def test_init(self):
from pyscf import dft
from pyscf import x2c
mol_r = mol
mol_u = gto.M(atom='Li', spin=1, verbose=0)
mol_r1 = gto.M(atom='H', spin=1, verbose=0)
sym_mol_r = molsym
sym_mol_u = gto.M(atom='Li', spin=1, symmetry=1, verbose=0)
sym_mol_r1 = gto.M(atom='H', spin=1, symmetry=1, verbose=0)
self.assertTrue(isinstance(scf.RKS(mol_r), dft.rks.RKS))
self.assertTrue(isinstance(scf.RKS(mol_u), dft.roks.ROKS))
self.assertTrue(isinstance(scf.UKS(mol_r), dft.uks.UKS))
self.assertTrue(isinstance(scf.ROKS(mol_r), dft.roks.ROKS))
self.assertTrue(isinstance(scf.GKS(mol_r), dft.gks.GKS))
self.assertTrue(isinstance(scf.KS(mol_r), dft.rks.RKS))
self.assertTrue(isinstance(scf.KS(mol_u), dft.uks.UKS))
self.assertTrue(isinstance(scf.RHF(mol_r), scf.hf.RHF))
self.assertTrue(isinstance(scf.RHF(mol_u), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.RHF(mol_r1), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.UHF(mol_r), scf.uhf.UHF))
self.assertTrue(isinstance(scf.UHF(mol_u), scf.uhf.UHF))
self.assertTrue(isinstance(scf.UHF(mol_r1), scf.uhf.UHF))
self.assertTrue(isinstance(scf.ROHF(mol_r), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.ROHF(mol_u), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.ROHF(mol_r1), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.HF(mol_r), scf.hf.RHF))
self.assertTrue(isinstance(scf.HF(mol_u), scf.uhf.UHF))
self.assertTrue(isinstance(scf.HF(mol_r1), scf.rohf.ROHF))
self.assertTrue(isinstance(scf.GHF(mol_r), scf.ghf.GHF))
self.assertTrue(isinstance(scf.GHF(mol_u), scf.ghf.GHF))
self.assertTrue(isinstance(scf.GHF(mol_r1), scf.ghf.GHF))
self.assertTrue(not isinstance(scf.DHF(mol_r), scf.dhf.RHF))
self.assertTrue(isinstance(scf.DHF(mol_u), scf.dhf.UHF))
self.assertTrue(isinstance(scf.DHF(mol_r1), scf.dhf.HF1e))
self.assertTrue(isinstance(scf.RHF(sym_mol_r), scf.hf_symm.RHF))
self.assertTrue(isinstance(scf.RHF(sym_mol_u), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.RHF(sym_mol_r1), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.UHF(sym_mol_r), scf.uhf_symm.UHF))
self.assertTrue(isinstance(scf.UHF(sym_mol_u), scf.uhf_symm.UHF))
self.assertTrue(isinstance(scf.UHF(sym_mol_r1), scf.uhf_symm.UHF))
self.assertTrue(isinstance(scf.ROHF(sym_mol_r), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.ROHF(sym_mol_u), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.ROHF(sym_mol_r1), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.HF(sym_mol_r), scf.hf_symm.RHF))
self.assertTrue(isinstance(scf.HF(sym_mol_u), scf.uhf_symm.UHF))
self.assertTrue(isinstance(scf.HF(sym_mol_r1), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.GHF(sym_mol_r), scf.ghf_symm.GHF))
self.assertTrue(isinstance(scf.GHF(sym_mol_u), scf.ghf_symm.GHF))
self.assertTrue(isinstance(scf.GHF(sym_mol_r1), scf.ghf_symm.GHF))
self.assertTrue(isinstance(scf.X2C(mol_r), x2c.x2c.UHF))
self.assertTrue(isinstance(scf.sfx2c1e(scf.HF(mol_r)), scf.rhf.RHF))
