#!/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>
#
'''
Co-iterative augmented hessian second order SCF solver (CIAH-SOSCF)
'''
from functools import reduce
import numpy
from pyscf import lib
from pyscf.pbc.scf import _response_functions # noqa
from pyscf.soscf import newton_ah
[docs]
def gen_g_hop_rhf(mf, mo_coeff, mo_occ, fock_ao=None, h1e=None):
cell = mf.cell
nkpts = len(mo_occ)
occidx = [numpy.where(mo_occ[k]==2)[0] for k in range(nkpts)]
viridx = [numpy.where(mo_occ[k]==0)[0] for k in range(nkpts)]
orbo = [mo_coeff[k][:,occidx[k]] for k in range(nkpts)]
orbv = [mo_coeff[k][:,viridx[k]] for k in range(nkpts)]
if fock_ao is None:
if h1e is None: h1e = mf.get_hcore()
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = h1e + mf.get_veff(cell, dm0)
fock = [reduce(numpy.dot, (mo_coeff[k].conj().T, fock_ao[k], mo_coeff[k]))
for k in range(nkpts)]
g = [fock[k][viridx[k][:,None],occidx[k]] * 2 for k in range(nkpts)]
foo = [fock[k][occidx[k][:,None],occidx[k]] for k in range(nkpts)]
fvv = [fock[k][viridx[k][:,None],viridx[k]] for k in range(nkpts)]
h_diag = [(fvv[k].diagonal().real[:,None]-foo[k].diagonal().real) * 2
for k in range(nkpts)]
vind = mf.gen_response(mo_coeff, mo_occ, singlet=None, hermi=1)
def h_op(x1):
x1 = _unpack(x1, mo_occ)
dm1 = []
for k in range(nkpts):
# *2 for double occupancy
d1 = reduce(numpy.dot, (orbv[k], x1[k]*2, orbo[k].conj().T))
dm1.append(d1+d1.conj().T)
v1 = vind(lib.asarray(dm1))
x2 = [0] * nkpts
for k in range(nkpts):
x2[k] = numpy.einsum('ps,sq->pq', fvv[k], x1[k]) * 2
x2[k]-= numpy.einsum('ps,rp->rs', foo[k], x1[k]) * 2
x2[k] += reduce(numpy.dot, (orbv[k].conj().T, v1[k], orbo[k])) * 2
return numpy.hstack([x.ravel() for x in x2])
return (numpy.hstack([x.ravel() for x in g]), h_op,
numpy.hstack([x.ravel() for x in h_diag]))
[docs]
def gen_g_hop_uhf(mf, mo_coeff, mo_occ, fock_ao=None, h1e=None):
cell = mf.cell
nkpts = len(mo_occ[0])
occidxa = [numpy.where(mo_occ[0][k]>0)[0] for k in range(nkpts)]
occidxb = [numpy.where(mo_occ[1][k]>0)[0] for k in range(nkpts)]
viridxa = [numpy.where(mo_occ[0][k]==0)[0] for k in range(nkpts)]
viridxb = [numpy.where(mo_occ[1][k]==0)[0] for k in range(nkpts)]
moa, mob = mo_coeff
orboa = [moa[k][:,occidxa[k]] for k in range(nkpts)]
orbva = [moa[k][:,viridxa[k]] for k in range(nkpts)]
orbob = [mob[k][:,occidxb[k]] for k in range(nkpts)]
orbvb = [mob[k][:,viridxb[k]] for k in range(nkpts)]
tot_vopair_a = sum(len(occidxa[k])*len(viridxa[k]) for k in range(nkpts))
if fock_ao is None:
if h1e is None: h1e = mf.get_hcore()
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = h1e + mf.get_veff(cell, dm0)
focka = [reduce(numpy.dot, (moa[k].conj().T, fock_ao[0][k], moa[k]))
for k in range(nkpts)]
fockb = [reduce(numpy.dot, (mob[k].conj().T, fock_ao[1][k], mob[k]))
for k in range(nkpts)]
fooa = [focka[k][occidxa[k][:,None],occidxa[k]] for k in range(nkpts)]
