variational6.py~

"""This module explicitly solves for the ghetto CC variational ansatz.
"""
import time
import numpy
import scipy
import warnings
import commutators
import scipy.sparse
import scipy.optimize
import resource
import scipy.sparse.linalg
from itertools import combinations
from sys import argv
import os

# Return matrix representation of creation or annihilation operator.

def JordanWignerTerm(index, n_orbitals):
  """Make a matrix representation of a fermion operator.

  Args:
    index: This is a nonzero integer. The integer indicates the tensor
      factor and the sign indicates raising or lowering.
    n_orbitals: This int gives the number of orbitals.

  Returns: The corresponding fermion operator.
  """
  # Define operators.
  I = scipy.sparse.csr_matrix([[1, 0], [0, 1]], dtype=float)
  Z = scipy.sparse.csr_matrix([[1, 0], [0, -1]], dtype=float)
  Q_raise = scipy.sparse.csr_matrix([[0, 0], [1, 0]], dtype=float)
  Q_lower = scipy.sparse.csr_matrix([[0, 1], [0, 0]], dtype=float)

  # Construct fermionic operator.
  assert index
  orbital = abs(index)
  operator = 1
  for tensor_factor in range(orbital - 1):
    operator = scipy.sparse.kron(operator, I, 'csr')
  if index > 0:
    operator = scipy.sparse.kron(operator, Q_raise, 'csr')
  else:
    operator = scipy.sparse.kron(operator, Q_lower, 'csr')
  for tensor_factor in range(n_orbitals - orbital):
    operator = scipy.sparse.kron(operator, Z, 'csr')
  assert scipy.sparse.isspmatrix_csr(operator)
  return operator


def JordanWignerTermSym(index, n_orbitals):
  """Make a matrix representation of a fermion operator.

  Args:
    index: This is a nonzero integer. The integer indicates the tensor
      factor and the sign indicates raising or lowering.
    n_orbitals: This int gives the number of orbitals.

  Returns: The corresponding fermion operator.
  """

  # Construct fermionic operator.
  assert index
  orbital = abs(index)
  op=[]
  if index > 0:
    op += 'Q'
    op += str(orbital)
    op += '-'
  else:
    op += 'q'
    op += str(orbital)
    op += '-'
  for tensor_factor in range(n_orbitals - orbital):
    op += 'Z'
    op += repr(int(tensor_factor))
    op += '-'
  form = ''.join(op)
  return form

# Initialize Jordan-Wigner dictionary so terms aren't constantly reformed.
def GetJordanWignerTerms(n_orbitals):
    jw_terms = {}
    for index in range(-n_orbitals, n_orbitals + 1):
      if index:
        jw_terms[index] = JordanWignerTerm(index, n_orbitals)
    return jw_terms

def GetJordanWignerTermsSym(n_orbitals):
    jw_terms_sym = {}
    for index in range(-n_orbitals, n_orbitals + 1):
      if index:
        jw_terms_sym[index] = JordanWignerTermSym(index, n_orbitals)
    return jw_terms

# Return a particular operator given the term and coefficient.
def MatrixForm(coefficient, term, jw_terms,
    add_conjugates=False, anti_hermitian=False):
  operator = coefficient
  for index in term:
    operator = operator * jw_terms[index]
  if add_conjugates and commutators.GetConjugate(term):
    if anti_hermitian:
      #print 'Enter to T-T^dagger'
      operator = 1j * (operator - operator.getH())
    else:
      #print 'Enter to i(T+T^dagger')
      operator = operator + operator.getH()
  return operator


# Expectation.
def Expectation(operator, psi):
  psi = scipy.sparse.csr_matrix(psi)
  operator = scipy.sparse.csr_matrix(operator)
  expectation = psi.getH() * operator * psi
  assert expectation.get_shape() == (1, 1)
  return numpy.real(expectation[0, 0])


# Get number operator.
def NumberOperator(n_orbitals):
  number_operator = 0
  jw_terms = GetJordanWignerTerms(n_orbitals)
  for tensor_factor in range(1, n_orbitals + 1):
    term = [tensor_factor, -tensor_factor]
    operator = MatrixForm(1, term, jw_terms)
    number_operator = number_operator + operator
  return number_operator


