use super::{MapBuilder, Map,
    TileType, Position, spawner, SHOW_MAPGEN_VISUALIZER};
use rltk::RandomNumberGenerator;
use specs::prelude::*;
use std::collections::HashMap;

pub struct CellularAutomataBuilder {
    map : Map,
    starting_position : Position,
    depth: i32,
    history: Vec<Map>,
    noise_areas : HashMap<i32, Vec<usize>>
}

impl MapBuilder for CellularAutomataBuilder {
    fn get_map(&self) -> Map {
        self.map.clone()
    }

    fn get_starting_position(&self) -> Position {
        self.starting_position.clone()
    }

    fn get_snapshot_history(&self) -> Vec<Map> {
        self.history.clone()
    }

    fn build_map(&mut self)  {
        self.build();
    }

    fn spawn_entities(&mut self, ecs : &mut World) {
        for area in self.noise_areas.iter() {
            spawner::spawn_region(ecs, area.1, self.depth);
        }
    }

    fn take_snapshot(&mut self) {
        if SHOW_MAPGEN_VISUALIZER {
            let mut snapshot = self.map.clone();
            for v in snapshot.revealed_tiles.iter_mut() {
                *v = true;
            }
            self.history.push(snapshot);
        }
    }
}

impl CellularAutomataBuilder {
    pub fn new(new_depth : i32) -> CellularAutomataBuilder {
        CellularAutomataBuilder{
            map : Map::new(new_depth),
            starting_position : Position{ x: 0, y : 0 },
            depth : new_depth,
            history: Vec::new(),
            noise_areas : HashMap::new()
        }
    }

    #[allow(clippy::map_entry)]
    fn build(&mut self) {
        let mut rng = RandomNumberGenerator::new();

        // First we completely randomize the map, setting 55% of it to be floor.
        for y in 1..self.map.height-1 {
            for x in 1..self.map.width-1 {
                let roll = rng.roll_dice(1, 100);
                let idx = self.map.xy_idx(x, y);
                if roll > 55 { self.map.tiles[idx] = TileType::Floor }
                else { self.map.tiles[idx] = TileType::Wall }
            }
        }
        self.take_snapshot();

        // Now we iteratively apply cellular automata rules
        for _i in 0..15 {
            let mut newtiles = self.map.tiles.clone();

            for y in 1..self.map.height-1 {
                for x in 1..self.map.width-1 {
                    let idx = self.map.xy_idx(x, y);
                    let mut neighbors = 0;
                    if self.map.tiles[idx - 1] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx + 1] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx - self.map.width as usize] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx + self.map.width as usize] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx - (self.map.width as usize - 1)] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx - (self.map.width as usize + 1)] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx + (self.map.width as usize - 1)] == TileType::Wall { neighbors += 1; }
                    if self.map.tiles[idx + (self.map.width as usize + 1)] == TileType::Wall { neighbors += 1; }

                    if neighbors > 4 || neighbors == 0 {
                        newtiles[idx] = TileType::Wall;
                    }
                    else {
                        newtiles[idx] = TileType::Floor;
                    }
                }
            }

            self.map.tiles = newtiles.clone();
            self.take_snapshot();
        }

        // Find a starting point; start at the middle and walk left until we find an open tile
        self.starting_position = Position{ x: self.map.width / 2, y : self.map.height / 2 };
        let mut start_idx = self.map.xy_idx(self.starting_position.x, self.starting_position.y);
        while self.map.tiles[start_idx] != TileType::Floor {
            self.starting_position.x -= 1;
            start_idx = self.map.xy_idx(self.starting_position.x, self.starting_position.y);
        }
        self.take_snapshot();

        // Find all tiles we can reach from the starting point
        let map_starts : Vec<i32> = vec![start_idx as i32];
        let dijkstra_map = rltk::DijkstraMap::new(self.map.width, self.map.height, &map_starts , &self.map, 200.0);
        let mut exit_tile = (0, 0.0f32);
        for (i, tile) in self.map.tiles.iter_mut().enumerate() {
            if *tile == TileType::Floor {
                let distance_to_start = dijkstra_map.map[i];
                // We can't get to this tile - so we'll make it a wall
                if distance_to_start == std::f32::MAX {
                    *tile = TileType::Wall;
                } else {
                    // If it is further away than our current exit candidate, move the exit
                    if distance_to_start > exit_tile.1 {
                        exit_tile.0 = i;
                        exit_tile.1 = distance_to_start;
                    }
                }
            }
        }
        self.take_snapshot();

        // Place the stairs
        self.map.tiles[exit_tile.0] = TileType::DownStairs;
        self.take_snapshot();

        // Now we build a noise map for use in spawning entities later
        let mut noise = rltk::FastNoise::seeded(rng.roll_dice(1, 65536) as u64);
        noise.set_noise_type(rltk::NoiseType::Cellular);
        noise.set_frequency(0.08);
        noise.set_cellular_distance_function(rltk::CellularDistanceFunction::Manhattan);

        for y in 1 .. self.map.height-1 {
            for x in 1 .. self.map.width-1 {
                let idx = self.map.xy_idx(x, y);
                if self.map.tiles[idx] == TileType::Floor {
                    let cell_value_f = noise.get_noise(x as f32, y as f32) * 10240.0;
                    let cell_value = cell_value_f as i32;

                    if self.noise_areas.contains_key(&cell_value) {
                        self.noise_areas.get_mut(&cell_value).unwrap().push(idx);
                    } else {
                        self.noise_areas.insert(cell_value, vec![idx]);
                    }
                }
            }
        }
    }
}
