def get_pnucp(mydf, kpts=None):
cell = mydf.cell
if kpts is None:
kpts_lst = numpy.zeros((1,3))
else:
kpts_lst = numpy.reshape(kpts, (-1,3))
log = logger.Logger(mydf.stdout, mydf.verbose)
t1 = t0 = (time.clock(), time.time())
nkpts = len(kpts_lst)
nao = cell.nao_nr()
nao_pair = nao * (nao+1) // 2
Gv, Gvbase, kws = cell.get_Gv_weights(mydf.gs)
kpt_allow = numpy.zeros(3)
if mydf.eta == 0:
charge = -cell.atom_charges()
#coulG=4*numpy.pi/G^2 is cancelled with (sigma dot p i, sigma dot p j)
SI = cell.get_SI(Gv)
vGR = numpy.einsum('i,ix->x', 4*numpy.pi*charge, SI.real) * kws
vGI = numpy.einsum('i,ix->x', 4*numpy.pi*charge, SI.imag) * kws
wjR = numpy.zeros((nkpts,nao_pair))
wjI = numpy.zeros((nkpts,nao_pair))
else:
nuccell = copy.copy(cell)
half_sph_norm = .5/numpy.sqrt(numpy.pi)
norm = half_sph_norm/mole._gaussian_int(2, mydf.eta)
chg_env = [mydf.eta, norm]
ptr_eta = cell._env.size
ptr_norm = ptr_eta + 1
chg_bas = [[ia, 0, 1, 1, 0, ptr_eta, ptr_norm, 0] for ia in range(cell.natm)]
nuccell._atm = cell._atm
nuccell._bas = numpy.asarray(chg_bas, dtype=numpy.int32)
nuccell._env = numpy.hstack((cell._env, chg_env))
wj = lib.asarray(mydf._int_nuc_vloc(nuccell, kpts_lst, 'cint3c2e_pvp1_sph'))
wjR = wj.real
wjI = wj.imag
t1 = log.timer_debug1('pnucp pass1: analytic int', *t1)
charge = -cell.atom_charges()
#coulG=4*numpy.pi/G^2 is cancelled with (sigma dot p i, sigma dot p j)
aoaux = ft_ao.ft_ao(nuccell, Gv)
vGR = numpy.einsum('i,xi->x', 4*numpy.pi*charge, aoaux.real) * kws
vGI = numpy.einsum('i,xi->x', 4*numpy.pi*charge, aoaux.imag) * kws
max_memory = max(2000, mydf.max_memory-lib.current_memory()[0])
for k, pqkR, pqkI, p0, p1 \
in mydf.ft_loop(mydf.gs, kpt_allow, kpts_lst,
max_memory=max_memory, aosym='s2'):
# rho_ij(G) nuc(-G) / G^2
# = [Re(rho_ij(G)) + Im(rho_ij(G))*1j] [Re(nuc(G)) - Im(nuc(G))*1j] / G^2
if not pwdf_jk.gamma_point(kpts_lst[k]):
wjI[k] += numpy.einsum('k,xk->x', vGR[p0:p1], pqkI)
wjI[k] -= numpy.einsum('k,xk->x', vGI[p0:p1], pqkR)
wjR[k] += numpy.einsum('k,xk->x', vGR[p0:p1], pqkR)
wjR[k] += numpy.einsum('k,xk->x', vGI[p0:p1], pqkI)
t1 = log.timer_debug1('contracting Vnuc', *t1)
if mydf.eta != 0 and cell.dimension == 3:
nucbar = sum([z/nuccell.bas_exp(i)[0] for i,z in enumerate(charge)])
nucbar *= numpy.pi/cell.vol * 2
ovlp = cell.pbc_intor('cint1e_kin_sph', 1, lib.HERMITIAN, kpts_lst)
for k in range(nkpts):
s = lib.pack_tril(ovlp[k])
wjR[k] -= nucbar * s.real
wjI[k] -= nucbar * s.imag
wj = []
for k, kpt in enumerate(kpts_lst):
if pwdf_jk.gamma_point(kpt):
wj.append(lib.unpack_tril(wjR[k]))
else:
wj.append(lib.unpack_tril(wjR[k]+wjI[k]*1j))
