util.py 文件源码

def _normalize_for_correlation(data, axis):
    """normalize the data before computing correlation

    The data will be z-scored and divided by sqrt(n)
    along the assigned axis

    Parameters
    ----------
    data: 2D array

    axis: int
        specify which dimension of the data should be normalized

    Returns
    -------
    data: 2D array
        the normalized data
    """
    shape = data.shape
    data = zscore(data, axis=axis, ddof=0)
    # if zscore fails (standard deviation is zero),
    # set all values to be zero
    data = np.nan_to_num(data)
    data = data / math.sqrt(shape[axis])
    return data