def test_rhf_smearing(self):
mf = pscf.RHF(cell)
pscf.addons.smearing_(mf, 0.1, 'fermi')
mo_energy = numpy.arange(nao)*.2+numpy.cos(.5)*.1
mf.get_occ(mo_energy)
self.assertAlmostEqual(mf.entropy, 3.0922723199786408, 9)
mf.smearing_method = 'gauss'
occ = mf.get_occ(mo_energy)
self.assertAlmostEqual(mf.entropy, 0.4152467504725415, 9)
mf.kernel()
self.assertAlmostEqual(mf.entropy, 0, 15)
def test_ccsd_t_hf(self):
'''Tests ccsd and ccsd_t for Hartree-Fock references using supercell
vs k-point calculation.'''
n = 14
cell = make_test_cell.test_cell_n3([n] * 3)
nk = [2, 1, 1]
kpts = cell.make_kpts(nk)
kpts -= kpts[0]
kks = pbcscf.KRHF(cell, kpts=kpts)
ekks = kks.kernel()
khf = pbcscf.KRHF(cell)
khf.__dict__.update(kks.__dict__)
mycc = pbcc.KRCCSD(khf)
eris = mycc.ao2mo()
ekcc, t1, t2 = mycc.kernel(eris=eris)
ekcc_t = mycc.ccsd_t(eris=eris)
# Run supercell
from pyscf.pbc.tools.pbc import super_cell
supcell = super_cell(cell, nk)
rks = pbcscf.RHF(supcell)
erks = rks.kernel()
rhf = pbcscf.RHF(supcell)
rhf.__dict__.update(rks.__dict__)
mycc = pbcc.RCCSD(rhf)
eris = mycc.ao2mo()
ercc, t1, t2 = mycc.kernel(eris=eris)
self.assertAlmostEqual(ercc / np.prod(nk), -0.15530756381467772, 6)
self.assertAlmostEqual(ercc / np.prod(nk), ekcc, 6)
ercc_t = mycc.ccsd_t(eris=eris)
self.assertAlmostEqual(ercc_t / np.prod(nk), -0.0011112735513837887, 6)
self.assertAlmostEqual(ercc_t / np.prod(nk), ekcc_t, 6)
def test_ccsd_t_hf_frozen(self):
'''Tests ccsd and ccsd_t for Hartree-Fock references with frozen orbitals
using supercell vs k-point calculation.'''
n = 14
cell = make_test_cell.test_cell_n3([n] * 3)
nk = [2, 1, 1]
kpts = cell.make_kpts(nk)
kpts -= kpts[0]
kks = pbcscf.KRHF(cell, kpts=kpts)
ekks = kks.kernel()
khf = pbcscf.KRHF(cell)
khf.__dict__.update(kks.__dict__)
mycc = pbcc.KRCCSD(khf, frozen=1)
eris = mycc.ao2mo()
ekcc, t1, t2 = mycc.kernel(eris=eris)
ekcc_t = mycc.ccsd_t(eris=eris)
# Run supercell
from pyscf.pbc.tools.pbc import super_cell
supcell = super_cell(cell, nk)
rks = pbcscf.RHF(supcell)
erks = rks.kernel()
rhf = pbcscf.RHF(supcell)
rhf.__dict__.update(rks.__dict__)
mycc = pbcc.RCCSD(rhf, frozen=2)
eris = mycc.ao2mo()
ercc, t1, t2 = mycc.kernel(eris=eris)
self.assertAlmostEqual(ercc / np.prod(nk), -0.1137362020855094, 6)
self.assertAlmostEqual(ercc / np.prod(nk), ekcc, 6)
ercc_t = mycc.ccsd_t(eris=eris)
self.assertAlmostEqual(ercc_t / np.prod(nk), -0.0006758642528821, 6)
self.assertAlmostEqual(ercc_t / np.prod(nk), ekcc_t, 6)
def test_hf(self):
with lib.light_speed(2) as c:
mf = scf.RHF(cell).sfx2c1e()
mf.with_df = df.AFTDF(cell)
dm = mf.get_init_guess()
h1 = mf.get_hcore()
self.assertAlmostEqual(
numpy.einsum('ij,ji', dm, h1),
2 / 3.7865300454631 * -0.47578184212352159 + 0j, 8)
kpts = cell.make_kpts([3, 1, 1])
