def test_jk(self):
mf0 = scf.RHF(cell)
dm = mf0.get_init_guess()
mydf = pwdf.PWDF(cell)
mydf.gs = [5] * 3
vj, vk = mydf.get_jk(dm)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 3.0455881073561235, 9)
self.assertAlmostEqual(ek1, 7.7905480251964629, 9)
numpy.random.seed(12)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao))
dm = dm + dm.T
vj1, vk1 = mydf.get_jk(dm, hermi=0)
ej1 = numpy.einsum('ij,ji->', vj1, dm)
ek1 = numpy.einsum('ij,ji->', vk1, dm)
self.assertAlmostEqual(ej1, 12.234106555081793, 9)
self.assertAlmostEqual(ek1, 43.988705494650802, 9)
numpy.random.seed(1)
kpt = numpy.random.random(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, 12.233546641482697, 9)
self.assertAlmostEqual(ek1, 43.946958026023722, 9)
def test_pwdf_k(self):
kpts = cell.get_abs_kpts([[-.25, -.25, -.25], [-.25, -.25, .25],
[-.25, .25, -.25], [-.25, .25, .25],
[.25, -.25, -.25], [.25, -.25, .25],
[.25, .25, -.25], [.25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8, nao, nao))
mydf = pwdf.PWDF(cell)
mydf.kpts = kpts
mydf.auxbasis = 'weigend'
vk = pwdf_jk.get_k_kpts(mydf, dm, 0, mydf.kpts)
self.assertAlmostEqual(finger(
vk[0]), (4.3373802352168278 - 0.062977052131451577j) / 8, 9)
self.assertAlmostEqual(finger(vk[1]),
(2.878809181709983 + 0.028843869853690692j) / 8,
9)
self.assertAlmostEqual(finger(
vk[2]), (3.7027622609953061 - 0.052034330663180237j) / 8, 9)
self.assertAlmostEqual(finger(
vk[3]), (5.0939994842559422 + 0.060094478876149444j) / 8, 9)
self.assertAlmostEqual(finger(
vk[4]), (4.2942087551592651 - 0.061138484763336887j) / 8, 9)
self.assertAlmostEqual(finger(
vk[5]), (3.9689429688683679 + 0.048471952758750547j) / 8, 9)
self.assertAlmostEqual(finger(
vk[6]), (3.6342630872923456 - 0.054892635365850449j) / 8, 9)
self.assertAlmostEqual(finger(
vk[7]), (3.3483735224533548 + 0.040877095049528467j) / 8, 9)
def test_pwdf_get_nuc(self):
v0 = fft.DF(cell).get_nuc(kpts[0])
df = pwdf.PWDF(cell)
v1 = df.get_nuc(kpts[0])
self.assertTrue(np.allclose(v0, v1, atol=1e-4, rtol=1e-4))
self.assertAlmostEqual(finger(v1),
(-5.7646030917912663 + 0.19126291999423831j), 8)
def test_get_eri_0123(self):
odf = pwdf.PWDF(cell1)
ref = kdf0.get_eri(kpts)
eri1111 = odf.get_eri(kpts)
self.assertTrue(np.allclose(eri1111, ref, atol=1e-8, rtol=1e-8))
self.assertAlmostEqual(finger(eri1111),
(1.2917759427391706 - 0.013340252488069412j), 9)
ref = fft.DF(cell1).get_mo_eri([numpy.eye(cell1.nao_nr())] * 4, kpts)
self.assertTrue(np.allclose(eri1111, ref, atol=1e-8, rtol=1e-8))
def get_hcore(self, cell=None, kpts=None):
if cell is None: cell = self.cell
if kpts is None:
kpts_lst = numpy.zeros((1,3))
else:
kpts_lst = numpy.reshape(kpts, (-1,3))
xcell, contr_coeff = self.get_xmol(cell)
with_df = pwdf.PWDF(xcell)
c = lib.param.LIGHT_SPEED
assert('1E' in self.approx.upper())
if 'ATOM' in self.approx.upper():
