def _setup(self):
"""
Gets algorithm properties.
"""
from IndirectCommon import getWSprefix
self._sample = self.getPropertyValue('SampleWorkspace')
self._resolution = self.getPropertyValue('ResolutionWorkspace')
self._e_min = self.getProperty('EnergyMin').value
self._e_max = self.getProperty('EnergyMax').value
self._number_points_per_bin = self.getProperty(
'BinReductionFactor').value
self._parameter_table = self.getPropertyValue('ParameterWorkspace')
if self._parameter_table == '':
self._parameter_table = getWSprefix(
self._sample) + 'TransformToIqtParameters'
self._calculate_errors = self.getProperty("CalculateErrors").value
self._number_of_iterations = self.getProperty(
"NumberOfIterations").value
self._seed = self.getProperty("SeedValue").value
self._output_workspace = self.getPropertyValue('OutputWorkspace')
if self._output_workspace == '':
self._output_workspace = getWSprefix(self._sample) + 'iqt'
self._dry_run = self.getProperty('DryRun').value
def _setup(self):
"""
Gets algorithm properties.
"""
from IndirectCommon import getWSprefix
self._sample = self.getPropertyValue('SampleWorkspace')
self._resolution = self.getPropertyValue('ResolutionWorkspace')
self._e_min = self.getProperty('EnergyMin').value
self._e_max = self.getProperty('EnergyMax').value
self._number_points_per_bin = self.getProperty(
'BinReductionFactor').value
self._parameter_table = self.getPropertyValue('ParameterWorkspace')
if self._parameter_table == '':
self._parameter_table = getWSprefix(
self._sample) + 'TransformToIqtParameters'
self._number_of_iterations = self.getProperty(
"NumberOfIterations").value
self._seed = self.getProperty("SeedValue").value
self._output_workspace = self.getPropertyValue('OutputWorkspace')
if self._output_workspace == '':
self._output_workspace = getWSprefix(self._sample) + 'iqt'
self._dry_run = self.getProperty('DryRun').value
def _setup(self):
"""
Gets algorithm properties.
"""
from IndirectCommon import getWSprefix
self._sample = self.getPropertyValue('Sample')
self._resolution = self.getPropertyValue('Resolution')
self._e_min = self.getProperty('EnergyMin').value
self._e_max = self.getProperty('EnergyMax').value
self._number_points_per_bin = self.getProperty('NumBins').value
self._parameter_table = self.getPropertyValue('ParameterWorkspace')
if self._parameter_table == '':
self._parameter_table = getWSprefix(
self._sample) + 'FuryParameters'
self._output_workspace = self.getPropertyValue('OutputWorkspace')
if self._output_workspace == '':
self._output_workspace = getWSprefix(self._sample) + 'iqt'
self._verbose = self.getProperty('Verbose').value
self._plot = self.getProperty('Plot').value
self._save = self.getProperty('Save').value
self._dry_run = self.getProperty('DryRun').value
def PyExec(self):
from IndirectCommon import getWSprefix
if self._create_output:
self._out_ws_table = self.getPropertyValue('OutputWorkspaceTable')
# Process vanadium workspace
van_ws = ConvertSpectrumAxis(InputWorkspace=self._van_ws,
OutputWorkspace='__ResNorm_vanadium',
Target='ElasticQ',
EMode='Indirect')
num_hist = van_ws.getNumberHistograms()
