def set_dc_params(model, entry, task_data):
"""
Helper method that sets the data collection parameters for a DataCollection.
:param DataCollectionQueueModel: The model to set parameters of
:param DataCollectionQueueEntry: The queue entry of the model
:param dict task_data: Dictionary with new parameters
"""
acq = model.acquisitions[0]
params = task_data['parameters']
acq.acquisition_parameters.set_from_dict(params)
acq.path_template.set_from_dict(params)
acq.path_template.base_prefix = params['prefix']
full_path = os.path.join(mxcube.session.get_base_image_directory(),
params.get('path', ''))
acq.path_template.directory = full_path
process_path = os.path.join(mxcube.session.get_base_process_directory(),
params.get('path', ''))
acq.path_template.process_directory = process_path
# If there is a centered position associated with this data collection, get
# the necessary data for the position and pass it to the collection.
if params["point"]:
for cpos in mxcube.diffractometer.savedCentredPos:
if cpos['posId'] == int(params['point']):
_cpos = qmo.CentredPosition(cpos['motor_positions'])
_cpos.index = int(params['point'])
acq.acquisition_parameters.centred_position = _cpos
if params["helical"]:
model.experiment_type = qme.EXPERIMENT_TYPE.HELICAL
if params["p1"]:
for cpos in mxcube.diffractometer.savedCentredPos:
if cpos['posId'] == int(params['p1']):
_cpos = qmo.CentredPosition(cpos['motor_positions'])
_cpos.index = int(params['p1'])
acq.acquisition_parameters.centred_position = _cpos
if params["p2"]:
acq2 = qmo.Acquisition()
for cpos in mxcube.diffractometer.savedCentredPos:
if cpos['posId'] == int(params['p2']):
_cpos = qmo.CentredPosition(cpos['motor_positions'])
_cpos.index = int(params['p2'])
acq2.acquisition_parameters.centred_position = _cpos
model.acquisitions.append(acq2)
model.set_enabled(task_data['checked'])
entry.set_enabled(task_data['checked'])
def _create_acq(self, sample):
parameters = self._acquisition_parameters
path_template = self._path_template
processing_parameters = self._processing_parameters
bl_setup = self._beamline_setup_hwobj
acq = queue_model_objects.Acquisition()
acq.acquisition_parameters = \
copy.deepcopy(parameters)
acq.acquisition_parameters.collect_agent = \
queue_model_enumerables.COLLECTION_ORIGIN.MXCUBE
acq.path_template = self._create_path_template(sample, path_template)
if self._in_plate_mode:
acq.acquisition_parameters.take_snapshots = 1
return acq
def _create_acq(self, sample):
parameters = self._acquisition_parameters
path_template = self._path_template
shape_history = self._shape_history
processing_parameters = self._processing_parameters
bl_setup = self._beamline_setup_hwobj
acq = queue_model_objects.Acquisition()
acq.acquisition_parameters = \
copy.deepcopy(parameters)
acq.acquisition_parameters.collect_agent = \
queue_model_enumerables.COLLECTION_ORIGIN.MXCUBE
acq.path_template = self._create_path_template(sample, path_template)
"""
if bl_setup.diffractometer_hwobj.in_plate_mode():
acq.acquisition_parameters.take_snapshots = False
else:
acq.acquisition_parameters.take_snapshots = True
"""
return acq
def create_dc(self,
sample,
run_number=None,
start_image=None,
num_images=None,
osc_start=None,
sc=None,
cpos=None,
inverse_beam=False):
tasks = []
# Acquisition for start position
acq = qmo.Acquisition()
acq.acquisition_parameters = \
copy.deepcopy(self._acquisition_parameters)
acq.acquisition_parameters.collect_agent = \
queue_model_enumerables.COLLECTION_ORIGIN.MXCUBE
acq.path_template = copy.deepcopy(self._path_template)
acq.acquisition_parameters.centred_position = cpos
if '<sample_name>' in acq.path_template.directory:
name = sample.get_name().replace(':', '-')
acq.path_template.directory = acq.path_template.directory.\
replace('<sample_name>', name)
acq.path_template.process_directory = acq.path_template.process_directory.\
replace('<sample_name>', name)
if '<acronym>-<name>' in acq.path_template.base_prefix:
acq.path_template.base_prefix = self.get_default_prefix(sample)
acq.path_template.run_numer = self._beamline_setup_hwobj.queue_model_hwobj.\
get_next_run_number(acq.path_template)
if run_number:
acq.path_template.run_number = run_number
if start_image:
acq.acquisition_parameters.first_image = start_image
acq.path_template.start_num = start_image
if num_images:
acq.acquisition_parameters.num_images = num_images
acq.path_template.num_files = num_images
if osc_start:
acq.acquisition_parameters.osc_start = osc_start
if inverse_beam:
acq.acquisition_parameters.inverse_beam = False
if self._beamline_setup_hwobj.in_plate_mode():
acq.acquisition_parameters.take_snapshots = False
else:
acq.acquisition_parameters.take_snapshots = True
processing_parameters = copy.deepcopy(self._processing_parameters)
dc = qmo.DataCollection([acq], sample.crystals[0],
processing_parameters)
