Counting 3,146 Big Data & Machine Learning Frameworks, Toolsets, and Examples...
Suggestion? Feedback? Tweet @stkim1

Author
Contributors
Last Commit
Sep. 18, 2018
Created
Mar. 29, 2018

HOTTBOX: Higher Order Tensors ToolBOX

Travis Appveyor Coveralls PyPi

Welcome to the toolbox for tensor decompositions, statistical analysis, visualisation, feature extraction, regression and non-linear classification of multi-dimensional data.

Installing HOTTBOX

There are two options available:

  1. Install hottbox as it is from pypi.org by executing:

    $ pip install hottbox
    
  2. Alternatively, you can clone the source code which you can find on our GitHub repository and install hottbox in editable mode:

    $ git clone https://github.com/hottbox/hottbox.git
    
    $ cd hottbox
    
    $ pip install -e .
    

    This will allow you to modify the source code in the way it will suit your needs. Additionally, you will be on top of the latest changes and will be able to start using new stable features which are located on develop branch until the official release. The list of provisional changes for the next release (and the CI status) can be also be found on develop branch in CHANGELOG file.

Running tests

hottbox is under active development, therefore, if you have chosen the second installation option, it is advisable to run tests in order to make sure that your current version of hottbox is stable. First, you will need to install pytest and pytest-cov packages:

$ pip install pytest pytest-cov

To run test, simply execute inside the main directory:

$ pytest -v --cov hottbox

HOTTBOX tutorials

Please check out our repository with tutorials on hottbox api and theoretical background on multi-linear algebra and tensor decompositions.

Development

We welcome new contributors of all experience levels. Detailed guidelines can be found on our web site.