def _int_nuc_vloc(mydf, nuccell, kpts, intor='cint3c2e_sph'):
'''Vnuc - Vloc'''
cell = mydf.cell
rcut = max(cell.rcut, nuccell.rcut)
Ls = cell.get_lattice_Ls(rcut=rcut)
expLk = numpy.asarray(numpy.exp(1j * numpy.dot(Ls, kpts.T)), order='C')
nkpts = len(kpts)
# Use the 3c2e code with steep s gaussians to mimic nuclear density
fakenuc = _fake_nuc(cell)
fakenuc._atm, fakenuc._bas, fakenuc._env = \
gto.conc_env(nuccell._atm, nuccell._bas, nuccell._env,
fakenuc._atm, fakenuc._bas, fakenuc._env)
nao = cell.nao_nr()
buf = [
numpy.zeros((nao, nao, fakenuc.natm),
order='F',
dtype=numpy.complex128) for k in range(nkpts)
]
ints = incore._wrap_int3c(cell, fakenuc, intor, 1, Ls, buf)
atm, bas, env = ints._envs[:3]
c_shls_slice = (ctypes.c_int * 6)(0, cell.nbas, cell.nbas, cell.nbas * 2,
cell.nbas * 2,
cell.nbas * 2 + fakenuc.natm)
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm, gto.PTR_COORD]
ptr_coordL = numpy.vstack(
(ptr_coordL, ptr_coordL + 1, ptr_coordL + 2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l + 1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
charge = cell.atom_charges()
charge = numpy.append(charge,
-charge) # (charge-of-nuccell, charge-of-fakenuc)
for k in range(nkpts):
v = numpy.einsum('ijz,z->ij', buf[k], charge)
buf[k] = lib.pack_tril(v + v.T.conj())
if cell.dimension == 3:
nucbar = sum([
z / nuccell.bas_exp(i)[0]
for i, z in enumerate(cell.atom_charges())
])
nucbar *= numpy.pi / cell.vol
ovlp = cell.pbc_intor('cint1e_ovlp_sph', 1, lib.HERMITIAN, kpts)
for k in range(nkpts):
s = lib.pack_tril(ovlp[k])
buf[k] += nucbar * s
return buf
def ecp_int(cell, kpts=None):
from pyscf.pbc.df import incore
if kpts is None:
kpts_lst = numpy.zeros((1, 3))
else:
kpts_lst = numpy.reshape(kpts, (-1, 3))
nkpts = len(kpts_lst)
Ls = cell.get_lattice_Ls()
expLk = numpy.asarray(numpy.exp(1j * numpy.dot(Ls, kpts_lst.T)), order='C')
ecpcell = gto.Mole()
ecpcell._atm = cell._atm
# append a single s function for auxiliary index.
# So the pbc fill_3c driver can handle the 2D integrals in (1,n,n) array
ecpbas = numpy.vstack([[0, 0, 1, 1, 0, 0, 0, 0],
cell._ecpbas]).astype(numpy.int32)
ecpcell._bas = ecpbas
ecpcell._env = cell._env
nao = cell.nao_nr()
buf = [
numpy.zeros((nao, nao), order='F', dtype=numpy.complex128)
for k in range(nkpts)
]
ints = incore._wrap_int3c(cell, ecpcell, 'ECPscalar_sph', 1, Ls, buf)
atm, bas, env = ints._envs[:3]
env[PTR_ECPBAS_OFFSET] = cell.nbas * 2 + 1
env[PTR_NECPBAS] = len(cell._ecpbas)
c_shls_slice = (ctypes.c_int * 6)(0, cell.nbas, cell.nbas, cell.nbas * 2,
cell.nbas * 2, cell.nbas * 2 + 1)
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm, PTR_COORD]
ptr_coordL = numpy.vstack(
(ptr_coordL, ptr_coordL + 1, ptr_coordL + 2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l + 1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
for k, kpt in enumerate(kpts_lst):
if abs(kpt).sum() < 1e-6:
buf[k] = buf[k].real + buf[k].real.T
else:
buf[k] = buf[k] + buf[k].T.conj()
if kpts is None or numpy.shape(kpts) == (3, ):
buf = buf[0]
return buf
def ecp_int(cell, kpts=None):
from pyscf.pbc.df import incore
if kpts is None:
kpts_lst = numpy.zeros((1,3))
else:
kpts_lst = numpy.reshape(kpts, (-1,3))
nkpts = len(kpts_lst)
Ls = cell.get_lattice_Ls()
expLk = numpy.asarray(numpy.exp(1j*numpy.dot(Ls, kpts_lst.T)), order='C')
ecpcell = gto.Mole()
