def test_from_file(self):
filename = os.path.join(test_dir, "EDI.cssr")
zeocssr = ZeoCssr.from_file(filename)
self.assertIsInstance(zeocssr.structure, Structure)
def setUp(self):
filepath = os.path.join(test_dir, 'POSCAR')
p = Poscar.from_file(filepath)
structure = BVAnalyzer().get_oxi_state_decorated_structure(p.structure)
self.zeocssr = ZeoCssr(structure)
def setUp(self):
filepath = os.path.join(PymatgenTest.TEST_FILES_DIR, "POSCAR")
p = Poscar.from_file(filepath)
structure = BVAnalyzer().get_oxi_state_decorated_structure(p.structure)
self.zeocssr = ZeoCssr(structure)
def setUp(self):
filepath = os.path.join(test_dir, 'POSCAR')
p = Poscar.from_file(filepath)
self.zeocssr = ZeoCssr(p.structure)
def test_from_file(self):
filename = os.path.join(PymatgenTest.TEST_FILES_DIR, "EDI.cssr")
zeocssr = ZeoCssr.from_file(filename)
self.assertIsInstance(zeocssr.structure, Structure)
def setUp(self):
filepath = os.path.join(PymatgenTest.TEST_FILES_DIR, "POSCAR")
p = Poscar.from_file(filepath)
self.zeocssr = ZeoCssr(p.structure)
def test_from_file(self):
filename = os.path.join(test_dir, "EDI.cssr")
zeocssr = ZeoCssr.from_file(filename)
self.assertIsInstance(zeocssr.structure, Structure)
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_voronoi_node_edge(structure, rad_dict, write_nt2_file=False):
"""
This function obtain the voronoi nodes and the edge information with 0 probe radius. It will contain neighboring
information of each nodes.
!!!Notice the nt2 file change the xyz to zxy. Thus the result need rotate. What a strange setting!!!
Args:
structure: orginal Structure
rad_dict: {'Na':10,...}
Returns:
Structure: the voronoi node structure. For each site, there are voronoi_radius, neighbor_atoms, neighbor_nodes
in the properties.
The neighbor_nodes in the format : [[node_No,channel_size,node_image]...] node image is list of int,
not array
The neighbor_atoms in the format: [1,2,3,4] the number is the sequence number of sites in structure. So
take care of the structure, don't do any change on the sequence order.
"""
with ScratchDir('.'):
name = "temp_zeo3"
cssr_file = name + ".cssr"
rad_file = name + ".rad"
mass_file = name + ".mass"
out_file = name + ".nt2"
cssr = ZeoCssr(structure)
with open(cssr_file, 'w+') as fp:
fp.write(str(cssr))
# CifWriter(structure).write_file(cif_file) the xyz need to rotate to zxy, so just use existing ZeoCssr
# rad_file
with open(rad_file, 'w+') as fp:
for el in rad_dict.keys():
fp.write("{} {}\n".format(el, rad_dict[el].real))
# mass_file
struct_element_set = set(structure.composition.elements)
with open(mass_file, 'w+') as fp:
for el in struct_element_set:
fp.write("{} {}\n".format(el, float(el.atomic_mass)))
bashcmd = "network -r {} -mass {} -nt2 {} {}".format(
rad_file, mass_file, out_file, cssr_file)
process = subprocess.Popen(bashcmd.split(), stdout=subprocess.PIPE)
zeo_plus_plus_output = process.communicate()[0]
with open(out_file, 'r') as fp:
nt2_file = fp.readlines()
if write_nt2_file != False:
with open(write_nt2_file, 'w+') as fp:
for i in nt2_file:
fp.write(i)
node_info_string_list = nt2_file[1:nt2_file.index('\n')]
edge_info_string_list = nt2_file[nt2_file.index('\n') + 2:]
# node info string to Structure object
species = ["X"] * len(node_info_string_list)
coords = []
voronoi_radius = []
neighbor_atoms_num = [
] # the four closest atoms, the number corresponding to the sequence number in structure
neighbor_nodes = [list() for _ in range(len(node_info_string_list))]
# the connected neighbor voronoi nodes, [node_No,channel_size,node_image], node image: [-1,0,0]
# means the actual connected neighbor will have a transition in -a direction.
# final_frac_coords = node_frac_coords+node_image
for site in node_info_string_list:
coords_temp = map(float, site.split()[1:4])
coords.append([coords_temp[1], coords_temp[2], coords_temp[0]])
voronoi_radius.append(float(site.split()[4]))
neighbor_atoms_num.append(map(int, site.split()[5:]))
for neighbor in edge_info_string_list:
valid_info = neighbor.split()
valid_info.pop(1) # there is a arrow in the output string
image_temp = map(int, valid_info[3:6])
valid_info = [
int(valid_info[0]),
int(valid_info[1]),
float(valid_info[2]),
[image_temp[1], image_temp[2], image_temp[0]]
]
neighbor_nodes[valid_info[0]].append(copy.deepcopy(valid_info[1:]))
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": voronoi_radius,
"neighbor_atoms": neighbor_atoms_num,
"neighbor_nodes": neighbor_nodes
}) # notice, to_unit_cell must be False,
# or the image of neighbor_nodes need change
return vor_node_struct
