Metadata-Version: 1.2
Name: scikit-tensor-py3
Version: 0.4.1
Summary: Python module for multilinear algebra and tensor factorizations
Home-page: http://github.com/evertrol/scikit-tensor-py3
Maintainer: Evert Rol
Maintainer-email: evert.rol@gmail.com
License: GPLv3
Download-URL: http://github.com/evertrol/scikit-tensor-py3
Description: scikit-tensor
        =============
        .. image:: https://travis-ci.org/evertrol/scikit-tensor-py3.svg?branch=master
          :target: https://travis-ci.org/evertrol/scikit-tensor-py3
        
        scikit-tensor is a Python module for multilinear algebra and tensor
        factorizations. Currently, scikit-tensor supports basic tensor operations
        such as folding/unfolding, tensor-matrix and tensor-vector products as
        well as the following tensor factorizations:
        
        * Canonical / Parafac Decomposition
        * Tucker Decomposition
        * RESCAL
        * DEDICOM
        * INDSCAL
        
        Moreover, all operations support dense and tensors.
        
        Note
        ----
        
        This is a Python 3 only compatible maintenance release. It appears the
        development for scikit-tensor has stalled, and the project has been
        abandoned. This fork only supports Python 3.5 and later, and is
        available on PyPI as `scikit-tensor-py3`, for easier installation.
        
        Issues and pull requests are welcomed, but issues relating algorithms
        and requests for additional algorithms may be postponed or ignored
        altogether. Technical (code) issues are welcomed.
        
        Dependencies
        ------------
        
        The required dependencies to build the software are `Numpy` and `SciPy`.
        
        Usage
        -----
        
        Example script to decompose sensory bread data (available from
        http://www.models.life.ku.dk/datasets) using CP-ALS::
        
        
            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')
        
        
        Installation
        ------------
        
        This package uses distutils, which is the default way of installing
        python modules. The use of virtual environments is recommended::
        
            pip install scikit-tensor-py3
        
        To install in development mode::
        
            git clone https://github.com/evertrol/scikit-tensor-py3.git
            pip install -e scikit-tensor
        
        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. See
        also the note above.
        
        Development is synchronized via git. Feel free to fork this project
        and make pull requests from that fork.
        
        Authors
        -------
        
        * Maximilian Nickel: `Web <http://web.mit.edu/~mnick/www>`_,
          `Email <mailto://mnick AT mit DOT edu>`,
          `Twitter <http://twitter.com/mnick>`_
        * Evert Rol (maintenance for Python 3 version): `Email <mailto:evert.rol@gmail.com>`_
        
        License
        -------
        
        scikit-tensor-py3 is licensed under the `GPLv3 <http://www.gnu.org/licenses/gpl-3.0.txt>`_
        
        Related Projects
        ----------------
        
        * `Matlab Tensor Toolbox <http://www.sandia.gov/~tgkolda/TensorToolbox/index-2.5.html>`_:
          A Matlab toolbox for tensor factorizations and tensor operations
          freely available for research and evaluation.
        
        * `Matlab Tensorlab <http://www.tensorlab.net/>`_ A Matlab toolbox for
          tensor factorizations, complex optimization, and tensor optimization
          freely available for non-commercial academic research.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.5
