def PyExec(self):
self._setup()
process_prog = Progress(self,
start=0.1,
end=0.9,
nreports=len(self._workspace_names))
process_prog.report("Running diffraction")
scan_alg = self.createChildAlgorithm(
"ISISIndirectDiffractionReduction", 0.05, 0.95)
scan_alg.setProperty(
'InputFiles', formatRuns(self._data_files, self._instrument_name))
scan_alg.setProperty('ContainerFiles', self._can_files)
scan_alg.setProperty('ContainerScaleFactor', self._can_scale)
scan_alg.setProperty('CalFile', self._calib_file)
scan_alg.setProperty('SumFiles', self._sum_files)
scan_alg.setProperty('LoadLogFiles', self._load_logs)
scan_alg.setProperty('Instrument', self._instrument_name)
scan_alg.setProperty('Mode', self._mode)
scan_alg.setProperty('SpectraRange', self._spectra_range)
scan_alg.setProperty('RebinParam', self._rebin_paras)
scan_alg.setProperty('GroupingPolicy', self._grouping_method)
scan_alg.setProperty('OutputWorkspace', self._output_ws)
scan_alg.execute()
logger.information('OutputWorkspace : %s' % self._output_ws)
self.setProperty('OutputWorkspace',
scan_alg.getPropertyValue('OutputWorkspace'))
workspace_names = mtd[self._output_ws].getNames()
scan_workspace = self._output_ws + '_scan'
temperatures = list()
run_numbers = []
for input_ws in workspace_names:
temp = self._get_temperature(input_ws)
if temp is not None:
temperatures.append(temp)
# Get the run number
run_no = self._get_InstrRun(input_ws)[1]
run_numbers.append(run_no)
clone_alg = self.createChildAlgorithm("CloneWorkspace",
enableLogging=False)
append_alg = self.createChildAlgorithm("AppendSpectra",
enableLogging=False)
for idx in range(len(workspace_names)):
if idx == 0:
clone_alg.setProperty("InputWorkspace", workspace_names[0])
clone_alg.setProperty("OutputWorkspace", scan_workspace)
clone_alg.execute()
scan_workspace = clone_alg.getProperty("OutputWorkspace").value
else:
append_alg.setProperty("InputWorkspace1", scan_workspace)
append_alg.setProperty("InputWorkspace2", workspace_names[idx])
append_alg.setProperty("OutputWorkspace", scan_workspace)
append_alg.execute()
scan_workspace = append_alg.getProperty(
"OutputWorkspace").value
# Set the vertical axis units
num_hist = scan_workspace.getNumberHistograms()
v_axis_is_temp = num_hist == len(temperatures)
if v_axis_is_temp:
logger.notice('Vertical axis is in temperature')
unit = ('Temperature', 'K')
else:
logger.notice('Vertical axis is in run number')
unit = ('Run No', '_last 3 digits')
# Create a new vertical axis for the workspaces
y_ws_axis = NumericAxis.create(len(run_numbers))
y_ws_axis.setUnit("Label").setLabel(unit[0], unit[1])
# Set the vertical axis values
for idx in range(num_hist):
if v_axis_is_temp:
y_ws_axis.setValue(idx, float(temperatures[idx]))
else:
y_ws_axis.setValue(idx, float(run_numbers[idx][-3:]))
# Add the new vertical axis to each workspace
scan_workspace.replaceAxis(1, y_ws_axis)
mtd.addOrReplace(self._output_ws + '_scan', scan_workspace)
def PyExec(self):
self._setup()
progress = Progress(self, 0.0, 0.05, 3)
progress.report('Energy transfer')
scan_alg = self.createChildAlgorithm("ISISIndirectEnergyTransferWrapper", 0.05, 0.95)
scan_alg.setProperty('InputFiles', formatRuns(self._data_files, self._instrument_name))
scan_alg.setProperty('SumFiles', self._sum_files)
scan_alg.setProperty('LoadLogFiles', self._load_logs)
scan_alg.setProperty('CalibrationWorkspace', self._calibration_ws)
scan_alg.setProperty('Instrument', self._instrument_name)
scan_alg.setProperty('Analyser', self._analyser)
scan_alg.setProperty('Reflection', self._reflection)
