def __init__(self, cif_string, transformations=None, primitive=True,
extend_collection=False):
"""
Generates a Transmuter from a cif string, possibly
containing multiple structures.
Args:
cif_string:
A string containing a cif or a series of cifs
transformations:
New transformations to be applied to all structures
primitive:
Whether to generate the primitive cell from the cif.
extend_collection:
Whether to use more than one output structure from one-to-many
transformations.
"""
transformed_structures = []
lines = cif_string.split("\n")
structure_data = []
read_data = False
for line in lines:
if re.match("^\s*data", line):
structure_data.append([])
read_data = True
if read_data:
structure_data[-1].append(line)
for data in structure_data:
tstruct = TransformedStructure.from_cif_string("\n".join(data), [],
primitive)
transformed_structures.append(tstruct)
StandardTransmuter.__init__(self, transformed_structures,
transformations, extend_collection)
def __init__(self,
cif_string,
transformations=None,
primitive=True,
extend_collection=False):
"""
Generates a Transmuter from a cif string, possibly
containing multiple structures.
Args:
cif_string: A string containing a cif or a series of cifs
transformations: New transformations to be applied to all
structures
primitive: Whether to generate the primitive cell from the cif.
extend_collection: Whether to use more than one output structure
from one-to-many transformations. extend_collection can be a
number, which determines the maximum branching for each
transformation.
"""
transformed_structures = []
lines = cif_string.split("\n")
structure_data = []
read_data = False
for line in lines:
if re.match("^\s*data", line):
structure_data.append([])
read_data = True
if read_data:
structure_data[-1].append(line)
for data in structure_data:
tstruct = TransformedStructure.from_cif_string(
"\n".join(data), [], primitive)
transformed_structures.append(tstruct)
super(CifTransmuter, self).__init__(transformed_structures,
transformations, extend_collection)
