def PyExec(self):
from IndirectReductionCommon import (
get_multi_frame_rebin, identify_bad_detectors, unwrap_monitor,
process_monitor_efficiency, scale_monitor, scale_detectors,
rebin_reduction, group_spectra, fold_chopped, rename_reduction)
self._setup()
load_opts = dict()
if self._instrument_name == 'VESUVIO':
load_opts['InstrumentParFile'] = self._par_filename
load_opts['Mode'] = 'FoilOut'
load_opts['LoadMonitors'] = True
self._workspace_names, self._chopped_data = load_file_ranges(
self._data_files,
self._ipf_filename,
self._spectra_range[0],
self._spectra_range[1],
sum_files=self._sum_files,
load_logs=self._load_logs,
load_opts=load_opts)
# applies the changes in the provided calibration file
self._apply_calibration()
# Load container if run is given
self._load_and_scale_container(self._container_scale_factor, load_opts)
# Load vanadium runs if given
if self._vanadium_runs:
self._vanadium_ws, _, _ = load_files(self._vanadium_runs,
self._ipf_filename,
self._spectra_range[0],
self._spectra_range[1],
load_logs=self._load_logs,
load_opts=load_opts)
if len(self._workspace_names) > len(self._vanadium_runs):
raise RuntimeError(
"There cannot be more sample runs than vanadium runs.")
for index, c_ws_name in enumerate(self._workspace_names):
is_multi_frame = isinstance(mtd[c_ws_name], WorkspaceGroup)
# Get list of workspaces
if is_multi_frame:
workspaces = mtd[c_ws_name].getNames()
else:
workspaces = [c_ws_name]
# Process rebinning for framed data
rebin_string_2, num_bins = get_multi_frame_rebin(
c_ws_name, self._rebin_string)
masked_detectors = identify_bad_detectors(workspaces[0])
# Process workspaces
for ws_name in workspaces:
monitor_ws_name = ws_name + '_mon'
# Subtract empty container if there is one
if self._container_workspace is not None:
Minus(LHSWorkspace=ws_name,
RHSWorkspace=self._container_workspace,
OutputWorkspace=ws_name)
if self._vanadium_ws:
van_ws_name = self._vanadium_ws[index]
van_ws = mtd[van_ws_name]
if self._container_workspace is not None:
cont_ws = mtd[self._container_workspace]
if van_ws.blocksize() > cont_ws.blocksize():
RebinToWorkspace(
WorkspaceToRebin=van_ws_name,
WorkspaceToMatch=self._container_workspace,
OutputWorkspace=van_ws_name)
elif cont_ws.blocksize() > van_ws.blocksize():
RebinToWorkspace(
WorkspaceToRebin=self._container_workspace,
WorkspaceToMatch=van_ws_name,
OutputWorkspace=self._container_workspace)
Minus(LHSWorkspace=van_ws_name,
RHSWorkspace=self._container_workspace,
OutputWorkspace=van_ws_name)
if mtd[ws_name].blocksize() > van_ws.blocksize():
RebinToWorkspace(WorkspaceToRebin=ws_name,
WorkspaceToMatch=van_ws_name,
OutputWorkspace=ws_name)
elif van_ws.blocksize() > mtd[ws_name].blocksize():
RebinToWorkspace(WorkspaceToRebin=van_ws_name,
WorkspaceToMatch=ws_name,
OutputWorkspace=van_ws_name)
replacement_value = 0.1 * find_minimum_non_zero_y_in_workspace(
van_ws)
logger.information(
'Replacing zeros in {0} with {1}.'.format(
van_ws_name, replacement_value))
ReplaceSpecialValues(
InputWorkspace=van_ws_name,
SmallNumberThreshold=0.0000001,
SmallNumberValue=replacement_value,
OutputWorkspace=self._replace_zeros_name)
Divide(LHSWorkspace=ws_name,
RHSWorkspace=self._replace_zeros_name,
OutputWorkspace=ws_name,
AllowDifferentNumberSpectra=True)
DeleteWorkspace(self._replace_zeros_name)
# Process monitor
if not unwrap_monitor(ws_name):
ConvertUnits(InputWorkspace=monitor_ws_name,
OutputWorkspace=monitor_ws_name,
Target='Wavelength',
EMode='Elastic')
process_monitor_efficiency(ws_name)
scale_monitor(ws_name)
# Scale detector data by monitor intensities
scale_detectors(ws_name, 'Elastic')
# Remove the no longer needed monitor workspace
DeleteWorkspace(monitor_ws_name)
# Convert to dSpacing
ConvertUnits(InputWorkspace=ws_name,
OutputWorkspace=ws_name,
Target='dSpacing',
EMode='Elastic')
# Handle rebinning
rebin_reduction(ws_name, self._rebin_string, rebin_string_2,
num_bins)
# Group spectra
group_spectra(ws_name,
masked_detectors=masked_detectors,
method=self._grouping_method,
group_ws=self._grouping_workspace)
if is_multi_frame:
fold_chopped(c_ws_name)
# Remove the container workspaces
if self._container_workspace is not None:
self._delete_all([self._container_workspace])
# Remove the vanadium workspaces
if self._vanadium_ws:
self._delete_all(self._vanadium_ws)
# Rename output workspaces
output_workspace_names = [
rename_reduction(ws_name, self._sum_files)
for ws_name in self._workspace_names
]
# Group result workspaces
GroupWorkspaces(InputWorkspaces=output_workspace_names,
OutputWorkspace=self._output_ws)
self.setProperty('OutputWorkspace', self._output_ws)
def PyExec(self):
from IndirectReductionCommon import (get_multi_frame_rebin,
identify_bad_detectors,
unwrap_monitor,
process_monitor_efficiency,
scale_monitor,
scale_detectors,
rebin_reduction,
group_spectra,
fold_chopped,
rename_reduction)
self._setup()
load_opts = dict()
if self._instrument_name == 'VESUVIO':
load_opts['InstrumentParFile'] = self._par_filename
load_opts['Mode'] = 'FoilOut'
load_opts['LoadMonitors'] = True
self._workspace_names, self._chopped_data = load_file_ranges(self._data_files,
self._ipf_filename,
self._spectra_range[0],
self._spectra_range[1],
sum_files=self._sum_files,
load_logs=self._load_logs,
load_opts=load_opts)
# applies the changes in the provided calibration file
self._apply_calibration()
# Load container if run is given
self._load_and_scale_container(self._container_scale_factor, load_opts)
# Load vanadium runs if given
if self._vanadium_runs:
self._vanadium_ws, _ = load_files(self._vanadium_runs,
self._ipf_filename,
self._spectra_range[0],
self._spectra_range[1],
load_logs=self._load_logs,
load_opts=load_opts)
if len(self._workspace_names) > len(self._vanadium_runs):
raise RuntimeError("There cannot be more sample runs than vanadium runs.")