scan_alg.setProperty('Efixed', self._efixed)
scan_alg.setProperty('SpectraRange', self._spectra_range)
scan_alg.setProperty('BackgroundRange', self._background_range)
scan_alg.setProperty('RebinString', self._rebin_string)
scan_alg.setProperty('DetailedBalance', self._detailed_balance)
scan_alg.setProperty('ScaleFactor', self._scale_factor)
scan_alg.setProperty('FoldMultipleFrames', self._fold_multiple_frames)
scan_alg.setProperty('GroupingMethod', self._grouping_method)
scan_alg.setProperty('GroupingWorkspace', self._grouping_ws)
scan_alg.setProperty('MapFile', self._grouping_map_file)
scan_alg.setProperty('UnitX', self._output_x_units)
scan_alg.setProperty('OutputWorkspace', self._red_ws)
scan_alg.execute()
logger.information('ReducedWorkspace : %s' % self._red_ws)
Rebin(InputWorkspace=self._red_ws,
OutputWorkspace=self._red_ws,
Params=self._energy_range,
EnableLogging=False)
input_workspace_names = mtd[self._red_ws].getNames()
inst = mtd[input_workspace_names[0]].getInstrument()
if inst.hasParameter('analyser'):
analyser_name = inst.getStringParameter('analyser')[0]
analyser_comp = inst.getComponentByName(analyser_name)
if analyser_comp is not None and analyser_comp.hasParameter('resolution'):
self._resolution = float(analyser_comp.getNumberParameter('resolution')[0])
else:
self._resolution = 0.01
logger.information('Resolution = %d' % self._resolution)
output_workspaces = list()
temperatures = list()
run_numbers = list()
sofqw_alg = self.createChildAlgorithm("SofQW", enableLogging=False)
group_alg = self.createChildAlgorithm("GroupWorkspaces", enableLogging=False)
for input_ws in input_workspace_names:
progress.report('SofQW for workspace: %s' % input_ws)
sofqw_alg.setProperty("InputWorkspace", input_ws)
sofqw_alg.setProperty("QAxisBinning", self._q_range)
sofqw_alg.setProperty("EMode", 'Indirect')
sofqw_alg.setProperty("ReplaceNaNs", True)
sofqw_alg.setProperty("Method", 'NormalisedPolygon')
sofqw_alg.setProperty("OutputWorkspace", input_ws + '_sqw')
sofqw_alg.execute()
mtd.addOrReplace(input_ws + '_sqw', sofqw_alg.getProperty("OutputWorkspace").value)
output_workspaces.append(input_ws + '_sqw')
# Get the sample temperature
temp = self._get_temperature(input_ws + '_sqw')
if temp is not None:
temperatures.append(temp)
else:
# Get the run number
run_no = self._get_InstrRun(input_ws)[1]
run_numbers.append(run_no)
y_axis = mtd[input_workspace_names[0] + '_sqw'].getAxis(1)
y_values = y_axis.extractValues()
q = list()
for idx in range(len(y_values)):
q.append(y_values[idx])
group_alg.setProperty("InputWorkspaces", output_workspaces)
group_alg.setProperty("OutputWorkspace", self._sqw_ws)
group_alg.execute()
mtd.addOrReplace(self._sqw_ws, group_alg.getProperty("OutputWorkspace").value)
logger.information('Sqw Workspace : %s' % self._sqw_ws)
# Get input workspaces
input_workspace_names = mtd[self._sqw_ws].getNames()
output_workspaces = list()
width_workspaces = list()
delete_alg = self.createChildAlgorithm("DeleteWorkspace", enableLogging=False)
create_alg = self.createChildAlgorithm("CreateWorkspace", enableLogging=False)
for input_ws in input_workspace_names:
progress.report('SofQWMoments for workspace: %s' % input_ws)
SofQWMoments(InputWorkspace=input_ws,
EnergyMin=self._energy_range[0],
EnergyMax=self._energy_range[2],
Scale=self._scale_factor,
OutputWorkspace=input_ws + '_mom',
EnableLogging=False)
output_workspaces.append(input_ws + '_mom')
progress.report('Fitting workspace: %s' % input_ws)
num_hist = mtd[input_ws].getNumberHistograms()
result = '__result'
