def test_optimize_contraction(self):
bas = gto.parse(r'''
#BASIS SET: (6s,3p) -> [2s,1p]
C S
2.9412494 -0.09996723
0.6834831 0.39951283
0.2222899 0.70011547
C S
2.9412494 0.15591627
0.6834831 0.60768372
0.2222899 0.39195739
''',
optimize=True)
self.assertEqual(len(bas), 1)
bas = [[
1, 0, [2.9412494, -0.09996723], [0.6834831, 0.39951283],
[0.2222899, 0.70011547]
],
[
1, 1, [2.9412494, -0.09996723], [0.6834831, 0.39951283],
[0.2222899, 0.70011547]
],
[
1, 1, [2.9412494, 0.15591627], [0.6834831, 0.60768372],
[0.2222899, 0.39195739]
]]
bas = gto.basis.parse_nwchem.optimize_contraction(bas)
self.assertEqual(len(bas), 2)
def test_optimize_contraction(self):
bas = gto.parse(r'''
#BASIS SET: (6s,3p) -> [2s,1p]
C S
2.9412494 -0.09996723
0.6834831 0.39951283
0.2222899 0.70011547
C S
2.9412494 0.15591627
0.6834831 0.60768372
0.2222899 0.39195739
''', optimize=True)
self.assertEqual(len(bas), 1)
bas = [[1, 0,
[2.9412494, -0.09996723],
[0.6834831, 0.39951283],
[0.2222899, 0.70011547]],
[1, 1,
[2.9412494, -0.09996723],
[0.6834831, 0.39951283],
[0.2222899, 0.70011547]],
[1, 1,
[2.9412494, 0.15591627],
[0.6834831, 0.60768372],
[0.2222899, 0.39195739]]]
bas = gto.basis.parse_nwchem.optimize_contraction(bas)
self.assertEqual(len(bas), 2)
def test_remove_zero(self):
bas = gto.parse(r'''
C S
7.2610457926 0.0000000000 0.0000000000
2.1056583087 0.0000000000 0.0000000000
0.6439906571 1.0000000000 0.0000000000
0.0797152017 0.0000000000 1.0000000000
0.0294029590 0.0000000000 0.0000000000
''')
self.assertEqual(len(bas[0]), 3)
bas = [[0, 0,
[7.2610457926, 0.0000000000, 0.0000000000],
[2.1056583087, 0.0000000000, 0.0000000000],
[0.6439906571, 1.0000000000, 0.0000000000],
[0.0797152017, 0.0000000000, 1.0000000000],
[0.0294029590, 0.0000000000, 0.0000000000]]]
bas = gto.basis.parse_nwchem.remove_zero(bas)
self.assertEqual(len(bas[0]), 4)
def test_remove_zero(self):
bas = gto.parse(r'''
C S
7.2610457926 0.0000000000 0.0000000000
2.1056583087 0.0000000000 0.0000000000
0.6439906571 1.0000000000 0.0000000000
0.0797152017 0.0000000000 1.0000000000
0.0294029590 0.0000000000 0.0000000000
''')
self.assertEqual(len(bas[0]), 3)
bas = [[0, 0,
[7.2610457926, 0.0000000000, 0.0000000000],
[2.1056583087, 0.0000000000, 0.0000000000],
[0.6439906571, 1.0000000000, 0.0000000000],
[0.0797152017, 0.0000000000, 1.0000000000],
[0.0294029590, 0.0000000000, 0.0000000000]]]
bas = gto.basis.parse_nwchem.remove_zero(bas)
self.assertEqual(len(bas[0]), 4)
def gen_qe_gto(qe_info, bset, x=[], fname='pyscf.orbitals.h5', prec=1e-12):
""" Writes periodic AO basis set in real space to hdf5 file.
This routine constructs a new gaussian basis set from a OptimizableBasisSet
object and an array of optimizable parameters.
With the resulting basis set, a new gto.Cell object is constructed consistent
with the QE calculation and used to generate the periodic AO basis set.
Parameters
----------
qe_info: Python Dictionary.
