def init_guess(self, mf, nstates=None, wfnsym=None):
if nstates is None: nstates = self.nstates
if wfnsym is None: wfnsym = self.wfnsym
mol = mf.mol
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mf.mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
e_ia_a[(orbsyma[occidxa, None]
^ orbsyma[viridxa]) != wfnsym] = 1e99
e_ia_b[(orbsymb[occidxb, None]
^ orbsymb[viridxb]) != wfnsym] = 1e99
e_ia = numpy.hstack((e_ia_a.ravel(), e_ia_b.ravel()))
nov = e_ia.size
nroot = min(nstates, nov)
x0 = numpy.zeros((nroot, nov))
idx = numpy.argsort(e_ia)
for i in range(nroot):
x0[i, idx[i]] = 1 # lowest excitations
return x0
def rotate_mo(self, mo_coeff, u, log=None):
mo = numpy.asarray((numpy.dot(mo_coeff[0], u[0]),
numpy.dot(mo_coeff[1], u[1])))
if self._scf.mol.symmetry:
orbsym = uhf_symm.get_orbsym(self._scf.mol, mo_coeff)
mo = lib.tag_array(mo, orbsym=orbsym)
return mo
def update_rotate_matrix(self, dx, mo_occ, u0=1, mo_coeff=None):
occidxa = mo_occ[0] > 0
occidxb = mo_occ[1] > 0
viridxa = ~occidxa
viridxb = ~occidxb
nmo = len(occidxa)
dr = numpy.zeros((2,nmo,nmo), dtype=dx.dtype)
uniq = numpy.array((viridxa[:,None] & occidxa,
viridxb[:,None] & occidxb))
dr[uniq] = dx
dr = dr - dr.conj().transpose(0,2,1)
if WITH_EX_EY_DEGENERACY:
mol = self._scf.mol
if mol.symmetry and mol.groupname in ('Dooh', 'Coov'):
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
_force_Ex_Ey_degeneracy_(dr[0], orbsyma)
_force_Ex_Ey_degeneracy_(dr[0], orbsymb)
if isinstance(u0, int) and u0 == 1:
return numpy.asarray((expmat(dr[0]), expmat(dr[1])))
else:
return numpy.asarray((numpy.dot(u0[0], expmat(dr[0])),
numpy.dot(u0[1], expmat(dr[1]))))
def update_rotate_matrix(self, dx, mo_occ, u0=1, mo_coeff=None):
occidxa = mo_occ[0] > 0
occidxb = mo_occ[1] > 0
viridxa = ~occidxa
viridxb = ~occidxb
nmo = len(occidxa)
dr = numpy.zeros((2, nmo, nmo), dtype=dx.dtype)
uniq = numpy.array(
(viridxa[:, None] & occidxa, viridxb[:, None] & occidxb))
dr[uniq] = dx
dr = dr - dr.conj().transpose(0, 2, 1)
if WITH_EX_EY_DEGENERACY:
mol = self._scf.mol
if mol.symmetry and mol.groupname in ('Dooh', 'Coov'):
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
_force_Ex_Ey_degeneracy_(dr[0], orbsyma)
_force_Ex_Ey_degeneracy_(dr[1], orbsymb)
if isinstance(u0, int) and u0 == 1:
return numpy.asarray((expmat(dr[0]), expmat(dr[1])))
else:
return numpy.asarray((numpy.dot(u0[0], expmat(dr[0])),
numpy.dot(u0[1], expmat(dr[1]))))
def init_guess(self, mf, nstates=None, wfnsym=None):
if nstates is None: nstates = self.nstates
if wfnsym is None: wfnsym = self.wfnsym
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
e_ai_a = mo_energy[0][viridxa].reshape(-1, 1) - mo_energy[0][occidxa]
e_ai_b = mo_energy[1][viridxb].reshape(-1, 1) - mo_energy[1][occidxb]
if wfnsym is not None and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = (orbsyma[viridxa].reshape(-1, 1)
^ orbsyma[occidxa]) != wfnsym
sym_forbidb = (orbsymb[viridxb].reshape(-1, 1)
^ orbsymb[occidxb]) != wfnsym
e_ai_a[sym_forbida] = 1e99
e_ai_b[sym_forbidb] = 1e99
eai = numpy.hstack((e_ai_a.ravel(), e_ai_b.ravel()))
nov = eai.size
nroot = min(nstates, nov)
x0 = numpy.zeros((nroot, nov))
idx = numpy.argsort(eai)
for i in range(nroot):
x0[i, idx[i]] = 1 # lowest excitations
return x0
def rotate_mo(self, mo_coeff, u, log=None):
mo = numpy.asarray((numpy.dot(mo_coeff[0], u[0]),
numpy.dot(mo_coeff[1], u[1])))
if self._scf.mol.symmetry:
orbsym = uhf_symm.get_orbsym(self._scf.mol, mo_coeff)
mo = lib.tag_array(mo, orbsym=orbsym)
return mo
def init_guess(self, mf, nstates=None, wfnsym=None):
if nstates is None: nstates = self.nstates
if wfnsym is None: wfnsym = self.wfnsym
mol = mf.mol
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
e_ia_max = max(e_ia_a.max(), e_ia_b.max())
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mf.mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma_in_d2h = numpy.asarray(orbsyma) % 10
orbsymb_in_d2h = numpy.asarray(orbsymb) % 10
e_ia_a[(orbsyma_in_d2h[occidxa, None]
^ orbsyma_in_d2h[viridxa]) != wfnsym] = 1e99
e_ia_b[(orbsymb_in_d2h[occidxb, None]
^ orbsymb_in_d2h[viridxb]) != wfnsym] = 1e99
e_ia = numpy.hstack((e_ia_a.ravel(), e_ia_b.ravel()))
e_ia_max = e_ia.max()
nov = e_ia.size
nstates = min(nstates, nov)
e_threshold = min(e_ia_max, e_ia[numpy.argsort(e_ia)[nstates - 1]])
# Handle degeneracy
e_threshold += 1e-6
idx = numpy.where(e_ia <= e_threshold)[0]
x0 = numpy.zeros((idx.size, nov))
for i, j in enumerate(idx):
x0[i, j] = 1 # Koopmans' excitations
return x0
def gen_tda_operation(mf, fock_ao=None, wfnsym=None):
'''(A+B)x
Kwargs:
wfnsym : int or str
Point group symmetry irrep symbol or ID for excited CIS wavefunction.
