def test_get_voronoi_nodes(self):
vor_node_struct, vor_edge_center_struct, vor_face_center_struct = \
get_voronoi_nodes(self.structure, self.rad_dict)
self.assertIsInstance(vor_node_struct, Structure)
self.assertIsInstance(vor_edge_center_struct, Structure)
self.assertIsInstance(vor_face_center_struct, Structure)
print(len(vor_node_struct.sites))
print(len(vor_face_center_struct.sites))
def test_get_voronoi_nodes(self):
vor_node_struct, vor_edge_center_struct, vor_face_center_struct = \
get_voronoi_nodes(self.structure, self.rad_dict)
self.assertIsInstance(vor_node_struct, Structure)
self.assertIsInstance(vor_edge_center_struct, Structure)
self.assertIsInstance(vor_face_center_struct, Structure)
print (len(vor_node_struct.sites))
print (len(vor_face_center_struct.sites))
def _symmetry_reduced_voronoi_nodes(structure, rad_dict):
"""
Obtain symmetry reduced voronoi nodes using Zeo++ and
pymatgen.symmetry.finder.SymmetryFinder
Args:
strucutre:
pymatgen Structure object
Returns:
Symmetrically distinct voronoi nodes as pymatgen Strucutre
"""
vor_node_struct = get_voronoi_nodes(structure, rad_dict)
vor_symmetry_finder = SymmetryFinder(vor_node_struct, symprec=1e-1)
vor_symm_struct = vor_symmetry_finder.get_symmetrized_structure()
#print vor_symm_struct.lattice
#print vor_symm_struct.lattice.abc, vor_symm_struct.lattice.angles
#print vor_node_struct.lattice
#print vor_node_struct.lattice.abc, vor_node_struct.lattice.angles
equiv_sites_list = vor_symm_struct.equivalent_sites
def add_closest_equiv_site(dist_sites, equiv_sites):
if not dist_sites:
dist_sites.append(equiv_sites[0])
else:
avg_dists = []
for site in equiv_sites:
dists = [
site.distance(dst_site, jimage=[0, 0, 0])
for dst_site in dist_sites
]
avg_dist = sum(dists) / len(dist_sites)
avg_dists.append(avg_dist)
min_avg_dist = min(avg_dists)
ind = avg_dists.index(min_avg_dist)
dist_sites.append(equiv_sites[ind])
dist_sites = []
for equiv_sites in equiv_sites_list:
add_closest_equiv_site(dist_sites, equiv_sites)
#lat = structure.lattice
#sp = [site.specie for site in sites] # "Al" because to Zeo++
#coords = [site.coords for site in sites]
#vor_node_radii = [site.properties['voronoi_radius'] for site in sites]
#vor_node_struct = Structure(lat, sp, coords,
# coords_are_cartesian=True,
# site_properties={'voronoi_radius':vor_node_radii}
# )
return dist_sites
def symmetry_reduced_voronoi_nodes(structure, rad_dict):
"""
Obtain symmetry reduced voronoi nodes using Zeo++ and
pymatgen.symmetry.finder.SymmetryFinder
Args:
strucutre:
pymatgen Structure object
Returns:
Symmetrically distinct voronoi nodes as pymatgen Strucutre
"""
vor_node_struct = get_voronoi_nodes(structure, rad_dict)
vor_symmetry_finder = SymmetryFinder(vor_node_struct, symprec=1e-1)
vor_symm_struct = vor_symmetry_finder.get_symmetrized_structure()
#print vor_symm_struct.lattice
#print vor_symm_struct.lattice.abc, vor_symm_struct.lattice.angles
#print vor_node_struct.lattice
#print vor_node_struct.lattice.abc, vor_node_struct.lattice.angles
equiv_sites_list = vor_symm_struct.equivalent_sites
def add_closest_equiv_site(dist_sites, equiv_sites):
if not dist_sites:
dist_sites.append(equiv_sites[0])
else:
avg_dists = []
for site in equiv_sites:
dists = [site.distance(dst_site, jimage=[0, 0, 0])
for dst_site in dist_sites]
avg_dist = sum(dists) / len(dist_sites)
avg_dists.append(avg_dist)
min_avg_dist = min(avg_dists)
ind = avg_dists.index(min_avg_dist)
dist_sites.append(equiv_sites[ind])
dist_sites = []
for equiv_sites in equiv_sites_list:
add_closest_equiv_site(dist_sites, equiv_sites)
#lat = structure.lattice
#sp = [site.specie for site in sites] # "Al" because to Zeo++
#coords = [site.coords for site in sites]
#vor_node_radii = [site.properties['voronoi_radius'] for site in sites]
#vor_node_struct = Structure(lat, sp, coords,
# coords_are_cartesian=True,
# site_properties={'voronoi_radius':vor_node_radii}
# )
return dist_sites
def symmetry_reduced_voronoi_nodes(
structure, rad_dict, high_accuracy_flag=False, symm_flag=True):
"""
Obtain symmetry reduced voronoi nodes using Zeo++ and
pymatgen.symmetry.finder.SymmetryFinder
Args:
strucutre: pymatgen Structure object
