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PeakFinder

Namespace: RTPROCESSINGLIB  ·  Library: DSP Library

Module

This page documents a header-level module — a collection of free functions that share an algorithmic topic. There is no enclosing C++ class; the functions live directly in the library namespace.

Python equivalent

mne.preprocessing.peak_finder in MNE-Python.

#include <dsp/peak_finder.h>

SPDX-License-Identifier: BSD-3-Clause Copyright (c) 2026 MNE-CPP Authors.

A peak is defined as a sample that is strictly larger than its two direct neighbours. The basic detector locates every such sample in linear time; three classical post-filters then prune the candidate list: a minimum height (absolute amplitude floor),

a minimum inter-peak distance in samples (suppressing close-by peaks by retaining only the tallest within the exclusion window), and

a minimum topographic prominence — the height by which a peak rises above the higher of the two adjacent valleys, computed in the same way as scipy.signal.peak_prominences.

The API mirrors scipy.signal.find_peaks closely so MEG/EEG analysis pipelines that already rely on SciPy semantics (cHPI peak picking, ECG R-wave detection, event onset extraction) port to mne-cpp without behavioural drift.

Functions​

peakFinder(data, params)​

QList< QPair< int, double > > peakFinder(const Eigen::VectorXd & data, const PeakFinderParams & params);

Find peaks in a 1D signal.

A peak is a sample that is strictly greater than both its neighbours. Additional filtering by height, distance, and prominence can be applied.

Parameters:

  • data : const Eigen::VectorXd & 1D signal (row vector or VectorXd).

  • params : const PeakFinderParams & Peak detection parameters.

Returns:

  • QList< QPair< int, double > > — List of (peak_index, peak_value) pairs, sorted by index.

peakProminences(data, peakIndices)​

Eigen::VectorXd peakProminences(const Eigen::VectorXd & data, const QList< int > & peakIndices);

Compute prominence of each peak.

Prominence is the vertical distance from a peak to the highest valley on either side before reaching a higher peak.

Parameters:

  • data : const Eigen::VectorXd & 1D signal.

  • peakIndices : const QList< int > & Indices of detected peaks.

Returns:

  • Eigen::VectorXd — Prominence value for each peak.

Authors of this file​