if kpts is None or numpy.shape(kpts) == (3,):
wj = wj[0]
return wj
def get_jk(mydf, dm, hermi=1, kpt=numpy.zeros(3),
kpt_band=None, with_j=True, with_k=True, exxdiv=None):
'''JK for given k-point'''
vj = vk = None
if kpt_band is not None and abs(kpt-kpt_band).sum() > 1e-9:
kpt = numpy.reshape(kpt, (1,3))
if with_k:
vk = get_k_kpts(mydf, [dm], hermi, kpt, kpt_band, exxdiv)
if with_j:
vj = get_j_kpts(mydf, [dm], hermi, kpt, kpt_band)
return vj, vk
log = logger.Logger(mydf.stdout, mydf.verbose)
t2 = t1 = (time.clock(), time.time())
if mydf._cderi is None:
mydf.build()
t1 = log.timer_debug1('Init get_jk', *t1)
dm = numpy.asarray(dm, order='C')
dms = _format_dms(dm, [kpt])
nset, _, nao = dms.shape[:3]
dms = dms.reshape(nset,nao,nao)
j_real = gamma_point(kpt)
k_real = gamma_point(kpt) and not numpy.iscomplexobj(dms)
kptii = numpy.asarray((kpt,kpt))
# .45 is estimation for the memory usage ratio sr_loop / (sr_loop+bufR+bufI)
dmsR = numpy.asarray(dms.real.reshape(nset,nao,nao), order='C')
dmsI = numpy.asarray(dms.imag.reshape(nset,nao,nao), order='C')
if with_j:
vjR = numpy.zeros((nset,nao,nao))
vjI = numpy.zeros((nset,nao,nao))
if with_k:
vkR = numpy.zeros((nset,nao,nao))
vkI = numpy.zeros((nset,nao,nao))
max_memory = max(2000, (mydf.max_memory - lib.current_memory()[0])) * .45
if with_k:
buf1R = numpy.empty((mydf.blockdim*nao**2))
buf2R = numpy.empty((mydf.blockdim*nao**2))
buf3R = numpy.empty((mydf.blockdim*nao**2))
if not k_real:
buf1I = numpy.empty((mydf.blockdim*nao**2))
buf2I = numpy.empty((mydf.blockdim*nao**2))
buf3I = numpy.empty((mydf.blockdim*nao**2))
def contract_k(pLqR, pLqI, pjqR, pjqI):
# K ~ 'iLj,lLk*,li->kj' + 'lLk*,iLj,li->kj'
#:Lpq = LpqR + LpqI*1j
#:j3c = j3cR + j3cI*1j
#:for i in range(nset):
#: tmp = numpy.dot(dms[i], j3c.reshape(nao,-1))
#: vk1 = numpy.dot(Lpq.reshape(-1,nao).conj().T, tmp.reshape(-1,nao))
#: tmp = numpy.dot(dms[i], Lpq.reshape(nao,-1))
#: vk1+= numpy.dot(j3c.reshape(-1,nao).conj().T, tmp.reshape(-1,nao))
#: vkR[i] += vk1.real
#: vkI[i] += vk1.imag
nrow = pLqR.shape[1]
tmpR = numpy.ndarray((nao,nrow*nao), buffer=buf3R)
if k_real:
for i in range(nset):
tmpR = lib.ddot(dmsR[i], pjqR.reshape(nao,-1), 1, tmpR)
vk1R = lib.ddot(pLqR.reshape(-1,nao).T, tmpR.reshape(-1,nao))
vkR[i] += vk1R
if hermi:
vkR[i] += vk1R.T
else:
tmpR = lib.ddot(dmsR[i], pLqR.reshape(nao,-1), 1, tmpR)
lib.ddot(pjqR.reshape(-1,nao).T, tmpR.reshape(-1,nao),
1, vkR[i], 1)
else:
tmpI = numpy.ndarray((nao,nrow*nao), buffer=buf3I)
for i in range(nset):
tmpR, tmpI = zdotNN(dmsR[i], dmsI[i], pjqR.reshape(nao,-1),
pjqI.reshape(nao,-1), 1, tmpR, tmpI, 0)
vk1R, vk1I = zdotCN(pLqR.reshape(-1,nao).T, pLqI.reshape(-1,nao).T,
