python-numpy-指数分布实例详解
如下所示:
# Seed random number generator np.random.seed(42) # Compute mean no-hitter time: tau tau = np.mean(nohitter_times) # Draw out of an exponential distribution with parameter tau: inter_nohitter_time inter_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 plot plt.show()
指数分布的拟合
# Create an ECDF from real data: x, y x, y = ecdf(nohitter_times) # Create a CDF from theoretical samples: x_theor, y_theor x_theor, y_theor = ecdf(inter_nohitter_time) # Overlay the plots plt.plot(x_theor, y_theor) plt.plot(x, y, marker=".", linestyle="none") # Margins and axis labels plt.margins(0.02) plt.xlabel("Games between no-hitters") plt.ylabel("CDF") # Show the plot plt.show()
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