def __init__(self, cis, mo_coeff=None, method="incore"):
log = logger.Logger(cis.stdout, cis.verbose)
cput0 = (time.clock(), time.time())
moidx = get_frozen_mask(cis)
cell = cis._scf.cell
nocc = cis.nocc
nmo = cis.nmo
nvir = nmo - nocc
nkpts = cis.nkpts
kpts = cis.kpts
if mo_coeff is None:
mo_coeff = cis.mo_coeff
dtype = mo_coeff[0].dtype
mo_coeff = self.mo_coeff = padded_mo_coeff(cis, mo_coeff)
# Re-make our fock MO matrix elements from density and fock AO
dm = cis._scf.make_rdm1(cis.mo_coeff, cis.mo_occ)
exxdiv = cis._scf.exxdiv if cis.keep_exxdiv else None
with lib.temporary_env(cis._scf, exxdiv=exxdiv):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cis._scf.get_hcore() + cis._scf.get_veff(cell, dm)
self.fock = np.asarray([
reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)
])
self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]
if not cis.keep_exxdiv:
# Add HFX correction in the self.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
self.mo_energy = [
_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(self.mo_energy)
]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cis, per_kpoint=True)
nonzero_padding = padding_k_idx(cis, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = np.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt) - 1]
if gap < 1e-5:
logger.warn(
cis,
"H**O-LUMO gap %s too small for KCCSD. "
"May cause issues in convergence.",
gap,
)
memory_needed = (nkpts**3 * nocc**2 * nvir**2) * 16 / 1e6
# CIS only needs two terms: <aj|ib> and <aj|bi>; another factor of two for safety
memory_needed *= 4
memory_now = lib.current_memory()[0]
fao2mo = cis._scf.with_df.ao2mo
kconserv = cis.khelper.kconserv
khelper = cis.khelper
if cis.direct and type(cis._scf.with_df) is not df.GDF:
raise ValueError("CIS direct method must be used with GDF")
if (cis.direct and type(cis._scf.with_df) is df.GDF
and cell.dimension != 2):
# cis._scf.with_df needs to be df.GDF only (not MDF)
_init_cis_df_eris(cis, self)
else:
if (method == "incore" and
(memory_needed + memory_now < cis.max_memory)
or cell.incore_anyway):
log.info("using incore ERI storage")
self.ovov = np.empty(
(nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype=dtype)
self.voov = np.empty(
(nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype=dtype)
for (ikp, ikq, ikr) in khelper.symm_map.keys():
iks = kconserv[ikp, ikq, ikr]
eri_kpt = fao2mo(
(mo_coeff[ikp], mo_coeff[ikq], mo_coeff[ikr],
mo_coeff[iks]),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]),
compact=False,
)
if dtype == np.float:
eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
eri_kpt_symm = khelper.transform_symm(
eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.ovov[kp, kr, kq] = (
eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts)
self.voov[kp, kr, kq] = (
eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts)
self.dtype = dtype
else:
log.info("using HDF5 ERI storage")
self.feri1 = lib.H5TmpFile()
self.ovov = self.feri1.create_dataset(
"ovov", (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir),
dtype.char)
self.voov = self.feri1.create_dataset(
"voov", (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir),
dtype.char)
# <ia|pq> = (ip|aq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbv_r = mo_coeff[kr][:, nocc:]
buf_kpt = fao2mo(
(orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False,
)
if mo_coeff[0].dtype == np.float:
buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nvir,
nmo).transpose(
0, 2, 1, 3)
self.dtype = buf_kpt.dtype
self.ovov[kp, kr, kq, :, :, :, :] = (
buf_kpt[:, :, :nocc, nocc:] / nkpts)
self.voov[kr, kp, ks, :, :, :, :] = (
buf_kpt[:, :, nocc:, :nocc].transpose(
1, 0, 3, 2) / nkpts)
cput1 = log.timer_debug1("transforming ovpq", *cput1)
log.timer("CIS integral transformation", *cput0)
def __init__(self, cc, mo_coeff=None):
from pyscf.pbc.cc.ccsd import _adjust_occ
import pyscf.pbc.tools.pbc as tools
if mo_coeff is None:
