def pyq1_dft(atomtuples=[(2, (0, 0, 0))],
basis='6-31G**',
maxit=10,
xcname='SVWN'):
from PyQuante import Ints, settings, Molecule
from PyQuante.dft import getXC
from PyQuante.MG2 import MG2 as MolecularGrid
from PyQuante.LA2 import mkdens, geigh, trace2
from PyQuante.Ints import getJ
print("PyQ1 DFT run")
atoms = Molecule('Pyq1', atomlist=atomtuples)
bfs = Ints.getbasis(atoms, basis=basis)
S, h, Ints = Ints.getints(bfs, atoms)
nclosed, nopen = nel // 2, nel % 2
assert nopen == 0
enuke = atoms.get_enuke()
grid_nrad = settings.DFTGridRadii
grid_fineness = settings.DFTGridFineness
gr = MolecularGrid(atoms, grid_nrad, grid_fineness)
gr.set_bf_amps(bfs)
orbe, orbs = geigh(h, S)
eold = 0
for i in range(maxit):
D = mkdens(orbs, 0, nclosed)
gr.setdens(D)
J = getJ(Ints, D)
Exc, Vxc = getXC(gr, nel, functional=xcname)
F = h + 2 * J + Vxc
orbe, orbs = geigh(F, S)
Ej = 2 * trace2(D, J)
Eone = 2 * trace2(D, h)
energy = Eone + Ej + Exc + enuke
print(i, energy, Eone, Ej, Exc, enuke)
if np.isclose(energy, eold):
break
eold = energy
return energy
def pyq1_dft(atomtuples=[(2,(0,0,0))],basis = '6-31G**',maxit=10,
xcname='SVWN'):
from PyQuante import Ints,settings,Molecule
from PyQuante.dft import getXC
from PyQuante.MG2 import MG2 as MolecularGrid
from PyQuante.LA2 import mkdens,geigh,trace2
from PyQuante.Ints import getJ
print ("PyQ1 DFT run")
atoms = Molecule('Pyq1',atomlist=atomtuples)
bfs = Ints.getbasis(atoms,basis=basis)
S,h,Ints = Ints.getints(bfs,atoms)
nclosed,nopen = nel//2,nel%2
assert nopen==0
enuke = atoms.get_enuke()
grid_nrad = settings.DFTGridRadii
grid_fineness = settings.DFTGridFineness
gr = MolecularGrid(atoms,grid_nrad,grid_fineness)
gr.set_bf_amps(bfs)
orbe,orbs = geigh(h,S)
eold = 0
for i in range(maxit):
D = mkdens(orbs,0,nclosed)
gr.setdens(D)
J = getJ(Ints,D)
Exc,Vxc = getXC(gr,nel,functional=xcname)
F = h+2*J+Vxc
orbe,orbs = geigh(F,S)
Ej = 2*trace2(D,J)
Eone = 2*trace2(D,h)
energy = Eone + Ej + Exc + enuke
print (i,energy,Eone,Ej,Exc,enuke)
if np.isclose(energy,eold):
break
eold = energy
return energy
def setup_grid(self, molecule, bfs, **kwargs):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = kwargs.get('grid_nrad', settings.DFTGridRadii)
grid_fineness = kwargs.get('grid_fineness', settings.DFTGridFineness)
self.gr = MolecularGrid(molecule, grid_nrad, grid_fineness, **kwargs)
self.gr.set_bf_amps(bfs)
return
def setup_grid(self, molecule, bfs, **opts):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = opts.get('grid_nrad', 32)
grid_fineness = opts.get('grid_fineness', 1)
self.gr = MolecularGrid(molecule, grid_nrad, grid_fineness, **opts)
self.gr.set_bf_amps(bfs)
return
def setup_grid(self,molecule,bfs,**kwargs):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = kwargs.get('grid_nrad',settings.DFTGridRadii)
grid_fineness = kwargs.get('grid_fineness',settings.DFTGridFineness)
self.gr = MolecularGrid(molecule,grid_nrad,grid_fineness,**kwargs)
self.gr.set_bf_amps(bfs)
return
def setup_grid(self,molecule,bfs,**opts):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = opts.get('grid_nrad',32)
grid_fineness = opts.get('grid_fineness',1)
self.gr = MolecularGrid(molecule,grid_nrad,grid_fineness,**opts)
self.gr.set_bf_amps(bfs)
return
class DFTHamiltonian(AbstractHamiltonian):
method = 'DFT'
def __init__(self, molecule, **kwargs):
from PyQuante.Convergence import DIIS
from PyQuante.DFunctionals import need_gradients
self.molecule = molecule
logging.info("DFT calculation on system %s" % self.molecule.name)
self.basis_set = BasisSet(molecule, **kwargs)
self.integrals = Integrals(molecule, self.basis_set, **kwargs)
self.iterator = SCFIterator()
self.h = self.integrals.get_h()
self.S = self.integrals.get_S()
self.ERI = self.integrals.get_ERI()
self.Enuke = molecule.get_enuke()
self.nel = molecule.get_nel()
self.F = self.h
self.functional = kwargs.get('functional', settings.DFTFunctional)
kwargs['do_grad_dens'] = need_gradients[self.functional]
self.setup_grid(molecule, self.basis_set.get(), **kwargs)
self.dmat = None
self.entropy = None
self.DoAveraging = kwargs.get('DoAveraging', settings.DFTAveraging)
if self.DoAveraging:
self.Averager = DIIS(self.S)
