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SmoothData v1¶

SmoothData dialog.

Table of Contents

Summary
- See Also
Properties
Description
Usage
- Example 1: use same NPoints for all spectra
- Example 2: use different NPoints for groups of spectra
Source

Summary ¶

Smooths out statistical fluctuations in a workspace’s data.

Properties ¶

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Name of the input workspace
OutputWorkspace	Output	MatrixWorkspace	Mandatory	The name of the workspace to be created as the output of the algorithm
NPoints	Input	int list	3	The number of points to average over (minimum 3). If an even number is given, it will be incremented by 1 to make it odd (default value 3)
GroupingWorkspace	Input	GroupingWorkspace		Optional: GroupingWorkspace to use for vector of NPoints.

Smooths out statistical jitter in a workspace’s data by making each point the mean average of itself and one or more points lying symmetrically either side of it. The statistical error on each point will be reduced by sqrt(npts) because more data is now contributing to it. For points at the end of each spectrum, a reduced number of smoothing points will be used. For example, if NPoints is 5 the first value in the spectrum will be smoothed by making it the average of the first 3 values, the next will use the first 4 and then the third and onwards will use the full 5 points in the averaging.

Usage ¶

Example 1: use same NPoints for all spectra ¶

# Create a workspace
ws = CreateSampleWorkspace()

# Smooth the spectra in ws NPoints = 3
smooth = SmoothData( ws, 3)

Example 2: use different NPoints for groups of spectra ¶

# Create a workspace
ws = CreateSampleWorkspace()
# Create a grouping workspace to put detectors from banks
# bank1 and bank2 into two separate groups
gr = CreateGroupingWorkspace(ws,GroupNames='bank1,bank2')

# Smooth the spectra in ws: first group with NPoints = 3 and
# second group with NPoints = 5
smooth = SmoothData( ws, [3,5], GroupingWorkspace='gr')