# Initialize Hartree-Fock state.
def HartreeFockState(n_electrons, n_orbitals):
  occupied = scipy.sparse.csr_matrix([[0], [1]], dtype=float)
  psi = 1.
  unoccupied = scipy.sparse.csr_matrix([[1], [0]], dtype=float)
  for orbital in range(n_electrons):
    psi = scipy.sparse.kron(psi, occupied, 'csr')
  for orbital in range(n_orbitals - n_electrons):
    psi = scipy.sparse.kron(psi, unoccupied, 'csr')
  return psi


# Test if matrix is Hermitian.
def IsHermitian(matrix):
  conjugate = matrix.getH()
  difference = matrix - conjugate
  if difference.nnz:
    discrepancy = max(map(abs, difference.data))
    if discrepancy > 1e-9:
      print 'Hermitian discrepancy = %s.' % repr(discrepancy)
      return False
  return True


# Construct an operator from terms and coefficients.
def MakeOperator(coefficients, terms, verbose=False):

  # Initialize.
  n_terms = len(coefficients)
  one_percent = numpy.rint(numpy.ceil(n_terms / 100.))
  start = time.clock()
  n_orbitals = commutators.OrbitalCount(terms)
  jw_terms = GetJordanWignerTerms(n_orbitals)

  # Loop over terms.
  operator = 0
  for i, (coefficient, term) in enumerate(zip(coefficients, terms)):
    operator = operator + MatrixForm(coefficient, term, jw_terms)

    # Report progress.
    if verbose and not (i + 1) % one_percent:
      percent_complete = numpy.rint(100. * (i + 1) / n_terms)
      elapsed = time.clock() - start
      rate = elapsed / percent_complete
      eta = rate * (100 - percent_complete)
      print('%s. Computation %i%% complete. Approximately %i '
            'minute(s) remaining.' % (time.strftime(
                '%B %d at %H:%M:%S', time.localtime()),
            percent_complete, round(eta / 60)))

  assert IsHermitian(operator)
  return operator


# Save a sparse matrix.
def SaveSparse(name, operator):
  numpy.savez(name, data=operator.data, indices=operator.indices,
              indptr=operator.indptr, shape=operator.shape)


# Load a sparse matrix.
def LoadSparse(name):
  loader = numpy.load(name)
  operator = scipy.sparse.csr_matrix((loader['data'], loader['indices'],
                                      loader['indptr']), shape=loader['shape'])
  return operator


# Get the relevant Slater determinants.
def GetDeterminants(n_orbitals, n_electrons, n_excitations):

  # Initialize reference state.
  reference = numpy.zeros(n_orbitals, int)
  reference[:n_electrons] = 1
  states = []

  # Loop over excitation level.
  for m in range(n_excitations + 1):
    for occupied in combinations(range(n_electrons), r=m):
      for unoccupied in combinations(range(n_electrons, n_orbitals), r=m):
        state = numpy.copy(reference)
        state[list(unoccupied)] = 1
        state[list(occupied)] = 0
        states += [state]
  return numpy.array(states)


# Return a projector into a restricted Fock space.
def ConfigurationProjector(n_orbitals, n_electrons, n_excitations):

  # Name.
  if n_excitations == 'all':
    n_excitations = n_orbitals - n_electrons
  name = 'data/operators/projector_%i_%i_%i.npz'\
      % (n_orbitals, n_electrons, n_excitations)

  # Attempt to load.
  try:
    projector = LoadSparse(name)

  except:
    # Initialize projector computation.
    n_hilbert = 2 ** n_orbitals
    states = GetDeterminants(n_orbitals, n_electrons, n_excitations)
    unoccupied = scipy.sparse.csr_matrix([[1], [0]], dtype=int)
    occupied = scipy.sparse.csr_matrix([[0], [1]], dtype=int)
    number_operator = NumberOperator(n_orbitals)

    # Construct projector.
    projector = 0
    for state in states:
      
      # Construct computational basis state in Hilbert space.
      ket = 1
      for qubit in state:
        if qubit:
          ket = scipy.sparse.kron(ket, occupied, 'csr')
        else:
          ket = scipy.sparse.kron(ket, unoccupied, 'csr')