self.assertTrue(isinstance(scf.sfx2c1e(scf.HF(mol_u)), scf.uhf.UHF))
self.assertTrue(isinstance(scf.sfx2c1e(scf.HF(mol_r1)), scf.rohf.ROHF))
self.assertTrue(
isinstance(scf.sfx2c1e(scf.HF(sym_mol_r)), scf.rhf_symm.RHF))
self.assertTrue(
isinstance(scf.sfx2c1e(scf.HF(sym_mol_u)), scf.uhf_symm.UHF))
self.assertTrue(
isinstance(scf.sfx2c1e(scf.HF(sym_mol_r1)), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.density_fit(scf.HF(mol_r)),
scf.rhf.RHF))
self.assertTrue(isinstance(scf.density_fit(scf.HF(mol_u)),
scf.uhf.UHF))
self.assertTrue(
isinstance(scf.density_fit(scf.HF(mol_r1)), scf.rohf.ROHF))
self.assertTrue(
isinstance(scf.density_fit(scf.HF(sym_mol_r)), scf.rhf_symm.RHF))
self.assertTrue(
isinstance(scf.density_fit(scf.HF(sym_mol_u)), scf.uhf_symm.UHF))
self.assertTrue(
isinstance(scf.density_fit(scf.HF(sym_mol_r1)), scf.hf_symm.ROHF))
self.assertTrue(isinstance(scf.newton(scf.HF(mol_r)), scf.rhf.RHF))
self.assertTrue(isinstance(scf.newton(scf.HF(mol_u)), scf.uhf.UHF))
self.assertTrue(isinstance(scf.newton(scf.HF(mol_r1)), scf.rohf.ROHF))
self.assertTrue(
isinstance(scf.newton(scf.HF(sym_mol_r)), scf.rhf_symm.RHF))
self.assertTrue(
isinstance(scf.newton(scf.HF(sym_mol_u)), scf.uhf_symm.UHF))
self.assertTrue(
isinstance(scf.newton(scf.HF(sym_mol_r1)), scf.hf_symm.ROHF))
H 0.000000 -1.246998 15.695371
''',
unit='Angstrom',
basis='ccpvtz',
max_memory=10000,
)
#
# By default optimal auxiliary basis (if possible) or even-tempered gaussian
# functions are used fitting basis. You can assign with_df.auxbasis to change
# the change the fitting basis.
#
mol.spin = 0
mol.charge = 0
mol.build(0, 0)
mf = scf.RKS(mol)
mf.xc = 'cam-b3lyp'
energy = mf.kernel()
mos = mf.mo_energy
print(mos)
print('mo occ: ', mf.mo_occ)
print('total num of electrons: ', sum(mf.mo_occ))
homoIndex = int(sum(mf.mo_occ) / 2 - 1)
lumoIndex = homoIndex + 1
bandGap = (mos[lumoIndex] - mos[homoIndex]) * 27.2114
print('index: ', homoIndex, lumoIndex)
print('h**o E:', mos[homoIndex])
print('lumo E:', mos[lumoIndex])
print('band Gap (eV):', bandGap)
def gen_scf_obj(mol, scf_method, **kwargs):
"""Generates an scf object setting all relevant parameters for use later in
embedding"""
if 'unrestricted' in kwargs and kwargs.get('unrestricted'):
if 'hf' in scf_method:
scf_obj = scf.UHF(mol)
else:
scf_obj = scf.UKS(mol)
scf_obj.xc = scf_method
elif mol.spin != 0:
if 'hf' in scf_method:
scf_obj = scf.ROHF(mol)
else:
scf_obj = scf.ROKS(mol)
scf_obj.xc = scf_method
else:
if 'hf' in scf_method:
scf_obj = scf.RHF(mol)
else:
scf_obj = scf.RKS(mol)
scf_obj.xc = scf_method
if 'diis_num' in kwargs:
if kwargs.get('diis_num') == 0:
scf_obj.DIIS = None
if kwargs.get('diis_num') == 1:
scf_obj.DIIS = scf.CDIIS
if kwargs.get('diis_num') == 2:
scf_obj.DIIS = scf.EDIIS
if kwargs.get('diis_num') == 3:
scf_obj.DIIS = scf.ADIIS
if 'grid_level' in kwargs:
grids = dft.gen_grid.Grids(mol)
