def __init__(self):
self._cache = {}
self._get_fns = {'E_n': get_E_n,
'sigma_f_n': get_sigma_f_n,
'sigma_a_n': get_sigma_a_n,
'sigma_rx_n': get_sigma_a_reaction_n,
'phi_g': lambda: phi_g(self['E_g'], self['E_n'], self['phi_n']),
}
def test_phi_g2():
E_g = np.array([0.0, 5.0, 10.0])
E_n = np.array([0.0, 5.0, 10.0])
phi_n = np.ones(2)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.0, 1.0])
assert_array_equal(observed, expected)
def test_phi_g5():
E_g = np.array([0.0, 4.0, 10.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.ones(4)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.6, 2.4])
assert_array_equal(observed, expected)
def test_phi_g5():
E_g = np.array([0.0, 4.0, 10.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.ones(4)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.6, 2.4])
assert_array_equal(observed, expected)
def test_phi_g2():
E_g = np.array([0.0, 5.0, 10.0])
E_n = np.array([0.0, 5.0, 10.0])
phi_n = np.ones(2)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.0, 1.0])
assert_array_equal(observed, expected)
def test_phi_g7():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.array([0.0, 2.0, 1.0, 0.5])
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.2, 1.9])
# Floating point error here requires 'alomst' equal
assert_array_almost_equal(observed, expected)
def test_phi_g6():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.ones(4)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.6, 1.6])
# Floating point error here requires 'alomst' equal
assert_array_almost_equal(phi_g, expected)
def test_phi_g7():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.array([0.0, 2.0, 1.0, 0.5])
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.2, 1.9])
# Floating point error here requires 'alomst' equal
assert_array_almost_equal(observed, expected)
def test_phi_g6():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.ones(4)
observed = phi_g(E_g, E_n, phi_n)
expected = np.array([1.6, 1.6])
# Floating point error here requires 'alomst' equal
assert_array_almost_equal(phi_g, expected)
def test_group_collapse1():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.array([0.0, 2.0, 1.0, 0.5])
sigma_n = np.array([1.0, 2.0, 3.0, 4.0])
expected = np.array([2.0, 5.0 / 1.9])
# First way of calling
observed = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n)
assert_array_almost_equal(observed, expected)
# Second method of calling
p_g = phi_g(E_g, E_n, phi_n)
pem = partial_energy_matrix(E_g, E_n)
observed = group_collapse(sigma_n, phi_n, phi_g=p_g, partial_energies=pem)
assert_array_almost_equal(observed, expected)
# bad call
assert_raises(ValueError, group_collapse, sigma_n, phi_n)
def test_group_collapse1():
E_g = np.array([0.0, 4.0, 8.0])
E_n = np.array([0.0, 2.5, 5.0, 7.5, 10.0])
phi_n = np.array([0.0, 2.0, 1.0, 0.5])
sigma_n = np.array([1.0, 2.0, 3.0, 4.0])
expected = np.array([2.0, 5.0 / 1.9])
# First way of calling
observed = group_collapse(sigma_n, phi_n, E_g=E_g, E_n=E_n)
assert_array_almost_equal(observed, expected)
# Second method of calling
p_g = phi_g(E_g, E_n, phi_n)
pem = partial_energy_matrix(E_g, E_n)
observed = group_collapse(sigma_n, phi_n, phi_g=p_g, partial_energies=pem)
assert_array_almost_equal(observed, expected)
# bad call
assert_raises(ValueError, group_collapse, sigma_n, phi_n)
