#!/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: Qiming Sun <osirpt.sun@gmail.com>
#
'''
Dirac Hartree-Fock
'''
from functools import reduce
import ctypes
import numpy
from pyscf import lib
from pyscf import gto
from pyscf.lib import logger
from pyscf.scf import hf
from pyscf.scf import _vhf
from pyscf.scf import chkfile
from pyscf.data import nist
from pyscf import __config__
zquatev = None
if getattr(__config__, 'scf_dhf_SCF_zquatev', True):
try:
# Install zquatev with
# pip install git+https://github.com/sunqm/zquatev
import zquatev
except ImportError:
pass
DEBUG = False
[docs]
def kernel(mf, conv_tol=1e-9, conv_tol_grad=None,
dump_chk=True, dm0=None, callback=None, conv_check=True):
'''the modified SCF kernel for Dirac-Hartree-Fock. In this kernel, the
SCF is carried out in three steps. First the 2-electron part is
approximated by large component integrals (LL|LL); Next, (SS|LL) the
interaction between large and small components are added; Finally,
converge the SCF with the small component contributions (SS|SS)
'''
if conv_tol_grad is None:
conv_tol_grad = numpy.sqrt(conv_tol)
logger.info(mf, 'Set gradient conv threshold to %g', conv_tol_grad)
if dm0 is None:
dm = mf.get_init_guess(mf.mol, mf.init_guess)
else:
dm = dm0
mf._coulomb_level = 'LLLL'
cycles = 0
if dm0 is None and mf._coulomb_level.upper() == 'LLLL':
scf_conv, e_tot, mo_energy, mo_coeff, mo_occ \
= hf.kernel(mf, 1e-2, 1e-1,
dump_chk, dm0=dm, callback=callback,
conv_check=False)
cycles += mf.cycles
dm = mf.make_rdm1(mo_coeff, mo_occ)
mf._coulomb_level = 'SSLL'
if mf.with_ssss:
if dm0 is None and (mf._coulomb_level.upper() == 'SSLL' or
mf._coulomb_level.upper() == 'LLSS'):
scf_conv, e_tot, mo_energy, mo_coeff, mo_occ \
= hf.kernel(mf, 1e-3, 1e-1,
dump_chk, dm0=dm, callback=callback,
conv_check=False)
cycles += mf.cycles
dm = mf.make_rdm1(mo_coeff, mo_occ)
mf._coulomb_level = 'SSSS'
else:
mf._coulomb_level = 'SSLL'
out = hf.kernel(mf, conv_tol, conv_tol_grad, dump_chk, dm0=dm,
callback=callback, conv_check=conv_check)
mf.cycles = cycles + mf.cycles
return out
[docs]
def energy_elec(mf, dm=None, h1e=None, vhf=None):
r'''Electronic part of Dirac-Hartree-Fock energy
Args:
mf : an instance of SCF class
Kwargs:
dm : 2D ndarray
one-particle density matrix
h1e : 2D ndarray
Core hamiltonian
vhf : 2D ndarray
HF potential
Returns:
Hartree-Fock electronic energy and the Coulomb energy
'''
if dm is None: dm = mf.make_rdm1()
if h1e is None: h1e = mf.get_hcore()
if vhf is None: vhf = mf.get_veff(mf.mol, dm)
e1 = numpy.einsum('ij,ji->', h1e, dm).real
e_coul = numpy.einsum('ij,ji->', vhf, dm).real * .5
logger.debug(mf, 'E1 = %.14g E_coul = %.14g', e1, e_coul)
if not mf.with_ssss and mf.ssss_approx == 'Visscher':
e_coul += _visscher_ssss_correction(mf, dm)
mf.scf_summary['e1'] = e1
mf.scf_summary['e2'] = e_coul
return e1+e_coul, e_coul
def _visscher_ssss_correction(mf, dm):
'''
Visscher point charge corrections for small component, TCA, 98, 68
Note there is a small difference to Visscher's work. The model
charges in Visscher's work are obtained from atomic calculations.
Charges here are Mulliken charges on small components.