      # Add to projector.
      density = ket * ket.getH()
      projector = projector + density

    # Save and return projector.
    SaveSparse(name, projector)
  return projector


# Return an operator.
def GetHamiltonian2(molecule, basis, n_excitations='FCI'):
  recompute = 1
  # Try to load it.
  name = 'data/operators/%s_%s_hamiltonian_%s.npz'\
      % (molecule, basis, str(n_excitations))
  try:
    assert not recompute
    hamiltonian = LoadSparse(name)

  # Compute pre-projected Hamiltonian.
  except:
    repulsion, coefficients, terms = commutators.GetHamiltonianTerms(molecule, basis, add_conjugates=True)
    hamiltonian = MakeOperator(coefficients, terms)

    # Project, if necessary.
    if n_excitations != 'FCI':
      n_hilbert = hamiltonian.shape[0]
      n_electrons = commutators.ElectronCount(molecule)
      n_orbitals = int(numpy.rint(numpy.log2(n_hilbert)))
      if n_orbitals - n_electrons > n_excitations:
        projector = ConfigurationProjector(
            n_orbitals, n_electrons, n_excitations)
        hamiltonian = projector * hamiltonian * projector.getH()

    # Save and return.
    SaveSparse(name, hamiltonian)
  return hamiltonian


# Return an operator.
def GetHamiltonian(molecule, basis, n_excitations='FCI'):
  # Try to load it.
  name = 'data/operators/%s_%s_hamiltonian_%s.npz'\
      % (molecule, basis, str(n_excitations))
  # Compute pre-projected Hamiltonian.
  repulsion, coefficients, terms = commutators.GetHamiltonianTerms(molecule, basis, add_conjugates=True)
  hamiltonian = MakeOperator(coefficients, terms)
  
  # Project, if necessary.
  if n_excitations != 'FCI':
    n_hilbert = hamiltonian.shape[0]
    n_electrons = commutators.ElectronCount(molecule)
    n_orbitals = int(numpy.rint(numpy.log2(n_hilbert)))
    if n_orbitals - n_electrons > n_excitations:
      projector = ConfigurationProjector(
        n_orbitals, n_electrons, n_excitations)
      hamiltonian = projector * hamiltonian * projector.getH()
      
    # Save and return.
  SaveSparse(name, hamiltonian)
  return hamiltonian


# Compute and save information about lowest or highest operator eigenvalue.
def SparseDiagonalize(operator, which='SA'):
  max_steps = 1e10
  values, vectors = scipy.sparse.linalg.eigsh(
      operator, 1, which=which, maxiter=max_steps)
  eigenstate = vectors[:, 0]
  print "the minimum energy in the energy vector is:",min(values),values[0]
  eigenstate = scipy.sparse.csr_matrix(eigenstate)
  return scipy.sparse.csr_matrix.transpose(eigenstate)
  
# Return the unitary corresponding to evolution under hamiltonian.
def GetUnitary(time, term):
  exponent = scipy.sparse.csc_matrix(-1j * time * term)
  assert IsHermitian(1j * exponent)
  with warnings.catch_warnings(record=False):
    warnings.simplefilter('ignore')
  unitary = scipy.sparse.linalg.expm(exponent)
  unitary.eliminate_zeros()
  return unitary.tocsr()


# Make a function object to return energy of variational ansatz.
class Objective:

  # Initialize function object.
  def __init__(self, terms, reference_state, hamiltonian, cc_form=False):

    # Initialize dictionary of unitaries.
    self.terms = terms
    self.hamiltonian = hamiltonian
    self.reference_state = reference_state
    n_orbitals = commutators.OrbitalCount(terms)
    jw_terms = GetJordanWignerTerms(n_orbitals)
    self.matrices = {}
    for term in terms:
      self.matrices[tuple(term)] = MatrixForm(
          1., term, jw_terms, add_conjugates=True, anti_hermitian=cc_form)
      assert IsHermitian(self.matrices[tuple(term)])
    self.min_energy = numpy.inf
    self.calls = 0

