multivar_horner

multivar_horner: A Python package for computing Horner factorisations of multivariate polynomials - Published in JOSS (2020)

https://github.com/jannikmi/multivar_horner

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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Found 1 DOI reference(s) in README
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Links to: arxiv.org, joss.theoj.org, zenodo.org
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Scientific vocabulary similarity
Low similarity (11.2%) to scientific vocabulary

Keywords

evaluation factorization horner horner-scheme hornerscheme-solver math mathematics multivariate multivariate-polynomials polynomial polynomial-evaluation polynomials python python3

Keywords from Contributors

simulations mesh

Last synced: 6 months ago · JSON representation

Repository

python package implementing a multivariate Horner scheme for efficiently evaluating multivariate polynomials

Basic Info

Host: GitHub
Owner: jannikmi
License: mit
Language: Python
Default Branch: master
Homepage: https://multivar-horner.readthedocs.io/en/latest/
Size: 5.01 MB

Statistics

Stars: 29
Watchers: 1
Forks: 3
Open Issues: 15
Releases: 7

Topics

evaluation factorization horner horner-scheme hornerscheme-solver math mathematics multivariate multivariate-polynomials polynomial polynomial-evaluation polynomials python python3

Created over 7 years ago · Last pushed 12 months ago

Metadata Files

Readme Changelog Contributing Funding License

README.rst

===============
multivar_horner
===============

.. image:: https://github.com/jannikmi/multivar_horner/actions/workflows/build.yml/badge.svg?branch=master
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    :alt: JOSS status
    :target: https://joss.theoj.org/papers/0b514c6894780f3cc81ed88c141631d4

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``multivar_horner`` is a python package implementing a multivariate
`Horner scheme ("Horner's method", "Horner's rule") `__
for efficiently evaluating multivariate polynomials.


Quick Guide:

.. code-block:: console

    pip install multivar_horner


For efficiency this package is compiling the instructions required for polynomial evaluation to C by default.
If you don't have a C compiler (``gcc`` or ``cc``) installed you also need to install numba for using an alternative method:

.. code-block:: console

    pip install multivar_horner[numba]


Simple example:

.. code-block:: python

    import numpy as np
    from multivar_horner import HornerMultivarPolynomial

    # input parameters defining the polynomial
    #   p(x) = 5.0 + 1.0 x_1^3 x_2^1 + 2.0 x_1^2 x_3^1 + 3.0 x_1^1 x_2^1 x_3^1
    coefficients = np.array([[5.0], [1.0], [2.0], [3.0]], dtype=np.float64)
    exponents = np.array([[0, 0, 0], [3, 1, 0], [2, 0, 1], [1, 1, 1]], dtype=np.uint32)

    # [#ops=7] p(x) = x_1 (x_1 (x_1 (1.0 x_2) + 2.0 x_3) + 3.0 x_2 x_3) + 5.0
    horner_polynomial = HornerMultivarPolynomial(coefficients, exponents)
    x = np.array([-2.0, 3.0, 1.0], dtype=np.float64)
    p_x = horner_polynomial(x)



Also see:

- `Documentation `__
- `GitHub `__
- `PyPI `__
- `paper (JOSS) `__
- `paper (arXiv) `__

Owner

Name: Jannik Kissinger
Login: jannikmi
Kind: user
Location: Heidelberg, Germany
Company: @svalabs

Website: https://www.linkedin.com/in/jannik-kissinger-546b7a181/
Repositories: 11
Profile: https://github.com/jannikmi

Algorithm Engineering - Machine Learning - Reinforcement Learning

GitHub Events

Total

Watch event: 3
Delete event: 1
Issue comment event: 1
Push event: 1
Pull request event: 4
Create event: 3

Last Year

Watch event: 3
Delete event: 1
Issue comment event: 1
Push event: 1
Pull request event: 4
Create event: 3

Committers

Last synced: 7 months ago

All Time

Total Commits: 208
Total Committers: 6
Avg Commits per committer: 34.667
Development Distribution Score (DDS): 0.298

Past Year

Commits: 1
Committers: 1
Avg Commits per committer: 1.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
MrMinimal64	g**b@m**t	146
MrMinimal64	p**n@m**t	47
dependabot[bot]	4****]	9
Steve Schmerler	g**t@e**m	3
David P. Sanders	d**s@g**m	2
MrMinimal64	M****4	1

Committer Domains (Top 20 + Academic)

michelfe.it: 2 elcorto.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 27
Total pull requests: 40
Average time to close issues: 6 months
Average time to close pull requests: about 1 month
Total issue authors: 9
Total pull request authors: 4
Average comments per issue: 1.96
Average comments per pull request: 0.38
Merged pull requests: 25
Bot issues: 0
Bot pull requests: 22

Past Year

Issues: 0
Pull requests: 7
Average time to close issues: N/A
Average time to close pull requests: about 2 months
Issue authors: 0
Pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 0.29
Merged pull requests: 1
Bot issues: 0
Bot pull requests: 7

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Top Authors

Issue Authors

jannikmi (19)
Cfather (1)
johan-girardot (1)
dpsanders (1)
pomeroyb (1)
Dannylee885 (1)
KPJoshi (1)
LordThunder333 (1)
hbarthels (1)

Pull Request Authors

dependabot[bot] (33)
jannikmi (17)
dpsanders (2)
elcorto (2)

Top Labels

Issue Labels

enhancement (15) help wanted (4) good first issue (4)

Pull Request Labels

dependencies (33) python (21)

Packages

Total packages: 1
Total downloads:
- pypi 104 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 14
Total maintainers: 1

pypi.org: multivar-horner

python package implementing a multivariate Horner scheme for efficiently evaluating multivariate polynomials

Homepage: https://multivar-horner.readthedocs.io/en/latest/
Documentation: https://multivar-horner.readthedocs.io/en/latest/
License: MIT
Latest release: 3.1.0
published about 3 years ago

Versions: 14
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 104 Last month

Rankings

Dependent packages count: 10.1%

Stargazers count: 12.3%

Forks count: 16.9%

Average: 19.8%

Dependent repos count: 21.6%

Downloads: 38.2%

Maintainers (1)

MrMinimal64

Last synced: 6 months ago

Dependencies

docs/requirements.txt pypi

Sphinx *
numpy *
sphinx-rtd-theme *
sphinxcontrib-bibtex *
toml *

poetry.lock pypi

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pyproject.toml pypi

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build ^0.8.0 develop
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pytest-cov ^3.0.0 develop
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sphinx-rtd-theme ^1.0.0 develop
sphinxcontrib-bibtex ^2.4.1 develop
tox ^3.24.4 develop
twine ^3.6.0 develop
numba ^0.55.2
numpy ^1.22
python >=3.8,<3.11

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actions/checkout v4 composite
actions/setup-python v5 composite
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pypa/gh-action-pypi-publish release/v1 composite

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multivar_horner

Science Score: 49.0%

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