Skip to main content

A Python module for nonnegative matrix factorization

Project description

Nimfa

https://travis-ci.org/marinkaz/nimfa.svg?branch=master https://coveralls.io/repos/github/marinkaz/nimfa/badge.svg?branch=master

Nimfa is a Python module that implements many algorithms for nonnegative matrix factorization. Nimfa is distributed under the BSD license.

The project was started in 2011 by Marinka Zitnik as a Google Summer of Code project, and since then many volunteers have contributed. See AUTHORS file for a complete list of contributors.

It is currently maintained by a team of volunteers.

Dependencies

Nimfa is tested to work under Python 2.7 and Python 3.4.

The required dependencies to build the software are NumPy >= 1.7.0, SciPy >= 0.12.0.

For running the examples Matplotlib >= 1.1.1 is required.

Install

This package uses setuptools, which is a common 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:

sudo python setup.py install

For more detailed installation instructions, see the web page http://nimfa.biolab.si

Use

Run alternating least squares nonnegative matrix factorization with projected gradients and Random Vcol initialization algorithm on medulloblastoma gene expression data:

>>> import nimfa
>>> V = nimfa.examples.medulloblastoma.read(normalize=True)
>>> lsnmf = nimfa.Lsnmf(V, seed='random_vcol', rank=50, max_iter=100)
>>> lsnmf_fit = lsnmf()
>>> print('Rss: %5.4f' % lsnmf_fit.fit.rss())
Rss: 0.2668
>>> print('Evar: %5.4f' % lsnmf_fit.fit.evar())
Evar: 0.9997
>>> print('K-L divergence: %5.4f' % lsnmf_fit.distance(metric='kl'))
K-L divergence: 38.8744
>>> print('Sparseness, W: %5.4f, H: %5.4f' % lsnmf_fit.fit.sparseness())
Sparseness, W: 0.7297, H: 0.8796

Cite

@article{Zitnik2012,
  title     = {Nimfa: A Python Library for Nonnegative Matrix Factorization},
  author    = {Zitnik, Marinka and Zupan, Blaz},
  journal   = {Journal of Machine Learning Research},
  volume    = {13},
  pages     = {849-853},
  year      = {2012}
}

Project details


Release history Release notifications

This version
History Node

1.3.4

History Node

1.3.3

History Node

1.3.2

History Node

1.3.1

History Node

1.3.0

History Node

1.2.3

History Node

1.2.2

History Node

1.1

History Node

1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
nimfa-1.3.4.tar.gz (5.7 MB) Copy SHA256 hash SHA256 Source None Sep 22, 2017

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging CloudAMQP CloudAMQP RabbitMQ AWS AWS Cloud computing Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page