def test_condense_linear_from_file_fmr_h_ch4_fchk():
# expected populations of CH4 computed with HORTON
with path('chemtools.data', 'ch4_uhf_ccpvdz.fchk') as fname:
model1 = CondensedConceptualDFT.from_file(fname, "linear", "FMR", "h")
model2 = CondensedConceptualDFT.from_file([fname], "linear", "FMR",
"h")
mol = Molecule.from_file(fname)
grid = MolecularGrid.from_molecule(mol, specs='insane', rotate=False)
model3 = CondensedConceptualDFT.from_file(fname,
"linear",
"FMR",
"h",
grid=grid)
model4 = CondensedConceptualDFT.from_file([fname],
"linear",
"FMR",
"h",
grid=grid)
expected = np.array(
[6.11301651, 0.97175462, 0.97175263, 0.9717521, 0.97174353])
# check using fname given as a string
check_condensed_reactivity(model1, "linear", expected, None, None, 10,
0.736396)
# check using fname given as a list
check_condensed_reactivity(model2, "linear", expected, None, None, 10,
0.736396)
# check using fname as a string & passing grid
check_condensed_reactivity(model3, "linear", expected, None, None, 10,
0.736396)
# check using fname as a list & passing grid
check_condensed_reactivity(model4, "linear", expected, None, None, 10,
0.736396)
def test_condense_quadratic_from_molecule_fmr_mbis_ch4():
# expected populations of CH4 computed with HORTON
with path('chemtools.data', 'ch4_uhf_ccpvdz.wfn') as fname:
molecule = Molecule.from_file(fname)
grid = MolecularGrid.from_molecule(molecule, 'fine')
part = DensPart.from_molecule(molecule, scheme='mbis', grid=grid)
expected = np.array(
[6.46038055, 0.88489494, 0.88492901, 0.88493897, 0.88492396])
computed = part.numbers - part.charges
assert np.all(abs(expected - computed) < 1.e-2)
assert np.all(abs(part.condense_to_atoms(part.density) - computed) < 1.e-2)
def _get_eos(filename, scheme):
# build proatom database
atoms = glob.glob('chemtools/data/atom_0*')
proatomdb = ProAtomDB.from_files(atoms, "power:5e-8:20:40:146")
# load molecule & make grid, denspart, and eos instances
with path('chemtools.data', filename) as file_path:
mol = Molecule.from_file(file_path)
grid = MolecularGrid.from_molecule(mol,
specs='power:5e-8:20:40:146',
k=4,
rotate=False)
part = DensPart.from_molecule(mol,
scheme=scheme,
grid=grid,
local=False,
proatomdb=proatomdb)
return EOS(mol, part)
