def setup_weights(system, grid, dens=None, near=None, far=None):
'''Define a weight function for the ESPCost
**Arguments:**
system
The system for which the weight function must be defined
grid
A UniformGrid object.
**Optional arguments:**
dens
The density-based criterion. This is a three-tuple with rho, lnrho0
and sigma. rho is the atomic or the pro-atomic electron density on
the same grid as the ESP data. lnrho0 and sigma are parameters
defined in JCTC, 3, 1004 (2007), DOI:10.1021/ct600295n. The weight
function takes the form::
exp(-sigma*(ln(rho) - lnrho0)**2)
Note that the density, rho, should not contain depletions in the
atomic cores, as is often encountered with pseudo-potential
computations. In that case it is recommended to construct a
promolecular density as input for this option.
near
Exclude points near the nuclei. This is a dictionary with as items
(number, (R0, gamma)).
far
Exclude points far away. This is a two-tuple: (R0, gamma).
'''
weights = np.ones(grid.shape)
# combine three possible mask functions
if dens is not None:
log.cite('hu2007', 'for the ESP fitting weight function')
rho, lnrho0, sigma = dens
assert (rho.shape == grid.shape).all()
multiply_dens_mask(rho, lnrho0, sigma, weights)
if near is not None:
for i in xrange(system.natom):
pair = near.get(system.numbers[i])
if pair is None:
pair = near.get(0)
if pair is None:
continue
r0, gamma = pair
if r0 > 5*angstrom:
raise ValueError('The wnear radius is excessive. Please keep it below 5 angstrom.')
multiply_near_mask(system.coordinates[i], grid, r0, gamma, weights)
if far is not None:
r0, gamma = far
multiply_far_mask(system.coordinates, grid, r0, gamma, weights)
# double that weight goes to zero at non-periodic edges
return weights
def setup_weights(coordinates, numbers, grid, dens=None, near=None, far=None):
'''Define a weight function for the ESPCost
**Arguments:**
coordinates
An array with shape (N, 3) containing atomic coordinates.
numbers
A vector with shape (N,) containing atomic numbers.
grid
A UniformGrid object.
**Optional arguments:**
dens
The density-based criterion. This is a three-tuple with rho, lnrho0
and sigma. rho is the atomic or the pro-atomic electron density on
the same grid as the ESP data. lnrho0 and sigma are parameters
defined in JCTC, 3, 1004 (2007), DOI:10.1021/ct600295n. The weight
function takes the form::
exp(-sigma*(ln(rho) - lnrho0)**2)
Note that the density, rho, should not contain depletions in the
atomic cores, as is often encountered with pseudo-potential
computations. In that case it is recommended to construct a
promolecular density as input for this option.
near
Exclude points near the nuclei. This is a dictionary with as items
(number, (R0, gamma)).
far
Exclude points far away. This is a two-tuple: (R0, gamma).
'''
natom, coordinates, numbers = typecheck_geo(coordinates,
numbers,
need_pseudo_numbers=False)
weights = np.ones(grid.shape)
# combine three possible mask functions
if dens is not None:
biblio.cite('hu2007', 'for the ESP fitting weight function')
rho, lnrho0, sigma = dens
assert (rho.shape == grid.shape).all()
multiply_dens_mask(rho, lnrho0, sigma, weights)
if near is not None:
for i in xrange(natom):
pair = near.get(numbers[i])
if pair is None:
pair = near.get(0)
if pair is None:
continue
r0, gamma = pair
if r0 > 5 * angstrom:
raise ValueError(
'The wnear radius is excessive. Please keep it below 5 angstrom.'
)
multiply_near_mask(coordinates[i], grid, r0, gamma, weights)
if far is not None:
r0, gamma = far
multiply_far_mask(coordinates, grid, r0, gamma, weights)
# double that weight goes to zero at non-periodic edges
return weights