def test_157_bse_h2o_rhf_cis(self):
""" This """
mol = gto.M(verbose=1,
atom='O 0 0 0; H 0 0.489 1.074; H 0 0.489 -1.074',
basis='cc-pvdz')
gto_mf = scf.RHF(mol)
gto_mf.kernel()
gto_td = tddft.TDDFT(gto_mf)
gto_td.nstates = 190
gto_td.kernel()
omegas = np.arange(0.0, 2.0, 0.01) + 1j * 0.03
p_ave = -polariz_freq_osc_strength(
gto_td.e, gto_td.oscillator_strength(), omegas).imag
data = np.array([omegas.real * HARTREE2EV, p_ave])
np.savetxt('test_0157_bse_h2o_rhf_cis_pyscf.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0157_bse_h2o_rhf_cis_pyscf.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=1e-6, rtol=1e-3))
nao_td = bse_iter(mf=gto_mf, gto=mol, verbosity=0, xc_code='CIS')
polariz = -nao_td.comp_polariz_inter_ave(omegas).imag
data = np.array([omegas.real * HARTREE2EV, polariz])
np.savetxt('test_0157_bse_h2o_rhf_cis_nao.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0157_bse_h2o_rhf_cis_nao.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=5e-5, rtol=5e-2),
msg="{}".format(
abs(data_ref - data).sum() / data.size))
def test_152_bse_h2b_uks_pz(self):
""" This """
mol = gto.M(verbose=1,
atom='B 0 0 0; H 0 0.489 1.074; H 0 0.489 -1.074',
basis='cc-pvdz',
spin=3)
gto_mf = scf.UKS(mol)
gto_mf.kernel()
gto_td = tddft.TDDFT(gto_mf)
gto_td.nstates = 190
gto_td.kernel()
omegas = np.arange(0.0, 2.0, 0.01) + 1j * 0.03
p_ave = -polariz_freq_osc_strength(
gto_td.e, gto_td.oscillator_strength(), omegas).imag
data = np.array([omegas.real * HARTREE2EV, p_ave])
np.savetxt('test_0152_bse_h2b_uks_pz_pyscf.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0152_bse_h2b_uks_pz_pyscf.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=1e-6, rtol=1e-3))
nao_td = bse_iter(mf=gto_mf, gto=mol, verbosity=0)
polariz = -nao_td.comp_polariz_inter_ave(omegas).imag
data = np.array([omegas.real * HARTREE2EV, polariz])
np.savetxt('test_0152_bse_h2b_uks_pz_nao.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0152_bse_h2b_uks_pz_nao.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=1e-6, rtol=1e-3))
def test_tddft_b3lyp(self):
mf = dft.RKS(mol)
mf.xc = 'b3lyp'
mf.grids.prune = False
mf.scf()
td = tddft.TDDFT(mf).run(nstates=3)
tdg = rks_grad.Gradients(td)
g1 = tdg.kernel(state=2)
self.assertAlmostEqual(g1[0,2], -1.55778110e-01, 8)
def test_tddft_lda(self):
mf = dft.RKS(mol)
mf.xc = 'LDA'
mf.grids.prune = False
mf.scf()
td = tddft.TDDFT(mf).run(nstates=3)
tdg = rks_grad.Gradients(td)
g1 = tdg.kernel(state=2)
self.assertAlmostEqual(g1[0,2], -1.31315477e-01, 9)
def test_0147_bse_h2o_rks_pz(self):
""" Interacting case """
mol = gto.M(
verbose=0,
atom='O 0 0 0;H 0 0.489 1.074;H 0 0.489 -1.074',
basis='cc-pvdz',
)
gto_hf = scf.RKS(mol)
gto_hf.kernel()
gto_td = tddft.TDDFT(gto_hf)
gto_td.nstates = 95
gto_td.kernel()
omegas = np.arange(0.0, 2.0, 0.01) + 1j * 0.03
p_ave = -polariz_freq_osc_strength(
gto_td.e, gto_td.oscillator_strength(), omegas).imag
data = np.array([omegas.real * HARTREE2EV, p_ave])
np.savetxt('test_0147_bse_h2o_rks_pz_pyscf.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0147_bse_h2o_rks_pz_pyscf.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=1e-6, rtol=1e-3))
nao_td = bse_iter(
mf=gto_hf,
gto=mol,
verbosity=0,
xc_code='LDA',
)
p_iter = -nao_td.comp_polariz_inter_ave(omegas).imag
data = np.array([omegas.real * HARTREE2EV, p_iter])
np.savetxt('test_0147_bse_h2o_rks_pz_nao.txt',
data.T,
fmt=['%f', '%f'])
data_ref = np.loadtxt('test_0147_bse_h2o_rks_pz_nao.txt-ref').T
self.assertTrue(np.allclose(data_ref, data, atol=1e-6, rtol=1e-3))
from __future__ import print_function, division
import unittest, numpy as np
from pyscf import gto, tddft, scf
from pyscf.nao import bse_iter
from pyscf.nao import polariz_inter_ave, polariz_nonin_ave
mol = gto.M( verbose = 0, atom = '''H 0 0 0; H 0.17 0.7 0.587''', basis = 'cc-pvdz',)
gto_mf = scf.RHF(mol)
gto_mf.kernel()
#print(gto_mf.mo_energy)
gto_td = tddft.TDDFT(gto_mf)
gto_td.nstates = 9
gto_td.singlet = True # False
gto_td.kernel()
nao_td = bse_iter(mf=gto_mf, gto=mol, verbosity=0)
class KnowValues(unittest.TestCase):
#def test_bse_iter_vs_tdhf_pyscf(self):
# """ Interacting case test """
# cdip = np.random.rand(nao_td.norbs,nao_td.norbs)+1j*np.random.rand(nao_td.norbs,nao_td.norbs)
# nao_td.apply_l0_exp(cdip, comega=0.2+1j*0.01)
def test_tddft_gto_vs_nao_inter(self):
""" Interacting case """
omegas = np.linspace(0.0,2.0,450)+1j*0.04
p_ave = -polariz_inter_ave(gto_mf, mol, gto_td, omegas).imag
data = np.array([omegas.real*27.2114, p_ave])
np.savetxt('hydrogen.tdhf.omega.inter.pav.txt', data.T, fmt=['%f','%f'])
#
# Author: Qiming Sun <*****@*****.**>
#
'''
A simple example to run TDDFT calculation.