dc.set_name(acq.path_template.get_prefix())
dc.set_number(acq.path_template.run_number)
dc.experiment_type = queue_model_enumerables.EXPERIMENT_TYPE.NATIVE
tasks.append(dc)
return tasks
def _create_task(self, sample, shape):
tasks = []
if not shape:
cpos = queue_model_objects.CentredPosition()
cpos.snapshot_image = self._shape_history.get_snapshot([])
else:
# Shapes selected and sample is mounted, get the
# centred positions for the shapes
if isinstance(shape, shape_history.Point):
snapshot = self._shape_history.\
get_snapshot([shape.qub_point])
cpos = shape.get_centred_positions()[0]
cpos.snapshot_image = snapshot
char_params = copy.deepcopy(self._char_params)
# Acquisition for start position
acq = queue_model_objects.Acquisition()
acq.acquisition_parameters = \
copy.deepcopy(self._acquisition_parameters)
acq.acquisition_parameters.collect_agent = \
queue_model_enumerables.COLLECTION_ORIGIN.MXCUBE
acq.acquisition_parameters.centred_position = cpos
acq.path_template = copy.deepcopy(self._path_template)
if self._beamline_setup_hwobj.in_plate_mode():
acq.acquisition_parameters.take_snapshots = False
else:
acq.acquisition_parameters.take_snapshots = True
if '<sample_name>' in acq.path_template.directory:
name = sample.get_name().replace(':', '-')
acq.path_template.directory = acq.path_template.directory.\
replace('<sample_name>', name)
acq.path_template.process_directory = acq.path_template.process_directory.\
replace('<sample_name>', name)
if '<acronym>-<name>' in acq.path_template.base_prefix:
acq.path_template.base_prefix = self.get_default_prefix(sample)
acq.path_template.run_numer = self._beamline_setup_hwobj.queue_model_hwobj.\
get_next_run_number(acq.path_template)
processing_parameters = copy.deepcopy(self._processing_parameters)
data_collection = queue_model_objects.\
DataCollection([acq], sample.crystals[0],
self._processing_parameters)
# Referance images for characterisations should be taken 90 deg apart
# this is achived by setting overap to -89
acq.acquisition_parameters.overlap = -89
data_collection.acquisitions[0] = acq
data_collection.experiment_type = queue_model_enumerables.EXPERIMENT_TYPE.EDNA_REF
char = queue_model_objects.Characterisation(data_collection,
char_params)
char.set_name(data_collection.acquisitions[0].\
path_template.get_prefix())
char.set_number(data_collection.acquisitions[0].\
path_template.run_number)
tasks.append(char)
self._path_template.run_number += 1
return tasks
def _create_task(self, sample, shape):
data_collections = []
if isinstance(shape, shape_history.Line):
if shape.get_qub_objects() is not None:
snapshot = self._shape_history.get_snapshot(
shape.get_qub_objects())
else:
snapshot = self._shape_history.get_snapshot([])
# Acquisition for start position
start_acq = qmo.Acquisition()
start_acq.acquisition_parameters = \
copy.deepcopy(self._acquisition_parameters)
start_acq.acquisition_parameters.collect_agent = \
COLLECTION_ORIGIN.MXCUBE
start_acq.acquisition_parameters.\
centred_position = copy.deepcopy(shape.start_cpos)
start_acq.path_template = copy.deepcopy(self._path_template)
start_acq.acquisition_parameters.centred_position.\
snapshot_image = snapshot
start_acq.path_template.suffix = self._session_hwobj.suffix
if self._beamline_setup_hwobj.in_plate_mode():
start_acq.acquisition_parameters.take_snapshots = False
else:
start_acq.acquisition_parameters.take_snapshots = True
if '<sample_name>' in start_acq.path_template.directory:
name = sample.get_name().replace(':', '-')
start_acq.path_template.directory = start_acq.path_template.directory.\
replace('<sample_name>', name)
start_acq.path_template.process_directory = start_acq.path_template.process_directory.\
replace('<sample_name>', name)
if '<acronym>-<name>' in start_acq.path_template.base_prefix:
start_acq.path_template.base_prefix = self.get_default_prefix(
sample)
start_acq.path_template.run_numer = self._beamline_setup_hwobj.queue_model_hwobj.\
get_next_run_number(start_acq.path_template)
# Add another acquisition for the end position
end_acq = qmo.Acquisition()
end_acq.acquisition_parameters = \
copy.deepcopy(self._acquisition_parameters)
end_acq.acquisition_parameters.collect_agent = \
COLLECTION_ORIGIN.MXCUBE
end_acq.acquisition_parameters.\
centred_position = shape.end_cpos
end_acq.path_template = copy.deepcopy(self._path_template)
end_acq.acquisition_parameters.centred_position.\
snapshot_image = snapshot
end_acq.path_template.suffix = self._session_hwobj.suffix
processing_parameters = copy.deepcopy(self._processing_parameters)
dc = qmo.DataCollection([start_acq, end_acq], sample.crystals[0],
processing_parameters)
dc.set_name(start_acq.path_template.get_prefix())
dc.set_number(start_acq.path_template.run_number)
dc.experiment_type = EXPERIMENT_TYPE.HELICAL
data_collections.append(dc)
self._path_template.run_number += 1
return data_collections