'''
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
sym_forbida = (orbsyma[occidxa, None] ^ orbsyma[viridxa]) != wfnsym
sym_forbidb = (orbsymb[occidxb, None] ^ orbsymb[viridxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
e_ia = hdiag = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
mo_a = numpy.asarray(numpy.hstack((orboa, orbva)), order='F')
mo_b = numpy.asarray(numpy.hstack((orbob, orbvb)), order='F')
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory * .8 - mem_now)
vresp = _gen_uhf_response(mf, hermi=0, max_memory=max_memory)
def vind(zs):
nz = len(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:, sym_forbid] = 0
dmov = numpy.empty((2, nz, nao, nao))
for i, z in enumerate(zs):
za = z[:nocca * nvira].reshape(nocca, nvira)
zb = z[nocca * nvira:].reshape(noccb, nvirb)
dmov[0, i] = reduce(numpy.dot, (orboa, za, orbva.conj().T))
dmov[1, i] = reduce(numpy.dot, (orbob, zb, orbvb.conj().T))
v1ao = vresp(dmov)
v1a = _ao2mo.nr_e2(v1ao[0], mo_a,
(0, nocca, nocca, nmo)).reshape(-1, nocca, nvira)
v1b = _ao2mo.nr_e2(v1ao[1], mo_b,
(0, noccb, noccb, nmo)).reshape(-1, noccb, nvirb)
for i, z in enumerate(zs):
za = z[:nocca * nvira].reshape(nocca, nvira)
zb = z[nocca * nvira:].reshape(noccb, nvirb)
v1a[i] += numpy.einsum('ia,ia->ia', e_ia_a, za)
v1b[i] += numpy.einsum('ia,ia->ia', e_ia_b, zb)
hx = numpy.hstack((v1a.reshape(nz, -1), v1b.reshape(nz, -1)))
if wfnsym is not None and mol.symmetry:
hx[:, sym_forbid] = 0
return hx
return vind, hdiag
def analyze(tdobj, verbose=None):
log = logger.new_logger(tdobj, verbose)
mol = tdobj.mol
mo_coeff = tdobj._scf.mo_coeff
mo_occ = tdobj._scf.mo_occ
nocc_a = numpy.count_nonzero(mo_occ[0] == 1)
nocc_b = numpy.count_nonzero(mo_occ[1] == 1)
e_ev = numpy.asarray(tdobj.e) * nist.HARTREE2EV
e_wn = numpy.asarray(tdobj.e) * nist.HARTREE2WAVENUMBER
wave_length = 1e11 / e_wn
log.note('\n** Excitation energies and oscillator strengths **')
if mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
orbsyma = orbsyma % 10
x_syma = (orbsyma[mo_occ[0] == 1, None]
^ orbsyma[mo_occ[0] == 0]).ravel()
else:
x_syma = None
f_oscillator = tdobj.oscillator_strength()
for i, ei in enumerate(tdobj.e):
x, y = tdobj.xy[i]
if x_syma is None:
log.note('Excited State %3d: %12.5f eV %9.2f nm f=%.4f', i + 1,
e_ev[i], wave_length[i], f_oscillator[i])
else:
wfnsym_id = x_syma[abs(x[0]).argmax()]
wfnsym = symm.irrep_id2name(mol.groupname, wfnsym_id)
log.note('Excited State %3d: %4s %12.5f eV %9.2f nm f=%.4f',
i + 1, wfnsym, e_ev[i], wave_length[i], f_oscillator[i])
if log.verbose >= logger.INFO:
for o, v in zip(*numpy.where(abs(x[0]) > 0.1)):
log.info(' %4da -> %4da %12.5f', o + MO_BASE,
v + MO_BASE + nocc_a, x[0][o, v])
for o, v in zip(*numpy.where(abs(x[1]) > 0.1)):
log.info(' %4db -> %4db %12.5f', o + MO_BASE,
v + MO_BASE + nocc_b, x[1][o, v])
if log.verbose >= logger.INFO:
log.info('\n** Transition electric dipole moments (AU) **')
log.info(
'state X Y Z Dip. S. Osc.'
)
trans_dip = tdobj.transition_dipole()
for i, ei in enumerate(tdobj.e):
dip = trans_dip[i]
log.info('%3d %11.4f %11.4f %11.4f %11.4f %11.4f', i + 1,
dip[0], dip[1], dip[2], numpy.dot(dip,
dip), f_oscillator[i])
log.info(
'\n** Transition velocity dipole moments (imaginary part AU) **')
log.info(
'state X Y Z Dip. S. Osc.'
)
trans_v = tdobj.transition_velocity_dipole()
f_v = tdobj.oscillator_strength(gauge='velocity', order=0)
for i, ei in enumerate(tdobj.e):
v = trans_v[i]
log.info('%3d %11.4f %11.4f %11.4f %11.4f %11.4f', i + 1, v[0],
v[1], v[2], numpy.dot(v, v), f_v[i])
log.info('\n** Transition magnetic dipole moments (AU) **')
log.info('state X Y Z')
trans_m = tdobj.transition_magnetic_dipole()
for i, ei in enumerate(tdobj.e):
m = trans_m[i]
log.info('%3d %11.4f %11.4f %11.4f', i + 1, m[0], m[1], m[2])
return tdobj
def get_vind(self, mf):
wfnsym = self.wfnsym
singlet = self.singlet
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
sym_forbida = (orbsyma[occidxa, None] ^ orbsyma[viridxa]) != wfnsym
sym_forbidb = (orbsymb[occidxb, None] ^ orbsymb[viridxb]) != wfnsym
sym_forbid = numpy.hstack(
(sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
e_ia = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
e_ia[sym_forbid] = 0
d_ia = numpy.sqrt(e_ia).ravel()
ed_ia = e_ia.ravel() * d_ia
hdiag = e_ia.ravel()**2
vresp = mf.gen_response(mo_coeff, mo_occ, hermi=1)
def vind(zs):
nz = len(zs)
zs = numpy.asarray(zs).reshape(nz, -1)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:, sym_forbid] = 0
dmsa = (zs[:, :nocca * nvira] * d_ia[:nocca * nvira]).reshape(
nz, nocca, nvira)
dmsb = (zs[:, nocca * nvira:] * d_ia[nocca * nvira:]).reshape(
nz, noccb, nvirb)
dmsa = lib.einsum('xov,po,qv->xpq', dmsa, orboa, orbva.conj())
dmsb = lib.einsum('xov,po,qv->xpq', dmsb, orbob, orbvb.conj())
dmsa = dmsa + dmsa.conj().transpose(0, 2, 1)
dmsb = dmsb + dmsb.conj().transpose(0, 2, 1)
v1ao = vresp(numpy.asarray((dmsa, dmsb)))
v1a = lib.einsum('xpq,po,qv->xov', v1ao[0], orboa.conj(), orbva)
v1b = lib.einsum('xpq,po,qv->xov', v1ao[1], orbob.conj(), orbvb)
hx = numpy.hstack((v1a.reshape(nz, -1), v1b.reshape(nz, -1)))
hx += ed_ia * zs
hx *= d_ia
return hx
return vind, hdiag
def get_nto(tdobj, state=1, threshold=OUTPUT_THRESHOLD, verbose=None):
r'''
Natural transition orbital analysis.
The natural transition density matrix between ground state and excited
state :math:`Tia = \langle \Psi_{ex} | i a^\dagger | \Psi_0 \rangle` can
be transformed to diagonal form through SVD
:math:`T = O \sqrt{\lambda} V^\dagger`. O and V are occupied and virtual
natural transition orbitals. The diagonal elements :math:`\lambda` are the
weights of the occupied-virtual orbital pair in the excitation.
Ref: Martin, R. L., JCP, 118, 4775-4777
Note in the TDHF/TDDFT calculations, the excitation part (X) is
interpreted as the CIS coefficients and normalized to 1. The de-excitation
part (Y) is ignored.
Args:
state : int
Excited state ID. state = 1 means the first excited state.
If state < 0, state ID is counted from the last excited state.
Kwargs:
threshold : float
Above which the NTO coefficients will be printed in the output.
Returns:
A list (weights, NTOs). NTOs are natural orbitals represented in AO
basis. The first N_occ NTOs are occupied NTOs and the rest are virtual
NTOs.
'''
if state == 0:
logger.warn(
tdobj, 'Excited state starts from 1. '
'Set state=1 for first excited state.')
