def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using 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
"""
temp_dir = tempfile.mkdtemp()
current_dir = os.getcwd()
name = "temp_zeo1"
zeo_inp_filename = name + ".cssr"
os.chdir(temp_dir)
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_file = None
rad_flag = False
if rad_dict:
rad_file = name + ".rad"
rad_flag = True
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
print >>fp, "{} {}".format(el, rad_dict[el].real)
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
vornet = atmnet.perform_voronoi_decomposition()
vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
voronoi_out_filename = name + '_voro.xyz'
voronoi_node_mol = ZeoVoronoiXYZ.from_file(voronoi_out_filename).molecule
#print voronoi_node_mol
species = ["X"] * len(voronoi_node_mol.sites)
coords = []
prop = []
for site in voronoi_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
)
voronoi_node_struct = Structure(
lattice, species, coords, coords_are_cartesian=True,
site_properties={"voronoi_radius": prop}
)
os.chdir(current_dir)
shutil.rmtree(temp_dir)
return voronoi_node_struct
def get_void_volume_surfarea(structure,
rad_dict=None,
chan_rad=0.3,
probe_rad=0.1):
"""
Computes the volume and surface area of isolated void using Zeo++.
Useful to compute the volume and surface area of vacant site.
Args:
structure: pymatgen Structure containing vacancy
rad_dict(optional): Dictionary with short name of elements and their
radii.
chan_rad(optional): Minimum channel Radius.
probe_rad(optional): Probe radius for Monte Carlo sampling.
Returns:
volume: floating number representing the volume of void
"""
with ScratchDir("."):
name = "temp_zeo"
zeo_inp_filename = name + ".cssr"
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_file = None
if rad_dict:
rad_file = name + ".rad"
with open(rad_file, "w") as fp:
for el in rad_dict.keys():
fp.write(f"{el} {rad_dict[el]}")
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, True, rad_file)
vol_str = volume(atmnet, 0.3, probe_rad, 10000)
sa_str = surface_area(atmnet, 0.3, probe_rad, 10000)
vol = None
sa = None
for line in vol_str.split("\n"):
if "Number_of_pockets" in line:
fields = line.split()
if float(fields[1]) > 1:
vol = -1.0
break
if float(fields[1]) == 0:
vol = -1.0
break
vol = float(fields[3])
for line in sa_str.split("\n"):
if "Number_of_pockets" in line:
fields = line.split()
if float(fields[1]) > 1:
# raise ValueError("Too many voids")
sa = -1.0
break
if float(fields[1]) == 0:
sa = -1.0
break
sa = float(fields[3])
if not vol or not sa:
raise ValueError("Error in zeo++ output stream")
return vol, sa
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_void_volume_surfarea(structure, rad_dict=None, chan_rad=0.3,
probe_rad=0.1):
"""
Computes the volume and surface area of isolated void using Zeo++.
Useful to compute the volume and surface area of vacant site.
Args:
structure: pymatgen Structure containing vacancy
rad_dict(optional): Dictionary with short name of elements and their
radii.
chan_rad(optional): Minimum channel Radius.
probe_rad(optional): Probe radius for Monte Carlo sampling.
