def get_high_accuracy_voronoi_nodes(structure, rad_dict, probe_rad=0.1):
"""
Analyze the void space in the input structure using high accuracy
voronoi decomposition.
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in structure.
If not given, Zeo++ default values are used.
Note: Zeo++ uses atomic radii of elements.
For ionic structures, pass rad_dict with ionic radii
probe_rad (optional): Sampling probe radius in Angstroms.
Default is 0.1 A
Returns:
voronoi nodes as pymatgen.core.structure.Strucutre within the
unit cell defined by the lattice of input structure
voronoi face centers as pymatgen.core.structure.Strucutre within the
unit cell defined by the lattice of input structure
"""
with ScratchDir("."):
name = "temp_zeo1"
zeo_inp_filename = name + ".cssr"
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_flag = True
rad_file = name + ".rad"
with open(rad_file, "w+") as fp:
for el in rad_dict.keys():
print(f"{el} {rad_dict[el].real}", file=fp)
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
# vornet, vor_edge_centers, vor_face_centers = \
# atmnet.perform_voronoi_decomposition()
red_ha_vornet = prune_voronoi_network_close_node(atmnet)
# generate_simplified_highaccuracy_voronoi_network(atmnet)
# get_nearest_largest_diameter_highaccuracy_vornode(atmnet)
red_ha_vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
voro_out_filename = name + "_voro.xyz"
voro_node_mol = ZeoVoronoiXYZ.from_file(voro_out_filename).molecule
species = ["X"] * len(voro_node_mol.sites)
coords = []
prop = []
for site in voro_node_mol.sites:
coords.append(list(site.coords))
prop.append(site.properties["voronoi_radius"])
lattice = Lattice.from_parameters(*structure.lattice.parameters)
vor_node_struct = Structure(
lattice,
species,
coords,
coords_are_cartesian=True,
to_unit_cell=True,
site_properties={"voronoi_radius": prop},
)
return vor_node_struct
def get_high_accuracy_voronoi_nodes(structure, rad_dict, probe_rad=0.1):
"""
Analyze the void space in the input structure using high accuracy
voronoi decomposition.
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in structure.
If not given, Zeo++ default values are used.
Note: Zeo++ uses atomic radii of elements.
For ionic structures, pass rad_dict with ionic radii
probe_rad (optional): Sampling probe radius in Angstroms.
Default is 0.1 A
Returns:
voronoi nodes as pymatgen.core.structure.Strucutre within the
unit cell defined by the lattice of input structure
voronoi face centers as pymatgen.core.structure.Strucutre within the
unit cell defined by the lattice of input structure
"""
with ScratchDir('.'):
name = "temp_zeo1"
zeo_inp_filename = name + ".cssr"
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_flag = True
rad_file = name + ".rad"
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
print("{} {}".format(el, rad_dict[el].real), file=fp)
atmnet = AtomNetwork.read_from_CSSR(
zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
# vornet, vor_edge_centers, vor_face_centers = \
# atmnet.perform_voronoi_decomposition()
red_ha_vornet = \
prune_voronoi_network_close_node(atmnet)
# generate_simplified_highaccuracy_voronoi_network(atmnet)
# get_nearest_largest_diameter_highaccuracy_vornode(atmnet)
red_ha_vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
voro_out_filename = name + '_voro.xyz'
voro_node_mol = ZeoVoronoiXYZ.from_file(voro_out_filename).molecule
species = ["X"] * len(voro_node_mol.sites)
coords = []
prop = []
for site in voro_node_mol.sites:
coords.append(list(site.coords))
prop.append(site.properties['voronoi_radius'])
lattice = Lattice.from_lengths_and_angles(
structure.lattice.abc, structure.lattice.angles)
vor_node_struct = Structure(
lattice, species, coords, coords_are_cartesian=True,
to_unit_cell=True, site_properties={"voronoi_radius": prop})
return vor_node_struct