mo_coeff = cc.mo_coeff
cput0 = (time.clock(), time.time())
symlib = cc.symlib
log = Logger(cc.stdout, cc.verbose)
self.lib = lib
nocc, nmo, nkpts = cc.nocc, cc.nmo, cc.nkpts
nvir = nmo - nocc
cell, kpts = cc._scf.cell, cc.kpts
gvec = cell.reciprocal_vectors()
sym1 = ['+-', [kpts,]*2, None, gvec]
sym2 = ['+-+-', [kpts,]*4, None, gvec]
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
madelung = tools.madelung(cell, kpts)
fock = None
if rank==0:
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with pyscflib.temporary_env(cc._scf, exxdiv=None):
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
fock = np.asarray([reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)])
fock = comm.bcast(fock, root=0)
self.dtype = dtype = np.result_type(*(mo_coeff, fock)).char
self.foo = zeros([nocc,nocc], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.fov = zeros([nocc,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.fvv = zeros([nvir,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.eia = zeros([nocc,nvir], np.float64, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self._foo = zeros([nocc,nocc], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self._fvv = zeros([nvir,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
foo = fock[:,:nocc,:nocc]
fov = fock[:,:nocc,nocc:]
fvv = fock[:,nocc:,nocc:]
mo_energy = [fock[k].diagonal().real for k in range(nkpts)]
mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(mo_energy)]
mo_e_o = [e[:nocc] for e in mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in mo_energy]
foo_ = np.asarray([np.diag(e) for e in mo_e_o])
fvv_ = np.asarray([np.diag(e) for e in mo_e_v])
eia = np.zeros([nkpts,nocc,nvir])
for ki in range(nkpts):
eia[ki] = _get_epq([0,nocc,ki,mo_e_o,nonzero_opadding],
[0,nvir,ki,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
if rank ==0:
self.foo.write(range(foo.size), foo.ravel())
self.fov.write(range(fov.size), fov.ravel())
self.fvv.write(range(fvv.size), fvv.ravel())
self.eia.write(range(eia.size), eia.ravel())
self._foo.write(range(foo_.size), foo_.ravel())
self._fvv.write(range(fvv_.size), fvv_.ravel())
else:
self.foo.write([],[])
self.fov.write([],[])
self.fvv.write([],[])
self.eia.write([],[])
self._foo.write([],[])
self._fvv.write([],[])
self.eijab = zeros([nocc,nocc,nvir,nvir], np.float64, sym2, symlib=symlib, verbose=cc.SYMVERBOSE)
kconserv = cc.khelper.kconserv
khelper = cc.khelper
idx_oovv = np.arange(nocc*nocc*nvir*nvir)
jobs = list(khelper.symm_map.keys())
tasks = static_partition(jobs)
ntasks = max(comm.allgather(len(tasks)))
nwrite = 0
for itask in tasks:
ikp, ikq, ikr = itask
pqr = np.asarray(khelper.symm_map[(ikp,ikq,ikr)])
nwrite += len(np.unique(pqr, axis=0))
nwrite_max = max(comm.allgather(nwrite))
write_count = 0
for itask in range(ntasks):
if itask >= len(tasks):
continue
ikp, ikq, ikr = tasks[itask]
iks = kconserv[ikp,ikq,ikr]
done = np.zeros([nkpts,nkpts,nkpts])
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
if done[kp,kq,kr]: continue
ks = kconserv[kp,kq,kr]
eia = _get_epq([0,nocc,kp,mo_e_o,nonzero_opadding],
[0,nvir,kq,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
ejb = _get_epq([0,nocc,kr,mo_e_o,nonzero_opadding],
[0,nvir,ks,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
eijab = eia[:,None,:,None] + ejb[None,:,None,:]
off = kp * nkpts**2 + kr * nkpts + kq
self.eijab.write(off*idx_oovv.size+idx_oovv, eijab.ravel())
done[kp,kq,kr] = 1
write_count += 1
for i in range(nwrite_max-write_count):
self.eijab.write([], [])
if type(cc._scf.with_df) is df.FFTDF:
_make_fftdf_eris(cc, self)
else:
from cc_sym import mpigdf
if type(cc._scf.with_df) is mpigdf.GDF:
_make_df_eris(cc, self)
elif type(cc._scf.with_df) is df.GDF:
log.warn("GDF converted to an MPIGDF object")
cc._scf.with_df = mpigdf.from_serial(cc._scf.with_df)
_make_df_eris(cc, self)
else:
raise NotImplementedError("DF object not recognized")
log.timer("ao2mo transformation", *cput0)