grids.level = kwargs.pop('grid_level')
grids.build()
scf_obj.grids = grids
if 'dynamic_level_shift' in kwargs and kwargs.get('dynamic_level_shift'):
if 'level_shift_factor' in kwargs:
lev_shift_factor = kwargs.pop('level_shift_factor')
scf.addons.dynamic_level_shift_(scf_obj, lev_shift_factor)
else:
scf.addons.dynamic_level_shift_(scf_obj)
if 'newton' in kwargs and kwargs.pop('newton'):
scf_obj = scf.newton(scf_obj)
if 'fast_newton' in kwargs and kwargs.pop('fast_newton'):
scf_obj.use_fast_newton = True
if 'frac_occ' in kwargs and kwargs.get('frac_occ'):
scf_obj = scf.addons.frac_occ(mf)
if 'remove_linear_dep' in kwargs and kwargs.get('remove_linear_dep'):
scf_obj = scf_obj.apply(scf.addons.remove_linear_dep)
if 'density_fitting' in kwargs and kwargs.get('density_fitting'):
scf_obj = scf_obj.density_fit()
if 'excited' in kwargs:
scf_obj.excited = kwargs['excited']
#Setup excited object.
pass
for key in kwargs:
setattr(scf_obj, key, kwargs[key])
return scf_obj
import os
import matplotlib.pyplot as plt
# Some input parameters, where obviously looping over dists is possible
basisname = "cc-pvdz" # reference basis set
dist = 0.7608986485 # equilibrium distance at this level of theory, verified!
coord = 'H 0 0 0; H 0 0 {0}'.format(str(dist))
verb = 0 # integer verbosity flag
step = 0.001 # should be adapted and so on but whatever
# Do a mean-field KS-DFT calculation at dist
mol = gto.Mole(
atom=coord, basis=basisname, charge=0,
spin=0) # build a molecule, neutral species, spin is N\alpha-N\beta here
mol.build()
mf = scf.RKS(mol) # run DFT calculation as reference
mf.verbose = verb # reduce output
mf.xc = 'lda,vwn' # we select an approximate xc functional, many options available e.g. 'pbe,pbe' or 'b3lyp'
edft = mf.kernel() # get DFT energy
nelec = mol.nelec # number of electrons
print('The number of electrons is now {0}'.format(nelec))
print(' At a distance R = {0} angstrom:'.format(dist))
print(' DFT energy: {0} a.u.\n'.format(edft)) # total energies
gradients = grad.RKS(mf).kernel(
) # We calculate analytical nuclear gradients, we choose the level of theory of the gradients
grad_atom_1 = gradients[0][2]
grad_atom_2 = gradients[1][2]
print(
' In the cartesian frame, gradient for atom 1 is {0}, gradient for atom 2 is {1}'
.format(grad_atom_1, grad_atom_2))
totgrad = -1 * grad_atom_1 + grad_atom_2
H 22.973000 23.598000 24.457000 H 23.982000 21.424000 25.481000 H 26.234000 21.645000 26.532000 H 27.292000 23.851000 26.796000 """ mol.basis = "6-31G*" mol.build() pe_options = cppe.PeOptions() pe_options.do_diis = True pe_options.potfile = "nilered_in_water.pot" pe = pol_embed.PolEmbed(mol, pe_options) pe.verbose = 4 lib.num_threads(32) mf = solvent.PE(scf.RKS(mol), pe) mf.xc = "camb3lyp" mf._numint.libxc = xcfun mf.conv_tol = 1e-8 mf.verbose = 4 mf.kernel() print(mf._pol_embed.cppe_state.summary_string) td = TDA(mf) td.verbose = 5 td.conv_tol = 1e-7 td.triplet = False td.singlet = True td.nstates = 3