'''
aoslice = mf.mol.aoslice_2c_by_atom()
n2c = dm[0].shape[0] // 2
s = mf.get_ovlp()
ss_mul_charges = []
for p0, p1 in aoslice[:,2:] + n2c:
mul_charge = numpy.einsum('ij,ji->', s[n2c:,p0:p1], dm[p0:p1,n2c:])
ss_mul_charges.append(mul_charge.real)
ss_mul_charges = numpy.array(ss_mul_charges)
e_coul_ss = gto.classical_coulomb_energy(mf.mol, ss_mul_charges)
mf.scf_summary['e_coul_ss'] = e_coul_ss
logger.debug(mf, 'Visscher corrections for small component = %.14g', e_coul_ss)
return e_coul_ss
[docs]
def get_jk_coulomb(mol, dm, hermi=1, coulomb_allow='SSSS',
opt_llll=None, opt_ssll=None, opt_ssss=None,
omega=None, verbose=None):
log = logger.new_logger(mol, verbose)
if hermi == 0 and DEBUG:
# J matrix is symmetrized in this function which is only true for
# density matrix with time reversal symmetry
_ensure_time_reversal_symmetry(mol, dm)
with mol.with_range_coulomb(omega):
if coulomb_allow.upper() == 'LLLL':
log.debug('Coulomb integral: (LL|LL)')
j1, k1 = _call_veff_llll(mol, dm, hermi, opt_llll)
n2c = j1.shape[1]
vj = numpy.zeros_like(dm)
vk = numpy.zeros_like(dm)
vj[...,:n2c,:n2c] = j1
vk[...,:n2c,:n2c] = k1
elif coulomb_allow.upper() == 'SSLL' \
or coulomb_allow.upper() == 'LLSS':
log.debug('Coulomb integral: (LL|LL) + (SS|LL)')
vj, vk = _call_veff_ssll(mol, dm, hermi, opt_ssll)
j1, k1 = _call_veff_llll(mol, dm, hermi, opt_llll)
n2c = j1.shape[1]
vj[...,:n2c,:n2c] += j1
vk[...,:n2c,:n2c] += k1
else: # coulomb_allow == 'SSSS'
log.debug('Coulomb integral: (LL|LL) + (SS|LL) + (SS|SS)')
vj, vk = _call_veff_ssll(mol, dm, hermi, opt_ssll)
j1, k1 = _call_veff_llll(mol, dm, hermi, opt_llll)
n2c = j1.shape[1]
vj[...,:n2c,:n2c] += j1
vk[...,:n2c,:n2c] += k1
j1, k1 = _call_veff_ssss(mol, dm, hermi, opt_ssss)
vj[...,n2c:,n2c:] += j1
vk[...,n2c:,n2c:] += k1
return vj, vk
get_jk = get_jk_coulomb
[docs]
def get_hcore(mol):
n2c = mol.nao_2c()
n4c = n2c * 2
c = lib.param.LIGHT_SPEED
t = mol.intor_symmetric('int1e_spsp_spinor') * .5
vn = mol.intor_symmetric('int1e_nuc_spinor')
wn = mol.intor_symmetric('int1e_spnucsp_spinor')
h1e = numpy.empty((n4c, n4c), numpy.complex128)
h1e[:n2c,:n2c] = vn
h1e[n2c:,:n2c] = t
h1e[:n2c,n2c:] = t
h1e[n2c:,n2c:] = wn * (.25/c**2) - t
return h1e
[docs]
def get_ovlp(mol):
n2c = mol.nao_2c()
n4c = n2c * 2
c = lib.param.LIGHT_SPEED
s = mol.intor_symmetric('int1e_ovlp_spinor')
t = mol.intor_symmetric('int1e_spsp_spinor')
s1e = numpy.zeros((n4c, n4c), numpy.complex128)
s1e[:n2c,:n2c] = s
s1e[n2c:,n2c:] = t * (.5/c)**2
return s1e
make_rdm1 = hf.make_rdm1
[docs]
def init_guess_by_minao(mol):
'''Initial guess in terms of the overlap to minimal basis.'''
dm = hf.init_guess_by_minao(mol)
return _proj_dmll(mol, dm, mol)
[docs]
def init_guess_by_1e(mol):
'''Initial guess from one electron system.'''
return UHF(mol).init_guess_by_1e(mol)
[docs]
def init_guess_by_atom(mol):
'''Initial guess from atom calculation.'''
dm = hf.init_guess_by_atom(mol)
return _proj_dmll(mol, dm, mol)
[docs]
def init_guess_by_huckel(mol):
'''Initial guess from on-the-fly Huckel, doi:10.1021/acs.jctc.8b01089.'''
dm = hf.init_guess_by_huckel(mol)
return _proj_dmll(mol, dm, mol)
[docs]
def init_guess_by_mod_huckel(mol):
'''Initial guess from on-the-fly Huckel, doi:10.1021/acs.jctc.8b01089,
employing the updated GWH rule from doi:10.1021/ja00480a005.'''
dm = hf.init_guess_by_mod_huckel(mol)
return _proj_dmll(mol, dm, mol)
[docs]
def init_guess_by_sap(mol, mf):
'''Generate initial guess density matrix from a superposition of
atomic potentials (SAP), doi:10.1021/acs.jctc.8b01089.
This is the Gaussian fit implementation, see doi:10.1063/5.0004046.
Args:
mol : MoleBase object
the molecule object for which the initial guess is evaluated
sap_basis : dict
SAP basis in internal format (python dictionary)
Returns:
dm0 : ndarray
SAP initial guess density matrix
'''
dm = hf.SCF.init_guess_by_sap(mf, mol)
return _proj_dmll(mol, dm, mol)
[docs]
def init_guess_by_chkfile(mol, chkfile_name, project=None):
'''Read SCF chkfile and make the density matrix for 4C-DHF initial guess.
Kwargs:
project : None or bool
Whether to project chkfile's orbitals to the new basis. Note when
the geometry of the chkfile and the given molecule are very
different, this projection can produce very poor initial guess.
In PES scanning, it is recommended to switch off project.
If project is set to None, the projection is only applied when the
basis sets of the chkfile's molecule are different to the basis
sets of the given molecule (regardless whether the geometry of
the two molecules are different). Note the basis sets are
considered to be different if the two molecules are derived from
the same molecule with different ordering of atoms.
