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_fake(scheme, pseudo, dowcor, local, absmean, **kwargs):
if pseudo:
sys, ugrid, mol_dens, proatomdb = get_fake_pseudo_oo()
else:
sys, ugrid, mol_dens, proatomdb = get_fake_co()
if dowcor:
wcor_numbers = range(119)
else:
wcor_numbers = []
CPartClass = cpart_schemes[scheme]
cpart = CPartClass(sys, ugrid, local, mol_dens, proatomdb, wcor_numbers,
**kwargs)
cpart.do_charges()
charges = cpart['charges']
print abs(charges.sum()), abs(charges).mean(), abs(
abs(charges).mean() - absmean)
assert abs(charges.sum()) < 1e-2
assert abs(abs(charges).mean() - absmean) < 1e-3
if kwargs.get('greedy', False):
# In case of a greedy algorithm, one should compare the proatoms
# in the partitioning object with proatoms directly evaluate with the
# proatom splines
check_proatom_splines(cpart)
def check_msa_hf_lan(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_lan()
kwargs['proatomdb'] = proatomdb
# Get the IOData
fn_fchk = context.get_fn('test/monosilicic_acid_hf_lan.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, both with local and global grids
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)
wpart.do_charges()
assert abs(wpart['charges'] - expecting).max() < 4e-3
check_proatom_splines(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 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_msa_hf_lan(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_lan()
kwargs['proatomdb'] = proatomdb
# Get the IOData
fn_fchk = context.get_fn('test/monosilicic_acid_hf_lan.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, both with local and global grids
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)
wpart.do_charges()
assert abs(wpart['charges'] - expecting).max() < 4e-3
if kwargs.get('greedy', False):
check_proatom_splines(wpart)
def check_fake(scheme, pseudo, dowcor, local, absmean, **kwargs):
if pseudo:
coordinates, numbers, pseudo_numbers, ugrid, moldens, proatomdb = get_fake_pseudo_oo()
else:
coordinates, numbers, ugrid, moldens, proatomdb = get_fake_co()
pseudo_numbers = numbers.astype(float)
if dowcor:
wcor_numbers = range(119)
else:
wcor_numbers = []
CPartClass = cpart_schemes[scheme]
cpart = CPartClass(coordinates, numbers, pseudo_numbers, ugrid,
moldens, proatomdb, local=local,
wcor_numbers=wcor_numbers, **kwargs)
assert cpart.local == local
cpart.do_charges()
charges = cpart['charges']
#print abs(charges.sum()), abs(charges).mean(), abs(abs(charges).mean() - absmean)
assert abs(charges.sum()) < 1e-2
assert abs(abs(charges).mean() - absmean) < 1e-3
if kwargs.get('greedy', False):
# In case of a greedy algorithm, one should compare the proatoms
# in the partitioning object with proatoms directly evaluate with the
# proatom splines
check_proatom_splines(cpart)
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)
def check_msa_hf_lan(scheme, expecting, needs_padb=True, **kwargs):
if needs_padb:
proatomdb = get_proatomdb_hf_lan()
kwargs['proatomdb'] = proatomdb
# Get the molecule
fn_fchk = context.get_fn('test/monosilicic_acid_hf_lan.fchk')
sys = System.from_file(fn_fchk)
# Create a grid for the partitioning
rtf = ExpRTransform(5e-4, 2e1, 120)
rgrid = RadialGrid(rtf)
# Do the partitioning, both with local and global grids
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)
wpart.do_charges()
assert abs(wpart['charges'] - expecting).max() < 4e-3
if kwargs.get('greedy', False):
check_proatom_splines(wpart)