def set_transmission_workspaces_on_output(self, transmission_bundles,
fit_state):
for transmission_bundle in transmission_bundles:
fit_performed = fit_state[DataType.to_string(
transmission_bundle.data_type)].fit_type != FitType.NoFit
calculated_transmission_workspace = transmission_bundle.calculated_transmission_workspace
unfitted_transmission_workspace = transmission_bundle.unfitted_transmission_workspace
if transmission_bundle.data_type is DataType.Can:
if does_can_workspace_exist_on_ads(
calculated_transmission_workspace):
# The workspace is cloned here because the transmission runs are diagnostic output so even though
# the values already exist they need to be labelled seperately for each reduction.
calculated_transmission_workspace = CloneWorkspace(
calculated_transmission_workspace, StoreInADS=False)
if does_can_workspace_exist_on_ads(
unfitted_transmission_workspace):
unfitted_transmission_workspace = CloneWorkspace(
unfitted_transmission_workspace, StoreInADS=False)
if fit_performed:
self.setProperty(
"OutputWorkspaceCalculatedTransmissionCan",
calculated_transmission_workspace)
self.setProperty("OutputWorkspaceUnfittedTransmissionCan",
unfitted_transmission_workspace)
elif transmission_bundle.data_type is DataType.Sample:
if fit_performed:
self.setProperty("OutputWorkspaceCalculatedTransmission",
calculated_transmission_workspace)
self.setProperty("OutputWorkspaceUnfittedTransmission",
unfitted_transmission_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The data type {0} should be"
" sample or can.".format(transmission_bundle.data_type))
def set_reduced_can_count_and_norm_on_output(self, output_bundles_parts):
"""
Sets the reduced can count and norm group workspaces on the output properties.
The reduced can workspaces can be:
1. LAB Can Count
2. LAB Can Norm
3. HAB Can Count
4. HAB Can Norm
:param output_bundles_parts: a list containing a single list of output bundle parts
"""
# Find the partial output bundles fo LAB Can and HAB Can if they exist
output_bundles_part = output_bundles_parts[0]
for output_bundle_part in output_bundles_part:
if output_bundle_part.data_type is DataType.CAN:
reduction_mode = output_bundle_part.reduction_mode
output_workspace_count = output_bundle_part.output_workspace_count
output_workspace_norm = output_bundle_part.output_workspace_norm
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace_norm is not None and output_workspace_count is not None and \
not does_can_workspace_exist_on_ads(output_workspace_norm) and \
not does_can_workspace_exist_on_ads(output_workspace_count):
if reduction_mode is ReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceLABCanNorm", output_workspace_norm)
elif reduction_mode is ReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceHABCanNorm", output_workspace_norm)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a partial can.".format(reduction_mode))
def set_reduced_can_workspace_on_output(self, output_bundles, output_bundles_part):
"""
Sets the reduced can workspaces on the output properties.
The reduced can workspaces can be:
1. LAB Can
2. LAB Can Count
3. LAB Can Norm
4. HAB Can
5. HAB Can Count
6. HAB Can Norm
:param output_bundles: a list of output bundles
:param output_bundles_part: a list of partial output bundles
"""
# Find the LAB Can and HAB Can entries if they exist
for output_bundle in output_bundles:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace is not None and not does_can_workspace_exist_on_ads(output_workspace):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCan", output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCan", output_bundle.output_workspace)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
# Find the partial output bundles fo LAB Can and HAB Can if they exist
for output_bundle_part in output_bundles_part:
if output_bundle_part.data_type is DataType.Can:
reduction_mode = output_bundle_part.reduction_mode
output_workspace_count = output_bundle_part.output_workspace_count
output_workspace_norm = output_bundle_part.output_workspace_norm
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace_norm is not None and output_workspace_count is not None and \
not does_can_workspace_exist_on_ads(output_workspace_norm) and \
not does_can_workspace_exist_on_ads(output_workspace_count):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceLABCanNorm", output_workspace_norm)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceHABCanNorm", output_workspace_norm)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a partial can.".format(reduction_mode))
def set_reduced_can_workspace_on_output(self, output_bundles, output_bundles_part):
"""
Sets the reduced can workspaces on the output properties.
