class VoronoiAnalyzerTest(PymatgenTest):
_multiprocess_shared_ = True
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)
def test_analyze(self):
# Check for the Voronoi index of site i in Structure
single_structure = self.va.analyze(self.s, n=5)
self.assertIn(
single_structure.view(),
np.array([4, 3, 3, 4, 2, 2, 1, 0]).view(),
"Cannot find the right polyhedron.",
)
# Check for the presence of a Voronoi index and its frequency in
# a ensemble (list) of Structures
ensemble = self.va.analyze_structures(self.ss,
step_freq=2,
most_frequent_polyhedra=10)
self.assertIn(
("[1 3 4 7 1 0 0 0]", 3),
ensemble,
"Cannot find the right polyhedron in ensemble.",
)
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)
class VoronoiIndex(BaseFeaturizer):
"""
The Voronoi indices n_i and the fractional Voronoi indices n_i/sum(n_i) that
reflects the i-fold symmetry in the local sites.
n_i denotes the number of the i-edged faces, and i is in the range of 3-10 here.
e.g. for bcc lattice, the Voronoi indices are [0,6,0,8,0,0...]
for fcc/hcp lattice, the Voronoi indices are [0,12,0,0,...]
for icosahedra, the Voronoi indices are [0,0,12,0,...]
"""
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, idx):
"""
Args:
struct (Structure): Pymatgen Structure object.
idx (int): index of target site in structure.
Returns:
list including Voronoi indices, sum of Voronoi indices, and
fractional Voronoi indices
"""
voro_index_result = []
voro_index_list = self.voronoi_analyzer.analyze(struct, n=idx)
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 feature_labels(self):
labels = []
for i in range(3, 11):
labels.append('voro_index_%d' % i)
labels.append('voro_index_sum')
for i in range(3, 11):
labels.append('voro_index_frac_%d' % i)
return labels
def citations(self):
citation = ('@book{okabe1992spatial, '
'title={Spatial tessellations}, '
'author={Okabe, Atsuyuki}, '
'year={1992}, '
'publisher={Wiley Online Library}}')
return citation
def implementors(self):
return ['Qi Wang']
class VoronoiAnalyzerTest(PymatgenTest):
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)
def test_analyze(self):
# Check for the Voronoi index of site i in Structure
single_structure = self.va.analyze(self.s, n=5)
self.assertIn(single_structure.view(),
np.array([4, 3, 3, 4, 2, 2, 1, 0]).view(),
"Cannot find the right polyhedron.")
# Check for the presence of a Voronoi index and its frequency in
# a ensemble (list) of Structures
ensemble = self.va.analyze_structures(self.ss, step_freq=2,
most_frequent_polyhedra=10)
self.assertIn(('[1 3 4 7 1 0 0 0]', 3),
ensemble, "Cannot find the right polyhedron in ensemble.")
class VoronoiAnalyzerTest(PymatgenTest):
def setUp(self):
self.ss = Xdatcar(os.path.join(test_dir, 'XDATCAR.MD')).structures
self.s = self.ss[19]
self.va = VoronoiAnalyzer(cutoff=4.0)
def test_analyze(self):
# Check for the Voronoi index of site i in Structure
single_structure = self.va.analyze(self.s, n=5)
self.assertIn(single_structure.view(),
np.array([5, 4, 2, 5, 3, 1, 0, 2]).view(),
"Cannot find the right polyhedron.")
# Check for the presence of a Voronoi index and its frequency in
# a ensemble (list) of Structures
ensemble = self.va.analyze_structures(self.ss, step_freq=2,
most_frequent_polyhedra=10)
self.assertIn(('[2 3 3 3 1 1 0 0]', 6),
ensemble, "Cannot find the right polyhedron in ensemble.")
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)
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)