  # Method to return unitary which prepares a state.
  def GetStatePrep(self, coefficients):
    unitary = 1.
    counter=0
    for coefficient, term in zip(coefficients, self.terms):
      counter=counter+1
      # print 'TERM %i' % (counter)
      # print '%s %s' % (term,repr(float(coefficient)))
      #sterm=SymbolicJordanWigner2(term,coefficient)
      #for i in range(len(sterm)):
      #  print sterm[i]
      term_matrix = self.matrices[tuple(term)].copy()
      term_unit = GetUnitary(coefficient, term_matrix)
      # print 'Unitary'
      # print term_unit
      unitary =  term_unit * unitary
    return unitary

  # Method to return unitary which prepares a state using single unitary.
  def ModStatePrep(self, coefficients):
    hamiltonian = 0.
    for coefficient, term in zip(coefficients, self.terms):
      if abs(float(coefficient)) > 1E-06:
        print '%s %s' % (term,repr(float(coefficient)))
      hamiltonian = hamiltonian + coefficient * self.matrices[tuple(term)].copy()
    unitary = GetUnitary(1., hamiltonian)
    return unitary

  # Write paren method which returns energy given variables.
  def __call__(self, variables):
    state_prep = self.ModStatePrep(variables)
    #state_prep = self.GetStatePrep(variables)
    state = state_prep * self.reference_state
    energy = Expectation(self.hamiltonian, state)
    self.calls += 1
    print 'CALL NUMBER: %i' %(self.calls)
    if energy < self.min_energy:
      print 'Energy difference: %e' % (self.min_energy-energy)
      self.min_energy = energy
#      print 'Lowest energy after %i calls is %f.' % (self.calls, energy)
    print("Memory usage:",resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1000)
    return energy


# Variationally determine optimal coefficients for state prep.
def VariationallyMinimize(terms, reference_state, initial_guess,
                          hamiltonian, cc_form=False):
  ObjectiveFunction = Objective(terms, reference_state, hamiltonian, cc_form)
  # method = 'L-BFGS-B'
  # solution = scipy.optimize.minimize(
      # ObjectiveFunction, initial_guess, method=method, options={'gtol':1e-06,'disp':True}).x
  method = 'BFGS'
  solution = scipy.optimize.minimize(
    ObjectiveFunction, initial_guess, method=method, options={'gtol':1e-06,'disp':True}).x
  # method = 'Powell'
  # solution = scipy.optimize.minimize(
  #   ObjectiveFunction, initial_guess, method=method, options={'ftol':0.000001,'xtol':0.0001}).x
  energy = ObjectiveFunction(solution)
  ncalls = ObjectiveFunction.calls
  return ncalls, solution, energy