rad_dict: Dictionary containing radii of spcies in the structure
high_accuracy_flag: Flag denotting whether to use high accuracy version of Zeo++
symm_flag: Flag denoting whether to return symmetrically distinct sites only
Returns:
Symmetrically distinct voronoi nodes as pymatgen Strucutre
"""
def add_closest_equiv_site(dist_sites, equiv_sites):
if not dist_sites:
dist_sites.append(equiv_sites[0])
else:
avg_dists = []
for site in equiv_sites:
dists = [site.distance(dst_site, jimage=[0, 0, 0])
for dst_site in dist_sites]
avg_dist = sum(dists) / len(dist_sites)
avg_dists.append(avg_dist)
min_avg_dist = min(avg_dists)
ind = avg_dists.index(min_avg_dist)
dist_sites.append(equiv_sites[ind])
def cmp_memoize_last_site(f): #Compares and stores last site
def not_duplicates(site1, site2):
if site1.distance(site2) < 1e-5:
return False
else:
return True
cmp_memoize_last_site.cache = None
def helper(x):
if not cmp_memoize_last_site.cache:
cmp_memoize_last_site.cache = f(x)
return True
y = f(x)
if not_duplicates(cmp_memoize_last_site.cache, y):
cmp_memoize_last_site.cache = y
return True
else:
return False
return helper
@cmp_memoize_last_site
def check_not_duplicates(site):
return site
if not symm_flag:
if not high_accuracy_flag:
vor_node_struct, vor_facecenter_struct = get_voronoi_nodes(
structure, rad_dict)
return vor_node_struct.sites, vor_facecenter_struct.sites
else:
# Only the nodes are from high accuracy voronoi decomposition
vor_node_struct, vor_facecenter_struct = \
get_high_accuracy_voronoi_nodes(structure, rad_dict)
# Before getting the symmetry, remove the duplicates
vor_node_struct.sites.sort(key = lambda site: site.voronoi_radius)
#print type(vor_node_struct.sites[0])
dist_sites = filter(check_not_duplicates, vor_node_struct.sites)
return dist_sites, vor_facecenter_struct.sites
if not high_accuracy_flag:
vor_node_struct, vor_facecenter_struct = get_voronoi_nodes(
structure, rad_dict)
vor_node_symmetry_finder = SymmetryFinder(vor_node_struct, symprec=1e-1)
vor_node_symm_struct = vor_node_symmetry_finder.get_symmetrized_structure()
node_equiv_sites_list = vor_node_symm_struct.equivalent_sites
node_dist_sites = []
for equiv_sites in node_equiv_sites_list:
add_closest_equiv_site(node_dist_sites, equiv_sites)
vor_fc_symmetry_finder = SymmetryFinder(
vor_facecenter_struct, symprec=1e-1)
vor_fc_symm_struct = vor_fc_symmetry_finder.get_symmetrized_structure()
facecenter_equiv_sites_list = vor_fc_symm_struct.equivalent_sites
facecenter_dist_sites = []
for equiv_sites in facecenter_equiv_sites_list:
add_closest_equiv_site(facecenter_dist_sites, equiv_sites)
if not facecenter_equiv_sites_list: # Fix this so doesn't arise
facecenter_dist_sites = vor_facecenter_struct.sites
return node_dist_sites, facecenter_dist_sites
else:
# Only the nodes are from high accuracy voronoi decomposition
vor_node_struct, vor_facecenter_struct = \
get_high_accuracy_voronoi_nodes(structure, rad_dict)
# Before getting the symmetry, remove the duplicates
vor_node_struct.sites.sort(key = lambda site: site.voronoi_radius)
#print type(vor_node_struct.sites[0])
dist_sites = filter(check_not_duplicates, vor_node_struct.sites)
# Increase the symmetry precision to 0.25
spg = SymmetryFinder(structure,symprec=2.5e-1).get_spacegroup()
# Remove symmetrically equivalent sites
i = 0
while (i < len(dist_sites)-1):
sites1 = [dist_sites[i]]
sites2 = [dist_sites[i+1]]
if spg.are_symmetrically_equivalent(sites1,sites2):
del dist_sites[i+1]
else:
i = i+1
node_dist_sites = dist_sites
vor_fc_symmetry_finder = SymmetryFinder(
vor_facecenter_struct, symprec=1e-1)
vor_fc_symm_struct = vor_fc_symmetry_finder.get_symmetrized_structure()
facecenter_equiv_sites_list = vor_fc_symm_struct.equivalent_sites
facecenter_dist_sites = []
for equiv_sites in facecenter_equiv_sites_list:
add_closest_equiv_site(facecenter_dist_sites, equiv_sites)
if not facecenter_equiv_sites_list: # Fix this so doesn't arise
facecenter_dist_sites = vor_facecenter_struct.sites
return node_dist_sites, facecenter_dist_sites
def symmetry_reduced_voronoi_nodes(structure,
rad_dict,
high_accuracy_flag=False,
symm_flag=True):
"""