'''
from pyscf.scf import addons
chk_mol, scf_rec = chkfile.load_scf(chkfile_name)
if project is None:
project = not gto.same_basis_set(chk_mol, mol)
# Check whether the two molecules are similar
if abs(mol.inertia_moment() - chk_mol.inertia_moment()).sum() > 0.5:
logger.warn(mol, "Large deviations found between the input "
"molecule and the molecule from chkfile\n"
"Initial guess density matrix may have large error.")
if project:
s = get_ovlp(mol)
def fproj(mo):
#TODO: check if mo is GHF orbital
if project:
mo = addons.project_mo_r2r(chk_mol, mo, mol)
norm = numpy.einsum('pi,pi->i', mo.conj(), s.dot(mo))
mo /= numpy.sqrt(norm)
return mo
mo = scf_rec['mo_coeff']
mo_occ = scf_rec['mo_occ']
if numpy.iscomplexobj(mo[0]): # DHF
dm = make_rdm1(fproj(mo), mo_occ)
else:
if mo[0].ndim == 1: # nr-RHF
dm = reduce(numpy.dot, (mo*mo_occ, mo.T))
else: # nr-UHF
dm = (reduce(numpy.dot, (mo[0]*mo_occ[0], mo[0].T)) +
reduce(numpy.dot, (mo[1]*mo_occ[1], mo[1].T)))
dm = _proj_dmll(chk_mol, dm, mol)
return dm
[docs]
def get_init_guess(mol, key='minao', **kwargs):
'''Generate density matrix for initial guess
Kwargs:
key : str
One of 'minao', 'atom', 'huckel', 'mod_huckel', 'hcore', '1e', 'sap', 'chkfile'.
'''
return UHF(mol).get_init_guess(mol, key, **kwargs)
[docs]
def time_reversal_matrix(mol, mat):
''' T(A_ij) = A[T(i),T(j)]^*
'''
tao = numpy.asarray(mol.time_reversal_map())
n2c = tao.size
# tao(i) = -j means T(f_i) = -f_j
# tao(i) = j means T(f_i) = f_j
idx = abs(tao) - 1 # -1 for C indexing convention
#:signL = [(1 if x>0 else -1) for x in tao]
#:sign = numpy.hstack((signL, signL))
#:tmat = numpy.empty_like(mat)
#:for j in range(mat.__len__()):
#: for i in range(mat.__len__()):
#: tmat[idx[i],idx[j]] = mat[j,i] * sign[i]*sign[j]
#:return tmat.conjugate()
sign_mask = tao < 0
if mat.shape[0] == n2c * 2:
idx = numpy.hstack((idx, idx+n2c))
sign_mask = numpy.hstack((sign_mask, sign_mask))
tmat = mat[idx[:,None], idx]
tmat[sign_mask,:] *= -1
tmat[:,sign_mask] *= -1
return tmat.conj()
[docs]
def analyze(mf, verbose=logger.DEBUG, **kwargs):
from pyscf.tools import dump_mat
log = logger.new_logger(mf, verbose)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
mo_coeff = mf.mo_coeff
mf.dump_scf_summary(log)
log.info('**** MO energy ****')
for i in range(len(mo_energy)):
if mo_occ[i] > 0:
log.info('occupied MO #%d energy= %.15g occ= %g',
i+1, mo_energy[i], mo_occ[i])
else:
log.info('virtual MO #%d energy= %.15g occ= %g',
i+1, mo_energy[i], mo_occ[i])
mol = mf.mol
if mf.verbose >= logger.DEBUG1:
log.debug(' ** MO coefficients of large component of positive state (real part) **')
label = mol.spinor_labels()
n2c = mo_coeff.shape[0] // 2
dump_mat.dump_rec(mf.stdout, mo_coeff[n2c:,:n2c].real, label, start=1)
dm = mf.make_rdm1(mo_coeff, mo_occ)
pop_chg = mf.mulliken_pop(mol, dm, mf.get_ovlp(), log)
dip = mf.dip_moment(mol, dm, verbose=log)
return pop_chg, dip
[docs]
def mulliken_pop(mol, dm, s=None, verbose=logger.DEBUG):
r'''Mulliken population analysis
.. math:: M_{ij} = D_{ij} S_{ji}
Mulliken charges
.. math:: \delta_i = \sum_j M_{ij}
'''
if s is None: s = get_ovlp(mol)
log = logger.new_logger(mol, verbose)
pop = numpy.einsum('ij,ji->i', dm, s).real
log.info(' ** Mulliken pop **')
for i, s in enumerate(mol.spinor_labels()):
log.info('pop of %s %10.5f', s, pop[i])
log.note(' ** Mulliken atomic charges **')
chg = numpy.zeros(mol.natm)
for i, s in enumerate(mol.spinor_labels(fmt=None)):
chg[s[0]] += pop[i]
chg = mol.atom_charges() - chg
for ia in range(mol.natm):
symb = mol.atom_symbol(ia)
log.note('charge of %d%s = %10.5f', ia, symb, chg[ia])
return pop, chg
[docs]
def dip_moment(mol, dm, unit='Debye', verbose=logger.NOTE, **kwargs):
r''' Dipole moment calculation
.. math::
\mu_x = -\sum_{\mu}\sum_{\nu} P_{\mu\nu}(\nu|x|\mu) + \sum_A Q_A X_A\\
\mu_y = -\sum_{\mu}\sum_{\nu} P_{\mu\nu}(\nu|y|\mu) + \sum_A Q_A Y_A\\
\mu_z = -\sum_{\mu}\sum_{\nu} P_{\mu\nu}(\nu|z|\mu) + \sum_A Q_A Z_A
where :math:`\mu_x, \mu_y, \mu_z` are the x, y and z components of dipole
moment
Args:
mol: an instance of :class:`Mole`
dm : a 2D ndarrays density matrices
Return:
A list: the dipole moment on x, y and z component
'''
log = logger.new_logger(mol, verbose)
charges = mol.atom_charges()
coords = mol.atom_coords()
charge_center = numpy.einsum('i,ix->x', charges, coords) / sum(charges)
with mol.with_common_orig(charge_center):
ll_dip = mol.intor_symmetric('int1e_r_spinor', comp=3)
ss_dip = mol.intor_symmetric('int1e_sprsp_spinor', comp=3)
n2c = mol.nao_2c()
c = lib.param.LIGHT_SPEED
dip = numpy.einsum('xij,ji->x', ll_dip, dm[:n2c,:n2c]).real
dip+= numpy.einsum('xij,ji->x', ss_dip, dm[n2c:,n2c:]).real * (.5/c)**2
dip *= -1.