def SymbolicJordanWigner(term,coefficient):
  termlen=len(term)
  if termlen==2:
    if abs(term[1])>abs(term[0]):
      p = abs(term[1])
      q = abs(term[0])
    else:
      p = abs(term[0])
      q = abs(term[1])
    sterm=[]
    coeff=0.5*coefficient
    for i in range(q+1,p):
      sterm += 'Z'
      sterm += str(i)
    sterm += ' '
    sterm += str(coeff)
    sterm += '('
    sterm += 'X'
    sterm += str(q)
    sterm += 'X'
    sterm += str(p)
    sterm += '+'
    sterm += 'Y'
    sterm += str(q)
    sterm += 'Y'
    sterm += str(p)
    sterm += ')'
  elif termlen==4:
    if abs(term[0])==abs(term[2]): 
      q=abs(term[0])
      p=abs(term[1])
      r=abs(term[3])
      sign=-1
      opt=1
    elif abs(term[0])==abs(term[3]):
      q=abs(term[0])
      p=abs(term[1])
      r=abs(term[2])
      sign=1
      opt=1
    elif abs(term[1])==abs(term[2]): 
      q=abs(term[1])
      p=abs(term[0])
      r=abs(term[3])
      sign=1
      opt=1
    elif abs(term[1])==abs(term[3]):
      q=abs(term[1])
      p=abs(term[0])
      r=abs(term[2])
      sign=-1
      opt=1
    else:
      opt=2
      sign=1
      if (abs(term[0])>abs(term[2]) and abs(term[1])>abs(term[3])) or (abs(term[0])>abs(term[3]) and abs(term[1])>abs(term[2])):
        if abs(term[1])>abs(term[0]):
          p=abs(term[1])
          q=abs(term[0])
          sign=-1*sign
        else:
          p=abs(term[0])
          q=abs(term[1])
          sign=1*sign
        if abs(term[3])>abs(term[2]):
          r=abs(term[3])
          s=abs(term[2])
          sign=-1*sign
        else:
          r=abs(term[2])
          s=abs(term[3])
          sign=1*sign
      else:
        if abs(term[1])>abs(term[0]):
          r=abs(term[1])
          s=abs(term[0])
          sign=-1*sign
        else:
          r=abs(term[0])
          s=abs(term[1])
          sign=1*sign
        if abs(term[3])>abs(term[2]):
          p=abs(term[3])
          q=abs(term[2])
          sign=-1*sign
        else:
          p=abs(term[2])
          q=abs(term[3])
          sign=1*sign
    if opt==1:
      if r>p:
        aux=r
        r=p
        p=aux
      sterm=[]
      coeff=sign*coefficient
      for i in range(r+1,p):
        sterm += 'Z'
        sterm += str(i)
      sterm += '['
      sterm += str(coeff)
      sterm += '('
      sterm += 'X'
      sterm += str(r)
      sterm += 'X'
      sterm += str(p)
      sterm += '+'
      sterm += 'Y'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(p)
      sterm += ')'
      sterm += '-'
      sterm += 'Z'
      sterm += str(q)
      sterm += ' '
      sterm += str(coeff)
      sterm += '('
      sterm += 'X'
      sterm += str(r)
      sterm += 'X'
      sterm += str(p)
      sterm += '+'
      sterm += 'Y'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(p)
      sterm += ')'
      sterm += ']'
      coeff=coefficient
    elif opt==2:
      sterm=[]
      coeff=sign*coefficient/8.0
      for i in range(s+1,r):
        sterm += 'Z'
        sterm += str(i)
      for i in range(q+1,p):
        sterm += 'Z'
        sterm += str(i)
      sterm += ' '
      sterm += str(coeff)
      sterm += '('
      sterm += 'X'
      sterm += str(s)
      sterm += 'X'
      sterm += str(r)
      sterm += 'X'
      sterm += str(q)
      sterm += 'X'
      sterm += str(p)
      sterm += '-'
      sterm += 'X'
      sterm += str(s)
      sterm += 'X'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(q)
      sterm += 'Y'
      sterm += str(p)
      sterm += '+'
      sterm += 'X'
      sterm += str(s)
      sterm += 'Y'
      sterm += str(r)
      sterm += 'X'
      sterm += str(q)
      sterm += 'Y'
      sterm += str(p)
      sterm += '+'
      sterm += 'Y'
      sterm += str(s)
      sterm += 'X'
      sterm += str(r)
      sterm += 'X'
      sterm += str(q)
      sterm += 'Y'
      sterm += str(p)
      sterm += '+'
      sterm += 'Y'
      sterm += str(s)
      sterm += 'X'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(q)
      sterm += 'X'
      sterm += str(p)
      sterm += '-'
      sterm += 'Y'
      sterm += str(s)
      sterm += 'Y'
      sterm += str(r)
      sterm += 'X'
      sterm += str(q)
      sterm += 'X'
      sterm += str(p)
      sterm += '+'
      sterm += 'X'
      sterm += str(s)
      sterm += 'Y'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(q)
      sterm += 'X'
      sterm += str(p)
      sterm += '+'
      sterm += 'Y'
      sterm += str(s)
      sterm += 'Y'
      sterm += str(r)
      sterm += 'Y'
      sterm += str(q)
      sterm += 'Y'
      sterm += str(p)
      sterm += ')'
  symterm=''.join(sterm)
  return symterm