atom_slices = xcell.offset_nr_by_atom()
nao = xcell.nao_nr()
x = numpy.zeros((nao,nao))
vloc = numpy.zeros((nao,nao))
wloc = numpy.zeros((nao,nao))
for ia in range(xcell.natm):
ish0, ish1, p0, p1 = atom_slices[ia]
shls_slice = (ish0, ish1, ish0, ish1)
t1 = xcell.intor('cint1e_kin_sph', shls_slice=shls_slice)
v1 = xcell.intor('cint1e_nuc_sph', shls_slice=shls_slice)
s1 = xcell.intor('cint1e_ovlp_sph', shls_slice=shls_slice)
w1 = xcell.intor('cint1e_pnucp_sph', shls_slice=shls_slice)
vloc[p0:p1,p0:p1] = v1
wloc[p0:p1,p0:p1] = w1
x[p0:p1,p0:p1] = x2c._x2c1e_xmatrix(t1, v1, w1, s1, c)
else:
raise NotImplementedError
t = xcell.pbc_intor('cint1e_kin_sph', 1, lib.HERMITIAN, kpts_lst)
s = xcell.pbc_intor('cint1e_ovlp_sph', 1, lib.HERMITIAN, kpts_lst)
v = with_df.get_nuc(kpts_lst)
#w = get_pnucp(with_df, kpts_lst)
if self.basis is not None:
s22 = s
s21 = pbcgto.intor_cross('cint1e_ovlp_sph', xcell, cell, kpts=kpts_lst)
h1_kpts = []
for k in range(len(kpts_lst)):
#h1 = x2c._get_hcore_fw(t[k], vloc, wloc, s[k], x, c) - vloc + v[k]
#h1 = x2c._get_hcore_fw(t[k], v[k], w[k], s[k], x, c)
h1 = x2c._get_hcore_fw(t[k], v[k], wloc, s[k], x, c)
if self.basis is not None:
c = lib.cho_solve(s22[k], s21[k])
h1 = reduce(numpy.dot, (c.T, h1, c))
if self.xuncontract and contr_coeff is not None:
h1 = reduce(numpy.dot, (contr_coeff.T, h1, contr_coeff))
h1_kpts.append(h1)
if kpts is None or numpy.shape(kpts) == (3,):
h1_kpts = h1_kpts[0]
return lib.asarray(h1_kpts)
def test_pwdf_k(self):
kpts = cell.make_kpts((2, 2, 2))
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8, nao, nao))
mydf = pwdf.PWDF(cell)
mydf.kpts = kpts
mydf.auxbasis = 'weigend'
vk = pwdf_jk.get_k_kpts(mydf, dm, 0, mydf.kpts)
self.assertAlmostEqual(finger(
vk[0]), (4.3373802352168278 - 0.062977052131451577j) / 8, 9)
self.assertAlmostEqual(finger(vk[1]),
(2.878809181709983 + 0.028843869853690692j) / 8,
9)
self.assertAlmostEqual(finger(
vk[2]), (3.7027622609953061 - 0.052034330663180237j) / 8, 9)
self.assertAlmostEqual(finger(
vk[3]), (5.0939994842559422 + 0.060094478876149444j) / 8, 9)
self.assertAlmostEqual(finger(
vk[4]), (4.2942087551592651 - 0.061138484763336887j) / 8, 9)
self.assertAlmostEqual(finger(
vk[5]), (3.9689429688683679 + 0.048471952758750547j) / 8, 9)
self.assertAlmostEqual(finger(
vk[6]), (3.6342630872923456 - 0.054892635365850449j) / 8, 9)
self.assertAlmostEqual(finger(
vk[7]), (3.3483735224533548 + 0.040877095049528467j) / 8, 9)
numpy.random.seed(1)
dm = numpy.random.random((8, nao, nao))
dm = dm + dm.transpose(0, 2, 1)
vk = pwdf_jk.get_k_kpts(mydf, dm, 1, mydf.kpts)
self.assertAlmostEqual(finger(vk[0]),
(8.7518173818250702 - 0.11793770445839372j) / 8,
9)
self.assertAlmostEqual(finger(
vk[1]), (5.7682393685317894 + 0.069482280306391239j) / 8, 9)
self.assertAlmostEqual(finger(