if unit.upper() == 'DEBYE':
dip *= nist.AU2DEBYE
log.note('Dipole moment(X, Y, Z, Debye): %8.5f, %8.5f, %8.5f', *dip)
else:
log.note('Dipole moment(X, Y, Z, A.U.): %8.5f, %8.5f, %8.5f', *dip)
return dip
[docs]
def get_grad(mo_coeff, mo_occ, fock_ao):
'''DHF Gradients'''
occidx = mo_occ > 0
viridx = ~occidx
g = reduce(numpy.dot, (mo_coeff[:,viridx].T.conj(), fock_ao,
mo_coeff[:,occidx]))
return g.ravel()
# Kramers unrestricted Dirac-Hartree-Fock
[docs]
class DHF(hf.SCF):
__doc__ = hf.SCF.__doc__ + '''
Attributes for Dirac-Hartree-Fock
with_ssss : bool or string, for Dirac-Hartree-Fock only
If False, ignore small component integrals (SS|SS). Default is True.
with_gaunt : bool, for Dirac-Hartree-Fock only
Default is False.
with_breit : bool, for Dirac-Hartree-Fock only
Gaunt + gauge term. Default is False.
Examples:
>>> mol = gto.M(atom='H 0 0 0; H 0 0 1', basis='ccpvdz', verbose=0)
>>> mf = scf.RHF(mol)
>>> e0 = mf.scf()
>>> mf = scf.DHF(mol)
>>> e1 = mf.scf()
>>> print('Relativistic effects = %.12f' % (e1-e0))
Relativistic effects = -0.000008854205
'''
conv_tol = getattr(__config__, 'scf_dhf_SCF_conv_tol', 1e-8)
with_ssss = getattr(__config__, 'scf_dhf_SCF_with_ssss', True)
with_gaunt = getattr(__config__, 'scf_dhf_SCF_with_gaunt', False)
with_breit = getattr(__config__, 'scf_dhf_SCF_with_breit', False)
# corrections for small component when with_ssss is set to False
ssss_approx = getattr(__config__, 'scf_dhf_SCF_ssss_approx', 'Visscher')
_keys = {'conv_tol', 'with_ssss', 'with_gaunt', 'with_breit', 'ssss_approx'}
def __init__(self, mol):
hf.SCF.__init__(self, mol)
self._coulomb_level = 'SSSS' # 'SSSS' ~ LLLL+LLSS+SSSS
[docs]
def dump_flags(self, verbose=None):
hf.SCF.dump_flags(self, verbose)
log = logger.new_logger(self, verbose)
log.info('with_ssss %s, with_gaunt %s, with_breit %s',
self.with_ssss, self.with_gaunt, self.with_breit)
if not self.with_ssss:
log.info('ssss_approx: %s', self.ssss_approx)
log.info('light speed = %s', lib.param.LIGHT_SPEED)
return self
[docs]
@lib.with_doc(get_hcore.__doc__)
def get_hcore(self, mol=None):
if mol is None:
mol = self.mol
return get_hcore(mol)
[docs]
@lib.with_doc(get_ovlp.__doc__)
def get_ovlp(self, mol=None):
if mol is None:
mol = self.mol
return get_ovlp(mol)
[docs]
def get_grad(self, mo_coeff, mo_occ, fock=None):
if fock is None:
dm1 = self.make_rdm1(mo_coeff, mo_occ)
fock = self.get_hcore(self.mol) + self.get_veff(self.mol, dm1)
return get_grad(mo_coeff, mo_occ, fock)
[docs]
def init_guess_by_minao(self, mol=None):
'''Initial guess in terms of the overlap to minimal basis.'''
if mol is None: mol = self.mol
return init_guess_by_minao(mol)
[docs]
def init_guess_by_atom(self, mol=None):
if mol is None: mol = self.mol
return init_guess_by_atom(mol)
[docs]
@lib.with_doc(hf.SCF.init_guess_by_huckel.__doc__)
def init_guess_by_huckel(self, mol=None):
if mol is None: mol = self.mol
logger.info(self, 'Initial guess from on-the-fly Huckel, doi:10.1021/acs.jctc.8b01089.')
return init_guess_by_huckel(mol)
[docs]
@lib.with_doc(hf.SCF.init_guess_by_mod_huckel.__doc__)
def init_guess_by_mod_huckel(self, mol=None):
if mol is None: mol = self.mol
logger.info(self, '''Initial guess from on-the-fly Huckel, doi:10.1021/acs.jctc.8b01089,
employing the updated GWH rule from doi:10.1021/ja00480a005.''')
