Implementation of AMPD algorithm for peak detection in quasi-periodic signals
Project description
README.md rev. 10 Feb 2023 by Luca Cerina. Copyright (c) 2023 Luca Cerina. Distributed under the Apache 2.0 License in the accompanying file LICENSE.
Automatic Multiscale-based Peak Detection (AMPD)
ampdLib implements automatic multiscale-based peak detection (AMPD) algorithm as in An Efficient Algorithm for Automatic Peak Detection in Noisy Periodic and Quasi-Periodic Signals, by Felix Scholkmann, Jens Boss and Martin Wolf, Algorithms 2012, 5, 588-603.
Python required dependencies
- Python >= 3.6
- Numpy
- Scipy for tests
Installation
The library can be easily installed with setuptools support using pip install . or via PyPI with pip install ampdlib
Usage
A simple example is:
peaks = ampdlib.ampd(input)
AMPD may require a lot of memory (N*(lsm_limit*N/2) bytes for a given length N and default lsm_limit). A solution is to divide the signal in windows with ampd_fast or ampd_fast_sub or determine a better lsm_limit for the minimum distance between peaks required by the use case with get_optimal_size.
Tests
The tests folder contains an ECG signal with annotated peaks in matlab format.
Contribution
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