The reduced can workspaces can be:
1. LAB Can
2. LAB Can Count
3. LAB Can Norm
4. HAB Can
5. HAB Can Count
6. HAB Can Norm
:param output_bundles: a list of output bundles
:param output_bundles_part: a list of partial output bundles
"""
# Find the LAB Can and HAB Can entries if they exist
for output_bundle in output_bundles:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace is not None and not does_can_workspace_exist_on_ads(output_workspace):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCan", output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCan", output_bundle.output_workspace)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
# Find the partial output bundles fo LAB Can and HAB Can if they exist
for output_bundle_part in output_bundles_part:
if output_bundle_part.data_type is DataType.Can:
reduction_mode = output_bundle_part.reduction_mode
output_workspace_count = output_bundle_part.output_workspace_count
output_workspace_norm = output_bundle_part.output_workspace_norm
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace_norm is not None and output_workspace_count is not None and \
not does_can_workspace_exist_on_ads(output_workspace_norm) and \
not does_can_workspace_exist_on_ads(output_workspace_count):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceLABCanNorm", output_workspace_norm)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCanCount", output_workspace_count)
self.setProperty("OutputWorkspaceHABCanNorm", output_workspace_norm)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a partial can.".format(reduction_mode))
def set_reduced_can_workspace_on_output(self, completed_event_bundled):
"""
Sets the reduced can workspaces on the output properties.
The reduced can workspaces can be either LAB or HAB
:param completed_event_bundled: a list containing output bundles
"""
# Find the LAB Can and HAB Can entries if they exist
lab_groups = WorkspaceGroup()
hab_groups = WorkspaceGroup()
for bundle in completed_event_bundled:
if bundle.output_bundle.data_type is DataType.CAN:
reduction_mode = bundle.output_bundle.reduction_mode
output_workspace = bundle.output_bundle.output_workspace
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
if reduction_mode is ReductionMode.LAB:
lab_groups.addWorkspace(output_workspace)
elif reduction_mode is ReductionMode.HAB:
hab_groups.addWorkspace(output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
self._set_prop_if_group_has_data("OutputWorkspaceLABCan", lab_groups)
self._set_prop_if_group_has_data("OutputWorkspaceHABCan", hab_groups)
def set_reduced_can_workspace_on_output(self, output_bundles):
"""
Sets the reduced can workspaces on the output properties.
The reduced can workspaces can be:
1. LAB Can
4. HAB Can
:param output_bundles: a list containing a single list of output bundles
"""
# Find the LAB Can and HAB Can entries if they exist
output_bundles = output_bundles[0]
for output_bundle in output_bundles:
if output_bundle.data_type is DataType.CAN:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace is not None and not does_can_workspace_exist_on_ads(output_workspace):
if reduction_mode is ReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCan", output_workspace)
elif reduction_mode is ReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCan", output_bundle.output_workspace)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
def set_transmission_workspaces_on_output(self, completed_event_slices,
fit_state):
calc_can, calc_sample = WorkspaceGroup(), WorkspaceGroup()
unfit_can, unfit_sample = WorkspaceGroup(), WorkspaceGroup()
output_hab_or_lab = None
for bundle in completed_event_slices:
if output_hab_or_lab is not None and output_hab_or_lab != bundle.output_bundle.reduction_mode:
continue # The transmission workspace for HAB/LAB is the same, so only output one
output_hab_or_lab = bundle.output_bundle.reduction_mode
calculated_transmission_workspace = bundle.transmission_bundle.calculated_transmission_workspace
unfitted_transmission_workspace = bundle.transmission_bundle.unfitted_transmission_workspace
if bundle.transmission_bundle.data_type is DataType.CAN:
if does_can_workspace_exist_on_ads(
calculated_transmission_workspace):