vk[2]), (7.1890462727492324 - 0.088727079644645671j) / 8, 9)
self.assertAlmostEqual(finger(vk[3]),
(10.08358152800003 + 0.1278144339422369j) / 8,
9)
self.assertAlmostEqual(finger(vk[4]),
(8.393281242945573 - 0.099410704957774876j) / 8,
9)
self.assertAlmostEqual(finger(vk[5]),
(7.9413682328898769 + 0.1015563120870652j) / 8,
9)
self.assertAlmostEqual(finger(
vk[6]), (7.3743790120272408 - 0.096290683129384574j) / 8, 9)
self.assertAlmostEqual(finger(vk[7]),
(6.8144379626901443 + 0.08071261392857812j) / 8,
9)
def test_eri1111(self):
kpts = numpy.random.random((4, 3)) * .25
kpts[3] = -numpy.einsum('ij->j', kpts[:3])
with_df = pwdf.PWDF(cell)
with_df.kpts = kpts
mo = (numpy.random.random((nao, nao)) + numpy.random.random(
(nao, nao)) * 1j)
eri = with_df.get_eri(kpts).reshape((nao, ) * 4)
eri0 = numpy.einsum('pjkl,pi->ijkl', eri, mo.conj())
eri0 = numpy.einsum('ipkl,pj->ijkl', eri0, mo)
eri0 = numpy.einsum('ijpl,pk->ijkl', eri0, mo.conj())
eri0 = numpy.einsum('ijkp,pl->ijkl', eri0, mo)
eri1 = with_df.ao2mo(mo, kpts)
self.assertAlmostEqual(
abs(eri1.reshape(eri0.shape) - eri0).sum(), 0, 9)
def test_pwdf_get_pp(self):
v0 = pgto.pseudo.get_pp(cell, kpts[0])
v1 = pwdf.PWDF(cell).get_pp(kpts)
self.assertTrue(np.allclose(v0, v1[0], atol=1e-5, rtol=1e-5))
self.assertAlmostEqual(finger(v1[0]),
(-5.6240305085898807 + 0.22094834207603817j), 8)
v0 = pgto.pseudo.get_pp(cell, kpts[1])
self.assertTrue(np.allclose(v0, v1[1], atol=1e-5, rtol=1e-5))
self.assertAlmostEqual(finger(v1[1]),
(-5.53877585793 + 1.043933371359j), 8)
self.assertAlmostEqual(finger(v1[2]),
(-6.05309558678 + 0.281728966073j), 8)
self.assertAlmostEqual(finger(v1[3]),
(-5.60115995450 + 0.275973062529j), 8)
def test_pwdf_get_pp(self):
v0 = pgto.pseudo.get_pp(cell, kpts[0])
v1 = pwdf.PWDF(cell).get_pp(kpts)
self.assertTrue(np.allclose(v0, v1[0], atol=1e-6, rtol=1e-6))
self.assertAlmostEqual(finger(v1[0]),
(-5.6240249381230019 + 0.22094834207065794j), 8)
v0 = pgto.pseudo.get_pp(cell, kpts[1])
self.assertTrue(np.allclose(v0, v1[1], atol=1e-6, rtol=1e-6))
self.assertAlmostEqual(finger(v1[1]),
(-5.53877028746 + 1.04393337137j), 8)
self.assertAlmostEqual(finger(v1[2]),
(-6.05309001635 + 0.281728966125j), 8)
self.assertAlmostEqual(finger(v1[3]),
(-5.60115438406 + 0.275973062578j), 8)
def test_get_eri_0011(self):
odf = pwdf.PWDF(cell1)
ref = kdf0.get_eri((kpts[0], kpts[0], kpts[1], kpts[1]))
eri0011 = odf.get_eri((kpts[0], kpts[0], kpts[1], kpts[1]))
self.assertTrue(np.allclose(eri0011, ref, atol=1e-3, rtol=1e-3))
self.assertAlmostEqual(finger(eri0011),
(1.2410162858084512 + 0.00074485383749912936j),
9)
ref = fft.FFTDF(cell1).get_mo_eri([numpy.eye(cell1.nao_nr())] * 4,
(kpts[0], kpts[0], kpts[1], kpts[1]))
eri0011 = odf.get_eri((kpts[0], kpts[0], kpts[1], kpts[1]))
self.assertTrue(np.allclose(eri0011, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri0011),
