def test_score_student_t_dbg_lp_equiv(): seed_all(0) def random_vec(dim): return numpy.random.uniform(low=-3., high=3., size=dim) def random_cov(dim): Q = random_orthonormal_matrix(dim) return numpy.dot(Q, Q.T) def random_values(dim): return (random_vec(dim), float(dim) + 1., random_vec(dim), random_cov(dim)) values = ( [random_values(2) for _ in xrange(10)] + [random_values(3) for _ in xrange(10)] ) for x, nu, mu, cov in values: dbg_mv_score = dbg_score_student_t(x, nu, mu, cov) lp_mv_score = lp_score_student_t(x, nu, mu, cov) assert_close(dbg_mv_score, lp_mv_score)
def test_score_student_t_scalar_equiv(): values = ( (1.2, 5., -0.2, 0.7), (-3., 3., 1.2, 1.3), ) for x, nu, mu, sigmasq in values: mv_args = [ numpy.array([x]), nu, numpy.array([mu]), numpy.array([[sigmasq]])] scalar_score = scalar_score_student_t(x, nu, mu, sigmasq) dbg_mv_score = dbg_score_student_t(*mv_args) lp_mv_score = lp_score_student_t(*mv_args) assert_close(scalar_score, dbg_mv_score) assert_close(scalar_score, lp_mv_score) assert_close(dbg_mv_score, lp_mv_score)
def test_score_student_t_scalar_equiv(): values = ( (1.2, 5., -0.2, 0.7), (-3., 3., 1.2, 1.3), ) for x, nu, mu, sigmasq in values: mv_args = [ numpy.array([x]), nu, numpy.array([mu]), numpy.array([[sigmasq]]) ] scalar_score = scalar_score_student_t(x, nu, mu, sigmasq) dbg_mv_score = dbg_score_student_t(*mv_args) lp_mv_score = lp_score_student_t(*mv_args) assert_close(scalar_score, dbg_mv_score) assert_close(scalar_score, lp_mv_score) assert_close(dbg_mv_score, lp_mv_score)
def test_score_student_t_dbg_lp_equiv(): seed_all(0) def random_vec(dim): return numpy.random.uniform(low=-3., high=3., size=dim) def random_cov(dim): Q = random_orthonormal_matrix(dim) return numpy.dot(Q, Q.T) def random_values(dim): return (random_vec(dim), float(dim) + 1., random_vec(dim), random_cov(dim)) values = ([random_values(2) for _ in xrange(10)] + [random_values(3) for _ in xrange(10)]) for x, nu, mu, cov in values: dbg_mv_score = dbg_score_student_t(x, nu, mu, cov) lp_mv_score = lp_score_student_t(x, nu, mu, cov) assert_close(dbg_mv_score, lp_mv_score)