def setUp(self):
data = get_data_from_file_fchk('pirrol.in.fchk')
self.pirrol = WfnSympy(
coordinates=data['coordinates'],
symbols=data['symbols'],
basis=data['basis'],
center=[0., 0., 0.],
axis=[1., 0., 0.],
# axis2=[0., 0., 1.],
alpha_mo_coeff=data['mo_coefficients']['alpha'][:18],
alpha_occupancy=data['alpha_occupancy'],
beta_occupancy=data['beta_occupancy'],
group='C6v')
def setUp(self):
self.data = get_data_from_file_fchk('ammonia.fchk')
self.structure = WfnSympy(
coordinates=self.data['coordinates'],
symbols=self.data['symbols'],
basis=self.data['basis'],
axis=[0.55944897, 0.69527034, -0.4512383],
axis2=[0., -0.4512383, -0.69527034],
alpha_mo_coeff=self.data['mo_coefficients']['alpha'],
group='C3v')
def get_wf_symmetry(structure,
basis,
mo_coeff,
center=None,
orientation=(0., 0., 1.),
orientation2=(0, 1, 0),
group='C2h',
occupancy=None):
"""
Simplified interface between pyqchem anf wfnsympy
:param structure: molecular geometry (3xn) array
:param basis: dictionary containing the basis
:param mo_coeff: molecular orbitals coefficients
:param center: center of the molecule
:param orientation: unit vector perpendicular to the plane of the molecule
:param group: point symmetry group
:return molsym: wfnsympy object
"""
alpha_mo_coeff = np.array(mo_coeff['alpha']).tolist()
alpha_occupancy = [0] * len(mo_coeff['alpha'])
alpha_occupancy[:int(structure.alpha_electrons
)] = [1] * structure.alpha_electrons
if 'beta' in mo_coeff:
beta_mo_coeff = np.array(mo_coeff['beta']).tolist()
beta_occupancy = [0] * len(mo_coeff['beta'])
beta_occupancy[:int(structure.alpha_electrons
)] = [1] * structure.alpha_electrons
else:
beta_mo_coeff = None
beta_occupancy = None
if occupancy is not None:
alpha_occupancy = occupancy['alpha']
if 'beta' in occupancy:
beta_occupancy = occupancy['beta']
molsym = WfnSympy(
coordinates=structure.get_coordinates(),
symbols=structure.get_symbols(),
basis=basis,
center=center,
axis=orientation,
axis2=orientation2,
alpha_mo_coeff=alpha_mo_coeff,
beta_mo_coeff=beta_mo_coeff,
alpha_occupancy=alpha_occupancy,
beta_occupancy=beta_occupancy,
#charge=structure.charge,
#multiplicity=structure.multiplicity,
group=group)
return molsym
def test_dens_occupancy(self):
self.structure = WfnSympy(
coordinates=self.data['coordinates'],
symbols=self.data['symbols'],
basis=self.data['basis'],
axis=[0.55944897, 0.69527034, -0.4512383],
axis2=[0., -0.4512383, -0.69527034],
alpha_mo_coeff=self.data['mo_coefficients']['alpha'],
group='C3v',
alpha_occupancy=[0, 1, 1, 1, 1])
np.testing.assert_allclose(4.5067, self.structure.csm_dens, rtol=1e-03)
def test_precision(self):
self.structure = WfnSympy(
coordinates=self.data['coordinates'],
symbols=self.data['symbols'],
basis=self.data['basis'],