# The workspace is cloned here because the transmission runs are diagnostic output so even though
# the values already exist they need to be labelled separately for each reduction.
calculated_transmission_workspace = CloneWorkspace(
calculated_transmission_workspace, StoreInADS=False)
if does_can_workspace_exist_on_ads(
unfitted_transmission_workspace):
unfitted_transmission_workspace = CloneWorkspace(
unfitted_transmission_workspace, StoreInADS=False)
if calculated_transmission_workspace:
calc_can.addWorkspace(calculated_transmission_workspace)
if unfitted_transmission_workspace:
unfit_can.addWorkspace(unfitted_transmission_workspace)
elif bundle.transmission_bundle.data_type is DataType.SAMPLE:
if calculated_transmission_workspace:
calc_sample.addWorkspace(calculated_transmission_workspace)
if unfitted_transmission_workspace:
unfit_sample.addWorkspace(unfitted_transmission_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The data type {0} should be"
" sample or can.".format(
bundle.transmission_bundle.data_type))
self._set_prop_if_group_has_data(
"OutputWorkspaceCalculatedTransmission", calc_sample)
self._set_prop_if_group_has_data("OutputWorkspaceUnfittedTransmission",
unfit_sample)
self._set_prop_if_group_has_data(
"OutputWorkspaceCalculatedTransmissionCan", calc_can)
self._set_prop_if_group_has_data(
"OutputWorkspaceUnfittedTransmissionCan", unfit_can)
def set_reduced_can_count_and_norm_on_output(self, completed_event_slices):
"""
Sets the reduced can count and norm group workspaces on the output properties.
This includes the HAB/LAB counts and Norms
:param completed_event_slices: a list containing a single list of output bundle parts
"""
# Find the partial output bundles fo LAB Can and HAB Can if they exist
lab_can_counts, hab_can_counts = WorkspaceGroup(), WorkspaceGroup()
lab_can_norms, hab_can_norms = WorkspaceGroup(), WorkspaceGroup()
for bundle in completed_event_slices:
if bundle.output_bundle.data_type is DataType.CAN:
reduction_mode = bundle.parts_bundle.reduction_mode
output_workspace_count = bundle.parts_bundle.output_workspace_count
output_workspace_norm = bundle.parts_bundle.output_workspace_norm
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace_norm is not None and output_workspace_count is not None and \
not does_can_workspace_exist_on_ads(output_workspace_norm) and \
not does_can_workspace_exist_on_ads(output_workspace_count):
if reduction_mode is ReductionMode.LAB:
lab_can_counts.addWorkspace(output_workspace_count)
lab_can_norms.addWorkspace(output_workspace_norm)
elif reduction_mode is ReductionMode.HAB:
hab_can_counts.addWorkspace(output_workspace_count)
hab_can_norms.addWorkspace(output_workspace_norm)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a partial can.".format(
reduction_mode))
self._set_prop_if_group_has_data("OutputWorkspaceLABCanCount",
lab_can_counts)
self._set_prop_if_group_has_data("OutputWorkspaceLABCanNorm",
lab_can_norms)
self._set_prop_if_group_has_data("OutputWorkspaceHABCanCount",
hab_can_counts)
self._set_prop_if_group_has_data("OutputWorkspaceHABCanNorm",
hab_can_norms)
def set_can_and_sam_on_output(self, completed_event_slices):
"""
Sets the reduced can and sample workspaces.
These is the LAB/HAB can and sample
Cans are also output for optimization, so check for double output.
:param output_bundles: a list containing a single list of output_bundles
"""
lab_cans, hab_cans = WorkspaceGroup(), WorkspaceGroup()
lab_samples, hab_samples = WorkspaceGroup(), WorkspaceGroup()
for bundle in completed_event_slices:
reduction_mode = bundle.output_bundle.reduction_mode
output_workspace = bundle.output_bundle.output_workspace
if bundle.output_bundle.data_type is DataType.CAN:
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
if reduction_mode is ReductionMode.LAB:
lab_cans.addWorkspace(output_workspace)
elif reduction_mode is ReductionMode.HAB:
hab_cans.addWorkspace(output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
elif bundle.output_bundle.data_type is DataType.SAMPLE:
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
if reduction_mode is ReductionMode.LAB:
lab_samples.addWorkspace(output_workspace)
elif reduction_mode is ReductionMode.HAB:
hab_samples.addWorkspace(output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a sample.".format(reduction_mode))
self._set_prop_if_group_has_data("OutputWorkspaceLABCan", lab_cans)
self._set_prop_if_group_has_data("OutputWorkspaceHABCan", hab_cans)
self._set_prop_if_group_has_data("OutputWorkspaceLABSample",
lab_samples)
self._set_prop_if_group_has_data("OutputWorkspaceHABSample",
hab_samples)
def set_transmission_workspaces_on_output(self, transmission_bundles, fit_state):
for transmission_bundle in transmission_bundles:
fit_performed = fit_state[DataType.to_string(transmission_bundle.data_type)].fit_type != FitType.NoFit
calculated_transmission_workspace = transmission_bundle.calculated_transmission_workspace
unfitted_transmission_workspace = transmission_bundle.unfitted_transmission_workspace
if transmission_bundle.data_type is DataType.Can:
if does_can_workspace_exist_on_ads(calculated_transmission_workspace):
