def matminer_comparisons(structures,
preset='cn',
crystal_site_args={},
site_stats_args={},
distance_tol=0.01):
'''
Distance based on crystal sites implmented by matminer
Args:
structures ([dict]): dictionary-encoded pymatgen Structure objects
preset (str): ['cn', 'ops'] CrystalNNFingerprint preset
crystal_site_args (dict): **kwargs passed to CrysatlSiteFingerprint
site_stats_args (dict): **kwargs passed to SiteStatsFingerprint
distance_tol (float): distance below which comparison will return True
Returns:
[bool]: comparisons between each pair of structures; goes like
[1-2, 1-3, ..., 1-n, 2-3, 2-4, ..., 2-n, ...]
'''
v = fingerprints.matminer_fingerprints(structures,
preset=preset,
crystal_site_args=crystal_site_args,
site_stats_args=site_stats_args)
distances = np.zeros((len(v), len(v)))
for i in range(len(v)):
for j in range(i, len(v)):
distance = np.linalg.norm(np.array(v[i]) - np.array(v[j]))
if distance <= distance_tol:
distance = 0.
distances[i, j] = (not bool(distance))
distances[j, i] = distances[i, j]
return distances.tolist()
def matminer_distances(structures,
preset='cn',
crystal_site_args={},
site_stats_args={},
distance_tol=1.e-6):
'''
Distance based on crystal sites implmented by matminer
Args:
structures ([dict]): dictionary-encoded pymatgen Structure objects
preset (str): ['cn', 'ops'] CrystalNNFingerprint preset
crystal_site_args (dict): **kwargs passed to CrysatlSiteFingerprint
site_stats_args (dict): **kwargs passed to SiteStatsFingerprint
distance_tol (float): distance below which distance will be rounded to 0
Returns:
[float]: distances between each pair of structures; goes like
[1-2, 1-3, ..., 1-n, 2-3, 2-4, ..., 2-n, ...]
'''
# structures = [Structure.from_dict(structure)
# for structure in structures]
v = fingerprints.matminer_fingerprints(structures,
preset=preset,
crystal_site_args=crystal_site_args,
site_stats_args=site_stats_args)
distances = []
for i, v_1 in enumerate(v):
for j, v_2 in enumerate(v[i:]):
if i != j + i:
distance = np.linalg.norm(np.array(v_1) - np.array(v_2))
if distance <= distance_tol:
distance = 0.
distances.append(distance)
return distances
def get(self):
parser = flask_restful.reqparse.RequestParser()
argument_names = [
'structures', 'preset', 'crystal_site_args', 'site_stats_args'
]
for argument_name in argument_names:
parser.add_argument(ARGUMENTS[argument_name])
args = parser.parse_args(strict=True)
args['structures'] = flask.json.loads(args['structures'])
calculated_fingerprints = fingerprints.matminer_fingerprints(**args)
return flask.jsonify(calculated_fingerprints)
structures.append(material['structure'])
document = {'source_id': material['_id'],
'soruce_collection': INPUT_COLLECTION,
'matminer_fingerprint': None,
'stidy_fingerprint': None}
documents.append(document)
except Exception as e:
logging.error('source_id: {} {}'.format(material['_id'], e))
else:
logging.error('Too large, {} atoms {}'.format(
len(structure.sites), material['_id']))
else:
logging.error('Unordered {}'.format(material['_id']))
logging.info('Calcluating matminer fingerprints')
matminer_fingerprints = fingerprints.matminer_fingerprints(structures)
logging.info('Adding fingerprints to documents')
matminer_documents = documents.copy()
for d, document in enumerate(matminer_documents):
matminer_documents[d]['matminer_fingerprint'] = matminer_fingerprints[d]
logging.info('inserting {} documents into {}'.format(
len(documents), 'matminer'))
result = matminer_collection.insert_many(documents)
logging.info('inserted {} documents'.format(len(result.inserted_ids)))
logging.info('Calculating STRUCTURE TIDY fingerprints')
stidy_fingerprints = fingerprints.stidy_fingerprints(structures)
logging.info('Adding fingerprints to documents')
stidy_documents = documents.copy()
for d, document in enumerate(stidy_documents):
stidy_documents[d]['stidy_fingerprint'] = stidy_fingerprints[d]