vis_corex.py 文件源码

def anomalies(log_z, row_label=None, prefix=''):
    from scipy.special import erf

    ns = log_z.shape[1]
    if row_label is None:
        row_label = list(map(str, range(ns)))
    a_score = np.sum(log_z[:, :, 0], axis=0)
    mean, std = np.mean(a_score), np.std(a_score)
    a_score = (a_score - mean) / std
    percentile = 1. / ns
    anomalies = np.where(0.5 * (1 - erf(a_score / np.sqrt(2)) ) < percentile)[0]
    f = safe_open(prefix + '/text_files/anomalies.txt', 'w+')
    for i in anomalies:
        f.write(row_label[i] + ', %0.1f\n' % a_score[i])
    f.close()