v_values = van_ws.getAxis(1).extractValues()
v_unit = van_ws.getAxis(1).getUnit().unitID()
# Process resolution workspace
padded_res_ws = self._process_res_ws(num_hist)
prog_namer = Progress(self, start=0.0, end=0.02, nreports=num_hist)
input_str = ''
for idx in range(num_hist):
input_str += '%s,i%d;' % (padded_res_ws, idx)
prog_namer.report('Generating PlotPeak input string')
out_name = getWSprefix(self._res_ws) + 'ResNorm_Fit'
function = 'name=TabulatedFunction,Workspace=%s,Scaling=1,Shift=0,XScaling=1,ties=(Shift=0)' % self._van_ws
plot_peaks = self.createChildAlgorithm(name='PlotPeakByLogValue', startProgress=0.02, endProgress=0.94, enableLogging=True)
plot_peaks.setProperty('Input', input_str)
plot_peaks.setProperty('OutputWorkspace', out_name)
plot_peaks.setProperty('Function', function)
plot_peaks.setProperty('FitType', 'Individual')
plot_peaks.setProperty('PassWSIndexToFunction', True)
plot_peaks.setProperty('CreateOutput', self._create_output)
plot_peaks.setProperty('StartX', self._e_min)
plot_peaks.setProperty('EndX', self._e_max)
plot_peaks.execute()
fit_params = plot_peaks.getProperty('OutputWorkspace').value
params = {'XScaling':'Stretch', 'Scaling':'Intensity'}
result_workspaces = []
prog_process = Progress(self, start=0.94, end=1.0, nreports=3)
for param_name, output_name in params.items():
result_workspaces.append(self._process_fit_params(fit_params, param_name, v_values, v_unit, output_name))
prog_process.report('Processing Fit data')
GroupWorkspaces(InputWorkspaces=result_workspaces,
OutputWorkspace=self._out_ws)
self.setProperty('OutputWorkspace', self._out_ws)
DeleteWorkspace(van_ws)
DeleteWorkspace(padded_res_ws)
prog_process.report('Deleting workspaces')
if self._create_output:
self.setProperty('OutputWorkspaceTable', fit_params)
def PyExec(self):
from IndirectCommon import StartTime, EndTime, getWSprefix
import inelastic_indirect_reducer
StartTime('IndirectResolution')
self._setup()
InelasticIndirectReduction(Instrument=self._instrument,
Analyser=self._analyser,
Reflection=self._reflection,
Grouping='All',
SumFiles=True,
InputFiles=self._input_files,
DetectorRange=self._detector_range,
OutputWorkspace='__icon_ws_group')
icon_ws = mtd['__icon_ws_group'].getItem(0).getName()
if self._out_ws == "":
self._out_ws = getWSprefix(icon_ws) + 'res'
if self._scale_factor != 1.0:
Scale(InputWorkspace=icon_ws,
OutputWorkspace=icon_ws,
Factor=self._scale_factor)
CalculateFlatBackground(InputWorkspace=icon_ws,
OutputWorkspace=self._out_ws,
StartX=self._background[0],
EndX=self._background[1],
Mode='Mean',
OutputMode='Subtract Background')
Rebin(InputWorkspace=self._out_ws,
OutputWorkspace=self._out_ws,
Params=self._rebin_string)
if self._smooth:
WienerSmooth(InputWorkspace=self._out_ws,
OutputWorkspace='__smooth_temp')
CopyLogs(InputWorkspace=self._out_ws,
OutputWorkspace='__smooth_temp')
RenameWorkspace(InputWorkspace='__smooth_temp',
OutputWorkspace=self._out_ws)
self._post_process()
self.setProperty('OutputWorkspace', self._out_ws)
EndTime('IndirectResolution')
def _setup(self):
"""
Gets algorithm properties.
