def __init__(self, cutoff=6.0):
"""
Args:
cutoff (float): cutoff distance in determining the potential
neighbors for Voronoi tessellation analysis
"""
self.cutoff = cutoff
self.voronoi_analyzer = VoronoiAnalyzer(cutoff=self.cutoff)
def featurize(self, struct, site):
"""
:param struct: Pymatgen Structure object
:param site: index of target site in structure
:return: voro_index: Voronoi indices
voro_index_sum: sum of Voronoi indices
voro_index_frac: fractional Voronoi indices
"""
voro_index_result = []
self.voronoi_analyzer = VoronoiAnalyzer(cutoff=self.cutoff)
voro_index_list = self.voronoi_analyzer.analyze(struct, n=site)
for voro_index in voro_index_list:
voro_index_result.append(voro_index)
voro_index_sum = sum(voro_index_list)
voro_index_result.append(voro_index_sum)
voro_index_frac_list = voro_index_list / voro_index_sum
for voro_index_frac in voro_index_frac_list:
voro_index_result.append(voro_index_frac)
return voro_index_result
def setUp(self):
self.ss = Xdatcar(os.path.join(test_dir, 'XDATCAR.MD')).structures
self.s = self.ss[1]
self.va = VoronoiAnalyzer(cutoff=4.0)
spacegroup1.get_space_group_symbol())
print('space group number of structure1:',
spacegroup1.get_space_group_number())
print('space group symbol of structure2:',
spacegroup2.get_space_group_symbol())
print('space group number of structure2:',
spacegroup2.get_space_group_number())
Voronoi = VoronoiCoordFinder(s2, target=None)
site = s2.num_sites
#print("s2[0]:",s2.sites)
print("s2_cart_coords[0]", s2.cart_coords[0])
#print("s2_distance_(0,1)",s2.get_distance(0,1))
polyhedra = Voronoi.get_voronoi_polyhedra(1)
coordinate = Voronoi.get_coordination_number(1)
coordinate_sites = Voronoi.get_coordinated_sites(1)
Voronoi_Analyzer = VoronoiAnalyzer()
anay = Voronoi_Analyzer.analyze(s1, n=0)
strucs = [s1, s2]
anays = Voronoi_Analyzer.analyze_structures(strucs)
print("Voronoi_Analyzer.analyze(s1,n=0):", anay)
#plt = Voronoi_Analyzer.plot_vor_analysis(anays)
relax = RelaxationAnalyzer(s1, s2)
volume_change = relax.get_percentage_volume_change()
lattice_parameter_changes = relax.get_percentage_lattice_parameter_changes()
print('initial volume:', s1.volume)
print('final volume:', s2.volume)
print("percent_volume_change:", volume_change)
print("percent_lattice_change:", lattice_parameter_changes)
bond_dist = relax.get_percentage_bond_dist_changes(max_radius=6)
print("percent_bond_distance_change:", bond_dist)
connec = VoronoiConnectivity(s2)
def list_number_of_facets_with_i_vertices(list_struc):
return [
VoronoiAnalyzer().analyze(structure, n=0) for structure in list_struc
]
def run_task(self, fw_spec):
# Get
data_dir = self.get('data_dir')
calc_rdf = self.get('calc_rdf', True)
calc_bad = self.get('calc_bad', True)
calc_voronoi = self.get('calc_voronoi', False)
calc_cage = self.get('calc_cage', True)
calc_pmf = self.get('calc_pmf', False)
calc_connectivity = self.get('calc_connectivity', False)
ionic_steps = []
for root, dirs, files in os.walk(data_dir):
for f in files:
if 'ionic_steps' in f:
name, ext = os.path.splitext(f)
if ext in ('.gz', '.GZ', '.Z'):
with gzip.open(f, "rb") as gzipped:
d = json.loads(gzipped.read().decode("ascii"))
else:
d = loadfn(f)
ionic_steps.extend(d)
structures = [step['structure'] for step in ionic_steps]
data_dict = {}
if calc_rdf:
logger.info("LOGGER: Calculating radial distribution functions...")
rdf = RadialDistributionFunction(structures=structures)
rdf.get_radial_distribution_functions(nproc=4)
cns = rdf.get_coordination_numbers()
fs = rdf.first_coordination_shell_radius
data_dict.update({'radial_distribution_functions': rdf.as_dict()})
data_dict.update({'coordination_numbers': cns})
if calc_cage:
logger.info("LOGGER: Calculating cage correlation function...")
ccf = CageCorrelationFunction(structures, fs)
ccf.get_cage_correlation_function()
# TODO: Make sure the CCFs work
if calc_pmf:
logger.info(
"LOGGER: Calculating the potential of mean force...")
# TODO: Need to include the implementation of PMF here
if calc_bad:
logger.info(
"LOGGER: Calculating bond angle distribution functions...")
bad = BondAngleDistribution(structures=structures)
bad.get_bond_angle_distribution(nproc=4)
data_dict.update(
{'bond_angle_distribution_functions': bad.as_dict()})
if calc_voronoi:
logger.info("LOGGER: Performing voronoi analysis...")
va = VoronoiAnalyzer(structures)
try:
poly = va.analyze_structures()
data_dict.update({'voronoi_polyhedra': poly})
except MemoryError:
logger.info(
"ERROR: Voronoi analysis failed due to insufficient memory..."
)
if calc_connectivity:
logger.info(
"LOGGER: Getting the connectivity motif distribution functions..."
)
# TODO: Implement after writing connectivity function
# write structural analysis results to json file and then zip it
write_dir = os.path.join(os.getcwd(), 'structural_analysis')
os.mkdir(write_dir)
for k, v in data_dict.items():
dumpfn(v, os.path.join(write_dir, '{}.json').format(k))
gzip_dir(write_dir)
return FWAction()
def setUp(self):
self.ss = Xdatcar(
os.path.join(PymatgenTest.TEST_FILES_DIR, "XDATCAR.MD")).structures
self.s = self.ss[1]
self.va = VoronoiAnalyzer(cutoff=4.0)
