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Project description

Tensor Toolbox provides functionalities for the decomposition of tensors in tensor-train format [1] and spectral tensor-train format [2].

The toolbox provides the following tools:

  • TT-svd

  • TT-cross

  • TT-vectors

  • TT-matrices

  • Quatics TT-vectors/matrices

  • TT-integration

  • Basic operations in TT format

  • Multi-linear algebra in TT format (Steepest descent, CG and GMRES)

  • STT-construction

  • STT-projection/interpolation

  • STT for single quantities and for fields


Use the usual pip command:

$ pip install TensorToolbox

The main dependencies of the package are the SpectralToolbox and mpi4py. The remaining dependencies should be resolved smoothly.

Some users might want to install the toolbox without MPI support. This is possible, but not through the pip command:

$ pip install –download=”/pth/to/downloaded/files” TensorToolbox

$ cd /pth/to/downloaded/files

$ tar xzf TensorToolbox-x.x.x.tar.gz

$ cd TensorToolbox-x.x.x

$ python install –without-mpi4py

Test Installation

You can test whether all the functionalities work by running the unit tests.

>>> import TensorToolbox
>>> TensorToolbox.RunUnitTests(maxprocs=None)

where maxprocs defines the number of processors to be used if MPI support is activated. Be patient. The number of unit tests grows with the number of functionalities implemented in the software.


Examples can be found inside the package. To find them, download the source:

$ pip install –download=”/pth/to/downloaded/files” TensorToolbox

$ cd /pth/to/downloaded/files

$ tar xzf TensorToolbox-x.x.x.tar.gz

$ cd TensorToolbox-x.x.x

$ cd Examples


[1] Oseledets, I. (2011). Tensor-train decomposition. SIAM Journal on Scientific Computing, 33(5), 2295–2317. Retrieved from

[2] Bigoni, D. and Marzouk, Y.M. and Engsig-Karup, A.P. (2014) Spectral tensor-train decomposition. (Submitted)

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TensorToolbox-0.1.2.tar.gz (1.0 MB view hashes)

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