def SymbolicJordanWigner2(term,coefficient):
  termlen=len(term)
  if termlen==2:
    if abs(term[1])>abs(term[0]):
      p = abs(term[1])
      q = abs(term[0])
    else:
      p = abs(term[0])
      q = abs(term[1])
    term1=[]
    term2=[]
    aux=range(2)
    coeff=''.join(str(0.5*coefficient))
    # term 1
    for i in range(q+1,p):
      aux[0] = 'Z'
      aux[1] = str(i)
      part = ''.join(aux)
      term1.append(part) 
    aux[0] = 'X'
    aux[1] = str(q)
    part = ''.join(aux)
    term1.append(part)
    aux[0] = 'X'
    aux[1] = str(p)
    part = ''.join(aux)
    term1.append(part)
    term1.append(str(coeff))
    # term 2
    for i in range(q+1,p):
      aux[0] = 'Z'
      aux[1] = str(i)
      part = ''.join(aux)
      term2.append(part) 
    aux[0] = 'Y'
    aux[1] = str(q)
    part = ''.join(aux)
    term2.append(part)
    aux[0] = 'Y'
    aux[1] = str(p)
    part = ''.join(aux)
    term2.append(part)
    term2.append(str(coeff))
    sterm=range(2)
    term1=' '.join(term1)
    term2=' '.join(term2)
    sterm[0]=term1
    sterm[1]=term2
  elif termlen==4:
    if abs(term[0])==abs(term[2]): 
      q=abs(term[0])
      p=abs(term[1])
      r=abs(term[3])
      sign=-1
      opt=1
    elif abs(term[0])==abs(term[3]):
      q=abs(term[0])
      p=abs(term[1])
      r=abs(term[2])
      sign=1
      opt=1
    elif abs(term[1])==abs(term[2]): 
      q=abs(term[1])
      p=abs(term[0])
      r=abs(term[3])
      sign=1
      opt=1
    elif abs(term[1])==abs(term[3]):
      q=abs(term[1])
      p=abs(term[0])
      r=abs(term[2])
      sign=-1
      opt=1
    else:
      opt=2
      sign=1
      if (abs(term[0])>abs(term[2]) and abs(term[1])>abs(term[3])) or (abs(term[0])>abs(term[3]) and abs(term[1])>abs(term[2])):
        if abs(term[1])>abs(term[0]):
          p=abs(term[1])
          q=abs(term[0])
          sign=-1*sign
        else:
          p=abs(term[0])
          q=abs(term[1])
          sign=1*sign
        if abs(term[3])>abs(term[2]):
          r=abs(term[3])
          s=abs(term[2])
          sign=-1*sign
        else:
          r=abs(term[2])
          s=abs(term[3])
          sign=1*sign
      else:
        if abs(term[1])>abs(term[0]):
          r=abs(term[1])
          s=abs(term[0])
          sign=-1*sign
        else:
          r=abs(term[0])
          s=abs(term[1])
          sign=1*sign
        if abs(term[3])>abs(term[2]):
          p=abs(term[3])
          q=abs(term[2])
          sign=-1*sign
        else:
          p=abs(term[2])
          q=abs(term[3])
          sign=1*sign
    if opt==1:
      if r>p:
        aux=r
        r=p
        p=aux
      term1=[]
      term2=[]
      term3=[]
      term4=[]
      aux=range(2)
      coeff=''.join(str(sign*coefficient))
      # term 1
      for i in range(r+1,p):
        aux[0] = 'Z'
        aux[1] = str(i)
        part = ''.join(aux)
