这里我们将使用matplotlib绘制直方图: plt.hist(random_numbers,bins=30,density=True,alpha=0.6,color='g')# 绘制直方图plt.title('Normal Distribution Histogram')# 设置标题plt.xlabel('Value')# x轴标签plt.ylabel('Density')# y轴标签# 绘制正态分布曲线xmin,xmax=plt.xlim()# 获取x的范围x=np.linspace...
Random number with seed 0 : 0.8444218515250481 Random number with seed 0 : 0.8444218515250481 Random number with seed 0 : 0.8444218515250481 Random number with seed 10 : 0.5714025946899135 Numpy.Random number with seed 10 : 0.771320643266746 Random number with seed 10 : 0.5714025946899135 Numpy.Random nu...
plt.hist(random_numbers, bins=30, density=True, alpha=0.6, color='g') 绘制标准正态分布的概率密度函数 xmin, xmax = plt.xlim() x = np.linspace(xmin, xmax, 100) p = np.exp(-x2/2) / np.sqrt(2 * np.pi) plt.plot(x, p, 'k', linewidth=2) plt.title('Standard Normal Distr...
def normal_distribution(mu, sigma, size=1000): return np.random.normal(mu, sigma, size)mu = 0sigma = 1size = 1000samples = normal_distribution(mu, sigma, size)plt.hist(samples, bins=30, density=True)plt.title("Normal Distribution")plt.show()指数分布 指数分布是一种连续型概率分布，用...
例如,normal()生成指定均值和标准差的正态分布随机数,poisson()生成泊松分布的随机数。 4.随机数生成器(Random Generators): 这个模块包含了Generator类,用于创建自定义随机数生成器,提供更多控制和功能。 使用Generator类,你可以设置不同的随机数生成器,种子,以及生成不同分布的随机数。
def CreateNormalDistribution(mu,sigma,num): ''' :param mu: 期望 :param sigma:标准差:param num: 多少个 :return: 生成正态分布随机数,并生成图片 ''' normal = numpy.random.normal(mu,sigma,num) sns.set_palette("hls") sns.distplot(normal, color="r", bins=1000, kde=True) ...
随机变量(Random Variable) 密度函数(Density Functions) 伯努利分布(Bernoulli Distribution) 二项式分布(Binomial Distribution) 均匀分布(Uniform Distribution) 泊松分布(Poisson Distribution) 正态分布(Normal Distribution) 长尾分布(Long-Tailed Distribution)
generate random permutation distributions on the real line: --- uniform triangular normal (Gaussian) lognormal negative exponential gamma beta pareto Weibull distributions on the circle (angles 0 to 2pi) --- circular uniform von Mises General notes...
pick random element pick random sample pick weighted random sample generate random permutation distributions on the real line: --- uniform triangular normal (Gaussian) lognormal negative exponential gamma beta pareto Weibull distributions on the circle...
% random variables with independent multivariate % normal distribution, with mean 0 and variance 1. % Then the incomplete gamma function, 'gammainc', % is used to map these points radially to fit in the % hypersphere of finite radius r with a uniform % spatial distribution. ...