(1.2410162860852818 + 0.00074485383748954838j),
9)
def test_pwdf_j(self):
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((4, nao, nao))
dm = dm + dm.transpose(0, 2, 1)
mydf = pwdf.PWDF(cell)
mydf.kpts = numpy.random.random((4, 3))
mydf.gs = numpy.asarray((5, ) * 3)
mydf.auxbasis = 'weigend'
vj = pwdf_jk.get_j_kpts(mydf, dm, 1, mydf.kpts)
self.assertAlmostEqual(finger(
vj[0]), (0.93946193432413905 + 0.00010862804196223034j) / 4, 9)
self.assertAlmostEqual(finger(
vj[1]), (0.94866073525335626 + 0.005571199307452865j) / 4, 9)
self.assertAlmostEqual(finger(
vj[2]), (1.1492194255929766 + 0.0093705761598793739j) / 4, 9)
self.assertAlmostEqual(finger(
vj[3]), (1.1397493412770023 + 0.010731970529096637j) / 4, 9)
def test_pwdf_get_ao_eri(self):
df0 = fft.FFTDF(cell)
df = pwdf.PWDF(cell)
eri0 = df0.get_ao_eri(compact=True)
eri1 = df.get_ao_eri(compact=True)
self.assertTrue(np.allclose(eri0, eri1, atol=1e-5, rtol=1e-5))
self.assertAlmostEqual(finger(eri1), 0.80425361966560172, 8)
eri0 = df0.get_ao_eri(kpts[0])
eri1 = df.get_ao_eri(kpts[0])
self.assertTrue(np.allclose(eri0, eri1, atol=1e-5, rtol=1e-5))
self.assertAlmostEqual(finger(eri1),
(2.9346374476387949 - 0.20479054936779137j), 8)
eri0 = df0.get_ao_eri(kpts)
eri1 = df.get_ao_eri(kpts)
self.assertTrue(np.allclose(eri0, eri1, atol=1e-5, rtol=1e-5))
self.assertAlmostEqual(finger(eri1),
(0.33709287302019619 - 0.94185725020966538j), 8)
def test_eri0000(self):
with_df = pwdf.PWDF(cell)
with_df.kpts = numpy.zeros((4, 3))
mo = (numpy.random.random((nao, nao)) + numpy.random.random(
(nao, nao)) * 1j)
eri = ao2mo.restore(1, with_df.get_eri(with_df.kpts), nao)
eri0 = numpy.einsum('pjkl,pi->ijkl', eri, mo.conj())
eri0 = numpy.einsum('ipkl,pj->ijkl', eri0, mo)
eri0 = numpy.einsum('ijpl,pk->ijkl', eri0, mo.conj())
eri0 = numpy.einsum('ijkp,pl->ijkl', eri0, mo)
eri1 = with_df.ao2mo(mo, with_df.kpts)
self.assertAlmostEqual(
abs(eri1.reshape(eri0.shape) - eri0).sum(), 0, 9)
mo = mo.real
eri0 = numpy.einsum('pjkl,pi->ijkl', eri, mo.conj())
eri0 = numpy.einsum('ipkl,pj->ijkl', eri0, mo)
eri0 = numpy.einsum('ijpl,pk->ijkl', eri0, mo.conj())
eri0 = numpy.einsum('ijkp,pl->ijkl', eri0, mo)
eri1 = with_df.ao2mo(mo, with_df.kpts, compact=False)
self.assertAlmostEqual(
abs(eri1.reshape(eri0.shape) - eri0).sum(), 0, 9)
def test_get_eri_0110(self):
odf = pwdf.PWDF(cell1)
ref = kdf0.get_eri((kpts[0], kpts[1], kpts[1], kpts[0]))
eri0110 = odf.get_eri((kpts[0], kpts[1], kpts[1], kpts[0]))
self.assertTrue(np.allclose(eri0110, ref, atol=1e-6, rtol=1e-6))
eri0110 = odf.get_eri(
(kpts[0] + 1e-8, kpts[1] + 1e-8, kpts[1], kpts[0]))
self.assertTrue(np.allclose(eri0110, ref, atol=1e-6, rtol=1e-6))
self.assertAlmostEqual(finger(eri0110),
(1.2928399254827956 - 0.011820590601969154j), 9)
ref = fft.FFTDF(cell1).get_mo_eri([numpy.eye(cell1.nao_nr())] * 4,