def __init__(self, cc, mo_coeff=None, method='incore'):
from pyscf.pbc import df
from pyscf.pbc import tools
from pyscf.pbc.cc.ccsd import _adjust_occ
log = logger.Logger(cc.stdout, cc.verbose)
cput0 = (time.clock(), time.time())
moidx = get_frozen_mask(cc)
cell = cc._scf.cell
kpts = cc.kpts
nkpts = cc.nkpts
nocc = cc.nocc
nmo = cc.nmo
nvir = nmo - nocc
# if any(nocc != np.count_nonzero(cc._scf.mo_occ[k]>0)
# for k in range(nkpts)):
# raise NotImplementedError('Different occupancies found for different k-points')
if mo_coeff is None:
mo_coeff = cc.mo_coeff
dtype = mo_coeff[0].dtype
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
# Re-make our fock MO matrix elements from density and fock AO
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with lib.temporary_env(cc._scf, exxdiv=None):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
self.fock = np.asarray([reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)])
self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]
# Add HFX correction in the self.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
self.mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(self.mo_energy)]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cc, per_kpoint=True)
nonzero_padding = padding_k_idx(cc, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = np.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt)-1]
if gap < 1e-5:
logger.warn(cc, 'H**O-LUMO gap %s too small for KCCSD. '
'May cause issues in convergence.', gap)
mem_incore, mem_outcore, mem_basic = _mem_usage(nkpts, nocc, nvir)
mem_now = lib.current_memory()[0]
fao2mo = cc._scf.with_df.ao2mo
kconserv = cc.khelper.kconserv
khelper = cc.khelper
orbo = np.asarray(mo_coeff[:,:,:nocc], order='C')
orbv = np.asarray(mo_coeff[:,:,nocc:], order='C')
if (method == 'incore' and (mem_incore + mem_now < cc.max_memory)
or cell.incore_anyway):
log.info('using incore ERI storage')
self.oooo = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nocc), dtype=dtype)
self.ooov = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nvir), dtype=dtype)
self.oovv = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nvir,nvir), dtype=dtype)
self.ovov = np.empty((nkpts,nkpts,nkpts,nocc,nvir,nocc,nvir), dtype=dtype)
self.voov = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nocc,nvir), dtype=dtype)
self.vovv = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nvir,nvir), dtype=dtype)
#self.vvvv = np.empty((nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype=dtype)
self.vvvv = cc._scf.with_df.ao2mo_7d(orbv, factor=1./nkpts).transpose(0,2,1,3,5,4,6)
for (ikp,ikq,ikr) in khelper.symm_map.keys():
iks = kconserv[ikp,ikq,ikr]
eri_kpt = fao2mo((mo_coeff[ikp],mo_coeff[ikq],mo_coeff[ikr],mo_coeff[iks]),
(kpts[ikp],kpts[ikq],kpts[ikr],kpts[iks]), compact=False)
if dtype == np.float: eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
eri_kpt_symm = khelper.transform_symm(eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.oooo[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, :nocc] / nkpts
self.ooov[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, nocc:] / nkpts
self.oovv[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, nocc:, nocc:] / nkpts
self.ovov[kp, kr, kq] = eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts
self.voov[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts
self.vovv[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, nocc:, nocc:] / nkpts
#self.vvvv[kp, kr, kq] = eri_kpt_symm[nocc:, nocc:, nocc:, nocc:] / nkpts
self.dtype = dtype
else:
log.info('using HDF5 ERI storage')
self.feri1 = lib.H5TmpFile()
self.oooo = self.feri1.create_dataset('oooo', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nocc), dtype.char)
self.ooov = self.feri1.create_dataset('ooov', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nvir), dtype.char)