ecpcell._atm = cell._atm
# append a single s function for auxiliary index.
# So the pbc fill_3c driver can handle the 2D integrals in (1,n,n) array
ecpbas = numpy.vstack([[0, 0, 1, 1, 0, 0, 0, 0], cell._ecpbas]).astype(numpy.int32)
ecpcell._bas = ecpbas
ecpcell._env = cell._env
nao = cell.nao_nr()
buf = [numpy.zeros((nao,nao), order='F', dtype=numpy.complex128)
for k in range(nkpts)]
ints = incore._wrap_int3c(cell, ecpcell, 'ECPscalar_sph', 1, Ls, buf)
atm, bas, env = ints._envs[:3]
env[PTR_ECPBAS_OFFSET] = cell.nbas * 2 + 1
env[PTR_NECPBAS] = len(cell._ecpbas)
c_shls_slice = (ctypes.c_int*6)(0, cell.nbas, cell.nbas, cell.nbas*2,
cell.nbas*2, cell.nbas*2+1)
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm,PTR_COORD]
ptr_coordL = numpy.vstack((ptr_coordL,ptr_coordL+1,ptr_coordL+2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l+1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
for k, kpt in enumerate(kpts_lst):
if abs(kpt).sum() < 1e-6:
buf[k] = buf[k].real + buf[k].real.T
else:
buf[k] = buf[k] + buf[k].T.conj()
if kpts is None or numpy.shape(kpts) == (3,):
buf = buf[0]
return buf
def _int_nuc_vloc(cell, nuccell, kpts):
'''Vnuc - Vloc'''
nimgs = numpy.max((cell.nimgs, nuccell.nimgs), axis=0)
Ls = numpy.asarray(cell.get_lattice_Ls(nimgs), order='C')
expLk = numpy.asarray(numpy.exp(1j * numpy.dot(Ls, kpts.T)), order='C')
nkpts = len(kpts)
# Use the 3c2e code with steep s gaussians to mimic nuclear density
fakenuc = _fake_nuc(cell)
fakenuc._atm, fakenuc._bas, fakenuc._env = \
gto.conc_env(nuccell._atm, nuccell._bas, nuccell._env,
fakenuc._atm, fakenuc._bas, fakenuc._env)
nao = cell.nao_nr()
buf = [
numpy.zeros((nao, nao, fakenuc.natm),
order='F',
dtype=numpy.complex128) for k in range(nkpts)
]
ints = incore._wrap_int3c(cell, fakenuc, 'cint3c2e_sph', 1, Ls, buf)
atm, bas, env = ints._envs[:3]
c_shls_slice = (ctypes.c_int * 6)(0, cell.nbas, cell.nbas, cell.nbas * 2,
cell.nbas * 2,
cell.nbas * 2 + fakenuc.natm)
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm, gto.PTR_COORD]
ptr_coordL = numpy.vstack(
(ptr_coordL, ptr_coordL + 1, ptr_coordL + 2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l + 1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
charge = cell.atom_charges()
charge = numpy.append(charge,
-charge) # (charge-of-nuccell, charge-of-fakenuc)
for k, kpt in enumerate(kpts):
v = numpy.einsum('ijz,z->ij', buf[k], charge)
if gamma_point(kpt):
buf[k] = v.real + v.real.T
else:
buf[k] = v + v.T.conj()
return buf
def _int_nuc_vloc(cell, nuccell, kpts):