axis=[0.55944897, 0.69527034, -0.4512383],
axis2=[0., -0.4512383, -0.69527034],
alpha_mo_coeff=self.data['mo_coefficients']['alpha'],
group='C3v',
tolerance=1e-04,
alpha_occupancy=self.data['alpha_occupancy'],
beta_occupancy=self.data['beta_occupancy'])
np.testing.assert_allclose(0.148, self.structure.csm_dens, rtol=1e-03)
def target_function(alpha, beta):
ax1 = np.dot(rotation_xy(alpha, beta), [1, 0, 0])
# ax2 = np.dot(rotation_xy(alpha, beta), [0, 0, 1])
pirrol = WfnSympy(
coordinates=data['coordinates'],
symbols=data['symbols'],
basis=data['basis'],
center=c_geom,
axis=ax1,
# axis2=ax2,
alpha_mo_coeff=data['mo_coefficients']['alpha'],
group='C5')
res = np.sum(np.sqrt(pirrol.csm_coef))
return res
def _get_wfnsym_results(self, group):
if self._electronic_structure is None:
raise Exception('Electronic structure not set')
key = _get_key_wfnsym(group, self._axis, self._axis2, self._center,
self._electronic_structure.alpha_occupancy,
self._electronic_structure.beta_occupancy)
if key not in self._results:
self._results[key] = WfnSympy(
coordinates=self._coordinates,
symbols=self._symbols,
basis=self._electronic_structure.basis,
center=self._center,
axis=self._axis,
axis2=self._axis2,
alpha_mo_coeff=self._electronic_structure.coefficients_a,
beta_mo_coeff=self._electronic_structure.coefficients_b,
group=group.upper(),
alpha_occupancy=self._electronic_structure.alpha_occupancy,
beta_occupancy=self._electronic_structure.beta_occupancy)
return self._results[key]
def test_degenerate_3(self):
configurations = [
[[1, 1, 1, 1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0, 1, 0, 0]],
[[1, 1, 1, 1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0, 0, 1, 0]],
[[1, 1, 1, 1, 1, 0, 1, 0, 0], [1, 1, 1, 1, 1, 1, 0, 0, 0]],
[[1, 1, 1, 1, 1, 0, 1, 0, 0], [1, 1, 1, 1, 1, 0, 0, 1, 0]],
[[1, 1, 1, 1, 1, 0, 0, 1, 0], [1, 1, 1, 1, 1, 1, 0, 0, 0]],
[[1, 1, 1, 1, 1, 0, 0, 1, 0], [1, 1, 1, 1, 1, 0, 1, 0, 0]],
]
for conf_alpha, conf_beta in configurations:
print(conf_alpha, conf_beta)
wf_results = WfnSympy(
coordinates=self.data['coordinates'],
symbols=self.data['symbols'],
basis=self.data['basis'],
axis=[
-0.5634811520306573, 0.5937396995245904,
-0.5744233286650642
],
axis2=[
-0.5910397590456458, -0.5756503475754583,
0.5650652002764983
],
alpha_mo_coeff=self.data['mo_coefficients']['alpha'],
group='Td',
alpha_occupancy=conf_alpha,
beta_occupancy=conf_beta,
)
wf_results.print_alpha_mo_IRD()
wf_results.print_wf_mo_IRD()
wf_alpha = np.round(wf_results.wf_IRd_a, decimals=2)
wf_beta = np.round(wf_results.wf_IRd_b, decimals=2)
wf_total = np.round(wf_results.wf_IRd, decimals=2)
print(wf_alpha, wf_beta, wf_total)
self.assertTupleEqual(tuple(wf_alpha), (0., 0., 0., 1., 0.))
self.assertTupleEqual(tuple(wf_beta), (0., 0., 0., 1., 0.))