fvva = [focka[k][viridxa[k][:,None],viridxa[k]] for k in range(nkpts)]
foob = [fockb[k][occidxb[k][:,None],occidxb[k]] for k in range(nkpts)]
fvvb = [fockb[k][viridxb[k][:,None],viridxb[k]] for k in range(nkpts)]
g = ([focka[k][viridxa[k][:,None],occidxa[k]] for k in range(nkpts)] +
[fockb[k][viridxb[k][:,None],occidxb[k]] for k in range(nkpts)])
h_diag = ([fvva[k].diagonal().real[:,None]-fooa[k].diagonal().real for k in range(nkpts)] +
[fvvb[k].diagonal().real[:,None]-foob[k].diagonal().real for k in range(nkpts)])
vind = mf.gen_response(mo_coeff, mo_occ, hermi=1)
nao = orboa[0].shape[0]
def h_op(x1):
x1a = _unpack(x1[:tot_vopair_a], mo_occ[0])
x1b = _unpack(x1[tot_vopair_a:], mo_occ[1])
dm1 = numpy.empty((2,nkpts,nao,nao), dtype=x1.dtype)
for k in range(nkpts):
d1 = reduce(numpy.dot, (orbva[k], x1a[k], orboa[k].conj().T))
dm1[0,k] = d1+d1.conj().T
for k in range(nkpts):
d1 = reduce(numpy.dot, (orbvb[k], x1b[k], orbob[k].conj().T))
dm1[1,k] = d1+d1.conj().T
v1 = vind(dm1)
x2a = [0] * nkpts
x2b = [0] * nkpts
for k in range(nkpts):
x2a[k] = numpy.einsum('ps,sq->pq', fvva[k], x1a[k])
x2a[k]-= numpy.einsum('ps,rp->rs', fooa[k], x1a[k])
x2b[k] = numpy.einsum('ps,sq->pq', fvvb[k], x1b[k])
x2b[k]-= numpy.einsum('ps,rp->rs', foob[k], x1b[k])
x2a[k] += reduce(numpy.dot, (orbva[k].conj().T, v1[0][k], orboa[k]))
x2b[k] += reduce(numpy.dot, (orbvb[k].conj().T, v1[1][k], orbob[k]))
return numpy.hstack([x.ravel() for x in (x2a+x2b)])
return (numpy.hstack([x.ravel() for x in g]), h_op,
numpy.hstack([x.ravel() for x in h_diag]))
[docs]
def gen_g_hop_rohf(mf, mo_coeff, mo_occ, fock_ao=None, h1e=None):
if getattr(fock_ao, 'focka', None) is None:
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = mf.get_fock(h1e, dm=dm0)
fock_ao = fock_ao.focka, fock_ao.fockb
mo_occa = occidxa = [occ > 0 for occ in mo_occ]
mo_occb = occidxb = [occ ==2 for occ in mo_occ]
ug, uh_op, uh_diag = gen_g_hop_uhf(mf, (mo_coeff,)*2, (mo_occa,mo_occb),
fock_ao, None)
nkpts = len(mo_occ)
idx_var_a = []
idx_var_b = []
p0 = 0
for k in range(nkpts):
viridxa = ~occidxa[k]
viridxb = ~occidxb[k]
uniq_var_a = viridxa[:,None] & occidxa[k]
uniq_var_b = viridxb[:,None] & occidxb[k]
uniq_ab = uniq_var_a | uniq_var_b
nmo = len(mo_occ[k])
n_uniq_ab = numpy.count_nonzero(uniq_ab)
idx_array = numpy.zeros((nmo,nmo), dtype=int)
idx_array[uniq_ab] = numpy.arange(n_uniq_ab)
idx_var_a.append(p0 + idx_array[uniq_var_a])
idx_var_b.append(p0 + idx_array[uniq_var_b])
p0 += n_uniq_ab
idx_var_a = numpy.hstack(idx_var_a)
idx_var_b = numpy.hstack(idx_var_b)
nvars = p0
def sum_ab(x):
x1 = numpy.zeros(nvars, dtype=x.dtype)
x1[idx_var_a] = x[:len(idx_var_a)]
x1[idx_var_b] += x[len(idx_var_a):]
return x1
g = sum_ab(ug)
h_diag = sum_ab(uh_diag)
def h_op(x):
# unpack ROHF rotation parameters
x1 = numpy.hstack((x[idx_var_a], x[idx_var_b]))
return sum_ab(uh_op(x1))
return g, h_op, h_diag
