_direction)][back_node]['weight'] -
                                       self.memory[int(yy - self.yMin), int(xx - self.xMin)]) < 0.0001)
                        elif direction == 1 and xx != self.xMax:
                            assert(abs(self.gt_graph[(xx + 1, yy, back_direction)][back_node]['weight'] -
                                       self.memory[int(yy - self.yMin), int(xx - self.xMin)]) < 0.0001)
                        elif direction == 2 and yy != self.yMin:
                            assert(abs(self.gt_graph[(xx, yy - 1, back_direction)][back_node]['weight'] -
                                       self.memory[int(yy - self.yMin), int(xx - self.xMin)]) < 0.0001)
                        elif direction == 3 and xx != self.xMin:
                            assert(abs(self.gt_graph[(xx - 1, yy, back_direction)][back_node]['weight'] -
                                       self.memory[int(yy - self.yMin), int(xx - self.xMin)]) < 0.0001)
            print('\t\t\tgraph tested successfully')

    def update_graph(self, graph_patch, pose):
        graph_patch, curr_val = graph_patch
        curr_val = np.array(curr_val)
        # Rotate the array to get its global coordinate frame orientation.
        rotation = int(pose[2])
        assert(rotation in {0, 1, 2, 3}), 'rotation was %s' % str(rotation)

        if rotation != 0:
            graph_patch = np.rot90(graph_patch, rotation)
        # Shift offsets to global coordinate frame.
        if rotation == 0:
            x_min = pose[0] - int(constants.STEPS_AHEAD / 2)
            y_min = pose[1] + 1
        elif rotation == 1:
            x_min = pose[0] + 1
            y_min = pose[1] - int(constants.STEPS_AHEAD / 2)
        elif rotation == 2:
            x_min = pose[0] - int(constants.STEPS_AHEAD / 2)
            y_min = pose[1] - constants.STEPS_AHEAD
        elif rotation == 3:
            x_min = pose[0] - constants.STEPS_AHEAD
            y_min = pose[1] - int(constants.STEPS_AHEAD / 2)
        else:
            raise Exception('Invalid pose direction')
        if self.construct_graph:
            for yi, yy in enumerate(range(y_min, y_min + constants.STEPS_AHEAD)):
                for xi, xx in enumerate(range(x_min, x_min + constants.STEPS_AHEAD)):
                    self.update_weight(xx, yy, graph_patch[yi, xi, 0])
            self.update_weight(pose[0], pose[1], curr_val[0])

    def get_graph_patch(self, pose):
        rotation = int(pose[2])
        assert(rotation in {0, 1, 2, 3})

        if rotation == 0:
            x_min = pose[0] - int(constants.STEPS_AHEAD / 2)
            y_min = pose[1] + 1
        elif rotation == 1:
            x_min = pose[0] + 1
            y_min = pose[1] - int(constants.STEPS_AHEAD / 2)
        elif rotation == 2:
            x_min = pose[0] - int(constants.STEPS_AHEAD / 2)
            y_min = pose[1] - constants.STEPS_AHEAD
        elif rotation == 3:
            x_min = pose[0] - constants.STEPS_AHEAD
            y_min = pose[1] - int(constants.STEPS_AHEAD / 2)
        else:
            raise Exception('Invalid pose direction')
        x_min -= self.xMin
        y_min -= self.yMin

        graph_patch = self.memory[y_min:y_min + constants.STEPS_AHEAD,
                                  x_min:x_min + constants.STEPS_AHEAD].copy()

        if rotation != 0:
            graph_patch = np.rot90(graph_patch, -rotation)

        return graph_patch, self.memory[pose[1] - self.yMin, pose[0] - self.xMin].copy()

    def add_impossible_spot(self, spot):
        self.update_weight(spot[0], spot[1], MAX_WEIGHT_IN_GRAPH)
        self.impossible_spots.add(spot)

    def update_weight(self, xx, yy, weight):
        if (xx, yy) not in self.impossible_spots:
            if self.construct_graph:
                for direction in range(4):
                    node = (xx, yy, direction)
                    self.update_edge(node, weight)
            self.memory[yy - self.yMin, xx - self.xMin] = weight
            self.shortest_paths = {}

    def update_edge(self, pose, weight):
        rotation = int(pose[2])
        assert(rotation in {0, 1, 2, 3})

