def from_dict(d, t=None):
''' Convert the dictionary to a scan model
Params:
d The dictionary of parameters
t The template dictionary to use
Returns:
The scan model
'''
from dxtbx.model import Scan
from scitbx.array_family import flex # import dependency
# If None, return None
if d == None:
if t == None: return None
else: return from_dict(t, None)
elif t != None:
d = dict(t.items() + d.items())
if not isinstance(d['exposure_time'], list):
d['exposure_time'] = [d['exposure_time']]
d.setdefault('batch_offset', 0) # backwards compatibility 20180205
if 'valid_image_ranges' not in d:
d['valid_image_ranges'] = {} # backwards compatibility 20181113
# Create the model from the dictionary
return Scan.from_dict(d)
def from_dict(d, t=None):
''' Convert the dictionary to a scan model
Params:
d The dictionary of parameters
t The template dictionary to use
Returns:
The scan model
'''
from dxtbx.model import Scan
from scitbx.array_family import flex # import dependency
# If None, return None
if d == None:
if t == None: return None
else: return from_dict(t, None)
elif t != None:
d = dict(t.items() + d.items())
if not isinstance(d['exposure_time'], list):
d['exposure_time'] = [d['exposure_time']]
# Create the model from the dictionary
return Scan.from_dict(d)
def from_dict(d, t=None):
"""Convert the dictionary to a scan model
Params:
d The dictionary of parameters
t The template dictionary to use
Returns:
The scan model
"""
if d is None and t is None:
return None
joint = t.copy() if t else {}
joint.update(d)
if not isinstance(joint["exposure_time"], list):
joint["exposure_time"] = [joint["exposure_time"]]
joint.setdefault("batch_offset", 0) # backwards compatibility 20180205
joint.setdefault("valid_image_ranges", {}) # backwards compatibility 20181113
# Create the model from the joint dictionary
return Scan.from_dict(joint)