Obtain symmetry reduced voronoi nodes using Zeo++ and
pymatgen.symmetry.finder.SymmetryFinder
Args:
strucutre: pymatgen Structure object
rad_dict: Dictionary containing radii of spcies in the structure
high_accuracy_flag: Flag denotting whether to use high accuracy version of Zeo++
symm_flag: Flag denoting whether to return symmetrically distinct sites only
Returns:
Symmetrically distinct voronoi nodes as pymatgen Strucutre
"""
def add_closest_equiv_site(dist_sites, equiv_sites):
if not dist_sites:
dist_sites.append(equiv_sites[0])
else:
avg_dists = []
for site in equiv_sites:
dists = [
site.distance(dst_site, jimage=[0, 0, 0])
for dst_site in dist_sites
]
avg_dist = sum(dists) / len(dist_sites)
avg_dists.append(avg_dist)
min_avg_dist = min(avg_dists)
ind = avg_dists.index(min_avg_dist)
dist_sites.append(equiv_sites[ind])
def cmp_memoize_last_site(f): #Compares and stores last site
def not_duplicates(site1, site2):
if site1.distance(site2) < 1e-5:
return False
else:
return True
cmp_memoize_last_site.cache = None
def helper(x):
if not cmp_memoize_last_site.cache:
cmp_memoize_last_site.cache = f(x)
return True
y = f(x)
if not_duplicates(cmp_memoize_last_site.cache, y):
cmp_memoize_last_site.cache = y
return True
else:
return False
return helper
@cmp_memoize_last_site
def check_not_duplicates(site):
return site
if not symm_flag:
if not high_accuracy_flag:
vor_node_struct, vor_facecenter_struct = get_voronoi_nodes(
structure, rad_dict)
return vor_node_struct.sites, vor_facecenter_struct.sites
else:
# Only the nodes are from high accuracy voronoi decomposition
vor_node_struct, vor_facecenter_struct = \
get_high_accuracy_voronoi_nodes(structure, rad_dict)
# Before getting the symmetry, remove the duplicates
vor_node_struct.sites.sort(key=lambda site: site.voronoi_radius)
#print type(vor_node_struct.sites[0])
dist_sites = filter(check_not_duplicates, vor_node_struct.sites)
return dist_sites, vor_facecenter_struct.sites
if not high_accuracy_flag:
vor_node_struct, vor_facecenter_struct = get_voronoi_nodes(
structure, rad_dict)
vor_node_symmetry_finder = SymmetryFinder(vor_node_struct,
symprec=1e-1)
vor_node_symm_struct = vor_node_symmetry_finder.get_symmetrized_structure(
)
node_equiv_sites_list = vor_node_symm_struct.equivalent_sites
node_dist_sites = []
for equiv_sites in node_equiv_sites_list:
add_closest_equiv_site(node_dist_sites, equiv_sites)
vor_fc_symmetry_finder = SymmetryFinder(vor_facecenter_struct,
symprec=1e-1)
vor_fc_symm_struct = vor_fc_symmetry_finder.get_symmetrized_structure()
facecenter_equiv_sites_list = vor_fc_symm_struct.equivalent_sites
facecenter_dist_sites = []
for equiv_sites in facecenter_equiv_sites_list:
add_closest_equiv_site(facecenter_dist_sites, equiv_sites)
if not facecenter_equiv_sites_list: # Fix this so doesn't arise
facecenter_dist_sites = vor_facecenter_struct.sites
return node_dist_sites, facecenter_dist_sites
else:
# Only the nodes are from high accuracy voronoi decomposition
vor_node_struct, vor_facecenter_struct = \
get_high_accuracy_voronoi_nodes(structure, rad_dict)
# Before getting the symmetry, remove the duplicates
vor_node_struct.sites.sort(key=lambda site: site.voronoi_radius)
#print type(vor_node_struct.sites[0])
dist_sites = filter(check_not_duplicates, vor_node_struct.sites)
# Increase the symmetry precision to 0.25
spg = SymmetryFinder(structure, symprec=2.5e-1).get_spacegroup()
# Remove symmetrically equivalent sites
i = 0
while (i < len(dist_sites) - 1):
sites1 = [dist_sites[i]]
sites2 = [dist_sites[i + 1]]
if spg.are_symmetrically_equivalent(sites1, sites2):
del dist_sites[i + 1]
else:
i = i + 1
node_dist_sites = dist_sites
vor_fc_symmetry_finder = SymmetryFinder(vor_facecenter_struct,
symprec=1e-1)
vor_fc_symm_struct = vor_fc_symmetry_finder.get_symmetrized_structure()
facecenter_equiv_sites_list = vor_fc_symm_struct.equivalent_sites
facecenter_dist_sites = []
for equiv_sites in facecenter_equiv_sites_list:
add_closest_equiv_site(facecenter_dist_sites, equiv_sites)
if not facecenter_equiv_sites_list: # Fix this so doesn't arise
facecenter_dist_sites = vor_facecenter_struct.sites
return node_dist_sites, facecenter_dist_sites