h1 = mf.get_hcore(kpt=kpts[1])
self.assertAlmostEqual(
numpy.einsum('ij,ji', dm, h1),
2 / 3.7865300454631 * -0.09637799091491725 + 0j, 8)
def test_get_jk_with_casscf(self):
from pyscf import mcscf
pcell = cell2.copy()
pcell.verbose = 0
pcell.mesh = [8]*3
mf = pbcscf.RHF(pcell)
mf.exxdiv = None
ehf = mf.kernel()
mc = mcscf.CASSCF(mf, 1, 2).run()
self.assertAlmostEqual(mc.e_tot, ehf, 9)
mc = mcscf.CASSCF(mf, 2, 0).run()
self.assertAlmostEqual(mc.e_tot, ehf, 9)
def test_krhf_vs_rhf(self):
np.random.seed(1)
k = np.random.random(3)
mf = pscf.RHF(cell, k, exxdiv='vcut_sph')
mf.max_cycle = 1
mf.diis = None
e1 = mf.kernel()
kmf = pscf.KRHF(cell, [k], exxdiv='vcut_sph')
kmf.max_cycle = 1
kmf.diis = None
e2 = kmf.kernel()
self.assertAlmostEqual(e1, e2, 9)
self.assertAlmostEqual(e1, -11.451118801956275, 9)
def get_scf(cell):
scf = pbchf.RHF(cell, exxdiv=None)
scf.conv_tol = 1e-10
scf.conv_tol_grad = 1e-8
scf.diis = True
scf.diis_space = 20
scf.direct_scf_tol = 1e-14
scf.init_guess = 'minao'
scf.max_cycle = 200
scf.max_memory = 8000
scf.verbose = 10
scf.scf()
return scf
def k2gamma(kmf, kmesh=None):
r'''
convert the k-sampled mean-field object to the corresponding supercell
gamma-point mean-field object.
math:
C_{\nu ' n'} = C_{\vecR\mu, \veck m} = \frac{1}{\sqrt{N_{\UC}}}
\e^{\ii \veck\cdot\vecR} C^{\veck}_{\mu m}
'''
def transform(mo_energy, mo_coeff, mo_occ):
scell, E_g, C_gamma = mo_k2gamma(kmf.cell, mo_energy, mo_coeff,
kmf.kpts, kmesh)[:3]
E_sort_idx = np.argsort(np.hstack(mo_energy))
mo_occ = np.hstack(mo_occ)[E_sort_idx]
return scell, E_g, C_gamma, mo_occ
if isinstance(kmf, scf.khf.KRHF):
scell, E_g, C_gamma, mo_occ = transform(kmf.mo_energy, kmf.mo_coeff,
kmf.mo_occ)
mf = scf.RHF(scell)
elif isinstance(kmf, scf.kuhf.KUHF):
scell, Ea, Ca, occ_a = transform(kmf.mo_energy[0], kmf.mo_coeff[0],
kmf.mo_occ[0])
scell, Eb, Cb, occ_b = transform(kmf.mo_energy[1], kmf.mo_coeff[1],
kmf.mo_occ[1])
mf = scf.UHF(scell)
E_g = [Ea, Eb]
C_gamma = [Ca, Cb]
mo_occ = [occ_a, occ_b]
else:
raise NotImplementedError('SCF object %s not supported' % kmf)
mf.mo_coeff = C_gamma
mf.mo_energy = E_g
mf.mo_occ = mo_occ
mf.converged = kmf.converged
# Scale energy by number of primitive cells within supercell
mf.e_tot = len(kmf.kpts) * kmf.e_tot
# Use unfolded overlap matrix for better error cancellation
#s_k = kmf.cell.pbc_intor('int1e_ovlp', hermi=1, kpts=kmf.kpts, pbcopt=lib.c_null_ptr())
s_k = kmf.get_ovlp()
ovlp = to_supercell_ao_integrals(kmf.cell, kmf.kpts, s_k)
assert np.allclose(ovlp, ovlp.T)
ovlp = (ovlp + ovlp.T) / 2
mf.get_ovlp = lambda *args: ovlp
return mf
def setUpModule():
global cell, cell1, mf0, kmdf, kmdf1, kpts
L = 5.
n = 11
cell = pgto.Cell()
cell.a = numpy.diag([L,L,L])
cell.mesh = numpy.array([n,n,n])
cell.atom = '''C 3. 2. 3.