# The workspace is cloned here because the transmission runs are diagnostic output so even though
# the values already exist they need to be labelled seperately for each reduction.
calculated_transmission_workspace = CloneWorkspace(calculated_transmission_workspace, StoreInADS=False)
if does_can_workspace_exist_on_ads(unfitted_transmission_workspace):
unfitted_transmission_workspace = CloneWorkspace(unfitted_transmission_workspace, StoreInADS=False)
if fit_performed:
self.setProperty("OutputWorkspaceCalculatedTransmissionCan", calculated_transmission_workspace)
self.setProperty("OutputWorkspaceUnfittedTransmissionCan", unfitted_transmission_workspace)
elif transmission_bundle.data_type is DataType.Sample:
if fit_performed:
self.setProperty("OutputWorkspaceCalculatedTransmission", calculated_transmission_workspace)
self.setProperty("OutputWorkspaceUnfittedTransmission", unfitted_transmission_workspace)
else:
raise RuntimeError("SANSSingleReduction: The data type {0} should be"
" sample or can.".format(transmission_bundle.data_type))
def set_can_and_sam_on_output(self, output_bundles):
'''
Sets the reduced can and sam workspaces.
These can be:
1. LAB Can
2. HAB Can
3. LAB Sample
4. HAB Sample
Cans are also output for optimization, so check for double output.
:param output_bundles: a list of output_bundles
'''
for output_bundle in output_bundles:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCan",
output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCan",
output_bundle.output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
elif output_bundle.data_type is DataType.Sample:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None:
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABSample",
output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABSample",
output_bundle.output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a sample.".format(reduction_mode))
def set_reduced_can_workspace_on_output(self, output_bundles):
"""
Sets the reduced can group workspaces on the output properties.
The reduced can workspaces can be:
LAB Can or
HAB Can
:param output_bundles: a list of output bundles
"""
workspace_group_lab_can = WorkspaceGroup()
workspace_group_hab_can = WorkspaceGroup()
# Find the LAB Can and HAB Can entries if they exist
for component_bundle in output_bundles:
for output_bundle in component_bundle:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
name = self._get_output_workspace_name(
output_bundle.state,
output_bundle.reduction_mode,
can=True)
AnalysisDataService.addOrReplace(
name, output_workspace)
if reduction_mode is ISISReductionMode.LAB:
workspace_group_lab_can.addWorkspace(
output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
workspace_group_hab_can.addWorkspace(
output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
if workspace_group_lab_can.size() > 0:
# LAB group workspace is non-empty, so we want to set it as output
self.setProperty("OutputWorkspaceLABCan", workspace_group_lab_can)
if workspace_group_hab_can.size() > 0:
self.setProperty("OutputWorkspaceHABCan", workspace_group_hab_can)
def set_can_and_sam_on_output(self, output_bundles):
'''
Sets the reduced can and sam workspaces.
These can be:
1. LAB Can
2. HAB Can
3. LAB Sample
4. HAB Sample
Cans are also output for optimization, so check for double output.
:param output_bundles: a list of output_bundles
'''
for output_bundle in output_bundles:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None and not does_can_workspace_exist_on_ads(output_workspace):
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABCan", output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABCan", output_bundle.output_workspace)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
elif output_bundle.data_type is DataType.Sample:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None:
if reduction_mode is ISISReductionMode.LAB:
self.setProperty("OutputWorkspaceLABSample", output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
self.setProperty("OutputWorkspaceHABSample", output_bundle.output_workspace)
else:
raise RuntimeError("SANSSingleReduction: The reduction mode {0} should not"
" be set with a sample.".format(reduction_mode))
def set_can_and_sam_on_output(self, output_bundles):
"""
Sets the reduced can and sam workspaces.
These can be:
1. LAB Can
2. HAB Can
3. LAB Sample
4. HAB Sample
Cans are also output for optimization, so check for double output.
