Metadata-Version: 1.1
Name: tensorly
Version: 0.1.3
Summary: Tensor learning in Python.
Home-page: https://github.com/tensorly/tensorly
Author: Jean Kossaifi
Author-email: jean.kossaifi@gmail.com
License: Modified BSD
Download-URL: https://github.com/tensorly/tensorly/tarball/0.1.3
Description: .. image:: https://badge.fury.io/py/tensorly.svg
            :target: https://badge.fury.io/py/tensorly
        
        .. image:: https://travis-ci.org/tensorly/tensorly.svg?branch=master
            :target: https://travis-ci.org/tensorly/tensorly
        
        TensorLy
        ========
        
        TensorLy is a fast and simple Python library for tensor learning. It builds on top of NumPy and SciPy and and allows for fast and straightforward tensor decomposition, tensor learning and tensor algebra.
        
        - **Website:** http://tensorly.github.io
        - **Source:**  https://github.com/tensorly/tensorly
        
        
        How to install
        --------------
         
        Easy option: install with pip
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Simply run::
        
           pip install -U tensorly
        
        That's it!
        
        Alternatively, you can pip install from the git repository::
        
           pip install git+https://github.com/tensorly/tensorly
        
        Development: install from git
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        The library is still very new and under heavy developement. To install the last version:
        
        Clone the repository and cd there::
        
           git clone https://github.com/tensorly/tensorly
           cd tensorly
        
        Then install the package (here in editable mode with `-e` or equivalently `--editable`)::
        
           pip install -e .
        
        Running the tests
        ~~~~~~~~~~~~~~~~~
        
        Testing and documentation are an essential part of this package and all functions come with uni-tests and documentation.
        
        You can run all the tests using the `nose` package::
        
           nosetests -v tensorly
        
        
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
