serving.py 文件源码

def correlation(probs):
    """Compute correlation rho(X,Y) = sqrt(1 - exp(-2 I(X;Y))).

    Args:
        probs: An [M, M]-shaped numpy array representing a joint distribution.

    Returns:
        A number in [0,1) representing the information-theoretic correlation.
    """
    assert len(probs.shape) == 2
    assert probs.shape[0] == probs.shape[1]
    mutual_information = (entropy(probs.sum(0)) + entropy(probs.sum(1)) -
                          entropy(probs.flatten()))
    return np.sqrt(1.0 - np.exp(-2.0 * mutual_information))