def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = 'sto-3g'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1], scaled_center=cls.k_c)
# K-points
cls.model_krhf = model_krhf = KRHF(cell, k).density_fit()
model_krhf.with_df._cderi = cls.df_file
model_krhf.conv_tol = 1e-14
model_krhf.kernel()
cls.td_model_krhf = td_model_krhf = ktd.TDRHF(model_krhf)
td_model_krhf.nroots = 10
td_model_krhf.kernel()
cls.gw_model_krhf = gw_model_krhf = kgw.GW(td_model_krhf)
gw_model_krhf.kernel()
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)], [1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1], scaled_center=cls.k_c)
# K-points
cls.model_krhf = model_krhf = KRHF(cell, k).density_fit()
model_krhf.kernel()
# Gamma
cls.td_model_rhf_gamma = gtd.TDRHF(model_krhf)
cls.td_model_rhf_gamma.kernel()
cls.ref_m_gamma = cls.td_model_rhf_gamma.eri.tdhf_full_form()
# Supercell
cls.td_model_rhf_supercell = std.TDRHF(model_krhf)
cls.td_model_rhf_supercell.kernel()
cls.ref_m_supercell = cls.td_model_rhf_supercell.eri.tdhf_full_form()
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)],
[1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1])
# The Gamma-point reference
cls.model_rks = model_rks = KRKS(super_cell(cell, [cls.k, 1, 1]))
model_rks.conv_tol = 1e-14
model_rks.kernel()
# K-points
cls.model_krks = model_krks = KRKS(cell, k)
model_krks.conv_tol = 1e-14
model_krks.kernel()
adjust_mf_phase(model_rks, model_krks)
ke = numpy.concatenate(model_krks.mo_energy)
ke.sort()
# Make sure mo energies are the same
testing.assert_allclose(model_rks.mo_energy[0], ke)
# TD
cls.td_model_rks = td_model_rks = tdp.TDProxy(model_rks, "dft")
td_model_rks.kernel()
cls.td_model_krks = td_model_krks = ktdp.TDProxy(model_krks, "dft", [cls.k, 1, 1], KRKS)
td_model_krks.kernel()
# GW
cls.gw = gw.GW(td_model_rks, td.TDRHF(model_rks).ao2mo())
cls.kgw = kgw.GW(td_model_krks, ktd.TDRHF(model_krks).ao2mo())
cls.order_k, cls.order_p, cls.order = ov_order_supercell(cls.kgw.imds)
orbs = []
for k in range(cls.k):
for o in numpy.arange(2, 6):
orbs.append(numpy.where(numpy.logical_and(cls.order_k == k, cls.order_p == o))[0][0])
cls.gw.orbs = numpy.array(orbs)
cls.kgw.orbs = numpy.arange(2, 6)
def test_class(self):
"""Tests container behavior (frozen vs non-frozen)."""
model = ktd.TDRHF(self.model_krhf, frozen=2)
model.nroots = self.td_model_krhf.nroots
model.kernel()
gw_model = kgw.GW(model)
gw_model.kernel()
testing.assert_allclose(gw_model.mo_energy, self.gw_model_krhf.mo_energy[:, 2:], atol=1e-4)
def test_class(self):
"""Tests container behavior."""
model = ktd.TDRHF(self.model_krhf)
model.nroots = self.td_model_rhf.nroots
assert not model.fast
model.kernel()
testing.assert_allclose(model.e, self.td_model_rhf.e, atol=1e-5)
nocc = nvirt = 4
testing.assert_equal(model.xy.shape,
(len(model.e), 2, 1, 1, nocc, nvirt))
assert_vectors_close(model.xy.squeeze(),
numpy.array(self.td_model_rhf.xy).squeeze(),
atol=1e-9)
def test_class(self):
"""Tests container behavior."""
