distributions.py 文件源码

def plot_kde(data):
    bw = 1.06 * st.stdev(data) / (len(data) ** .2)
    kde = KernelDensity(kernel='gaussian', bandwidth=bw).fit(
        np.array(data).reshape(-1, 1))
    s = np.linspace(0, 1)
    e = kde.score_samples(s.reshape(-1, 1))
    plt.plot(s, e)

    mi, ma = argrelextrema(e, np.less)[0], argrelextrema(e, np.greater)[0]
    logger.info("Minima: %s" % s[mi])
    logger.info("Maxima: %s" % s[ma])

    plt.plot(s[:mi[0] + 1], e[:mi[0] + 1], 'r',
             s[mi[0]:mi[1] + 1], e[mi[0]:mi[1] + 1], 'g',
             s[mi[1]:], e[mi[1]:], 'b',
             s[ma], e[ma], 'go',
             s[mi], e[mi], 'ro')

    plt.xlabel('Probability')