return init_guess_by_mod_huckel(mol)
[docs]
@lib.with_doc(hf.SCF.init_guess_by_sap.__doc__)
def init_guess_by_sap(self, mol=None, **kwargs):
if mol is None: mol = self.mol
return init_guess_by_sap(mol, self)
[docs]
def init_guess_by_chkfile(self, chkfile=None, project=None):
if chkfile is None: chkfile = self.chkfile
return init_guess_by_chkfile(self.mol, chkfile, project=project)
[docs]
def build(self, mol=None):
if self.verbose >= logger.WARN:
self.check_sanity()
return self
[docs]
def get_occ(self, mo_energy=None, mo_coeff=None):
if mo_energy is None: mo_energy = self.mo_energy
mol = self.mol
c = lib.param.LIGHT_SPEED
n4c = len(mo_energy)
n2c = n4c // 2
mo_occ = numpy.zeros(n2c * 2)
nocc = mol.nelectron
if mo_energy[n2c] > -1.999 * c**2:
mo_occ[n2c:n2c+nocc] = 1
else:
logger.warn(self, 'Variational collapse. PES mo_energy %g < -2c^2',
mo_energy[n2c])
lumo = mo_energy[mo_energy > -1.999 * c**2][nocc]
mo_occ[mo_energy > -1.999 * c**2] = 1
mo_occ[mo_energy >= lumo] = 0
if self.verbose >= logger.INFO:
if mo_energy[n2c+nocc-1]+1e-3 > mo_energy[n2c+nocc]:
logger.warn(self, 'HOMO %.15g == LUMO %.15g',
mo_energy[n2c+nocc-1], mo_energy[n2c+nocc])
else:
logger.info(self, 'HOMO %d = %.12g LUMO %d = %.12g',
nocc, mo_energy[n2c+nocc-1],
nocc+1, mo_energy[n2c+nocc])
logger.debug1(self, 'NES mo_energy = %s', mo_energy[:n2c])
logger.debug(self, 'PES mo_energy = %s', mo_energy[n2c:])
return mo_occ
make_rdm1 = lib.module_method(make_rdm1, absences=['mo_coeff', 'mo_occ'])
energy_elec = energy_elec
[docs]
def init_direct_scf(self, mol=None):
if mol is None: mol = self.mol
def set_vkscreen(opt, name):
opt._this.r_vkscreen = _vhf._fpointer(name)
cpu0 = (logger.process_clock(), logger.perf_counter())
opt_llll = _VHFOpt(mol, 'int2e_spinor', 'CVHFrkbllll_prescreen',
'CVHFrkb_q_cond', 'CVHFrkb_dm_cond',
direct_scf_tol=self.direct_scf_tol)
set_vkscreen(opt_llll, 'CVHFrkbllll_vkscreen')
c1 = .5 / lib.param.LIGHT_SPEED
opt_ssss = _VHFOpt(mol, 'int2e_spsp1spsp2_spinor',
'CVHFrkbllll_prescreen', 'CVHFrkb_q_cond',
'CVHFrkb_dm_cond',
direct_scf_tol=self.direct_scf_tol/c1**4)
opt_ssss.direct_scf_tol = self.direct_scf_tol
opt_ssss.q_cond *= c1**2
set_vkscreen(opt_ssss, 'CVHFrkbllll_vkscreen')
opt_ssll = _VHFOpt(mol, 'int2e_spsp1_spinor',
'CVHFrkbssll_prescreen',
dmcondname='CVHFrkbssll_dm_cond',
direct_scf_tol=self.direct_scf_tol)
opt_ssll.q_cond = numpy.array([opt_llll.q_cond, opt_ssss.q_cond])
set_vkscreen(opt_ssll, 'CVHFrkbssll_vkscreen')
#TODO: prescreen for gaunt
opt_gaunt = None
logger.timer(self, 'init_direct_scf', *cpu0)
return opt_llll, opt_ssll, opt_ssss, opt_gaunt
[docs]
def get_jk(self, mol=None, dm=None, hermi=1, with_j=True, with_k=True,
omega=None):
if mol is None: mol = self.mol
if dm is None: dm = self.make_rdm1()
t0 = (logger.process_clock(), logger.perf_counter())
log = logger.new_logger(self)
if self.direct_scf and self._opt.get(omega) is None:
with mol.with_range_coulomb(omega):
self._opt[omega] = self.init_direct_scf(mol)
vhfopt = self._opt.get(omega)
if vhfopt is None:
opt_llll = opt_ssll = opt_ssss = opt_gaunt = None
else:
opt_llll, opt_ssll, opt_ssss, opt_gaunt = vhfopt
vj, vk = get_jk_coulomb(mol, dm, hermi, self._coulomb_level,
opt_llll, opt_ssll, opt_ssss, omega, log)
if self.with_breit:
assert omega is None
if ('SSSS' in self._coulomb_level.upper() or
# for the case both with_breit and with_ssss are set
(not self.with_ssss and 'SSLL' in self._coulomb_level.upper())):
vj1, vk1 = _call_veff_gaunt_breit(mol, dm, hermi, opt_gaunt, True)
log.debug('Add Breit term')
vj += vj1
vk += vk1
elif self.with_gaunt and 'SS' in self._coulomb_level.upper():
assert omega is None
log.debug('Add Gaunt term')
vj1, vk1 = _call_veff_gaunt_breit(mol, dm, hermi, opt_gaunt, False)
vj += vj1
vk += vk1
log.timer('vj and vk', *t0)
return vj, vk
[docs]
def get_veff(self, mol=None, dm=None, dm_last=0, vhf_last=0, hermi=1):
'''Dirac-Coulomb'''
if mol is None: mol = self.mol
if dm is None: dm = self.make_rdm1()
if self.direct_scf:
ddm = numpy.array(dm) - numpy.array(dm_last)
