#!/usr/bin/env python
# Copyright 2014-2019 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>
#
'''
MP2 analytical nuclear gradients
'''
import numpy
from pyscf import lib
from functools import reduce
from pyscf import gto
from pyscf.lib import logger
from pyscf.grad import rhf as rhf_grad
from pyscf.scf import cphf
from pyscf.mp import mp2
from pyscf.ao2mo import _ao2mo
[docs]
def grad_elec(mp_grad, t2, atmlst=None, verbose=logger.INFO):
mp = mp_grad.base
log = logger.new_logger(mp, verbose)
time0 = logger.process_clock(), logger.perf_counter()
log.debug('Build mp2 rdm1 intermediates')
d1 = mp2._gamma1_intermediates(mp, t2)
doo, dvv = d1
time1 = log.timer_debug1('rdm1 intermediates', *time0)
# Set nocc, nvir for half-transformation of 2pdm. Frozen orbitals are excluded.
# nocc, nvir should be updated to include the frozen orbitals when proceeding
# the 1-particle quantities later.
mol = mp_grad.mol
with_frozen = not ((mp.frozen is None)
or (isinstance(mp.frozen, (int, numpy.integer)) and mp.frozen == 0)
or (len(mp.frozen) == 0))
OA, VA, OF, VF = _index_frozen_active(mp.get_frozen_mask(), mp.mo_occ)
orbo = mp.mo_coeff[:,OA]
orbv = mp.mo_coeff[:,VA]
nao, nocc = orbo.shape
nvir = orbv.shape[1]
# Partially transform MP2 density matrix and hold it in memory
# The rest transformation are applied during the contraction to ERI integrals
part_dm2 = _ao2mo.nr_e2(t2.reshape(nocc**2,nvir**2),
numpy.asarray(orbv.T, order='F'), (0,nao,0,nao),
's1', 's1').reshape(nocc,nocc,nao,nao)
part_dm2 = (part_dm2.transpose(0,2,3,1) * 4 -
part_dm2.transpose(0,3,2,1) * 2)
hf_dm1 = mp._scf.make_rdm1(mp.mo_coeff, mp.mo_occ)
if atmlst is None:
atmlst = range(mol.natm)
offsetdic = mol.offset_nr_by_atom()
diagidx = numpy.arange(nao)
diagidx = diagidx*(diagidx+1)//2 + diagidx
de = numpy.zeros((len(atmlst),3))
Imat = numpy.zeros((nao,nao))
fdm2 = lib.H5TmpFile()
vhf1 = fdm2.create_dataset('vhf1', (len(atmlst),3,nao,nao), 'f8')
# 2e AO integrals dot 2pdm
max_memory = max(0, mp.max_memory - lib.current_memory()[0])
blksize = max(1, int(max_memory*.9e6/8/(nao**3*2.5)))
for k, ia in enumerate(atmlst):
shl0, shl1, p0, p1 = offsetdic[ia]
ip1 = p0
vhf = numpy.zeros((3,nao,nao))
for b0, b1, nf in _shell_prange(mol, shl0, shl1, blksize):
ip0, ip1 = ip1, ip1 + nf
dm2buf = lib.einsum('pi,iqrj->pqrj', orbo[ip0:ip1], part_dm2)
dm2buf+= lib.einsum('qi,iprj->pqrj', orbo, part_dm2[:,ip0:ip1])
dm2buf = lib.einsum('pqrj,sj->pqrs', dm2buf, orbo)
dm2buf = dm2buf + dm2buf.transpose(0,1,3,2)
dm2buf = lib.pack_tril(dm2buf.reshape(-1,nao,nao)).reshape(nf,nao,-1)
dm2buf[:,:,diagidx] *= .5
shls_slice = (b0,b1,0,mol.nbas,0,mol.nbas,0,mol.nbas)
eri0 = mol.intor('int2e', aosym='s2kl', shls_slice=shls_slice)
Imat += lib.einsum('ipx,iqx->pq', eri0.reshape(nf,nao,-1), dm2buf)
eri0 = None
eri1 = mol.intor('int2e_ip1', comp=3, aosym='s2kl',
shls_slice=shls_slice).reshape(3,nf,nao,-1)
de[k] -= numpy.einsum('xijk,ijk->x', eri1, dm2buf) * 2
dm2buf = None
# HF part
for i in range(3):
eri1tmp = lib.unpack_tril(eri1[i].reshape(nf*nao,-1))
eri1tmp = eri1tmp.reshape(nf,nao,nao,nao)
vhf[i] += numpy.einsum('ijkl,ij->kl', eri1tmp, hf_dm1[ip0:ip1])
vhf[i] -= numpy.einsum('ijkl,il->kj', eri1tmp, hf_dm1[ip0:ip1]) * .5
vhf[i,ip0:ip1] += numpy.einsum('ijkl,kl->ij', eri1tmp, hf_dm1)
vhf[i,ip0:ip1] -= numpy.einsum('ijkl,jk->il', eri1tmp, hf_dm1) * .5
eri1 = eri1tmp = None
vhf1[k] = vhf
log.debug('2e-part grad of atom %d %s = %s', ia, mol.atom_symbol(ia), de[k])
time1 = log.timer_debug1('2e-part grad of atom %d'%ia, *time1)