'''
from pyscf import gto, scf, dft, tddft
mol = gto.Mole()
mol.build(
atom='H 0 0 0; F 0 0 1.1', # in Angstrom
basis='631g',
symmetry=True,
)
mf = dft.RKS(mol)
mf.xc = 'b3lyp'
mf.kernel()
mytd = tddft.TDDFT(mf)
#mytd.nstates = 10
mytd.kernel()
mytd.analyze()
# PySCF-1.6.1 and newer supports the .TDDFT method to create a TDDFT
# object after importing tdscf module.
from pyscf import tddft
mytd = mf.TDDFT().run()
mytd = scf.RHF(mol).run().TDHF().run()
sys.argv = [sys.argv[0]]
# -----------------------
# PYSCF
# -----------------------
mol = gto.M(atom=atomic_coords,
basis=basis_set,
spin=spin,
charge=charge,
verbose=5)
my_dft = dft.RKS(mol)
my_dft.xc = functional
if density_fit:
my_dft = my_dft.density_fit()
my_dft.with_df.auxbasis = aux_basis_set
my_dft.run()
my_tddft = tddft.TDDFT(my_dft)
# my_tddft.nstates = 10
my_tddft.kernel()
excitation_energies = (my_tddft.e * 27.2114).tolist()
properties = {
"excitationEnergies": excitation_energies,
}
stringified_properties = json.dumps(properties)
print('atoms+bits properties:\n~{}~'.format(stringified_properties))
can be set in TDDFT. ''' import copy from pyscf import gto, dft, tddft mol = gto.M(atom='N 0 0 0; N 0 0 1', basis='6-31g*') mf = dft.RKS(mol).run(xc='pbe0') # # A common change for TDDFT is to use different XC functional library. For # example, PBE0 is not supported by the default XC library (libxc) in the TDDFT # calculation. Changing to xcfun library for TDDFT can solve this problem # mf._numint.libxc = dft.xcfun td = tddft.TDDFT(mf) print(td.kernel()[0] * 27.2114) # # Overwriting the relevant attributes of the ground state mf object, # the TDDFT calculations can be run with different XC, grids. # mf.xc = 'lda,vwn' mf.grids.set(level=2).kernel(with_non0tab=True) td = tddft.TDDFT(mf) print(td.kernel()[0] * 27.2114) # # Overwriting the ground state SCF object is unsafe. A better solution is to # create a new fake SCF object to hold different XC, grids parameters. #
TDDFT analytical nuclear gradients.
'''
from pyscf import gto, scf, dft, tddft
mol = gto.M(atom=[['O', 0., 0., 0], ['H', 0., -0.757, 0.587],
['H', 0., 0.757, 0.587]],
basis='ccpvdz')
mf = scf.RHF(mol).run()
postmf = tddft.TDHF(mf).run()
g = postmf.nuc_grad_method()
g.kernel(state=1)
mf = dft.RKS(mol).x2c().set(xc='pbe0').run()
# Switch to xcfun because 3rd order GGA functional derivative is not
# available in libxc
mf._numint.libxc = dft.xcfun
postmf = tddft.TDDFT(mf).run()
# PySCF-1.6.1 and newer supports the .Gradients method to create a grad
# object after grad module was imported. It is equivalent to call the
# .nuc_grad_method method.
from pyscf import grad
g = postmf.Gradients()
g.kernel(state=1)
#mf = scf.UHF(mol).x2c().run()
#postmf = tddft.TDHF(mf).run()
#g = postmf.nuc_grad_method()
#g.kernel()
def diagonalize(a, b, nroots=5):
nocc, nvir = a.shape[:2]
a = a.reshape(nocc * nvir, nocc * nvir)
b = b.reshape(nocc * nvir, nocc * nvir)
e = numpy.linalg.eig(numpy.bmat([[a, b], [-b.conj(), -a.conj()]]))[0]
lowest_e = numpy.sort(e[e > 0])[:nroots]
return lowest_e
mf = scf.RHF(mol).run()
a, b = tddft.TDHF(mf).get_ab()
print('Direct diagoanlization:', diagonalize(a, b))
print('Reference:', tddft.TDHF(mf).kernel(nstates=5)[0])
mf = dft.RKS(mol).run(xc='lda,vwn')
a, b = tddft.TDDFT(mf).get_ab()
print('Direct diagoanlization:', diagonalize(a, b))
print('Reference:', tddft.TDDFT(mf).kernel(nstates=5)[0])
mf = dft.RKS(mol).run(xc='b3lyp')
a, b = tddft.TDDFT(mf).get_ab()
print('Direct diagoanlization:', diagonalize(a, b))
print('Reference:', tddft.TDDFT(mf).kernel(nstates=5)[0])
#
# UHF/UKS-TDDFT
#
def diagonalize(a, b, nroots=4):
a_aa, a_ab, a_bb = a
b_aa, b_ab, b_bb = b