state_id = state
elif state < 0:
state_id = state
else:
state_id = state - 1
mol = tdobj.mol
mo_coeff = tdobj._scf.mo_coeff
mo_occ = tdobj._scf.mo_occ
orbo_a = mo_coeff[0][:, mo_occ[0] == 1]
orbv_a = mo_coeff[0][:, mo_occ[0] == 0]
orbo_b = mo_coeff[1][:, mo_occ[1] == 1]
orbv_b = mo_coeff[1][:, mo_occ[1] == 0]
nocc_a = orbo_a.shape[1]
nvir_a = orbv_a.shape[1]
nocc_b = orbo_b.shape[1]
nvir_b = orbv_b.shape[1]
cis_t1a, cis_t1b = tdobj.xy[state_id][0]
norm = numpy.linalg.norm(cis_t1a)**2 + numpy.linalg.norm(cis_t1b)**2
cis_t1a *= 1. / norm
cis_t1b *= 1. / norm
if mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
o_sym_a = orbsyma[mo_occ[0] == 1]
v_sym_a = orbsyma[mo_occ[0] == 0]
o_sym_b = orbsymb[mo_occ[1] == 1]
v_sym_b = orbsymb[mo_occ[1] == 0]
nto_o_a = numpy.eye(nocc_a)
nto_v_a = numpy.eye(nvir_a)
nto_o_b = numpy.eye(nocc_b)
nto_v_b = numpy.eye(nvir_b)
weights_o_a = numpy.zeros(nocc_a)
weights_v_a = numpy.zeros(nvir_a)
weights_o_b = numpy.zeros(nocc_b)
weights_v_b = numpy.zeros(nvir_b)
for ir in set(orbsyma):
idx = numpy.where(o_sym_a == ir)[0]
if idx.size > 0:
dm_oo = numpy.dot(cis_t1a[idx], cis_t1a[idx].T)
weights_o_a[idx], nto_o_a[idx[:, None],
idx] = numpy.linalg.eigh(dm_oo)
idx = numpy.where(v_sym_a == ir)[0]
if idx.size > 0:
dm_vv = numpy.dot(cis_t1a[:, idx].T, cis_t1a[:, idx])
weights_v_a[idx], nto_v_a[idx[:, None],
idx] = numpy.linalg.eigh(dm_vv)
for ir in set(orbsymb):
idx = numpy.where(o_sym_b == ir)[0]
if idx.size > 0:
dm_oo = numpy.dot(cis_t1b[idx], cis_t1b[idx].T)
weights_o_b[idx], nto_o_b[idx[:, None],
idx] = numpy.linalg.eigh(dm_oo)
idx = numpy.where(v_sym_b == ir)[0]
if idx.size > 0:
dm_vv = numpy.dot(cis_t1b[:, idx].T, cis_t1b[:, idx])
weights_v_b[idx], nto_v_b[idx[:, None],
idx] = numpy.linalg.eigh(dm_vv)
def sort(weights, nto, sym):
# weights in descending order
idx = numpy.argsort(-weights)
weights = weights[idx]
nto = nto[:, idx]
sym = sym[idx]
return weights, nto, sym
weights_o_a, nto_o_a, o_sym_a = sort(weights_o_a, nto_o_a, o_sym_a)
weights_v_a, nto_v_a, v_sym_a = sort(weights_v_a, nto_v_a, v_sym_a)
weights_o_b, nto_o_b, o_sym_b = sort(weights_o_b, nto_o_b, o_sym_b)
weights_v_b, nto_v_b, v_sym_b = sort(weights_v_b, nto_v_b, v_sym_b)
nto_orbsyma = numpy.hstack((o_sym_a, v_sym_a))
nto_orbsymb = numpy.hstack((o_sym_b, v_sym_b))
if nocc_a < nvir_a:
weights_a = weights_o_a
else:
weights_a = weights_v_a
if nocc_b < nvir_b:
weights_b = weights_o_b
else:
weights_b = weights_v_b
else:
nto_o_a, w_a, nto_v_aT = numpy.linalg.svd(cis_t1a)
nto_o_b, w_b, nto_v_bT = numpy.linalg.svd(cis_t1b)
nto_v_a = nto_v_aT.conj().T
nto_v_b = nto_v_bT.conj().T
weights_a = w_a**2
weights_b = w_b**2
nto_orbsyma = nto_orbsymb = None
def _set_phase_(c):
idx = numpy.argmax(abs(c.real), axis=0)
c[:, c[idx, numpy.arange(c.shape[1])].real < 0] *= -1
_set_phase_(nto_o_a)
_set_phase_(nto_o_b)
_set_phase_(nto_v_a)
_set_phase_(nto_v_b)
occupied_nto_a = numpy.dot(orbo_a, nto_o_a)
occupied_nto_b = numpy.dot(orbo_b, nto_o_b)
virtual_nto_a = numpy.dot(orbv_a, nto_v_a)
virtual_nto_b = numpy.dot(orbv_b, nto_v_b)
nto_coeff = (numpy.hstack((occupied_nto_a, virtual_nto_a)),
numpy.hstack((occupied_nto_b, virtual_nto_b)))
if mol.symmetry:
nto_coeff = (lib.tag_array(nto_coeff[0], orbsym=nto_orbsyma),
lib.tag_array(nto_coeff[1], orbsym=nto_orbsymb))
log = logger.new_logger(tdobj, verbose)
if log.verbose >= logger.INFO:
log.info('State %d: %g eV NTO largest component %s', state_id + 1,
tdobj.e[state_id] * nist.HARTREE2EV,
weights_a[0] + weights_b[0])
fmt = '%' + str(lib.param.OUTPUT_DIGITS) + 'f (MO #%d)'
o_idx_a = numpy.where(abs(nto_o_a[:, 0]) > threshold)[0]
v_idx_a = numpy.where(abs(nto_v_a[:, 0]) > threshold)[0]
o_idx_b = numpy.where(abs(nto_o_b[:, 0]) > threshold)[0]
v_idx_b = numpy.where(abs(nto_v_b[:, 0]) > threshold)[0]
log.info(' alpha occ-NTO: ' +
' + '.join([(fmt % (nto_o_a[i, 0], i + MO_BASE))
for i in o_idx_a]))
log.info(' alpha vir-NTO: ' +
' + '.join([(fmt % (nto_v_a[i, 0], i + MO_BASE + nocc_a))
for i in v_idx_a]))
log.info(' beta occ-NTO: ' +
' + '.join([(fmt % (nto_o_b[i, 0], i + MO_BASE))
for i in o_idx_b]))
log.info(' beta vir-NTO: ' +
' + '.join([(fmt % (nto_v_b[i, 0], i + MO_BASE + nocc_b))
for i in v_idx_b]))
return (weights_a, weights_b), nto_coeff
def get_vind(self, mf):
wfnsym = self.wfnsym
singlet = self.singlet
mol = mf.mol
mo_coeff = mf.mo_coeff
assert(mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0]>0)[0]
occidxb = numpy.where(mo_occ[1]>0)[0]
viridxa = numpy.where(mo_occ[0]==0)[0]
viridxb = numpy.where(mo_occ[1]==0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:,occidxa]
orbob = mo_coeff[1][:,occidxb]
orbva = mo_coeff[0][:,viridxa]
orbvb = mo_coeff[1][:,viridxb]
if wfnsym is not None and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = (orbsyma[viridxa].reshape(-1,1) ^ orbsyma[occidxa]) != wfnsym
sym_forbidb = (orbsymb[viridxb].reshape(-1,1) ^ orbsymb[occidxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ai_a = mo_energy[0][viridxa].reshape(-1,1) - mo_energy[0][occidxa]
e_ai_b = mo_energy[1][viridxb].reshape(-1,1) - mo_energy[1][occidxb]
e_ai = numpy.hstack((e_ai_a.reshape(-1), e_ai_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
e_ai[sym_forbid] = 0
dai = numpy.sqrt(e_ai).ravel()
edai = e_ai.ravel() * dai
hdiag = e_ai.ravel() ** 2
if mf.grids.coords is None:
mf.grids.build()
ni = mf._numint
hyb = ni.hybrid_coeff(mf.xc, spin=mol.spin)
dm0 = None # mf.make_rdm1(mf.mo_coeff, mf.mo_occ)
rho0, vxc, fxc = ni.cache_xc_kernel(mf.mol, mf.grids, mf.xc,
mo_coeff, mo_occ, spin=1)
mem_now = lib.current_memory()[0]
max_memory = max(2000, self.max_memory*.8-mem_now)
def vind(zs):
nz = len(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:,sym_forbid] = 0
dmvo = numpy.empty((2,nz,nao,nao))
for i in range(nz):
z = dai * zs[i]
za = z[:nocca*nvira].reshape(nvira,nocca)
zb = z[nocca*nvira:].reshape(nvirb,noccb)
dm = reduce(numpy.dot, (orbva, za, orboa.T))
dmvo[0,i] = dm + dm.T
dm = reduce(numpy.dot, (orbvb, zb, orbob.T))
dmvo[1,i] = dm + dm.T