Dictionary with information from QE calculation, generated by qe_driver_init.
bset: Object of type OptimizableBasisSet.
Contains information about a (possibly dynamic) basis set.
x: fp array. Default: [] (no variable parameters in bset)
Array with variational parameters in the bset object.
fname: string. Default: 'pyscf.orbitals.h5'
Name of hdf5 file.
prec: floating point number. Default: 1e-12
Precision used to generate AO orbitals in real space. Controls sum over periodic images.
Returns
-------
nao: integer
Number of atomic orbitals generates.
"""
assert (len(x) == bset.number_of_params)
basis = {}
for I, atm in enumerate(qe_info['species']):
basis.update({atm: molgto.parse(bset.basis_str(atm, x))})
cell = make_cell(qe_info['latt'],
qe_info['species'],
qe_info['at_id'],
qe_info['at_pos'],
basis_=basis,
mesh=qe_info['mesh'],
prec=prec)
nao = cell.nao_nr()
write_esh5_orbitals(cell, qe_info['outdir'] + fname, kpts=qe_info['kpts'])
return nao
'''
Use gto.basis.parse and gto.basis.load functions to input user-specified basis functions.
'''
dirnow = os.path.realpath(os.path.join(__file__, '..'))
basis_file_from_user = os.path.join(dirnow, 'h_sto3g.dat')
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = {'O': gto.parse('''
# Parse NWChem format basis string (see https://bse.pnl.gov/bse/portal).
# Comment lines are ignored
#BASIS SET: (6s,3p) -> [2s,1p]
O S
130.7093200 0.15432897
23.8088610 0.53532814
6.4436083 0.44463454
O SP
5.0331513 -0.09996723 0.15591627
1.1695961 0.39951283 0.60768372
0.3803890 0.70011547 0.39195739
'''),
'H1': gto.load(basis_file_from_user, 'H'),
'H2': gto.load('sto-3g', 'He') # or use basis of another atom
}
)
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = {'O': 'unc-ccpvdz', # prefix "unc-" will uncontract the ccpvdz basis.
# It is equivalent to assigning
def test_format_basis(self):
mol = gto.M(atom='''O 0 0 0; 1 0 1 0; H 0 0 1''', basis={8: 'ccpvdz'})
self.assertEqual(mol.nao_nr(), 14)
mol = gto.M(atom='''O 0 0 0; H:1 0 1 0; H@2 0 0 1''',
basis={
'O': 'ccpvdz',
'H:1': 'sto3g',
'H': 'unc-iglo3'
})
self.assertEqual(mol.nao_nr(), 32)
mol = gto.M(atom='''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis={
'default': ('6-31g', [[0, [.05, 1.]], []]),
'H2': 'sto3g'
})
self.assertEqual(mol.nao_nr(), 14)
mol = gto.M(
atom='''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis={
'H1':
gto.parse('''
# Parse NWChem format basis string (see https://bse.pnl.gov/bse/portal).
# Comment lines are ignored
#BASIS SET: (6s,3p) -> [2s,1p]
H S
2.9412494 -0.09996723
0.6834831 0.39951283
0.2222899 0.70011547
H S
2.9412494 0.15591627
0.6834831 0.60768372
0.2222899 0.39195739
''',
optimize=True),
'O':
'unc-ccpvdz',
'H2':
gto.load('sto-3g', 'He') # or use basis of another atom
})
self.assertEqual(mol.nao_nr(), 29)
mol = gto.M(
atom='''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis={
'H': [
'sto3g', '''unc
C S
71.6168370 0.15432897
13.0450960 0.53532814
3.5305122 0.44463454
C SP
2.9412494 -0.09996723 0.15591627
0.6834831 0.39951283 0.60768372
0.2222899 0.70011547 0.39195739
'''
],
'O':
mol.expand_etbs([
(0, 4, 1.5, 2.2), # s-function
(1, 2, 0.5, 2.2)
]) # p-function
})
self.assertEqual(mol.nao_nr(), 42)
mol = gto.M(atom='''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis=('sto3g', 'ccpvdz', '3-21g',
gto.etbs([(0, 4, 1.5, 2.2), (1, 2, 0.5, 2.2)]),
[[0, numpy.array([1e3, 1.])]]))
