def test_161_bse_h2b_spin1_uhf_cis(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=1)
gto_mf = scf.UHF(mol)
gto_mf.kernel()
gto_td = tddft.TDHF(gto_mf)
gto_td.nstates = 150
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_0161_bse_h2b_spin1_uhf_cis_pyscf.txt',
data.T,
fmt=['%f', '%f'])
#data_ref = np.loadtxt('test_0159_bse_h2b_uhf_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_0161_bse_h2b_spin1_uhf_cis_nao.txt',
data.T,
fmt=['%f', '%f'])
from pyscf.pbc import gto, scf
cell = gto.M(
a=numpy.eye(3) * 3.5668,
atom='''C 0. 0. 0.
C 0.8917 0.8917 0.8917
C 1.7834 1.7834 0.
C 2.6751 2.6751 0.8917
C 1.7834 0. 1.7834
C 2.6751 0.8917 2.6751
C 0. 1.7834 1.7834
C 0.8917 2.6751 2.6751''',
basis='6-31g',
verbose=4,
)
mf = scf.RHF(cell).density_fit()
mf.with_df.gs = [5] * 3
mf.kernel()
#
# Import CC, TDDFT moduel from the molecular implementations
#
from pyscf import cc, tddft
mycc = cc.CCSD(mf)
mycc.kernel()
mytd = tddft.TDHF(mf)
mytd.nstates = 5
mytd.kernel()
import numpy
from pyscf import gto, scf, tddft, qmmm
mol = gto.M(atom='''
C 1.1879 -0.3829 0.0000
C 0.0000 0.5526 0.0000
O -1.1867 -0.2472 0.0000
H -1.9237 0.3850 0.0000
H 2.0985 0.2306 0.0000
H 1.1184 -1.0093 0.8869
H 1.1184 -1.0093 -0.8869
H -0.0227 1.1812 0.8852
H -0.0227 1.1812 -0.8852
''',
basis='3-21g',
verbose=4)
numpy.random.seed(1)
coords = numpy.random.random((5, 3)) * 10
charges = (numpy.arange(5) + 1.) * -.1
#
# Background charges have to be patched to the underlying SCF calculaitons.
#
mf = scf.RHF(mol)
mf = qmmm.mm_charge(mf, coords, charges).run()
tddft.TDA(mf).run()
tddft.TDHF(mf).run()
#!/usr/bin/env python
#
# Author: Qiming Sun <*****@*****.**>
#
'''
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)
#
# RHF/RKS-TDDFT
#
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])
#