# Recompute nocc, nvir to include the frozen orbitals and make contraction for
# the 1-particle quantities, see also the kernel function in ccsd_grad module.
mo_coeff = mp.mo_coeff
mo_energy = mp._scf.mo_energy
nao, nmo = mo_coeff.shape
nocc = numpy.count_nonzero(mp.mo_occ > 0)
Imat = reduce(numpy.dot, (mo_coeff.T, Imat, mp._scf.get_ovlp(), mo_coeff)) * -1
dm1mo = numpy.zeros((nmo,nmo))
if with_frozen:
dco = Imat[OF[:,None],OA] / (mo_energy[OF,None] - mo_energy[OA])
dfv = Imat[VF[:,None],VA] / (mo_energy[VF,None] - mo_energy[VA])
dm1mo[OA[:,None],OA] = doo + doo.T
dm1mo[OF[:,None],OA] = dco
dm1mo[OA[:,None],OF] = dco.T
dm1mo[VA[:,None],VA] = dvv + dvv.T
dm1mo[VF[:,None],VA] = dfv
dm1mo[VA[:,None],VF] = dfv.T
else:
dm1mo[:nocc,:nocc] = doo + doo.T
dm1mo[nocc:,nocc:] = dvv + dvv.T
dm1 = reduce(numpy.dot, (mo_coeff, dm1mo, mo_coeff.T))
vhf = mp._scf.get_veff(mp.mol, dm1) * 2
Xvo = reduce(numpy.dot, (mo_coeff[:,nocc:].T, vhf, mo_coeff[:,:nocc]))
Xvo+= Imat[:nocc,nocc:].T - Imat[nocc:,:nocc]
dm1mo += _response_dm1(mp, Xvo)
time1 = log.timer_debug1('response_rdm1 intermediates', *time1)
Imat[nocc:,:nocc] = Imat[:nocc,nocc:].T
im1 = reduce(numpy.dot, (mo_coeff, Imat, mo_coeff.T))
time1 = log.timer_debug1('response_rdm1', *time1)
log.debug('h1 and JK1')
# Initialize hcore_deriv with the underlying SCF object because some
# extensions (e.g. QM/MM, solvent) modifies the SCF object only.
mf_grad = mp_grad.base._scf.nuc_grad_method()
hcore_deriv = mf_grad.hcore_generator(mol)
s1 = mf_grad.get_ovlp(mol)
zeta = lib.direct_sum('i+j->ij', mo_energy, mo_energy) * .5
zeta[nocc:,:nocc] = mo_energy[:nocc]
zeta[:nocc,nocc:] = mo_energy[:nocc].reshape(-1,1)
zeta = reduce(numpy.dot, (mo_coeff, zeta*dm1mo, mo_coeff.T))
dm1 = reduce(numpy.dot, (mo_coeff, dm1mo, mo_coeff.T))
p1 = numpy.dot(mo_coeff[:,:nocc], mo_coeff[:,:nocc].T)
vhf_s1occ = reduce(numpy.dot, (p1, mp._scf.get_veff(mol, dm1+dm1.T), p1))
time1 = log.timer_debug1('h1 and JK1', *time1)
# Hartree-Fock part contribution
dm1p = hf_dm1 + dm1*2
dm1 += hf_dm1
zeta += rhf_grad.make_rdm1e(mo_energy, mo_coeff, mp.mo_occ)
for k, ia in enumerate(atmlst):
shl0, shl1, p0, p1 = offsetdic[ia]
# s[1] dot I, note matrix im1 is not hermitian
de[k] += numpy.einsum('xij,ij->x', s1[:,p0:p1], im1[p0:p1])
de[k] += numpy.einsum('xji,ij->x', s1[:,p0:p1], im1[:,p0:p1])
# h[1] \dot DM, contribute to f1
h1ao = hcore_deriv(ia)
de[k] += numpy.einsum('xij,ji->x', h1ao, dm1)
# -s[1]*e \dot DM, contribute to f1
de[k] -= numpy.einsum('xij,ij->x', s1[:,p0:p1], zeta[p0:p1] )
de[k] -= numpy.einsum('xji,ij->x', s1[:,p0:p1], zeta[:,p0:p1])
# -vhf[s_ij[1]], contribute to f1, *2 for s1+s1.T
de[k] -= numpy.einsum('xij,ij->x', s1[:,p0:p1], vhf_s1occ[p0:p1]) * 2
de[k] -= numpy.einsum('xij,ij->x', vhf1[k], dm1p)
log.timer('%s gradients' % mp.__class__.__name__, *time0)
return de
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def as_scanner(grad_mp):
'''Generating a nuclear gradients scanner/solver (for geometry optimizer).
