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scikit-tensor

version 0.1

Python module for multilinear algebra and tensor factorizations

Download: http://github.com/mnick/scikit-tensor
Homepage: http://github.com/mnick/scikit-tensor
PyPI: http://pypi.python.org/pypi/scikit-tensor
People: ('Maximilian Nickel',)

Description

scikit-tensor
=============

scikit-tensor is a Python module for multilinear algebra and tensor
factorizations.

Dependencies
------------

The required dependencies to build the software are ``Numpy >= 1.3``,
``SciPy >= 0.7``.

Usage
-----

Example script to decompose sensory bread data (available from
http://www.models.life.ku.dk/datasets) using CP-ALS

.. code:: python

import logging
from scipy.io.matlab import loadmat
from sktensor import dtensor, cp_als

# Set logging to DEBUG to see CP-ALS information
logging.basicConfig(level=logging.DEBUG)

# Load Matlab data and convert it to dense tensor format
mat = loadmat('../data/sensory-bread/brod.mat')
T = dtensor(mat['X'])

# Decompose tensor using CP-ALS
P, fit, itr, exectimes = cp_als(T, 3, init='random')

References
----------

If you use ``scikit-tensor`` in your research, please cite

::

Maximilian Nickel. scikit-tensor Library (Version 0.1). Available Online, November 2013.

Install
-------

This package uses distutils, which is the default way of installing
python modules. To install in your home directory, use

::

python setup.py install --user

To install for all users on Unix/Linux

::

python setup.py build
sudo python setup.py install

To install in development mode

::

python setup.py develop

Contributing & Development
--------------------------

scikit-tensor is still an extremely young project, and I'm happy for any
contributions (patches, code, bugfixes, *documentation*, whatever) to
get it to a stable and useful point. Feel free to get in touch with me
via email (mnick at AT mit DOT edu) or directly via github.

Development is synchronized via git. To clone this repository, run

::

git clone git://github.com/scikit-learn/scikit-learn.git

Authors
-------

Maximilian Nickel

- http://twitter.com/mnick
- http://github.com/mnick

License
-------

scikit-tensor is licensed under the GPLv3
http://www.gnu.org/licenses/gpl-3.0.txt

Installation

PyPI

You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikit-tensor

Using pip

You can install scikit-tensor for yourself from the terminal by running:

pip install --user scikit-tensor

If you want to install it for all users on your machine, do:

pip install scikit-tensor
On Linux, do sudo pip install scikit-tensor.

If you don't yet have the pip tool, you can get it following these instructions.

This package was discovered in PyPI.