params_table = '__result_Parameters'
dataX = list()
dataY = list()
dataE = list()
func = 'name=Lorentzian,Amplitude=1.0,PeakCentre=0.0,FWHM=0.01'
func += ',constraint=(Amplitude>0.0,FWHM>0.0)'
for idx in range(num_hist):
Fit(InputWorkspace=input_ws,
Function=func,
DomainType='Simple',
WorkspaceIndex=idx,
Minimizer='Levenberg-Marquardt',
MaxIterations=500,
CreateOutput=True,
Output=result,
OutputParametersOnly=False,
EnableLogging=False)
dataX.append(q[idx])
para_y = np.asarray(mtd[params_table].column('Value'))
dataY.append(para_y[2])
para_e = np.asarray(mtd[params_table].column('Error'))
dataE.append(para_e[2])
progress.report('Creating width workspace')
width_ws = input_ws + '_width'
create_alg.setProperty("OutputWorkspace", width_ws)
create_alg.setProperty("DataX", dataX)
create_alg.setProperty("DataY", dataY)
create_alg.setProperty("DataE", dataE)
create_alg.setProperty("NSpec", 1)
create_alg.setProperty("UnitX", 'MomentumTransfer')
create_alg.setProperty("YUnitLabel", 'FWHM')
create_alg.execute()
mtd.addOrReplace(width_ws, create_alg.getProperty("OutputWorkspace").value)
width_workspaces.append(width_ws)
delete_alg.setProperty("Workspace", params_table)
delete_alg.execute()
delete_alg.setProperty("Workspace", result + '_NormalisedCovarianceMatrix')
delete_alg.execute()
delete_alg.setProperty("Workspace", result + '_Workspace')
delete_alg.execute()
logger.information('Moment Workspace : %s' % self._moment_ws)
width_workspace = self._sqw_ws + '_width'
clone_alg = self.createChildAlgorithm("CloneWorkspace", enableLogging=True)
append_alg = self.createChildAlgorithm("AppendSpectra", enableLogging=True)
for idx in range(len(width_workspaces)):
if idx == 0:
clone_alg.setProperty("InputWorkspace", width_workspaces[0])
clone_alg.setProperty("OutputWorkspace", width_workspace)
clone_alg.execute()
mtd.addOrReplace(width_workspace, clone_alg.getProperty("OutputWorkspace").value)
else:
append_alg.setProperty("InputWorkspace1", width_workspace)
append_alg.setProperty("InputWorkspace2", width_workspaces[idx])
append_alg.setProperty("OutputWorkspace", width_workspace)
append_alg.execute()
mtd.addOrReplace(width_workspace, append_alg.getProperty("OutputWorkspace").value)
logger.information('Width Workspace : %s' % width_workspace)
numb_temp = len(temperatures)
x_axis_is_temp = len(input_workspace_names) == numb_temp
if x_axis_is_temp:
logger.information('X axis is in temperature')
unit = ('Temperature', 'K')
else:
logger.information('X axis is in run number')
unit = ('Run No', 'last 3 digits')
xdat = list()
ydat = list()
edat = list()
for idx in range(len(temperatures)):
x = mtd[width_workspace].readX(idx)
y = mtd[width_workspace].readY(idx)
e = mtd[width_workspace].readE(idx)
if x_axis_is_temp:
xdat.append(float(temperatures[idx]))
else:
xdat.append(float(run_numbers[idx][-3:]))
ydat.append(y[5] / x[5])
edat.append(e[5] / x[5])
diffusion_workspace = self._sqw_ws + '_diffusion'
create_alg = self.createChildAlgorithm("CreateWorkspace", enableLogging=False)
create_alg.setProperty("OutputWorkspace", diffusion_workspace)
create_alg.setProperty("DataX", xdat)
create_alg.setProperty("DataY", ydat)
create_alg.setProperty("DataE", edat)
create_alg.setProperty("NSpec", 1)
create_alg.setProperty("YUnitLabel", 'Diffusion')
create_alg.execute()
mtd.addOrReplace(diffusion_workspace, create_alg.getProperty("OutputWorkspace").value)
unitx = mtd[diffusion_workspace].getAxis(0).setUnit("Label")
unitx.setLabel(unit[0], unit[1])
logger.information('Diffusion Workspace : %s' % diffusion_workspace)
