Smart Arrays Peaks

What the package can do for you

This package provides functions that detect peaks (maximum values) in one- or two-dimensional arrays. Peak detection (peak search, peak picking) does not simply mean finding maximum values. Data originating from measurements are often subject to noise, i.e. random small variations of the measured values. The provided algorithms therefore allow you to specify a noise value to suppress to exclude noise effects from peak search.

The major API functionalities

  • class PeakPicker1D

This example will pick the positive and negative peaks in the entire array using the noise discriminator 2.0. The result contains the array indices of the found peaks.

List<int> peakIndices = PeakPicker1D.detectPeaks( array, 0, array.length, 2.0, 0.0, PeakPicker1D.PICK_POSNEG, 0);

  • class PeakPicker2D:

This example will pick the negative peaks in the entire array2D using the noise discriminator 2.0. The result contains the array indices (row/column pairs) of the found peaks.

List<List<int>> peakIndices = PeakPicker2D.detectPeaks( array2D, 0, array2D.length,0,array2D[0].lebngth, 2.0, 0.00, PeakPicker1D.PICK_NEG, 0);

Detailed API

Please view the detailed API documentation in the API reference of this package (sidebar at the right of this page).

smart_arrays_base: Basic functions for 1D and 2D arrays

smart_arrays_numerics: Numerics with 1D and 2D arrays

smart_arrays_compress: Compress 1D and 2D arrays to a smaller size.

smart_arrays_lmfit: Fits (x, y) data given as arrays to a specified model function using the Levenberg-Marquardt algorithm.

smart_lorentz-gauss: Compute Lorentz-Gauss (pseudo-Voigt) line shapes.

smart_signal_processing: Fourier transform and more.

smart_dialogs: Easy-to-use dialogs in Web applications

Libraries

smart_arrays_peaks