self.assertTupleEqual(tuple(wf_total), (0., 0., 0., 0.5, 0.5))
def get_wf_symmetry(structure,
basis,
mo_coeff,
center=None,
orientation=(0., 0., 1.),
orientation2=(0, 1, 0),
group='C2h'):
"""
Simplified interface between pyqchem anf wfnsympy
:param structure: molecular geometry (3xn) array
:param basis: dictionary containing the basis
:param mo_coeff: molecular orbitals coefficients
:param center: center of the molecule
:param orientation: unit vector perpendicular to the plane of the molecule
:param group: point symmetry group
:return molsym: wfnsympy object
"""
alpha_mo_coeff = np.array(mo_coeff['alpha']).tolist()
if 'beta' in mo_coeff:
beta_mo_coeff = np.array(mo_coeff['beta']).tolist()
else:
beta_mo_coeff = None
molsym = WfnSympy(coordinates=structure.get_coordinates(),
symbols=structure.get_symbols(),
basis=basis,
center=center,
VAxis=orientation,
VAxis2=orientation2,
alpha_mo_coeff=alpha_mo_coeff,
beta_mo_coeff=beta_mo_coeff,
charge=structure.charge,
multiplicity=structure.multiplicity,
group=group)
return molsym
class TestWfnsympy(unittest.TestCase):
def setUp(self):
data = get_data_from_file_fchk('pirrol.in.fchk')
self.pirrol = WfnSympy(
coordinates=data['coordinates'],
symbols=data['symbols'],
basis=data['basis'],
center=[0., 0., 0.],
axis=[1., 0., 0.],
# axis2=[0., 0., 1.],
alpha_mo_coeff=data['mo_coefficients']['alpha'][:18],
alpha_occupancy=data['alpha_occupancy'],
beta_occupancy=data['beta_occupancy'],
group='C6v')
def test_symlab(self):
symlab_test = [
'E', '2C6', '2C3', 'C2', 's_v1', 's_d1', 's_v2', 's_d2', 's_v3',
's_d3'
]
self.assertEqual(self.pirrol.SymLab, symlab_test)
def test_csm_coef(self):
csm_coef_test = [
5.331142e-07, 9.999894e+01, 1.000000e+02, 1.000000e+02,
1.000000e+02, 1.000000e+02, 9.999894e+01, 5.331136e-07,
9.999894e+01, 1.000000e+02
]
np.testing.assert_allclose(csm_coef_test,
self.pirrol.csm_coef,
rtol=1e-6)
def test_mo_SOEVs_a(self):
mo_soevs_a_test = [
[
1.00000000e+00, -1.32522730e-03, -2.85032614e-05,
3.06252669e-05, 3.06252669e-05, -2.85032614e-05,
-1.32522730e-03, 1.00000000e+00, -1.32522730e-03,
-2.85032614e-05
],
[
1.00000000e+00, 1.58035432e-03, -3.10152695e-02,
-2.47373332e-02, 2.47373332e-02, 3.10152695e-02,
-1.58035432e-03, -1.00000000e+00, -1.58035432e-03,
3.10152695e-02
],
[
1.00000000e+00, 8.01242421e-04, 3.03781569e-02, 2.42405846e-02,
2.42405846e-02, 3.03781569e-02, 8.01242421e-04, 1.00000000e+00,
8.01242421e-04, 3.03781569e-02
],
[
1.00000000e+00, 2.18367913e-01, 3.02127679e-04,
-1.91732435e-04, -1.91732435e-04, 3.02127680e-04,
2.18367913e-01, 1.00000000e+00, 2.18367913e-01, 3.02127679e-04
],
[
1.00000000e+00, -2.24480923e-01, -1.21956191e-04,
9.67591395e-06, -9.67591395e-06, 1.21956191e-04,
2.24480923e-01, -1.00000000e+00, 2.24480923e-01, 1.21956191e-04
],
[
1.00000000e+00, 7.97590267e-01, 6.16140384e-01, 5.62311755e-01,
5.62311755e-01, 6.16140384e-01, 7.97590267e-01, 1.00000000e+00,
7.97590267e-01, 6.16140384e-01
],