model = ktd.TDRHF(self.model_krhf)
model.nroots = self.td_model_rhf.nroots
assert not model.fast
model.kernel()
testing.assert_allclose(model.e, self.td_model_rhf.e, atol=1e-5)
nocc = nvirt = 4
testing.assert_equal(model.xy.shape,
(len(model.e), 2, self.k, self.k, nocc, nvirt))
vecs = model.xy.reshape(len(model.xy), -1)[:, self.ov_order]
assert_vectors_close(vecs,
numpy.array(self.td_model_rhf.xy).squeeze(),
atol=1e-5)
# Test real
testing.assert_allclose(model.e.imag, 0, atol=1e-8)
def test_class(self):
"""Tests container behavior."""
model = ktd.TDRHF(self.model_krhf)
model.nroots = self.td_model_krhf.nroots
assert model.fast
model.kernel()
e, xy = model.kernel()
model.fast = False
model.kernel()
# Slow vs fast
testing.assert_allclose(model.e, e)
assert_vectors_close(model.xy, xy)
# ... vs ref
testing.assert_allclose(model.e, self.td_model_krhf.e, atol=1e-5)
assert_vectors_close(model.xy.squeeze(),
numpy.array(self.td_model_krhf.xy).squeeze(),
atol=1e-12)
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)], [1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1], scaled_center=cls.k_c)
# K-points
cls.model_krhf = model_krhf = KRHF(cell, k).density_fit()
model_krhf.conv_tol = 1e-14
model_krhf.kernel()
ke = numpy.concatenate(model_krhf.mo_energy)
ke.sort()
# Make sure no degeneracies are present
testing.assert_array_less(1e-4, ke[1:] - ke[:-1])
# TD
cls.td_model_srhf = td_model_srhf = std.TDRHF(model_krhf)
td_model_srhf.kernel()
cls.td_model_krhf = td_model_krhf = ktd.TDRHF(model_krhf)
td_model_krhf.kernel()
# adjust_td_phase(td_model_srhf, td_model_krhf)
# GW
cls.gw = sgw.GW(td_model_srhf)
cls.kgw = kgw.GW(td_model_krhf)
def test_imds_frozen(self):
"""Tests intermediates: frozen vs non-frozen."""
frozen = 2
sample_ref = (0, 2)
sample_frozen = (0, 0)
td = ktd.TDRHF(self.model_krhf, frozen=frozen)
td.nroots = self.td_model_krhf.nroots
td.kernel()
adjust_td_phase(self.td_model_krhf, td)
testing.assert_allclose(self.td_model_krhf.e, td.e, atol=1e-4)
testing.assert_allclose(self.td_model_krhf.xy[..., 2:, :], td.xy, atol=1e-3)
gw_frozen = kgw.GW(td)
gw_frozen.kernel()
selection = gw_frozen.imds.eri.space
selection_o = numpy.concatenate(tuple(i[:j] for i, j in zip(selection, self.gw_model_krhf.imds.eri.nocc)))
selection_v = numpy.concatenate(tuple(i[j:] for i, j in zip(selection, self.gw_model_krhf.imds.eri.nocc)))
selection = numpy.concatenate([selection_o, selection_v])
imd_ref = self.gw_model_krhf.imds.tdm[..., selection, :][..., selection]
testing.assert_allclose(gw_frozen.imds.tdm, imd_ref, atol=1e-4)
test_energies = numpy.linspace(-2, 3, 300)
ref_samples = numpy.array(tuple(
self.gw_model_krhf.imds.get_sigma_element(i, sample_ref, 0.01)
for i in test_energies
))
frozen_samples = numpy.array(tuple(
gw_frozen.imds.get_sigma_element(i, sample_frozen, 0.01)
for i in test_energies
))
testing.assert_allclose(ref_samples, frozen_samples, atol=1e-4)
testing.assert_allclose(
self.gw_model_krhf.imds.get_rhs(sample_ref),
gw_frozen.imds.get_rhs(sample_frozen),
atol=1e-14,
)
def test_class(self):
"""Tests container behavior (frozen vs non-frozen)."""
