def test_jk_metric(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
jkdf = mdf.MDF(mol)
jkdf.metric = 'S'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, 9.5034429456575253e-5, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, -4.759826947520196e-5, 9)
jkdf = mdf.MDF(mol)
jkdf.metric = 'T'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, 0.005304754655668375, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, 0.076335586801803856, 9)
jkdf = mdf.MDF(mol)
jkdf.metric = 'J'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, -6.56455759013852e-5, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, -4.965601597461955e-5, 9)
def test_rhf_0d(self):
from pyscf.df import mdf_jk
from pyscf.scf import hf
L = 4
cell = pbcgto.Cell()
cell.build(unit = 'B',
a = numpy.eye(3)*L*5,
gs = [10]*3,
atom = '''He 2 2 2; He 2 2 3''',
dimension = 0,
verbose = 0,
basis = { 'He': [[0, (0.8, 1.0)],
[0, (1.0, 1.0)],
[0, (1.2, 1.0)]]})
mol = cell.to_mol()
mf = mdf_jk.density_fit(hf.RHF(mol))
mf.with_df.gs = [10]*3
mf.with_df.auxbasis = {'He':[[0, (1e6, 1)]]}
mf.with_df.charge_constraint = False
mf.with_df.metric = 'S'
eref = mf.kernel()
mf = pbchf.RHF(cell)
mf.with_df = pdf.PWDF(cell)
mf.get_hcore = lambda *args: hf.get_hcore(mol)
mf.energy_nuc = lambda *args: mol.energy_nuc()
e1 = mf.kernel()
self.assertAlmostEqual(e1, eref, 8)
def test_rhf_0d(self):
from pyscf.df import mdf_jk
from pyscf.scf import hf
L = 4
cell = pbcgto.Cell()
cell.build(
unit='B',
a=numpy.eye(3) * L * 5,
gs=[10] * 3,
atom='''He 2 2 2; He 2 2 3''',
dimension=0,
verbose=0,
basis={'He': [[0, (0.8, 1.0)], [0, (1.0, 1.0)], [0, (1.2, 1.0)]]})
mol = cell.to_mol()
mf = mdf_jk.density_fit(hf.RHF(mol))
mf.with_df.gs = [10] * 3
mf.with_df.auxbasis = {'He': [[0, (1e6, 1)]]}
mf.with_df.charge_constraint = False
mf.with_df.metric = 'S'
eref = mf.kernel()
mf = pbchf.RHF(cell)
mf.with_df = pdf.PWDF(cell)
mf.exxdiv = None
mf.get_hcore = lambda *args: hf.get_hcore(mol)
mf.energy_nuc = lambda *args: mol.energy_nuc()
e1 = mf.kernel()
self.assertAlmostEqual(e1, eref, 8)
def test_j(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
mf = mdf_jk.density_fit(scf.RHF(mol), auxbasis='weigend', gs=(10,)*3)
vj1 = mf.get_j(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm), 50.470715659848707, 9)
def test_jk_charge_constraint(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, 0.0003166388141693232, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, 0.0005799101835037845, 9)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.metric = 'T'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, 0.12360821384800857, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, 0.4701984522179572, 9)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.metric = 'J'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, -6.3466650786381251e-5, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, -4.5425207332527862e-5, 9)
def test_j(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
mf = mdf_jk.density_fit(scf.RHF(mol),
auxbasis='weigend',
gs=(10, ) * 3)
vj1 = mf.get_j(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm),
50.470715659848707, 9)
def test_jk(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
#mf = poisson_jk.with_poisson_(scf.RHF(mol), auxbasis='weigend', gs=(10,)*3)
mf = mdf_jk.density_fit(scf.RHF(mol), auxbasis='weigend', gs=(10,)*3)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm), 50.470715659848707, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm), 66.448255856461131, 9)
vk1 = mf.get_k(mol, dm, hermi=0)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm), 66.448255856461131, 9)
def test_jk_metric(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
jkdf = mdf.MDF(mol)
jkdf.metric = 'S'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, 9.5034429456575253e-5, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, -4.759826947520196e-5, 9)
jkdf = mdf.MDF(mol)
jkdf.metric = 'T'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, 0.005304754655668375, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, 0.076335586801803856, 9)
jkdf = mdf.MDF(mol)
jkdf.metric = 'J'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10, ) * 3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, -6.56455759013852e-5, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, -4.965601597461955e-5, 9)
def test_jk_hermi0(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
dm[:2,-3:] *= .5
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm, hermi=0)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
mf = mdf_jk.density_fit(scf.RHF(mol), auxbasis='weigend', gs=(10,)*3)
vj1, vk1 = mf.get_jk(mol, dm, hermi=0)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, 0.00010173096167420681, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, -6.4503261583581661e-5, 9)
def test_jk_charge_constraint(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, 0.0003166388141693232, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, 0.0005799101835037845, 9)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.metric = 'T'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, 0.12360821384800857, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, 0.4701984522179572, 9)
jkdf = mdf.MDF(mol)
jkdf.charge_constraint = False
jkdf.metric = 'J'
jkdf.auxbasis = 'weigend'
jkdf.gs = (10,)*3
mf = mdf_jk.density_fit(scf.RHF(mol), with_df=jkdf)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm)-ej0, -6.3466650786381251e-5, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm)-ek0, -4.5425207332527862e-5, 9)
def test_jk_hermi0(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
dm[:2, -3:] *= .5
vj0, vk0 = scf.RHF(mol).get_jk(mol, dm, hermi=0)
ej0 = numpy.einsum('ij,ij->', vj0, dm)
ek0 = numpy.einsum('ij,ij->', vk0, dm)
mf = mdf_jk.density_fit(scf.RHF(mol),
auxbasis='weigend',
gs=(10, ) * 3)
vj1, vk1 = mf.get_jk(mol, dm, hermi=0)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vj1, dm) - ej0, 0.00010173096167420681, 9)
self.assertAlmostEqual(
numpy.einsum('ij,ij->', vk1, dm) - ek0, -6.4503261583581661e-5, 9)
def test_jk(self):
numpy.random.seed(12)
nao = mol.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
#mf = poisson_jk.with_poisson_(scf.RHF(mol), auxbasis='weigend', gs=(10,)*3)
mf = mdf_jk.density_fit(scf.RHF(mol),
auxbasis='weigend',
gs=(10, ) * 3)
vj1, vk1 = mf.get_jk(mol, dm)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vj1, dm),
50.470715659848707, 9)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm),
66.448255856461131, 9)
vk1 = mf.get_k(mol, dm, hermi=0)
self.assertAlmostEqual(numpy.einsum('ij,ij->', vk1, dm),
66.448255856461131, 9)
def update_mf(self, mf):
from pyscf.df import mdf_jk
return mdf_jk.density_fit(mf, self.auxbasis, self.gs, with_df=self)
