ruptures is a Python library for off-line change point detection.
This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models.
ruptures focuses on ease of use by providing a well-documented and consistent interface.
In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package.
How to cite
If you use
ruptures in a scientific publication, we would appreciate citations to the following paper:
- C. Truong, L. Oudre, N. Vayatis. Selective review of offline change point detection methods. Signal Processing, 167:107299, 2020. [journal] [pdf]
Dependencies and install
Installation instructions can be found here.
(Please refer to the documentation for more advanced use.)
The following snippet creates a noisy piecewise constant signal, performs a penalized kernel change point detection and displays the results (alternating colors mark true regimes and dashed lines mark estimated change points).
import matplotlib.pyplot as plt import ruptures as rpt # generate signal n_samples, dim, sigma = 1000, 3, 4 n_bkps = 4 # number of breakpoints signal, bkps = rpt.pw_constant(n_samples, dim, n_bkps, noise_std=sigma) # detection algo = rpt.Pelt(model="rbf").fit(signal) result = algo.predict(pen=10) # display rpt.display(signal, bkps, result) plt.show()
See the changelog for a history of notable changes to
Thanks to all our contributors
This project is under BSD license.
BSD 2-Clause License Copyright (c) 2017, ENS Paris-Saclay, CNRS All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.