distribution.py 文件源码

def median_percentile(data, des_percentiles='68+95+99'):
    """

    :param data:
    :param des_percentiles: string with +separated values of the percentiles
    :return:
    """
    median = np.nanmedian(data, axis=0)
    out = np.array(map(int, des_percentiles.split("+")))
    for i in range(out.size):
        assert 0 <= out[i] <= 100, 'Percentile must be >0 <100; instead is %f' % out[i]
    list_percentiles = np.empty((2*out.size,), dtype=out.dtype)
    list_percentiles[0::2] = out        # Compute the percentile
    list_percentiles[1::2] = 100 - out  # Compute also the mirror percentile
    percentiles = np.nanpercentile(data, list_percentiles, axis=0)
    return [median, percentiles]