def PyExec(self):
self._setup()
progress = Progress(self, 0.0, 0.05, 3)
progress.report('Energy transfer')
scan_alg = self.createChildAlgorithm(
"ISISIndirectEnergyTransferWrapper", 0.05, 0.95)
scan_alg.setProperty(
'InputFiles', formatRuns(self._data_files, self._instrument_name))
scan_alg.setProperty('SumFiles', self._sum_files)
scan_alg.setProperty('LoadLogFiles', self._load_logs)
scan_alg.setProperty('CalibrationWorkspace', self._calibration_ws)
scan_alg.setProperty('Instrument', self._instrument_name)
scan_alg.setProperty('Analyser', self._analyser)
scan_alg.setProperty('Reflection', self._reflection)
scan_alg.setProperty('Efixed', self._efixed)
scan_alg.setProperty('SpectraRange', self._spectra_range)
scan_alg.setProperty('BackgroundRange', self._background_range)
scan_alg.setProperty('RebinString', self._rebin_string)
scan_alg.setProperty('DetailedBalance', self._detailed_balance)
scan_alg.setProperty('ScaleFactor', self._scale_factor)
scan_alg.setProperty('FoldMultipleFrames', self._fold_multiple_frames)
scan_alg.setProperty('GroupingMethod', self._grouping_method)
scan_alg.setProperty('GroupingWorkspace', self._grouping_ws)
scan_alg.setProperty('MapFile', self._grouping_map_file)
scan_alg.setProperty('UnitX', self._output_x_units)
scan_alg.setProperty('OutputWorkspace', self._red_ws)
scan_alg.execute()
logger.information('ReducedWorkspace : %s' % self._red_ws)
Rebin(InputWorkspace=self._red_ws,
OutputWorkspace=self._red_ws,
Params=self._energy_range,
EnableLogging=False)
input_workspace_names = mtd[self._red_ws].getNames()
inst = mtd[input_workspace_names[0]].getInstrument()
if inst.hasParameter('analyser'):
analyser_name = inst.getStringParameter('analyser')[0]
analyser_comp = inst.getComponentByName(analyser_name)
if analyser_comp is not None and analyser_comp.hasParameter(
'resolution'):
self._resolution = float(
analyser_comp.getNumberParameter('resolution')[0])
else:
self._resolution = 0.01
logger.information('Resolution = %d' % self._resolution)
output_workspaces = list()
temperatures = list()
run_numbers = list()
sofqw_alg = self.createChildAlgorithm("SofQW", enableLogging=False)
group_alg = self.createChildAlgorithm("GroupWorkspaces",
enableLogging=False)
for input_ws in input_workspace_names:
progress.report('SofQW for workspace: %s' % input_ws)
sofqw_alg.setProperty("InputWorkspace", input_ws)
sofqw_alg.setProperty("QAxisBinning", self._q_range)
sofqw_alg.setProperty("EMode", 'Indirect')
sofqw_alg.setProperty("ReplaceNaNs", True)
sofqw_alg.setProperty("Method", 'NormalisedPolygon')
sofqw_alg.setProperty("OutputWorkspace", input_ws + '_sqw')
sofqw_alg.execute()
mtd.addOrReplace(input_ws + '_sqw',
sofqw_alg.getProperty("OutputWorkspace").value)
output_workspaces.append(input_ws + '_sqw')
# Get the sample temperature
temp = self._get_temperature(input_ws + '_sqw')
if temp is not None:
temperatures.append(temp)
else:
# Get the run number
run_no = self._get_InstrRun(input_ws)[1]
run_numbers.append(run_no)
y_axis = mtd[input_workspace_names[0] + '_sqw'].getAxis(1)
y_values = y_axis.extractValues()
q = list()
for idx in range(len(y_values)):
q.append(y_values[idx])
group_alg.setProperty("InputWorkspaces", output_workspaces)
group_alg.setProperty("OutputWorkspace", self._sqw_ws)
group_alg.execute()
mtd.addOrReplace(self._sqw_ws,
group_alg.getProperty("OutputWorkspace").value)
logger.information('Sqw Workspace : %s' % self._sqw_ws)
# Get input workspaces
input_workspace_names = mtd[self._sqw_ws].getNames()
output_workspaces = list()
width_workspaces = list()