Returns:
volume: floating number representing the volume of void
"""
with ScratchDir('.'):
name = "temp_zeo"
zeo_inp_filename = name + ".cssr"
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_file = None
if rad_dict:
rad_file = name + ".rad"
with open(rad_file, 'w') as fp:
for el in rad_dict.keys():
fp.write("{0} {1}".format(el, rad_dict[el]))
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, True, rad_file)
vol_str = volume(atmnet, 0.3, probe_rad, 10000)
sa_str = surface_area(atmnet, 0.3, probe_rad, 10000)
print vol_str, sa_str
vol = None
sa = None
for line in vol_str.split("\n"):
if "Number_of_pockets" in line:
fields = line.split()
if float(fields[1]) > 1:
vol = -1.0
break
if float(fields[1]) == 0:
vol = -1.0
break
vol = float(fields[3])
for line in sa_str.split("\n"):
if "Number_of_pockets" in line:
fields = line.split()
if float(fields[1]) > 1:
#raise ValueError("Too many voids")
sa = -1.0
break
if float(fields[1]) == 0:
sa = -1.0
break
sa = float(fields[3])
if not vol or not sa:
raise ValueError("Error in zeo++ output stream")
return vol, sa
def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using 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
"""
temp_dir = tempfile.mkdtemp()
current_dir = os.getcwd()
name = "temp_zeo"
zeo_inp_filename = name + ".cssr"
os.chdir(temp_dir)
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_file = None
if rad_dict:
rad_file = name + ".rad"
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
fp.write("{0} {1}".format(el, rad_dict[el]))
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, True, rad_file)
vornet = atmnet.perform_voronoi_decomposition()
vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
voronoi_out_filename = name + '_voro.xyz'
voronoi_node_mol = ZeoVoronoiXYZ.from_file(voronoi_out_filename).molecule
#print voronoi_node_mol
species = ["X"] * len(voronoi_node_mol.sites)
coords = []
prop = []
for site in voronoi_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)
voronoi_node_struct = Structure(lattice,
species,
coords,
coords_are_cartesian=True,
site_properties={"voronoi_radius": prop})
os.chdir(current_dir)
shutil.rmtree(temp_dir)
return voronoi_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
def get_free_sphere_params(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using 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.Structure within the
unit cell defined by the lattice of input structure
voronoi face centers as pymatgen.core.structure.Structure 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_file = None
rad_flag = False
if rad_dict:
rad_file = name + ".rad"
rad_flag = True
with open(rad_file, "w+") as fp:
for el in rad_dict.keys():
fp.write(f"{el} {rad_dict[el].real}\n")
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename,
rad_flag=rad_flag,
rad_file=rad_file)
out_file = "temp.res"
atmnet.calculate_free_sphere_parameters(out_file)
if os.path.isfile(out_file) and os.path.getsize(out_file) > 0:
with open(out_file) as fp:
output = fp.readline()
else:
output = ""
fields = [val.strip() for val in output.split()][1:4]
if len(fields) == 3:
fields = [float(field) for field in fields]
free_sphere_params = {
"inc_sph_max_dia": fields[0],
"free_sph_max_dia": fields[1],
"inc_sph_along_free_sph_path_max_dia": fields[2],
}
return free_sphere_params
def get_free_sphere_params(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using 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_file = None
rad_flag = False
if rad_dict:
rad_file = name + ".rad"
rad_flag = True
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
fp.write("{} {}\n".format(el, rad_dict[el].real))
atmnet = AtomNetwork.read_from_CSSR(
zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
out_file = "temp.res"
atmnet.calculate_free_sphere_parameters(out_file)
if os.path.isfile(out_file) and os.path.getsize(out_file) > 0:
with open(out_file, "rt") as fp:
output = fp.readline()
else:
output = ""
fields = [val.strip() for val in output.split()][1:4]
if len(fields) == 3:
fields = [float(field) for field in fields]
free_sphere_params = {'inc_sph_max_dia': fields[0],
'free_sph_max_dia': fields[1],
'inc_sph_along_free_sph_path_max_dia': fields[2]}
return free_sphere_params
def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using 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_file = None
