def _cart_dists(self, s1, s2, avg_lattice, mask, normalization, lll_frac_tol=None):
"""
Finds a matching in cartesian space. Finds an additional
fractional translation vector to minimize RMS distance
Args:
s1, s2: numpy arrays of fractional coordinates. len(s1) >= len(s2)
avg_lattice: Lattice on which to calculate distances
mask: numpy array of booleans. mask[i, j] = True indicates
that s2[i] cannot be matched to s1[j]
normalization (float): inverse normalization length
Returns:
Distances from s2 to s1, normalized by (V/Natom) ^ 1/3
Fractional translation vector to apply to s2.
Mapping from s1 to s2, i.e. with numpy slicing, s1[mapping] => s2
"""
if len(s2) > len(s1):
raise ValueError("s1 must be larger than s2")
if mask.shape != (len(s2), len(s1)):
raise ValueError("mask has incorrect shape")
# vectors are from s2 to s1
vecs, d_2 = pbc_shortest_vectors(avg_lattice, s2, s1, mask,
return_d2=True,
lll_frac_tol=lll_frac_tol)
lin = LinearAssignment(d_2)
s = lin.solution
short_vecs = vecs[np.arange(len(s)), s]
translation = np.average(short_vecs, axis=0)
f_translation = avg_lattice.get_fractional_coords(translation)
new_d2 = np.sum((short_vecs - translation) ** 2, axis=-1)
return new_d2 ** 0.5 * normalization, f_translation, s
def _cart_dists(self, s1, s2, avg_lattice, mask, normalization, lll_frac_tol=None):
"""
Finds a matching in cartesian space. Finds an additional
fractional translation vector to minimize RMS distance
Args:
s1, s2: numpy arrays of fractional coordinates. len(s1) >= len(s2)
avg_lattice: Lattice on which to calculate distances
mask: numpy array of booleans. mask[i, j] = True indicates
that s2[i] cannot be matched to s1[j]
normalization (float): inverse normalization length
Returns:
Distances from s2 to s1, normalized by (V/Natom) ^ 1/3
Fractional translation vector to apply to s2.
Mapping from s1 to s2, i.e. with numpy slicing, s1[mapping] => s2
"""
if len(s2) > len(s1):
raise ValueError("s1 must be larger than s2")
if mask.shape != (len(s2), len(s1)):
raise ValueError("mask has incorrect shape")
# vectors are from s2 to s1
vecs, d_2 = pbc_shortest_vectors(avg_lattice, s2, s1, mask,
return_d2=True,
lll_frac_tol=lll_frac_tol)
lin = LinearAssignment(d_2)
s = lin.solution
short_vecs = vecs[np.arange(len(s)), s]
translation = np.average(short_vecs, axis=0)
f_translation = avg_lattice.get_fractional_coords(translation)
new_d2 = np.sum((short_vecs - translation) ** 2, axis=-1)
return new_d2 ** 0.5 * normalization, f_translation, s
def get_ionic_pol_change(struct2, struct1, psp_table, extra_trans=None):
"""should already be translated"""
LOGGER.info("Finding ionic change in polarization")
if extra_trans is None:
extra_trans = np.array([0., 0., 0.])
else:
# convert extra_trans to cartesian
extra_trans = np.array(extra_trans) * np.array(struct2.lattice.abc)
mask = get_mask(struct2, struct1)
vecs, d_2 = pbc_shortest_vectors(struct2.lattice,
struct2.frac_coords,
struct1.frac_coords,
mask,
return_d2=True,
lll_frac_tol=[0.4, 0.4, 0.4])
lin = LinearAssignment(d_2)
s = lin.solution
species = [struct1[i].species_string for i in s]
short_vecs = vecs[np.arange(len(s)), s]
LOGGER.debug("Displacements:")
LOGGER.debug(short_vecs)
pol_change = np.array([0., 0., 0.])
for v, sp in zip(short_vecs, species):
pol_change += (v -
extra_trans) * psp_table.pseudo_with_symbol(sp).Z_val
LOGGER.debug("{}\t{}\t{}".format(
sp,
psp_table.pseudo_with_symbol(sp).Z_val, v))
return (ECHARGE * 10**20) * pol_change / struct2.lattice.volume
