7. 伪随机数的生成

虽然Python内置的random模块中可以生成随机数，但是每次只能随机生成一个随机数，但是每次只能随机生成一个数字，而且随机数的种类也不够丰富。

这里不写完了，书本72页。

import seaborn as snsimport matplotlib.pyplot as pltfrom scipy import statsimport numpy as np# 生成各种正态分布随机数np.random.seed(1234)rn1 = np.random.normal(loc = 0, scale = 1, size = 1000)rn2 = np.random.normal(loc = 0, scale = 2, size = 1000) rn3 = np.random.normal(loc = 2, scale = 3, size = 1000)rn4 = np.random.normal(loc = 5, scale = 3, size = 1000)# 绘图plt.style.use('ggplot')sns.distplot(rn1,hist = False,kde = False,fit = stats.norm,fit_kws = {'color':'black','label':'u=0,s=1','linestyle':'-'})sns.distplot(rn2,hist = False,kde = False,fit = stats.norm,fit_kws = {'color':'red','label':'u=0,s=2','linestyle':'--'})sns.distplot(rn3,hist = False,kde = False,fit = stats.norm,fit_kws = {'color':'blue','label':'u=2,s=3','linestyle':':'})sns.distplot(rn4,hist = False,kde = False,fit = stats.norm,fit_kws = {'color':'purple','label':'u=5,s=3','linestyle':'-.'})#呈现图例plt.legend()#呈现图形plt.show()

OUT：

import seaborn as snsimport matplotlib.pyplot as pltfrom scipy import statsimport numpy as npnp.random.seed(1234)re1 = np.random.exponential(scale=0.5,size=1000)re2 = np.random.exponential(scale=1,size=1000)re3 = np.random.exponential(scale=1.5,size=1000)# 绘图sns.distplot(re1,hist=False,kde=False,fit=stats.expon,fit_kws={'color':'black','label':'lambda=0.5','linestyle':'-'})sns.distplot(re2,hist=False,kde=False,fit=stats.expon,fit_kws={'color':'red','label':'lambda=1','linestyle':'--'})sns.distplot(re3,hist=False,kde=False,fit=stats.expon,fit_kws={'color':'blue','label':'lambda=1.5','linestyle':':'})# 呈现图例plt.legend()# 呈现图形plt.show()

OUT：

本章总结