def from_sa_mcscf(mc,
fname,
state=None,
cas_natorb=False,
cas_mo_energy=False,
**kwargs):
if state is None:
return from_mcscf(mc, fname, cas_natorb=cas_natorb, **kwargs)
casdm1 = mc.fcisolver.states_make_rdm1(mc.ci, mc.ncas, mc.nelecas)[state]
mo_coeff, mo_ci, mo_energy = mc.canonicalize(ci=mc.ci[state],
cas_natorb=cas_natorb,
casdm1=casdm1)
if not cas_mo_energy:
mo_energy[mc.ncore:][:mc.ncas] = 0.0
# TODO: cleaner interface. Probably invent "state_make_?dm*" functions ("state" singular)
# and apply them also to the StateAverageMCSCFSolver instance
mo_occ = np.zeros_like(mo_energy)
mo_occ[:mc.ncore] = 2.0
ci = mc.ci
ci[state] = mo_ci
mo_occ[mc.ncore:][:mc.ncas] = mc.fcisolver.states_make_rdm1(
ci, mc.ncas, mc.nelecas)[state].diagonal()
return from_mo(mc.mol,
fname,
mo_coeff,
occ=mo_occ,
ene=mo_energy,
**kwargs)
# # Load MF orbitals # chkname = "_chk/pp_dianion_dz_b3lyp.chk" mol = chkfile.load_mol(chkname) mol.verbose = 5 mf = dft.RKS(mol) mf.__dict__.update(chkfile.load(chkname, "scf")) # # SA-MCSCF # nelecas, ncas = (4, 4) n_states = 3 weights = np.ones(n_states) / n_states mc = mcscf.CASSCF(mf, ncas, nelecas).state_average_(weights) mc.fix_spin(ss=0) mc.natorb = True mc.chkfile = "_chk/pp_dianion_dz_cas_4e_4o.chk" cas_list = [142, 143, 150, 151] mo = mcscf.sort_mo(mc, mf.mo_coeff, cas_list) mc.mc1step(mo) # # Analysis and processing # mc.analyze() molden.from_mcscf(mc, "_molden/pp_dianion_dz_cas_4e_4o.molden") molden.from_mo(mol, "_molden/pp_dianion_dz_cas_4e_4o_alt.molden", mc.mo_coeff)
mf.chkfile = "_chk/pp_anion_pt_chg_dz_b3lyp.chk" mf.kernel() # mf.analyze() # # Dump orbitals # molden.dump_scf(mf, "_molden/pp_anion_pt_chg_dz_b3lyp.molden") # # SA-MCSCF # nelecas, ncas = (4, 4) n_states = 3 weights = np.ones(n_states) / n_states mc = mcscf.CASSCF(mf, ncas, nelecas).state_average_(weights) mc.fix_spin(ss=0) mc.natorb = True mc.chkfile = "_chk/pp_anion_pt_chg_dz_cas_4e_4o.chk" cas_list = [118, 119, 120, 121] mo = mcscf.sort_mo(mc, mf.mo_coeff, cas_list) mc.mc1step(mo) # # Analysis and processing # mc.analyze() molden.from_mcscf(mc, "_molden/pp_anion_pt_chg_dz_cas.molden") molden.from_mo(mol, "_molden/pp_anion_pt_chg_dz_cas_alt.molden", mc.mo_coeff)
gsmo = np.load(gsmofile)
mc = mcpdft.CASSCF(mf, transl_type + fnal, ncas, nelecas, grids_level=3)
mo = mcscf.project_init_guess(mc, gsmo, prev_mol=gsmol)
molden.from_mo(mol, 'check_projection.molden', mo)
mc.kernel(mo)
mc = mc.as_scanner()
else:
mc = mcpdft.CASSCF(mf, transl_type + fnal, ncas, nelecas,
grids_level=3).run().as_scanner()
mc0 = mcpdft.CASSCF(mf, otfnal0, ncas, nelecas,
grids_level=3).run().as_scanner()
mc1 = mcpdft.CASSCF(mf, otfnal1, ncas, nelecas,
grids_level=3).run().as_scanner()
mc2 = mcpdft.CASSCF(mf, otfnal2, ncas, nelecas,
grids_level=3).run().as_scanner()
molden.from_mcscf(mc0, moldenfile)
np.save(mofile, mc.mo_coeff)
# Do MCSCF scan forwards
table = np.zeros((HHrange.size, 9))
table[:, 0] = HHrange
for ix, HHdist in enumerate(HHrange):
geom = 'H 0 0 0; H 0 0 {:.6f}'.format(HHdist)
efci = fci(geom)
epdft = mc(geom)
mc0.mo_coeff = mc1.mo_coeff = mc2.mo_coeff = mc.mo_coeff
molden.from_mo(mol, logfile[:-3] + '{:.2f}.molden'.format(HHdist),
mc.mo_coeff)
epdft0 = mc0(geom)
epdft1 = mc1(geom)
epdft2 = mc2(geom)
# Load MF orbitals # chkname = "_chk/pp_neutral_dz_b3lyp.chk" mol = chkfile.load_mol(chkname) mol.verbose = 5 mf = dft.RKS(mol) mf.__dict__.update(chkfile.load(chkname, "scf")) # # SA-MCSCF # nelecas, ncas = (4, 4) n_states = 3 weights = np.ones(n_states) / n_states mc = mcscf.CASSCF(mf, ncas, nelecas).state_average_(weights) mc.fix_spin(ss=0) mc.natorb = True mc.chkfile = "_chk/pp_neutral_dz_cas_4e_4o.chk" cas_list = [148, 149, 150, 151] mo = mcscf.sort_mo(mc, mf.mo_coeff, cas_list) mc.mc1step(mo) # # Analysis and processing # mc.analyze() molden.from_mo(mol, "_molden/pp_neutral_dz_cas_4e_4o_alt.molden", mc.mo_coeff) molden.from_mcscf(mc, "_molden/pp_neutral_dz_cas_4e_4o.molden")