# Be careful with the parameter ordering conventions are different for the
# _unpack function here and the one in tdscf.krhf
def _unpack(vo, mo_occ):
z = []
p1 = 0
for k, occ in enumerate(mo_occ):
no = numpy.count_nonzero(occ > 0)
nv = occ.size - no
p0, p1 = p1, p1 + nv * no
z.append(vo[p0:p1].reshape(nv,no))
return z
class _SecondOrderKRHF(newton_ah._CIAH_SOSCF):
gen_g_hop = gen_g_hop_rhf
def update_rotate_matrix(self, dx, mo_occ, u0=1, mo_coeff=None):
p0 = 0
u = []
for k, occ in enumerate(mo_occ):
occidx = occ > 0
viridx = ~occidx
nocc = occidx.sum()
nvir = viridx.sum()
nmo = nocc + nvir
dr = numpy.zeros((nmo,nmo), dtype=dx.dtype)
dr[viridx[:,None] & occidx] = dx[p0:p0+nocc*nvir]
dr = dr - dr.conj().T
p0 += nocc * nvir
u1 = newton_ah.expmat(dr)
if isinstance(u0, int) and u0 == 1:
u.append(u1)
else:
u.append(numpy.dot(u0[k], u1))
return lib.asarray(u)
def rotate_mo(self, mo_coeff, u, log=None):
return lib.asarray([numpy.dot(mo, u[k]) for k,mo in enumerate(mo_coeff)])
class _SecondOrderKUHF(newton_ah._CIAH_SOSCF):
gen_g_hop = gen_g_hop_uhf
def update_rotate_matrix(self, dx, mo_occ, u0=1, mo_coeff=None):
nkpts = len(mo_occ[0])
p0 = 0
u = []
for occ in mo_occ:
ua = []
for k in range(nkpts):
occidx = occ[k] > 0
viridx = ~occidx
nocc = occidx.sum()
nvir = viridx.sum()
nmo = nocc + nvir
dr = numpy.zeros((nmo,nmo), dtype=dx.dtype)
dr[viridx[:,None] & occidx] = dx[p0:p0+nocc*nvir]
dr = dr - dr.conj().T
p0 += nocc * nvir
u1 = newton_ah.expmat(dr)
if isinstance(u0, int) and u0 == 1:
ua.append(u1)
else:
ua.append(numpy.dot(u0[k], u1))
u.append(ua)
return lib.asarray(u)
def rotate_mo(self, mo_coeff, u, log=None):
mo = ([numpy.dot(mo, u[0][k]) for k, mo in enumerate(mo_coeff[0])],
[numpy.dot(mo, u[1][k]) for k, mo in enumerate(mo_coeff[1])])
return lib.asarray(mo)
class _SecondOrderKROHF(_SecondOrderKRHF):
gen_g_hop = gen_g_hop_rohf
[docs]
def newton(mf):
from pyscf.pbc import scf as pscf
if not isinstance(mf, pscf.khf.KSCF):
# Note for single k-point other than gamma point (mf.kpt != 0) mf object,
# orbital hessian is approximated by gamma point hessian.
return newton_ah.newton(mf)
if isinstance(mf, newton_ah._CIAH_SOSCF):
return mf
if isinstance(mf, pscf.kuhf.KUHF):
cls = _SecondOrderKUHF
elif isinstance(mf, pscf.krohf.KROHF):
cls = _SecondOrderKROHF
elif isinstance(mf, pscf.kghf.KGHF):
raise NotImplementedError
else:
cls = _SecondOrderKRHF
return lib.set_class(cls(mf), (cls, mf.__class__))
if __name__ == '__main__':
import pyscf.pbc.gto as pbcgto
import pyscf.pbc.scf as pscf
cell = pbcgto.Cell()
cell.atom = '''
He 0 0 1
He 1 0 1
'''
cell.basis = 'ccpvdz'
cell.a = numpy.eye(3) * 4
cell.mesh = [11] * 3
cell.verbose = 4
cell.build()
nks = [2,1,1]
mf = pscf.KRHF(cell, cell.make_kpts(nks))
mf.max_cycle = 2
mf.kernel()
mf.max_cycle = 5
pscf.newton(mf).kernel()
mf = pscf.KUHF(cell, cell.make_kpts(nks))
mf.max_cycle = 2
mf.kernel()
mf.max_cycle = 5
pscf.newton(mf).kernel()
