Metadata-Version: 2.1
Name: recursivenodes
Version: 0.2.0
Summary: Recursively defined interpolation nodes for the simplex
Home-page: https://tisaac.gitlab.io/recursivenodes/
Author: Toby Isaac
Author-email: tisaac@cc.gatech.edu
License: MIT
Project-URL: Bug Tracker, https://gitlab.com/tisaac/recursivenodes/issues
Project-URL: Source Code, https://gitlab.com/tisaac/recursivenodes/
Description: # `recursivenodes`: Recursive, parameter-free, explicitly defined interpolation nodes for simplices
        
        This package includes one module level function, `recursive_nodes()`, which returns
        nodes for polynomial interpolation on the simplex in arbitrary dimensions.
        
        The nodes have a few nice properties: they are explicitly constructed and fully
        symmetric, and their traces on edges are Lobatto-Gauss-Legendre nodes (or any
        other node set you wish to use).  Among explicitly constructed nodes, they
        appear to have the best interpolation properties.  You can find more details in
        the [documentation](https://tisaac.gitlab.io/recursivenodes), and even more in the
        [preprint](https://arxiv.org/abs/2002.09421).
        
        ```bibtex
        @misc{isaac2020recursive,
            title={Recursive, parameter-free, explicitly defined interpolation nodes for simplices},
            author={Tobin Isaac},
            year={2020},
            eprint={2002.09421},
            archivePrefix={arXiv},
            primaryClass={math.NA}
        }
        ```
        
        ## Requirements:
        
        - Only `numpy` is needed for `recursive_nodes()`.
        - The `lebesgue` submodules requires `scipy`.
        - Testing requires `coverage`, `pytest` and `matplotlib`.
        - Building documentation additionally requires `sphinx`, `sphinxcontrib-bibtex`, and `sphinxcontrib-tikz`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: doc
Provides-Extra: lebesgue
Provides-Extra: all