v1ao = ni.nr_uks_fxc(mol, mf.grids, mf.xc, dm0, dmvo, 0, 1, rho0,
vxc, fxc, max_memory)
if self.singlet:
vj = mf.get_j(mf.mol, dmvo, hermi=1)
v1ao += vj[0] + vj[1]
v1a = _ao2mo.nr_e2(v1ao[0], mo_coeff[0], (nocca,nmo,0,nocca))
v1b = _ao2mo.nr_e2(v1ao[1], mo_coeff[1], (noccb,nmo,0,noccb))
hx = numpy.hstack((v1a.reshape(nz,-1), v1b.reshape(nz,-1)))
for i, z in enumerate(zs):
hx[i] += edai * z
hx[i] *= dai
return hx
return vind, hdiag
def get_vind(self, mf):
wfnsym = self.wfnsym
singlet = self.singlet
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
sym_forbida = (orbsyma[occidxa, None] ^ orbsyma[viridxa]) != wfnsym
sym_forbidb = (orbsymb[occidxb, None] ^ orbsymb[viridxb]) != wfnsym
sym_forbid = numpy.hstack(
(sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
e_ia = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
e_ia[sym_forbid] = 0
d_ia = numpy.sqrt(e_ia).ravel()
ed_ia = e_ia.ravel() * d_ia
hdiag = e_ia.ravel()**2
vresp = _gen_uhf_response(mf, mo_coeff, mo_occ, hermi=1)
def vind(zs):
nz = len(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:, sym_forbid] = 0
dmov = numpy.empty((2, nz, nao, nao))
for i in range(nz):
z = d_ia * zs[i]
za = z[:nocca * nvira].reshape(nocca, nvira)
zb = z[nocca * nvira:].reshape(noccb, nvirb)
dm = reduce(numpy.dot, (orboa, za, orbva.T))
dmov[0, i] = dm + dm.T
dm = reduce(numpy.dot, (orbob, zb, orbvb.T))
dmov[1, i] = dm + dm.T
v1ao = vresp(dmov)
v1a = _ao2mo.nr_e2(v1ao[0], mo_coeff[0], (0, nocca, nocca, nmo))
v1b = _ao2mo.nr_e2(v1ao[1], mo_coeff[1], (0, noccb, noccb, nmo))
hx = numpy.hstack((v1a.reshape(nz, -1), v1b.reshape(nz, -1)))
for i, z in enumerate(zs):
hx[i] += ed_ia * z
hx[i] *= d_ia
return hx
return vind, hdiag
def _gen_hop_uhf_external(mf, with_symmetry=True, verbose=None):
mol = mf.mol
mo_coeff = mf.mo_coeff
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
occidxa = numpy.where(mo_occ[0]>0)[0]
occidxb = numpy.where(mo_occ[1]>0)[0]
viridxa = numpy.where(mo_occ[0]==0)[0]
viridxb = numpy.where(mo_occ[1]==0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:,occidxa]
orbob = mo_coeff[1][:,occidxb]
orbva = mo_coeff[0][:,viridxa]
orbvb = mo_coeff[1][:,viridxb]
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = orbsyma[viridxa].reshape(-1,1) != orbsyma[occidxa]
sym_forbidb = orbsymb[viridxb].reshape(-1,1) != orbsymb[occidxb]
sym_forbid1 = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
h1e = mf.get_hcore()
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = h1e + mf.get_veff(mol, dm0)
focka = reduce(numpy.dot, (mo_coeff[0].conj().T, fock_ao[0], mo_coeff[0]))
fockb = reduce(numpy.dot, (mo_coeff[1].conj().T, fock_ao[1], mo_coeff[1]))
fooa = focka[occidxa[:,None],occidxa]
fvva = focka[viridxa[:,None],viridxa]
foob = fockb[occidxb[:,None],occidxb]
fvvb = fockb[viridxb[:,None],viridxb]
h_diaga =(focka[viridxa,viridxa].reshape(-1,1) - focka[occidxa,occidxa])
h_diagb =(fockb[viridxb,viridxb].reshape(-1,1) - fockb[occidxb,occidxb])
hdiag1 = numpy.hstack((h_diaga.reshape(-1), h_diagb.reshape(-1)))
if with_symmetry and mol.symmetry:
hdiag1[sym_forbid1] = 0
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory*.8-mem_now)
vrespz = _gen_uhf_response(mf, with_j=False, hermi=2)
def hop_real2complex(x1):
if with_symmetry and mol.symmetry:
x1 = x1.copy()
x1[sym_forbid1] = 0
x1a = x1[:nvira*nocca].reshape(nvira,nocca)
x1b = x1[nvira*nocca:].reshape(nvirb,noccb)
x2a = numpy.einsum('pr,rq->pq', fvva, x1a)
x2a-= numpy.einsum('sq,ps->pq', fooa, x1a)
x2b = numpy.einsum('pr,rq->pq', fvvb, x1b)
x2b-= numpy.einsum('qs,ps->pq', foob, x1b)
d1a = reduce(numpy.dot, (orbva, x1a, orboa.conj().T))
d1b = reduce(numpy.dot, (orbvb, x1b, orbob.conj().T))
dm1 = numpy.array((d1a-d1a.conj().T, d1b-d1b.conj().T))
v1 = vrespz(dm1)
x2a += reduce(numpy.dot, (orbva.conj().T, v1[0], orboa))
x2b += reduce(numpy.dot, (orbvb.conj().T, v1[1], orbob))
x2 = numpy.hstack((x2a.ravel(), x2b.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid1] = 0
return x2
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbidab = orbsyma[viridxa].reshape(-1,1) != orbsymb[occidxb]
sym_forbidba = orbsymb[viridxb].reshape(-1,1) != orbsyma[occidxa]
sym_forbid2 = numpy.hstack((sym_forbidab.ravel(), sym_forbidba.ravel()))
hdiagab = fvva.diagonal().reshape(-1,1) - foob.diagonal()
hdiagba = fvvb.diagonal().reshape(-1,1) - fooa.diagonal()
hdiag2 = numpy.hstack((hdiagab.ravel(), hdiagba.ravel()))
if with_symmetry and mol.symmetry:
hdiag2[sym_forbid2] = 0
vresp1 = _gen_uhf_response(mf, with_j=False, hermi=0)
# Spin flip GHF solution is not considered
def hop_uhf2ghf(x1):
if with_symmetry and mol.symmetry:
x1 = x1.copy()
x1[sym_forbid2] = 0
x1ab = x1[:nvira*noccb].reshape(nvira,noccb)
x1ba = x1[nvira*noccb:].reshape(nvirb,nocca)
x2ab = numpy.einsum('pr,rq->pq', fvva, x1ab)
x2ab-= numpy.einsum('sq,ps->pq', foob, x1ab)
x2ba = numpy.einsum('pr,rq->pq', fvvb, x1ba)
x2ba-= numpy.einsum('qs,ps->pq', fooa, x1ba)
d1ab = reduce(numpy.dot, (orbva, x1ab, orbob.conj().T))
d1ba = reduce(numpy.dot, (orbvb, x1ba, orboa.conj().T))
dm1 = numpy.array((d1ab+d1ba.conj().T, d1ba+d1ab.conj().T))
v1 = vresp1(dm1)
x2ab += reduce(numpy.dot, (orbva.conj().T, v1[0], orbob))
x2ba += reduce(numpy.dot, (orbvb.conj().T, v1[1], orboa))
x2 = numpy.hstack((x2ab.real.ravel(), x2ba.real.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid2] = 0
return x2
return hop_real2complex, hdiag1, hop_uhf2ghf, hdiag2
def _gen_hop_uhf_external(mf, with_symmetry=True, verbose=None):
mol = mf.mol
mo_coeff = mf.mo_coeff
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
occidxa = numpy.where(mo_occ[0]>0)[0]
occidxb = numpy.where(mo_occ[1]>0)[0]
viridxa = numpy.where(mo_occ[0]==0)[0]
viridxb = numpy.where(mo_occ[1]==0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:,occidxa]
orbob = mo_coeff[1][:,occidxb]
orbva = mo_coeff[0][:,viridxa]
orbvb = mo_coeff[1][:,viridxb]
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = orbsyma[viridxa].reshape(-1,1) != orbsyma[occidxa]
sym_forbidb = orbsymb[viridxb].reshape(-1,1) != orbsymb[occidxb]