self.assertEqual(mol.nao_nr(), 77)
mol.atom = 'Hg'
mol.basis = 'ccpvdz'
self.assertRaises(RuntimeError, mol.build)
mol.basis = {
'H':
gto.parse('''
H S
23.843185 0.00411490
10.212443 0.01046440
4.374164 0.02801110
1.873529 0.07588620
0.802465 0.18210620
0.343709 0.34852140
0.147217 0.37823130
0.063055 0.11642410
H S
0.029292 1.00000000
H S
0.091791 1.00000000
H S
0.287637 1.00000000
H P
0.106105 1.00000000
H P
0.393954 1.00000000
H P
1.462694 1.00000000
H D
0.295883 1.00000000
H D
1.065841 1.00000000
'''),
'O':
gto.parse('''
def run():
### PYSCF INPUT
r0 = 1.50
molecule = '''
Cr
Cr 1 {}
'''.format(r0)
charge = 0
spin = 0
basis_set = 'def2-svp'
### TPSCI BASIS INPUT
orb_basis = 'scf'
cas = True
cas_nstart = 12
cas_nstop = 42
loc_start = 1
loc_stop = 6
cas_nel = 24
def ordering_diatomics_cr(mol, C):
# {{{
##DZ basis diatomics reordering with frozen 1s
orb_type = ['s', 'pz', 'dz', 'px', 'dxz', 'py', 'dyz', 'dx2-y2', 'dxy']
ref = np.zeros(C.shape[1])
## Find dimension of each space
dim_orb = []
for orb in orb_type:
print("Orb type", orb)
idx = 0
for label in mol.ao_labels():
if orb in label:
#print(label)
idx += 1
##frozen 1s orbitals
if orb == 's':
idx -= 6
elif orb == 'px':
idx -= 2
elif orb == 'py':
idx -= 2
elif orb == 'pz':
idx -= 2
dim_orb.append(idx)
print(idx)
new_idx = []
## Find orbitals corresponding to each orb space
for i, orb in enumerate(orb_type):
print("Orbital type:", orb)
from pyscf import mo_mapping
s_pop = mo_mapping.mo_comps(orb, mol, C)
print(s_pop)
ref += s_pop
cas_list = s_pop.argsort()[-dim_orb[i]:]
print('cas_list', np.array(cas_list))
new_idx.extend(cas_list)
#print(orb,' population for active space orbitals', s_pop[cas_list])
ao_labels = mol.ao_labels()
#idx = mol.search_ao_label(['N.*s'])
#for i in idx:
# print(i, ao_labels[i])
print(ref)
print(new_idx)
for label in mol.ao_labels():
print(label)
return new_idx
# }}}
# basis is SVP read comments by alex thom paper DOI:10.1021/acs.jctc.9b01023
from pyscf import gto
basis_set = {
'Cr':
gto.parse('''
BASIS "ao basis" PRINT
#BASIS SET: (14s,8p,5d) -> [5s,2p,2d]
Cr S
51528.086349 0.14405823106E-02
7737.2103487 0.11036202287E-01
1760.3748470 0.54676651806E-01
496.87706544 0.18965038103
161.46520598 0.38295412850
55.466352268 0.29090050668
Cr S
107.54732999 -0.10932281100
12.408671897 0.64472599471
5.0423628826 0.46262712560
Cr S
8.5461640165 -0.22711013286
1.3900441221 0.73301527591
0.56066602876 0.44225565433
Cr S
0.71483705972E-01 1.0000000000
Cr S
0.28250687604E-01 1.0000000000
Cr P
640.48536096 0.96126715203E-02
150.69711194 0.70889834655E-01
47.503755296 0.27065258990
16.934120165 0.52437343414
6.2409680590 0.34107994714
Cr P
3.0885463206 0.33973986903
