Metadata-Version: 2.1
Name: opnmf
Version: 0.0.2
Summary: orthogonal projective non-negative matrix factorization
Home-page: https://juaml.github.io/opnmf
Author: Fede Raimondo
Author-email: f.raimondo@fz-juelich.de
License: UNKNOWN
Download-URL: https://github.com/juaml/opnmf
Project-URL: Documentation, https://juaml.github.io/opnmf
Project-URL: Source, https://github.com/juaml/opnmf
Project-URL: Tracker, https://github.com/juaml/opnmfissues/
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.md
License-File: AUTHORS.rst

# opnmf

This package implements orthogonal projective non-negative matrix factorization as described in:

Z. Yang and E. Oja, "Linear and Nonlinear Projective Nonnegative Matrix Factorization," in IEEE Transactions on Neural Networks, vol. 21, no. 5, pp. 734-749, May 2010, doi: 10.1109/TNN.2010.2041361.

## Citing

If you use this software, consider citing:

Sotiras A, Resnick SM, Davatzikos C. Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization. Neuroimage. 2015;108:1-16. doi:10.1016/j.neuroimage.2014.11.045