C 1. 1. 1.'''
cell.basis = 'ccpvdz'
cell.verbose = 0
cell.rcut = 17
cell.build(0,0)
mf0 = pscf.RHF(cell)
mf0.exxdiv = 'vcut_sph'
numpy.random.seed(1)
kpts = numpy.random.random((5,3))
kpts[0] = 0
kpts[3] = kpts[0]-kpts[1]+kpts[2]
kpts[4] *= 1e-5
kmdf = mdf.MDF(cell)
kmdf.linear_dep_threshold = 1e-7
kmdf.auxbasis = 'weigend'
kmdf.kpts = kpts
kmdf.mesh = (11,)*3
kmdf.eta = 0.154728892598
cell1 = pgto.Cell()
cell1.a = numpy.eye(3) * 3.
cell1.mesh = [10]*3
cell1.atom = '''C 3. 2. 3.
C 1. 1. 1.'''
cell1.basis = [[0, (3.5, 1)], [0, (1.0, 1)], [1, (0.6, 1)]]
cell1.rcut = 9.5
cell1.build(0,0)
kmdf1 = mdf.MDF(cell1)
kmdf1.linear_dep_threshold = 1e-7
kmdf1.auxbasis = df.aug_etb(cell1, 1.8)
kmdf1.kpts = kpts
kmdf1.mesh = [6]*3
kmdf1.eta = 0.1
def test_cell(cell, ngs, nk):
#############################################
# Do a supercell Gamma-pt calculation #
#############################################
supcell = pyscf.pbc.tools.super_cell(cell, nk)
supcell.gs = np.array([
nk[0] * ngs + 1 * (nk[0] - 1) // 2, nk[1] * ngs + 1 * (nk[1] - 1) // 2,
nk[2] * ngs + 1 * (nk[2] - 1) // 2
])
print "supcell gs =", supcell.gs
supcell.build()
scaled_gamma = ase.dft.kpoints.monkhorst_pack((1, 1, 1))
gamma = supcell.get_abs_kpts(scaled_gamma)
#############################################
# Running HF #
#############################################
print ""
print "*********************************"
print "STARTING HF "
print "*********************************"
print ""
mf = pbchf.RHF(supcell, exxdiv=None)
mf.conv_tol = 1e-15
#mf.verbose = 7
escf = mf.scf()
escf_per_cell = escf / np.prod(nk)
print "scf energy (per unit cell) = %.17g" % escf_per_cell
#############################################
# Running CCSD #
#############################################
print ""
print "*********************************"
print "STARTING CCSD "
print "*********************************"
print ""
cc = pyscf.pbc.cc.CCSD(mf)
cc.conv_tol = 1e-15
#cc.verbose = 7
ecc, t1, it2 = cc.kernel()
ecc_per_cell = ecc / np.prod(nk)
print "cc energy (per unit cell) = %.17g" % ecc_per_cell
return escf_per_cell, ecc_per_cell
def test_get_veff(self):
mf = pscf.RHF(cell)
numpy.random.seed(1)
nao = cell.nao_nr()
dm = numpy.random.random((nao, nao)) + numpy.random.random(
(nao, nao)) * 1j
dm = dm + dm.conj().T
v11 = mf.get_veff(cell, dm, kpt=cell.get_abs_kpts([.25, .25, .25]))
v12 = mf.get_veff(cell,
dm,
kpts_band=cell.get_abs_kpts([.25, .25, .25]))
v13 = mf.get_veff(cell,
dm,
kpt=cell.get_abs_kpts([-1. / 3, 1. / 3, .25]),
kpts_band=cell.get_abs_kpts([.25, .25, .25]))
v14 = mf.get_veff(cell,
dm,
kpt=cell.get_abs_kpts([-1. / 3, 1. / 3, .25]),
kpts_band=cell.make_kpts([2, 1, 1]))
self.assertTrue(v11.dtype == numpy.complex128)
self.assertTrue(v12.dtype == numpy.complex128)
mf = pscf.UHF(cell)
v21 = mf.get_veff(cell, dm, kpt=cell.get_abs_kpts([.25, .25, .25]))
dm = [dm * .5, dm * .5]
v22 = mf.get_veff(cell,
dm,
kpts_band=cell.get_abs_kpts([.25, .25, .25]))
v23 = mf.get_veff(cell,
dm,
kpt=cell.get_abs_kpts([-1. / 3, 1. / 3, .25]),
kpts_band=cell.get_abs_kpts([.25, .25, .25]))
v24 = mf.get_veff(cell,
dm,
kpt=cell.get_abs_kpts([-1. / 3, 1. / 3, .25]),
kpts_band=cell.make_kpts([2, 1, 1]))
self.assertAlmostEqual(abs(v11 - v21).max(), 0, 9)
self.assertAlmostEqual(abs(v12 - v22).max(), 0, 9)
self.assertAlmostEqual(abs(v13 - v23).max(), 0, 9)
self.assertAlmostEqual(abs(v14 - v24).max(), 0, 9)
self.assertAlmostEqual(lib.finger(v11),
-0.30110964334164825 + 0.81409418199767414j, 9)
self.assertAlmostEqual(lib.finger(v12),
-2.1601376488983997 - 9.4070613374115908j, 9)
def test_ccsd_t_non_hf_frozen(self):
'''Tests ccsd and ccsd_t for non-Hartree-Fock references with frozen orbitals
using supercell vs k-point calculation.'''
