DMelt:DataAnalysis/9 Peak Finders

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Peak finders

DataMelt has several Java algorithms for identifications of peaks in data. Let us consider a peak identification algorithms in arrays of data. It is important for peak identification in time series, mass spectra and other areas.

Given a spectrum and search parameters, performs a digital filter peak search as specified in V. Hnatowicz et al in Comp Phys Comm 60 (1990) 111-125. Setting the sensitivity to a typical value of 3 gives a 3% chance for any peak found to be false.Maximum separation in sigma between peaks is 1.3.


You can also find peak finder based on the algorithms described in the paper "A non-parametric peak finder algorithm and its application in searches for new physics" by S.Chekanov, M.Erickson, arxiv.org:1110.3772 "Advances in High Energy Physics", vol. 2013, Article ID 162986. This peak identification algorithm is implemented in Python:

Run this code and you will see an image with identified peaks. It also calculate significance and the width. The output of this algorithm is shown in this image:

DMelt example: A peak finding algorithm in X-Y data.

The identified peaks are shown in blue color.

More information on this topic is in DMelt books