def from_dict(cls, obj):
assert obj['__id__'] == 'XSweep'
return_obj = cls(name=None, sample=None, wavelength=None)
for k, v in obj.iteritems():
if k in ('_indexer', '_refiner', '_integrater') and v is not None:
from libtbx.utils import import_python_object
cls = import_python_object(
import_path=".".join((v['__module__'], v['__name__'])),
error_prefix='', target_must_be='', where_str='').object
v = cls.from_dict(v)
if k == '_indexer':
v.add_indexer_sweep(return_obj)
elif k == '_refiner':
v.add_refiner_sweep(return_obj)
elif k == '_integrater':
v.set_integrater_sweep(return_obj, reset=False)
if isinstance(v, dict):
#if v.get('__id__') == 'ExperimentList':
#from dxtbx.model.experiment.experiment_list import ExperimentListFactory
#v = ExperimentListFactory.from_dict(v)
if v.get('__id__') == 'imageset':
from dxtbx.serialize.imageset import imageset_from_dict
v = imageset_from_dict(v, check_format=False)
setattr(return_obj, k, v)
if return_obj._indexer is not None and return_obj._integrater is not None:
return_obj._integrater._intgr_indexer = return_obj._indexer
if return_obj._integrater is not None and return_obj._refiner is not None:
return_obj._integrater._intgr_refiner = return_obj._refiner
if return_obj._indexer is not None and return_obj._refiner is not None:
return_obj._refiner._refinr_indexers[return_obj.get_epoch(1)] \
= return_obj._indexer
return return_obj
def from_dict(cls, obj):
assert obj["__id__"] == "Integrater"
return_obj = cls()
for k, v in obj.iteritems():
if k in ("_intgr_indexer", "_intgr_refiner") and v is not None:
from libtbx.utils import import_python_object
cls = import_python_object(
import_path=".".join((v["__module__"], v["__name__"])),
error_prefix="",
target_must_be="",
where_str="",
).object
v = cls.from_dict(v)
if isinstance(v, dict):
if v.get("__id__") == "ExperimentList":
from dxtbx.model.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v)
elif v.get("__id__") == "imageset":
from dxtbx.serialize.imageset import imageset_from_dict
v = imageset_from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def from_dict(cls, obj):
assert obj['__id__'] == 'XSweep'
return_obj = cls(name=None, sample=None, wavelength=None)
for k, v in obj.iteritems():
if k in ('_indexer', '_refiner', '_integrater') and v is not None:
from libtbx.utils import import_python_object
cls = import_python_object(import_path=".".join(
(v['__module__'], v['__name__'])),
error_prefix='',
target_must_be='',
where_str='').object
v = cls.from_dict(v)
if k == '_indexer':
v.add_indexer_sweep(return_obj)
elif k == '_refiner':
v.add_refiner_sweep(return_obj)
elif k == '_integrater':
v.set_integrater_sweep(return_obj, reset=False)
if isinstance(v, dict):
#if v.get('__id__') == 'ExperimentList':
#from dxtbx.model.experiment_list import ExperimentListFactory
#v = ExperimentListFactory.from_dict(v)
if v.get('__id__') == 'imageset':
from dxtbx.serialize.imageset import imageset_from_dict
v = imageset_from_dict(v, check_format=False)
setattr(return_obj, k, v)
if return_obj._indexer is not None and return_obj._integrater is not None:
return_obj._integrater._intgr_indexer = return_obj._indexer
if return_obj._integrater is not None and return_obj._refiner is not None:
return_obj._integrater._intgr_refiner = return_obj._refiner
if return_obj._indexer is not None and return_obj._refiner is not None:
return_obj._refiner._refinr_indexers[return_obj.get_epoch(1)] \
= return_obj._indexer
return return_obj
def imageset_from_string(string, directory=None):
"""Load the string and return the models.
Params:
string The JSON string to load
Returns:
The models
"""
return imageset_from_dict(json.loads(string, object_hook=_decode_dict),
directory=directory)
def imageset_from_string(string):
''' Load the string and return the models.
Params:
string The JSON string to load
Returns:
The models
'''
import json
from dxtbx.serialize.imageset import imageset_from_dict
return imageset_from_dict(json.loads(string, object_hook=_decode_dict))
def imageset(filename):
"""Load the given JSON file.
Params:
infile The input filename
Returns:
The models
"""
# If the input is a string then open and read from that file
filename = os.path.abspath(filename)
directory = os.path.dirname(filename)
with open(filename) as infile:
return imageset_from_dict(json.load(infile), directory=directory)
def imageset_from_string(string, directory=None):
"""Load the string and return the models.
Params:
string The JSON string to load
Returns:
The models
"""
warnings.warn(
"This function is deprecated and will be removed in the next release",
DeprecationWarning,
stacklevel=2,
)
return imageset_from_dict(json.loads(string), directory=directory)
def from_dict(cls, obj):
assert obj['__id__'] == 'Indexer'
assert obj['__name__'] == cls.__name__
return_obj = cls()
for k, v in obj.iteritems():
if k == '_indxr_helper' and v is not None:
from xia2.Schema.Interfaces.Indexer import _IndexerHelper
v = _IndexerHelper(v)
if k == '_indxr_imagesets' and len(v):
assert v[0].get('__id__') == 'imageset'
from dxtbx.serialize.imageset import imageset_from_dict
v = [imageset_from_dict(v_, check_format=False) for v_ in v]
if isinstance(v, dict):
if v.get('__id__') == 'ExperimentList':
from dxtbx.model.experiment.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def from_dict(cls, obj):
assert obj['__id__'] == 'Indexer'
assert obj['__name__'] == cls.__name__
return_obj = cls()
for k, v in obj.iteritems():
if k == '_indxr_helper' and v is not None:
from xia2.Schema.Interfaces.Indexer import _IndexerHelper
v = _IndexerHelper(v)
if k == '_indxr_imagesets' and len(v):
assert v[0].get('__id__') == 'imageset'
from dxtbx.serialize.imageset import imageset_from_dict
v = [imageset_from_dict(v_, check_format=False) for v_ in v]
if isinstance(v, dict):
if v.get('__id__') == 'ExperimentList':
from dxtbx.model.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def from_dict(cls, obj):
assert obj['__id__'] == 'Integrater'
return_obj = cls()
for k, v in obj.iteritems():
if k in ('_intgr_indexer', '_intgr_refiner') and v is not None:
from libtbx.utils import import_python_object
cls = import_python_object(
import_path=".".join((v['__module__'], v['__name__'])),
error_prefix='', target_must_be='', where_str='').object
v = cls.from_dict(v)
if isinstance(v, dict):
if v.get('__id__') == 'ExperimentList':
from dxtbx.model.experiment.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v)
elif v.get('__id__') == 'imageset':
from dxtbx.serialize.imageset import imageset_from_dict
v = imageset_from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def from_dict(cls, obj):
assert obj["__id__"] == "Indexer"
assert obj["__name__"] == cls.__name__
return_obj = cls()
for k, v in obj.items():
if k == "_indxr_helper" and v is not None:
v = _IndexerHelper(v)
if k == "_indxr_imagesets" and len(v):
assert v[0].get("__id__") == "imageset"
from dxtbx.serialize.imageset import imageset_from_dict
v = [imageset_from_dict(v_, check_format=False) for v_ in v]
if isinstance(v, dict):
if v.get("__id__") == "ExperimentList":
from dxtbx.model.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj