def METHOD_NAME(A, B):
    """
    Compute correlation coefficients and return as a np array
    """
    A, B = np.array(A), np.array(B)
    # Rowwise mean of input arrays & subtract from input arrays themeselves
    A_mA = A - A.mean(1)[:, None]
    B_mB = B - B.mean(1)[:, None]
    # Sum of squares across rows
    ssA = (A_mA**2).sum(1)
    ssB = (B_mB**2).sum(1)
    # Finally get corr coeff
    return np.dot(A_mA, B_mB.T) / np.sqrt(np.dot(ssA[:, None], ssB[None]))