【隔离中的代码(3)】上帝视角计算生物最佳生存温度并绘图

实现要求：

• 在前一天实现功能的基础上，利用‘繁衍’下一代的记忆功能，逐渐逼近生存的最优温度条件；
• 绘制曲线尝试描述生物数量随温度变化的改变；

完整代码：

# ！usr/bin/env python3
# -*- coding:utf-8 -*-

"""
@author : 24nemo
 @date  : 2022年03月16日
"""

import random

import matplotlib.pyplot as plt


class Creature(object):
    def __init__(self):
        self.downTemp = random.randint(0, 85)
        self.upTemp = self.downTemp + 15
        self.age = 0
        self.live = True

    def born(self, downTemp):
        self.downTemp = random.randint(downTemp - 10, downTemp + 10)
        self.upTemp = self.downTemp + 15

    def time_lapse(self, resource, currentTemp):
        if currentTemp > self.upTemp or currentTemp < self.downTemp:
            self.live = False
            return 0, None

        if self.age >= 10:
            self.live = False
            return 0, None

        if resource > 0:
            son_1 = Creature()
            son_1.born(self.downTemp)
            return 2, son_1

        else:
            return 1, None

    def getPreferTemp(self):
        return (self.downTemp + self.upTemp) / 2


def time_lapse(currentTemp, epoch_set):
    resource = 10000 - len(num_creature)
    for epoch in range(epoch_set):
        new_son = []
        for i in num_creature:
            state, son = i.time_lapse(resource, currentTemp)
            if state == 2:
                new_son.append(son)
                resource -= 1
            else:
                pass
        count_dead = 0
        for i in range(len(num_creature) - 1, 0, -1):
            if num_creature[i].live == False:
                del num_creature[i]
                count_dead += 1
        dead_num.append(count_dead)
        for i in new_son:
            num_creature.append(i)

    print(len(num_creature))
    sum = 0
    for i in num_creature:
        sum = sum + i.getPreferTemp()

    sum = sum / len(num_creature)
    preferTemp.append(sum)
    print(sum)


num_creature = []
for i in range(5000):
    num_creature.append(Creature())

dead_num = []
preferTemp = []

xlabel = range(60)
linearTemp = []
for i in range(30, 70):
    time_lapse(i, 2)
    linearTemp.append(i)

for iii in range(20):
    time_lapse(69, 2)
    linearTemp.append(69)

plt.plot(xlabel, preferTemp)
plt.plot(xlabel, linearTemp)
plt.show()

结果展示：

在这里插入图片描述

我的理解还是非常滞后，完全跟不上旭哥的思路，还得干