def check_water_hf_sto3g(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_sto3g()
kwargs['proatomdb'] = proatomdb
# Get the IOData
fn_fchk = context.get_fn('test/water_sto3g_hf_g03.fchk')
mol = IOData.from_file(fn_fchk)
dm_full = mol.get_dm_full()
# Create a grid for the partitioning
rtf = ExpRTransform(5e-4, 2e1, 120)
rgrid = RadialGrid(rtf)
# Do the partitioning
mode = 'only' if kwargs.get('local', True) else 'discard'
grid = BeckeMolGrid(mol.coordinates,
mol.numbers,
mol.pseudo_numbers, (rgrid, 110),
random_rotate=False,
mode=mode)
moldens = mol.obasis.compute_grid_density_dm(dm_full, grid.points)
WPartClass = wpart_schemes[scheme]
wpart = WPartClass(mol.coordinates, mol.numbers, mol.pseudo_numbers, grid,
moldens, **kwargs)
names = wpart.do_all()
check_names(names, wpart)
assert abs(wpart['charges'] - expecting).max() < 2e-3
assert abs(wpart['charges'] -
wpart['cartesian_multipoles'][:, 0]).max() < 1e-3
assert abs(wpart['charges'] - wpart['pure_multipoles'][:, 0]).max() < 1e-3
check_proatom_splines(wpart)
return wpart
def check_jbw_coarse(local):
# This test is not supposed to generate meaningful numbers. The cube data
# is too coarse and the reference atoms may have little similarities with
# the DFT density.
# Load the cube file
fn_cube = context.get_fn('test/jbw_coarse_aedens.cube')
sys = System.from_file(fn_cube)
mol_dens = sys.extra['cube_data']
ugrid = sys.grid
# Load some pro-atoms
proatomdb = ProAtomDB.from_refatoms(numbers=[8, 14],
max_kation=0,
max_anion=0)
# Run the partitioning
cpart = HirshfeldCPart(sys, ugrid, local, mol_dens, proatomdb, range(119))
# Do some testing
if local:
names = cpart.do_all()
check_names(names, cpart)
else:
cpart.do_charges()
wcor = cpart.get_wcor()
assert abs(cpart['populations'].sum() -
ugrid.integrate(wcor, mol_dens)) < 1e-10
def check_jbw_coarse(local):
# This test is not supposed to generate meaningful numbers. The cube data
# is too coarse and the reference atoms may have little similarities with
# the DFT density.
# Load the cube file
fn_cube = context.get_fn('test/jbw_coarse_aedens.cube')
mol = IOData.from_file(fn_cube)
moldens = mol.cube_data
ugrid = mol.grid
# Load some pro-atoms
proatomdb = ProAtomDB.from_refatoms(numbers=[8,14], max_kation=0, max_anion=0)
# Run the partitioning
cpart = HirshfeldCPart(mol.coordinates, mol.numbers, mol.pseudo_numbers,
ugrid, moldens, proatomdb, local=local,
wcor_numbers=range(119))
# Do some testing
assert cpart.local == local
if local:
names = cpart.do_all()
check_names(names, cpart)
else:
cpart.do_charges()
wcor = cpart.get_wcor()
assert abs(cpart['pseudo_populations'].sum() - ugrid.integrate(wcor, moldens)) < 1e-10
def check_water_hf_sto3g(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_sto3g()
kwargs['proatomdb'] = proatomdb
# Get the IOData
fn_fchk = context.get_fn('test/water_sto3g_hf_g03.fchk')
mol = IOData.from_file(fn_fchk)
dm_full = mol.get_dm_full()
# Create a grid for the partitioning
rtf = ExpRTransform(5e-4, 2e1, 120)
rgrid = RadialGrid(rtf)
# Do the partitioning
mode = 'only' if kwargs.get('local', True) else 'discard'
grid = BeckeMolGrid(mol.coordinates, mol.numbers, mol.pseudo_numbers, (rgrid, 110), random_rotate=False, mode=mode)
moldens = mol.obasis.compute_grid_density_dm(dm_full, grid.points)
WPartClass = wpart_schemes[scheme]
wpart = WPartClass(mol.coordinates, mol.numbers, mol.pseudo_numbers, grid, moldens, **kwargs)
names = wpart.do_all()
check_names(names, wpart)
assert abs(wpart['charges'] - expecting).max() < 2e-3
assert abs(wpart['charges'] - wpart['cartesian_multipoles'][:,0]).max() < 1e-3
assert abs(wpart['charges'] - wpart['pure_multipoles'][:,0]).max() < 1e-3
if kwargs.get('greedy', False):
check_proatom_splines(wpart)
return wpart
def check_water_hf_sto3g(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_sto3g()
kwargs['proatomdb'] = proatomdb
# Get the molecule
fn_fchk = context.get_fn('test/water_sto3g_hf_g03.fchk')
sys = System.from_file(fn_fchk)
sys.wfn.update_dm('alpha')
# Create a grid for the partitioning
rtf = ExpRTransform(5e-4, 2e1, 120)
rgrid = RadialGrid(rtf)
# Do the partitioning
mode = 'only' if kwargs.get('local', True) else 'discard'
grid = BeckeMolGrid(sys, (rgrid, 110), random_rotate=False, mode=mode)
WPartClass = wpart_schemes[scheme]
wpart = WPartClass(sys, grid, **kwargs)
names = wpart.do_all()
check_names(names, wpart)
assert abs(wpart['charges'] - expecting).max() < 2e-3
assert abs(wpart['charges'] - wpart['cartesian_multipoles'][:,0]).max() < 1e-3
assert abs(wpart['charges'] - wpart['pure_multipoles'][:,0]).max() < 1e-3
if kwargs.get('greedy', False):
check_proatom_splines(wpart)