n = 14
cell = make_test_cell.test_cell_n3([n] * 3)
#import sys
#cell.stdout = sys.stdout
#cell.verbose = 7
nk = [2, 1, 1]
kpts = cell.make_kpts(nk)
kpts -= kpts[0]
kks = pbcdft.KRKS(cell, kpts=kpts)
ekks = kks.kernel()
khf = pbcscf.KRHF(cell)
khf.__dict__.update(kks.__dict__)
mycc = pbcc.KRCCSD(khf, frozen=1)
eris = mycc.ao2mo()
ekcc, t1, t2 = mycc.kernel(eris=eris)
ekcc_t = mycc.ccsd_t(eris=eris)
# Run supercell
from pyscf.pbc.tools.pbc import super_cell
supcell = super_cell(cell, nk)
rks = pbcdft.RKS(supcell)
erks = rks.kernel()
rhf = pbcscf.RHF(supcell)
rhf.__dict__.update(rks.__dict__)
mycc = pbcc.RCCSD(rhf, frozen=2)
eris = mycc.ao2mo()
ercc, t1, t2 = mycc.kernel(eris=eris)
self.assertAlmostEqual(ercc / np.prod(nk), -0.11467718013872311, 6)
self.assertAlmostEqual(ercc / np.prod(nk), ekcc, 6)
ercc_t = mycc.ccsd_t(eris=eris)
self.assertAlmostEqual(ercc_t / np.prod(nk), -0.00066503872045200996,
6)
self.assertAlmostEqual(ercc_t / np.prod(nk), ekcc_t, 6)
def run_cell(cell, n, nk):
#############################################
# Do a supercell Gamma-pt calculation #
#############################################
supcell = pyscf.pbc.tools.super_cell(cell, nk)
supcell.build()
gamma = [0, 0, 0]
mf = pbchf.RHF(supcell, exxdiv=None)
mf.conv_tol = 1e-14
#mf.verbose = 7
escf = mf.scf()
escf_per_cell = escf / np.prod(nk)
cc = pyscf.pbc.cc.CCSD(mf)
cc.conv_tol = 1e-8
ecc, t1, it2 = cc.kernel()
ecc_per_cell = ecc / np.prod(nk)
return escf_per_cell, ecc_per_cell
def test_jk_single_kpt_high_cost(self):
mf0 = pscf.RHF(cell)
mf0.exxdiv = None
mf = df_jk.density_fit(mf0, auxbasis='weigend', mesh=(11,)*3)
mf.with_df.mesh = cell.mesh
mf.with_df.eta = 0.3
mf.with_df.exp_to_discard = 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)
j_ref = 48.283789539266174 # rsjk result
k_ref = 32.30441176447805 # rsjk result
self.assertAlmostEqual(ej1, j_ref, 4)
self.assertAlmostEqual(ek1, k_ref, 2)
self.assertAlmostEqual(ej1, 48.283745538383684, 8)
self.assertAlmostEqual(ek1, 32.30260871417842 , 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, 242.04678235140264, 8)
self.assertAlmostEqual(ek1, 280.15934926575903, 8)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = df.DF(cell, [kpt]).set(auxbasis='weigend')
mydf.linear_dep_threshold = 1e-7
mydf.mesh = cell.mesh
mydf.eta = 0.3
mydf.exp_to_discard = mydf.eta
vj, vk = mydf.get_jk(dm, 1, kpt, exxdiv=None)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.15121903857556+0j, 8)
self.assertAlmostEqual(ek1, 279.64649194057051+0j, 8)
vj, vk = mydf.get_jk(dm, 1, kpt, with_j=False, exxdiv='ewald')
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ek1, 691.64624456329909+0j, 6)
def test_pp_int(self):
from pyscf import gto, scf
from pyscf.pbc import gto as pbcgto
from pyscf.pbc import scf as pbcscf
from pyscf.pbc import df
cell = pbcgto.Cell()
cell.atom = 'He 1. .5 .5; C .1 1.3 2.1'
