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x
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...
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...
Normally Distributed Random Numbers') plt.xlabel('Value') plt.ylabel('Frequency') plt.show() # 存储生成的随机数到CSV文件 with open('normal_distribution_random_numbers.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile) for number in random_numbers: writer.writerow([number...
使用NumPy的numpy.random模块可以生成各种常见的概率分布,让随机数的生成符合一定的规则 正态分布(Normal Distribution): 生成方法: 使用numpy.random.normal()函数生成。需要指定均值(loc)和标准差(scale)。 特点: 正态分布是一种对称的、钟形曲线分布,均值、中位数和众数相等。它具有良好的数学性质,广泛用于自然现...
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) ...
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_numbers,bins=50,density=True,alpha=0.7)# 计算理论正态分布曲线x=np.linspace(mu-3*sigma,mu+3*sigma,100)y=1/(sigma*np.sqrt(2*np.pi))*np.exp(-(x-mu)**2/(2*sigma**2))# 绘制理论曲线plt.plot(x,y,color='red',linewidth=2)# 添加标题和标签plt.title('Normal Distribution')...