delete_alg = self.createChildAlgorithm("DeleteWorkspace",
enableLogging=False)
create_alg = self.createChildAlgorithm("CreateWorkspace",
enableLogging=False)
for input_ws in input_workspace_names:
progress.report('SofQWMoments for workspace: %s' % input_ws)
SofQWMoments(InputWorkspace=input_ws,
EnergyMin=self._energy_range[0],
EnergyMax=self._energy_range[2],
Scale=self._scale_factor,
OutputWorkspace=input_ws + '_mom',
EnableLogging=False)
output_workspaces.append(input_ws + '_mom')
progress.report('Fitting workspace: %s' % input_ws)
num_hist = mtd[input_ws].getNumberHistograms()
result = '__result'
params_table = '__result_Parameters'
dataX = list()
dataY = list()
dataE = list()
func = 'name=Lorentzian,Amplitude=1.0,PeakCentre=0.0,FWHM=0.01'
func += ',constraint=(Amplitude>0.0,FWHM>0.0)'
for idx in range(num_hist):
Fit(InputWorkspace=input_ws,
Function=func,
DomainType='Simple',
WorkspaceIndex=idx,
Minimizer='Levenberg-Marquardt',
MaxIterations=500,
CreateOutput=True,
Output=result,
OutputParametersOnly=False,
EnableLogging=False)
dataX.append(q[idx])
para_y = np.asarray(mtd[params_table].column('Value'))
dataY.append(para_y[2])
para_e = np.asarray(mtd[params_table].column('Error'))
dataE.append(para_e[2])
progress.report('Creating width workspace')
width_ws = input_ws + '_width'
create_alg.setProperty("OutputWorkspace", width_ws)
create_alg.setProperty("DataX", dataX)
create_alg.setProperty("DataY", dataY)
create_alg.setProperty("DataE", dataE)
create_alg.setProperty("NSpec", 1)
create_alg.setProperty("UnitX", 'MomentumTransfer')
create_alg.setProperty("YUnitLabel", 'FWHM')
create_alg.execute()
mtd.addOrReplace(width_ws,
create_alg.getProperty("OutputWorkspace").value)
width_workspaces.append(width_ws)
delete_alg.setProperty("Workspace", params_table)
delete_alg.execute()
delete_alg.setProperty("Workspace",
result + '_NormalisedCovarianceMatrix')
delete_alg.execute()
delete_alg.setProperty("Workspace", result + '_Workspace')
delete_alg.execute()
logger.information('Moment Workspace : %s' % self._moment_ws)
width_workspace = self._sqw_ws + '_width'
clone_alg = self.createChildAlgorithm("CloneWorkspace",
enableLogging=True)
append_alg = self.createChildAlgorithm("AppendSpectra",
enableLogging=True)
for idx in range(len(width_workspaces)):
if idx == 0:
clone_alg.setProperty("InputWorkspace", width_workspaces[0])
clone_alg.setProperty("OutputWorkspace", width_workspace)
clone_alg.execute()
mtd.addOrReplace(
width_workspace,
clone_alg.getProperty("OutputWorkspace").value)
else:
append_alg.setProperty("InputWorkspace1", width_workspace)
append_alg.setProperty("InputWorkspace2",
width_workspaces[idx])
append_alg.setProperty("OutputWorkspace", width_workspace)
append_alg.execute()
mtd.addOrReplace(
width_workspace,
append_alg.getProperty("OutputWorkspace").value)
logger.information('Width Workspace : %s' % width_workspace)
numb_temp = len(temperatures)
x_axis_is_temp = len(input_workspace_names) == numb_temp
if x_axis_is_temp:
logger.information('X axis is in temperature')
unit = ('Temperature', 'K')
else:
logger.information('X axis is in run number')
unit = ('Run No', 'last 3 digits')
xdat = list()
ydat = list()
edat = list()
for idx in range(len(temperatures)):
x = mtd[width_workspace].readX(idx)
y = mtd[width_workspace].readY(idx)
e = mtd[width_workspace].readE(idx)
if x_axis_is_temp:
xdat.append(float(temperatures[idx]))
else:
xdat.append(float(run_numbers[idx][-3:]))
ydat.append(y[5] / x[5])
edat.append(e[5] / x[5])
diffusion_workspace = self._sqw_ws + '_diffusion'
