distributions.py 文件源码

def vmf_logp(x, lon_lat, kappa):

    if x[1] < -90. or x[1] > 90.:
        raise ZeroProbability
        return -np.inf

    if kappa < eps:
        return np.log(1. / 4. / np.pi)

    mu = np.array([np.cos(lon_lat[1] * d2r) * np.cos(lon_lat[0] * d2r),
                   np.cos(lon_lat[1] * d2r) * np.sin(lon_lat[0] * d2r),
                   np.sin(lon_lat[1] * d2r)])
    test_point = np.transpose(np.array([np.cos(x[1] * d2r) * np.cos(x[0] * d2r),
                                        np.cos(x[1] * d2r) *
                                        np.sin(x[0] * d2r),
                                        np.sin(x[1] * d2r)]))

    logp_elem = np.log( -kappa / ( 2. * np.pi * np.expm1(-2. * kappa)) ) + \
        kappa * (np.dot(test_point, mu) - 1.)

    logp = logp_elem.sum()
    return logp