distances.py 文件源码

def covariance_distance_from_matrices(m1, m2, mul_factor=1):
    """
    Covariance distance between matrices m1 and m2, defined as
    d = factor * (1 - (trace(m1 * m2)) / (norm_fro(m1) + norm_fro(m2)))
    :param m1: matrix
    :param m2: matrix
    :param mul_factor: multiplicative factor for the formula, it equals to the maximal value the distance can reach
    :return: mul_factor * (1 - (np.trace(m1.dot(m2))) / (np.linalg.norm(m1) + np.linalg.norm(m2)))
    """
    if np.nan not in m1 and np.nan not in m2:
        return \
            mul_factor * (1 - (np.trace(m1.dot(m2)) / (np.linalg.norm(m1, ord='fro') * np.linalg.norm(m2, ord='fro'))))
    else:
        return np.nan


# --- global distances: (segm, segm) |-> real