sym_forbid1 = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
h1e = mf.get_hcore()
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = h1e + mf.get_veff(mol, dm0)
focka = reduce(numpy.dot, (mo_coeff[0].T, fock_ao[0], mo_coeff[0]))
fockb = reduce(numpy.dot, (mo_coeff[1].T, fock_ao[1], mo_coeff[1]))
fooa = focka[occidxa[:,None],occidxa]
fvva = focka[viridxa[:,None],viridxa]
foob = fockb[occidxb[:,None],occidxb]
fvvb = fockb[viridxb[:,None],viridxb]
h_diaga =(focka[viridxa,viridxa].reshape(-1,1) - focka[occidxa,occidxa])
h_diagb =(fockb[viridxb,viridxb].reshape(-1,1) - fockb[occidxb,occidxb])
hdiag1 = numpy.hstack((h_diaga.reshape(-1), h_diagb.reshape(-1)))
if with_symmetry and mol.symmetry:
hdiag1[sym_forbid1] = 0
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory*.8-mem_now)
vrespz = _gen_uhf_response(mf, with_j=False, hermi=2)
def hop_real2complex(x1):
if with_symmetry and mol.symmetry:
x1 = x1.copy()
x1[sym_forbid1] = 0
x1a = x1[:nvira*nocca].reshape(nvira,nocca)
x1b = x1[nvira*nocca:].reshape(nvirb,noccb)
x2a = numpy.einsum('pr,rq->pq', fvva, x1a)
x2a-= numpy.einsum('sq,ps->pq', fooa, x1a)
x2b = numpy.einsum('pr,rq->pq', fvvb, x1b)
x2b-= numpy.einsum('qs,ps->pq', foob, x1b)
d1a = reduce(numpy.dot, (orbva, x1a, orboa.T.conj()))
d1b = reduce(numpy.dot, (orbvb, x1b, orbob.T.conj()))
dm1 = numpy.array((d1a-d1a.T.conj(), d1b-d1b.T.conj()))
v1 = vrespz(dm1)
x2a += reduce(numpy.dot, (orbva.T.conj(), v1[0], orboa))
x2b += reduce(numpy.dot, (orbvb.T.conj(), v1[1], orbob))
x2 = numpy.hstack((x2a.ravel(), x2b.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid1] = 0
return x2
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbidab = orbsyma[viridxa].reshape(-1,1) != orbsymb[occidxb]
sym_forbidba = orbsymb[viridxb].reshape(-1,1) != orbsyma[occidxa]
sym_forbid2 = numpy.hstack((sym_forbidab.ravel(), sym_forbidba.ravel()))
hdiagab = fvva.diagonal().reshape(-1,1) - foob.diagonal()
hdiagba = fvvb.diagonal().reshape(-1,1) - fooa.diagonal()
hdiag2 = numpy.hstack((hdiagab.ravel(), hdiagba.ravel()))
if with_symmetry and mol.symmetry:
hdiag2[sym_forbid2] = 0
vresp1 = _gen_uhf_response(mf, with_j=False, hermi=0)
# Spin flip GHF solution is not considered
def hop_uhf2ghf(x1):
if with_symmetry and mol.symmetry:
x1 = x1.copy()
x1[sym_forbid2] = 0
x1ab = x1[:nvira*noccb].reshape(nvira,noccb)
x1ba = x1[nvira*noccb:].reshape(nvirb,nocca)
x2ab = numpy.einsum('pr,rq->pq', fvva, x1ab)
x2ab-= numpy.einsum('sq,ps->pq', foob, x1ab)
x2ba = numpy.einsum('pr,rq->pq', fvvb, x1ba)
x2ba-= numpy.einsum('qs,ps->pq', fooa, x1ba)
d1ab = reduce(numpy.dot, (orbva, x1ab, orbob.T.conj()))
d1ba = reduce(numpy.dot, (orbvb, x1ba, orboa.T.conj()))
dm1 = numpy.array((d1ab+d1ba.T.conj(), d1ba+d1ab.T.conj()))
v1 = vresp1(dm1)
x2ab += reduce(numpy.dot, (orbva.T.conj(), v1[0], orbob))
x2ba += reduce(numpy.dot, (orbvb.T.conj(), v1[1], orboa))
x2 = numpy.hstack((x2ab.ravel(), x2ba.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid2] = 0
return x2
return hop_real2complex, hdiag1, hop_uhf2ghf, hdiag2
def get_vind(self, mf):
wfnsym = self.wfnsym
singlet = self.singlet
mol = mf.mol
mo_coeff = mf.mo_coeff
assert(mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0]>0)[0]
occidxb = numpy.where(mo_occ[1]>0)[0]
viridxa = numpy.where(mo_occ[0]==0)[0]
viridxb = numpy.where(mo_occ[1]==0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:,occidxa]
orbob = mo_coeff[1][:,occidxb]
orbva = mo_coeff[0][:,viridxa]
orbvb = mo_coeff[1][:,viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
sym_forbida = (orbsyma[occidxa,None] ^ orbsyma[viridxa]) != wfnsym
sym_forbidb = (orbsymb[occidxb,None] ^ orbsymb[viridxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = (mo_energy[0][viridxa,None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb,None] - mo_energy[1][occidxb]).T
e_ia = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
e_ia[sym_forbid] = 0
d_ia = numpy.sqrt(e_ia).ravel()
ed_ia = e_ia.ravel() * d_ia
hdiag = e_ia.ravel() ** 2
vresp = _gen_uhf_response(mf, mo_coeff, mo_occ, hermi=1)
def vind(zs):
nz = len(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:,sym_forbid] = 0
dmov = numpy.empty((2,nz,nao,nao))
for i in range(nz):
z = d_ia * zs[i]
za = z[:nocca*nvira].reshape(nocca,nvira)
zb = z[nocca*nvira:].reshape(noccb,nvirb)
dm = reduce(numpy.dot, (orboa, za, orbva.T))
dmov[0,i] = dm + dm.T
dm = reduce(numpy.dot, (orbob, zb, orbvb.T))
dmov[1,i] = dm + dm.T
v1ao = vresp(dmov)
v1a = _ao2mo.nr_e2(v1ao[0], mo_coeff[0], (0,nocca,nocca,nmo))
v1b = _ao2mo.nr_e2(v1ao[1], mo_coeff[1], (0,noccb,noccb,nmo))
hx = numpy.hstack((v1a.reshape(nz,-1), v1b.reshape(nz,-1)))
for i, z in enumerate(zs):
hx[i] += ed_ia * z
hx[i] *= d_ia
return hx
return vind, hdiag
def gen_g_hop_uhf(mf, mo_coeff, mo_occ, fock_ao=None, h1e=None,
with_symmetry=True):
mol = mf.mol
mo_coeff0 = mo_coeff
if getattr(mf, '_scf', None) and mf._scf.mol != mol:
#TODO: construct vind with dual-basis treatment, (see also JCP, 118, 9497)
mo_coeff = (addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[0], mol),
addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[1], mol))
occidxa = numpy.where(mo_occ[0]>0)[0]
occidxb = numpy.where(mo_occ[1]>0)[0]
viridxa = numpy.where(mo_occ[0]==0)[0]
viridxb = numpy.where(mo_occ[1]==0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:,occidxa]
orbob = mo_coeff[1][:,occidxb]
orbva = mo_coeff[0][:,viridxa]
orbvb = mo_coeff[1][:,viridxb]
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = orbsyma[viridxa,None] != orbsyma[occidxa]
sym_forbidb = orbsymb[viridxb,None] != orbsymb[occidxb]
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
if fock_ao is None:
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = mf.get_fock(h1e, dm=dm0)
focka = reduce(numpy.dot, (mo_coeff[0].conj().T, fock_ao[0], mo_coeff[0]))
fockb = reduce(numpy.dot, (mo_coeff[1].conj().T, fock_ao[1], mo_coeff[1]))
else:
focka = reduce(numpy.dot, (mo_coeff0[0].conj().T, fock_ao[0], mo_coeff0[0]))
fockb = reduce(numpy.dot, (mo_coeff0[1].conj().T, fock_ao[1], mo_coeff0[1]))
