AlphaCalc dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MatrixWorkspace | Mandatory | Name of the input workspace |
| ForwardSpectra | Input | int list | 1 | The spectra numbers of the forward group (default to 1) |
| BackwardSpectra | Input | int list | 2 | The spectra numbers of the backward group (default to 2) |
| FirstGoodValue | Input | number | Optional | First good value (default lowest value of x) |
| LastGoodValue | Input | number | Optional | Last good value (default highest value of x) |
| Alpha | Output | number | The alpha efficiency (default to 1.0) |
Returns the relative efficiency of the forward detector group compared to the backward detector group. If Alpha is larger than 1 more counts has been collected in the forward group.
Note
This algorithm leaves the input workspace unchanged. To group detectors in a workspace use MuonGroupDetectors v1.
Example - Calculating Alpha:
y = [1,1,1,1,1] + [2,2,2,2,2]
x = [1,2,3,4,5,6] * 2
input = CreateWorkspace(x,y, NSpec=2)
alpha = AlphaCalc(input)
print 'Alpha value: {0:.3f}'.format(alpha)
Output:
Alpha value: 0.500
Example - Calculating Alpha, reversing forward and backward spectra:
y = [1,1,1,1,1] + [2,2,2,2,2]
x = [1,2,3,4,5,6] * 2
input = CreateWorkspace(x,y, NSpec=2)
alpha = AlphaCalc(input,
ForwardSpectra=[2],
BackwardSpectra=[1])
print 'Alpha value: {0:.3f}'.format(alpha)
Output:
Alpha value: 2.000
Categories: Algorithms | Muon