nel = molecule.get_nel()
nclosed, nopen = molecule.get_closedopen()
logging.info("Nclosed/open = %d, %d" % (nclosed, nopen))
self.solver = SolverFactory(nel, nclosed, nopen, self.S, **kwargs)
return
def __repr__(self):
lstr = [
'Hamiltonian constructed for method %s' % self.method,
repr(self.molecule),
repr(self.basis_set),
repr(self.iterator)
]
return '\n'.join(lstr)
def get_energy(self):
return self.energy
def iterate(self, **kwargs):
return self.iterator.iterate(self, **kwargs)
def setup_grid(self, molecule, bfs, **kwargs):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = kwargs.get('grid_nrad', settings.DFTGridRadii)
grid_fineness = kwargs.get('grid_fineness', settings.DFTGridFineness)
self.gr = MolecularGrid(molecule, grid_nrad, grid_fineness, **kwargs)
self.gr.set_bf_amps(bfs)
return
def update(self, **kwargs):
from PyQuante.LA2 import trace2
from PyQuante.Ints import getJ
from PyQuante.dft import getXC
#self.DoAveraging = kwargs.get('DoAveraging',True)
#if self.DoAveraging:
# self.Averager = DIIS(self.S)
if self.DoAveraging and self.dmat is not None:
self.F = self.Averager.getF(self.F, self.dmat)
self.dmat, self.entropy = self.solver.solve(self.F, **kwargs)
D = self.dmat
self.gr.setdens(D)
self.J = getJ(self.ERI, D)
self.Ej = 2 * trace2(D, self.J)
self.Exc, self.XC = getXC(self.gr,
self.nel,
functional=self.functional)
self.Eone = 2 * trace2(D, self.h)
self.F = self.h + 2 * self.J + self.XC
self.energy = self.Eone + self.Ej + self.Exc + self.Enuke + self.entropy
return
class DFTHamiltonian(AbstractHamiltonian):
method='DFT'
def __init__(self,molecule,**kwargs):
from PyQuante.Convergence import DIIS
from PyQuante.DFunctionals import need_gradients
self.molecule = molecule
logging.info("DFT calculation on system %s" % self.molecule.name)
self.basis_set = BasisSet(molecule,**kwargs)
self.integrals = Integrals(molecule,self.basis_set,**kwargs)
self.iterator = SCFIterator()
self.h = self.integrals.get_h()
self.S = self.integrals.get_S()
self.ERI = self.integrals.get_ERI()
self.Enuke = molecule.get_enuke()
self.nel = molecule.get_nel()
self.F = self.h
self.functional = kwargs.get('functional',settings.DFTFunctional)
kwargs['do_grad_dens'] = need_gradients[self.functional]
self.setup_grid(molecule,self.basis_set.get(),**kwargs)
self.dmat = None
self.entropy = None
self.DoAveraging = kwargs.get('DoAveraging',settings.DFTAveraging)
if self.DoAveraging:
self.Averager = DIIS(self.S)
nel = molecule.get_nel()
nclosed,nopen = molecule.get_closedopen()
logging.info("Nclosed/open = %d, %d" % (nclosed,nopen))
self.solver = SolverFactory(nel,nclosed,nopen,self.S,**kwargs)
return
def __repr__(self):
lstr = ['Hamiltonian constructed for method %s' % self.method,
repr(self.molecule),
repr(self.basis_set),
repr(self.iterator)]
return '\n'.join(lstr)
def get_energy(self): return self.energy
def iterate(self,**kwargs): return self.iterator.iterate(self,**kwargs)
def setup_grid(self,molecule,bfs,**kwargs):
#from PyQuante.MolecularGrid import MolecularGrid
from PyQuante.MG2 import MG2 as MolecularGrid
grid_nrad = kwargs.get('grid_nrad',settings.DFTGridRadii)
grid_fineness = kwargs.get('grid_fineness',settings.DFTGridFineness)
self.gr = MolecularGrid(molecule,grid_nrad,grid_fineness,**kwargs)
self.gr.set_bf_amps(bfs)
return
def update(self,**kwargs):
from PyQuante.LA2 import trace2
from PyQuante.Ints import getJ
from PyQuante.dft import getXC
#self.DoAveraging = kwargs.get('DoAveraging',True)
#if self.DoAveraging:
# self.Averager = DIIS(self.S)
if self.DoAveraging and self.dmat is not None:
self.F = self.Averager.getF(self.F,self.dmat)
self.dmat,self.entropy = self.solver.solve(self.F,**kwargs)
D = self.dmat
self.gr.setdens(D)
self.J = getJ(self.ERI,D)
self.Ej = 2*trace2(D,self.J)
self.Exc,self.XC = getXC(self.gr,self.nel,
functional=self.functional)
self.Eone = 2*trace2(D,self.h)
self.F = self.h+2*self.J+self.XC
self.energy = self.Eone + self.Ej + self.Exc + self.Enuke + self.entropy
return
def gto_lda_inputs(bfs,atoms): grid_nrad = 32 # number of radial shells per atom grid_fineness = 1 #option gr = MolecularGrid(atoms,grid_nrad,grid_fineness) gr.set_bf_amps(bfs) return gr
