Collection of various optimization methods, including tensor based, for multivariate functions and multidimensional data arrays
Project description
teneva_opti
Description
Collection of various optimization methods (search for the global minimum and/or maximum) for multivariate functions and multidimensional data arrays (tensors). This library is based on a software product teneva. See also related benchmarks library teneva_bm.
Installation
Current version "0.3.4".
The package can be installed via pip: pip install teneva_opti (it requires the Python programming language of the version 3.8 or 3.9). It can be also downloaded from the repository teneva_opti and installed by python setup.py install command from the root folder of the project.
We test optimizers with benchmarks from teneva_bm library. For installation of additional dependencies (gym and mujoco) for agent collection , please, do the following (for existing conda environment teneva_opti; if you are using a different environment name, then please make the appropriate substitution in the script):
wget https://raw.githubusercontent.com/AndreiChertkov/teneva_bm/main/install_mujoco.py && python install_mujoco.py --env teneva_opti && rm install_mujoco.py
In the case of problems with
scikit-learn, uninstall itpip uninstall scikit-learnand then install it from the anaconda:conda install -c anaconda scikit-learn.
Documentation and examples (TODO)
Please, run the demo script:
clear && python demo.py
Authors
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