如下所示：
# Seed random number generatornp.random.seed(42) # Compute mean no-hitter time: tautau = np.mean(nohitter_times) # Draw out of an exponential distribution with parameter tau: inter_nohitter_timeinter_nohitter_time = np.random.exponential(tau, 100000) # Plot the PDF and label axes_ = plt.hist(inter_nohitter_time, bins=50, normed=True, histtype='step')_ = plt.xlabel('Games between no-hitters')_ = plt.ylabel('PDF') # Show the plotplt.show()指数分布的拟合
# Create an ECDF from real data: x, yx, y = ecdf(nohitter_times) # Create a CDF from theoretical samples: x_theor, y_theorx_theor, y_theor = ecdf(inter_nohitter_time) # Overlay the plotsplt.plot(x_theor, y_theor)plt.plot(x, y, marker='.', linestyle='none') # Margins and axis labelsplt.margins(0.02)plt.xlabel('Games between no-hitters')plt.ylabel('CDF') # Show the plotplt.show()以上这篇python-numpy-指数分布实例详解就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。
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