代码源自:
https://github.com/PacktPublishing/Bayesian-Analysis-with-Python
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import matplotlib.pyplot as plt import numpy as np from scipy import stats import seaborn as sns palette = 'muted' sns.set_palette(palette); sns.set_color_codes(palette) n_params = [1, 2, 4] p_params = [0.25, 0.5, 0.75] x = np.arange(0, max(n_params)+1) f, ax = plt.subplots(len(n_params), len(p_params), sharex=True, sharey=True) for i in range(3): for j in range(3): n = n_params[i] p = p_params[j] y = stats.binom(n=n, p=p).pmf(x) ax[i,j].vlines(x, 0, y, colors='b', lw=5) ax[i,j].set_ylim(0, 1) ax[i,j].plot(0, 0, label="n = {:3.2f}\np = {:3.2f}".format(n, p), alpha=0) ax[i,j].legend(fontsize=12) ax[2,1].set_xlabel('$\\theta$', fontsize=14) ax[1,0].set_ylabel('$p(y|\\theta)$', fontsize=14) ax[0,0].set_xticks(x) plt.savefig('B04958_01_03.png', dpi=300, figsize=(5.5, 5.5)) plt.show()
绘图:
![](https://img2022.cnblogs.com/blog/1088037/202206/1088037-20220608225321872-1359881873.png)
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