rad_flag = False
if rad_dict:
rad_file = name + ".rad"
rad_flag = True
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
fp.write("{} {}\n".format(el, rad_dict[el].real))
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()
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})
# PMG-Zeo c<->a transformation for voronoi face centers
rot_face_centers = [(center[1], center[2], center[0]) for center in
vor_face_centers]
rot_edge_centers = [(center[1], center[2], center[0]) for center in
vor_edge_centers]
species = ["X"] * len(rot_face_centers)
prop = [0.0] * len(rot_face_centers) # Vor radius not evaluated for fc
vor_facecenter_struct = Structure(
lattice, species, rot_face_centers, coords_are_cartesian=True,
to_unit_cell=True, site_properties={"voronoi_radius": prop})
species = ["X"] * len(rot_edge_centers)
prop = [0.0] * len(rot_edge_centers) # Vor radius not evaluated for fc
vor_edgecenter_struct = Structure(
lattice, species, rot_edge_centers, coords_are_cartesian=True,
to_unit_cell=True, site_properties={"voronoi_radius": prop})
return vor_node_struct, vor_edgecenter_struct, vor_facecenter_struct
# -*- coding: utf-8 -*-
from zeo.high_accuracy import high_accuracy_atmnet
from zeo.netstorage import AtomNetwork
atmnet = AtomNetwork.read_from_CSSR('MgO.cssr', rad_file='MgO.rad')
atmnet.write_to_XYZ('orig_mgo.xyz', False, True)
vornet,fcs = atmnet.perform_voronoi_decomposition()
vornet.write_to_XYZ('orig_mgo_voro.xyz', 0)
vornet.analyze_writeto_XYZ('orig_mgo', 0.4, atmnet)
high_accuracy_atmnet(atmnet, 'DEF')
vornet,fcs = atmnet.perform_voronoi_decomposition()
vornet.write_to_XYZ('test_high.xyz', 0)
vornet.analyze_writeto_XYZ('mgo_high', 0.4, atmnet)
atmnet.write_to_CIF('highacc_MgO.cif')
atmnet.calculate_free_sphere_parameters('MgO.res')
#
#atmnet = AtomNetwork.read_from_CIF("mgo.cif", rad_file="MgO.rad")
#vornet = atmnet.perform_voronoi_decomposition()
#vornet.write_to_XYZ("mgo.xyz", 0)
#vornet.analyze_writeto_XYZ('mgo1', 0.4, atmnet)
#high_accuracy_atmnet(atmnet, "DEF")
#vornet = atmnet.perform_voronoi_decomposition()
#vornet.write_to_XYZ("mgo_high.xyz", 0)
#vornet.analyze_writeto_XYZ('mgo_high', 0.4, atmnet)
#atmnet.write_to_CIF("highacc_mgo.cif")
#atmnet.calculate_free_sphere_parameters('mgo.res')
#
#
#atmnet = AtomNetwork.read_from_CIF("mgo.cif", rad_file="MgO.rad")
#high_accuracy_atmnet(atmnet, "LOW")
#atmnet.write_to_XYZ("mgo_ha_lowset.xyz", False, True)
def get_high_accuracy_voronoi_nodes_alt(structure, rad_dict, probe_rad=0.1):
"""
Function to replace high_accuracy_voronoi_nodes function. In testing
mode.
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.
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 >>fp, "{} {}".format(el, rad_dict[el].real)
atmnet = AtomNetwork.read_from_CSSR(
zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
vornet, voronoi_face_centers = atmnet.perform_voronoi_decomposition()
red_ha_vornet = \
generate_simplified_highaccuracy_voronoi_network(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)
voronoi_node_struct = Structure(
lattice, species, coords, coords_are_cartesian=True,
to_unit_cell=True, site_properties={"voronoi_radius": prop})
#PMG-Zeo c<->a transformation for voronoi face centers
rot_face_centers = [(center[1],center[2],center[0]) for center in
voronoi_face_centers]
species = ["X"] * len(rot_face_centers)
# Voronoi radius not evaluated for fc. Fix in future versions
prop = [0.0] * len(rot_face_centers)
voronoi_facecenter_struct = Structure(
lattice, species, rot_face_centers, coords_are_cartesian=True,
to_unit_cell=True, site_properties={"voronoi_radius": prop})
return voronoi_node_struct, voronoi_facecenter_struct
from zeo.netstorage import AtomNetwork
atmnet = AtomNetwork.read_from_CSSR("MgO.cssr", rad_file="MgO.rad")
a = atmnet.perform_voronoi_decomposition()
#vornet,edge_centers, face_centers = atmnet.perform_voronoi_decomposition()
#print 'edge_centers', edge_centers
#print 'face_centers', face_centers
print len(a)
print a
def get_voronoi_percolate_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
This function is used to get voronoi percolate nodes. Different from get_percolated_node_edge,
the vor_accessible_node_struct returned by this one does not contain neighbor information. So if you need
neighboring information of each accessible node, you may use get_percolated_node_edge function.
