154 lines
6.4 KiB
Python
154 lines
6.4 KiB
Python
# Copyright (C) 2020 by ÿnérant, eichhornchen, nicomarg, charlse
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# SPDX-License-Identifier: GPL-3.0-or-later
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from functools import reduce
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from queue import PriorityQueue
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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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class Player(FightingEntity):
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"""
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The class of the player
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"""
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current_xp: int = 0
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max_xp: int = 10
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inventory: list
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paths: Dict[Tuple[int, int], Tuple[int, int]]
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def __init__(self, name: str = "player", maxhealth: int = 20,
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strength: int = 5, intelligence: int = 1, charisma: int = 1,
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dexterity: int = 1, constitution: int = 1, level: int = 1,
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current_xp: int = 0, max_xp: int = 10, inventory: list = None,
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*args, **kwargs) \
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-> None:
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super().__init__(name=name, maxhealth=maxhealth, strength=strength,
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intelligence=intelligence, charisma=charisma,
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dexterity=dexterity, constitution=constitution,
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level=level, *args, **kwargs)
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self.current_xp = current_xp
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self.max_xp = max_xp
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self.inventory = inventory if inventory else list()
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for i in range(len(self.inventory)):
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if isinstance(self.inventory[i], dict):
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entity_classes = self.get_all_entity_classes_in_a_dict()
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item_class = entity_classes[self.inventory[i]["type"]]
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self.inventory[i] = item_class(**self.inventory[i])
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self.paths = dict()
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def move(self, y: int, x: int) -> None:
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"""
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Moves the view of the map (the point on which the camera is centered)
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according to the moves of the player.
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"""
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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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Add levels to the player as much as it is possible.
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"""
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while self.current_xp > self.max_xp:
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self.level += 1
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self.current_xp -= self.max_xp
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self.max_xp = self.level * 10
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self.health = self.maxhealth
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self.strength = self.strength + 1
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# TODO Remove it, that's only fun
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self.map.spawn_random_entities(randint(3 * self.level,
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10 * self.level))
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def add_xp(self, xp: int) -> None:
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"""
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Add some experience to the player.
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If the required amount is reached, level up.
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"""
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self.current_xp += xp
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self.level_up()
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# noinspection PyTypeChecker,PyUnresolvedReferences
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def check_move(self, y: int, x: int, move_if_possible: bool = False) \
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-> bool:
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"""
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If the player tries to move but a fighting entity is there,
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the player fights this entity.
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If the entity dies, the player is rewarded with some XP
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"""
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# Don't move if we are dead
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if self.dead:
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return False
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for entity in self.map.entities:
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if entity.y == y and entity.x == x:
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if entity.is_fighting_entity():
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self.map.logs.add_message(self.hit(entity))
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if entity.dead:
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self.add_xp(randint(3, 7))
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return True
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elif entity.is_item():
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entity.hold(self)
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return super().check_move(y, x, move_if_possible)
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def recalculate_paths(self, max_distance: int = 8) -> None:
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"""
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Use Dijkstra algorithm to calculate best paths for monsters to go to
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the player. Actually, the paths are computed for each tile adjacent to
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the player then for each step the monsters use the best path avaliable.
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"""
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distances = []
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predecessors = []
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# four Dijkstras, one for each adjacent tile
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for dir_y, dir_x in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
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queue = PriorityQueue()
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new_y, new_x = self.y + dir_y, self.x + dir_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[new_y][new_x].can_walk():
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continue
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queue.put(((1, 0), (new_y, new_x)))
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visited = [(self.y, self.x)]
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distances.append({(self.y, self.x): (0, 0), (new_y, new_x): (1, 0)})
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predecessors.append({(new_y, new_x): (self.y, self.x)})
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while not queue.empty():
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dist, (y, x) = queue.get()
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if dist[0] >= max_distance or (y, x) in visited:
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continue
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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[new_y][new_x].can_walk():
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continue
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new_distance = (dist[0] + 1,
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dist[1] + (not self.map.is_free(y, x)))
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if not (new_y, new_x) in distances[-1] or \
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distances[-1][(new_y, new_x)] > new_distance:
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predecessors[-1][(new_y, new_x)] = (y, x)
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distances[-1][(new_y, new_x)] = new_distance
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queue.put((new_distance, (new_y, new_x)))
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# For each tile that is reached by at least one Dijkstra, sort the
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# different paths by distance to the player. For the technical bits :
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# The reduce function is a fold starting on the first element of the
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# iterable, and we associate the points to their distance, sort
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# along the distance, then only keep the points.
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self.paths = {}
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for y, x in reduce(set.union,
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[set(p.keys()) for p in predecessors], set()):
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self.paths[(y, x)] = [p for d, p in sorted(
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[(distances[i][(y, x)], predecessors[i][(y, x)])
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for i in range(len(distances)) if (y, x) in predecessors[i]])]
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def save_state(self) -> dict:
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"""
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Saves the state of the entity into a dictionary
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"""
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d = super().save_state()
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d["current_xp"] = self.current_xp
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d["max_xp"] = self.max_xp
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d["inventory"] = [item.save_state() for item in self.inventory]
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return d
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