def read(filename: str):
"""
Reads ClusterExpansion object from file.
Parameters
---------
filename
file from which to read
"""
with tarfile.open(name=filename, mode='r') as tar_file:
cs_file = tempfile.NamedTemporaryFile()
cs_file.write(tar_file.extractfile('cluster_space').read())
cs_file.seek(0)
cs = ClusterSpace.read(cs_file.name)
items = pickle.load(tar_file.extractfile('items'))
ce = ClusterExpansion.__new__(ClusterExpansion)
ce._cluster_space = cs
ce._parameters = items['parameters']
# TODO: remove if condition once metadata is firmly established
if 'metadata' in items:
ce._metadata = items['metadata']
assert list(items['parameters']) == list(ce.parameters)
return ce
def read(infile: Union[str, BinaryIO, TextIO]):
"""
Reads StructureContainer object from file.
Parameters
----------
infile
file from which to read
"""
if isinstance(infile, str):
filename = infile
else:
filename = infile.name
if not tarfile.is_tarfile(filename):
raise TypeError('{} is not a tar file'.format(filename))
temp_db_file = tempfile.NamedTemporaryFile()
with tarfile.open(mode='r', name=filename) as tar_file:
cs_file = tar_file.extractfile('cluster_space')
temp_db_file.write(tar_file.extractfile('database').read())
temp_db_file.seek(0)
cluster_space = ClusterSpace.read(cs_file)
database = ase.db.connect(temp_db_file.name, type='db')
structure_container = StructureContainer(cluster_space)
fit_structures = []
for row in database.select():
data = row.data
fit_structure = FitStructure(row.toatoms(),
user_tag=data['user_tag'],
cv=data['cluster_vector'],
properties=data['properties'])
fit_structures.append(fit_structure)
structure_container._structure_list = fit_structures
return structure_container