def __init__(self, mol, mints):
mult = mol.multiplicity()
nelec = get_nelec(mol)
self.conv = get_conv()
self.Na = int(0.5 * (nelec + mult - 1))
self.Nb = nelec - self.Na
V = np.array(mints.ao_potential())
T = np.array(mints.ao_kinetic())
G = np.array(mints.ao_eri())
self.S = np.array(mints.ao_overlap())
self.Hcore = T + V
self.G = G.transpose((0, 2, 1, 3))
self.X = np.matrix(la.funm(self.S, lambda x: x**(-0.5)))
self.Vnu = mol.nuclear_repulsion_energy()
## alpha and beta density matrices
self.Da = np.random.rand(*self.X.shape)
self.Da = self.Da + self.Da.T
self.Db = np.random.rand(*self.X.shape)
self.Db = self.Db + self.Db.T
self.E = 0.0
def __init__(self,mol,mints):
mult = mol.multiplicity()
nelec = get_nelec(mol)
self.conv = get_conv()
self.Na = int( 0.5*(nelec+mult-1) )
self.Nb = nelec - self.Na
V = np.array( mints.ao_potential() )
T = np.array( mints.ao_kinetic() )
G = np.array( mints.ao_eri() )
self.S = np.array( mints.ao_overlap() )
self.Hcore = T + V
self.G = G.transpose((0,2,1,3))
self.X = np.matrix( la.funm(self.S, lambda x : x**(-0.5) ) )
self.Vnu = mol.nuclear_repulsion_energy()
## alpha and beta density matrices
self.Da = np.random.rand(*self.X.shape)
self.Da = self.Da + self.Da.T
self.Db = np.random.rand(*self.X.shape)
self.Db = self.Db + self.Db.T
self.E = 0.0
def __init__(self,mol,mints):
self.docc = get_docc(mol)
self.nbf = get_nbf(mints)
self.conv = get_conv()
self.maxiter = get_maxiter()
self.rhf = RHF(mol,mints)
self.E_scf = self.rhf.get_energy()
self.e = self.rhf.e
self.G = self.rhf.G
self.C = self.rhf.C
def __init__(self,mol,mints):
self.nocc = get_nocc(mol)
self.nbf = get_nbf(mints)
self.norb = 2*self.nbf
self.conv = get_conv()
self.maxiter = get_maxiter()
self.uhf = UHF(mol,mints)
self.E_uhf = self.uhf.get_energy()
self.e = self.uhf.e
self.g = self.uhf.g
self.C = self.uhf.C
def __init__(self,mol,mints):
"""
initialize rhf class
takes objects:
1. mol: a psi4 molecule, get_active_molecule()
2. mints: molecular integrals from libmints in psi4
"""
self.docc = get_docc(mol)
self.nbf = get_nbf(mints)
self.conv = get_conv()
self.maxiter = get_maxiter()
self.S = np.matrix(mints.ao_overlap() )
self.X = np.matrix(la.funm(self.S,lambda x : x**(-0.5)))
self.T = np.matrix(mints.ao_kinetic() )
self.V = np.matrix(mints.ao_potential() )
self.H = self.T+self.V
self.G = np.array(mints.ao_eri() ).swapaxes(1,2)
self.D = np.zeros((self.nbf,self.nbf))
self.Vnu = mol.nuclear_repulsion_energy()
self.E = 0
def __init__(self,mol,mints):
self.nbf = get_nbf(mints)
self.norb = 2* self.nbf
self.nocc = get_nocc(mol)
self.conv = get_conv()
self.maxiter = get_maxiter()
m = self.nbf
N = self.norb
# overlap matrix
S = mints.ao_overlap()
self.Z = block_oei(S)
self.X = np.matrix(la.funm(self.Z,lambda x : x**(-0.5)))
# KE matrix
T = mints.ao_kinetic()
self.T = block_oei(T)
# PE matrix
V = mints.ao_potential()
self.V = block_oei(V)
self.Vnu = mol.nuclear_repulsion_energy()
# Hcore
self.H = self.T + self.V
# ERI matrix
G = np.array( mints.ao_eri() ) #### mxmxmxm tensor
self.G = block_tei(G)
self.g = self.G.swapaxes(1,2) #### ( m n | r s ) -> < m r | n s >
# Density matrix
self.D = np.matrix(np.zeros(self.Z.shape))
self.E = 0.0
