MatrixProfile

MatrixProfile is a Python 3 library, brought to you by the Matrix Profile Foundation, for mining time series data. The Matrix Profile is a novel data structure with corresponding algorithms (stomp, regimes, motifs, etc.) developed by the Keogh and Mueen research groups at UC-Riverside and the University of New Mexico. The goal of this library is to make these algorithms accessible to both the novice and expert through standardization of core concepts, a simplistic API, and sensible default parameter values.

In addition to this Python library, the Matrix Profile Foundation, provides implementations in other languages. These languages have a pretty consistent API allowing you to easily switch between them without a huge learning curve.

• tsmp - an R implementation

• go-matrixprofile - a Golang implementation

Python Support

Currently, we support the following versions of Python:

• 3.5

• 3.6

• 3.7

• 3.8

• 3.9

Python 2 is no longer supported. There are earlier versions of this library that support Python 2.

Installation

The easiest way to install this library is using pip. If you would like to install it from source, please review the installation documentation for your platform.

pip install matrixprofile

Getting Started

This article provides introductory material on the Matrix Profile: Introduction to Matrix Profiles

This article provides details about core concepts introduced in this library: How To Painlessly Analyze Your Time Series

Our documentation provides a quick start guide, examples and api documentation. It is the source of truth for getting up and running.

Algorithms

For details about the algorithms implemented, including performance characteristics, please refer to the documentation.

@article{Van Benschoten2020,
    doi = {10.21105/joss.02179},
    url = {https://doi.org/10.21105/joss.02179},
    year = {2020},
    publisher = {The Open Journal},
    volume = {5},
    number = {49},
    pages = {2179},
    author = {Andrew Van Benschoten and Austin Ouyang and Francisco Bischoff and Tyler Marrs},
    title = {MPA: a novel cross-language API for time series analysis},
    journal = {Journal of Open Source Software}
}