fooa = focka[occidxa[:,None],occidxa]
fvva = focka[viridxa[:,None],viridxa]
foob = fockb[occidxb[:,None],occidxb]
fvvb = fockb[viridxb[:,None],viridxb]
g = numpy.hstack((focka[viridxa[:,None],occidxa].ravel(),
fockb[viridxb[:,None],occidxb].ravel()))
h_diaga = fvva.diagonal().real[:,None] - fooa.diagonal().real
h_diagb = fvvb.diagonal().real[:,None] - foob.diagonal().real
h_diag = numpy.hstack((h_diaga.reshape(-1), h_diagb.reshape(-1)))
if with_symmetry and mol.symmetry:
g[sym_forbid] = 0
h_diag[sym_forbid] = 0
vind = _gen_uhf_response(mf, mo_coeff, mo_occ, hermi=1)
def h_op(x):
if with_symmetry and mol.symmetry:
x = x.copy()
x[sym_forbid] = 0
x1a = x[:nvira*nocca].reshape(nvira,nocca)
x1b = x[nvira*nocca:].reshape(nvirb,noccb)
x2a = numpy.einsum('pr,rq->pq', fvva, x1a)
x2a-= numpy.einsum('sq,ps->pq', fooa, x1a)
x2b = numpy.einsum('pr,rq->pq', fvvb, x1b)
x2b-= numpy.einsum('sq,ps->pq', foob, x1b)
d1a = reduce(numpy.dot, (orbva, x1a, orboa.conj().T))
d1b = reduce(numpy.dot, (orbvb, x1b, orbob.conj().T))
dm1 = numpy.array((d1a+d1a.conj().T,d1b+d1b.conj().T))
v1 = vind(dm1)
x2a += reduce(numpy.dot, (orbva.conj().T, v1[0], orboa))
x2b += reduce(numpy.dot, (orbvb.conj().T, v1[1], orbob))
x2 = numpy.hstack((x2a.ravel(), x2b.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid] = 0
return x2
return g, h_op, h_diag
def gen_g_hop_uhf(mf,
mo_coeff,
mo_occ,
fock_ao=None,
h1e=None,
with_symmetry=True):
mol = mf.mol
if hasattr(mf, '_scf') and id(mf._scf.mol) != id(mol):
mo_coeff = (addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[0], mol),
addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[1], mol))
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = orbsyma[viridxa].reshape(-1, 1) != orbsyma[occidxa]
sym_forbidb = orbsymb[viridxb].reshape(-1, 1) != orbsymb[occidxb]
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
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(mol, dm0)
focka = reduce(numpy.dot, (mo_coeff[0].T, fock_ao[0], mo_coeff[0]))
fockb = reduce(numpy.dot, (mo_coeff[1].T, fock_ao[1], mo_coeff[1]))
fooa = focka[occidxa[:, None], occidxa]
fvva = focka[viridxa[:, None], viridxa]
foob = fockb[occidxb[:, None], occidxb]
fvvb = fockb[viridxb[:, None], viridxb]
g = numpy.hstack((focka[occidxa[:, None],
viridxa].T.ravel(), fockb[occidxb[:, None],
viridxb].T.ravel()))
h_diaga = focka[viridxa, viridxa].reshape(-1, 1) - focka[occidxa, occidxa]
h_diagb = fockb[viridxb, viridxb].reshape(-1, 1) - fockb[occidxb, occidxb]
h_diag = numpy.hstack((h_diaga.reshape(-1), h_diagb.reshape(-1)))
if with_symmetry and mol.symmetry:
g[sym_forbid] = 0
h_diag[sym_forbid] = 0
vind = _gen_uhf_response(mf, mo_coeff, mo_occ, hermi=1)
def h_op(x):
if with_symmetry and mol.symmetry:
x = x.copy()
x[sym_forbid] = 0
x1a = x[:nvira * nocca].reshape(nvira, nocca)
x1b = x[nvira * nocca:].reshape(nvirb, noccb)
x2a = numpy.einsum('pr,rq->pq', fvva, x1a)
x2a -= numpy.einsum('sq,ps->pq', fooa, x1a)
x2b = numpy.einsum('pr,rq->pq', fvvb, x1b)
x2b -= numpy.einsum('sq,ps->pq', foob, x1b)
d1a = reduce(numpy.dot, (orbva, x1a, orboa.T.conj()))
d1b = reduce(numpy.dot, (orbvb, x1b, orbob.T.conj()))
dm1 = numpy.array((d1a + d1a.T.conj(), d1b + d1b.T.conj()))
v1 = vind(dm1)
x2a += reduce(numpy.dot, (orbva.T.conj(), v1[0], orboa))
x2b += reduce(numpy.dot, (orbvb.T.conj(), v1[1], orbob))
x2 = numpy.hstack((x2a.ravel(), x2b.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid] = 0
return x2
return g, h_op, h_diag
def get_vind(self, mf):
'''
[ A B][X]
[-B -A][Y]
'''
wfnsym = self.wfnsym
singlet = self.singlet
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = (orbsyma[viridxa].reshape(-1, 1)
^ orbsyma[occidxa]) != wfnsym
sym_forbidb = (orbsymb[viridxb].reshape(-1, 1)
^ orbsymb[occidxb]) != wfnsym
sym_forbid = numpy.hstack(
(sym_forbida.ravel(), sym_forbidb.ravel()))
e_ai_a = mo_energy[0][viridxa].reshape(-1, 1) - mo_energy[0][occidxa]
e_ai_b = mo_energy[1][viridxb].reshape(-1, 1) - mo_energy[1][occidxb]
e_ai = hdiag = numpy.hstack((e_ai_a.reshape(-1), e_ai_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
hdiag = numpy.hstack((hdiag.ravel(), hdiag.ravel()))
mo_a = numpy.asarray(numpy.hstack((orboa, orbva)), order='F')
mo_b = numpy.asarray(numpy.hstack((orbob, orbvb)), order='F')
mem_now = lib.current_memory()[0]
max_memory = max(2000, self.max_memory * .8 - mem_now)
vresp = _gen_uhf_response(mf, hermi=0, max_memory=max_memory)
def vind(xys):
nz = len(xys)
if wfnsym is not None and mol.symmetry:
# shape(nz,2,-1): 2 ~ X,Y
xys = numpy.copy(zs).reshape(nz, 2, -1)
xys[:, :, :, sym_forbid] = 0
dms = numpy.empty((2, nz, nao, nao)) # 2 ~ alpha,beta
for i in range(nz):
x, y = xys[i].reshape(2, -1)
xa = x[:nocca * nvira].reshape(nvira, nocca)
xb = x[nocca * nvira:].reshape(nvirb, noccb)
ya = y[:nocca * nvira].reshape(nvira, nocca)
yb = y[nocca * nvira:].reshape(nvirb, noccb)
dmx = reduce(numpy.dot, (orbva, xa, orboa.T))
dmy = reduce(numpy.dot, (orboa, ya.T, orbva.T))
dms[0, i] = dmx + dmy # AX + BY
dmx = reduce(numpy.dot, (orbvb, xb, orbob.T))
dmy = reduce(numpy.dot, (orbob, yb.T, orbvb.T))
dms[1, i] = dmx + dmy # AX + BY
v1ao = vresp(dms)
v1avo = _ao2mo.nr_e2(v1ao[0], mo_a, (nocca, nmo, 0, nocca))
v1bvo = _ao2mo.nr_e2(v1ao[1], mo_b, (noccb, nmo, 0, noccb))
v1aov = _ao2mo.nr_e2(v1ao[0], mo_a, (0, nocca, nocca, nmo))
v1bov = _ao2mo.nr_e2(v1ao[1], mo_b, (0, noccb, noccb, nmo))
hx = numpy.empty((nz, 2, nvira * nocca + nvirb * noccb),
dtype=v1avo.dtype)
for i in range(nz):
x, y = xys[i].reshape(2, -1)
hx[i, 0, :nvira * nocca] = v1avo[i].ravel()
hx[i, 0, nvira * nocca:] = v1bvo[i].ravel()
hx[i, 0] += e_ai * x # AX
hx[i, 1, :nvira *
nocca] = -v1aov[i].reshape(nocca, nvira).T.ravel()
hx[i, 1,
nvira * nocca:] = -v1bov[i].reshape(noccb, nvirb).T.ravel()
hx[i, 1] -= e_ai * y #-AY
if wfnsym is not None and mol.symmetry:
hx[:, :, sym_forbid] = 0
return hx.reshape(nz, -1)
return vind, hdiag
def gen_tda_hop(mf, fock_ao=None, wfnsym=None, max_memory=2000):
'''(A+B)x
Kwargs:
wfnsym : int
Point group symmetry for excited CIS wavefunction.