cell.basis = {
'He': [(0, (2.5, 1)), (0, (1., 1))],
'C': 'gth-szv',
}
cell.pseudo = {
'C':
'gth-pade',
'He':
pbcgto.pseudo.parse('''He
2
0.40000000 3 -1.98934751 -0.75604821 0.95604821
2
0.29482550 3 1.23870466 .855 .3
.71 -1.1
.9
0.32235865 2 2.25670239 -0.39677748
0.93894690
''')
}
cell.a = numpy.eye(3)
cell.dimension = 0
cell.build()
mol = cell.to_mol()
hcore = scf.RHF(mol).get_hcore()
mydf = df.AFTDF(cell)
ref = mydf.get_pp() + mol.intor('int1e_kin')
self.assertAlmostEqual(abs(hcore - ref).max(), 0, 2)
mf = pbcscf.RHF(cell)
mf.with_df = mydf
mf.run()
e_ref = mf.e_tot
e_tot = scf.RHF(mol).run().e_tot
self.assertAlmostEqual(abs(e_ref - e_tot).max(), 0, 6)
def test_jk_single_kpt_high_cost(self):
mf0 = pscf.RHF(cell)
mf0.exxdiv = None
mf = rsdf_jk.density_fit(mf0, auxbasis='weigend', mesh=(11,)*3)
mf.with_df.mesh = cell.mesh
mf.with_df.omega = 0.3
mf.with_df.exp_to_discard = 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)
j_ref = 48.283789539266174 # rsjk result
k_ref = 32.30441176447805 # rsjk result
self.assertAlmostEqual(ej1, j_ref, 4)
self.assertAlmostEqual(ek1, k_ref, 2)
self.assertAlmostEqual(ej1, 48.2837455394308037, 7)
self.assertAlmostEqual(ek1, 32.3026087105977950, 7)
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, 242.0467816643269714, 7)
self.assertAlmostEqual(ek1, 280.1593488661793572, 7)
numpy.random.seed(1)
kpt = numpy.random.random(3)
mydf = rsdf.RSDF(cell, [kpt]).set(auxbasis='weigend')
mydf.linear_dep_threshold = 1e-7
mydf.omega = 0.3
mydf.exp_to_discard = 0.3
vj, vk = mydf.get_jk(dm, 1, kpt, exxdiv=None)
ej1 = numpy.einsum('ij,ji->', vj, dm)
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ej1, 241.1512182675005249+0j, 7)
self.assertAlmostEqual(ek1, 279.6464915858919085+0j, 7)
vj, vk = mydf.get_jk(dm, 1, kpt, with_j=False, exxdiv='ewald')
ek1 = numpy.einsum('ij,ji->', vk, dm)
self.assertAlmostEqual(ek1, 691.6462442086188958+0j, 6)
def _get_pbc(self):
import pyscf.pbc.gto as pbc_gto
import pyscf.pbc.scf as pbc_scf
cell = pbc_gto.Cell()
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.685068664391 1.685068664391 1.685068664391
'''
cell.basis = 'gth-szv'
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 = 0
cell.build()
pbc_mf = pbc_scf.RHF(cell, exxdiv=None)
pbc_mf.kernel()
return pbc_mf
def _get_pbc2(self):
import pyscf.pbc.gto as pbc_gto
import pyscf.pbc.scf as pbc_scf
cell = pbc_gto.Cell()
cell.atom = '''
C 0.000000000000 0.000000000000 0.000000000000
C 1.685068664391 1.685068664391 1.685068664391
'''
cell.basis = 'gth-szv'
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 = 0
cell.build()
kpt = cell.make_kpts((1, 1, 1), scaled_center=(0, 0, 1./3.))
pbc_mf2 = pbc_scf.RHF(cell, kpt=kpt, exxdiv=None)
pbc_mf2.kernel()
return pbc_mf2
def k2gamma(kmf, kmesh=None):
r'''
convert the k-sampled mean-field object to the corresponding supercell
gamma-point mean-field object.
