#Time-series Topology (TS-TOP) Release Date: June 2016

This project contains the source code and datasets for the time-series topology data analysis tool suite for time-series characterization and classification as described in the paper :

Seversky, Lee M., Shelby Davis, and Matthew Berger. "On Time-Series Topological Data Analysis: New Data and Opportunities." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2016.

If you use the software or associated data please use the following citation:

@InProceedings{Seversky_2016_CVPR_Workshops,
author = {Seversky, Lee M. and Davis, Shelby and Berger, Matthew},
title = {On Time-Series Topological Data Analysis: New Data and Opportunities},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2016}
}

From Arnur Nigmetov (Graz Unvirsity of Technology, Graz, Austria)

Download and Extract [Hera] (https://bitbucket.org/grey_narn/hera/downloads)

Move geom_bottleneck to tstop/ext/geom_dist/bottleneck

Move geom_matching to tstop/ext/geom_dist/wasserstein

From David M. Mount and Sunil Arya (University of Maryland, College Park, Maryland)

Download ANN and extract to tstop/ext/ANN

Install boost python and serialization libraries, scikit-learn, matplotlib, Eigen 3, cmake, and optionally wxPython On machines with apt-get:

$ sudo apt-get install libboost-python-dev libboost-serialization-dev python-matplotlib python-sklearn python-wxgtk3.0-dev libeigen3-dev cmake

Run in tstop

$ cmake -DCMAKE_BUILD_TYPE=release .
$ make 

Add tstop/python to the PYTHONPATH environment variable

For detailed documentation please see: [Documentation] (python/persistence/README.md)

For a short tutorial please see: [Time-series Topology Tutorial] (python/persistence/tutorial.md)

Time-series datasets and precomputed topological features: [Download] (https://drive.google.com/open?id=0B-eHoAvCU5B5M3dMS3VQWU5IRzA)