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# EstimateMuonAsymmetryFromCounts v1¶

## Summary¶

This algorithm gives an estimate for the asymmetry.

## Properties¶

Name

Direction

Type

Default

Description

InputWorkspace

Input

MatrixWorkspace

Mandatory

The name of the input 2D workspace.

WorkspaceName

Input

string

The name used in the normalization table. If this is blank the InputWorkspace’s name will be used.

OutputWorkspace

Output

MatrixWorkspace

Mandatory

The name of the output 2D workspace.

OutputUnNormData

Input

boolean

False

If to output the data with just the exponential decay removed.

OutputUnNormWorkspace

Output

MatrixWorkspace

unNormalisedData

The name of the output unnormalized workspace.

Spectra

Input

int list

The workspace indices to remove the exponential decay from.

StartX

Input

number

0.1

The lower limit for calculating the asymmetry (an X value).

EndX

Input

number

15

The upper limit for calculating the asymmetry (an X value).

NormalizationIn

Input

number

0

If this value is non-zero then this is used for the normalization, instead of being estimated.

NormalizationTable

InOut

TableWorkspace

Name of the table containing the normalizations for the asymmetries.

If the NormalizationIn property is greater than zero, the algorithm will apply the user defined normalization to the data instead of calculating an estimate.

## Description¶

This algorithm estimates the asymmetry from the specified muon spectra. By default, all of the spectra in a workspace will be corrected.

The formula for estimating the asymmetry is given by:

$\textrm{NewData} = (\textrm{OldData}\times e^\frac{t}{\tau})/(F N_0) - 1.0,$

where $$\tau$$ is the muon lifetime (2.1969811e-6 seconds), $$F$$ is the number of good frames and $$N_0$$ is a fitted normalization constant. The normalization is given by

$N_0= \frac{\Delta t\sum_j(\textrm{OldData}_j)}{\tau F \left( \exp(-\frac{t_0}{\tau})-\exp(-\frac{t_N}{\tau})\right) },$

where the summation only includes the data with times bewtween $$t_0$$ and $$t_N$$ and $$\Delta t$$ is the time step.

## Usage¶

Example - Removing exponential decay:

import math
import numpy as np

tab = CreateEmptyTableWorkspace()

y = [100, 150, 50, 10, 5]
x = [1,2,3,4,5,6]
input = CreateWorkspace(x,y)
run = input.getRun()
output,unnorm=EstimateMuonAsymmetryFromCounts(InputWorkspace=input,spectra=0,NormalizationTable=tab,StartX=1,EndX=5,OutputUnNormData=True)
print("Asymmetry   :  {}".format(['{0:.2f}'.format(value) for value in output.readY(0)]))
print("Unnormalized:  {}".format(['{0:.2f}'.format(value) for value in unnorm.readY(0)]))
print("Normalization constant: {0:.2f}".format(tab.column(0)[0]))


Output:

Asymmetry   :  ['-0.31', '0.64', '-0.14', '-0.73', '-0.79']
Unnormalized:  ['19.79', '46.80', '24.59', '7.75', '6.11']
Normalization constant: 28.56


Example - Setting the normalization:

import math
import numpy as np

tab = CreateEmptyTableWorkspace()

y = [100, 150, 50, 10, 5]
x = [1,2,3,4,5,6]
input = CreateWorkspace(x,y)
run = input.getRun()

output=EstimateMuonAsymmetryFromCounts(InputWorkspace=input,spectra=0,NormalizationTable=tab,StartX=1,EndX=5,NormalizationIn=20.0)

print("Asymmetry:  {}".format(['{0:.2f}'.format(value) for value in output.readY(0)]))
print("Normalization constant: {0:.2f}".format(tab.column(0)[0]))


Output:

Asymmetry:  ['-0.01', '1.34', '0.23', '-0.61', '-0.69']
Normalization constant: 20.00


Categories: AlgorithmIndex | Muon