math:
C_{\nu ' n'} = C_{\vecR\mu, \veck m} = \frac{1}{\sqrt{N_{\UC}}}
\e^{\ii \veck\cdot\vecR} C^{\veck}_{\mu m}
'''
scell, E_g, C_gamma = mo_k2gamma(kmf.cell, kmf.mo_energy, kmf.mo_coeff,
kmf.kpts, kmesh)[:3]
E_sort_idx = np.argsort(np.hstack(kmf.mo_energy))
mo_occ = np.hstack(kmf.mo_occ)[E_sort_idx]
mf = scf.RHF(scell)
mf.mo_coeff = C_gamma
mf.mo_energy = E_g
mf.mo_occ = mo_occ
return mf
def run_cell(cell, n, nk):
#############################################
# Do a supercell Gamma-pt calculation #
#############################################
supcell = pyscf.pbc.tools.super_cell(cell, nk)
supcell.build()
gamma = [0, 0, 0]
#############################################
# Running HF #
#############################################
# print ""
# print "*********************************"
# print "STARTING HF "
# print "*********************************"
# print ""
mf = pbchf.RHF(supcell, exxdiv=None)
mf.conv_tol = 1e-14
#mf.verbose = 7
escf = mf.scf()
escf_per_cell = escf / np.prod(nk)
# print "scf energy (per unit cell) = %.17g" % escf_per_cell
#############################################
# Running CCSD #
#############################################
# print ""
# print "*********************************"
# print "STARTING CCSD "
# print "*********************************"
# print ""
cc = pyscf.pbc.cc.CCSD(mf)
cc.conv_tol = 1e-8
#cc.verbose = 7
ecc, t1, it2 = cc.kernel()
ecc_per_cell = ecc / np.prod(nk)
# print "cc energy (per unit cell) = %.17g" % ecc_per_cell
return escf_per_cell, ecc_per_cell
def test_single_kpt(self):
cell = pbcgto.Cell()
cell.atom = '''
H 0 0 0
H 1 0 0
H 0 1 0
H 0 1 1
'''
cell.a = np.eye(3) * 2
cell.basis = [[0, [1.2, 1]], [1, [1.0, 1]]]
cell.verbose = 0
cell.build()
kpts = cell.get_abs_kpts([.5, .5, .5]).reshape(1, 3)
mf = pbcscf.KRHF(cell, kpts=kpts).run(conv_tol=1e-9)
kcc = pyscf.pbc.cc.kccsd_rhf.RCCSD(mf)
e0 = kcc.kernel()[0]
mf = pbcscf.RHF(cell, kpt=kpts[0]).run()
mycc = pyscf.pbc.cc.RCCSD(mf)
e1 = mycc.kernel()[0]
self.assertAlmostEqual(e0, e1, 7)
def k2gamma(kmf, kmesh=None):
r'''
convert the k-sampled mean-field object to the corresponding supercell
gamma-point mean-field object.
math:
C_{\nu ' n'} = C_{\vecR\mu, \veck m} = \frac{1}{\sqrt{N_{\UC}}}
\e^{\ii \veck\cdot\vecR} C^{\veck}_{\mu m}
'''
from pyscf.pbc import scf
def transform(mo_energy, mo_coeff, mo_occ):
scell, E_g, C_gamma = mo_k2gamma(kmf.cell, mo_energy, mo_coeff,
kmf.kpts, kmesh)[:3]
E_sort_idx = np.argsort(np.hstack(mo_energy))
mo_occ = np.hstack(mo_occ)[E_sort_idx]
return scell, E_g, C_gamma, mo_occ
if isinstance(kmf, scf.khf.KRHF):
scell, E_g, C_gamma, mo_occ = transform(kmf.mo_energy, kmf.mo_coeff,
kmf.mo_occ)
mf = scf.RHF(scell)
elif isinstance(kmf, scf.kuhf.KUHF):
scell, Ea, Ca, occ_a = transform(kmf.mo_energy[0], kmf.mo_coeff[0],
kmf.mo_occ[0])
scell, Eb, Cb, occ_b = transform(kmf.mo_energy[1], kmf.mo_coeff[1],
kmf.mo_occ[1])
mf = scf.UHF(scell)
E_g = [Ea, Eb]
C_gamma = [Ca, Cb]
mo_occ = [occ_a, occ_b]
else:
raise NotImplementedError('SCF object %s not supported' % kmf)
mf.mo_coeff = C_gamma
mf.mo_energy = E_g
mf.mo_occ = mo_occ
return mf
def test_ccsd_t_non_hf(self):
'''Tests ccsd and ccsd_t for non-Hartree-Fock references.'''
