########
quadax
########
|License| |DOI| |Issues| |Pypi|
|Docs| |UnitTests| |Codecov|
quadax is a library for numerical quadrature and integration using JAX.
- ``vmap``-able, ``jit``-able, differentiable.
- Scalar or vector valued integrands.
- Finite or infinite domains with discontinuities or singularities within the domain of integration.
- Globally adaptive Gauss-Kronrod and Clenshaw-Curtis quadrature for smooth integrands (similar to ``scipy.integrate.quad``)
- Adaptive tanh-sinh quadrature for singular or near singular integrands.
- Quadrature from sampled values using trapezoidal and Simpsons methods.
Coming soon:
- Custom JVP/VJP rules (currently AD works by differentiating the loop which isn't the most efficient.)
- N-D quadrature (cubature)
- QMC methods
- Integration with weight functions
- Sparse grids (maybe, need to play with data structures and JAX)
Installation
============
quadax is installable with `pip`:
.. code-block:: console
pip install quadax
Usage
=====
.. code-block:: python
import jax.numpy as jnp
import numpy as np
from quadax import quadgk
fun = lambda t: t * jnp.log(1 + t)
epsabs = epsrel = 1e-5 # by default jax uses 32 bit, higher accuracy requires going to 64 bit
a, b = 0, 1
y, info = quadgk(fun, [a, b], epsabs=epsabs, epsrel=epsrel)
assert info.err < max(epsabs, epsrel*abs(y))
np.testing.assert_allclose(y, 1/4, rtol=epsrel, atol=epsabs)
For full details of various options see the `API documentation <https://quadax.readthedocs.io/en/latest/api.html>`__
.. |License| image:: https://img.shields.io/github/license/f0uriest/quadax?color=blue&logo=open-source-initiative&logoColor=white
:target: https://github.com/f0uriest/quadax/blob/master/LICENSE
:alt: License
.. |DOI| image:: https://zenodo.org/badge/709132830.svg
:target: https://zenodo.org/doi/10.5281/zenodo.10035983
:alt: DOI
.. |Docs| image:: https://img.shields.io/readthedocs/quadax?logo=Read-the-Docs
:target: https://quadax.readthedocs.io/en/latest/?badge=latest
:alt: Documentation
.. |UnitTests| image:: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml/badge.svg
:target: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml
:alt: UnitTests
.. |Codecov| image:: https://codecov.io/github/f0uriest/quadax/graph/badge.svg?token=MB11I7WE3I
:target: https://codecov.io/github/f0uriest/quadax
:alt: Coverage
.. |Issues| image:: https://img.shields.io/github/issues/f0uriest/quadax
:target: https://github.com/f0uriest/quadax/issues
:alt: GitHub issues
.. |Pypi| image:: https://img.shields.io/pypi/v/quadax
:target: https://pypi.org/project/quadax/
:alt: Pypi
Raw data
{
"_id": null,
"home_page": "https://github.com/f0uriest/quadax",
"name": "quadax",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "integration quadrature gauss kronrod tanh sinh romberg adaptive",
"author": "Rory Conlin",
"author_email": "wconlin@princeton.edu",
"download_url": "https://files.pythonhosted.org/packages/71/35/e1c7820f2b4d2612a6559b8807f455210cf3d3ae28b8a59d4242676cdeb3/quadax-0.2.5.tar.gz",
"platform": null,
"description": "\n########\nquadax\n########\n|License| |DOI| |Issues| |Pypi|\n\n|Docs| |UnitTests| |Codecov|\n\nquadax is a library for numerical quadrature and integration using JAX.\n\n- ``vmap``-able, ``jit``-able, differentiable.\n- Scalar or vector valued integrands.\n- Finite or infinite domains with discontinuities or singularities within the domain of integration.\n- Globally adaptive Gauss-Kronrod and Clenshaw-Curtis quadrature for smooth integrands (similar to ``scipy.integrate.quad``)\n- Adaptive tanh-sinh quadrature for singular or near singular integrands.\n- Quadrature from sampled values using trapezoidal and Simpsons methods.\n\nComing soon:\n\n- Custom JVP/VJP rules (currently AD works by differentiating the loop which isn't the most efficient.)