        term1.append(part) 
      aux[0] = 'X'
      aux[1] = str(r)
      part = ''.join(aux)
      term1.append(part)
      aux[0] = 'X'
      aux[1] = str(p)
      part = ''.join(aux)
      term1.append(part)
      term1.append(str(coeff))
      # term 2
      for i in range(r+1,p):
        aux[0] = 'Z'
        aux[1] = str(i)
        part = ''.join(aux)
        term2.append(part) 
      aux[0] = 'Y'
      aux[1] = str(r)
      part = ''.join(aux)
      term2.append(part)
      aux[0] = 'Y'
      aux[1] = str(p)
      part = ''.join(aux)
      term2.append(part)
      term2.append(str(coeff))
      # term 3
      coeff=''.join(str(-sign*coefficient))
      for i in range(r+1,p):
        aux[0] = 'Z'
        aux[1] = str(i)
        part = ''.join(aux)
        term3.append(part) 
      aux[0] = 'Z'
      aux[1] = str(q)
      part = ''.join(aux)
      term3.append(part)
      aux[0] = 'X'
      aux[1] = str(r)
      part = ''.join(aux)
      term3.append(part)
      aux[0] = 'X'
      aux[1] = str(p)
      part = ''.join(aux)
      term3.append(part)
      term3.append(str(coeff))
      # term 4
      for i in range(r+1,p):
        aux[0] = 'Z'
        aux[1] = str(i)
        part = ''.join(aux)
        term4.append(part) 
      aux[0] = 'Z'
      aux[1] = str(q)
      part = ''.join(aux)
      term4.append(part)
      aux[0] = 'Y'
      aux[1] = str(r)
      part = ''.join(aux)
      term4.append(part)
      aux[0] = 'Y'
      aux[1] = str(p)
      part = ''.join(aux)
      term4.append(part)
      term4.append(str(coeff))
      sterm=range(4)
      term1=' '.join(term1)
      term2=' '.join(term2)
      term3=' '.join(term3)
      term4=' '.join(term4)
      sterm[0]=term1
      sterm[1]=term2
      sterm[2]=term3
      sterm[3]=term4
    elif opt==2:
      aux=range(2)
      sterm=range(8)
      XY=['XXXX','XXYY','XYXY','YXXY','YXYX','YYXX','XYYX','YYYY']
      XYsigns=[1,-1,1,1,1,-1,1,1]
      for j in range(8):
        term1=[]
        coeff=''.join(str(XYsigns[j]*sign*coefficient/8.0))
        # term1
        for i in range(s+1,r):
          aux[0] = 'Z'
          aux[1] = str(i)
          part = ''.join(aux)
          term1.append(part) 
        for i in range(q+1,p):
          aux[0] = 'Z'
          aux[1] = str(i)
          part = ''.join(aux)
          term1.append(part) 
        aux[0] = XY[j][0]
        aux[1] = str(s)
        part = ''.join(aux)
        term1.append(part)
        aux[0] = XY[j][1]
        aux[1] = str(r)
        part = ''.join(aux)
        term1.append(part)
        aux[0] = XY[j][2]
        aux[1] = str(q)
        part = ''.join(aux)
        term1.append(part)
        aux[0] = XY[j][3]
        aux[1] = str(p)
        part = ''.join(aux)
        term1.append(part)
        term1.append(str(coeff))
        term1=' '.join(term1)
        sterm[j]=term1
  symterm=sterm
  return symterm