[
1.00000000e+00, 5.06929014e-01, -1.34275096e-01,
-3.75219254e-01, -3.75219254e-01, -1.34275096e-01,
5.06929014e-01, 1.00000000e+00, 5.06929014e-01, -1.34275096e-01
],
[
1.00000000e+00, 4.09168542e-01, -4.50809663e-01,
-8.28810626e-01, 8.28810626e-01, 4.50809663e-01,
-4.09168542e-01, -1.00000000e+00, -4.09168542e-01,
4.50809663e-01
],
[
9.99999998e-01, -1.45640081e-01, -7.07265257e-02,
4.98181993e-01, 4.98181993e-01, -7.07265257e-02,
-1.45640081e-01, 9.99999998e-01, -1.45640081e-01,
-7.07265257e-02
],
[
1.00000000e+00, -5.14408504e-01, -3.22442719e-01,
6.92978124e-01, -6.92978124e-01, 3.22442719e-01,
5.14408504e-01, -1.00000000e+00, 5.14408504e-01, 3.22442719e-01
],
[
9.99999998e-01, 5.68141874e-01, 4.92191987e-01, 6.78888006e-01,
6.78888006e-01, 4.92191987e-01, 5.68141874e-01, 9.99999998e-01,
5.68141874e-01, 4.92191987e-01
],
[
1.00000000e+00, 1.44894779e-01, -2.23530452e-01,
-3.63772946e-01, -3.63772946e-01, -2.23530452e-01,
1.44894779e-01, 1.00000000e+00, 1.44894779e-01, -2.23530452e-01
],
[
9.99999999e-01, -2.09577512e-01, -5.34982970e-02,
-3.85232598e-01, 3.85232598e-01, 5.34982970e-02,
2.09577512e-01, -9.99999999e-01, 2.09577512e-01, 5.34982970e-02
],
[
9.99999999e-01, 8.94091923e-01, 7.88572690e-01, 7.46740593e-01,
7.46740593e-01, 7.88572690e-01, 8.94091923e-01, 9.99999999e-01,
8.94091923e-01, 7.88572690e-01
],
[
1.00000000e+00, -3.43439533e-01, 6.92332621e-02,
-3.67952436e-01, 3.67952436e-01, -6.92332621e-02,
3.43439533e-01, -1.00000000e+00, 3.43439533e-01,
-6.92332621e-02
],
[
9.99999998e-01, -6.52313367e-01, 3.71284414e-01,
-3.90435661e-01, -3.90435661e-01, 3.71284414e-01,
-6.52313367e-01, 9.99999998e-01, -6.52313367e-01,
3.71284414e-01
],
[
9.99999999e-01, 4.40770928e-01, -3.00193848e-01,
-5.75538171e-01, -5.75538171e-01, -3.00193848e-01,
4.40770928e-01, 9.99999999e-01, 4.40770928e-01, -3.00193848e-01
],
[
1.00000000e+00, 4.37251180e-01, -4.82843548e-01,
-8.48062831e-01, 8.48062831e-01, 4.82843548e-01,
-4.37251180e-01, -1.00000000e+00, -4.37251180e-01,
4.82843548e-01
]
]
self.pirrol.print_overlap_mo_alpha()
np.testing.assert_allclose(mo_soevs_a_test,
self.pirrol.mo_SOEVs_a,
rtol=1e-6)
def test_wf_SOEVs_a(self):
wf_soevs_a_test = [
9.99999997e-01, 3.25103201e-03, 8.71324571e-08, -2.99110905e-08,
2.99110905e-08, -8.71324571e-08, -3.25103201e-03, -9.99999997e-01,
-3.25103201e-03, -8.71324571e-08
]
np.testing.assert_allclose(wf_soevs_a_test,
self.pirrol.wf_SOEVs_a,
rtol=1e-6)
def test_grim_coef(self):
grim_coef_test = [
1.480872e-08, 6.382904e+01, 7.534673e+01, 5.909258e+01,
5.909258e+01, 7.534673e+01, 6.382904e+01, 1.480871e-08,
6.382904e+01, 7.534673e+01
]
np.testing.assert_allclose(grim_coef_test,
self.pirrol.grim_coef,
rtol=1e-6)
0.000000000, 0.000000000, 0.000000000
],
[
-0.125818566, 0.820120983, 0.000000000, 0.000000000,
-0.763538862, -0.769155124, -0.769155124
],
[
0.000000000, 0.000000000, 0.959800163, 0.000000000,
0.000000000, 0.814629717, -0.814629717
