def mulliken_meta(mol, dm_ao, verbose=logger.DEBUG,
pre_orth_method=PRE_ORTH_METHOD, s=None):
'''Mulliken population analysis, based on meta-Lowdin AOs.
'''
nao = mol.nao_nr()
dma = dm_ao[:nao,:nao]
dmb = dm_ao[nao:,nao:]
if s is not None:
assert(s.size == nao**2 or numpy.allclose(s[:nao,:nao], s[nao:,nao:]))
s = s[:nao,:nao]
return uhf.mulliken_meta(mol, (dma,dmb), verbose, pre_orth_method, s)
import pandas as pd
import numpy as np
from pyscf import lib
from pyscf.scf.uhf import mulliken_meta
from pyscf.dft.uks import UKS
mol = lib.chkfile.load_mol('pyscf_driver.py.chkfile')
scf = UKS(mol)
dm = scf.from_chk('pyscf_driver.py.chkfile')
orbdf = pd.DataFrame(mol.spherical_labels(),
columns=['atid', 'at', 'orb', 'type'])
pops = mulliken_meta(mol, dm, verbose=1)
orbdf['up'] = pops[0][0]
orbdf['dn'] = pops[0][1]
orbdf['spin'] = orbdf['up'] - orbdf['dn']
orbdf['charge'] = orbdf['up'] + orbdf['dn']
atdf = orbdf.groupby(['atid', 'at']).agg({
'spin': np.sum,
'charge': np.sum,
'up': np.sum,
'dn': np.sum
})
print(atdf[['up', 'dn', 'charge', 'spin']])
print("Max spin:", abs(atdf['spin']).max())
print("Total charge:", atdf['charge'].sum())
print("Total spin:", atdf['spin'].sum())