for frozen in (1, [0, 1]):
try:
model = ktd.TDRHF(self.model_krhf, frozen=frozen)
model.nroots = self.td_model_krhf.nroots
model.kernel()
mask_o, mask_v = tdhf_frozen_mask(model.eri, kind="o,v")
testing.assert_allclose(model.e,
self.td_model_krhf.e,
atol=1e-4)
assert_vectors_close(
model.xy,
numpy.array(self.td_model_krhf.xy)[..., mask_o, :][...,
mask_v],
atol=1e-3,
)
except Exception:
print(
"When testing class with frozen={} the following exception occurred:"
.format(repr(frozen)))
raise
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)], [1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1])
# K-points
cls.model_krks = model_krks = KRKS(cell, k)
model_krks.conv_tol = 1e-14
model_krks.kernel()
# TD
cls.td_model_srks = td_model_srks = stdp.TDProxy(
model_krks, "dft", [cls.k, 1, 1], KRKS)
td_model_srks.kernel()
cls.td_model_krks = td_model_krks = ktdp.TDProxy(
model_krks, "dft", [cls.k, 1, 1], KRKS)
td_model_krks.kernel()
# GW
cls.gw = sgw.GW(td_model_srks, std.TDRHF(model_krks).ao2mo())
cls.kgw = kgw.GW(td_model_krks, ktd.TDRHF(model_krks).ao2mo())
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)], [1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1])
# K-points
cls.model_krhf = model_krhf = KRHF(cell, k).density_fit()
model_krhf.conv_tol = 1e-14
model_krhf.kernel()
# Add random phases
numpy.random.seed(0)
for i in model_krhf.mo_coeff:
i *= numpy.exp(2.j * numpy.pi *
numpy.random.rand(i.shape[1]))[numpy.newaxis, :]
# The slow supercell KTDHF
cls.td_model_krhf = td_model_krhf = krhf_slow_supercell.TDRHF(
model_krhf)
td_model_krhf.kernel()
cls.ref_m = td_model_krhf.eri.tdhf_full_form()
def setUpClass(cls):
cls.cell = cell = Cell()
# Lift some degeneracies
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.67 1.68 1.69
'''
cell.basis = {'C': [[0, (0.8, 1.0)],
[1, (1.0, 1.0)]]}
# cell.basis = 'gth-dzvp'
cell.pseudo = 'gth-pade'
cell.a = '''
0.000000000, 3.370137329, 3.370137329
3.370137329, 0.000000000, 3.370137329
3.370137329, 3.370137329, 0.000000000'''
cell.unit = 'B'
cell.verbose = 5
cell.build()
k = cell.make_kpts([cls.k, 1, 1], scaled_center=cls.k_c)
# The Gamma-point reference
cls.model_rhf = model_rhf = RHF(super_cell(cell, [cls.k, 1, 1]), kpt=k[0]).density_fit()
model_rhf.conv_tol = 1e-14
model_rhf.kernel()
# K-points
cls.model_krhf = model_krhf = KRHF(cell, k).density_fit()
model_krhf.conv_tol = 1e-14
model_krhf.kernel()
adjust_mf_phase(model_rhf, model_krhf)
ke = numpy.concatenate(model_krhf.mo_energy)
ke.sort()
# Make sure mo energies are the same
testing.assert_allclose(model_rhf.mo_energy, ke)
# Make sure no degeneracies are present
testing.assert_array_less(1e-4, ke[1:] - ke[:-1])
# TD
cls.td_model_rhf = td_model_rhf = td.TDRHF(model_rhf)
td_model_rhf.kernel()
cls.td_model_krhf = td_model_krhf = ktd.TDRHF(model_krhf)
td_model_krhf.kernel()
adjust_td_phase(td_model_rhf, td_model_krhf)
# GW
cls.gw = gw.GW(td_model_rhf)
cls.kgw = kgw.GW(td_model_krhf)
cls.order_k, cls.order_p, cls.order = ov_order_supercell(cls.kgw.imds)
orbs = []
for k in range(cls.k):
for o in numpy.arange(2, 6):
orbs.append(numpy.where(numpy.logical_and(cls.order_k == k, cls.order_p == o))[0][0])
cls.gw.orbs = numpy.array(orbs)
cls.kgw.orbs = numpy.arange(2, 6)