Being able to calculate paths is now a property of fighting entities.

squirrelbattle/entities/player.py

@@ -1,8 +1,6 @@
 # Copyright (C) 2020 by ÿnérant, eichhornchen, nicomarg, charlse
 # SPDX-License-Identifier: GPL-3.0-or-later
 
-from functools import reduce
-from queue import PriorityQueue
 from random import randint
 from typing import Dict, Tuple
 
@@ -15,7 +13,6 @@ class Player(InventoryHolder, FightingEntity):
     """
     current_xp: int = 0
     max_xp: int = 10
-    paths: Dict[Tuple[int, int], Tuple[int, int]]
 
     def __init__(self, name: str = "player", maxhealth: int = 20,
                  strength: int = 5, intelligence: int = 1, charisma: int = 1,
@@ -87,55 +84,6 @@ class Player(InventoryHolder, FightingEntity):
                     entity.hold(self)
         return super().check_move(y, x, move_if_possible)
 
-    def recalculate_paths(self, max_distance: int = 8) -> None:
-        """
-        Uses Dijkstra algorithm to calculate best paths for monsters to go to
-        the player.
-        """
-        distances = []
-        predecessors = []
-        # four Dijkstras, one for each adjacent tile
-        for dir_y, dir_x in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
-            queue = PriorityQueue()
-            new_y, new_x = self.y + dir_y, self.x + dir_x
-            if not 0 <= new_y < self.map.height or \
-                    not 0 <= new_x < self.map.width or \
-                    not self.map.tiles[new_y][new_x].can_walk():
-                continue
-            queue.put(((1, 0), (new_y, new_x)))
-            visited = [(self.y, self.x)]
-            distances.append({(self.y, self.x): (0, 0), (new_y, new_x): (1, 0)})
-            predecessors.append({(new_y, new_x): (self.y, self.x)})
-            while not queue.empty():
-                dist, (y, x) = queue.get()
-                if dist[0] >= max_distance or (y, x) in visited:
-                    continue
-                visited.append((y, x))
-                for diff_y, diff_x in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
-                    new_y, new_x = y + diff_y, x + diff_x
-                    if not 0 <= new_y < self.map.height or \
-                            not 0 <= new_x < self.map.width or \
-                            not self.map.tiles[new_y][new_x].can_walk():
-                        continue
-                    new_distance = (dist[0] + 1,
-                                    dist[1] + (not self.map.is_free(y, x)))
-                    if not (new_y, new_x) in distances[-1] or \
-                            distances[-1][(new_y, new_x)] > new_distance:
-                        predecessors[-1][(new_y, new_x)] = (y, x)
-                        distances[-1][(new_y, new_x)] = new_distance
-                        queue.put((new_distance, (new_y, new_x)))
-        # For each tile that is reached by at least one Dijkstra, sort the
-        # different paths by distance to the player. For the technical bits :
-        # The reduce function is a fold starting on the first element of the
-        # iterable, and we associate the points to their distance, sort
-        # along the distance, then only keep the points.
-        self.paths = {}
-        for y, x in reduce(set.union,
-                           [set(p.keys()) for p in predecessors], set()):
-            self.paths[(y, x)] = [p for d, p in sorted(
-                [(distances[i][(y, x)], predecessors[i][(y, x)])
-                 for i in range(len(distances)) if (y, x) in predecessors[i]])]
-
     def save_state(self) -> dict:
         """
         Saves the state of the entity into a dictionary