New pathfinding that avoids most of the mobs getting stuck, closes #35

squirrelbattle/entities/monsters.py

@@ -43,11 +43,14 @@ class Monster(FightingEntity):
         # If they can't move and they are already close to the player,
         # They hit.
         if target and (self.y, self.x) in target.paths:
-            # Move to target player
-            next_y, next_x = target.paths[(self.y, self.x)]
-            moved = self.check_move(next_y, next_x, True)
-            if not moved and self.distance_squared(target) <= 1:
-                self.map.logs.add_message(self.hit(target))
+            # Move to target player by choosing the best avaliable path
+            for next_y, next_x in target.paths[(self.y, self.x)]:
+                moved = self.check_move(next_y, next_x, True)
+                if moved:
+                    break
+                if self.distance_squared(target) <= 1:
+                    self.map.logs.add_message(self.hit(target))
+                    break
         else:
             # Move in a random direction
             # If the direction is not available, try another one

squirrelbattle/entities/player.py

@@ -1,9 +1,10 @@
 # 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
-from queue import PriorityQueue
 
 from ..interfaces import FightingEntity
 
@@ -93,32 +94,52 @@ class Player(FightingEntity):
 
     def recalculate_paths(self, max_distance: int = 8) -> None:
         """
-        Use Dijkstra algorithm to calculate best paths
-        for monsters to go to the player.
+        Use Dijkstra algorithm to calculate best paths for monsters to go to
+        the player. Actually, the paths are computed for each tile adjacent to
+        the player then for each step the monsters use the best path avaliable.
         """
-        queue = PriorityQueue()
-        queue.put((0, (self.y, self.x)))
-        visited = []
-        distances = {(self.y, self.x): 0}
-        predecessors = {}
-        while not queue.empty():
-            dist, (y, x) = queue.get()
-            if dist >= max_distance or (y,x) in visited:
+        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
-            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():
+            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
-                new_distance = dist + 1
-                if not (new_y, new_x) in distances or \
-                        distances[(new_y, new_x)] > new_distance:
-                    predecessors[(new_y, new_x)] = (y, x)
-                    distances[(new_y, new_x)] = new_distance
-                    queue.put((new_distance, (new_y, new_x)))
-        self.paths = predecessors
+                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]):
+            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:
         """