Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis.
- Install the latest release from pypi (
pip install pyttb
). - This is open source software. Please see LICENSE for the terms of the license (2-clause BSD).
- For more information or for feedback on this project, please contact us.
pyttb provides the following classes and functions for manipulating dense, sparse, and structured tensors, along with algorithms for computing low-rank tensor models.
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pyttb supports multiple tensor types, including dense and sparse, as well as specially structured tensors, such as the Krusal format (stored as factor matrices).
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CP methods such as alternating least squares, direct optimization, and weighted optimization (for missing data). Also alternative decompositions such as Poisson Tensor Factorization via alternating Poisson regression.
.. toctree:: :maxdepth: 1 getting_started.rst
.. toctree:: :maxdepth: 2 reference.rst
Please see references for how to cite a variety of algorithms implemented in this project.
.. toctree:: :maxdepth: 2 bibtex.rst
Please email dmdunla@sandia.gov with any questions about pyttb that cannot be resolved via issue reporting. Stories of its usefulness are especially welcome. We will try to respond to every email may not always be successful due to the volume of emails.