def new_centred_position(self, state, centring_status):
"""
Adds a new centred position, connected to the brick which handles
centring (HutchMenuBrick).
"""
p_dict = {}
if "motors" in centring_status and "extraMotors" in centring_status:
p_dict = dict(centring_status["motors"],
**centring_status["extraMotors"])
elif "motors" in centring_status:
p_dict = dict(centring_status["motors"])
if p_dict:
cpos = queue_model_objects.CentredPosition(p_dict)
# self.position_history.add_centred_position(state, cpos)
try:
screen_pos = self.diffractometer_hwobj.motor_positions_to_screen(
cpos.as_dict())
point = shape_history.Point(self.shape_history.get_drawing(),
cpos, screen_pos)
# qub_point = self.shape_history.draw_position(screen_pos)
if point:
# self.shape_history.add_point(cpos, qub_point)
self.shape_history.add_shape(point)
cpos.set_index(point.get_index())
except BaseException:
logging.getLogger("HWR").exception(
"Could not get screen positons for %s" % cpos)
traceback.print_exc()
def _create_task(self, sample, shape):
data_collections = []
if self.periodic_table.current_edge:
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 = copy.deepcopy(shape.get_centred_positions()[0])
cpos.snapshot_image = snapshot
path_template = self._create_path_template(sample, self._path_template)
energy_scan = queue_model_objects.EnergyScan(sample, path_template, cpos)
energy_scan.set_name(path_template.get_prefix())
energy_scan.set_number(path_template.run_number)
energy_scan.element_symbol = self.periodic_table.current_element
energy_scan.edge = self.periodic_table.current_edge
data_collections.append(energy_scan)
self._path_template.run_number += 1
else:
logging.getLogger("user_level_log").info(
"No element selected, please select an element."
)
return data_collections
def _create_task(self, sample, shape):
data_collections = []
if self.count_time is not None:
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 = copy.deepcopy(shape.get_centred_positions()[0])
cpos.snapshot_image = snapshot
path_template = self._create_path_template(sample, self._path_template)
xrf_spectrum = queue_model_objects.XRFSpectrum(sample, path_template, cpos)
xrf_spectrum.set_name(path_template.get_prefix())
xrf_spectrum.set_number(path_template.run_number)
xrf_spectrum.count_time = self.count_time
data_collections.append(xrf_spectrum)
self._path_template.run_number += 1
else:
logging.getLogger("user_level_log").info("Incorrect count time value")
return data_collections
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 = copy.deepcopy(shape.get_centred_positions()[0])
cpos.snapshot_image = snapshot
char_params = copy.deepcopy(self._char_params)
acq = self._create_acq(sample)
dc = queue_model_objects.DataCollection([acq], sample.crystals[0],
self._processing_parameters)
# Reference images for characterisations should be taken 90 deg apart
# this is achived by setting overap to -89
acq.acquisition_parameters.overlap = -89
acq.acquisition_parameters.centred_position = cpos
dc.acquisitions[0] = acq
dc.experiment_type = queue_model_enumerables.EXPERIMENT_TYPE.EDNA_REF
char = queue_model_objects.Characterisation(dc, char_params)
char.set_name(dc.acquisitions[0].path_template.get_prefix())
char.set_number(dc.acquisitions[0].path_template.run_number)
tasks.append(char)
self._path_template.run_number += 1
return tasks