self.oovv = self.feri1.create_dataset('oovv', (nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype.char)
self.ovov = self.feri1.create_dataset('ovov', (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype.char)
self.voov = self.feri1.create_dataset('voov', (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype.char)
self.vovv = self.feri1.create_dataset('vovv', (nkpts, nkpts, nkpts, nvir, nocc, nvir, nvir), dtype.char)
vvvv_required = ((not cc.direct)
# cc._scf.with_df needs to be df.GDF only (not MDF)
or type(cc._scf.with_df) is not df.GDF
# direct-vvvv for pbc-2D is not supported so far
or cell.dimension == 2)
if vvvv_required:
self.vvvv = self.feri1.create_dataset('vvvv', (nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype.char)
# <ij|pq> = (ip|jq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbo_r = mo_coeff[kr][:, :nocc]
buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbo_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nocc, nmo).transpose(0, 2, 1, 3)
self.dtype = buf_kpt.dtype
self.oooo[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, :nocc] / nkpts
self.ooov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
self.oovv[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:] / nkpts
cput1 = log.timer_debug1('transforming oopq', *cput1)
# <ia|pq> = (ip|aq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbv_r = mo_coeff[kr][:, nocc:]
buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nvir, nmo).transpose(0, 2, 1, 3)
self.ovov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
# TODO: compute vovv on the fly
self.vovv[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:].transpose(1, 0, 3, 2) / nkpts
self.voov[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, :nocc].transpose(1, 0, 3, 2) / nkpts
cput1 = log.timer_debug1('transforming ovpq', *cput1)
## Without k-point symmetry
# cput1 = time.clock(), time.time()
# for kp in range(nkpts):
# for kq in range(nkpts):
# for kr in range(nkpts):
# ks = kconserv[kp,kq,kr]
# orbv_p = mo_coeff[kp][:,nocc:]
# orbv_q = mo_coeff[kq][:,nocc:]
# orbv_r = mo_coeff[kr][:,nocc:]
# orbv_s = mo_coeff[ks][:,nocc:]
# for a in range(nvir):
# orbva_p = orbv_p[:,a].reshape(-1,1)
# buf_kpt = fao2mo((orbva_p,orbv_q,orbv_r,orbv_s),
# (kpts[kp],kpts[kq],kpts[kr],kpts[ks]), compact=False)
# if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
# buf_kpt = buf_kpt.reshape((1,nvir,nvir,nvir)).transpose(0,2,1,3)
# self.vvvv[kp,kr,kq,a,:,:,:] = buf_kpt[:] / nkpts
# cput1 = log.timer_debug1('transforming vvvv', *cput1)
cput1 = time.clock(), time.time()
mem_now = lib.current_memory()[0]
if not vvvv_required:
_init_df_eris(cc, self)
elif nvir ** 4 * 16 / 1e6 + mem_now < cc.max_memory:
for (ikp, ikq, ikr) in khelper.symm_map.keys():
iks = kconserv[ikp, ikq, ikr]
orbv_p = mo_coeff[ikp][:, nocc:]
orbv_q = mo_coeff[ikq][:, nocc:]
orbv_r = mo_coeff[ikr][:, nocc:]
orbv_s = mo_coeff[iks][:, nocc:]
# unit cell is small enough to handle vvvv in-core
buf_kpt = fao2mo((orbv_p,orbv_q,orbv_r,orbv_s),
kpts[[ikp,ikq,ikr,iks]], compact=False)
if dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape((nvir, nvir, nvir, nvir))
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
buf_kpt_symm = khelper.transform_symm(buf_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.vvvv[kp, kr, kq] = buf_kpt_symm / nkpts
else:
raise MemoryError('Minimal memory requirements %s MB'
% (mem_now + nvir ** 4 / 1e6 * 16 * 2))
for (ikp, ikq, ikr) in khelper.symm_map.keys():
for a in range(nvir):
orbva_p = orbv_p[:, a].reshape(-1, 1)
buf_kpt = fao2mo((orbva_p, orbv_q, orbv_r, orbv_s),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape((1, nvir, nvir, nvir)).transpose(0, 2, 1, 3)
self.vvvv[ikp, ikr, ikq, a, :, :, :] = buf_kpt[0, :, :, :] / nkpts
# Store symmetric permutations
self.vvvv[ikr, ikp, iks, :, a, :, :] = buf_kpt.transpose(1, 0, 3, 2)[:, 0, :, :] / nkpts
self.vvvv[ikq, iks, ikp, :, :, a, :] = buf_kpt.transpose(2, 3, 0, 1).conj()[:, :, 0, :] / nkpts