# Unit tests.
def main():

  # Test parameters.
  molecule = str(argv[1])
  basis = str(argv[2])
  try:
    cc_form = bool(argv[3])
  except:
    cc_form = False
  try:
    run_type = str(argv[4])
  except:
    run_type = 'ucc'

  try:
    dirpath = str(argv[5])
  except:
    dirpath = None


  # Get Hamiltonian
  print 'dirpath',dirpath
  fci_hamiltonian = GetHamiltonian(molecule, basis, n_excitations='FCI')
  cisd_hamiltonian = GetHamiltonian(molecule, basis, n_excitations=2)
  repulsion, coefficients, ham_terms = commutators.GetHamiltonianTerms(molecule, basis)
  print 'Number of terms %i' % len(ham_terms)
  print "terms:", ham_terms
  n_electrons = commutators.ElectronCount(molecule)
  n_orbitals = commutators.OrbitalCount(ham_terms)
  print "n orbitals:",n_orbitals
  basis_parsed=basis.split('-')

  print basis_parsed
  print basis_parsed[0]
  energies=[]

  # Get states and energies.
  fci_state = SparseDiagonalize(fci_hamiltonian)
  print fci_state
  cisd_state = SparseDiagonalize(cisd_hamiltonian)
  print cisd_state
  hf_state = HartreeFockState(n_electrons, n_orbitals)
  fci_energy = Expectation(fci_hamiltonian, fci_state)
  cisd_energy = Expectation(fci_hamiltonian, cisd_state)
  hf_energy = Expectation(fci_hamiltonian, hf_state)
  print basis_parsed
  energies=[basis_parsed[0],str(hf_energy+repulsion),str(cisd_energy+repulsion),str(fci_energy+repulsion)]

  # Get terms
  initial_guess = []
  terms = []
  # JRF
  jw_terms = GetJordanWignerTerms(n_orbitals)
  counter=0
  coeffs=[]
  thres=1E-08

  if run_type=='troyer':
    
    for coefficient, term in zip(coefficients, ham_terms):
      # JRF
      counter=counter+1
      hterm=MatrixForm(1., term, jw_terms, add_conjugates=True, anti_hermitian=cc_form)
      hcontribution=Expectation(hterm, cisd_state)
      initial_guess += [hcontribution]
      terms += [term]

  elif run_type=='troyer-wc':

    # JRF
    for coefficient, term in zip(coefficients, ham_terms):
      # JRF
      print term
      hterm=MatrixForm(1., term, jw_terms, add_conjugates=True, anti_hermitian=cc_form)
      hcontribution=Expectation(hterm, cisd_state)
      if commutators.GetConjugate(term):
        counter=counter+1
        initial_guess += [hcontribution]
        terms += [term]

  elif run_type=='ucc':

    opt=1
    if opt==1:
      n_excitations=2
      print 'electrons:',n_electrons
      ncore=0
      occ=range(ncore+1,n_electrons+1)
      vir=range(n_electrons+1,n_orbitals+1)
      operators=[]
      for n in range(1,n_excitations+1):
        for cosa1 in combinations(occ,n):
          print "cosa1",cosa1
          for cosa2 in combinations(vir,n):
            print "cosa2",cosa2
            cosita=[]
            cosita.extend(cosa2[::-1])
            cosita.extend([x * -1 for x in cosa1[::-1]])
            operators.append(cosita)
      print 'operators:', operators
    else:
      operators=[[3,4,-2,-1],[6,5,-2,-1]]
    # JRF
    for term in operators:
      # JRF
      print term
      hterm=MatrixForm(1., term, jw_terms, add_conjugates=True, anti_hermitian=False)
      hcontribution=Expectation(hterm, cisd_state)
      # print "hamiltonian terms"
      # print ham_terms
      # location=ham_terms.index(term)
      # hcontribution=coefficients[location]
      counter=counter+1
      initial_guess += [hcontribution]
      terms += [term]
    
  print initial_guess

  filename1=molecule+basis+'.out'
  output1=open(filename1,'a')
  # output2=open('OptimalParameters_H3pd__CCD.out','a')
  print 'This is the number of terms for VQE:',counter
  ncalls, solution, variational_energy = VariationallyMinimize(
      terms, hf_state, initial_guess, fci_hamiltonian, cc_form)
  print 'Variationally optimal energy is %s.\n' % repr(float(variational_energy+repulsion))
  diff=variational_energy-fci_energy
  print 'Data %f %s %i %s.\n' % (thres,repr(float(variational_energy)),counter,repr(float(diff)))
  print 'Optimal parameters \n'
  for t, ov in zip(terms,solution):
    if abs(ov)>1E-6:
      print t,ov
  print energies
  # Obtain variational solution.
  print 'Analyzing %s in the %s basis.\n' % (molecule, basis)
  print 'Hartree-Fock energy is %s.' % repr(float(hf_energy))
  print '\nExact (FCI) energy is %s.' % repr(float(fci_energy))
  print 'CISD energy is %s.' % repr(float(cisd_energy))
  print 'Hartree-Fock energy is %s.' % repr(float(hf_energy))

  # writing results
  energies.append(str(variational_energy+repulsion))
  energies.append(str(diff))
  energies.append(ncalls)
  energies.append(counter)
  output1.write((" ".join(str(i) for i in energies)+'\n'))
  output1.close()
  # output2.write((basis_parsed[0]+" ".join(str(i) for i in solution )+'\n'))
  # output2.close()

# Run.
if __name__ == '__main__':
  main()