Args:
structure (Structure): Structure object for analysis
rad_dict (dict): optional, dictionary of radii of elements in structures.
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:
Returns:
vor_node_struct, vor_accessible_node_struct, vor_edgecenter_struct, vor_facecenter_struct (Structure):
"""
with ScratchDir('.'):
name = "temp_zeo2"
zeo_inp_filename = name + ".cssr"
ZeoCssr(structure).write_file(zeo_inp_filename)
rad_file = None
rad_flag = False
if rad_dict:
rad_file = name + ".rad"
rad_flag = True
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
fp.write("{} {}\n".format(el, rad_dict[el].real))
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()
vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
voro_out_filename = name + '_voro.xyz'
voro_node_mol = ZeoVoronoiXYZ.from_file(name + '_voro.xyz').molecule
voro_accessible_node_mol = ZeoVoronoiXYZ.from_file(
name + '_voro_accessible.xyz').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=False,
site_properties={"voronoi_radius": prop})
# percolate node struct
species = ["X"] * len(voro_accessible_node_mol.sites)
coords = []
prop = []
for site in voro_accessible_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_accessible_node_struct = Structure(
lattice,
species,
coords,
coords_are_cartesian=True,
to_unit_cell=False,
site_properties={"voronoi_radius": prop})
# PMG-Zeo c<->a transformation for voronoi face centers
rot_face_centers = [(center[1], center[2], center[0])
for center in vor_face_centers]
rot_edge_centers = [(center[1], center[2], center[0])
for center in vor_edge_centers]
species = ["X"] * len(rot_face_centers)
prop = [0.0] * len(rot_face_centers) # Vor radius not evaluated for fc
vor_facecenter_struct_origin = Structure(
lattice,
species,
rot_face_centers,
coords_are_cartesian=True,
to_unit_cell=False,
site_properties={"voronoi_radius": prop})
vor_facecenter_struct = Structure.from_sites(
list(set([i for i in vor_facecenter_struct_origin])))
species = ["X"] * len(rot_edge_centers)
prop = [0.0] * len(rot_edge_centers) # Vor radius not evaluated for fc
vor_edgecenter_struct_origin = Structure(
lattice,
species,
rot_edge_centers,
coords_are_cartesian=True,
to_unit_cell=False,
site_properties={"voronoi_radius": prop})
vor_edgecenter_struct = Structure.from_sites(
list(set([i for i in vor_edgecenter_struct_origin])))
return vor_node_struct, vor_accessible_node_struct, vor_edgecenter_struct, vor_facecenter_struct
def get_high_accuracy_voronoi_nodes_alt(structure, rad_dict, probe_rad=0.1):
"""
Function to replace high_accuracy_voronoi_nodes function. In testing
mode.
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.
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 >> fp, "{} {}".format(el, rad_dict[el].real)
atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename,
rad_flag=rad_flag,
rad_file=rad_file)
vornet, voronoi_face_centers = atmnet.perform_voronoi_decomposition()
red_ha_vornet = \
generate_simplified_highaccuracy_voronoi_network(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)
voronoi_node_struct = Structure(lattice,
species,
coords,
coords_are_cartesian=True,
to_unit_cell=True,
site_properties={"voronoi_radius": prop})
#PMG-Zeo c<->a transformation for voronoi face centers
rot_face_centers = [(center[1], center[2], center[0])
for center in voronoi_face_centers]
species = ["X"] * len(rot_face_centers)
# Voronoi radius not evaluated for fc. Fix in future versions
prop = [0.0] * len(rot_face_centers)
voronoi_facecenter_struct = Structure(
lattice,
species,
rot_face_centers,
coords_are_cartesian=True,
to_unit_cell=True,
site_properties={"voronoi_radius": prop})
return voronoi_node_struct, voronoi_facecenter_struct
