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Version bump
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marinkaz committed Jun 25, 2016
1 parent 39d44a8 commit 8e11177
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6 changes: 3 additions & 3 deletions docs/source/conf.py
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# General information about the project.
project = 'Nimfa'
copyright = '2016, Marinka Zitnik'
copyright = '2016, The Nimfa developers'

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
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# The short X.Y version.
version = '1.3'
# The full version, including alpha/beta/rc tags.
release = '1.3.0'
release = '1.3.1'

# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
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# (source start file, target name, title, author, documentclass [howto/manual]).
latex_documents = [
('index', 'nimfa-APythonLibraryforNonnegativeMatrixFactorization.tex', 'nimfa - A Python Library for Nonnegative Matrix Factorization',
'Marinka Zitnik', 'manual'),
'The Nimfa developers', 'manual'),
]

# The name of an image file (relative to this directory) to place at the top of
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4 changes: 4 additions & 0 deletions docs/source/index.rst
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Expand Up @@ -5,6 +5,10 @@ Welcome to Nimfa
`Nimfa`_ is a Python library for nonnegative matrix factorization. It includes implementations of several factorization methods, initialization approaches, and quality scoring.
Both dense and sparse matrix representation are supported.

Nimfa is distributed under the BSD license.

****

The sample script using Nimfa on medulloblastoma gene expression data is given below. It uses alternating least squares nonnegative matrix
factorization with projected gradient method for subproblems [Lin2007]_ and Random Vcol [Albright2006]_ initialization algorithm. An object returned by ``nimfa.mf_run`` is
fitted factorization model through which user can access matrix factors and estimate quality measures.
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2 changes: 1 addition & 1 deletion nimfa/__init__.py
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"""

__license__ = 'BSD'
__version__ = '1.3.0'
__version__ = '1.3.1'
__maintainer__ = 'Marinka Zitnik'
__email__ = '[email protected]'

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2 changes: 1 addition & 1 deletion setup.py
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KEYWORDS = ['matrix factorization', 'nonnegative matrix factorization',
'bioinformatics', 'data mining', 'machine learning']
LICENSE = 'BSD'
VERSION = '1.3.0'
VERSION = '1.3.1'
ISRELEASED = True

INSTALL_REQUIRES = (
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