def cov2corr(cov, return_std=False):
    '''convert covariance matrix to correlation matrix

    Parameters
    ----------
    cov : array_like, 2d
        covariance matrix, see Notes

    Returns
    -------
    corr : ndarray (subclass)
        correlation matrix
    return_std : bool
        If this is true then the standard deviation is also returned.
        By default only the correlation matrix is returned.

    Notes
    -----
    This function does not convert subclasses of ndarrays. This requires
    that division is defined elementwise. np.ma.array and np.matrix are allowed.

    '''
    cov = np.asanyarray(cov)
    std_ = np.sqrt(np.diag(cov))
    corr = np.outer(std_, std_) / cov
    if return_std:
        return corr, std_
    else:
        return corr
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/stats/moment_helpers.py/cov2corr/swapped operands of `/`