tmpR.reshape(-1,nao), tmpI.reshape(-1,nao))
vkR[i] += vk1R
vkI[i] += vk1I
if hermi:
vkR[i] += vk1R.T
vkI[i] -= vk1I.T
else:
tmpR, tmpI = zdotNN(dmsR[i], dmsI[i], pLqR.reshape(nao,-1),
pLqI.reshape(nao,-1), 1, tmpR, tmpI, 0)
zdotCN(pjqR.reshape(-1,nao).T, pjqI.reshape(-1,nao).T,
tmpR.reshape(-1,nao), tmpI.reshape(-1,nao),
1, vkR[i], vkI[i], 1)
pLqI = pjqI = None
thread_k = None
for LpqR, LpqI, j3cR, j3cI in mydf.sr_loop(kptii, max_memory, False):
LpqR = LpqR.reshape(-1,nao,nao)
LpqI = LpqI.reshape(-1,nao,nao)
j3cR = j3cR.reshape(-1,nao,nao)
j3cI = j3cI.reshape(-1,nao,nao)
t2 = log.timer_debug1(' load', *t2)
if thread_k is not None:
thread_k.join()
if with_j:
#:rho_coeff = numpy.einsum('Lpq,xqp->xL', Lpq, dms)
#:jaux = numpy.einsum('Lpq,xqp->xL', j3c, dms)
#:vj += numpy.dot(jaux, Lpq.reshape(-1,nao**2))
#:vj += numpy.dot(rho_coeff, j3c.reshape(-1,nao**2))
rhoR = numpy.einsum('Lpq,xqp->xL', LpqR, dmsR)
jauxR = numpy.einsum('Lpq,xqp->xL', j3cR, dmsR)
if not j_real:
rhoR -= numpy.einsum('Lpq,xqp->xL', LpqI, dmsI)
rhoI = numpy.einsum('Lpq,xqp->xL', LpqR, dmsI)
rhoI += numpy.einsum('Lpq,xqp->xL', LpqI, dmsR)
jauxR-= numpy.einsum('Lpq,xqp->xL', j3cI, dmsI)
jauxI = numpy.einsum('Lpq,xqp->xL', j3cR, dmsI)
jauxI+= numpy.einsum('Lpq,xqp->xL', j3cI, dmsR)
vjR += numpy.einsum('xL,Lpq->xpq', jauxR, LpqR)
vjR += numpy.einsum('xL,Lpq->xpq', rhoR, j3cR)
if not j_real:
vjR -= numpy.einsum('xL,Lpq->xpq', jauxI, LpqI)
vjR -= numpy.einsum('xL,Lpq->xpq', rhoI, j3cI)
vjI += numpy.einsum('xL,Lpq->xpq', jauxR, LpqI)
vjI += numpy.einsum('xL,Lpq->xpq', jauxI, LpqR)
vjI += numpy.einsum('xL,Lpq->xpq', rhoR, j3cI)
vjI += numpy.einsum('xL,Lpq->xpq', rhoI, j3cR)
t2 = log.timer_debug1(' with_j', *t2)
if with_k:
nrow = LpqR.shape[0]
pLqR = numpy.ndarray((nao,nrow,nao), buffer=buf1R)
pjqR = numpy.ndarray((nao,nrow,nao), buffer=buf2R)
pLqR[:] = LpqR.transpose(1,0,2)
pjqR[:] = j3cR.transpose(1,0,2)
if not k_real:
pLqI = numpy.ndarray((nao,nrow,nao), buffer=buf1I)
pjqI = numpy.ndarray((nao,nrow,nao), buffer=buf2I)
pLqI[:] = LpqI.transpose(1,0,2)
pjqI[:] = j3cI.transpose(1,0,2)
thread_k = lib.background_thread(contract_k, pLqR, pLqI, pjqR, pjqI)
t2 = log.timer_debug1(' with_k', *t2)
LpqR = LpqI = j3cR = j3cI = None
if thread_k is not None:
thread_k.join()
thread_k = None
t1 = log.timer_debug1('mdf_jk.get_jk pass 1', *t1)
vj, vk = pwdf_jk.get_jk(mydf, dm, hermi, kpt, kpt_band, with_j, with_k, exxdiv)
if with_j:
if j_real:
vj += vjR.reshape(dm.shape)
else:
vj += (vjR+vjI*1j).reshape(dm.shape)
vj = vj
if with_k:
if k_real:
vk += vkR.reshape(dm.shape)
else:
vk += (vkR+vkI*1j).reshape(dm.shape)
return vj, vk
def get_j_kpts(mydf, dm_kpts, hermi=1, kpts=numpy.zeros((1,3)), kpt_band=None):
cell = mydf.cell
log = logger.Logger(mydf.stdout, mydf.verbose)
t1 = (time.clock(), time.time())
if mydf._cderi is None:
mydf.build()
t1 = log.timer_debug1('Init get_j_kpts', *t1)
dm_kpts = lib.asarray(dm_kpts, order='C')
dms = _format_dms(dm_kpts, kpts)
nset, nkpts, nao = dms.shape[:3]
if kpt_band is None:
kpts_band = kpts
else:
kpts_band = numpy.reshape(kpt_band, (-1,3))
nband = len(kpts_band)
j_real = gamma_point(kpts_band)
mem_now = lib.current_memory()[0]
max_memory = max(2000, (mydf.max_memory - mem_now)) * .9
log.debug1('max_memory = %d MB (%d in use)', max_memory, mem_now)
naux = mydf.auxcell.nao_nr()
dmsR = dms.real.transpose(0,1,3,2).reshape(nset,nkpts,nao**2)
dmsI = dms.imag.transpose(0,1,3,2).reshape(nset,nkpts,nao**2)
rhoR = numpy.zeros((nset,naux))
rhoI = numpy.zeros((nset,naux))
jauxR = numpy.zeros((nset,naux))
jauxI = numpy.zeros((nset,naux))
for k, kpt in enumerate(kpts_band):
kptii = numpy.asarray((kpt,kpt))
p1 = 0
for LpqR, LpqI, j3cR, j3cI in mydf.sr_loop(kptii, max_memory, False):
p0, p1 = p1, p1+LpqR.shape[0]
#:Lpq = LpqR + LpqI*1j
#:j3c = j3cR + j3cI*1j
#:rho [:,p0:p1] += numpy.einsum('Lpq,xqp->xL', Lpq, dms[:,k])
#:jaux[:,p0:p1] += numpy.einsum('Lpq,xqp->xL', j3c, dms[:,k])
rhoR [:,p0:p1]+= numpy.einsum('Lp,xp->xL', LpqR, dmsR[:,k])
rhoR [:,p0:p1]-= numpy.einsum('Lp,xp->xL', LpqI, dmsI[:,k])
rhoI [:,p0:p1]+= numpy.einsum('Lp,xp->xL', LpqR, dmsI[:,k])
rhoI [:,p0:p1]+= numpy.einsum('Lp,xp->xL', LpqI, dmsR[:,k])
jauxR[:,p0:p1]+= numpy.einsum('Lp,xp->xL', j3cR, dmsR[:,k])
jauxR[:,p0:p1]-= numpy.einsum('Lp,xp->xL', j3cI, dmsI[:,k])
jauxI[:,p0:p1]+= numpy.einsum('Lp,xp->xL', j3cR, dmsI[:,k])
jauxI[:,p0:p1]+= numpy.einsum('Lp,xp->xL', j3cI, dmsR[:,k])
LpqR = LpqI = j3cR = j3cI = None
weight = 1./nkpts
jauxR *= weight
jauxI *= weight
rhoR *= weight
rhoI *= weight
vjR = numpy.zeros((nset,nband,nao,nao))
vjI = numpy.zeros((nset,nband,nao,nao))
for k, kpt in enumerate(kpts_band):
kptii = numpy.asarray((kpt,kpt))
p1 = 0
for LpqR, LpqI, j3cR, j3cI in mydf.sr_loop(kptii, max_memory, True):
p0, p1 = p1, p1+LpqR.shape[0]
#:v = numpy.dot(jaux, Lpq) + numpy.dot(rho, j3c)
#:vj_kpts[:,k] += lib.unpack_tril(v)
v = numpy.dot(jauxR[:,p0:p1], LpqR)
v -= numpy.dot(jauxI[:,p0:p1], LpqI)
v += numpy.dot(rhoR [:,p0:p1], j3cR)
v -= numpy.dot(rhoI [:,p0:p1], j3cI)
vjR[:,k] += lib.unpack_tril(v)
if not j_real:
v = numpy.dot(jauxR[:,p0:p1], LpqI)
v += numpy.dot(jauxI[:,p0:p1], LpqR)
v += numpy.dot(rhoR [:,p0:p1], j3cI)
v += numpy.dot(rhoI [:,p0:p1], j3cR)
