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Our group's Github page is [here](https://github.com/DynamicsAndNeuralSystems).
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You can find software packages for the tools we develop, and investigate code for reproducing results in our published papers.
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### CompEngine
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We have developed an interactive website, [_CompEngine_](http://www.comp-engine.org), that allows you to upload and explore connections between your time-series data and a library of thousands of diverse empirical and synthetic time series.
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### Open software
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<ahref="http://www.comp-engine.org"class="btn btn-lg btn-default"role="button">Have a play!</a>
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We have also developed a range of software packages related to time-series analysis (with more on the way!)
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### Open software
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Details of open time-series analysis software developed in our group is detailed on a dedicated [website](https://time-series-features.gitbook.io/time-series-analysis-tools/).
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We have also developed a range of software packages related to time-series analysis (with more on the way!):
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Below are a few key packages:
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-[_hctsa_ (Matlab)](https://github.com/benfulcher/hctsa), allows you to apply thousands of time-series analysis methods to a time-series dataset in Matlab.
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-[_hctsa_ (Matlab)](https://github.com/benfulcher/hctsa), allows you to extract thousands of time-series analysis features from a collection of time series.
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-[_pyhctsa_ (python)](https://github.com/DynamicsAndNeuralSystems/pyhctsa) is a reimplementation of the _hctsa_ feature library in python, with a subset of the features implemented so far.
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-[_catch22_ (C, Matlab, python, R, Julia)](https://github.com/DynamicsAndNeuralSystems/catch22) allows you to evaluate 22 time-series features, coded efficiently in C and wrapped for python and with native versions for [R](https://github.com/hendersontrent/Rcatch22) and [Julia](https://github.com/brendanjohnharris/Catch22.jl).
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-[_pyspi_ (python)](https://github.com/olivercliff/pyspi) is a comprehensive library for computing pairwise interactions from multivariate time series.
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-[_theft_ (R)](https://github.com/hendersontrent/theft) implements the extraction, analysis, and visualisation of a range of open time-series features.
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### Advice
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We keep an active website containing general research advice across a range of topics [here](https://benfulcher.github.io/ResearchResources/).
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<!-- ### CompEngine
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We have developed an interactive website, [_CompEngine_](http://www.comp-engine.org), that allows you to upload and explore connections between your time-series data and a library of thousands of diverse empirical and synthetic time series.
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<a href="http://www.comp-engine.org" class="btn btn-lg btn-default" role="button">Have a play!</a>
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