#!/usr/bin/env python
# Copyright 2014-2020 The PySCF Developers. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Author: Xing Zhang <zhangxing.nju@gmail.com>
#
import numpy as np
from pyscf import __config__
from pyscf import lib
from pyscf.lib import logger
from pyscf.pbc.lib import kpts as libkpts
from pyscf.pbc.scf import khf, khf_ksymm, kuhf_ksymm
from pyscf.pbc.dft import gen_grid, multigrid
from pyscf.pbc.dft import rks, kuks
[docs]
@lib.with_doc(kuks.get_veff.__doc__)
def get_veff(ks, cell=None, dm=None, dm_last=0, vhf_last=0, hermi=1,
kpts=None, kpts_band=None):
if cell is None: cell = ks.cell
if dm is None: dm = ks.make_rdm1()
if kpts is None: kpts = ks.kpts
if isinstance(kpts, np.ndarray):
return kuks.get_veff(ks, cell, dm, dm_last, vhf_last, hermi, kpts, kpts_band)
t0 = (logger.process_clock(), logger.perf_counter())
ni = ks._numint
# ndim = 4 : dm.shape = ([alpha,beta], nkpts, nao, nao)
ground_state = (dm.ndim == 4 and dm.shape[0] == 2 and kpts_band is None)
if kpts_band is None: kpts_band = kpts.kpts_ibz
dm_bz = dm
if ground_state:
if len(dm[0]) != kpts.nkpts_ibz:
raise RuntimeError("Number of input density matrices does not \
match the number of IBZ kpts: %d vs %d."
% (len(dm[0]), kpts.nkpts_ibz))
dm_bz = kpts.transform_dm(dm)
hybrid = ni.libxc.is_hybrid_xc(ks.xc)
if not hybrid and isinstance(ks.with_df, multigrid.MultiGridFFTDF):
if ks.nlc or ni.libxc.is_nlc(ks.xc):
raise NotImplementedError(f'MultiGrid for NLC functional {ks.xc} + {ks.nlc}')
n, exc, vxc = multigrid.nr_uks(ks.with_df, ks.xc, dm_bz, hermi,
kpts.kpts, kpts_band,
with_j=True, return_j=False)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
return vxc
ks.initialize_grids(cell, dm_bz, kpts.kpts, ground_state)
if hermi == 2: # because rho = 0
n, exc, vxc = (0,0), 0, 0
else:
max_memory = ks.max_memory - lib.current_memory()[0]
n, exc, vxc = ni.nr_uks(cell, ks.grids, ks.xc, dm_bz,
kpts=kpts.kpts, kpts_band=kpts_band,
max_memory=max_memory)
logger.debug(ks, 'nelec by numeric integration = %s', n)
if ks.nlc or ni.libxc.is_nlc(ks.xc):
if ni.libxc.is_nlc(ks.xc):
xc = ks.xc
else:
assert ni.libxc.is_nlc(ks.nlc)
xc = ks.nlc
n, enlc, vnlc = ni.nr_nlc_vxc(cell, ks.nlcgrids, xc, dm_bz[0]+dm_bz[1],
0, hermi, kpts.kpts, max_memory=max_memory)
exc += enlc
vxc += vnlc
logger.debug(ks, 'nelec with nlc grids = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
weight = kpts.weights_ibz
if not hybrid:
vj = ks.get_j(cell, dm[0]+dm[1], hermi, kpts, kpts_band)
vxc += vj
else:
omega, alpha, hyb = ni.rsh_and_hybrid_coeff(ks.xc, spin=cell.spin)
if getattr(ks.with_df, '_j_only', False): # for GDF and MDF
logger.warn(ks, 'df.j_only cannot be used with hybrid functional')
ks.with_df._j_only = False
# Rebuild df object due to the change of parameter _j_only
if ks.with_df._cderi is not None:
