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_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 density_fit(mf, auxbasis=None, gs=(10,10,10), with_df=None):
'''Generte density-fitting SCF object
Args:
auxbasis : str or basis dict
Same format to the input attribute mol.basis.
The default basis 'weigend+etb' means weigend-coulomb-fit basis
for light elements and even-tempered basis for heavy elements.
gs : tuple
number of grids in each (+)direction
with_df : MDF object
'''
mf_class = mf.__class__
if with_df is None:
with_df = mdf.MDF(mf.mol)
with_df.max_memory = mf.max_memory
with_df.stdout = mf.stdout
with_df.verbose = mf.verbose
with_df.auxbasis = auxbasis
with_df.gs = gs
class XDFHF(mf_class):
def __init__(self):
self.__dict__.update(mf.__dict__)
self.with_df = with_df
self._keys = self._keys.union(['with_df'])
def get_jk(self, mol=None, dm=None, hermi=1):
if self.with_df:
return get_jk(self.with_df, mol, dm, hermi, self.opt,
True, True)
else:
return mf_class.get_jk(self, mol, dm, hermi)
def get_j(self, mol=None, dm=None, hermi=1):
if self.with_df:
return get_jk(self.with_df, mol, dm, hermi, self.opt,
True, False)[0]
else:
return mf_class.get_j(self, mol, dm, hermi)
def get_k(self, mol=None, dm=None, hermi=1):
if self.with_df:
return get_jk(self.with_df, mol, dm, hermi, self.opt,
False, True)[1]
else:
return mf_class.get_k(self, mol, dm, hermi)
return XDFHF()
#mf0.max_cycle = 0
mf0.kernel()
dm1 = mf0.make_rdm1()
#dm1 = numpy.random.random(dm.shape)
#dm1 = dm1 + dm1.T
#auxbasis = {'C': gto.expand_etbs([[0, 10, .5, 2.], [1, 7, .3, 2.]])}
auxbasis = 'weigend'
#auxbasis = 'sto3g'
#auxbasis = 'tzp'
#auxbasis = {'Fe': gto.mole.uncontract(gto.basis.load('tzp', 'Fe'))}
#auxbasis = mdf._default_basis(mol, addons.aug_etb_for_dfbasis(mol, beta=2.2, start_at=0))
#auxbasis = addons.aug_etb_for_dfbasis(mol, beta=2.2, start_at=0)
auxbasis = None
#auxbasis = addons.aug_etb_for_dfbasis(mol, beta=2.2, start_at=0)
#auxbasis = mdf._default_basis(mol)
#mf = scf.density_fit(scf.RHF(mol), auxbasis)
#mf = with_poisson_(scf.RHF(mol), auxbasis, gs=(50,302))
mf = mdf.MDF(mol).set(auxbasis=auxbasis, gs=(5,)*3).update_mf(scf.RHF(mol))
vj0, vk0 = mf0.get_jk(mol, dm)
vj1, vk1 = mf.get_jk(mol, dm)
print('J', numpy.einsum('ij,ij->', vj1, dm1), 'ref=2495.9843578661084',
'exact', numpy.einsum('ij,ij->', vj0, dm1))
print('K', numpy.einsum('ij,ij->', vk1, dm1), 'ref=426.19988812673307',
'exact', numpy.einsum('ij,ij->', vk0, dm1))
print('J-K', numpy.einsum('ij,ij->', vj1-vk1*.5, dm1), 'ref=2282.8844138027462',
'exact', numpy.einsum('ij,ij->', vj0-vk0*.5, dm1))
exit()
print(mf.scf())