:param output_bundles: a list of output_bundles
"""
workspace_group_lab_can = WorkspaceGroup()
workspace_group_hab_can = WorkspaceGroup()
workspace_group_lab_sample = WorkspaceGroup()
workspace_group_hab_sample = WorkspaceGroup()
for component_bundle in output_bundles:
for output_bundle in component_bundle:
if output_bundle.data_type is DataType.Can:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None and not does_can_workspace_exist_on_ads(
output_workspace):
can_name = self._get_output_workspace_name(
output_bundle.state,
output_bundle.reduction_mode,
can=True)
AnalysisDataService.addOrReplace(
can_name, output_workspace)
if reduction_mode is ISISReductionMode.LAB:
workspace_group_lab_can.addWorkspace(
output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
workspace_group_hab_can.addWorkspace(
output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a can.".format(reduction_mode))
elif output_bundle.data_type is DataType.Sample:
reduction_mode = output_bundle.reduction_mode
output_workspace = output_bundle.output_workspace
if output_workspace is not None:
sample_name = self._get_output_workspace_name(
output_bundle.state,
output_bundle.reduction_mode,
sample=True)
AnalysisDataService.addOrReplace(
sample_name, output_workspace)
if reduction_mode is ISISReductionMode.LAB:
workspace_group_lab_sample.addWorkspace(
output_workspace)
elif reduction_mode is ISISReductionMode.HAB:
workspace_group_hab_sample.addWorkspace(
output_workspace)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a sample.".format(
reduction_mode))
if workspace_group_hab_can.size() > 0:
self.setProperty("OutputWorkspaceHABCan", workspace_group_hab_can)
if workspace_group_hab_sample.size() > 0:
self.setProperty("OutputWorkspaceHABSample",
workspace_group_hab_sample)
if workspace_group_lab_can.size() > 0:
self.setProperty("OutputWorkspaceLABCan", workspace_group_lab_can)
if workspace_group_lab_sample.size() > 0:
self.setProperty("OutputWorkspaceLABSample",
workspace_group_lab_sample)
def set_reduced_can_count_and_norm_on_output(self, output_bundles_parts):
"""
Sets the reduced can count and norm group workspaces on the output properties.
The reduced can workspaces can be:
1. LAB Can Count
2. LAB Can Norm
3. HAB Can Count
4. HAB Can Norm
:param output_bundles_parts: a list of output bundle parts
"""
workspace_group_lab_can_count = WorkspaceGroup()
workspace_group_lab_can_norm = WorkspaceGroup()
workspace_group_hab_can_count = WorkspaceGroup()
workspace_group_hab_can_norm = WorkspaceGroup()
# Find the partial output bundles fo LAB Can and HAB Can if they exist
for event_slice_bundles in output_bundles_parts:
for output_bundle_part in event_slice_bundles:
if output_bundle_part.data_type is DataType.Can:
reduction_mode = output_bundle_part.reduction_mode
output_workspace_count = output_bundle_part.output_workspace_count
output_workspace_norm = output_bundle_part.output_workspace_norm
# Make sure that the output workspace is not None which can be the case if there has never been a
# can set for the reduction.
if output_workspace_norm is not None and output_workspace_count is not None and \
not does_can_workspace_exist_on_ads(output_workspace_norm) and \
not does_can_workspace_exist_on_ads(output_workspace_count):
name = self._get_output_workspace_name(
output_bundle_part.state,
output_bundle_part.reduction_mode)
count_name = name + "_hab_can_count"
norm_name = name + "_hab_can_norm"
AnalysisDataService.addOrReplace(
count_name, output_workspace_count)
AnalysisDataService.addOrReplace(
norm_name, output_workspace_norm)
if reduction_mode is ISISReductionMode.LAB:
workspace_group_lab_can_count.addWorkspace(
output_workspace_count)
workspace_group_lab_can_norm.addWorkspace(
output_workspace_norm)
elif reduction_mode is ISISReductionMode.HAB:
workspace_group_hab_can_count.addWorkspace(
output_workspace_count)
workspace_group_hab_can_norm.addWorkspace(
output_workspace_norm)
else:
raise RuntimeError(
"SANSSingleReduction: The reduction mode {0} should not"
" be set with a partial can.".format(
reduction_mode))
if workspace_group_lab_can_count.size() > 0:
self.setProperty("OutputWorkspaceLABCanCount",
workspace_group_lab_can_count)
if workspace_group_lab_can_norm.size() > 0:
self.setProperty("OutputWorkspaceLABCanNorm",
workspace_group_lab_can_norm)
if workspace_group_hab_can_count.size() > 0:
self.setProperty("OutputWorkspaceHABCanCount",
workspace_group_hab_can_count)
if workspace_group_hab_can_norm.size() > 0:
self.setProperty("OutputWorkspaceHABCanNorm",
workspace_group_hab_can_norm)