'''Vnuc - Vloc'''
nimgs = numpy.max((cell.nimgs, nuccell.nimgs), axis=0)
Ls = numpy.asarray(cell.get_lattice_Ls(nimgs), order='C')
expLk = numpy.asarray(numpy.exp(1j*numpy.dot(Ls, kpts.T)), order='C')
nkpts = len(kpts)
# Use the 3c2e code with steep s gaussians to mimic nuclear density
fakenuc = _fake_nuc(cell)
fakenuc._atm, fakenuc._bas, fakenuc._env = \
gto.conc_env(nuccell._atm, nuccell._bas, nuccell._env,
fakenuc._atm, fakenuc._bas, fakenuc._env)
nao = cell.nao_nr()
buf = [numpy.zeros((nao,nao,fakenuc.natm), order='F', dtype=numpy.complex128)
for k in range(nkpts)]
ints = incore._wrap_int3c(cell, fakenuc, 'cint3c2e_sph', 1, Ls, buf)
atm, bas, env = ints._envs[:3]
c_shls_slice = (ctypes.c_int*6)(0, cell.nbas, cell.nbas, cell.nbas*2,
cell.nbas*2, cell.nbas*2+fakenuc.natm)
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm,gto.PTR_COORD]
ptr_coordL = numpy.vstack((ptr_coordL,ptr_coordL+1,ptr_coordL+2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l+1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
charge = cell.atom_charges()
charge = numpy.append(charge, -charge) # (charge-of-nuccell, charge-of-fakenuc)
for k, kpt in enumerate(kpts):
v = numpy.einsum('ijz,z->ij', buf[k], charge)
if gamma_point(kpt):
buf[k] = v.real + v.real.T
else:
buf[k] = v + v.T.conj()
return buf
def _int_vloc_part2(cell, fakecell, kpts, intor='cint3c1e_sph'):
'''Vnuc - Vloc'''
from pyscf.pbc.df import incore
# sum over largest number of images in either cell or auxcell
nimgs = numpy.max((cell.nimgs, fakecell.nimgs), axis=0)
Ls = numpy.asarray(cell.get_lattice_Ls(nimgs), order='C')
expLk = numpy.asarray(numpy.exp(1j * numpy.dot(Ls, kpts.T)), order='C')
nkpts = len(kpts)
nao = cell.nao_nr()
naux = fakecell.nao_nr()
buf = [
numpy.zeros((nao, nao, naux), order='F', dtype=numpy.complex128)
for k in range(nkpts)
]
ints = incore._wrap_int3c(cell, fakecell, intor, 1, Ls, buf)
atm, bas, env = ints._envs[:3]
c_shls_slice = (ctypes.c_int * 6)(0, cell.nbas, cell.nbas, cell.nbas * 2,
cell.nbas * 2, len(bas))
xyz = cell.atom_coords().copy('C')
ptr_coordL = atm[:cell.natm, gto.PTR_COORD]
ptr_coordL = numpy.vstack(
(ptr_coordL, ptr_coordL + 1, ptr_coordL + 2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l + 1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
for k, kpt in enumerate(kpts):
v = numpy.einsum('ijk->ij', buf[k])
if abs(kpt).sum() < 1e-9: # gamma_point:
v = v.real + v.real.T
else:
v = v + v.T.conj()
buf[k] = v
return buf
def _int_vloc_part2(cell, fakecell, kpts, intor='cint3c1e_sph'):