1.1791047769 0.57272062927
0.43369774432 0.24582728206
Cr D
27.559479426 0.30612488044E-01
7.4687020327 0.15593270944
2.4345903574 0.36984421276
0.78244754808 0.47071118077
Cr D
0.21995774311 0.33941649889
END''')
}
### TPSCI CLUSTER INPUT
init_fspace = ((1, 1), (3, 3), (3, 3), (3, 3), (1, 1), (1, 1))
blocks = [
range(0, 4),
range(4, 10),
range(10, 16),
range(16, 22),
range(22, 26),
range(26, 30)
]
# Integrals from pyscf
#Integrals from pyscf
pmol = PyscfHelper()
pmol.init(molecule,
charge,
spin,
basis_set,
orb_basis,
cas_nstart=cas_nstart,
cas_nstop=cas_nstop,
cas_nel=cas_nel,
cas=True,
loc_nstart=loc_start,
loc_nstop=loc_stop)
h = pmol.h
g = pmol.g
ecore = pmol.ecore
print("Ecore:%16.8f" % ecore)
C = pmol.C
K = pmol.K
mol = pmol.mol
mo_energy = pmol.mf.mo_energy
dm_aa = pmol.dm_aa
dm_bb = pmol.dm_bb
do_tci = 1
#cluster using hcore
idx = ordering_diatomics_cr(mol, C)
h, g = reorder_integrals(idx, h, g)
C = C[:, idx]
mo_energy = mo_energy[idx]
dm_aa = dm_aa[:, idx]
dm_aa = dm_aa[idx, :]
dm_bb = dm_bb[:, idx]
dm_bb = dm_bb[idx, :]
print(dm_aa)
from pyscf import molden
molden.from_mo(pmol.mol, 'h8.molden', C)
print(h)
mol = pmol.mol
if mol.symmetry == True:
from pyscf import symm
mo = symm.symmetrize_orb(mol, C)
osym = symm.label_orb_symm(mol, mol.irrep_name, mol.symm_orb, mo)
#symm.addons.symmetrize_space(mol, mo, s=None, check=True, tol=1e-07)
for i in range(len(osym)):
print("%4d %8s %16.8f" % (i + 1, osym[i], mo_energy[i]))
clusters, clustered_ham, ci_vector = system_setup(h,
g,
ecore,
blocks,
init_fspace,
cmf_maxiter=20,
cmf_dm_guess=(dm_aa,
dm_bb),
cmf_diis=True,
max_roots=100,
delta_elec=3)
ndata = 0
for ci in clusters:
for o in ci.ops:
for f in ci.ops[o]:
ndata += ci.ops[o][f].size * ci.ops[o][f].itemsize
print(" Amount of data stored in TDMs: %12.2f Gb" % (ndata * 1e-9))
init_fspace = ((1, 1), (3, 3), (3, 3), (3, 3), (1, 1), (1, 1))
ci_vector, pt_vector, etci, etci2, t_conv = bc_cipsi_tucker(
ci_vector.copy(),
clustered_ham,
pt_type='mp',
thresh_cipsi=1e-3,
thresh_ci_clip=1e-6,
max_tucker_iter=4,
nbody_limit=4,
thresh_search=1e-3,
thresh_asci=1e-2,
tucker_state_clip=100, #don't use any pt for tucker
tucker_conv_target=0, #converge variational energy
nproc=None)
ci_vector, pt_vector, etci, etci2, t_conv = bc_cipsi_tucker(
ci_vector.copy(),
clustered_ham,
pt_type='mp',
thresh_cipsi=1e-5,
thresh_ci_clip=1e-7,
max_tucker_iter=2,
nbody_limit=4,
thresh_search=1e-4,
thresh_asci=1e-2,
tucker_state_clip=100, #don't use any pt for tucker
tucker_conv_target=0, #converge variational energy
nproc=None)
ci_vector, pt_vector, etci, etci2, t_conv = bc_cipsi_tucker(
ci_vector.copy(),
clustered_ham,
pt_type='mp',