'''
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = (orbsyma[viridxa].reshape(-1, 1)
^ orbsyma[occidxa]) != wfnsym
sym_forbidb = (orbsymb[viridxb].reshape(-1, 1)
^ orbsymb[occidxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ai_a = mo_energy[0][viridxa].reshape(-1, 1) - mo_energy[0][occidxa]
e_ai_b = mo_energy[1][viridxb].reshape(-1, 1) - mo_energy[1][occidxb]
e_ai = hdiag = numpy.hstack((e_ai_a.reshape(-1), e_ai_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
mo_a = numpy.asarray(numpy.hstack((orboa, orbva)), order='F')
mo_b = numpy.asarray(numpy.hstack((orbob, orbvb)), order='F')
mem_now = lib.current_memory()[0]
max_memory = max(2000, max_memory * .8 - mem_now)
vresp = _gen_uhf_response(mf, hermi=0, max_memory=max_memory)
def vind(zs):
nz = len(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:, sym_forbid] = 0
dmvo = numpy.empty((2, nz, nao, nao))
for i, z in enumerate(zs):
za = z[:nocca * nvira].reshape(nvira, nocca)
zb = z[nocca * nvira:].reshape(nvirb, noccb)
dmvo[0, i] = reduce(numpy.dot, (orbva, za, orboa.T))
dmvo[1, i] = reduce(numpy.dot, (orbvb, zb, orbob.T))
v1ao = vresp(dmvo)
v1a = _ao2mo.nr_e2(v1ao[0], mo_a,
(nocca, nmo, 0, nocca)).reshape(-1, nvira, nocca)
v1b = _ao2mo.nr_e2(v1ao[1], mo_b,
(noccb, nmo, 0, noccb)).reshape(-1, nvirb, noccb)
for i, z in enumerate(zs):
za = z[:nocca * nvira].reshape(nvira, nocca)
zb = z[nocca * nvira:].reshape(nvirb, noccb)
v1a[i] += numpy.einsum('ai,ai->ai', e_ai_a, za)
v1b[i] += numpy.einsum('ai,ai->ai', e_ai_b, zb)
hx = numpy.hstack((v1a.reshape(nz, -1), v1b.reshape(nz, -1)))
if wfnsym is not None and mol.symmetry:
hx[:, sym_forbid] = 0
return hx
return vind, hdiag
def gen_tdhf_operation(mf, fock_ao=None, singlet=True, wfnsym=None):
'''Generate function to compute
[ A B][X]
[-B -A][Y]
'''
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma = orbsyma % 10
orbsymb = orbsymb % 10
sym_forbida = (orbsyma[occidxa, None] ^ orbsyma[viridxa]) != wfnsym
sym_forbidb = (orbsymb[occidxb, None] ^ orbsymb[viridxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = (mo_energy[0][viridxa, None] - mo_energy[0][occidxa]).T
e_ia_b = (mo_energy[1][viridxb, None] - mo_energy[1][occidxb]).T
e_ia = hdiag = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
hdiag = numpy.hstack((hdiag.ravel(), hdiag.ravel()))
mo_a = numpy.asarray(numpy.hstack((orboa, orbva)), order='F')
mo_b = numpy.asarray(numpy.hstack((orbob, orbvb)), order='F')
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory * .8 - mem_now)
vresp = _gen_uhf_response(mf, hermi=0, max_memory=max_memory)
def vind(xys):
nz = len(xys)
if wfnsym is not None and mol.symmetry:
# shape(nz,2,-1): 2 ~ X,Y
xys = numpy.copy(xys).reshape(nz, 2, -1)
xys[:, :, sym_forbid] = 0
dms = numpy.empty((2, nz, nao, nao)) # 2 ~ alpha,beta
for i in range(nz):
x, y = xys[i].reshape(2, -1)
xa = x[:nocca * nvira].reshape(nocca, nvira)
xb = x[nocca * nvira:].reshape(noccb, nvirb)
ya = y[:nocca * nvira].reshape(nocca, nvira)
yb = y[nocca * nvira:].reshape(noccb, nvirb)
dmx = reduce(numpy.dot, (orboa, xa, orbva.T))
dmy = reduce(numpy.dot, (orbva, ya.T, orboa.T))
dms[0, i] = dmx + dmy # AX + BY
dmx = reduce(numpy.dot, (orbob, xb, orbvb.T))
dmy = reduce(numpy.dot, (orbvb, yb.T, orbob.T))
dms[1, i] = dmx + dmy # AX + BY
v1ao = vresp(dms)
v1avo = _ao2mo.nr_e2(v1ao[0], mo_a, (nocca, nmo, 0, nocca))
v1bvo = _ao2mo.nr_e2(v1ao[1], mo_b, (noccb, nmo, 0, noccb))
v1aov = _ao2mo.nr_e2(v1ao[0], mo_a, (0, nocca, nocca, nmo))
v1bov = _ao2mo.nr_e2(v1ao[1], mo_b, (0, noccb, noccb, nmo))
hx = numpy.empty((nz, 2, nvira * nocca + nvirb * noccb),
dtype=v1avo.dtype)
for i in range(nz):
x, y = xys[i].reshape(2, -1)
hx[i, 0, :nvira * nocca] = v1aov[i].ravel()
hx[i, 0, nvira * nocca:] = v1bov[i].ravel()
hx[i, 0] += e_ia * x # AX
hx[i,
1, :nvira * nocca] = -v1avo[i].reshape(nvira, nocca).T.ravel()
hx[i, 1,
nvira * nocca:] = -v1bvo[i].reshape(nvirb, noccb).T.ravel()
hx[i, 1] -= e_ia * y #-AY
if wfnsym is not None and mol.symmetry:
hx[:, :, sym_forbid] = 0
return hx.reshape(nz, -1)
return vind, hdiag
def gen_tda_operation(mf, fock_ao=None, wfnsym=None):
'''(A+B)x
Kwargs:
wfnsym : int or str
Point group symmetry irrep symbol or ID for excited CIS wavefunction.
