pca.py 文件源码

def PA(samples, variables):
    datasets = 5000
    eig_vals = []

    for i in range(datasets):
        data = np.random.standard_normal((variables, samples))
        cor_ = np.corrcoef(data)
        eig_vals.append(np.sort(np.linalg.eig(cor_)[0])[::-1])


    quantile = (np.round(np.percentile(eig_vals, 95.0, axis=0), 4))
    mean_ = (np.round(np.mean(eig_vals, axis=0), 4))
    return quantile