Peak picking

Finds peaks or troughs in a vector or 2-D matrix.

pickpeaks

Pick peaks.

Summary

pickpeaks is similar to MATLAB's findpeaks in that it returns local peaks and their indices for the input X, but has some advantages

• It is faster (much faster for large vectors),
• It allows X to be a 2D matrix (not just a vector) and the user can specify across which dimension to look for peaks.
• It gives the option to either pick peaks or troughs.

Call

The call is

    [Vo, Io] = pickpeaks(X, npts, dim, mode);

Examples of usage are:

    [Vo,Io] = pickpeaks(X);
    [Vo,Io] = pickpeaks(X, [], [], 'troughs');
    [Vo,Io] = pickpeaks(X, 10, [], 'troughs'); % require at least 10 samples distance between troughs.
    [Vo,Io] = pickpeaks(X, [], 2);             % search for peaks across rows

Comparison with findpeaks

pickpeaks

• does not provide the findpeaks option 'Threshold'.
• does not provide the findpeaks’ options: 'MinPeakHeight', 'NPeaks', 'SortStr'.

The effect of these options ('MinPeakHeight', 'NPeaks', 'SortStr') can be achieved easily by manipulating the output. E.g. if Vo, Io are the output of pickpeaks, the following will yield the same result as setting 'MinPeakHeight' to 0.5:

    i = find(Vo < 0.5);
    Vo(i) = []; 
    Io(i) = [];

The screenshot was generated by

x = randn(200,1);
tic, [val,ind] = pickpeaks(x,10); toc
tic, [pks,loc] = findpeaks(x,'minpeakdistance',10); toc
figure
    plot(x); hold all;
    plot(ind, val, 'ro', loc, pks, 'k+', 'MarkerSize', 10);
    legend('x', 'pickpeaks', 'findpeaks');

Notice another difference between findpeaks and pickpeaks: findpeaks does not qualify some peaks (e.g. 3 peaks around sample 50) because there are other peaks in their vicinity, which did not qualify either. pickpeaks will pick those as well.