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FindPeaksConvolve v1

Summary

Finds peaks in a dataset through the use of a convolution vector

Properties

Name

Direction

Type

Default

Description

InputWorkspace

Input

MatrixWorkspace

Mandatory

An input workspace.

OutputWorkspace

Output

WorkspaceGroup

Mandatory

An output workspace.

CreateIntermediateWorkspaces

Input

boolean

False

Output workspaces showing intermediate working steps

StartWorkspaceIndex

Input

number

Optional

EndWorkspaceIndex

Input

number

Optional

EstimatedPeakExtent

Input

number

Optional

Estimated PeakExtent of the peaks to be found

EstimatedPeakExtentNBins

Input

number

Optional

Optional: Estimated PeakExtent of the peaks to be found in number of bins

IOverSigmaThreshold

Input

number

3

Minimum Signal/Noise ratio for a peak to be considered significant

MergeNearbyPeaks

Input

boolean

True

Attempt to remove inflections in the data, where a local minima/maxima occurs which is not signficiant enough to be considered a peak

FindHighestDataPointInPeak

Input

boolean

False

When searching for peaks in the raw data around the iOverSigma maxima, take the highest value, rather than favouring datapoints closer to the maxima

Description

Finds peak centres using convolution with a shoebox kernel to approximate the second derivative, taking maxima above an I/Sigma threshold. Algorithm designed by Richard Waite and implemented by Mial Lewis.

Usage

Output:

Categories: AlgorithmIndex | Optimization\PeakFinding

Source

C++ header: FindPeaksConvolve.h

C++ source: FindPeaksConvolve.cpp