n = 14
cell = make_test_cell.test_cell_n3([n] * 3)
nk = [2, 1, 1]
kpts = cell.make_kpts(nk)
kpts -= kpts[0]
kks = pbcdft.KRKS(cell, kpts=kpts)
ekks = kks.kernel()
khf = pbcscf.KRHF(cell)
khf.__dict__.update(kks.__dict__)
mycc = pbcc.KRCCSD(khf)
eris = mycc.ao2mo()
ekcc, t1, t2 = mycc.kernel(eris=eris)
ekcc_t = mycc.ccsd_t(eris=eris)
# Run supercell
from pyscf.pbc.tools.pbc import super_cell
supcell = super_cell(cell, nk)
rks = pbcdft.RKS(supcell)
erks = rks.kernel()
rhf = pbcscf.RHF(supcell)
rhf.__dict__.update(rks.__dict__)
mycc = pbcc.RCCSD(rhf)
eris = mycc.ao2mo()
ercc, t1, t2 = mycc.kernel(eris=eris)
self.assertAlmostEqual(ercc / np.prod(nk), -0.15632445245405927, 6)
self.assertAlmostEqual(ercc / np.prod(nk), ekcc, 6)
ercc_t = mycc.ccsd_t(eris=eris)
self.assertAlmostEqual(ercc_t / np.prod(nk), -0.00114619248449, 6)
self.assertAlmostEqual(ercc_t / np.prod(nk), ekcc_t, 6)
def setUpModule():
global cell, cell1, cell2, kpts, kpt0, kpts1, mf0
cell = pgto.Cell()
cell.atom = 'He 1. .5 .5; C .1 1.3 2.1'
cell.basis = {'He': [(0, (2.5, 1)), (0, (1., 1))],
'C' :'gth-szv',}
cell.pseudo = {'C':'gth-pade'}
cell.a = np.eye(3) * 2.5
cell.mesh = [21] * 3
cell.build()
np.random.seed(1)
kpts = np.random.random((4,3))
kpts[3] = kpts[0]-kpts[1]+kpts[2]
kpt0 = np.zeros(3)
cell1 = pgto.Cell()
cell1.atom = 'He 1. .5 .5; He .1 1.3 2.1'
cell1.basis = {'He': [(0, (2.5, 1)), (0, (1., 1))]}
cell1.a = np.eye(3) * 2.5
cell1.mesh = [21] * 3
cell1.build()
cell2 = pgto.Cell()
cell2.atom = '''
He 1.3 .2 .3
He .1 .1 1.1 '''
cell2.basis = {'He': [[0, [0.8, 1]],
[1, [0.6, 1]]]}
cell2.mesh = [17]*3
cell2.a = numpy.array(([2.0, .9, 0. ],
[0.1, 1.9, 0.4],
[0.8, 0 , 2.1]))
cell2.build()
kpts1 = np.random.random((4,3))
kpts1[3] = kpts1[0]-kpts1[1]+kpts1[2] + cell2.reciprocal_vectors().T.dot(np.ones(3))
mf0 = pbcscf.RHF(cell)
mf0.exxdiv = None
def test_kpt_vs_supercell_high_cost(self):
# For large n, agreement is always achieved
# n = 17
# For small n, agreement only achieved if "wrapping" k-k'+G in get_coulG
n = 9
nk = (3, 1, 1)
cell = make_primitive_cell([n] * 3)
abs_kpts = cell.make_kpts(nk, wrap_around=True)
kmf = khf.KRHF(cell, abs_kpts, exxdiv='vcut_sph')
ekpt = kmf.scf()
self.assertAlmostEqual(ekpt, -11.221426249047617, 8)
# nk = (5, 1, 1)
# abs_kpts = cell.make_kpts(nk, wrap_around=True)
# kmf = khf.KRHF(cell, abs_kpts, exxdiv='vcut_sph')
# ekpt = kmf.scf()
# self.assertAlmostEqual(ekpt, -12.337299166550796, 8)
supcell = pyscf.pbc.tools.super_cell(cell, nk)
mf = pscf.RHF(supcell, exxdiv='vcut_sph')
esup = mf.scf() / np.prod(nk)
self.assertAlmostEqual(ekpt, esup, 8)
L = 5.
n = 11
cell = pgto.Cell()
cell.a = numpy.diag([L,L,L])
cell.mesh = numpy.array([n,n,n])
cell.atom = '''C 3. 2. 3.
