单位网站建设实施方案/免费推广广告链接

用python实现的一个简单的生态模拟系统

• 红色：顶层捕食者（攻击性越强颜色越红）
• 绿色：中层消费者
• 蓝色：底层生产者
• ​动态行为：
• 底层生物主动寻找黄色食物
• 中层生物追捕底层生物
• 顶层生物猎杀中层生物
• ​统计面板：
• 实时显示各层级生物数量
• 食物数量和帧率显示

import pygame
import math
import random
from enum import Enum
from collections import defaultdict
from dataclasses import dataclass# 初始化Pygame
pygame.init()# 常量定义
SCREEN_WIDTH = 1280
SCREEN_HEIGHT = 720
FPS = 45
GRID_SIZE = 60
MAX_FOOD = 150
FOOD_SPAWN_RATE = 0.02# 基因参数结构体
@dataclass
class Genes:size: floatspeed: floatsense_range: floatmetabolism: floataggression: float# 生态位类型枚举
class TrophicLevel(Enum):TOP = 0  # 顶层捕食者（红色）MIDDLE = 1  # 中层消费者（绿色）BOTTOM = 2  # 底层生产者（蓝色）# 食物类
class Food:def __init__(self):self.x = random.uniform(0, SCREEN_WIDTH)self.y = random.uniform(0, SCREEN_HEIGHT)self.energy = random.uniform(8, 15)self.size = 3def draw(self, surface):pygame.draw.circle(surface, (255, 255, 100), (int(self.x), int(self.y)), self.size)# 生物类
class Organism:def __init__(self, x, y, level, genes=None):self.x = xself.y = yself.level = levelself.age = 0self.sick = Falseself.energy = 150.0# 基因系统if genes:self.genes = geneselse:self.genes = self._generate_genes(level)# 动态属性self.color = self._get_color()self.direction = random.uniform(0, 2 * math.pi)self.target = Nonedef _generate_genes(self, level):"""根据生态位生成初始基因"""base_genes = {TrophicLevel.TOP: (8, 2.8, 120, 0.06, 0.8),TrophicLevel.MIDDLE: (6, 2.0, 90, 0.04, 0.5),TrophicLevel.BOTTOM: (4, 1.2, 60, 0.02, 0.2)}size, speed, sense, meta, agg = base_genes[level]return Genes(size * random.uniform(0.9, 1.1),speed * random.uniform(0.9, 1.1),sense * random.uniform(0.8, 1.2),meta * random.uniform(0.9, 1.1),agg * random.uniform(0.8, 1.2))def _get_color(self):"""根据生态位和攻击性生成颜色"""base_colors = {TrophicLevel.TOP: (200, 50, 50),TrophicLevel.MIDDLE: (50, 200, 50),TrophicLevel.BOTTOM: (50, 50, 200)}r, g, b = base_colors[self.level]return (min(255, int(r * (1 + self.genes.aggression / 3))),min(255, int(g * (1 - self.genes.aggression / 3))),b)def move_towards(self, target_x, target_y):"""向目标方向移动"""dx = target_x - self.xdy = target_y - self.ytarget_angle = math.atan2(dy, dx)angle_diff = (target_angle - self.direction) % (2 * math.pi)# 平滑转向if angle_diff > math.pi:angle_diff -= 2 * math.piself.direction += angle_diff * 0.1# 前进self.x += self.genes.speed * math.cos(self.direction)self.y += self.genes.speed * math.sin(self.direction)def avoid(self, target_x, target_y):"""躲避目标"""dx = target_x - self.xdy = target_y - self.ytarget_angle = math.atan2(dy, dx)self.direction = target_angle + math.pi  # 反向def update_target(self, foods, organisms):"""根据感知选择目标"""closest_food = Noneclosest_predator = Noneclosest_prey = Nonemin_food_dist = float('inf')min_pred_dist = float('inf')min_prey_dist = float('inf')# 感知范围内检测for obj in foods + organisms:if obj is self:continuedx = obj.x - self.xdy = obj.y - self.ydist_sq = dx ** 2 + dy ** 2# 食物检测（仅底层）if (self.level == TrophicLevel.BOTTOM andisinstance(obj, Food) anddist_sq < self.genes.sense_range ** 2 anddist_sq < min_food_dist):closest_food = objmin_food_dist = dist_sq# 天敌检测if (isinstance(obj, Organism) andobj.level.value == self.level.value - 1 anddist_sq < self.genes.sense_range ** 2 anddist_sq < min_pred_dist):closest_predator = objmin_pred_dist = dist_sq# 猎物检测if (isinstance(obj, Organism) andobj.level.value == self.level.value + 1 anddist_sq < self.genes.sense_range ** 2 anddist_sq < min_prey_dist):closest_prey = objmin_prey_dist = dist_sq# 行为优先级：躲避天敌 > 寻找食物/猎物 > 随机游走if closest_predator:self.target = closest_predatorself.avoid(self.target.x, self.target.y)elif closest_prey and self.level != TrophicLevel.BOTTOM:self.target = closest_preyself.move_towards(self.target.x, self.target.y)elif closest_food and self.level == TrophicLevel.BOTTOM:self.target = closest_foodself.move_towards(self.target.x, self.target.y)else:# 随机方向微调self.direction += random.uniform(-0.3, 0.3)def check_collision(self, other):"""通用碰撞检测方法"""if isinstance(other, Organism):dx = self.x - other.xdy = self.y - other.yreturn dx ** 2 + dy ** 2 < (self.genes.size + other.genes.size) ** 2elif isinstance(other, Food):dx = self.x - other.xdy = self.y - other.yreturn dx ** 2 + dy ** 2 < (self.genes.size + other.size) ** 2return Falsedef draw(self, surface):"""绘制生物体"""pygame.draw.circle(surface,self.color,(int(self.x), int(self.y)),int(self.genes.size))def update(self, foods):self.age += 1self.energy -= self.genes.metabolismif self.sick and random.random() < 0.03:self.sick = Falseif self.level == TrophicLevel.BOTTOM:self.energy += 0.05self.energy = min(self.energy, 200)def reproduce(self):child_genes = Genes(size=max(2, self.genes.size * random.uniform(0.95, 1.05)),speed=max(0.5, self.genes.speed * random.uniform(0.9, 1.1)),sense_range=max(30, self.genes.sense_range * random.uniform(0.8, 1.2)),metabolism=max(0.01, self.genes.metabolism * random.uniform(0.95, 1.05)),aggression=min(1.0, self.genes.aggression * random.uniform(0.9, 1.1)))child = Organism(self.x + random.uniform(-20, 20),self.y + random.uniform(-20, 20),self.level,child_genes)self.energy -= 35return child# 模拟管理器
class EcosystemSimulation:def __init__(self):self.screen = pygame.display.set_mode((SCREEN_WIDTH, SCREEN_HEIGHT))self.clock = pygame.time.Clock()self.font = pygame.font.Font(None, 28)self.organisms = []self.foods = []self.init_ecosystem()def init_ecosystem(self):# 初始种群分布for _ in range(80):x = random.uniform(0, SCREEN_WIDTH)y = random.uniform(0, SCREEN_HEIGHT)level = random.choices(list(TrophicLevel),weights=[0.12, 0.25, 0.63])[0]self.organisms.append(Organism(x, y, level))# 初始食物for _ in range(80):self.foods.append(Food())def spawn_food(self):if random.random() < FOOD_SPAWN_RATE and len(self.foods) < MAX_FOOD:self.foods.append(Food())def handle_collisions(self):to_add = []to_remove = []grid = defaultdict(list)# 建立空间索引for org in self.organisms:grid_key = (int(org.x // GRID_SIZE), int(org.y // GRID_SIZE))grid[grid_key].append(org)# 处理生物行为for org in self.organisms:org.update_target(self.foods, self.organisms)# 边界反弹if org.x < 0 or org.x > SCREEN_WIDTH:org.direction = math.pi - org.directionif org.y < 0 or org.y > SCREEN_HEIGHT:org.direction = -org.directionorg.x = max(0, min(SCREEN_WIDTH, org.x))org.y = max(0, min(SCREEN_HEIGHT, org.y))# 进食检测（底层吃食物）if org.level == TrophicLevel.BOTTOM:for food in self.foods[:]:if org.check_collision(food):org.energy += food.energyself.foods.remove(food)# 捕食检测current_key = (int(org.x // GRID_SIZE), int(org.y // GRID_SIZE))for dx in (-1, 0, 1):for dy in (-1, 0, 1):neighbor_key = (current_key[0] + dx, current_key[1] + dy)for other in grid.get(neighbor_key, []):if org != other and org.check_collision(other):if org.level.value == other.level.value + 1:org.energy += other.energy * 0.6to_remove.append(other)# 繁殖与死亡for org in self.organisms[:]:org.update(self.foods)if org.energy > 130 and org.age > 18:to_add.append(org.reproduce())if org.energy <= 0 or org.age > 250:to_remove.append(org)# 更新列表self.organisms = [o for o in self.organisms if o not in to_remove]self.organisms.extend(to_add)def draw_stats(self):stats = [f"Time: {pygame.time.get_ticks() // 1000}s",f"Organisms: {len(self.organisms)}",f"  TOP: {sum(1 for o in self.organisms if o.level == TrophicLevel.TOP)}",f"  MID: {sum(1 for o in self.organisms if o.level == TrophicLevel.MIDDLE)}",f"  BOT: {sum(1 for o in self.organisms if o.level == TrophicLevel.BOTTOM)}",f"Food: {len(self.foods)}",f"FPS: {self.clock.get_fps():.1f}"]for i, text in enumerate(stats):surface = self.font.render(text, True, (240, 240, 240))self.screen.blit(surface, (10, 10 + i * 28))def run(self):running = Truewhile running:for event in pygame.event.get():if event.type == pygame.QUIT:running = False# 更新状态self.spawn_food()self.handle_collisions()# 渲染self.screen.fill((18, 18, 18))for food in self.foods:food.draw(self.screen)for org in self.organisms:org.draw(self.screen)self.draw_stats()pygame.display.flip()self.clock.tick(FPS)pygame.quit()if __name__ == "__main__":sim = EcosystemSimulation()sim.run()