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PeakFinderParams

Namespace: RTPROCESSINGLIB  ·  Library: DSP Library

#include <dsp/peak_finder.h>

struct UTILSLIB::PeakFinderParams

Parameters for peak detection.

src/examples/ex_dsp_analysis/main.cpp
PeakFinderParams params;
params.dMinHeight = 0.5; // like scipy.signal.find_peaks(height=0.5, distance=30)
params.iMinDistance = 30;
const QList<QPair<int, double>> peaks = peakFinder(wave, params); // (sample, value), sorted by sample
const VectorXd prominence = peakProminences(wave, {2, 9, 15});

Example​

Used in examples​

ex_dsp_analysis​

DSP library: Welch PSD, FIR filtering, peak finding, envelope correlation, SPHARA and simulation.

src/examples/ex_dsp_analysis/main.cpp, line 138
PeakFinderParams params;
params.dMinHeight = 0.5; // like scipy.signal.find_peaks(height=0.5, distance=30)
params.iMinDistance = 30;
const QList<QPair<int, double>> peaks = peakFinder(wave, params); // (sample, value), sorted by sample
const VectorXd prominence = peakProminences(wave, {2, 9, 15});
PeakFinderParams byProminence;
byProminence.dProminence = 0.5;
PeakFinderParams byDistance;
byDistance.iMinDistance = 10;
ok &= expect(indices(peaks) == QList<int>({9, 51, 92, 128, 170}) && indices(peakFinder(wave, byProminence)) == QList<int>({9, 51, 92, 128, 170}) && indices(peakFinder(wave, byDistance)) == QList<int>({9, 22, 37, 51, 64, 79, 92, 114, 128, 141, 156, 170, 183, 198}) && (prominence - Vector3d(0.18086696, 1.298166714, 0.289199146)).cwiseAbs().maxCoeff() < 1e-8,
             "peakFinder (height, distance, prominence) and peakProminences match scipy");

ex_dsp_spectral​

Spectral and filtering tools of the dsp library on signals with known content.

src/examples/ex_dsp_spectral/main.cpp, line 207
VectorXd trace(10);
trace << 0, 1, 0, 3, 0, 2, 0, 5, 1, 0;
const QList<QPair<int, double>> allPeaks = peakFinder(trace);
PeakFinderParams params;
params.dProminence = 2.5;
const QList<QPair<int, double>> strongPeaks = peakFinder(trace, params);
const VectorXd prominences = peakProminences(trace, {1, 3, 5, 7});
// scipy.signal.find_peaks / peak_prominences
ok &= expect(allPeaks.size() == 4 && allPeaks[3].first == 7 && strongPeaks.size() == 2 && strongPeaks[0].first == 3 && maxError(prominences, {1.0, 3.0, 2.0, 5.0}) == 0.0,
             "peaks [1, 3, 5, 7], prominences [1, 3, 2, 5], prominence >= 2.5 keeps [3, 7] (scipy)");

Authors of this file​