'''Vnuc - Vloc'''
from pyscf.pbc.df import incore
# sum over largest number of images in either cell or auxcell
rcut = max(cell.rcut, fakecell.rcut)
Ls = cell.get_lattice_Ls(rcut=rcut)
expLk = numpy.asarray(numpy.exp(1j*numpy.dot(Ls, kpts.T)), order='C')
nkpts = len(kpts)
nao = cell.nao_nr()
naux = fakecell.nao_nr()
buf = [numpy.zeros((nao,nao,naux), order='F', dtype=numpy.complex128)
for k in range(nkpts)]
ints = incore._wrap_int3c(cell, fakecell, intor, 1, Ls, buf)
atm, bas, env = ints._envs[:3]
c_shls_slice = (ctypes.c_int*6)(0, cell.nbas, cell.nbas, cell.nbas*2,
cell.nbas*2, len(bas))
xyz = cell.atom_coords().copy('C')
ptr_coordL = atm[:cell.natm,gto.PTR_COORD]
ptr_coordL = numpy.vstack((ptr_coordL,ptr_coordL+1,ptr_coordL+2)).T.copy('C')
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
exp_Lk = numpy.einsum('k,ik->ik', expLk[l].conj(), expLk[:l+1])
exp_Lk = numpy.asarray(exp_Lk, order='C')
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
for k, kpt in enumerate(kpts):
v = numpy.einsum('ijk->ij', buf[k])
if abs(kpt).sum() < 1e-9: # gamma_point:
v = v.real + v.real.T
else:
v = v + v.T.conj()
buf[k] = v
return buf
def aux_e2(cell,
auxcell,
erifile,
intor='cint3c2e_sph',
aosym='s1',
comp=1,
kptij_lst=None,
dataname='eri_mo',
max_memory=2000,
verbose=0):
'''3-center AO integrals (ij|L) with double lattice sum:
\sum_{lm} (i[l]j[m]|L[0]), where L is the auxiliary basis.
On diks, the integrals are stored as (kptij_idx, naux, nao_pair)
Args:
kptij_lst : (*,2,3) array
A list of (kpti, kptj)
'''
if comp > 1:
raise NotImplementedError('comp = %d' % comp)
if h5py.is_hdf5(erifile):
feri = h5py.File(erifile)
if dataname in feri:
del (feri[dataname])
if dataname + '-kptij' in feri:
del (feri[dataname + '-kptij'])
else:
feri = h5py.File(erifile, 'w')
if kptij_lst is None:
kptij_lst = numpy.zeros((1, 2, 3))
feri[dataname + '-kptij'] = kptij_lst
nkptij = len(kptij_lst)
# sum over largest number of images in either cell or auxcell
nimgs = numpy.max((cell.nimgs, auxcell.nimgs), axis=0)
Ls = cell.get_lattice_Ls(nimgs)
logger.debug1(cell, "pbc.df.outcore.Images %s", nimgs)
logger.debug3(cell, "Ls = %s", Ls)
nao = cell.nao_nr()
#naux = auxcell.nao_nr('ssc' in intor)
naux = auxcell.nao_nr()
aosym_s2 = numpy.zeros(nkptij, dtype=bool)
for k, kptij in enumerate(kptij_lst):
key = '%s/%d' % (dataname, k)
if abs(kptij).sum() < 1e-9: # gamma_point:
dtype = 'f8'
else:
dtype = 'c16'
aosym_s2[k] = abs(kptij[0] - kptij[1]).sum() < 1e-9
if aosym_s2[k]:
nao_pair = nao * (nao + 1) // 2
else:
nao_pair = nao * nao
if comp == 1:
shape = (naux, nao_pair)
else:
shape = (comp, naux, nao_pair)
chunks = (min(256, naux), min(256, nao_pair)) # 512 KB
feri.create_dataset(key, shape, dtype, chunks=chunks)
if naux == 0:
feri.close()
return erifile
aux_loc = auxcell.ao_loc_nr('ssc' in intor)
buflen = max(8, int(max_memory * 1e6 / 16 / (nkptij * nao**2 * comp)))
auxranges = balance_segs(aux_loc[1:] - aux_loc[:-1], buflen)
buflen = max([x[2] for x in auxranges])
buf = [
numpy.zeros(nao * nao * buflen * comp, dtype=numpy.complex128)
for k in range(nkptij)
]
ints = incore._wrap_int3c(cell, auxcell, intor, comp, Ls, buf)
atm, bas, env = ints._envs[:3]
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm, PTR_COORD]
ptr_coordL = numpy.vstack(
(ptr_coordL, ptr_coordL + 1, ptr_coordL + 2)).T.copy('C')
kpti = kptij_lst[:, 0]
kptj = kptij_lst[:, 1]
if numpy.all(aosym_s2):
def ccsum_or_reorder(Lpq):
tmp = numpy.asarray(Lpq.transpose(0, 2, 1).conj(), order='C')
tmp += Lpq
return tmp
else:
def ccsum_or_reorder(Lpq):
return numpy.asarray(Lpq, order='C')
naux0 = 0
for istep, auxrange in enumerate(auxranges):
sh0, sh1, nrow = auxrange
c_shls_slice = (ctypes.c_int * 6)(0, cell.nbas, cell.nbas,
cell.nbas * 2, cell.nbas * 2 + sh0,
cell.nbas * 2 + sh1)
if numpy.all(aosym_s2):
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
e = numpy.dot(
Ls[:l + 1] - L1,
kptj.T) # Lattice sum over half of the images {1..l}
exp_Lk = numpy.exp(1j * numpy.asarray(e, order='C'))
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
else:
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
e = numpy.dot(Ls, kptj.T) - numpy.dot(L1, kpti.T)
exp_Lk = numpy.exp(1j * numpy.asarray(e, order='C'))
ints(exp_Lk, c_shls_slice)
for k, kptij in enumerate(kptij_lst):
h5dat = feri['%s/%d' % (dataname, k)]
# transpose 3201 as (comp,L,i,j)
mat = numpy.ndarray((nao, nao, nrow, comp),
order='F',
dtype=numpy.complex128,
buffer=buf[k])
for icomp, vi in enumerate(mat.transpose(3, 2, 0, 1)):
v = ccsum_or_reorder(vi)
if abs(kptij).sum() < 1e-9: # gamma_point:
v = v.real
if aosym_s2[k]:
v = lib.pack_tril(v)
else:
v = v.reshape(nrow, -1)
if comp == 1:
h5dat[naux0:naux0 + nrow] = v
else:
h5dat[icomp, naux0:naux0 + nrow] = v
mat[:] = 0
naux0 += nrow
feri.close()
return erifile
def aux_e2(cell, auxcell, erifile, intor='cint3c2e_sph', aosym='s1', comp=1,
kptij_lst=None, dataname='eri_mo', max_memory=2000, verbose=0):
'''3-center AO integrals (ij|L) with double lattice sum:
\sum_{lm} (i[l]j[m]|L[0]), where L is the auxiliary basis.
