Metadata-Version: 2.1
Name: athena-mathlab
Version: 0.1.2.post2304
Summary: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis
Home-page: https://github.com/mathLab/ATHENA
Author: Marco Tezzele, Francesco Romor
Author-email: marcotez@gmail.com, francesco.romor@gmail.com
License: MIT
Keywords: parameter-space-reduction active-subspaces kernel-active-subspaces model-reduction sensitivity-analysis nonlinear-level-set-learning
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
License-File: LICENSE.rst
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: torch
Requires-Dist: GPyOpt
Requires-Dist: scikit-learn
Requires-Dist: scikit-learn-extra
Provides-Extra: docs
Requires-Dist: Sphinx (>=1.4) ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Provides-Extra: formatting
Requires-Dist: yapf ; extra == 'formatting'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Provides-Extra: tutorials
Requires-Dist: pyro ; extra == 'tutorials'
Requires-Dist: pyhmc ; extra == 'tutorials'

ATHENA is a Python package for reduction of high dimensional parameter spaces in the context of numerical analysis. It allows the use of several dimensionality reduction techniques such as Active Subspaces (AS), Kernel-based Active Subspaces (KAS), and Nonlinear Level-set Learning (NLL).

It is particularly suited for the study of parametric PDEs, for sensitivity analysis, and for the approximation of engineering quantities of interest. It can handle both scalar and vectorial high dimensional functions, making it a useful tool also to reduce the burden of computational intensive optimization tasks.