]]
wf_results = WfnSympy(
coordinates=[[0.0000000000, 0.0000000000, -0.0428008531],
[-0.7581074140, 0.0000000000, -0.6785995734],
[0.7581074140, 0.000000000, -0.6785995734]],
symbols=['O', 'H', 'H'],
basis=basis,
alpha_mo_coeff=mo_coefficients[:5],
alpha_occupancy=[0, 1, 1, 0, 0],
beta_occupancy=[1, 1, 1, 1, 1],
group='c2v')
wf_results.print_alpha_mo_IRD()
wf_results.print_overlap_mo_alpha()
wf_results.print_overlap_wf()
wf_results.print_wf_mo_IRD()
def get_orbital_state(orbital_soev):
state_orb = SymmetryBase(group='c2v',
rep=pd.Series(orbital_soev,
index=["E", "C2", "sv_xz",
from wfnsympy import WfnSympy
from wfnsympy.file_io import get_data_from_file_fchk
import numpy as np
# data = get_data_from_file_fchk('pirrol.in.fchk')
data = get_data_from_file_fchk('methane.fchk')
structure = WfnSympy(
coordinates=data['coordinates'],
symbols=data['symbols'],
basis=data['basis'],
alpha_mo_coeff=data['mo_coefficients']['alpha'],
# center=[0., 0., 0.],
# axis=[0., 0., 1.],
# axis2=[0, 1, 0],
alpha_occupancy=data['alpha_occupancy'],
beta_occupancy=data['beta_occupancy'],
group='Td')
structure.print_CSM()
structure.print_overlap_mo_alpha()
structure.print_dens_CSM()
print('axis: ', structure.axis, np.linalg.norm(structure.axis))
print('axis2: ', structure.axis2, np.linalg.norm(structure.axis2))
print('center: ', structure.center)
def setUp(self):
basis = {
'name':
'STO-3G',
'primitive_type':
'gaussian',
'atoms': [{
'symbol':
'O',
'shells': [{
'shell_type':
's',
'p_exponents': [130.70932, 23.808861, 6.4436083],
'con_coefficients':
[0.154328969, 0.535328136, 0.444634536],
'p_con_coefficients': [0.0, 0.0, 0.0]
}, {
'shell_type':
'sp',
'p_exponents': [5.0331513, 1.1695961, 0.380389],
'con_coefficients':
[-0.0999672287, 0.399512825, 0.700115461],
'p_con_coefficients':
[0.155916268, 0.607683714, 0.391957386]
}]
}, {
'symbol':
'H',
'shells': [{
'shell_type':
's',
'p_exponents': [3.42525091, 0.62391373, 0.1688554],
'con_coefficients':
[0.154328971, 0.535328142, 0.444634542],
'p_con_coefficients': [0.0, 0.0, 0.0]
}]
}, {
'symbol':
'H',
'shells': [{
'shell_type':
's',
'p_exponents': [3.42525091, 0.62391373, 0.1688554],
'con_coefficients':
[0.154328971, 0.535328142, 0.444634542],
'p_con_coefficients': [0.0, 0.0, 0.0]
}]
}]
}
mo_coefficients = [[
0.994216442, 0.025846814, 0.000000000, 0.000000000, -0.004164076,
-0.005583712, -0.005583712
],
[
0.233766661, -0.844456594, 0.000000000,
0.000000000, 0.122829781, -0.155593214,
-0.155593214
],
[
0.000000000, 0.000000000, 0.612692349,
0.000000000, 0.000000000, -0.449221684,
0.449221684
],
[
-0.104033343, 0.538153649, 0.000000000,
0.000000000, 0.755880259, -0.295107107,
-0.295107107
],
[
0.000000000, 0.000000000, 0.000000000,
-1.000000000, 0.000000000, 0.000000000,
0.000000000
],
[
-0.125818566, 0.820120983, 0.000000000,
0.000000000, -0.763538862, -0.769155124,
-0.769155124
],
[
0.000000000, 0.000000000, 0.959800163,
0.000000000, 0.000000000, 0.814629717,
