Multidimensional cross approximation in the tensor-train (TT) format.
Project description
teneva
Description
This python package, named teneva (tensor evaluation), provides very compact implementation for the multidimensional cross approximation algorithm in the tensor-train (TT) format. This package also contains a function for quickly calculating the values of the constructed low-rank tensor approximation, as well as a number of auxiliary useful utilities.
In the current implementation, this software product actually duplicates the functionality related to the rectcross algoritm of the popular ttpy python package.
However, this compact implementation does not require a fortran compiler to be installed.
Requirements
- Python programming language (version >= 3.7).
- "Standard" python packages numpy and scipy (all of them are included in anaconda distribution).
- Python package numba.
With this package, the tensor values at the given points will be calculated an order of magnitude faster.
Installation
- Install python (version >= 3.7) and "standard" python packages listed in the section Requirements above. The best way is to install only anaconda distribution which includes all the packages.
- Install numba python package according to instructions from the corresponding repository.
- Download this repository and run
python setup.py installfrom the root folder of the project.You can install this package via pip:
pip install teneva. - To uninstall this package from the system run
pip uninstall teneva.
Examples
See this colab notebook with examples.
See also the folder examples with some demos in the jupyter format.
Tests
See colab notebook, where the comparison with the package ttpy is provided.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
