FindPeaks
From MantidProject
Contents |
Summary
Searches for peaks in a dataset.
Properties
| Order | Name | Direction | Type | Default | Description |
|---|---|---|---|---|---|
| 1 | InputWorkspace | Input | Workspace | Mandatory | The name of the workspace to search. |
| 2 | FWHM | Input | integer | 7 | The number of points covered, on average, by the fwhm of a peak. |
| 3 | Tolerance | Input | integer | 4 | A measure of the strictness desired in meeting the condition on peak candidates. Mariscotti recommends 2. |
| 4 | PeaksList | Output | TableWorkspace | Mandatory | The name of the TableWorkspace in which to store the list of peaks found. |
| 5 | WorkspaceIndex | Input | integer | Optional | If set, will only find peaks in the given spectrum of the workspace. Otherwise, all spectra will be searched. |
Description
This algorithm searches all the spectra in a workspace for peaks, returning a list of the found and successfully fitted peaks. The search algorithm is described in full in reference [1]. In summary: the second difference of each spectrum is computed and smoothed. This smoothed data is then searched for patterns consistent with the presence of a peak. The list of candidate peaks found is passed to a fitting routine and those that are successfully fitted are kept and returned in the output workspace (and logged at information level).
The output TableWorkspace contains the following columns, which reflect the fact that the peak has been fitted to a Gaussian atop a linear background: spectrum, centre, width, height, backgroundintercept & backgroundslope.
Subalgorithms used
FindPeaks uses the SmoothData algorithm to, well, smooth the data - a necessary step to identify peaks in statistically fluctuating data. The Gaussian algorithm is used to fit candidate peaks.
References
- M.A.Mariscotti, A method for automatic identification of peaks in the presence of background and its application to spectrum analysis, NIM 50 (1967) 309.
Source Code
Header FindPeaks.h
Source FindPeaks.cpp
