Source code for pyscf.mp.dfmp2

#!/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
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'''
density fitting MP2,  3-center integrals incore.
'''

import numpy
from pyscf import lib
from pyscf.lib import logger
from pyscf.ao2mo import _ao2mo
from pyscf import df
from pyscf.mp import mp2
from pyscf.mp.mp2 import make_rdm1, make_rdm2
from pyscf import __config__

WITH_T2 = getattr(__config__, 'mp_dfmp2_with_t2', True)


[docs] def kernel(mp, mo_energy=None, mo_coeff=None, eris=None, with_t2=WITH_T2, verbose=logger.NOTE): if mo_energy is not None or mo_coeff is not None: # For backward compatibility. In pyscf-1.4 or earlier, mp.frozen is # not supported when mo_energy or mo_coeff is given. assert (mp.frozen == 0 or mp.frozen is None) if eris is None: eris = mp.ao2mo(mo_coeff) if mo_energy is None: mo_energy = eris.mo_energy if mo_coeff is None: mo_coeff = eris.mo_coeff nocc = mp.nocc nvir = mp.nmo - nocc naux = mp.with_df.get_naoaux() eia = mo_energy[:nocc,None] - mo_energy[None,nocc:] if with_t2: t2 = numpy.empty((nocc,nocc,nvir,nvir), dtype=mo_coeff.dtype) else: t2 = None Lov = numpy.empty((naux, nocc*nvir)) p1 = 0 for istep, qov in enumerate(mp.loop_ao2mo(mo_coeff, nocc)): logger.debug(mp, 'Load cderi step %d', istep) p0, p1 = p1, p1 + qov.shape[0] Lov[p0:p1] = qov emp2_ss = emp2_os = 0 for i in range(nocc): buf = numpy.dot(Lov[:,i*nvir:(i+1)*nvir].T, Lov).reshape(nvir,nocc,nvir) gi = numpy.array(buf, copy=False) gi = gi.reshape(nvir,nocc,nvir).transpose(1,0,2) t2i = gi/lib.direct_sum('jb+a->jba', eia, eia[i]) edi = numpy.einsum('jab,jab', t2i, gi) * 2 exi = -numpy.einsum('jab,jba', t2i, gi) emp2_ss += edi*0.5 + exi emp2_os += edi*0.5 if with_t2: t2[i] = t2i buf = gi = t2i = None # free mem emp2_ss = emp2_ss.real emp2_os = emp2_os.real emp2 = lib.tag_array(emp2_ss+emp2_os, e_corr_ss=emp2_ss, e_corr_os=emp2_os) return emp2, t2
[docs] class DFMP2(mp2.MP2): _keys = set(['with_df']) def __init__(self, mf, frozen=None, mo_coeff=None, mo_occ=None): mp2.MP2.__init__(self, mf, frozen, mo_coeff, mo_occ) if getattr(mf, 'with_df', None): self.with_df = mf.with_df else: self.with_df = df.DF(mf.mol) self.with_df.auxbasis = df.make_auxbasis(mf.mol, mp2fit=True)
[docs] def reset(self, mol=None): self.with_df.reset(mol) return mp2.MP2.reset(self, mol)
[docs] def loop_ao2mo(self, mo_coeff, nocc): mo = numpy.asarray(mo_coeff, order='F') nmo = mo.shape[1] ijslice = (0, nocc, nocc, nmo) Lov = None with_df = self.with_df nvir = nmo - nocc naux = with_df.get_naoaux() mem_now = lib.current_memory()[0] max_memory = max(2000, self.max_memory*.9-mem_now) blksize = int(min(naux, max(with_df.blockdim, (max_memory*1e6/8-nocc*nvir**2*2)/(nocc*nvir)))) for eri1 in with_df.loop(blksize=blksize): Lov = _ao2mo.nr_e2(eri1, mo, ijslice, aosym='s2', out=Lov) yield Lov
[docs] def ao2mo(self, mo_coeff=None): eris = mp2._ChemistsERIs() # Initialize only the mo_coeff eris._common_init_(self, mo_coeff) return eris
[docs] def make_rdm1(self, t2=None, ao_repr=False): if t2 is None: t2 = self.t2 assert t2 is not None return make_rdm1(self, t2, ao_repr=ao_repr)
[docs] def make_rdm2(self, t2=None, ao_repr=False): if t2 is None: t2 = self.t2 assert t2 is not None return make_rdm2(self, t2, ao_repr=ao_repr)
[docs] def nuc_grad_method(self): raise NotImplementedError
# For non-canonical MP2
[docs] def update_amps(self, t2, eris): raise NotImplementedError
[docs] def init_amps(self, mo_energy=None, mo_coeff=None, eris=None, with_t2=WITH_T2): return kernel(self, mo_energy, mo_coeff, eris, with_t2)
MP2 = DFMP2 from pyscf import scf scf.hf.RHF.DFMP2 = lib.class_as_method(DFMP2) scf.rohf.ROHF.DFMP2 = None scf.uhf.UHF.DFMP2 = None del (WITH_T2) if __name__ == '__main__': from pyscf import scf from pyscf import gto mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.build() mf = scf.RHF(mol).run() pt = DFMP2(mf) emp2, t2 = pt.kernel() print(emp2 - -0.204004830285) pt.with_df = df.DF(mol) pt.with_df.auxbasis = 'weigend' emp2, t2 = pt.kernel() print(emp2 - -0.204254500453) mf = scf.density_fit(scf.RHF(mol), 'weigend') mf.kernel() pt = DFMP2(mf) emp2, t2 = pt.kernel() print(emp2 - -0.203986171133) pt.with_df = df.DF(mol) pt.with_df.auxbasis = df.make_auxbasis(mol, mp2fit=True) emp2, t2 = pt.kernel() print(emp2 - -0.203738031827) pt.frozen = 2 emp2, t2 = pt.kernel() print(emp2 - -0.14433975122418313)