Use Dijkstra algorithm to describe monster paths
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@ -17,20 +17,15 @@ class Monster(FightingEntity):
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target = entity
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break
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if target:
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# A Dijkstra algorithm has ran that targets the player.
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# With that way, monsters can simply follow the path.
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# If they can't move and they are already close to the player,
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# They hit.
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if target and (self.y, self.x) in target.paths:
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# Move to target player
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y, x = self.vector(target)
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if abs(y) > abs(x): # Move vertically
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if y > 0:
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self.move_down()
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else:
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self.move_up()
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else: # Move horizontally
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if x > 0:
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self.move_right()
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else:
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self.move_left()
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if self.distance_squared(target) <= 1:
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next_y, next_x = target.paths[(self.y, self.x)]
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moved = self.check_move(next_y, next_x, True)
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if not moved and self.distance_squared(target) <= 1:
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self.hit(target)
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else:
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for _ in range(100):
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@ -1,4 +1,5 @@
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from random import randint
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from typing import Dict, Tuple
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from ..interfaces import FightingEntity
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@ -14,6 +15,7 @@ class Player(FightingEntity):
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level: int = 1
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current_xp: int = 0
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max_xp: int = 10
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paths: Dict[Tuple[int, int], Tuple[int, int]]
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def move(self, y: int, x: int) -> None:
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"""
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@ -22,6 +24,7 @@ class Player(FightingEntity):
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super().move(y, x)
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self.map.currenty = y
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self.map.currentx = x
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self.recalculate_paths()
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def level_up(self) -> None:
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"""
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@ -61,3 +64,26 @@ class Player(FightingEntity):
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self.add_xp(randint(3, 7))
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return True
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return super().check_move(y, x, move_if_possible)
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def recalculate_paths(self) -> None:
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"""
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Use Dijkstra algorithm to calculate best paths
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for monsters to go to the player.
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"""
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queue = [(self.y, self.x)]
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visited = []
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predecessors = {}
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while queue:
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y, x = queue.pop(0)
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visited.append((y, x))
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for diff_y, diff_x in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
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new_y, new_x = y + diff_y, x + diff_x
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if not 0 <= new_y < self.map.height or \
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not 0 <= new_x < self.map.width or \
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not self.map.tiles[y][x].can_walk() or \
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(new_y, new_x) in visited or \
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(new_y, new_x) in queue:
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continue
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predecessors[(new_y, new_x)] = (y, x)
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queue.append((new_y, new_x))
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self.paths = predecessors
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