def create_task(self, sample, shape):
(tasks, sc) = ([], None)
try:
sample_is_mounted = self._beamline_setup_hwobj.sample_changer_hwobj.\
getLoadedSample().getCoords() == sample.location
except AttributeError:
sample_is_mounted = False
dm = self._beamline_setup_hwobj.diffractometer_hwobj
fully_automatic = (not dm.user_confirms_centring)
free_pin_mode = sample.free_pin_mode
temp_tasks = self._create_task(sample, shape)
if (not fully_automatic):
if ((not free_pin_mode) and (not sample_is_mounted) or (not shape)):
# No centred positions selected, or selected sample not
# mounted create sample centring task.
# Check if the tasks requires centring, assumes that all
# the "sub tasks" has the same centring requirements.
if temp_tasks[0].requires_centring():
sc = queue_model_objects.SampleCentring('sample-centring')
tasks.append(sc)
for task in temp_tasks:
if sc:
sc.add_task(task)
tasks.append(task)
return tasks
def add_centring(id):
'''
Add a centring task to the sample with id: <id>, integer.
Args: id, current id of the sample where add the method
id: int (parsed to int anyway)
Return: command sent successfully? http status response, 200 ok,
409 something bad happened. Plus:
data ={ "CentringId": newId}
'''
params = request.get_json()
logging.getLogger('HWR').info(
'[QUEUE] centring add requested with data: ' + str(params))
cent_node = qmo.SampleCentring()
cent_entry = qe.SampleCentringQueueEntry()
cent_entry.set_data_model(cent_node)
cent_entry.set_queue_controller(qm)
node = mxcube.queue.get_node(int(id))
entry = mxcube.queue.queue_hwobj.get_entry_with_model(node)
entry._set_background_color = qutils.PMock()
new_node = mxcube.queue.add_child_at_id(
int(id), cent_node) # add_child does not return id!
entry.enqueue(cent_entry)
logging.getLogger('HWR').info('[QUEUE] centring added to sample')
resp = jsonify({'QueueId': new_node, 'Type': 'Centring', 'Params': params})
resp.status_code = 200
return resp
def create_task(self, sample, shape):
(tasks, sc) = ([], None)
try:
sample_is_mounted = self._beamline_setup_hwobj.sample_changer_hwobj.\
getLoadedSample().getCoords() == sample.location
except AttributeError:
sample_is_mounted = False
dm = self._beamline_setup_hwobj.diffractometer_hwobj
fully_automatic = (not dm.user_confirms_centring)
free_pin_mode = sample.free_pin_mode
temp_tasks = self._create_task(sample, shape)
sample_is_mounted = True
if (not fully_automatic):
if ((not free_pin_mode) and (not sample_is_mounted)
or (not shape)):
# No centred positions selected, or selected sample not
# mounted create sample centring task.
# Check if the tasks requires centring, assumes that all
# the "sub tasks" has the same centring requirements.
if temp_tasks[0].requires_centring():
kappa = None
kappa_phi = None
task_label = "Centring"
if isinstance(temp_tasks[0],
queue_model_objects.DataCollection):
kappa = temp_tasks[0].acquisitions[
0].acquisition_parameters.kappa
kappa_phi = temp_tasks[0].acquisitions[
0].acquisition_parameters.kappa_phi
if kappa is not None and \
kappa_phi is not None:
task_label = "Centring (kappa=%0.1f,phi=%0.1f)" %\
(kappa, kappa_phi)
elif isinstance(temp_tasks[0],
queue_model_objects.Characterisation):
kappa = temp_tasks[0].reference_image_collection.\
acquisitions[0].acquisition_parameters.kappa
kappa_phi = temp_tasks[0].reference_image_collection.\
acquisitions[0].acquisition_parameters.kappa_phi
if kappa and kappa_phi:
task_label = "Centring (kappa=%0.1f,phi=%0.1f)" % \
(kappa, kappa_phi)
sc = queue_model_objects.SampleCentring(
task_label, kappa, kappa_phi)
tasks.append(sc)
for task in temp_tasks:
if sc:
sc.add_task(task)
tasks.append(task)
return tasks
def create_task(self, sample, shape):
(tasks, sc) = ([], None)
dm = self._beamline_setup_hwobj.diffractometer_hwobj
sample_is_mounted = False
if self._in_plate_mode:
try:
sample_is_mounted = self._beamline_setup_hwobj.plate_manipulator_hwobj.\
getLoadedSample().getCoords() == sample.location
except:
sample_is_mounted = False
else:
try:
sample_is_mounted = self._beamline_setup_hwobj.sample_changer_hwobj.\
getLoadedSample().getCoords() == sample.location
except AttributeError:
sample_is_mounted = False
fully_automatic = (not dm.user_confirms_centring)
free_pin_mode = sample.free_pin_mode
temp_tasks = self._create_task(sample, shape)
if len(temp_tasks) == 0:
return
if ((not free_pin_mode) and (not sample_is_mounted) or (not shape)):
# No centred positions selected, or selected sample not
# mounted create sample centring task.
# Check if the tasks requires centring, assumes that all
# the "sub tasks" has the same centring requirements.
if temp_tasks[0].requires_centring():
if self._tree_brick.dc_tree_widget.centring_method == \
queue_model_enumerables.CENTRING_METHOD.MANUAL:
#Manual 3 click centering
acq_par = None
kappa = None
kappa_phi = None
task_label = "Manual centring"
if isinstance(temp_tasks[0],
queue_model_objects.DataCollection):
acq_par = temp_tasks[0].acquisitions[0].\
acquisition_parameters
elif isinstance(temp_tasks[0],
queue_model_objects.Characterisation):
acq_par = temp_tasks[0].reference_image_collection.\
acquisitions[0].acquisition_parameters
if acq_par:
kappa = acq_par.kappa
kappa_phi = acq_par.kappa_phi
if kappa is not None and kappa_phi is not None:
task_label = "Manual centring (kappa=%0.1f,phi=%0.1f)" % \
(kappa, kappa_phi)
sc = queue_model_objects.SampleCentring(
task_label, kappa, kappa_phi)
elif self._tree_brick.dc_tree_widget.centring_method == \
queue_model_enumerables.CENTRING_METHOD.LOOP:
#Optical automatic centering with user confirmation
sc = queue_model_objects.OpticalCentring(
user_confirms=True)
elif self._tree_brick.dc_tree_widget.centring_method == \
queue_model_enumerables.CENTRING_METHOD.FULLY_AUTOMATIC:
#Optical automatic centering without user confirmation
sc = queue_model_objects.OpticalCentring()
elif self._tree_brick.dc_tree_widget.centring_method == \
queue_model_enumerables.CENTRING_METHOD.XRAY:
#Xray centering
mesh_dc = self._create_dc_from_grid(sample)
mesh_dc.run_processing_parallel = "XrayCentering"
sc = queue_model_objects.XrayCentering(mesh_dc)
if sc:
tasks.append(sc)
for task in temp_tasks:
if sc:
sc.add_task(task)
tasks.append(task)
return tasks