thresh_cipsi=1e-6,
thresh_ci_clip=1e-8,
max_tucker_iter=2,
nbody_limit=4,
thresh_search=1e-4,
thresh_asci=1e-2,
tucker_state_clip=100, #don't use any pt for tucker
tucker_conv_target=0, #converge variational energy
nproc=None)
ci_vector, pt_vector, etci, etci2, t_conv = bc_cipsi_tucker(
ci_vector.copy(),
clustered_ham,
pt_type='mp',
thresh_cipsi=1e-7,
thresh_ci_clip=1e-9,
max_tucker_iter=4,
nbody_limit=4,
thresh_search=1e-4,
thresh_asci=1e-2,
tucker_state_clip=100, #don't use any pt for tucker
tucker_conv_target=0, #converge variational energy
nproc=None)
tci_dim = len(ci_vector)
ci_vector.print()
ecore = clustered_ham.core_energy
etci += ecore
etci2 += ecore
print(" TCI: %12.9f Dim:%6d" % (etci, tci_dim))
'Al':
Mgto.parse('''
Al S
8.257944 0.003287
4.514245 -0.017168
2.467734 0.069766
1.348998 -0.183475
0.737436 -0.147133
0.403123 0.046882
0.220369 0.308423
0.120466 0.451564
0.065853 0.302904
0.035999 0.079545
Al S
0.236926 1.000000
Al P
1.570603 -0.002645
0.977752 -0.037850
0.608683 0.006636
0.378925 0.089291
0.235893 0.134421
0.146851 0.256105
0.091420 0.238970
0.056912 0.260677
0.035429 0.112350
0.022056 0.052665
Al P
0.202698 1.000000
Al D
0.192882 1.000000
''')
}
def test_format_basis(self):
mol = gto.M(atom = '''O 0 0 0; 1 0 1 0; H 0 0 1''',
basis = {8: 'ccpvdz'})
self.assertEqual(mol.nao_nr(), 14)
mol = gto.M(atom = '''O 0 0 0; H:1 0 1 0; H@2 0 0 1''',
basis = {'O': 'ccpvdz', 'H:1': 'sto3g', 'H': 'unc-iglo3'})
self.assertEqual(mol.nao_nr(), 32)
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = {'default': ('6-31g', [[0, [.05, 1.]], []]), 'H2': 'sto3g'}
)
self.assertEqual(mol.nao_nr(), 14)
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = {'H1': gto.parse('''
# Parse NWChem format basis string (see https://bse.pnl.gov/bse/portal).
# Comment lines are ignored
#BASIS SET: (6s,3p) -> [2s,1p]
H S
2.9412494 -0.09996723
0.6834831 0.39951283
0.2222899 0.70011547
H S
2.9412494 0.15591627
0.6834831 0.60768372
0.2222899 0.39195739
''', optimize=True),
'O': 'unc-ccpvdz',
'H2': gto.load('sto-3g', 'He') # or use basis of another atom
}
)
self.assertEqual(mol.nao_nr(), 29)
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = {'H': ['sto3g', '''unc
C S
71.6168370 0.15432897
13.0450960 0.53532814
3.5305122 0.44463454
C SP
2.9412494 -0.09996723 0.15591627
0.6834831 0.39951283 0.60768372
0.2222899 0.70011547 0.39195739
'''],
'O': mol.expand_etbs([(0, 4, 1.5, 2.2), # s-function
(1, 2, 0.5, 2.2)]) # p-function
}
)
self.assertEqual(mol.nao_nr(), 42)
mol = gto.M(
atom = '''O 0 0 0; H1 0 1 0; H2 0 0 1''',
basis = ('sto3g', 'ccpvdz', '3-21g',
gto.etbs([(0, 4, 1.5, 2.2), (1, 2, 0.5, 2.2)]),
[[0, numpy.array([1e3, 1.])]])