'''
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma_in_d2h = numpy.asarray(orbsyma) % 10
orbsymb_in_d2h = numpy.asarray(orbsymb) % 10
sym_forbida = (orbsyma_in_d2h[occidxa, None]
^ orbsyma_in_d2h[viridxa]) != wfnsym
sym_forbidb = (orbsymb_in_d2h[occidxb, None]
^ orbsymb_in_d2h[viridxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = mo_energy[0][viridxa] - mo_energy[0][occidxa, None]
e_ia_b = mo_energy[1][viridxb] - mo_energy[1][occidxb, None]
e_ia = numpy.hstack((e_ia_a.reshape(-1), e_ia_b.reshape(-1)))
hdiag = e_ia
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory * .8 - mem_now)
vresp = mf.gen_response(hermi=0, max_memory=max_memory)
def vind(zs):
zs = numpy.asarray(zs)
if wfnsym is not None and mol.symmetry:
zs = numpy.copy(zs)
zs[:, sym_forbid] = 0
za = zs[:, :nocca * nvira].reshape(-1, nocca, nvira)
zb = zs[:, nocca * nvira:].reshape(-1, noccb, nvirb)
dmova = lib.einsum('xov,po,qv->xpq', za, orboa, orbva.conj())
dmovb = lib.einsum('xov,po,qv->xpq', zb, orbob, orbvb.conj())
v1ao = vresp(numpy.asarray((dmova, dmovb)))
v1a = lib.einsum('xpq,po,qv->xov', v1ao[0], orboa.conj(), orbva)
v1b = lib.einsum('xpq,po,qv->xov', v1ao[1], orbob.conj(), orbvb)
v1a += numpy.einsum('xia,ia->xia', za, e_ia_a)
v1b += numpy.einsum('xia,ia->xia', zb, e_ia_b)
nz = zs.shape[0]
hx = numpy.hstack((v1a.reshape(nz, -1), v1b.reshape(nz, -1)))
if wfnsym is not None and mol.symmetry:
hx[:, sym_forbid] = 0
return hx
return vind, hdiag
def gen_g_hop_uhf(mf,
mo_coeff,
mo_occ,
fock_ao=None,
h1e=None,
with_symmetry=True):
mol = mf.mol
mo_coeff0 = mo_coeff
if getattr(mf, '_scf', None) and mf._scf.mol != mol:
#TODO: construct vind with dual-basis treatment, (see also JCP, 118, 9497)
mo_coeff = (addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[0], mol),
addons.project_mo_nr2nr(mf._scf.mol, mo_coeff[1], mol))
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if with_symmetry and mol.symmetry:
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
sym_forbida = orbsyma[viridxa, None] != orbsyma[occidxa]
sym_forbidb = orbsymb[viridxb, None] != orbsymb[occidxb]
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
if fock_ao is None:
if getattr(mf, '_scf', None) and mf._scf.mol != mol:
h1e = mf.get_hcore(mol)
dm0 = mf.make_rdm1(mo_coeff, mo_occ)
fock_ao = mf.get_fock(h1e, dm=dm0)
focka = reduce(numpy.dot,
(mo_coeff[0].conj().T, fock_ao[0], mo_coeff[0]))
fockb = reduce(numpy.dot,
(mo_coeff[1].conj().T, fock_ao[1], mo_coeff[1]))
else:
focka = reduce(numpy.dot,
(mo_coeff0[0].conj().T, fock_ao[0], mo_coeff0[0]))
fockb = reduce(numpy.dot,
(mo_coeff0[1].conj().T, fock_ao[1], mo_coeff0[1]))
fooa = focka[occidxa[:, None], occidxa]
fvva = focka[viridxa[:, None], viridxa]
foob = fockb[occidxb[:, None], occidxb]
fvvb = fockb[viridxb[:, None], viridxb]
g = numpy.hstack((focka[viridxa[:, None],
occidxa].ravel(), fockb[viridxb[:, None],
occidxb].ravel()))
h_diaga = fvva.diagonal().real[:, None] - fooa.diagonal().real
h_diagb = fvvb.diagonal().real[:, None] - foob.diagonal().real
h_diag = numpy.hstack((h_diaga.reshape(-1), h_diagb.reshape(-1)))
if with_symmetry and mol.symmetry:
g[sym_forbid] = 0
h_diag[sym_forbid] = 0
vind = _gen_uhf_response(mf, mo_coeff, mo_occ, hermi=1)
def h_op(x):
if with_symmetry and mol.symmetry:
x = x.copy()
x[sym_forbid] = 0
x1a = x[:nvira * nocca].reshape(nvira, nocca)
x1b = x[nvira * nocca:].reshape(nvirb, noccb)
x2a = numpy.einsum('pr,rq->pq', fvva, x1a)
x2a -= numpy.einsum('sq,ps->pq', fooa, x1a)
x2b = numpy.einsum('pr,rq->pq', fvvb, x1b)
x2b -= numpy.einsum('sq,ps->pq', foob, x1b)
d1a = reduce(numpy.dot, (orbva, x1a, orboa.conj().T))
d1b = reduce(numpy.dot, (orbvb, x1b, orbob.conj().T))
dm1 = numpy.array((d1a + d1a.conj().T, d1b + d1b.conj().T))
v1 = vind(dm1)
x2a += reduce(numpy.dot, (orbva.conj().T, v1[0], orboa))
x2b += reduce(numpy.dot, (orbvb.conj().T, v1[1], orbob))
x2 = numpy.hstack((x2a.ravel(), x2b.ravel()))
if with_symmetry and mol.symmetry:
x2[sym_forbid] = 0
return x2
return g, h_op, h_diag
def gen_tdhf_operation(mf, fock_ao=None, singlet=True, wfnsym=None):
'''Generate function to compute
[ A B][X]
[-B -A][Y]
'''
mol = mf.mol
mo_coeff = mf.mo_coeff
assert (mo_coeff[0].dtype == numpy.double)
mo_energy = mf.mo_energy
mo_occ = mf.mo_occ
nao, nmo = mo_coeff[0].shape
occidxa = numpy.where(mo_occ[0] > 0)[0]
occidxb = numpy.where(mo_occ[1] > 0)[0]
viridxa = numpy.where(mo_occ[0] == 0)[0]
viridxb = numpy.where(mo_occ[1] == 0)[0]
nocca = len(occidxa)
noccb = len(occidxb)
nvira = len(viridxa)
nvirb = len(viridxb)
orboa = mo_coeff[0][:, occidxa]
orbob = mo_coeff[1][:, occidxb]
orbva = mo_coeff[0][:, viridxa]
orbvb = mo_coeff[1][:, viridxb]
if wfnsym is not None and mol.symmetry:
if isinstance(wfnsym, str):
wfnsym = symm.irrep_name2id(mol.groupname, wfnsym)
orbsyma, orbsymb = uhf_symm.get_orbsym(mol, mo_coeff)
wfnsym = wfnsym % 10 # convert to D2h subgroup
orbsyma_in_d2h = numpy.asarray(orbsyma) % 10
orbsymb_in_d2h = numpy.asarray(orbsymb) % 10
sym_forbida = (orbsyma_in_d2h[occidxa, None]
^ orbsyma_in_d2h[viridxa]) != wfnsym
sym_forbidb = (orbsymb_in_d2h[occidxb, None]
^ orbsymb_in_d2h[viridxb]) != wfnsym
sym_forbid = numpy.hstack((sym_forbida.ravel(), sym_forbidb.ravel()))
e_ia_a = mo_energy[0][viridxa] - mo_energy[0][occidxa, None]
e_ia_b = mo_energy[1][viridxb] - mo_energy[1][occidxb, None]
e_ia = hdiag = numpy.hstack((e_ia_a.ravel(), e_ia_b.ravel()))
if wfnsym is not None and mol.symmetry:
hdiag[sym_forbid] = 0
hdiag = numpy.hstack((hdiag, -hdiag))
mem_now = lib.current_memory()[0]
max_memory = max(2000, mf.max_memory * .8 - mem_now)
vresp = mf.gen_response(hermi=0, max_memory=max_memory)
def vind(xys):
nz = len(xys)
xys = numpy.asarray(xys).reshape(nz, 2, -1)
if wfnsym is not None and mol.symmetry:
# shape(nz,2,-1): 2 ~ X,Y
xys = numpy.copy(xys)
xys[:, :, sym_forbid] = 0
xs, ys = xys.transpose(1, 0, 2)
xa = xs[:, :nocca * nvira].reshape(nz, nocca, nvira)
xb = xs[:, nocca * nvira:].reshape(nz, noccb, nvirb)
ya = ys[:, :nocca * nvira].reshape(nz, nocca, nvira)
yb = ys[:, nocca * nvira:].reshape(nz, noccb, nvirb)
# dms = AX + BY
dmsa = lib.einsum('xov,po,qv->xpq', xa, orboa, orbva.conj())
dmsa += lib.einsum('xov,pv,qo->xpq', ya, orbva, orboa.conj())
dmsb = lib.einsum('xov,po,qv->xpq', xb, orbob, orbvb.conj())
dmsb += lib.einsum('xov,pv,qo->xpq', yb, orbvb, orbob.conj())
v1ao = vresp(numpy.asarray((dmsa, dmsb)))
v1aov = lib.einsum('xpq,po,qv->xov', v1ao[0], orboa.conj(), orbva)
v1bov = lib.einsum('xpq,po,qv->xov', v1ao[1], orbob.conj(), orbvb)
v1avo = lib.einsum('xpq,pv,qo->xov', v1ao[0], orbva.conj(), orboa)
v1bvo = lib.einsum('xpq,pv,qo->xov', v1ao[1], orbvb.conj(), orbob)
v1ov = xs * e_ia # AX
v1vo = ys * e_ia # AY
v1ov[:, :nocca * nvira] += v1aov.reshape(nz, -1)
v1vo[:, :nocca * nvira] += v1avo.reshape(nz, -1)
v1ov[:, nocca * nvira:] += v1bov.reshape(nz, -1)
v1vo[:, nocca * nvira:] += v1bvo.reshape(nz, -1)
if wfnsym is not None and mol.symmetry:
v1ov[:, sym_forbid] = 0
v1vo[:, sym_forbid] = 0
hx = numpy.hstack((v1ov, -v1vo))
return hx
return vind, hdiag