The returned solver is a function. This function requires one argument
"mol" as input and returns total MP2 energy.
The solver will automatically use the results of last calculation as the
initial guess of the new calculation. All parameters assigned in the
MP2 and the underlying SCF objects (max_memory etc) are automatically
applied in the solver.
Note scanner has side effects. It may change many underlying objects
(_scf, with_df, with_x2c, ...) during calculation.
Examples::
>>> from pyscf import gto, scf, mp
>>> mol = gto.M(atom='H 0 0 0; F 0 0 1')
>>> mp2_scanner = mp.MP2(scf.RHF(mol)).nuc_grad_method().as_scanner()
>>> e_tot, grad = mp2_scanner(gto.M(atom='H 0 0 0; F 0 0 1.1'))
>>> e_tot, grad = mp2_scanner(gto.M(atom='H 0 0 0; F 0 0 1.5'))
'''
if isinstance(grad_mp, lib.GradScanner):
return grad_mp
logger.info(grad_mp, 'Create scanner for %s', grad_mp.__class__)
name = grad_mp.__class__.__name__ + MP2_GradScanner.__name_mixin__
return lib.set_class(MP2_GradScanner(grad_mp),
(MP2_GradScanner, grad_mp.__class__), name)
[docs]
class MP2_GradScanner(lib.GradScanner):
def __init__(self, g):
lib.GradScanner.__init__(self, g)
def __call__(self, mol_or_geom, **kwargs):
if isinstance(mol_or_geom, gto.MoleBase):
assert mol_or_geom.__class__ == gto.Mole
mol = mol_or_geom
else:
mol = self.mol.set_geom_(mol_or_geom, inplace=False)
self.reset(mol)
mp_scanner = self.base
mp_scanner(mol, with_t2=True)
de = self.kernel(mp_scanner.t2)
return mp_scanner.e_tot, de
@property
def converged(self):
return self.base._scf.converged
def _shell_prange(mol, start, stop, blksize):
l = mol._bas[start:stop,gto.ANG_OF]
if mol.cart:
dims = (l+1)*(l+2)//2 * mol._bas[start:stop,gto.NCTR_OF]
else:
dims = (l*2+1) * mol._bas[start:stop,gto.NCTR_OF]
nao = 0
ib0 = start
for ib, now in zip(range(start, stop), dims):
nao += now
if nao > blksize:
yield (ib0, ib, nao-now)
ib0 = ib
nao = now
yield (ib0, stop, nao)
def _response_dm1(mp, Xvo):
nvir, nocc = Xvo.shape
nmo = nocc + nvir
mo_energy = mp._scf.mo_energy
mo_occ = mp.mo_occ
mo_coeff = mp.mo_coeff
def fvind(x):
x = x.reshape(Xvo.shape)
dm = reduce(numpy.dot, (mo_coeff[:,nocc:], x, mo_coeff[:,:nocc].T))
v = mp._scf.get_veff(mp.mol, dm + dm.T)
v = reduce(numpy.dot, (mo_coeff[:,nocc:].T, v, mo_coeff[:,:nocc]))
return v * 2
dvo = cphf.solve(fvind, mo_energy, mo_occ, Xvo, max_cycle=30)[0]
dm1 = numpy.zeros((nmo,nmo))
dm1[nocc:,:nocc] = dvo
dm1[:nocc,nocc:] = dvo.T
return dm1
def _index_frozen_active(frozen_mask, mo_occ):
OA = numpy.where(( frozen_mask) & (mo_occ> 0))[0] # occupied active orbitals
OF = numpy.where((~frozen_mask) & (mo_occ> 0))[0] # occupied frozen orbitals
VA = numpy.where(( frozen_mask) & (mo_occ==0))[0] # virtual active orbitals
VF = numpy.where((~frozen_mask) & (mo_occ==0))[0] # virtual frozen orbitals
return OA, VA, OF, VF
[docs]
class Gradients(rhf_grad.GradientsBase):
grad_elec = grad_elec
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def kernel(self, t2=None, atmlst=None, verbose=None):
log = logger.new_logger(self, verbose)
if t2 is None: t2 = self.base.t2
if t2 is None: t2 = self.base.kernel()[1]
if atmlst is None:
atmlst = self.atmlst
else:
self.atmlst = atmlst
de = self.grad_elec(t2, atmlst, verbose=log)
self.de = de + self.grad_nuc(atmlst=atmlst)
if self.mol.symmetry:
self.de = self.symmetrize(self.de, atmlst)
self._finalize()
return self.de
# Calling the underlying SCF nuclear gradients because it may be modified
# by external modules (e.g. QM/MM, solvent)
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def grad_nuc(self, mol=None, atmlst=None):
mf_grad = self.base._scf.nuc_grad_method()
return mf_grad.grad_nuc(mol, atmlst)
as_scanner = as_scanner
to_gpu = lib.to_gpu
Grad = Gradients
# Inject to RMP2 class
mp2.MP2.Gradients = lib.class_as_method(Gradients)