(kpts[0], kpts[1], kpts[1], kpts[0]))
eri0110 = odf.get_eri((kpts[0], kpts[1], kpts[1], kpts[0]))
self.assertTrue(np.allclose(eri0110, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri0110),
(1.2928399254827956 - 0.011820590601969154j), 9)
eri0110 = odf.get_eri(
(kpts[0] + 1e-8, kpts[1] + 1e-8, kpts[1], kpts[0]))
self.assertTrue(np.allclose(eri0110, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri0110),
(1.2928399254827956 - 0.011820590601969154j), 9)
def test_get_eri_gamma(self):
odf = pwdf.PWDF(cell1)
ref = odf.get_eri(compact=True)
df = fft.DF(cell1)
eri0000 = df.get_eri(compact=True)
self.assertTrue(eri0000.dtype == numpy.double)
self.assertTrue(np.allclose(eri0000, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri0000), 0.23714016293926865, 9)
ref = odf.get_eri((kpts[0], kpts[0], kpts[0], kpts[0]))
eri1111 = df.get_eri((kpts[0], kpts[0], kpts[0], kpts[0]))
self.assertTrue(np.allclose(eri1111, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri1111),
(1.2410388899583582 - 5.2370501878355006e-06j),
9)
eri1111 = df.get_eri(
(kpts[0] + 1e-8, kpts[0] + 1e-8, kpts[0], kpts[0]))
self.assertTrue(np.allclose(eri1111, ref, atol=1e-9, rtol=1e-9))
self.assertAlmostEqual(finger(eri1111),
(1.2410388899583582 - 5.2370501878355006e-06j),
9)
def test_pwdf_k1(self):
kpts = cell.get_abs_kpts([[-.25, -.25, -.25], [-.25, -.25, .25],
[-.25, .25, -.25], [-.25, .25, .25],
[.25, -.25, -.25], [.25, -.25, .25],
[.25, .25, -.25], [.25, .25, .25]])
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((8, nao, nao))
mydf = pwdf.PWDF(cell)
mydf.kpts = kpts
mydf.auxbasis = 'weigend'
numpy.random.seed(1)
dm = numpy.random.random((8, nao, nao))
dm = dm + dm.transpose(0, 2, 1)
vk = pwdf_jk.get_k_kpts(mydf, dm, 1, mydf.kpts)
self.assertAlmostEqual(finger(vk[0]),
(8.7518173818250702 - 0.11793770445839372j) / 8,
9)
self.assertAlmostEqual(finger(
vk[1]), (5.7682393685317894 + 0.069482280306391239j) / 8, 9)
self.assertAlmostEqual(finger(
vk[2]), (7.1890462727492324 - 0.088727079644645671j) / 8, 9)
self.assertAlmostEqual(finger(vk[3]),
(10.08358152800003 + 0.1278144339422369j) / 8,
9)
self.assertAlmostEqual(finger(vk[4]),
(8.393281242945573 - 0.099410704957774876j) / 8,
9)
self.assertAlmostEqual(finger(vk[5]),
(7.9413682328898769 + 0.1015563120870652j) / 8,
9)
self.assertAlmostEqual(finger(
vk[6]), (7.3743790120272408 - 0.096290683129384574j) / 8, 9)
self.assertAlmostEqual(finger(vk[7]),
(6.8144379626901443 + 0.08071261392857812j) / 8,
9)
def test_pwdf_get_nuc(self):
df = pwdf.PWDF(cell)
v1 = df.get_nuc(kpts[0])
self.assertAlmostEqual(finger(v1),
(-6.0893491060887159 + 0.19823828749533859j), 8)
from pyscf.pbc import scf as pscf
from pyscf.pbc.df import pwdf
L = 5.
n = 5
cell = pgto.Cell()
cell.a = numpy.diag([L, L, L])
cell.gs = numpy.array([n, n, n])
cell.atom = '''He 3. 2. 3.
He 1. 1. 1.'''