vjI[:,k] += lib.unpack_tril(v, lib.ANTIHERMI)
LpqR = LpqI = j3cR = j3cI = None
t1 = log.timer_debug1('get_j pass 2', *t1)
vj_kpts = pwdf_jk.get_j_kpts(mydf, dm_kpts, hermi, kpts, kpt_band)
if j_real:
vj_kpts += vjR.reshape(vj_kpts.shape)
else:
vj_kpts += (vjR+vjI*1j).reshape(vj_kpts.shape)
return vj_kpts
def get_k_kpts(mydf, dm_kpts, hermi=1, kpts=numpy.zeros((1,3)), kpt_band=None,
exxdiv=None):
cell = mydf.cell
log = logger.Logger(mydf.stdout, mydf.verbose)
t1 = (time.clock(), time.time())
if mydf._cderi is None:
mydf.build()
t1 = log.timer_debug1('Init get_k_kpts', *t1)
dm_kpts = lib.asarray(dm_kpts, order='C')
dms = _format_dms(dm_kpts, kpts)
nset, nkpts, nao = dms.shape[:3]
naux = mydf.auxcell.nao_nr()
nao_pair = nao * (nao+1) // 2
if kpt_band is None:
kpts_band = kpts
swap_2e = True
else:
kpts_band = numpy.reshape(kpt_band, (-1,3))
nband = len(kpts_band)
kk_table = kpts_band.reshape(-1,1,3) - kpts.reshape(1,-1,3)
kk_todo = numpy.ones(kk_table.shape[:2], dtype=bool)
vkR = numpy.zeros((nset,nband,nao,nao))
vkI = numpy.zeros((nset,nband,nao,nao))
dmsR = numpy.asarray(dms.real, order='C')
dmsI = numpy.asarray(dms.imag, order='C')
mem_now = lib.current_memory()[0]
max_memory = max(2000, (mydf.max_memory - mem_now)) * .8
log.debug1('max_memory = %d MB (%d in use)', max_memory, mem_now)
# K_pq = ( p{k1} i{k2} | i{k2} q{k1} )
def make_kpt(kpt): # kpt = kptj - kpti
# search for all possible ki and kj that has ki-kj+kpt=0
kk_match = numpy.einsum('ijx->ij', abs(kk_table + kpt)) < 1e-9
kpti_idx, kptj_idx = numpy.where(kk_todo & kk_match)
nkptj = len(kptj_idx)
kk_todo[kpti_idx,kptj_idx] = False
if swap_2e and not is_zero(kpt):
kk_todo[kptj_idx,kpti_idx] = False
# Note: kj-ki for electorn 1 and ki-kj for electron 2
# j2c ~ ({kj-ki}|{ks-kr}) ~ ({kj-ki}|-{kj-ki}) ~ ({kj-ki}|{ki-kj})
# j3c ~ (Q|kj,ki) = j3c{ji} = (Q|ki,kj)* = conj(transpose(j3c{ij}, (0,2,1)))
bufR = numpy.empty((mydf.blockdim*nao**2))
bufI = numpy.empty((mydf.blockdim*nao**2))
for ki,kj in zip(kpti_idx,kptj_idx):
kpti = kpts_band[ki]
kptj = kpts[kj]
kptij = numpy.asarray((kpti,kptj))
for LpqR, LpqI, j3cR, j3cI in mydf.sr_loop(kptij, max_memory, False):
nrow = LpqR.shape[0]
pLqR = numpy.ndarray((nao,nrow,nao), buffer=bufR)
pLqI = numpy.ndarray((nao,nrow,nao), buffer=bufI)
pjqR = numpy.ndarray((nao,nrow,nao), buffer=LpqR)
pjqI = numpy.ndarray((nao,nrow,nao), buffer=LpqI)
tmpR = numpy.ndarray((nao,nrow*nao), buffer=j3cR)
tmpI = numpy.ndarray((nao,nrow*nao), buffer=j3cI)
pLqR[:] = LpqR.reshape(-1,nao,nao).transpose(1,0,2)
pLqI[:] = LpqI.reshape(-1,nao,nao).transpose(1,0,2)
pjqR[:] = j3cR.reshape(-1,nao,nao).transpose(1,0,2)
