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Mean v1

../_images/Mean-v1_dlg.png

Mean dialog.

Summary

Calculates the arithemetic mean of the workspaces provided.

See Also

MostLikelyMean, WeightedMean, WeightedMeanOfWorkspace

Properties

Name

Direction

Type

Default

Description

Workspaces

Input

string

Mandatory

Input workspaces. Comma separated workspace names

OutputWorkspace

Output

MatrixWorkspace

Mandatory

Output mean workspace

Description

Calculates the arithmetic mean of the y values of the workspaces provided. If each input workspace is labelled \(w_i\) and there are N workspaces then the mean is computed as:

\[m = \frac{1}{N} \sum_{i=0}^{N-1} w_i\]

where m is the output workspace. The x values are copied from the first input workspace.

Restrictions

All input workspaces must have the same shape and the x axis must be in the same order.

Usage:

Example: Simple mean of two workspaces

# Create two  2-spectrum workspaces with Y values 1->8 & 3->10
dataX = [0,1,2,3,4,
         0,1,2,3,4]
dataY = [1,2,3,4,
         5,6,7,8]
ws_1 = CreateWorkspace(dataX, dataY, NSpec=2)
dataY = [3,4,5,6,
         7,8,9,10]
ws_2 = CreateWorkspace(dataX, dataY, NSpec=2)

result = Mean("ws_1, ws_2") # note the comma-separate strings
print("Mean of y values in first spectrum: {}".format(result.readY(0)))
print("Mean of y values in second spectrum: {}".format(result.readY(1)))

Output:

Mean of y values in first spectrum: [ 2.  3.  4.  5.]
Mean of y values in second spectrum: [ 6.  7.  8.  9.]

Categories: AlgorithmIndex | Arithmetic

Source

Python: Mean.py