)
self.assertEqual(mol.nao_nr(), 77)
mol.atom = 'Hg'
mol.basis = 'ccpvdz'
self.assertRaises(RuntimeError, mol.build)
def generate_hamiltonian():
### PYSCF INPUT
r0 = 1.50
molecule = '''
Cr
Cr 1 {}
'''.format(r0)
charge = 0
spin = 0
basis_set = 'def2-svp'
### TPSCI BASIS INPUT
orb_basis = 'scf'
cas = True
cas_nstart = 12
cas_nstop = 42
loc_start = 1
loc_stop = 6
cas_nel = 24
def ordering_diatomics_cr(mol,C):
# {{{
##DZ basis diatomics reordering with frozen 1s
orb_type = ['s','pz','dz','px','dxz','py','dyz','dx2-y2','dxy']
ref = np.zeros(C.shape[1])
## Find dimension of each space
dim_orb = []
for orb in orb_type:
print("Orb type",orb)
idx = 0
for label in mol.ao_labels():
if orb in label:
#print(label)
idx += 1
##frozen 1s orbitals
if orb == 's':
idx -= 6
elif orb == 'px':
idx -=2
elif orb == 'py':
idx -=2
elif orb == 'pz':
idx -=2
dim_orb.append(idx)
print(idx)
new_idx = []
## Find orbitals corresponding to each orb space
for i,orb in enumerate(orb_type):
print("Orbital type:",orb)
from pyscf import mo_mapping
s_pop = mo_mapping.mo_comps(orb, mol, C)
print(s_pop)
ref += s_pop
cas_list = s_pop.argsort()[-dim_orb[i]:]
print('cas_list', np.array(cas_list))
new_idx.extend(cas_list)
#print(orb,' population for active space orbitals', s_pop[cas_list])
ao_labels = mol.ao_labels()
#idx = mol.search_ao_label(['N.*s'])
#for i in idx:
# print(i, ao_labels[i])
print(ref)
print(new_idx)
for label in mol.ao_labels():
print(label)
return new_idx
# }}}
# basis is SVP read comments by alex thom paper DOI:10.1021/acs.jctc.9b01023
from pyscf import gto
basis_set={'Cr': gto.parse('''
BASIS "ao basis" PRINT
#BASIS SET: (14s,8p,5d) -> [5s,2p,2d]
Cr S
51528.086349 0.14405823106E-02
7737.2103487 0.11036202287E-01
1760.3748470 0.54676651806E-01
496.87706544 0.18965038103
161.46520598 0.38295412850
55.466352268 0.29090050668
Cr S
107.54732999 -0.10932281100
12.408671897 0.64472599471
5.0423628826 0.46262712560
Cr S
8.5461640165 -0.22711013286
1.3900441221 0.73301527591
0.56066602876 0.44225565433
Cr S
0.71483705972E-01 1.0000000000
Cr S
0.28250687604E-01 1.0000000000
Cr P
640.48536096 0.96126715203E-02
150.69711194 0.70889834655E-01
47.503755296 0.27065258990
16.934120165 0.52437343414
6.2409680590 0.34107994714
Cr P
3.0885463206 0.33973986903
1.1791047769 0.57272062927
0.43369774432 0.24582728206
Cr D
27.559479426 0.30612488044E-01
7.4687020327 0.15593270944
2.4345903574 0.36984421276
0.78244754808 0.47071118077
Cr D
0.21995774311 0.33941649889
END''')}
### TPSCI CLUSTER INPUT
init_fspace = ((1, 1),(3, 3),(3, 3),(3, 3), (1, 1), (1, 1))
blocks = [range(0,4),range(4,10),range(10,16),range(16,22),range(22,26),range(26,30)]
# Integrals from pyscf
#Integrals from pyscf
pmol = PyscfHelper()
pmol.init(molecule,charge,spin,basis_set,orb_basis,
cas_nstart=cas_nstart,cas_nstop=cas_nstop,cas_nel=cas_nel,cas=True,
loc_nstart=loc_start,loc_nstop = loc_stop)
h = pmol.h
g = pmol.g
ecore = pmol.ecore
print("Ecore:%16.8f"%ecore)
C = pmol.C
K = pmol.K
mol = pmol.mol
mo_energy = pmol.mf.mo_energy
dm_aa = pmol.dm_aa
