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BayesStretch2 v1¶
Summary¶
Creates a grid showing the variation of a stretched exponential function for different FWHM and beta values.
Properties¶
Name |
Direction |
Type |
Default |
Description |
|---|---|---|---|---|
NumberProcessors |
Input |
long |
12 |
Number of cpu’s to use, default is all’ |
NumberFWHM |
Input |
long |
3 |
Number of sigma values |
NumberBeta |
Input |
long |
3 |
Number of beta values |
StartBeta |
Input |
number |
0.5 |
Start of beta values |
EndBeta |
Input |
number |
1 |
End of beta values |
StartFWHM |
Input |
number |
0.01 |
Start of FWHM values |
EndFWHM |
Input |
number |
0.1 |
End of FWHM values |
SampleWorkspace |
Input |
Mandatory |
Name of the Sample input Workspace |
|
ResolutionWorkspace |
Input |
Mandatory |
Name of the resolution input Workspace |
|
EMin |
Input |
number |
-0.2 |
The start of the fit range. Default=-0.2 |
EMax |
Input |
number |
0.2 |
The end of the fit range. Default=0.2 |
Elastic |
Input |
boolean |
True |
Fit option for using the elastic peak |
Background |
Input |
string |
Flat |
Fit option for the type of background. Allowed values: [‘Linear’, ‘Flat’, ‘None’] |
OutputWorkspaceFit |
Output |
WorkspaceGroup |
Mandatory |
The name of the fit output workspaces |
OutputWorkspaceContour |
Output |
WorkspaceGroup |
Mandatory |
The name of the contour output workspaces |
Description¶
This is a variation of the stretched exponential option of Quasi. For each spectrum a fit is performed for a grid of \(\beta\) a FWHM values. The unnormalised probability is given for the \(z\) values.
This routine replaces the BayesStretch algorithm.
Categories: AlgorithmIndex | Workflow\MIDAS
Source¶
Python: BayesStretch2.py