ks.with_df.build()
vj, vk = ks.get_jk(cell, dm, hermi, kpts, kpts_band)
vj = vj[0] + vj[1]
vk *= hyb
if omega != 0:
vklr = ks.get_k(cell, dm, hermi, kpts, kpts_band, omega=omega)
vklr *= (alpha - hyb)
vk += vklr
vxc += vj - vk
if ground_state:
exc -= (np.einsum('K,Kij,Kji', weight, dm[0], vk[0]) +
np.einsum('K,Kij,Kji', weight, dm[1], vk[1])).real * .5
if ground_state:
ecoul = np.einsum('K,Kij,Kji', weight, dm[0]+dm[1], vj).real * .5
else:
ecoul = None
vxc = lib.tag_array(vxc, ecoul=ecoul, exc=exc, vj=None, vk=None)
return vxc
[docs]
def get_rho(mf, dm=None, grids=None, kpts=None):
from pyscf.pbc.dft import krks_ksymm
if dm is None:
dm = mf.make_rdm1()
return krks_ksymm.get_rho(mf, dm[0]+dm[1], grids, kpts)
[docs]
class KsymAdaptedKUKS(kuks.KUKS, kuhf_ksymm.KUHF):
get_veff = get_veff
get_rho = get_rho
kpts = khf_ksymm.KsymAdaptedKSCF.kpts
get_ovlp = khf_ksymm.KsymAdaptedKSCF.get_ovlp
get_hcore = khf_ksymm.KsymAdaptedKSCF.get_hcore
get_jk = khf_ksymm.KsymAdaptedKSCF.get_jk
init_guess_by_chkfile = khf_ksymm.KsymAdaptedKSCF.init_guess_by_chkfile
dump_chk = khf_ksymm.KsymAdaptedKSCF.dump_chk
nelec = kuhf_ksymm.KUHF.nelec
get_init_guess = kuhf_ksymm.KUHF.get_init_guess
get_occ = kuhf_ksymm.KUHF.get_occ
eig = kuhf_ksymm.KUHF.eig
get_orbsym = kuhf_ksymm.KUHF.get_orbsym
orbsym = kuhf_ksymm.KUHF.orbsym
_finalize = kuhf_ksymm.KUHF._finalize
def __init__(self, cell, kpts=libkpts.KPoints(), xc='LDA,VWN',
exxdiv=getattr(__config__, 'pbc_scf_SCF_exxdiv', 'ewald')):
kuhf_ksymm.KUHF.__init__(self, cell, kpts, exxdiv=exxdiv)
rks.KohnShamDFT.__init__(self, xc)
[docs]
def dump_flags(self, verbose=None):
kuhf_ksymm.KUHF.dump_flags(self, verbose)
rks.KohnShamDFT.dump_flags(self, verbose)
return self
[docs]
def energy_elec(self, dm_kpts=None, h1e_kpts=None, vhf=None):
if h1e_kpts is None: h1e_kpts = self.get_hcore(self.cell, self.kpts)
if dm_kpts is None: dm_kpts = self.make_rdm1()
if vhf is None or getattr(vhf, 'ecoul', None) is None:
vhf = self.get_veff(self.cell, dm_kpts)
weight = self.kpts.weights_ibz
e1 = np.einsum('k,kij,kji', weight, h1e_kpts, dm_kpts[0]+dm_kpts[1])
ecoul = vhf.ecoul
tot_e = e1 + ecoul + vhf.exc
self.scf_summary['e1'] = e1.real
self.scf_summary['coul'] = ecoul.real
self.scf_summary['exc'] = vhf.exc.real
logger.debug(self, 'E1 = %s Ecoul = %s Exc = %s', e1, ecoul, vhf.exc)
if khf.CHECK_COULOMB_IMAG and abs(ecoul.imag > self.cell.precision*10):
logger.warn(self, "Coulomb energy has imaginary part %s. "
"Coulomb integrals (e-e, e-N) may not converge !",
ecoul.imag)
return tot_e.real, vhf.ecoul + vhf.exc
[docs]
def to_hf(self):
'''Convert to KRHF object.'''
from pyscf.pbc.scf.kuhf_ksymm import KUHF
return self._transfer_attrs_(KUHF(self.cell, self.kpts))
KUKS = KsymAdaptedKUKS