-0.814629717
]]
self.wf_results = WfnSympy(
coordinates=[[0.0000000000, 0.0000000000, -0.0428008531],
[-0.7581074140, 0.0000000000, -0.6785995734],
[0.7581074140, 0.000000000, -0.6785995734]],
symbols=['O', 'H', 'H'],
basis=basis,
alpha_mo_coeff=mo_coefficients[:5],
group='C2v')
self.wf_results.print_alpha_mo_IRD()
class TestWfnsympy(unittest.TestCase):
def setUp(self):
basis = {
'name':
'STO-3G',
'primitive_type':
'gaussian',
'atoms': [{
'symbol':
'O',
'shells': [{
'shell_type':
's',
'p_exponents': [130.70932, 23.808861, 6.4436083],
'con_coefficients':
[0.154328969, 0.535328136, 0.444634536],
'p_con_coefficients': [0.0, 0.0, 0.0]
}, {
'shell_type':
'sp',
'p_exponents': [5.0331513, 1.1695961, 0.380389],
'con_coefficients':
[-0.0999672287, 0.399512825, 0.700115461],
'p_con_coefficients':
[0.155916268, 0.607683714, 0.391957386]
}]
}, {
'symbol':
'H',
'shells': [{
'shell_type':
's',
'p_exponents': [3.42525091, 0.62391373, 0.1688554],
'con_coefficients':
[0.154328971, 0.535328142, 0.444634542],
'p_con_coefficients': [0.0, 0.0, 0.0]
}]
}, {
'symbol':
'H',
'shells': [{
'shell_type':
's',
'p_exponents': [3.42525091, 0.62391373, 0.1688554],
'con_coefficients':
[0.154328971, 0.535328142, 0.444634542],
'p_con_coefficients': [0.0, 0.0, 0.0]
}]
}]
}
mo_coefficients = [[
0.994216442, 0.025846814, 0.000000000, 0.000000000, -0.004164076,
-0.005583712, -0.005583712
],
[
0.233766661, -0.844456594, 0.000000000,
0.000000000, 0.122829781, -0.155593214,
-0.155593214
],
[
0.000000000, 0.000000000, 0.612692349,
0.000000000, 0.000000000, -0.449221684,
0.449221684
],
[
-0.104033343, 0.538153649, 0.000000000,
0.000000000, 0.755880259, -0.295107107,
-0.295107107
],
[
0.000000000, 0.000000000, 0.000000000,
-1.000000000, 0.000000000, 0.000000000,
0.000000000
],
[
-0.125818566, 0.820120983, 0.000000000,
0.000000000, -0.763538862, -0.769155124,
-0.769155124
],
[
0.000000000, 0.000000000, 0.959800163,
0.000000000, 0.000000000, 0.814629717,
-0.814629717
]]
self.wf_results = WfnSympy(
coordinates=[[0.0000000000, 0.0000000000, -0.0428008531],
[-0.7581074140, 0.0000000000, -0.6785995734],
[0.7581074140, 0.000000000, -0.6785995734]],
symbols=['O', 'H', 'H'],
basis=basis,
alpha_mo_coeff=mo_coefficients[:5],
group='C2v')
self.wf_results.print_alpha_mo_IRD()
def test_csm_coef(self):
csm_coef_test = [0, 0, 0, 0]
np.testing.assert_allclose(csm_coef_test,
self.wf_results.csm_coef,
atol=1e-5)
def test_mo_SOEVs_a(self):
mo_soevs_a_test = [[1, 1, 1, 1], [1, 1, 1, 1], [1, -1, 1, -1],
[1, 1, 1, 1], [1, -1, -1, 1]]
self.wf_results.print_overlap_mo_alpha()
np.testing.assert_allclose(mo_soevs_a_test,
self.wf_results.mo_SOEVs_a,
atol=1e-5)
def test_wf_SOEVs_a(self):
wf_soevs_a_test = [1, 1, -1, -1]
np.testing.assert_allclose(wf_soevs_a_test,
self.wf_results.wf_SOEVs_a,
atol=1e-5)
def test_grim_coef(self):
grim_coef_test = [0, 0, 0, 0]
np.testing.assert_allclose(grim_coef_test,
self.wf_results.grim_coef,
atol=1e-5)