vj, vk = self.get_jk(mol, ddm, hermi=hermi)
return numpy.array(vhf_last) + vj - vk
else:
vj, vk = self.get_jk(mol, dm, hermi=hermi)
return vj - vk
[docs]
def scf(self, dm0=None):
cput0 = (logger.process_clock(), logger.perf_counter())
self.build()
self.dump_flags()
self.converged, self.e_tot, \
self.mo_energy, self.mo_coeff, self.mo_occ \
= kernel(self, self.conv_tol, self.conv_tol_grad,
dm0=dm0, callback=self.callback,
conv_check=self.conv_check)
logger.timer(self, 'SCF', *cput0)
self._finalize()
return self.e_tot
[docs]
def analyze(self, verbose=None):
if verbose is None: verbose = self.verbose
return analyze(self, verbose)
[docs]
@lib.with_doc(mulliken_pop.__doc__)
def mulliken_pop(self, mol=None, dm=None, s=None, verbose=logger.DEBUG):
if mol is None: mol = self.mol
if dm is None: dm = self.make_rdm1()
if s is None: s = self.get_ovlp(mol)
return mulliken_pop(mol, dm, s=s, verbose=verbose)
[docs]
@lib.with_doc(dip_moment.__doc__)
def dip_moment(self, mol=None, dm=None, unit='Debye', verbose=logger.NOTE,
**kwargs):
if mol is None: mol = self.mol
if dm is None: dm = self.make_rdm1()
return dip_moment(mol, dm, unit, verbose=verbose, **kwargs)
[docs]
def sfx2c1e(self):
raise NotImplementedError
[docs]
def x2c1e(self):
from pyscf.x2c import x2c
x2chf = x2c.UHF(self.mol)
x2chf.__dict__.update(self.__dict__)
return x2chf
x2c = x2c1e
[docs]
def nuc_grad_method(self):
from pyscf.grad import dhf
return dhf.Gradients(self)
[docs]
def reset(self, mol=None):
'''Reset mol and clean up relevant attributes for scanner mode'''
if mol is not None:
self.mol = mol
self._coulomb_level = 'SSSS' # 'SSSS' ~ LLLL+LLSS+SSSS
self._opt = {None: None}
return self
[docs]
def stability(self, internal=None, external=None, verbose=None, return_status=False, **kwargs):
'''
DHF/DKS stability analysis.
See also pyscf.scf.stability.rhf_stability function.
Kwargs:
return_status: bool
Whether to return `stable_i` and `stable_e`
Returns:
If return_status is False (default), the return value includes
two set of orbitals, which are more close to the stable condition.
The first corresponds to the internal stability
and the second corresponds to the external stability.
Else, another two boolean variables (indicating current status:
stable or unstable) are returned.
The first corresponds to the internal stability
and the second corresponds to the external stability.
'''
from pyscf.scf.stability import dhf_stability
return dhf_stability(self, verbose, return_status, **kwargs)
[docs]
def to_rhf(self):
raise RuntimeError
[docs]
def to_uhf(self):
raise RuntimeError
[docs]
def to_ghf(self):
raise RuntimeError
[docs]
def to_rks(self, xc=None):
raise RuntimeError
[docs]
def to_uks(self, xc=None):
raise RuntimeError
[docs]
def to_gks(self, xc=None):
raise RuntimeError
[docs]
def to_dhf(self):
return self
[docs]
def to_dks(self, xc='HF'):
'''Convert the input mean-field object to a DKS object.
Note this conversion only changes the class of the mean-field object.
The total energy and wave-function are the same as them in the input
mean-field object.
'''
from pyscf.dft import dks
mf = self.view(dks.UDKS)
mf.xc = xc
mf.converged = False
return mf
to_ks = to_dks
to_gpu = lib.to_gpu
UHF = UDHF = DHF
[docs]
class HF1e(DHF):
scf = hf._hf1e_scf
def _eigh(self, h, s):
if zquatev:
return zquatev.solve_KR_FCSCE(self.mol, h, s)
else:
return DHF._eigh(self, h, s)
[docs]
class RDHF(DHF):
'''Kramers restricted Dirac-Hartree-Fock'''
def __init__(self, mol):
if mol.nelectron.__mod__(2) != 0:
raise ValueError('Invalid electron number %i.' % mol.nelectron)
if zquatev is None:
raise RuntimeError('zquatev library is required to perform Kramers-restricted DHF')
UHF.__init__(self, mol)
def _eigh(self, h, s):
return zquatev.solve_KR_FCSCE(self.mol, h, s)
[docs]
def x2c1e(self):
from pyscf.x2c import x2c
x2chf = x2c.RHF(self.mol)
x2chf.__dict__.update(self.__dict__)
return x2chf
x2c = x2c1e
[docs]
def to_dks(self, xc='HF'):
'''Convert the input mean-field object to a DKS object.
