本文主要是介绍数据可视化训练第四天(模拟投掷筛子并且统计频次),希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!
投掷一个筛子
import matplotlib.pyplot as plt
from random import randint
import numpy as npclass Die:"""模拟投掷筛子"""def __init__(self,num_sides=6):self.num_sides=num_sidesdef roll(self):return randint(1,self.num_sides)num=100000#投掷1000次
num_sides=12
results=[]
die=Die(num_sides)#创建一个6面筛子for value in range(num):results.append(die.roll())frequencies=[]for i in range(1,num_sides+1):frequencies.append(results.count(i))fig,ax =plt.subplots()
x_values=list(range(1,num_sides+1))
p=ax.bar(x_values,frequencies,label='frequency')ax.set_title("The frequency of chromophores")
ax.set_xlabel('surface')
ax.set_ylabel('quanity')
#设置bar的格式
ax.bar_label(p,label_type='edge')ax.legend()plt.show()
投掷两个筛子
import matplotlib.pyplot as plt
from random import randint
import numpy as npclass Die:"""模拟投掷筛子"""def __init__(self,num_sides=6):self.num_sides=num_sidesdef roll(self):return randint(1,self.num_sides)num=100000#投掷1000次
num_sides=6
results=[]
die=Die(num_sides)#创建一个6面筛子
die1=Die(num_sides)for value in range(num):results.append(die.roll()+die1.roll())frequencies=[]for i in range(1,num_sides*2+1):frequencies.append(results.count(i))#绘图
fig,ax =plt.subplots()
x_values=list(range(1,num_sides*2+1))
p=ax.bar(x_values,frequencies,label='frequency')ax.set_title("The frequency of chromophores")
ax.set_xlabel('surface')
ax.set_ylabel('quanity')
ax.set_xticks(x_values)
#设置bar的格式
ax.bar_label(p,label_type='edge')ax.legend()plt.show()
重构代码
import matplotlib.pyplot as plt
from random import randint
import numpy as npclass Die:"""模拟投掷筛子"""def __init__(self,num_sides=[6]):self.num_sides=num_sidesself.results=[]def roll(self):"""返回投掷筛子的总点数"""result=0for value in self.num_sides:result+=randint(1,value)return resultdef roll_many(self,num=1000):"""投掷多次返回每次投掷的结果"""for value in range(num):self.results.append(self.roll())return self.resultsdef get_sum(self):"""返回点数的最大和"""sum_=0for value in self.num_sides:sum_+=valuereturn sum_def get_frenquencies(self):"""获得每个点数出现的频次"""frequencise=[]sum_=self.get_sum()for i in range(1,sum_+1):frequency=self.results.count(i)frequencise.append(frequency)return frequencisenum=100000#投掷1000次
#可以投掷任意数量的筛子
num_sides=[6,6,2]
die=Die(num_sides=num_sides)
results=die.roll_many(num)
frequencise=die.get_frenquencies()
print(frequencise)#绘图
fig,ax =plt.subplots()
x_values=list(range(1,die.get_sum()+1))
p=ax.bar(x_values,frequencise,label='frequency')ax.set_title("The frequency of chromophores")
ax.set_xlabel('surface')
ax.set_ylabel('quanity')
ax.set_xticks(x_values)
#设置bar的格式
ax.bar_label(p,label_type='edge')ax.legend()plt.show()
这篇关于数据可视化训练第四天(模拟投掷筛子并且统计频次)的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!