def test_rks_b3lypg(self):
mf = dft.RKS(h2o)
mf.grids.prune = None
mf.run(conv_tol=1e-15, xc='b3lypg')
g = grad.RKS(mf)
g1 = g.grad()
self.assertAlmostEqual(finger(g1), 0.066541921001296467, 9)
def test_rks_bp86(self):
mf = dft.RKS(h2o)
mf.grids.prune = None
mf.run(conv_tol=1e-15, xc='b88,p86')
g = grad.RKS(mf)
g1 = g.grad()
self.assertAlmostEqual(finger(g1), 0.10362532283229957, 9)
def test_rks_lda(self):
mf = dft.RKS(h2o)
mf.grids.prune = None
mf.run(conv_tol=1e-15, xc='lda,vwn')
g = grad.RKS(mf)
g1 = g.grad()
self.assertAlmostEqual(finger(g1), 0.098438461959390822, 9)
def gga_grad(self):
if self._gga_grad is not NotImplemented:
return self._gga_grad
if self.gga_eng.mo_coeff is None:
self.gga_eng.kernel()
gga_grad = grad.RKS(self.gga_eng)
self._gga_grad = gga_grad
return self._gga_grad
def test_rks_scanner(self):
mol1 = mol.copy()
mol1.set_geom_('''
H 0. 0. 0.9
F 0. 0.1 0.''')
mf_scanner = grad.RKS(scf.RKS(mol).set(conv_tol=1e-14)).as_scanner()
e, de = mf_scanner(mol)
self.assertAlmostEqual(finger(de), 0.458572523892797, 7)
e, de = mf_scanner(mol1)
self.assertAlmostEqual(finger(de), 0.12763259021187467, 7)
def EF(molstr,basis = "6-311g**", xc = "PBE0"): m1 = gto.Mole() m1.atom = molstr m1.basis = basis m1.build() mf = dft.RKS(m1) mf.xc = xc mf.kernel() energy = mf.e_tot force = grad.RKS(mf).kernel()/0.52917721092 * -JOULEPERHARTREE return energy, force
def calc_gradients_elec(mole, one_dm: np.ndarray, mf, coeffs, occs, energies):
"""Calculate electronic part of nuclear gradients.
Parameters
----------
mole
A PySCF mole object.
one_dm
One-particle density matrix understood by IOdata
projected and formatted in a PySCF-compatible way
(single 2d array or list for a,b 2d arrays)
mf
A PySCF mean field object. Its only use is method specification.
coeffs
AO coefficient matrix understood by IOdata
projected and formatted in a PySCF-compatible way
(single 2d array or list for a,b 2d arrays)
occs
Occupation numbers formatted in a PySCF-compatible way
(single 1d array or list for a,b 1d arrays)
energies
MO energies formatted in a PySCF-compatible way
(single 1d array or list for a,b 1d arrays)
Returns
-------
grad_elec
Nuclear gradients in a.u. per cartesian coordinate per atom.
(Due to electrons)
"""
mo_energy = energies
mo_coeff = coeffs
mo_occ = occs
if len(one_dm) == 2:
try:
grad_elec = grad.UKS(mf).grad_elec(mo_energy=mo_energy,
mo_coeff=mo_coeff,
mo_occ=mo_occ)
except:
grad_elec = grad.UHF(mf).grad_elec(mo_energy=mo_energy,
mo_coeff=mo_coeff,
mo_occ=mo_occ)
else:
try:
grad_elec = grad.RKS(mf).grad_elec(mo_energy=mo_energy,
mo_coeff=mo_coeff,
mo_occ=mo_occ)
except:
grad_elec = grad.RHF(mf).grad_elec(mo_energy=mo_energy,
mo_coeff=mo_coeff,
mo_occ=mo_occ)
return grad_elec
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
gradients = grad.RKS(mf).kernel(
) # We calculate analytical nuclear gradients, we choose the level of theory of the gradients
print(mol.atom_coords())
print(gradients)
dist = 1.5
coord = 'H 0 0 0; H 0 0 {0}'.format(str(dist))
# Do a mean-field KS-DFT calculation at a new 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
#!/usr/bin/env python
'''
Set the default XC functional library to XCFun (https://github.com/dftlibs/xcfun)
'''
from pyscf import gto, dft, grad
mol = gto.M(
atom = '''
F 0. 0. 0.
H 0. 0. 1.587 ''',
basis = 'ccpvdz')
#
# Modifying _NumInt.libxc changes the default XC library globally. All DFT
# calculations will call the xcfun to evaluate XC values.
#
dft.numint._NumInt.libxc = dft.xcfun
mf = dft.RKS(mol)
mf.xc = 'b88,lyp'
mf.kernel()
grad.RKS(mf).run()