DirectILLApplySelfShielding dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MatrixWorkspace | Mandatory | Input workspace. |
| OutputWorkspace | Output | Workspace | Mandatory | The output of the algorithm. |
| Cleanup | Input | string | Cleanup ON | What to do with intermediate workspaces. Allowed values: [‘Cleanup ON’, ‘Cleanup OFF’] |
| SubalgorithmLogging | Input | string | Logging OFF | Enable or disable subalgorithms to print in the logs. Allowed values: [‘Logging OFF’, ‘Logging ON’] |
| EmptyContainerWorkspace | Input | MatrixWorkspace | Reduced empty container workspace. | |
| EmptyContainerScaling | Input | number | 1 | Scaling factor (transmission, if no self shielding is applied) for empty container. |
| SelfShieldingCorrectionWorkspace | Input | MatrixWorkspace | A workspace containing self shielding correction factors. |
This algorithm subtracts empty container data and applies self-shielding corrections to InputWorkspace. Both operations are optional: what is actually done depends on the input properties.
This algorithm is part of ILL’s direct geometry data reduction algorithms.
SelfShieldingCorrectionWorkspace can be obtained from the DirectILLSelfShielding algorithm.
Example - Absorption corrections and empty container subtraction
import numpy
import scipy.stats
# Create a fake IN4 workspace.
# We need an instrument and a template first.
empty_IN4 = LoadEmptyInstrument(InstrumentName='IN4')
nHist = empty_IN4.getNumberHistograms()
# Make TOF bin edges.
xs = numpy.arange(530.0, 2420.0, 4.0)
# Make some Gaussian spectra.
ys = 1000.0 * scipy.stats.norm.pdf(xs[:-1], loc=970, scale=60)
# Repeat data for each histogram.
xs = numpy.tile(xs, nHist)
ys = numpy.tile(ys, nHist)
ws = CreateWorkspace(
DataX=xs,
DataY=ys,
NSpec=nHist,
UnitX='TOF',
ParentWorkspace=empty_IN4
)
# Manually correct monitor spectrum number as LoadEmptyInstrument does
# not know about such details.
SetInstrumentParameter(
Workspace=ws,
ParameterName='default-incident-monitor-spectrum',
ParameterType='Number',
Value=str(1)
)
# Add incident energy information to sample logs.
AddSampleLog(
Workspace=ws,
LogName='Ei',
LogText=str(57),
LogType='Number',
LogUnit='meV',
NumberType='Double'
)
# Elastic channel information is missing in the sample logs.
# It can be given as single valued workspace, as well.
elasticChannelWS = CreateSingleValuedWorkspace(107)
# Create a fake 'empty container' workspace for background subtraction.
ecws = Scale(
InputWorkspace=ws,
Factor=0.1
)
DirectILLCollectData(
InputWorkspace=ws,
OutputWorkspace='preprocessed',
ElasticChannelWorkspace=elasticChannelWS,
IncidentEnergyCalibration='Energy Calibration OFF', # Normally we would do this for IN4.
)
DirectILLCollectData(
InputWorkspace=ecws,
OutputWorkspace='preprocessed_ecws',
ElasticChannelWorkspace=elasticChannelWS,
IncidentEnergyCalibration='Energy Calibration OFF'
)
sampleGeometry = {
'Shape': 'Cylinder',
'Height': 8.0,
'Radius': 1.5,
'Center': [0.0, 0.0, 0.0]
}
sampleMaterial = {
'ChemicalFormula': 'V',
'SampleNumberDensity': 0.05
}
SetSample(
InputWorkspace='preprocessed',
Geometry=sampleGeometry,
Material=sampleMaterial
)
DirectILLSelfShielding(
InputWorkspace='preprocessed',
OutputWorkspace='absorption_corrections',
SimulationInstrument='Full Instrument', # IN4 is small enough.
NumberOfSimulatedWavelengths=10
)
DirectILLApplySelfShielding(
InputWorkspace='preprocessed',
OutputWorkspace='absorptionCorrected',
EmptyContainerWorkspace='preprocessed_ecws',
SelfShieldingCorrectionWorkspace='absorption_corrections'
)
preprocessed = mtd['preprocessed']
maxY = numpy.amax(preprocessed.readY(0))
print('Elastic peak maximum before corrections: {:.3}'.format(maxY))
corrected = mtd['absorptionCorrected']
maxY = numpy.amax(corrected.readY(0))
print('After empty container subtraction and absorption corrections: {:.3}'.format(maxY))
Output:
Elastic peak maximum before corrections: 26.7
After empty container subtraction and absorption corrections: 48.0
Categories: Algorithms | Workflow\Inelastic