pyttb: Python Tensor Toolbox

Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis.

  • 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.

Functionality

pyttb provides the following classes and functions for manipulating dense, sparse, and structured tensors, along with algorithms for computing low-rank tensor models.

  • Tensor Classes

    pyttb supports multiple tensor types, including dense and sparse, as well as specially structured tensors, such as the Krusal format (stored as factor matrices).

  • Algorithms

    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.

Python API

How to Cite

Please see references for how to cite a variety of algorithms implemented in this project.

Contact

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.

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