        (xx, yy, direction) = pose
        back_direction = (direction + 2) % 4
        back_pose = (xx, yy, back_direction)
        if direction == 0 and yy != self.yMax:
            forward_pose = (xx, yy + 1, back_direction)
        elif direction == 1 and xx != self.xMax:
            forward_pose = (xx + 1, yy, back_direction)
        elif direction == 2 and yy != self.yMin:
            forward_pose = (xx, yy - 1, back_direction)
        elif direction == 3 and xx != self.xMin:
            forward_pose = (xx - 1, yy, back_direction)
        else:
            raise NotImplementedError('Unknown direction')
        if (forward_pose, back_pose) not in self.updated_weights:
            self.updated_weights[(forward_pose, back_pose)] = self.gt_graph[forward_pose][back_pose]['weight']
        self.gt_graph[forward_pose][back_pose]['weight'] = weight

    def get_shortest_path(self, pose, goal_pose):
        assert(pose[2] in {0, 1, 2, 3})
        assert(goal_pose[2] in {0, 1, 2, 3})

        # Store horizons for possible final look correction.
        curr_horizon = int(pose[3])
        goal_horizon = int(goal_pose[3])

        pose = tuple(int(pp) for pp in pose[:3])
        goal_pose = tuple(int(pp) for pp in goal_pose[:3])

        try:
            assert(self.construct_graph), 'Graph was not constructed, cannot get shortest path.'
            assert(pose in self.gt_graph), 'start point not in graph'
            assert(goal_pose in self.gt_graph), 'start point not in graph'
        except Exception as ex:
            print('pose', pose, 'goal_pose', goal_pose)
            raise ex

        if (pose, goal_pose) not in self.shortest_paths:
            path = nx.astar_path(self.gt_graph, pose, goal_pose,
                                 heuristic=lambda nodea, nodeb: (abs(nodea[0] - nodeb[0]) + abs(nodea[1] - nodeb[1]) +
                                                                 abs(nodea[2] - nodeb[2])),
                                 weight='weight')
            for ii, pp in enumerate(path):
                self.shortest_paths[(pp, goal_pose)] = path[ii:]
        path = self.shortest_paths[(pose, goal_pose)]
        max_point = 1
        for ii in range(len(path) - 1):
            weight = self.gt_graph[path[ii]][path[ii + 1]]['weight']
            if path[ii][:2] != path[ii + 1][:2]:
                if abs(self.memory[path[ii + 1][1] - self.yMin, path[ii + 1][0] - self.xMin] - weight) > 0.001:
                    print(self.memory[path[ii + 1][1] - self.yMin, path[ii + 1][0] - self.xMin], weight)
                    raise AssertionError('weights do not match')
            if weight >= PRED_WEIGHT_THRESH:
                break
            max_point += 1
        path = path[:max_point]

        actions = [Graph.get_plan_move(path[ii], path[ii + 1]) for ii in range(len(path) - 1)]
        Graph.horizon_adjust(actions, path, curr_horizon, goal_horizon)

        return actions, path

    def get_shortest_path_unweighted(self, pose, goal_pose):
        assert(pose[2] in {0, 1, 2, 3})
        assert(goal_pose[2] in {0, 1, 2, 3})
        curr_horizon = int(pose[3])
        goal_horizon = int(goal_pose[3])
        pose = tuple(int(pp) for pp in pose[:3])
        goal_pose = tuple(int(pp) for pp in goal_pose[:3])

        try:
            assert(self.construct_graph), 'Graph was not constructed, cannot get shortest path.'
            assert(pose in self.gt_graph), 'start point not in graph'
            assert(goal_pose in self.gt_graph), 'start point not in graph'
        except Exception as ex:
            print('pose', pose, 'goal_pose', goal_pose)
            raise ex

        if (pose, goal_pose) not in self.shortest_paths_unweighted:
            # TODO: swap this out for astar (might be get_shortest_path tho) and update heuristic to account for
            # TODO: actual number of turns.
            path = nx.shortest_path(self.gt_graph, pose, goal_pose)
            for ii, pp in enumerate(path):
                self.shortest_paths_unweighted[(pp, goal_pose)] = path[ii:]
        path = self.shortest_paths_unweighted[(pose, goal_pose)]

        actions = [Graph.get_plan_move(path[ii], path[ii + 1]) for ii in range(len(path) - 1)]
        Graph.horizon_adjust(actions, path, curr_horizon, goal_horizon)
        return actions, path

    def update_map(self, env):
        event = env.step({'action': 'GetReachablePositions'})
        new_reachable_positions = event.metadata['reachablePositions']
        new_memory = np.full_like(self.memory[:, :], MAX_WEIGHT_IN_GRAPH)
        if self.construct_graph:
            for point in new_reachable_positions:
                xx = int(point['x'] / constants.AGENT_STEP_SIZE)
                yy = int(point['z'] / constants.AGENT_STEP_SIZE)
                new_memory[yy - self.yMin, xx - self.xMin] = 1 + EPSILON
        changed_locations = np.where(np.logical_xor(self.memory[:, :] == MAX_WEIGHT_IN_GRAPH, new_memory == MAX_WEIGHT_IN_GRAPH))
        for location in zip(*changed_locations):
            self.update_weight(location[1] + self.xMin, location[0] + self.yMin, 1 + EPSILON)