"""
from IndirectCommon import getWSprefix
self._sample = self.getPropertyValue('Sample')
self._resolution = self.getPropertyValue('Resolution')
self._e_min = self.getProperty('EnergyMin').value
self._e_max = self.getProperty('EnergyMax').value
self._number_points_per_bin = self.getProperty('NumBins').value
self._parameter_table = self.getPropertyValue('ParameterWorkspace')
if self._parameter_table == '':
self._parameter_table = getWSprefix(self._sample) + 'FuryParameters'
self._output_workspace = self.getPropertyValue('OutputWorkspace')
if self._output_workspace == '':
self._output_workspace = getWSprefix(self._sample) + 'iqt'
self._plot = self.getProperty('Plot').value
self._save = self.getProperty('Save').value
self._dry_run = self.getProperty('DryRun').value
def PyExec(self):
from IndirectCommon import getWSprefix
# Process vanadium workspace
van_ws = ConvertSpectrumAxis(
InputWorkspace=self._van_ws, OutputWorkspace="__ResNorm_vanadium", Target="ElasticQ", EMode="Indirect"
)
num_hist = van_ws.getNumberHistograms()
v_values = van_ws.getAxis(1).extractValues()
v_unit = van_ws.getAxis(1).getUnit().unitID()
# Process resolution workspace
padded_res_ws = self._process_res_ws(num_hist)
input_str = ""
for idx in range(num_hist):
input_str += "%s,i%d;" % (padded_res_ws, idx)
out_name = getWSprefix(self._res_ws) + "ResNorm_Fit"
function = "name=TabulatedFunction,Workspace=%s,Scaling=1,Shift=0,XScaling=1,ties=(Shift=0)" % self._van_ws
fit_params = PlotPeakByLogValue(
Input=input_str,
OutputWorkspace=out_name,
Function=function,
FitType="Individual",
PassWSIndexToFunction=True,
CreateOutput=self._create_output,
StartX=self._e_min,
EndX=self._e_max,
)
params = {"XScaling": "Stretch", "Scaling": "Intensity"}
result_workspaces = []
for param_name, output_name in params.items():
result_workspaces.append(self._process_fit_params(fit_params, param_name, v_values, v_unit, output_name))
GroupWorkspaces(InputWorkspaces=result_workspaces, OutputWorkspace=self._out_ws)
self.setProperty("OutputWorkspace", self._out_ws)
DeleteWorkspace(van_ws)
DeleteWorkspace(padded_res_ws)
if not self._create_output:
DeleteWorkspace(fit_params)
def PyExec(self):
from IndirectCommon import (getWSprefix, convertToElasticQ)
setup_prog = Progress(self, start=0.0, end=0.1, nreports=4)
self._fit_type = self._fit_type[:-2]
logger.information('Option: ' + self._fit_type)
logger.information(self._function)
setup_prog.report('Cropping workspace')
tmp_fit_name = "__IqtFit_ws"
crop_alg = self.createChildAlgorithm("CropWorkspace")
crop_alg.setProperty("InputWorkspace", self._input_ws)
crop_alg.setProperty("OutputWorkspace", tmp_fit_name)
crop_alg.setProperty("XMin", self._start_x)
crop_alg.setProperty("XMax", self._end_x)
crop_alg.execute()
num_hist = self._input_ws.getNumberHistograms()
if self._spec_max is None:
self._spec_max = num_hist - 1
# Name stem for generated workspace
output_workspace = '%sIqtFit_%s_s%d_to_%d' % (getWSprefix(
self._input_ws.getName()), self._fit_type, self._spec_min,
self._spec_max)
setup_prog.report('Converting to Histogram')
convert_to_hist_alg = self.createChildAlgorithm("ConvertToHistogram")
convert_to_hist_alg.setProperty(
"InputWorkspace",
crop_alg.getProperty("OutputWorkspace").value)
convert_to_hist_alg.setProperty("OutputWorkspace", tmp_fit_name)
convert_to_hist_alg.execute()
mtd.addOrReplace(
tmp_fit_name,
convert_to_hist_alg.getProperty("OutputWorkspace").value)
setup_prog.report('Convert to Elastic Q')
convertToElasticQ(tmp_fit_name)
# Build input string for PlotPeakByLogValue
input_str = [
tmp_fit_name + ',i%d' % i
for i in range(self._spec_min, self._spec_max + 1)
]
input_str = ';'.join(input_str)
fit_prog = Progress(self, start=0.1, end=0.8, nreports=2)
fit_prog.report('Fitting...')
