def test_sigma_s_gh(): # Tests stub b = pyne.data.b("H1") aw = pyne.data.atomic_mass("H1") E = np.logspace(-6, 1, 10)[::-1] E_centers = (E[1:] + E[:-1]) / 2.0 expected = np.diag(pyne.xs.models.sigma_s(E_centers, b, aw, 600.0)) observed = sigma_s_gh("H1", 600.0, group_struct=E) assert_array_equal(expected, observed)
def test_sigma_s_gh(): # Tests stub b = pyne.data.b('H1') aw = pyne.data.atomic_mass('H1') E = np.logspace(-6, 1, 10)[::-1] E_centers = (E[1:] + E[:-1]) / 2.0 expected = np.diag(pyne.xs.models.sigma_s(E_centers, b, aw, 600.0)) observed = sigma_s_gh('H1', 600.0, group_struct=E) assert_array_equal(expected, observed)
def test_sigma_s_gh(): # Tests stub b = pyne.data.b('H1') aw = pyne.data.nuc_weight('H1') E = np.logspace(-6, 1, 10)[::-1] E_centers = (E[1:] + E[:-1]) / 2.0 expected = np.diag(pyne.xs.models.sigma_s(E_centers, b, aw, 600.0)) observed = sigma_s_gh('H1', 600.0, E_g=E) assert_array_equal(expected, observed)
def test_sigma_s(): E_g = np.logspace(-6, 1, 10)[::-1] expected = sigma_s_gh("H1", 600.0, E_g).sum(axis=1) observed = sigma_s("H1", 600.0, E_g) assert_array_equal(expected, observed)
def test_sigma_s(): E_g = np.logspace(-6, 1, 10)[::-1] expected = sigma_s_gh('H1', 600.0, E_g).sum(axis=1) observed = sigma_s('H1', 600.0, E_g) assert_array_equal(expected, observed)