Note this conversion only changes the class of the mean-field object.
The total energy and wave-function are the same as them in the input
mean-field object.
'''
from pyscf.dft import dks
mf = self.view(dks.RDKS)
mf.xc = xc
mf.converged = False
return mf
RHF = RDHF
def _ensure_time_reversal_symmetry(mol, mat):
if mat.ndim == 2:
mat = [mat]
for m in mat:
if abs(m - time_reversal_matrix(mol, m)).max() > 1e-9:
raise RuntimeError('Matrix does have time reversal symmetry')
def _time_reversal_triu_(mol, vj):
n2c = vj.shape[1]
idx, idy = numpy.triu_indices(n2c, 1)
if vj.ndim == 2:
Tvj = time_reversal_matrix(mol, vj)
vj[idx,idy] = Tvj[idy,idx].conj()
else:
for i in range(vj.shape[0]):
Tvj = time_reversal_matrix(mol, vj[i])
vj[i,idx,idy] = Tvj[idy,idx].conj()
return vj
def _mat_hermi_(vk, hermi):
if hermi == 1:
if vk.ndim == 2:
vk = lib.hermi_triu(vk, hermi)
else:
for i in range(vk.shape[0]):
vk[i] = lib.hermi_triu(vk[i], hermi)
return vk
def _jk_triu_(mol, vj, vk, hermi):
if hermi == 0:
return _time_reversal_triu_(mol, vj), vk
else:
return _mat_hermi_(vj, hermi), _mat_hermi_(vk, hermi)
def _call_veff_llll(mol, dm, hermi=1, mf_opt=None):
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
n2c = dm.shape[0] // 2
dms = dm[:n2c,:n2c].copy()
else:
n2c = dm.shape[1] // 2
dms = dm[:,:n2c,:n2c].copy()
vj, vk = _vhf.rdirect_mapdm('int2e_spinor', 's8',
('ji->s2kl', 'jk->s1il'), dms, 1,
mol._atm, mol._bas, mol._env, mf_opt)
return _jk_triu_(mol, vj, vk, hermi)
def _call_veff_ssll(mol, dm, hermi=1, mf_opt=None):
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
dm1 = dm[numpy.newaxis]
else:
dm1 = numpy.asarray(dm)
n_dm = len(dm1)
n2c = dm1.shape[1] // 2
dms = numpy.vstack([dm1[:,:n2c,:n2c],
dm1[:,n2c:,n2c:],
dm1[:,n2c:,:n2c],
dm1[:,:n2c,n2c:]])
if hermi:
jks = (['lk->s2ij'] * n_dm +
['ji->s2kl'] * n_dm +
['jk->s1il'] * n_dm)
else:
jks = (['lk->s2ij'] * n_dm +
['ji->s2kl'] * n_dm +
['jk->s1il'] * n_dm +
['li->s1kj'] * n_dm)
c1 = .5 / lib.param.LIGHT_SPEED
vx = _vhf.rdirect_bindm('int2e_spsp1_spinor', 's4', jks, dms, 1,
mol._atm, mol._bas, mol._env, mf_opt)
vx = vx.reshape(-1,n_dm,n2c,n2c) * c1**2
vj = numpy.zeros((n_dm,n2c*2,n2c*2), dtype=numpy.complex128)
vk = numpy.zeros((n_dm,n2c*2,n2c*2), dtype=numpy.complex128)
if hermi == 0:
vj[:,n2c:,n2c:] = _time_reversal_triu_(mol, vx[0])
vj[:,:n2c,:n2c] = _time_reversal_triu_(mol, vx[1])
vk[:,n2c:,:n2c] = vx[2]
vk[:,:n2c,n2c:] = vx[3]
else:
vj[:,n2c:,n2c:] = _mat_hermi_(vx[0], hermi)
vj[:,:n2c,:n2c] = _mat_hermi_(vx[1], hermi)
vk[:,n2c:,:n2c] = vx[2]
vk[:,:n2c,n2c:] = vx[2].conj().transpose(0,2,1)
vj = vj.reshape(dm.shape)
vk = vk.reshape(dm.shape)
return vj, vk
def _call_veff_ssss(mol, dm, hermi=1, mf_opt=None):
c1 = .5 / lib.param.LIGHT_SPEED
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
n2c = dm.shape[0] // 2
dms = dm[n2c:,n2c:].copy()
else:
n2c = dm[0].shape[0] // 2
dms = []
for dmi in dm:
dms.append(dmi[n2c:,n2c:].copy())
vj, vk = _vhf.rdirect_mapdm('int2e_spsp1spsp2_spinor', 's8',
('ji->s2kl', 'jk->s1il'), dms, 1,
mol._atm, mol._bas, mol._env, mf_opt) * c1**4
return _jk_triu_(mol, vj, vk, hermi)
def _call_veff_gaunt_breit(mol, dm, hermi=1, mf_opt=None, with_breit=False):
if with_breit:
# integral function int2e_breit_ssp1ssp2_spinor evaluates
# -1/2[alpha1*alpha2/r12 + (alpha1*r12)(alpha2*r12)/r12^3]
intor_prefix = 'int2e_breit_'
else:
