teneva-ht-jax 0.1.2

Compact implementation of basic operations in the Hierarchical Tucker (HT) format for approximation and sampling from multidimensional arrays and multivariate functions

teneva_ht_jax

Description

This python package, named teneva_ht_jax (tensor evaluation with Hierarchical Tucker and jax), provides a very compact implementation of basic operations in the Hierarchical Tucker (HT) format, including approximation and sampling from multidimensional arrays and multivariate functions. The program code is organized within a functional paradigm and it is very easy to learn and use.

Installation

Current version "0.1.2".

The package can be installed via pip: pip install teneva_ht_jax (it requires the Python programming language of the version >= 3.8). It can be also downloaded from the repository teneva_ht_jax and installed by python setup.py install command from the root folder of the project.

Required python packages numpy (1.22+), scipy (1.8+), jax (3.3+; cpu version) and optax (0.1.5+) will be automatically installed during the installation of the main software product. However, it is recommended that you manually install them first.

Documentation and examples

• See detailed online documentation for a description and various numerical examples for each function.
• See the jupyter notebooks in the ./demo folder with brief description and demonstration of the capabilities of each function from the teneva_ht_jax package. Note that all examples from this folder are also presented in the online documentation.

Authors

• Andrei Chertkov
• Gleb Ryzhakov
• Ivan Oseledets
• Will be extended soon ;)

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