贝叶斯更新

def solve():
    import numpy as np
    import matplotlib.pyplot as plt
    from scipy import stats
    np.random.seed(____)
    true_p = ____
    n_flips = ____
    flips = np.random.binomial(____, true_p, n_flips)
    alpha_prior, beta_prior = ____, ____
    alpha_posterior = alpha_prior
    beta_posterior = beta_prior
    x = np.linspace(____, ____, ____)
    fig, axes = plt.subplots(____, ____, figsize=(____, ____))
    checkpoints = [____, ____, ____, ____]
    for idx, checkpoint in enumerate(____):
        if checkpoint > ____:
            for i in range(____):
                if flips[i] == ____:
                    alpha_posterior += ____
                else:
                    beta_posterior += ____
        ax = axes[idx // ____, idx % ____]
        ax.plot(x, stats.beta.pdf(____), '____', linewidth=____)
        ax.axvline(____)
        ax.set_title(____)
        ax.set_xlabel(____)
        ax.set_ylabel(____)
        ax.legend()
        ax.grid(____)
    plt.tight_layout()
    plt.show()