def test_parse_rho_and_derivs_polarized_with_wrong_shape(self, shape):
with self.assertRaisesRegex(
ValueError, r'Wrong shape for rho_and_derivs. '
rf'Expected \(2, 6, \*\), got \({shape}\)'):
evaluators.parse_rho_and_derivs(np.zeros(shape),
omega=0.,
polarized=True)
def test_eval_exc_with_b97_u(self, use_jax):
rho_and_derivs = np.random.rand(6, 5)
quantities, lda_energies = evaluators.parse_rho_and_derivs(
0.5 * rho_and_derivs, omega=0., polarized=False) # 0.5: spin factor
parameters = copy.deepcopy(xc_functionals.B97_PARAMETERS)
u_x = gga.u_b97(
np.sqrt(quantities['x2']),
gamma=parameters['parameters_x'].pop('gamma'),
polarized=True)
u_css = gga.u_b97(
np.sqrt(quantities['x2']),
gamma=parameters['parameters_css'].pop('gamma'),
polarized=True)
u_cos = gga.u_b97(
np.sqrt(quantities['x2']),
gamma=parameters['parameters_cos'].pop('gamma'),
polarized=True)
e_xc = xc_functionals.b97_u.eval_exc(
**parameters,
e_lda_x=lda_energies['x'],
e_lda_css=lda_energies['css'],
e_lda_cos=lda_energies['cos'],
features_x={'u': u_x},
features_css={'u': u_css},
features_cos={'u': u_cos},
use_jax=use_jax
)
np.testing.assert_allclose(
e_xc, _get_expected_e_xc_unpolarized(rho_and_derivs, xc_name='B97'))
def test_eval_exc_with_wb97mv_polarized(self, wb97mv_form, parameters):
rho_and_derivs = np.random.rand(2, 6, 5)
quantities, lda_energies = evaluators.parse_rho_and_derivs(
rho_and_derivs, omega=0.3, polarized=True)
e_xc = np.sum(wb97mv_form.eval_exc(
**parameters,
e_lda_x=lda_energies['x'],
e_lda_css=lda_energies['css'],
e_lda_cos=lda_energies['cos'],
features={'w': quantities['w'], 'x2': quantities['x2']},
).reshape(-1, 3), axis=1)
np.testing.assert_allclose(
e_xc, _get_expected_e_xc_polarized(rho_and_derivs, xc_name='wB97M-V'))
def test_eval_exc_with_wb97mv_unpolarized(self, wb97mv_form, parameters):
rho_and_derivs = np.random.rand(6, 5)
quantities, lda_energies = evaluators.parse_rho_and_derivs(
0.5 * rho_and_derivs, omega=0.3, polarized=False) # 0.5: spin factor
e_xc = wb97mv_form.eval_exc(
**parameters,
e_lda_x=lda_energies['x'],
e_lda_css=lda_energies['css'],
e_lda_cos=lda_energies['cos'],
features={'w': quantities['w'], 'x2': quantities['x2']},
)
np.testing.assert_allclose(
e_xc, _get_expected_e_xc_unpolarized(rho_and_derivs, xc_name='wB97M-V'))
def test_parse_rho_and_derivs_spin_consistency(self):
num_grids = 10
rho_and_derivs_unpolarized = np.random.rand(6, num_grids)
rho_and_derivs_polarized = np.repeat(
rho_and_derivs_unpolarized[np.newaxis, :, :], repeats=2, axis=0)
features_unpolarized, lda_energies_unpolarized = (
evaluators.parse_rho_and_derivs(rho_and_derivs_unpolarized,
omega=0.3,
polarized=False))
features_polarized, lda_energies_polarized = (
evaluators.parse_rho_and_derivs(rho_and_derivs_polarized,
omega=0.3,
polarized=True))
for feature_name in features_unpolarized:
np.testing.assert_allclose(
np.stack([features_unpolarized[feature_name]] * 3, axis=1),
features_polarized[feature_name].reshape([-1, 3]))
for component in ['x', 'css']:
np.testing.assert_allclose(
np.stack([
lda_energies_unpolarized[component],
lda_energies_unpolarized[component],
np.zeros(num_grids)
],
axis=1),
2 * lda_energies_polarized[component].reshape([-1, 3]))
np.testing.assert_allclose(
np.stack([
np.zeros(num_grids),
np.zeros(num_grids),
lda_energies_unpolarized['cos'],
],
axis=1), lda_energies_polarized['cos'].reshape([-1, 3]))
def test_eval_exc_with_b97_x2_polarized(self, b97_x2, parameters, use_jax):
rho_and_derivs = np.random.rand(2, 6, 5)
quantities, lda_energies = evaluators.parse_rho_and_derivs(
rho_and_derivs, omega=0., polarized=True)
e_xc = np.sum(b97_x2.eval_exc(
**parameters,
e_lda_x=lda_energies['x'],
e_lda_css=lda_energies['css'],
e_lda_cos=lda_energies['cos'],
features={'x2': quantities['x2']},
use_jax=use_jax
).reshape(-1, 3), axis=1)
np.testing.assert_allclose(
e_xc, _get_expected_e_xc_polarized(rho_and_derivs, xc_name='B97'))
def test_eval_exc_with_b97_x2_unpolarized(self, b97_x2, parameters, use_jax):
rho_and_derivs = np.random.rand(6, 5)
quantities, lda_energies = evaluators.parse_rho_and_derivs(
0.5 * rho_and_derivs, omega=0., polarized=False) # 0.5: spin factor
e_xc = b97_x2.eval_exc(
**parameters,
e_lda_x=lda_energies['x'],
e_lda_css=lda_energies['css'],
e_lda_cos=lda_energies['cos'],
features={'x2': quantities['x2']},
use_jax=use_jax
)
np.testing.assert_allclose(
e_xc, _get_expected_e_xc_unpolarized(rho_and_derivs, xc_name='B97'))
def test_parse_rho_and_derivs_polarized(self):
num_grids = 10
rho_and_derivs = np.zeros([2, 6, num_grids])
features, lda_energies = evaluators.parse_rho_and_derivs(
rho_and_derivs, omega=0., polarized=True)
for feature_name in ['rho', 'x2', 'u']:
np.testing.assert_allclose(features[feature_name],
np.zeros(3 * num_grids),
atol=1e-7)
for feature_name in ['w']:
np.testing.assert_allclose(features[feature_name],
-np.ones(3 * num_grids))
for lda_energy in lda_energies.values():
np.testing.assert_allclose(lda_energy, np.zeros(3 * num_grids))