#cell.basis = {'He': [[0, (1.0, 1.0)]]}
#cell.basis = '631g'
#cell.basis = {'He': [[0, (2.4, 1)], [1, (1.1, 1)]]}
cell.basis = 'ccpvdz'
cell.verbose = 0
cell.build(0, 0)
cell.verbose = 5
df = pwdf.PWDF(cell)
df.gs = (15, ) * 3
dm = pscf.RHF(cell).get_init_guess()
vj, vk = df.get_jk(cell, dm)
print(numpy.einsum('ij,ji->', df.get_nuc(cell), dm),
'ref=-10.384051732669329')
df.analytic_ft = True
#print(numpy.einsum('ij,ji->', vj, dm), 'ref=5.3766911667862516')
#print(numpy.einsum('ij,ji->', vk, dm), 'ref=8.2255177602309022')
print(numpy.einsum('ij,ji->', df.get_nuc(cell), dm),
'ref=-10.447018516011319')
def test_get_mo_eri(self):
df0 = fft.FFTDF(cell)
odf = pwdf.PWDF(cell)
nao = cell.nao_nr()
numpy.random.seed(5)
mo = (numpy.random.random((nao, nao)) + numpy.random.random(
(nao, nao)) * 1j)
eri_mo0 = df0.get_mo_eri((mo, ) * 4, kpts)
eri_mo1 = odf.get_mo_eri((mo, ) * 4, kpts)
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
kpts_t = (kpts[2], kpts[3], kpts[0], kpts[1])
eri_mo2 = df0.get_mo_eri((mo, ) * 4, kpts_t)
eri_mo2 = eri_mo2.reshape(
(nao, ) * 4).transpose(2, 3, 0, 1).reshape(nao**2, -1)
self.assertTrue(np.allclose(eri_mo2, eri_mo0, atol=1e-7, rtol=1e-7))
eri_mo0 = df0.get_mo_eri((mo, ) * 4, (kpts[0], ) * 4)
eri_mo1 = odf.get_mo_eri((mo, ) * 4, (kpts[0], ) * 4)
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
eri_mo0 = df0.get_mo_eri((mo, ) * 4, (
kpts[0],
kpts[1],
kpts[1],
kpts[0],
))
eri_mo1 = odf.get_mo_eri((mo, ) * 4, (
kpts[0],
kpts[1],
kpts[1],
kpts[0],
))
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
eri_mo0 = df0.get_mo_eri((mo, ) * 4, (
kpt0,
kpt0,
kpts[0],
kpts[0],
))
eri_mo1 = odf.get_mo_eri((mo, ) * 4, (
kpt0,
kpt0,
kpts[0],
kpts[0],
))
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
eri_mo0 = df0.get_mo_eri((mo, ) * 4, (
kpts[0],
kpts[0],
kpt0,
kpt0,
))
eri_mo1 = odf.get_mo_eri((mo, ) * 4, (
kpts[0],
kpts[0],
kpt0,
kpt0,
))
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
mo1 = mo[:, :nao // 2 + 1]
eri_mo0 = df0.get_mo_eri((mo1, mo, mo, mo1), (kpts[0], ) * 4)
eri_mo1 = odf.get_mo_eri((mo1, mo, mo, mo1), (kpts[0], ) * 4)
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
eri_mo0 = df0.get_mo_eri((mo1, mo, mo1, mo), (
kpts[0],
kpts[1],
kpts[1],
kpts[0],
))
eri_mo1 = odf.get_mo_eri((mo1, mo, mo1, mo), (
kpts[0],
kpts[1],
kpts[1],
kpts[0],
))
self.assertTrue(np.allclose(eri_mo1, eri_mo0, atol=1e-7, rtol=1e-7))
wj = wj[0]
return wj
if __name__ == '__main__':
from pyscf.pbc import scf
cell = pbcgto.Cell()
cell.build(unit = 'B',
a = numpy.eye(3)*4,
gs = [5]*3,
atom = 'H 0 0 0; H 0 0 1.8',
verbose = 4,
basis='sto3g')
lib.param.LIGHT_SPEED = 2
mf = scf.RHF(cell)
mf.with_df = pwdf.PWDF(cell)
enr = mf.kernel()
print('E(NR) = %.12g' % enr)
mf = sfx2c1e(mf)
esfx2c = mf.kernel()
print('E(SFX2C1E) = %.12g' % esfx2c)
mf = scf.KRHF(cell)
mf.with_df = pwdf.PWDF(cell)
mf.kpts = cell.make_kpts([2,2,1])
enr = mf.kernel()
print('E(k-NR) = %.12g' % enr)
mf = sfx2c1e(mf)
esfx2c = mf.kernel()