ms.PlotPeakByLogValue(Input=input_str,
OutputWorkspace=output_workspace,
Function=self._function,
Minimizer=self._minimizer,
MaxIterations=self._max_iterations,
StartX=self._start_x,
EndX=self._end_x,
FitType='Sequential',
CreateOutput=True)
fit_prog.report('Fitting complete')
conclusion_prog = Progress(self, start=0.8, end=1.0, nreports=5)
# Remove unsused workspaces
delete_alg = self.createChildAlgorithm("DeleteWorkspace")
delete_alg.setProperty(
"Workspace", output_workspace + '_NormalisedCovarianceMatrices')
delete_alg.execute()
delete_alg.setProperty("Workspace", output_workspace + '_Parameters')
delete_alg.execute()
delete_alg.setProperty("Workspace", tmp_fit_name)
delete_alg.execute()
conclusion_prog.report('Renaming workspaces')
# rename workspaces to match user input
rename_alg = self.createChildAlgorithm("RenameWorkspace")
if output_workspace + "_Workspaces" != self._fit_group_name:
rename_alg.setProperty("InputWorkspace",
output_workspace + "_Workspaces")
rename_alg.setProperty("OutputWorkspace", self._fit_group_name)
rename_alg.execute()
if output_workspace != self._parameter_name:
rename_alg.setProperty("InputWorkspace", output_workspace)
rename_alg.setProperty("OutputWorkspace", self._parameter_name)
rename_alg.execute()
# Create *_Result workspace
parameter_names = 'A0,Intensity,Tau,Beta'
conclusion_prog.report('Processing indirect fit parameters')
pifp_alg = self.createChildAlgorithm("ProcessIndirectFitParameters")
pifp_alg.setProperty("InputWorkspace", self._parameter_name)
pifp_alg.setProperty("ColumnX", "axis-1")
pifp_alg.setProperty("XAxisUnit", "MomentumTransfer")
pifp_alg.setProperty("ParameterNames", parameter_names)
pifp_alg.setProperty("OutputWorkspace", self._result_name)
pifp_alg.execute()
self._result_ws = pifp_alg.getProperty("OutputWorkspace").value
mtd.addOrReplace(self._result_name, self._result_ws)
# Process generated workspaces
wsnames = mtd[self._fit_group_name].getNames()
for i, workspace in enumerate(wsnames):
output_ws = output_workspace + '_Workspace_%d' % i
rename_alg.setProperty("InputWorkspace", workspace)
rename_alg.setProperty("OutputWorkspace", output_ws)
rename_alg.execute()
conclusion_prog.report('Copying and transfering sample logs')
self._transfer_sample_logs()
self.setProperty('OutputParameterWorkspace', self._parameter_name)
self.setProperty('OutputWorkspaceGroup', self._fit_group_name)
self.setProperty('OutputResultWorkspace', self._result_ws)
conclusion_prog.report('Algorithm complete')
def PyExec(self):
from IndirectCommon import (getWSprefix, convertToElasticQ)
setup_prog = Progress(self, start=0.0, end=0.1, nreports=4)
self._fit_type = self._fit_type[:-2]
logger.information('Option: ' + self._fit_type)
logger.information(self._function)
setup_prog.report('Cropping workspace')
tmp_fit_name = "__IqtFit_ws"
crop_alg = self.createChildAlgorithm("CropWorkspace", enableLogging=False)
crop_alg.setProperty("InputWorkspace", self._input_ws)
crop_alg.setProperty("OutputWorkspace", tmp_fit_name)
crop_alg.setProperty("XMin", self._start_x)
crop_alg.setProperty("XMax", self._end_x)
crop_alg.execute()
num_hist = self._input_ws.getNumberHistograms()
if self._spec_max is None:
self._spec_max = num_hist - 1
# Name stem for generated workspace
output_workspace = '%sIqtFit_%s_s%d_to_%d' % (getWSprefix(self._input_ws.name()),
self._fit_type, self._spec_min,
self._spec_max)
setup_prog.report('Converting to Histogram')
convert_to_hist_alg = self.createChildAlgorithm("ConvertToHistogram", enableLogging=False)
convert_to_hist_alg.setProperty("InputWorkspace", crop_alg.getProperty("OutputWorkspace").value)
convert_to_hist_alg.setProperty("OutputWorkspace", tmp_fit_name)
convert_to_hist_alg.execute()
mtd.addOrReplace(tmp_fit_name, convert_to_hist_alg.getProperty("OutputWorkspace").value)
setup_prog.report('Convert to Elastic Q')
convertToElasticQ(tmp_fit_name)
# Build input string for PlotPeakByLogValue
input_str = [tmp_fit_name + ',i%d' % i for i in range(self._spec_min, self._spec_max + 1)]
input_str = ';'.join(input_str)
fit_prog = Progress(self, start=0.1, end=0.8, nreports=2)
fit_prog.report('Fitting...')