    def navigate_to_goal(self, game_state, start_pose, end_pose):
        # Look down

        self.update_map(game_state.env)

        start_angle = start_pose[3]
        if start_angle > 180:
            start_angle -= 360
        if start_angle != 45:  # pitch angle
            # Perform initial tilt to get to 45 degrees.
            tilt_pose = [pp for pp in start_pose]
            tilt_pose[3] = 45
            tilt_actions, _ = self.get_shortest_path(start_pose, tilt_pose)
            for action in tilt_actions:
                game_state.step(action)
            start_pose = tuple(tilt_pose)

        actions, path = self.get_shortest_path(start_pose, end_pose)
        while len(actions) > 0:
            for ii, (action, pose) in enumerate(zip(actions, path)):
                game_state.step(action)
                event = game_state.env.last_event
                last_action_success = event.metadata['lastActionSuccess']

                if not last_action_success:
                    # Can't traverse here, make sure the weight is correct.
                    if action['action'].startswith('Look') or action['action'].startswith('Rotate'):
                        raise Exception('Look action failed %s' % event.metadata['errorMessage'])
                    self.add_impossible_spot(path[ii + 1])
                    break
            pose = game_util.get_pose(event)
            actions, path = self.get_shortest_path(pose, end_pose)
        print('nav done')

    @staticmethod
    def get_plan_move(pose0, pose1):
        if (pose0[2] + 1) % 4 == pose1[2]:
            action = {'action': 'RotateRight'}
        elif (pose0[2] - 1) % 4 == pose1[2]:
            action = {'action': 'RotateLeft'}
        else:
            action = {'action': 'MoveAhead', 'moveMagnitude': constants.AGENT_STEP_SIZE}
        return action

    @staticmethod
    def horizon_adjust(actions, path, hor0, hor1):
        if hor0 < hor1:
            for _ in range((hor1 - hor0) // constants.AGENT_HORIZON_ADJ):
                actions.append({'action': 'LookDown'})
                path.append(path[-1])
        elif hor0 > hor1:
            for _ in range((hor0 - hor1) // constants.AGENT_HORIZON_ADJ):
                actions.append({'action': 'LookUp',})
                path.append(path[-1])


if __name__ == '__main__':
    # Test graphs
    env = game_util.create_env()
    scenes = sorted(constants.TRAIN_SCENE_NUMBERS + constants.TEST_SCENE_NUMBERS)
    while True:
        scene_id = random.choice(scenes)
        graph = Graph(use_gt=True, construct_graph=True, scene_id=scene_id)
        game_util.reset(env, scene_id,
                        render_image=False,
                        render_depth_image=False,
                        render_class_image=False,
                        render_object_image=False)
        num_points = len(graph.points)
        point1 = random.randint(0, num_points - 1)
        point2 = point1
        while point2 == point1:
            point2 = random.randint(0, num_points)
        point1 = graph.points[point1]
        point2 = graph.points[point2]
        start_pose = (point1[0], point1[1], random.randint(0, 3), 0)
        end_pose = (point2[0], point2[1], random.randint(0, 3), 0)
        agent_height = env.last_event.metadata['agent']['position']['y']
        action = {'action': 'TeleportFull',
                  'x': start_pose[0] * constants.AGENT_STEP_SIZE,
                  'y': agent_height,
                  'z': start_pose[1] * constants.AGENT_STEP_SIZE,
                  'rotateOnTeleport': True,
                  'rotation': start_pose[2],
                  'horizon': start_pose[3],
                  }
        env.step(action)
        actions, path = graph.get_shortest_path(start_pose, end_pose)
        while len(actions) > 0:
            for ii, (action, pose) in enumerate(zip(actions, path)):
                env.step(action)
                event = env.last_event
                last_action_success = event.metadata['lastActionSuccess']

                if not last_action_success:
                    # Can't traverse here, make sure the weight is correct.
                    if action['action'].startswith('Look') or action['action'].startswith('Rotate'):
                        raise Exception('Look action failed %s' % event.metadata['errorMessage'])
                    graph.add_impossible_spot(path[ii + 1])
                    break
            pose = game_util.get_pose(event)
            actions, path = graph.get_shortest_path(pose, end_pose)
        if end_pose == pose:
            print('made it')
        else:
            print('could not make it :(')

