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Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MatrixWorkspace | Mandatory | |
OutputWorkspace | Output | MatrixWorkspace | Mandatory | |
Method | Input | string | Value | Scaling method - either a simple scaling by value or using a reference data set. Allowed values: [‘Value’, ‘ReferenceData’] |
ScalingFactor | Input | number | 1 | Scaling factor to use with the Value method |
ReferenceDataFilename | Input | string | Reference data file to compute the scaling factor. Allowed values: [‘xml’, ‘nxs’, ‘nxs.h5’] | |
BeamstopDiameter | Input | number | 0 | Diameter of the beam on the detector, in mm |
AttenuatorTransmission | Input | number | 1 | Attenuator transmission used in the measurement |
ApplySensitivity | Input | boolean | False | If True, the sensitivity correction will be applied to the reference data set |
ReductionProperties | Input | string | __sans_reduction_properties | Property manager name for the reduction |
OutputMessage | Output | string | Output message |
Calculate and apply absolute scale correction for SANS data. The method used can either be a simple scaling using the ScalingFactor property, or computing the scaling factor using a reference data set. In this case, the reference data is loaded, normalized and corrected for detector sensitivity. The corrected reference data is then used to compute the scaling factor according to
\(f = \frac{N_b}{M*T} ( d/L )^2\)
where \(N_b\) is the total count within the distance of a beam diameter of the beam center.
\(M\) is the monitor count.
\(T\) is the attenuator transmission.
\(d\) is the detector pixel width.
\(L\) is the sample-detector distance.
The input workspace is then scaled by \(1/f\).
This algorithm is rarely called directly. It is called by HFIRSANSReduction.
Categories: AlgorithmIndex | Workflow\SANS\UsesPropertyManager
Python: SANSAbsoluteScale.py