def gathermo_vecs(flist, act_orbs):
'''
input
flist - chkfile list
act_orbs - orbitals you want to optimize basis for
output
vecs_list - vectors list, shape: act_mo x nvectors x ncomps
ovlp - overlap necessary for constraints
'''
vecs_list = []
for f, a in zip(flist, act_orbs):
mol = lib.chkfile.load_mol(f)
m = ROHF(mol)
m.__dict__.update(lib.chkfile.load(f, 'scf'))
vecs = m.mo_coeff[:, a].T
vecs_list.append(vecs)
vecs_list = np.array(vecs_list)
vecs_list = np.einsum('ijk->jik', vecs_list)
return vecs_list, m.get_ovlp()
m.__dict__.update(lib.chkfile.load('rohf/Cuvtz_r1.725_s1_ROHF_0.chk', 'scf'))
for i in (mol.basis["Cu"]):
if (len(cu_basis) < 2):
if (i[0] == 0): cu_basis.append(i)
elif (len(cu_basis) == 2):
if (i[0] == 1): cu_basis.append(i)
elif (len(cu_basis) == 3):
if (i[0] == 2): cu_basis.append(i)
else:
pass
o_basis = []
for i in (mol.basis["O"]):
if (len(o_basis) == 0):
if (i[0] == 0): o_basis.append(i)
elif (len(o_basis) == 1):
if (i[0] == 1): o_basis.append(i)
else:
pass
minbasis = {'Cu': cu_basis, 'O': o_basis}
#Build IAOs
s = m.get_ovlp()
a = lo.iao.iao(mol, mo_coeff, minao=minbasis)
a = lo.vec_lowdin(a, s)
a.dump('b3lyp_iao_b.pickle')
#Plot IAOs
m.mo_coeff[:, :a.shape[1]] = a
print_qwalk_mol(mol, m, method='scf', basename='qwalk/b3lyp_iao_b')