ms.PlotPeakByLogValue(Input=input_str,
OutputWorkspace=output_workspace,
Function=self._function,
Minimizer=self._minimizer,
MaxIterations=self._max_iterations,
StartX=self._start_x,
EndX=self._end_x,
FitType='Sequential',
CreateOutput=True)
fit_prog.report('Fitting complete')
conclusion_prog = Progress(self, start=0.8, end=1.0, nreports=5)
# Remove unused workspaces
delete_alg = self.createChildAlgorithm("DeleteWorkspace", enableLogging=False)
delete_alg.setProperty("Workspace", output_workspace + '_NormalisedCovarianceMatrices')
delete_alg.execute()
delete_alg.setProperty("Workspace", output_workspace + '_Parameters')
delete_alg.execute()
delete_alg.setProperty("Workspace", tmp_fit_name)
delete_alg.execute()
conclusion_prog.report('Renaming workspaces')
# rename workspaces to match user input
rename_alg = self.createChildAlgorithm("RenameWorkspace", enableLogging=False)
if output_workspace + "_Workspaces" != self._fit_group_name:
rename_alg.setProperty("InputWorkspace", output_workspace + "_Workspaces")
rename_alg.setProperty("OutputWorkspace", self._fit_group_name)
rename_alg.execute()
if output_workspace != self._parameter_name:
rename_alg.setProperty("InputWorkspace", output_workspace)
rename_alg.setProperty("OutputWorkspace", self._parameter_name)
rename_alg.execute()
# Create *_Result workspace
parameter_names = 'A0,Height,Lifetime,Stretching'
conclusion_prog.report('Processing indirect fit parameters')
pifp_alg = self.createChildAlgorithm("ProcessIndirectFitParameters")
pifp_alg.setProperty("InputWorkspace", self._parameter_name)
pifp_alg.setProperty("ColumnX", "axis-1")
pifp_alg.setProperty("XAxisUnit", "MomentumTransfer")
pifp_alg.setProperty("ParameterNames", parameter_names)
pifp_alg.setProperty("OutputWorkspace", self._result_name)
pifp_alg.execute()
self._result_ws = pifp_alg.getProperty("OutputWorkspace").value
mtd.addOrReplace(self._result_name, self._result_ws)
# Process generated workspaces
wsnames = mtd[self._fit_group_name].getNames()
for i, workspace in enumerate(wsnames):
output_ws = output_workspace + '_Workspace_%d' % i
rename_alg.setProperty("InputWorkspace", workspace)
rename_alg.setProperty("OutputWorkspace", output_ws)
rename_alg.execute()
conclusion_prog.report('Copying and transferring sample logs')
self._transfer_sample_logs()
self.setProperty('OutputParameterWorkspace', self._parameter_name)
self.setProperty('OutputWorkspaceGroup', self._fit_group_name)
self.setProperty('OutputResultWorkspace', self._result_ws)
conclusion_prog.report('Algorithm complete')