self.vvvv[iks, ikq, ikr, :, :, :, a] = buf_kpt.transpose(3, 2, 1, 0).conj()[:, :, :, 0] / nkpts
cput1 = log.timer_debug1('transforming vvvv', *cput1)
log.timer('CCSD integral transformation', *cput0)
def __init__(self, cc, mo_coeff=None):
from pyscf.pbc.cc.ccsd import _adjust_occ
import pyscf.pbc.tools.pbc as tools
if mo_coeff is None:
mo_coeff = cc.mo_coeff
cput0 = (time.clock(), time.time())
log = Logger(cc.stdout, cc.verbose)
self.lib = lib
nocc, nmo, nkpts = cc.nocc, cc.nmo, cc.nkpts
nvir = nmo - nocc
cell, kpts = cc._scf.cell, cc.kpts
gvec = cell.reciprocal_vectors()
sym1 = ['+-', [
kpts,
] * 2, None, gvec]
sym2 = ['+-+-', [
kpts,
] * 4, None, gvec]
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
madelung = tools.madelung(cell, kpts)
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with pyscflib.temporary_env(cc._scf, exxdiv=None):
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
fock = np.asarray([
reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)
])
self.dtype = dtype = np.result_type(*fock).char
self.foo = tensor(fock[:, :nocc, :nocc], sym1)
self.fov = tensor(fock[:, :nocc, nocc:], sym1)
self.fvv = tensor(fock[:, nocc:, nocc:], sym1)
mo_energy = [fock[k].diagonal().real for k in range(nkpts)]
mo_energy = [
_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(mo_energy)
]
mo_e_o = [e[:nocc] for e in mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in mo_energy]
foo_ = np.asarray([np.diag(e) for e in mo_e_o])
fvv_ = np.asarray([np.diag(e) for e in mo_e_v])
self._foo = tensor(foo_, sym1)
self._fvv = tensor(fvv_, sym1)
eia = np.zeros([nkpts, nocc, nvir])
for ki in range(nkpts):
eia[ki] = _get_epq([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nvir, ki, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
self.eia = tensor(eia, sym1)
self.oooo = zeros([nocc, nocc, nocc, nocc], dtype, sym2)
self.ooov = zeros([nocc, nocc, nocc, nvir], dtype, sym2)
self.ovov = zeros([nocc, nvir, nocc, nvir], dtype, sym2)
self.oovv = zeros([nocc, nocc, nvir, nvir], dtype, sym2)
self.ovvo = zeros([nocc, nvir, nvir, nocc], dtype, sym2)
self.ovvv = zeros([nocc, nvir, nvir, nvir], dtype, sym2)
self.vvvv = zeros([nvir, nvir, nvir, nvir], dtype, sym2)
self.eijab = zeros([nocc, nocc, nvir, nvir], np.float64, sym2)
with_df = cc._scf.with_df
fao2mo = cc._scf.with_df.ao2mo
kconserv = cc.khelper.kconserv
khelper = cc.khelper
jobs = list(khelper.symm_map.keys())
for itask in jobs:
ikp, ikq, ikr = itask
iks = kconserv[ikp, ikq, ikr]
eri_kpt = fao2mo(
(mo_coeff[ikp], mo_coeff[ikq], mo_coeff[ikr], mo_coeff[iks]),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]),
compact=False)
if dtype == np.float: eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo) / nkpts
done = np.zeros([nkpts, nkpts, nkpts])
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
if done[kp, kq, kr]: continue
eri_kpt_symm = khelper.transform_symm(eri_kpt, kp, kq, kr)
oooo = eri_kpt_symm[:nocc, :nocc, :nocc, :nocc]
ooov = eri_kpt_symm[:nocc, :nocc, :nocc, nocc:]
ovov = eri_kpt_symm[:nocc, nocc:, :nocc, nocc:]
oovv = eri_kpt_symm[:nocc, :nocc, nocc:, nocc:]
ovvo = eri_kpt_symm[:nocc, nocc:, nocc:, :nocc]
ovvv = eri_kpt_symm[:nocc, nocc:, nocc:, nocc:]
vvvv = eri_kpt_symm[nocc:, nocc:, nocc:, nocc:]
ks = kconserv[kp, kq, kr]
eia = _get_epq([0, nocc, kp, mo_e_o, nonzero_opadding],
[0, nvir, kq, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
ejb = _get_epq([0, nocc, kr, mo_e_o, nonzero_opadding],
[0, nvir, ks, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
eijab = eia[:, None, :, None] + ejb[None, :, None, :]
self.oooo.array[kp, kq, kr] = oooo
self.ooov.array[kp, kq, kr] = ooov
self.ovov.array[kp, kq, kr] = ovov
self.oovv.array[kp, kq, kr] = oovv
self.ovvo.array[kp, kq, kr] = ovvo
self.ovvv.array[kp, kq, kr] = ovvv
self.vvvv.array[kp, kq, kr] = vvvv
self.eijab.array[kp, kr, kq] = eijab
done[kp, kq, kr] = 1
log.timer("ao2mo transformation", *cput0)