basic_segment_statistics.py 文件源码

def median_absolute_deviation(data, subject_median=None, axis=0):
    """
    Returns the median absolute deviation (MAD) for the given data.
    :param data: A DataFrame holding the data to calculate the MAD from.
    :param subject_median: If given, these will be used as the medians which the deviation is calculated from. If None
                           The median of the given data is used.
    :param axis: The axis to calculate over.
    :return: A Series object with the median absolute deviations over the given *axis* for the *data*.
    """
    """A robust estimate of the standard deviation"""
    # The scaling factor for estimating the standard deviation from the MAD
    c = scipy.stats.norm.ppf(3 / 4)
    if isinstance(data, pd.DataFrame):
        if subject_median is None:
            subject_median = data.median(axis=axis)
        median_residuals = data - subject_median
        mad = median_residuals.abs().median(axis=axis)
    else:
        if subject_median is None:
            subject_median = np.median(data, axis=axis)
        median_residuals = data - subject_median[:, np.newaxis]  # deviation between median and data
        mad = np.median(np.abs(median_residuals), axis=axis)
    return mad / c