Metadata-Version: 2.1
Name: matrixprofile-ts
Version: 0.0.2
Summary: An Open Source Python Time Series Library For Motif Discovery using Matrix Profile
Home-page: https://github.com/target/matrixprofile-ts
Author: Andrew Van Benschoten
Author-email: andrew.vanbenschoten@target.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: numpy

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# matrixprofile-ts

## What is it?
matrixprofile-ts is a Python 3 library for evaluating time series data using the matrix profile algorithms developed by the Keough and Mueen research groups at the University of California-Riverside and the University of New Mexico. Current algorithms implemented include MASS, STMP, STAMP and STAMPI.

## Getting Started with Matrix Profile

### Installation
matrixprofile-ts is available on pip:

`pip install matrixprofile-ts`


### Tutorial
The GitHub repo includes a Jupyter Notebook tutorial containing basic examples of using matrix profile (see the docs folder). This notebook also renders automatically on the GitHub website.



### Matrix Profile Citations
Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, Eamonn Keogh (2016). Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View that Includes Motifs, Discords and Shapelets. IEEE ICDM 2016. (http://www.cs.ucr.edu/~eamonn/MatrixProfile.html)