dm_bb = pmol.dm_bb
do_fci = 0
do_hci = 0
do_tci = 1
if do_fci:
efci, fci_dim = run_fci_pyscf(h,g,nelec,ecore=ecore)
if do_hci:
ehci, hci_dim = run_hci_pyscf(h,g,nelec,ecore=ecore,select_cutoff=5e-4,ci_cutoff=5e-4)
#cluster using hcore
idx = ordering_diatomics_cr(mol,C)
h,g = reorder_integrals(idx,h,g)
C = C[:,idx]
mo_energy = mo_energy[idx]
dm_aa = dm_aa[:,idx]
dm_aa = dm_aa[idx,:]
dm_bb = dm_bb[:,idx]
dm_bb = dm_bb[idx,:]
print(dm_aa)
from pyscf import molden
molden.from_mo(pmol.mol, 'h8.molden', C)
print(h)
mol = pmol.mol
if mol.symmetry == True:
from pyscf import symm
mo = symm.symmetrize_orb(mol, C)
osym = symm.label_orb_symm(mol, mol.irrep_name, mol.symm_orb, mo)
#symm.addons.symmetrize_space(mol, mo, s=None, check=True, tol=1e-07)
for i in range(len(osym)):
print("%4d %8s %16.8f"%(i+1,osym[i],mo_energy[i]))
clusters = []
for ci,c in enumerate(blocks):
clusters.append(Cluster(ci,c))
print(" Clusters:")
[print(ci) for ci in clusters]
clustered_ham = ClusteredOperator(clusters, core_energy=ecore)
print(" Add 1-body terms")
clustered_ham.add_local_terms()
clustered_ham.add_1b_terms(h)
print(" Add 2-body terms")
clustered_ham.add_2b_terms(g)
# intial state
ci_vector = ClusteredState(clusters)
ci_vector.init(init_fspace)
ci_vector.print()
# do cmf
do_cmf = 1
if do_cmf:
# Get CMF reference
e_cmf, cmf_conv, rdm_a, rdm_b = cmf(clustered_ham, ci_vector, h, g, max_iter=10, dm_guess=(dm_aa, dm_bb), diis=True)
print(" Final CMF Total Energy %12.8f" %(e_cmf + ecore))
# build cluster basis and operator matrices using CMF optimized density matrices
for ci_idx, ci in enumerate(clusters):
print(ci)
fspaces_i = init_fspace[ci_idx]
delta_e = 2
fspaces_i = ci.possible_fockspaces( delta_elec=(fspaces_i[0], fspaces_i[1], delta_e) )
print()
print(" Form basis by diagonalizing local Hamiltonian for cluster: ",ci_idx)
ci.form_fockspace_eigbasis(h, g, fspaces_i, max_roots=100, rdm1_a=rdm_a, rdm1_b=rdm_b)
print(" Build mats for cluster ",ci.idx)
ci.build_op_matrices()
ci.build_local_terms(h,g)
hamiltonian_file = open('hamiltonian_file', 'wb')
pickle.dump(clustered_ham, hamiltonian_file)
print(" Done.")
gto.parse('''
BASIS "ao basis" PRINT
#BASIS SET: (14s,8p,5d) -> [5s,2p,2d]
Cr S
51528.086349 0.14405823106E-02
7737.2103487 0.11036202287E-01
1760.3748470 0.54676651806E-01
496.87706544 0.18965038103
161.46520598 0.38295412850
55.466352268 0.29090050668
Cr S
107.54732999 -0.10932281100
12.408671897 0.64472599471
5.0423628826 0.46262712560
Cr S
8.5461640165 -0.22711013286
1.3900441221 0.73301527591
0.56066602876 0.44225565433
Cr S
0.71483705972E-01 1.0000000000
Cr S
0.28250687604E-01 1.0000000000
Cr P
640.48536096 0.96126715203E-02
150.69711194 0.70889834655E-01
47.503755296 0.27065258990
16.934120165 0.52437343414
6.2409680590 0.34107994714
Cr P
3.0885463206 0.33973986903
1.1791047769 0.57272062927
0.43369774432 0.24582728206
Cr D
27.559479426 0.30612488044E-01
7.4687020327 0.15593270944
2.4345903574 0.36984421276
0.78244754808 0.47071118077
Cr D
0.21995774311 0.33941649889
END''')