On diks, the integrals are stored as (kptij_idx, naux, nao_pair)
Args:
kptij_lst : (*,2,3) array
A list of (kpti, kptj)
'''
if comp > 1:
raise NotImplementedError('comp = %d' % comp)
if h5py.is_hdf5(erifile):
feri = h5py.File(erifile)
if dataname in feri:
del(feri[dataname])
if dataname+'-kptij' in feri:
del(feri[dataname+'-kptij'])
else:
feri = h5py.File(erifile, 'w')
if kptij_lst is None:
kptij_lst = numpy.zeros((1,2,3))
feri[dataname+'-kptij'] = kptij_lst
nkptij = len(kptij_lst)
# sum over largest number of images in either cell or auxcell
nimgs = numpy.max((cell.nimgs, auxcell.nimgs), axis=0)
Ls = cell.get_lattice_Ls(nimgs)
logger.debug1(cell, "pbc.df.outcore.Images %s", nimgs)
logger.debug3(cell, "Ls = %s", Ls)
nao = cell.nao_nr()
#naux = auxcell.nao_nr('ssc' in intor)
naux = auxcell.nao_nr()
aosym_s2 = numpy.zeros(nkptij, dtype=bool)
for k, kptij in enumerate(kptij_lst):
key = '%s/%d' % (dataname, k)
if abs(kptij).sum() < 1e-9: # gamma_point:
dtype = 'f8'
else:
dtype = 'c16'
aosym_s2[k] = abs(kptij[0]-kptij[1]).sum() < 1e-9
if aosym_s2[k]:
nao_pair = nao * (nao+1) // 2
else:
nao_pair = nao * nao
if comp == 1:
shape = (naux,nao_pair)
else:
shape = (comp,naux,nao_pair)
chunks = (min(256,naux), min(256,nao_pair)) # 512 KB
feri.create_dataset(key, shape, dtype, chunks=chunks)
if naux == 0:
feri.close()
return erifile
aux_loc = auxcell.ao_loc_nr('ssc' in intor)
buflen = max(8, int(max_memory*1e6/16/(nkptij*nao**2*comp)))
auxranges = balance_segs(aux_loc[1:]-aux_loc[:-1], buflen)
buflen = max([x[2] for x in auxranges])
buf = [numpy.zeros(nao*nao*buflen*comp, dtype=numpy.complex128)
for k in range(nkptij)]
ints = incore._wrap_int3c(cell, auxcell, intor, comp, Ls, buf)
atm, bas, env = ints._envs[:3]
xyz = numpy.asarray(cell.atom_coords(), order='C')
ptr_coordL = atm[:cell.natm,PTR_COORD]
ptr_coordL = numpy.vstack((ptr_coordL,ptr_coordL+1,ptr_coordL+2)).T.copy('C')
kpti = kptij_lst[:,0]
kptj = kptij_lst[:,1]
if numpy.all(aosym_s2):
def ccsum_or_reorder(Lpq):
tmp = numpy.asarray(Lpq.transpose(0,2,1).conj(), order='C')
tmp += Lpq
return tmp
else:
def ccsum_or_reorder(Lpq):
return numpy.asarray(Lpq, order='C')
naux0 = 0
for istep, auxrange in enumerate(auxranges):
sh0, sh1, nrow = auxrange
c_shls_slice = (ctypes.c_int*6)(0, cell.nbas, cell.nbas, cell.nbas*2,
cell.nbas*2+sh0, cell.nbas*2+sh1)
if numpy.all(aosym_s2):
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
e = numpy.dot(Ls[:l+1]-L1, kptj.T) # Lattice sum over half of the images {1..l}
exp_Lk = numpy.exp(1j * numpy.asarray(e, order='C'))
exp_Lk[l] = .5
ints(exp_Lk, c_shls_slice)
else:
for l, L1 in enumerate(Ls):
env[ptr_coordL] = xyz + L1
e = numpy.dot(Ls, kptj.T) - numpy.dot(L1, kpti.T)
exp_Lk = numpy.exp(1j * numpy.asarray(e, order='C'))
ints(exp_Lk, c_shls_slice)
for k, kptij in enumerate(kptij_lst):
h5dat = feri['%s/%d'%(dataname,k)]
# transpose 3201 as (comp,L,i,j)
mat = numpy.ndarray((nao,nao,nrow,comp), order='F',
dtype=numpy.complex128, buffer=buf[k])
for icomp, vi in enumerate(mat.transpose(3,2,0,1)):
v = ccsum_or_reorder(vi)
if abs(kptij).sum() < 1e-9: # gamma_point:
v = v.real
if aosym_s2[k]:
v = lib.pack_tril(v)
else:
v = v.reshape(nrow,-1)
if comp == 1:
h5dat[naux0:naux0+nrow] = v
else:
h5dat[icomp,naux0:naux0+nrow] = v
mat[:] = 0
naux0 += nrow
feri.close()
return erifile