for index, c_ws_name in enumerate(self._workspace_names):
is_multi_frame = isinstance(mtd[c_ws_name], WorkspaceGroup)
# Get list of workspaces
if is_multi_frame:
workspaces = mtd[c_ws_name].getNames()
else:
workspaces = [c_ws_name]
# Process rebinning for framed data
rebin_string_2, num_bins = get_multi_frame_rebin(c_ws_name,
self._rebin_string)
masked_detectors = identify_bad_detectors(workspaces[0])
# Process workspaces
for ws_name in workspaces:
monitor_ws_name = ws_name + '_mon'
# Subtract empty container if there is one
if self._container_workspace is not None:
Minus(LHSWorkspace=ws_name,
RHSWorkspace=self._container_workspace,
OutputWorkspace=ws_name)
if self._vanadium_ws:
van_ws_name = self._vanadium_ws[index]
van_ws = mtd[van_ws_name]
if self._container_workspace is not None:
cont_ws = mtd[self._container_workspace]
if van_ws.blocksize() > cont_ws.blocksize():
RebinToWorkspace(WorkspaceToRebin=van_ws_name,
WorkspaceToMatch=self._container_workspace,
OutputWorkspace=van_ws_name)
elif cont_ws.blocksize() > van_ws.blocksize():
RebinToWorkspace(WorkspaceToRebin=self._container_workspace,
WorkspaceToMatch=van_ws_name,
OutputWorkspace=self._container_workspace)
Minus(LHSWorkspace=van_ws_name,
RHSWorkspace=self._container_workspace,
OutputWorkspace=van_ws_name)
if mtd[ws_name].blocksize() > van_ws.blocksize():
RebinToWorkspace(WorkspaceToRebin=ws_name,
WorkspaceToMatch=van_ws_name,
OutputWorkspace=ws_name)
elif van_ws.blocksize() > mtd[ws_name].blocksize():
RebinToWorkspace(WorkspaceToRebin=van_ws_name,
WorkspaceToMatch=ws_name,
OutputWorkspace=van_ws_name)
Divide(LHSWorkspace=ws_name,
RHSWorkspace=van_ws_name,
OutputWorkspace=ws_name,
AllowDifferentNumberSpectra=True)
# Process monitor
if not unwrap_monitor(ws_name):
ConvertUnits(InputWorkspace=monitor_ws_name,
OutputWorkspace=monitor_ws_name,
Target='Wavelength',
EMode='Elastic')
process_monitor_efficiency(ws_name)
scale_monitor(ws_name)
# Scale detector data by monitor intensities
scale_detectors(ws_name, 'Elastic')
# Remove the no longer needed monitor workspace
DeleteWorkspace(monitor_ws_name)
# Convert to dSpacing
ConvertUnits(InputWorkspace=ws_name,
OutputWorkspace=ws_name,
Target='dSpacing',
EMode='Elastic')
# Handle rebinning
rebin_reduction(ws_name,
self._rebin_string,
rebin_string_2,
num_bins)
# Group spectra
group_spectra(ws_name,
masked_detectors=masked_detectors,
method=self._grouping_method,
group_ws=self._grouping_workspace)
if is_multi_frame:
fold_chopped(c_ws_name)
# Remove the container workspaces
if self._container_workspace is not None:
self._delete_all([self._container_workspace])
# Remove the vanadium workspaces
if self._vanadium_ws:
self._delete_all(self._vanadium_ws)
# Rename output workspaces
output_workspace_names = [rename_reduction(ws_name, self._sum_files) for ws_name in self._workspace_names]
# Group result workspaces
GroupWorkspaces(InputWorkspaces=output_workspace_names,
OutputWorkspace=self._output_ws)
self.setProperty('OutputWorkspace', self._output_ws)