from __future__ import print_function, division
import unittest, numpy as np
from pyscf import gto, tddft, scf
from pyscf.nao import tddft_tem
from pyscf.nao import polariz_inter_ave, polariz_nonin_ave
mol = gto.M(
verbose=1,
atom=''' H -0.5 -0.5 -0.5; H 0.5 0.5 0.5''',
basis='cc-pvdz',
)
gto_mf = scf.RKS(mol)
gto_mf.kernel()
gto_td = tddft.TDDFT(gto_mf)
gto_td.nstates = 9
gto_td.kernel()
nao_td = tddft_tem(mf=gto_mf, gto=mol)
class KnowValues(unittest.TestCase):
def test_tddft_tem(self):
""" Interacting case """
p_iter = -nao_td.get_spectrum_inter().imag
data = np.array([nao_td.freq.real * 27.2114, p_iter])
np.savetxt('hydrogen.tddft_tem_lda.omega.inter.pav.txt',
data.T,
fmt=['%f', '%f'])
gobj.so_eff_charge = True gobj.kernel() # # Attribute gauge_orig controls whether to use GIAO. GIAO is used by default. # gobj.gauge_orig = mol.atom_coord(1) # on N atom gobj.dia_soc2e = False gobj.para_soc2e = True gobj.so_eff_charge = False gobj.kernel() # # In pure DFT (LDA, GGA), CPSCF has no effects. Setting cphf=False can switch # off CPSCF. # mf = dft.UKS(mol).set(xc='bp86').run() gobj = gtensor.uks.GTensor(mf).set(verbose=4) gobj.cphf = False gobj.gauge_orig = (0, 0, 0) gobj.kernel() # # Only UHF and UKS are supported in g-tensor module. ROHF and ROKS need to be # transfered to UHF or UKS before calling g-tensor methods. # mf = scf.RKS(mol).run() mf = scf.convert_to_uhf(mf) gobj = gtensor.uhf.GTensor(mf).set(verbose=4) print(gobj.kernel())
def do_scf(mol, func, dm0=None):
mf = scf.RKS(mol)
mf.xc = func
mf.kernel(dm0=dm0)
dm = mf.make_rdm1()
return (mf, dm)
import sys
import os
import matplotlib.pyplot as plt
# Some input parameters, where obviously looping over dists is possible
basisname = "cc-pvdz" # reference basis set
dist = 0.7608986485 # equilibrium distance at this level of theory, verified!
coord = 'H 0 0 0; H 0 0 {0}'.format(str(dist))
verb = 0 # integer verbosity flag
# Do a mean-field KS-DFT calculation at dist
mol = gto.Mole(
atom=coord, basis=basisname, charge=0,
spin=0) # build a molecule, neutral species, spin is N\alpha-N\beta here
mol.build()
mf = scf.RKS(mol) # run DFT calculation as reference
mf.verbose = verb # reduce output
mf.xc = 'lda,vwn' # we select an approximate xc functional, many options available e.g. 'pbe,pbe' or 'b3lyp'
edft = mf.kernel() # get DFT energy
nelec = mol.nelec # number of electrons
print('The number of electrons is now {0}'.format(nelec))
print(' At a distance R = {0} angstrom:'.format(dist))
print(' DFT energy: {0} a.u.\n'.format(edft)) # total energies
mol_eq = optimize(mf)
#print(mol_eq.atom_coords())
dist = (mol_eq.atom_coords()[0][2] +
mol_eq.atom_coords()[1][2]) * 0.529177 # bohr to angstrom conversion
mf = scf.RKS(mol_eq).run(xc='lda,vwn', verbose=0)
print(' At a distance R = {0} angstrom:'.format(dist))
print('DFT energy is now: {0} a.u.\n'.format(mf.e_tot))