create_alg = self.createChildAlgorithm("CreateWorkspace",
enableLogging=False)
create_alg.setProperty("OutputWorkspace", diffusion_workspace)
create_alg.setProperty("DataX", xdat)
create_alg.setProperty("DataY", ydat)
create_alg.setProperty("DataE", edat)
create_alg.setProperty("NSpec", 1)
create_alg.setProperty("YUnitLabel", 'Diffusion')
create_alg.execute()
mtd.addOrReplace(diffusion_workspace,
create_alg.getProperty("OutputWorkspace").value)
unitx = mtd[diffusion_workspace].getAxis(0).setUnit("Label")
unitx.setLabel(unit[0], unit[1])
logger.information('Diffusion Workspace : %s' % diffusion_workspace)
def PyExec(self):
self._setup()
process_prog = Progress(self, start=0.1, end=0.9, nreports=len(self._workspace_names))
process_prog.report("Running diffraction")
scan_alg = self.createChildAlgorithm("ISISIndirectDiffractionReduction", 0.05, 0.95)
scan_alg.setProperty('InputFiles', formatRuns(self._data_files, self._instrument_name))
scan_alg.setProperty('ContainerFiles', self._can_files)
scan_alg.setProperty('ContainerScaleFactor', self._can_scale)
scan_alg.setProperty('CalFile', self._calib_file)
scan_alg.setProperty('SumFiles', self._sum_files)
scan_alg.setProperty('LoadLogFiles', self._load_logs)
scan_alg.setProperty('Instrument', self._instrument_name)
scan_alg.setProperty('Mode', self._mode)
scan_alg.setProperty('SpectraRange', self._spectra_range)
scan_alg.setProperty('RebinParam', self._rebin_paras)
scan_alg.setProperty('GroupingPolicy', self._grouping_method)
scan_alg.setProperty('OutputWorkspace', self._output_ws)
scan_alg.execute()
logger.information('OutputWorkspace : %s' % self._output_ws)
self.setProperty('OutputWorkspace', scan_alg.getPropertyValue('OutputWorkspace'))
workspace_names = mtd[self._output_ws].getNames()
scan_workspace = self._output_ws + '_scan'
temperatures = list()
run_numbers = []
for input_ws in workspace_names:
temp = self._get_temperature(input_ws)
if temp is not None:
temperatures.append(temp)
# Get the run number
run_no = self._get_InstrRun(input_ws)[1]
run_numbers.append(run_no)
clone_alg = self.createChildAlgorithm("CloneWorkspace", enableLogging=False)
append_alg = self.createChildAlgorithm("AppendSpectra", enableLogging=False)
for idx in range(len(workspace_names)):
if idx == 0:
clone_alg.setProperty("InputWorkspace", workspace_names[0])
clone_alg.setProperty("OutputWorkspace", scan_workspace)
clone_alg.execute()
scan_workspace = clone_alg.getProperty("OutputWorkspace").value
else:
append_alg.setProperty("InputWorkspace1", scan_workspace)
append_alg.setProperty("InputWorkspace2", workspace_names[idx])
append_alg.setProperty("OutputWorkspace", scan_workspace)
append_alg.execute()
scan_workspace = append_alg.getProperty("OutputWorkspace").value
# Set the vertical axis units
num_hist = scan_workspace.getNumberHistograms()
v_axis_is_temp = num_hist == len(temperatures)
if v_axis_is_temp:
logger.notice('Vertical axis is in temperature')
unit = ('Temperature', 'K')
else:
logger.notice('Vertical axis is in run number')
unit = ('Run No', '_last 3 digits')
# Create a new vertical axis for the workspaces
y_ws_axis = NumericAxis.create(len(run_numbers))
y_ws_axis.setUnit("Label").setLabel(unit[0], unit[1])
# Set the vertical axis values
for idx in range(num_hist):
if v_axis_is_temp:
y_ws_axis.setValue(idx, float(temperatures[idx]))
else:
y_ws_axis.setValue(idx, float(run_numbers[idx][-3:]))
# Add the new vertical axis to each workspace
scan_workspace.replaceAxis(1, y_ws_axis)
mtd.addOrReplace(self._output_ws + '_scan', scan_workspace)