C 1. 1. 1.'''
cell.basis = 'ccpvdz'
cell.verbose = 0
cell.max_memory = 0
cell.rcut = 28.3
cell.build()
mf0 = pscf.RHF(cell)
mf0.exxdiv = None
def finger(a):
w = numpy.cos(numpy.arange(a.size))
return numpy.dot(a.ravel(), w)
class KnowValues(unittest.TestCase):
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)
cell.unit = 'A' cell.a = [[4, 0, 0], [0, 1, 0], [0, 0, 1]] cell.atom = ''' H 0.0000000 0.0000000 0.0000000 H 1.0000000 0.0000000 0.0000000 H 2.0000000 0.0000000 0.0000000 H 3.0000000 0.0000000 0.0000000 ''' cell.basis = 'sto-6g' cell.dimension = 1 cell.verbose = 4 cell.build() gdf = df.GDF(cell) mf = scf.RHF(cell) mf.with_df = gdf mf.with_df.auxbasis = 'cc-pvdz-jkfit' mf.max_cycle = 150 mf.chkfile = name + '.chk' #mf.with_df._cderi_to_save = name+'_eri.h5' #mf.with_df._cderi = name+'_eri.h5' #mf = mole_scf.addons.remove_linear_dep_(mf) #mf.__dict__.update(scf.chkfile.load(name+'.chk', 'scf')) #dm = mf.make_rdm1() ehf = mf.kernel() ncore = 0 nao, nmo = mf.mo_coeff.shape nocc = cell.nelectron // 2 - ncore nvir = nmo - nocc - ncore
n = 5
cell = pgto.Cell()
cell.a = numpy.diag([L, L, L])
cell.gs = numpy.array([n, n, n])
cell.atom = '''C 3. 2. 3.
C 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
mf = pscf.RHF(cell)
dm = mf.get_init_guess()
auxbasis = 'weigend'
#from pyscf import df
#auxbasis = df.addons.aug_etb_for_dfbasis(cell, beta=1.5, start_at=0)
#from pyscf.pbc.df import mdf
#mf.with_df = mdf.MDF(cell)
#mf.auxbasis = auxbasis
mf = density_fit(mf, auxbasis)
mf.with_df.gs = (5, ) * 3
vj = mf.with_df.get_jk(dm, exxdiv=mf.exxdiv, with_k=False)[0]
print(numpy.einsum('ij,ji->', vj, dm), 'ref=46.698942480902062')
vj, vk = mf.with_df.get_jk(dm, exxdiv=mf.exxdiv)
print(numpy.einsum('ij,ji->', vj, dm), 'ref=46.698942480902062')
print(numpy.einsum('ij,ji->', vk, dm), 'ref=37.348163681114187')
print(numpy.einsum('ij,ji->', mf.get_hcore(cell), dm),
3.370137329, 3.370137329, 0.000000000''' cell.unit = 'B' cell.verbose = 5 cell.precision = 1e-12 cell.build() cell.rcut *= 2.0 cell.build() omegas = [-10.99479191] # #Run old code # supcell = super_cell(cell, nmp) mf = scf.RHF(supcell, exxdiv=None) mf.diis = None mf.conv_tol_grad = 1e-8 mf.conv_tol = 1e-8 ehf = mf.kernel() mf.analyze() mycc = cc.RCCSD(mf) mycc.frozen = [0, 1, 3, 4, 5, 6, 9, 10, 11, 12, 14, 15] mycc.ip_partition = None mycc.ea_partition = None mycc.conv_tol_normt = 1e-10 mycc.conv_tol = 1e-10 mycc.kernel() #p=[8,9,10,11,12,13,14,15] #q=[8,9,10,11,12,13,14,15] p = [2, 3]
f.write(''.join(['%5.3s' % atomN[0]
for atomN in vaspAtomicInfo]) + '\n')
f.write(''.join(['%5d' % atomN[1]
for atomN in vaspAtomicInfo]) + '\n')
f.write('Cartesian \n')
for ia in range(cell.natm):
f.write(' %14.8f %14.8f %14.8f\n' % tuple(swappedCoords[ia]))
f.write('\n')
f.write('%6.5s %6.5s %6.5s \n' % (self.nx, self.ny, self.nz))
fmt = ' %14.8e '
for iz in range(self.nz):
for iy in range(self.ny):
f.write('\n')
for ix in range(self.nx):
f.write(fmt % field[ix, iy, iz])
def read(self, chgcar_file):
raise NotImplementedError
if __name__ == '__main__':
from pyscf.pbc import scf
from pyscf.tools import chgcar
cell = gto.M(atom='H 0 0 0; H 0 0 1', a=numpy.eye(3) * 3)
mf = scf.RHF(cell).run()
chgcar.density(cell, 'h2.CHGCAR', mf.make_rdm1()) #makes total density
chgcar.orbital(cell, 'h2_mo1.CHGCAR', mf.mo_coeff[:,
0]) # makes mo#1 (sigma)
chgcar.orbital(cell, 'h2_mo2.CHGCAR',
mf.mo_coeff[:, 1]) # makes mo#2 (sigma*)
