from moha.system.operator.base import OperatorNames
from moha.posthf.cc.auxiliary import *
from moha.io.log import log, timer
import numpy as np
import copy
__all__ = ['CCSDSolver']
[docs]class CCSDSolver(object):
"""The coupled cluster singles and double solver.
Attributes
----------
ham
Chemical Hamiltonian.
wfn
Hartree Fock wavefunction.
hf_results : dict
Hartree Fock calculation results.
maxiter : int
Maximum numer of iteration.
E_conv : float
Energy for convergence.
Methods
-------
__init__(self,ham,wfn,hf_results)
Initialize the solver.
kernel(self)
Kernel of the solver.
assign_hamiltonian(self,ham)
Assign the chemical Hamiltonian to the solver.
assign_wavefunction(self,wfn)
Assign the Hartree Fock wavefunction to the solver.
assign_hartree_fock_results(self,hf_results)
Assign the Hartree Fock calculation results to the solver.
assign_maximum_iteration(self,maxiter)
Assign the maximum number of iteration to the solver.
assign_energy_convergence(self,E_conv)
Assign the energy for convergence to the solver.
"""
def __init__(self,ham,wfn,hf_results,maxiter=100,E_conv=1.0E-8):
"""Initialize the solver.
Attributes
----------
ham
Chemical Hamiltonian.
wfn
Hartree Fock wavefunction.
hf_results : dict
Hartree Fock calculation results.
maxiter : int
Maximum numer of iteration.
E_conv : float
Energy for convergence.
"""
self.assign_hamiltonian(ham)
self.assign_wavefunction(wfn)
self.assign_hartree_fock_results(hf_results)
self.assign_maximum_iteration(maxiter)
self.assign_energy_convergence(E_conv)
[docs] @timer.with_section('CCSD')
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
CCSD calculation results.
"""
log.hline()
log('CCSD Section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
occ = wfn.occ
Nelec = occ['alpha'] + occ['beta']
C = wfn.coefficients
nspin = ham.nspin
#Transfer Fock integral from spatial to spin basis
fs = spinfock(wfn.orbital_energies)
#Transfer electron repulsion integral from atomic basis
#to molecular basis
ham.operators[OperatorNames.Eri].basis_transformation(C)
#build double bar integral <ij||kl>
spinints = ham.operators[OperatorNames.Eri].double_bar
ts,td,Dai,Dabij = initialize(fs,spinints,Nelec,nspin)
ECCSD = 0
DECC = 1.0
Iter = 0
log.hline()
log('{0:2s} {1:3s} {2:4s}'.format('Iter', 'ECC', 'Delta'))
log.hline()
while DECC > self.E_conv or Iter> self.maxiter: # arbitrary convergence criteria
Iter += 1
OLDCC = ECCSD
Fae,Fmi,Fme,Wmnij,Wabef,Wmbej = updateintermediates(True,Nelec,nspin,fs,spinints,ts,td)
ts = makeT1(True,Nelec,nspin,fs,spinints,ts,td,Dai,Fae,Fmi,Fme)
td = makeT2(True,Nelec,nspin,fs,spinints,ts,td,Dabij,Fae,Fmi,Fme,Wmnij,Wabef,Wmbej)
ECCSD = ccsdenergy(Nelec,nspin,fs,spinints,ts,td)
DECC = abs(ECCSD - OLDCC)
log('{0:2d} {1:3f} {2:4f}'.format(Iter, ECCSD, DECC))
log.hline()
log('CCSD Energy = {}'.format(ECCSD))
log('Total Energy = {}'.format(hf_results['total_energy']+ECCSD))
log.hline()
results = {
"success":True,
"CCSD_energy":ECCSD,
"total_energy":hf_results['total_energy']+ECCSD
}
return results
[docs] def assign_hamiltonian(self,ham):
"""Assign the chemical Hamiltonian to the solver.
Attributes
----------
ham
Chemical Hamiltonian.
"""
self.ham = ham
[docs] def assign_wavefunction(self,wfn):
"""Assign the Hartree Fock wavefunction to the solver.
Attributes
----------
wfn
Hartree Fock wavefunction.
"""
self.wfn = wfn
[docs] def assign_hartree_fock_results(self,hf_results):
"""Assign the Hartree Fock calculation results to the solver.
Attributes
----------
hf_results : dict
Hartree Fock calculation results.
Raises
------
TypeError
If Hartree Fock calculation results is not a dictionary.
"""
if not isinstance(hf_results, dict):
raise TypeError("Hartree Fock calculation results must be a dictionary")
self.hf_results = hf_results
[docs] def assign_maximum_iteration(self,maxiter):
"""Assign the maximum number of iteration to the solver.
Attributes
----------
maxiter : int
Maximum numer of iteration.
Raises
------
TypeError
If maximum number of iteration is not an integer.
ValueError
If maximum number of iteration is not a positive number.
"""
if not isinstance(maxiter, int):
raise TypeError("Maximum number of iteration must be an integer")
if maxiter <= 0:
raise ValueError("Maximum number of iteration must be a positive number")
self.maxiter = maxiter
[docs] def assign_energy_convergence(self,E_conv):
"""Assign the energy for convergence to the solver.
Attributes
----------
E_conv : float
Energy for convergence.
Raises
------
TypeError
If Energy for convergence is not an integer.
ValueError
If Energy for convergence is not a positive number.
"""
if not isinstance(E_conv, float):
raise TypeError("Energy for convergence must be a float")
if E_conv <= 0:
raise ValueError("Energy for convergence must be a positive number")
self.E_conv = E_conv