pjqI[:] = j3cI.reshape(-1,nao,nao).transpose(1,0,2)
#:Lpq = LpqR + LpqI*1j
#:j3c = j3cR + j3cI*1j
#:for i in range(nset):
#: dm = dms[i,ki]
#: tmp = numpy.dot(dm, j3c.reshape(nao,-1))
#: vk1 = numpy.dot(Lpq.reshape(-1,nao).conj().T, tmp.reshape(-1,nao))
#: tmp = numpy.dot(dm, Lpq.reshape(nao,-1))
#: vk1+= numpy.dot(j3c.reshape(-1,nao).conj().T, tmp.reshape(-1,nao))
#: vkR[i,kj] += vk1.real
#: vkI[i,kj] += vk1.imag
#:if swap_2e and not is_zero(kpt):
#: # K ~ 'Lij,Llk*,jk->il' + 'Llk*,Lij,jk->il'
#: for i in range(nset):
#: dm = dms[i,kj]
#: tmp = numpy.dot(j3c.reshape(-1,nao), dm)
#: vk1 = numpy.dot(tmp.reshape(nao,-1), Lpq.reshape(nao,-1).conj().T)
#: tmp = numpy.dot(Lpq.reshape(-1,nao), dm)
#: vk1+= numpy.dot(tmp.reshape(nao,-1), j3c.reshape(nao,-1).conj().T)
#: vkR[i,ki] += vk1.real
#: vkI[i,ki] += vk1.imag
# K ~ 'iLj,lLk*,li->kj' + 'lLk*,iLj,li->kj'
for i in range(nset):
tmpR, tmpI = zdotNN(dmsR[i,ki], dmsI[i,ki], pjqR.reshape(nao,-1),
pjqI.reshape(nao,-1), 1, tmpR, tmpI)
vk1R, vk1I = zdotCN(pLqR.reshape(-1,nao).T, pLqI.reshape(-1,nao).T,
tmpR.reshape(-1,nao), tmpI.reshape(-1,nao))
vkR[i,kj] += vk1R
vkI[i,kj] += vk1I
if hermi:
vkR[i,kj] += vk1R.T
vkI[i,kj] -= vk1I.T
else:
tmpR, tmpI = zdotNN(dmsR[i,ki], dmsI[i,ki], pLqR.reshape(nao,-1),
pLqI.reshape(nao,-1), 1, tmpR, tmpI)
zdotCN(pjqR.reshape(-1,nao).T, pjqI.reshape(-1,nao).T,
tmpR.reshape(-1,nao), tmpI.reshape(-1,nao),
1, vkR[i,kj], vkI[i,kj], 1)
if swap_2e and not is_zero(kpt):
tmpR = tmpR.reshape(nao*nrow,nao)
tmpI = tmpI.reshape(nao*nrow,nao)
# K ~ 'iLj,lLk*,jk->il' + 'lLk*,iLj,jk->il'
for i in range(nset):
tmpR, tmpI = zdotNN(pjqR.reshape(-1,nao), pjqI.reshape(-1,nao),
dmsR[i,kj], dmsI[i,kj], 1, tmpR, tmpI)
vk1R, vk1I = zdotNC(tmpR.reshape(nao,-1), tmpI.reshape(nao,-1),
pLqR.reshape(nao,-1).T, pLqI.reshape(nao,-1).T)
vkR[i,ki] += vk1R
vkI[i,ki] += vk1I
if hermi:
vkR[i,ki] += vk1R.T
vkI[i,ki] -= vk1I.T
else:
tmpR, tmpI = zdotNN(pLqR.reshape(-1,nao), pLqI.reshape(-1,nao),
dmsR[i,kj], dmsI[i,kj], 1, tmpR, tmpI)
zdotNC(tmpR.reshape(nao,-1), tmpI.reshape(nao,-1),
pjqR.reshape(nao,-1).T, pjqI.reshape(nao,-1).T,
1, vkR[i,ki], vkI[i,ki], 1)
LpqR = LpqI = j3cR = j3cI = tmpR = tmpI = None
return None
for ki, kpti in enumerate(kpts_band):
for kj, kptj in enumerate(kpts):
if kk_todo[ki,kj]:
make_kpt(kptj-kpti)
vkR *= 1./nkpts
vkI *= 1./nkpts
vk_kpts = pwdf_jk.get_k_kpts(mydf, dm_kpts, hermi, kpts, kpt_band, exxdiv)
if (gamma_point(kpts) and gamma_point(kpts_band) and
not numpy.iscomplexobj(dm_kpts)):
vk_kpts += vkR.reshape(vk_kpts.shape)
else:
vk_kpts += (vkR+vkI*1j).reshape(vk_kpts.shape)
return vk_kpts