# integral function int2e_ssp1ssp2_spinor evaluates only
# alpha1*alpha2/r12. Minus sign was not included.
intor_prefix = 'int2e_'
if hermi == 0 and DEBUG:
_ensure_time_reversal_symmetry(mol, dm)
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
n_dm = 1
n2c = dm.shape[0] // 2
dmls = dm[:n2c,n2c:].copy()
dmsl = dm[n2c:,:n2c].copy()
dmll = dm[:n2c,:n2c].copy()
dmss = dm[n2c:,n2c:].copy()
dms = [dmsl, dmsl, dmls, dmll, dmss]
else:
n_dm = len(dm)
n2c = dm[0].shape[0] // 2
dmll = [dmi[:n2c,:n2c].copy() for dmi in dm]
dmls = [dmi[:n2c,n2c:].copy() for dmi in dm]
dmsl = [dmi[n2c:,:n2c].copy() for dmi in dm]
dmss = [dmi[n2c:,n2c:].copy() for dmi in dm]
dms = dmsl + dmsl + dmls + dmll + dmss
vj = numpy.zeros((n_dm,n2c*2,n2c*2), dtype=numpy.complex128)
vk = numpy.zeros((n_dm,n2c*2,n2c*2), dtype=numpy.complex128)
jks = ('lk->s1ij',) * n_dm \
+ ('jk->s1il',) * n_dm
vx = _vhf.rdirect_bindm(intor_prefix+'ssp1ssp2_spinor', 's1', jks, dms[:n_dm*2], 1,
mol._atm, mol._bas, mol._env, mf_opt)
vj[:,:n2c,n2c:] = vx[:n_dm,:,:]
vk[:,:n2c,n2c:] = vx[n_dm:,:,:]
jks = ('lk->s1ij',) * n_dm \
+ ('li->s1kj',) * n_dm \
+ ('jk->s1il',) * n_dm
vx = _vhf.rdirect_bindm(intor_prefix+'ssp1sps2_spinor', 's1', jks, dms[n_dm*2:], 1,
mol._atm, mol._bas, mol._env, mf_opt)
vj[:,:n2c,n2c:]+= vx[ :n_dm ,:,:]
vk[:,n2c:,n2c:] = vx[n_dm :n_dm*2,:,:]
vk[:,:n2c,:n2c] = vx[n_dm*2: ,:,:]
if hermi == 1:
vj[:,n2c:,:n2c] = vj[:,:n2c,n2c:].transpose(0,2,1).conj()
vk[:,n2c:,:n2c] = vk[:,:n2c,n2c:].transpose(0,2,1).conj()
elif hermi == 2:
vj[:,n2c:,:n2c] = -vj[:,:n2c,n2c:].transpose(0,2,1).conj()
vk[:,n2c:,:n2c] = -vk[:,:n2c,n2c:].transpose(0,2,1).conj()
else:
raise NotImplementedError
vj = vj.reshape(dm.shape)
vk = vk.reshape(dm.shape)
c1 = .5 / lib.param.LIGHT_SPEED
if with_breit:
vj *= c1**2
vk *= c1**2
else:
vj *= -c1**2
vk *= -c1**2
return vj, vk
def _proj_dmll(mol_nr, dm_nr, mol):
'''Project non-relativistic atomic density matrix to large component spinor
representation
'''
from pyscf.scf import addons
proj = addons.project_mo_nr2r(mol_nr, numpy.eye(mol_nr.nao_nr()), mol)
n2c = proj.shape[0]
n4c = n2c * 2
dm = numpy.zeros((n4c,n4c), dtype=numpy.complex128)
# *.5 because alpha and beta are summed in project_mo_nr2r
dm_ll = reduce(numpy.dot, (proj, dm_nr*.5, proj.T.conj()))
dm[:n2c,:n2c] = (dm_ll + time_reversal_matrix(mol, dm_ll)) * .5
return dm
class _VHFOpt(_vhf._VHFOpt):
def set_dm(self, dm, atm, bas, env):
if self._dmcondname is None:
return
mol = self.mol
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
n_dm = 1
else:
n_dm = len(dm)
dm = numpy.asarray(dm, order='C')
ao_loc = mol.ao_loc_2c()
if isinstance(self._dmcondname, ctypes._CFuncPtr):
fdmcond = self._dmcondname
else:
fdmcond = getattr(_vhf.libcvhf, self._dmcondname)
nbas = mol.nbas
dm_cond = numpy.empty((n_dm*2, nbas, nbas))
fdmcond(dm_cond.ctypes, dm.ctypes, ctypes.c_int(n_dm),
ao_loc.ctypes, mol._atm.ctypes, ctypes.c_int(mol.natm),
mol._bas.ctypes, ctypes.c_int(nbas), mol._env.ctypes)
self.dm_cond = dm_cond
if __name__ == '__main__':
import pyscf.gto
mol = pyscf.gto.Mole()
mol.verbose = 5
mol.output = 'out_dhf'
mol.atom.extend([['He', (0.,0.,0.)], ])
mol.basis = {
'He': [(0, 0, (1, 1)),
(0, 0, (3, 1)),
(1, 0, (1, 1)), ]}
mol.build()
##############
# SCF result
method = UHF(mol)
energy = method.scf() #-2.38146942868
print(energy)
method.with_gaunt = True
print(method.scf()) # -2.38138339005
method.with_breit = True
print(method.scf()) # -2.38138339005
