def test_jk_pbc_local_fit(self):
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
jkdf = mdf.MDF(cell)
jkdf.metric = 'S'
jkdf.auxbasis = 'weigend'
jkdf.approx_sr_level = 2
jkdf.gs = (5, ) * 3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.15904061299113, 9)
self.assertAlmostEqual(ek1, 280.2553652304353, 9)
jkdf = mdf.MDF(cell)
jkdf.metric = 'T'
jkdf.approx_sr_level = 3
jkdf.auxbasis = 'weigend'
jkdf.gs = (5, ) * 3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.17554856213894, 9)
self.assertAlmostEqual(ek1, 280.27281092754305, 9)
def test_jk_pbc_local_fit(self):
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
jkdf = mdf.MDF(cell)
jkdf.metric = 'S'
jkdf.auxbasis = 'weigend'
jkdf.approx_sr_level = 2
jkdf.gs = (5,)*3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.15904061299113, 9)
self.assertAlmostEqual(ek1, 280.2553652304353, 9)
jkdf = mdf.MDF(cell)
jkdf.metric = 'T'
jkdf.approx_sr_level = 3
jkdf.auxbasis = 'weigend'
jkdf.gs = (5,)*3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.17554856213894, 9)
self.assertAlmostEqual(ek1, 280.27281092754305, 9)
def test_jk_pbc_local_fit(self):
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
jkdf = mdf.MDF(cell)
jkdf.metric = 'S'
jkdf.auxbasis = 'weigend'
jkdf.approx_sr_level = 2
jkdf.gs = (5,)*3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.17560414134402, 8)
self.assertAlmostEqual(ek1, 280.27525544272237, 8)
jkdf = mdf.MDF(cell)
jkdf.metric = 'T'
jkdf.approx_sr_level = 3
jkdf.auxbasis = 'weigend'
jkdf.gs = (5,)*3
mf = mdf_jk.density_fit(mf0, with_df=jkdf)
vj1, vk1 = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.1790506110278, 8)
self.assertAlmostEqual(ek1, 280.2763653230468, 8)
def test_jk_single_kpt(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', mesh=(11,)*3)
mf.with_df.mesh = [11]*3
mf.with_df.eta = 0.3
mf.with_df.linear_dep_threshold = 1e-7
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698950904264514, 8)
self.assertAlmostEqual(ek1, 31.724297945923094, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.19379703364774, 8)
self.assertAlmostEqual(ek1, 280.28450527230103, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt]).set(auxbasis='weigend')
mydf.linear_dep_threshold = 1e-7
mydf.mesh = [11]*3
mydf.eta = 0.3
vj, vk = mydf.get_jk(dm, 1, kpt, exxdiv='ewald')
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.29955504573206+0j, 8)
self.assertAlmostEqual(ek1, 691.76854602384913+0j, 8)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5,)*3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698923699173982, 9)
self.assertAlmostEqual(ek1, 31.722934801807845, 9)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.17738846073865, 9)
self.assertAlmostEqual(ek1, 280.27434674577881, 9)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 0, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 240.96357256500787, 9)
self.assertAlmostEqual(ek1, 691.41111361623132, 9)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5,)*3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698944426560104, 8)
self.assertAlmostEqual(ek1, 31.723136985575099, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.18066893105836, 8)
self.assertAlmostEqual(ek1, 280.27749933492305, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 1, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 240.96370951556852, 8)
self.assertAlmostEqual(ek1, 691.41117108086291, 8)
def test_jk_single_kpt(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5, ) * 3)
mf.with_df.gs = [5] * 3
mf.with_df.eta = 0.3
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698952864035398, 8)
self.assertAlmostEqual(ek1, 31.724297969652138, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.19367653513683, 8)
self.assertAlmostEqual(ek1, 280.28452000317401, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt]).set(auxbasis='weigend')
mydf.gs = [5] * 3
mydf.eta = 0.3
vj, vk = mydf.get_jk(dm, 1, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.29943526257165 + 0j, 8)
self.assertAlmostEqual(ek1, 691.76856392279456 + 0j, 8)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5, ) * 3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698952864038205, 8)
self.assertAlmostEqual(ek1, 31.724297969654103, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.19367653513686, 8)
self.assertAlmostEqual(ek1, 280.28452000317549, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 1, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.29943526257196 + 0j, 8)
self.assertAlmostEqual(ek1, 691.7685639227974 + 0j, 8)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5, ) * 3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698944426560104, 8)
self.assertAlmostEqual(ek1, 31.723136985575099, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.18066893105836, 8)
self.assertAlmostEqual(ek1, 280.27749933492305, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 1, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 240.96370951556852, 8)
self.assertAlmostEqual(ek1, 691.41117108086291, 8)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5,)*3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698951249368726, 8)
self.assertAlmostEqual(ek1, 31.724431026527277, 8)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao,nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.19444220341163, 8)
self.assertAlmostEqual(ek1, 280.28473250798748, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 1, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.30019902835264+0j, 8)
self.assertAlmostEqual(ek1, 691.76877471308376+0j, 8)
def test_jk(self):
mf = mdf_jk.density_fit(mf0, auxbasis='weigend', gs=(5, ) * 3)
dm = mf.get_init_guess()
vj, vk = mf.get_jk(cell, dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 46.698923699173982, 9)
self.assertAlmostEqual(ek1, 31.722934801807845, 9)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj1, vk1 = mf.get_jk(cell, dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 242.17738846073865, 9)
self.assertAlmostEqual(ek1, 280.27434674577881, 9)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = mdf.MDF(cell, [kpt])
vj, vk = mydf.get_jk(dm, 0, kpt)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 240.96357256500787, 9)
self.assertAlmostEqual(ek1, 691.41111361623132, 9)
def mix_density_fit(self, auxbasis=None, with_df=None):
from pyscf.pbc.df import mdf_jk
return mdf_jk.density_fit(self, auxbasis, with_df=with_df)
def mix_density_fit(self, auxbasis=None, with_df=None):
from pyscf.df.addons import aug_etb_for_dfbasis
from pyscf.pbc.df import mdf_jk
if auxbasis is None:
auxbasis = aug_etb_for_dfbasis(self.cell, beta=1.8, start_at=0)
return mdf_jk.density_fit(self, auxbasis, with_df)
def mix_density_fit(self, auxbasis=None, with_df=None):
from pyscf.pbc.df import mdf_jk
return mdf_jk.density_fit(self, auxbasis, with_df=with_df)