\n- N-D quadrature (cubature)\n- QMC methods\n- Integration with weight functions\n- Sparse grids (maybe, need to play with data structures and JAX)\n\nInstallation\n============\n\nquadax is installable with `pip`:\n\n.. code-block:: console\n\n pip install quadax\n\n\n\nUsage\n=====\n\n.. code-block:: python\n\n import jax.numpy as jnp\n import numpy as np\n from quadax import quadgk\n\n fun = lambda t: t * jnp.log(1 + t)\n\n epsabs = epsrel = 1e-5 # by default jax uses 32 bit, higher accuracy requires going to 64 bit\n a, b = 0, 1\n y, info = quadgk(fun, [a, b], epsabs=epsabs, epsrel=epsrel)\n assert info.err < max(epsabs, epsrel*abs(y))\n np.testing.assert_allclose(y, 1/4, rtol=epsrel, atol=epsabs)\n\n\nFor full details of various options see the `API documentation <https://quadax.readthedocs.io/en/latest/api.html>`__\n\n\n.. |License| image:: https://img.shields.io/github/license/f0uriest/quadax?color=blue&logo=open-source-initiative&logoColor=white\n :target: https://github.com/f0uriest/quadax/blob/master/LICENSE\n :alt: License\n\n.. |DOI| image:: https://zenodo.org/badge/709132830.svg\n :target: https://zenodo.org/doi/10.5281/zenodo.10035983\n :alt: DOI\n\n.. |Docs| image:: https://img.shields.io/readthedocs/quadax?logo=Read-the-Docs\n :target: https://quadax.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation\n\n.. |UnitTests| image:: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml/badge.svg\n :target: https://github.com/f0uriest/quadax/actions/workflows/unittest.yml\n :alt: UnitTests\n\n.. |Codecov| image:: https://codecov.io/github/f0uriest/quadax/graph/badge.svg?token=MB11I7WE3I\n :target: https://codecov.io/github/f0uriest/quadax\n :alt: Coverage\n\n.. |Issues| image:: https://img.shields.io/github/issues/f0uriest/quadax\n :target: https://github.com/f0uriest/quadax/issues\n :alt: GitHub issues\n\n.. |Pypi| image:: https://img.shields.io/pypi/v/quadax\n :target: https://pypi.org/project/quadax/\n :alt: Pypi\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Numerical quadrature with JAX",
"version": "0.2.5",
"project_urls": {
"Contributing": "https://github.com/f0uriest/quadax/blob/master/CONTRIBUTING.rst",
"Documentation": "https://quadax.readthedocs.io/",
"Homepage": "https://github.com/f0uriest/quadax",
"Issues Tracker": "https://github.com/f0uriest/quadax/issues",
"Source Code": "https://github.com/f0uriest/quadax/"
},
"split_keywords": [
"integration",
"quadrature",
"gauss",
"kronrod",
"tanh",
"sinh",
"romberg",
"adaptive"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "df6e42790d8e403b9fa99afb8f8d73911f856a1777b096efe24ef63589ead0d0",
"md5": "342d296ee2694c85ea4d7ca1b973d965",
"sha256": "1c12c1aab71ff306905a660eb33baf4046918cabf1321c5da7f9ab85b0788b85"
},
"downloads": -1,
"filename": "quadax-0.2.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "342d296ee2694c85ea4d7ca1b973d965",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 31217,
"upload_time": "2025-01-21T02:25:43",
"upload_time_iso_8601": "2025-01-21T02:25:43.939088Z",
"url": "https://files.pythonhosted.org/packages/df/6e/42790d8e403b9fa99afb8f8d73911f856a1777b096efe24ef63589ead0d0/quadax-0.2.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "7135e1c7820f2b4d2612a6559b8807f455210cf3d3ae28b8a59d4242676cdeb3",
"md5": "1d69cbe410d0ae673ff5562f0f466a0b",
"sha256": "26b57477ea869fba8040ffbb6d9f67be3f63850856d0c5fb2e755676b640007b"
},
"downloads": -1,
"filename": "quadax-0.2.5.tar.gz",
"has_sig": false,
"md5_digest": "1d69cbe410d0ae673ff5562f0f466a0b",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 35089,
"upload_time": "2025-01-21T02:25:45",
"upload_time_iso_8601": "2025-01-21T02:25:45.931571Z",
"url": "https://files.pythonhosted.org/packages/71/35/e1c7820f2b4d2612a6559b8807f455210cf3d3ae28b8a59d4242676cdeb3/quadax-0.2.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-01-21 02:25:45",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "f0uriest",
"github_project": "quadax",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "equinox",
"specs": [
[
">=",
"0.11.0"
],
[
"<=",
"0.11.11"
]
]
},
{
"name": "jax",
"specs": [
[
">=",
"0.3.2"
],
[
"<=",
"0.5.0"
]
]
},
{
"name": "numpy",
"specs": [
[
">=",
"1.20.0"
],
[
"<=",
"2.2.2"
]
]
}
],
"lcname": "quadax"
}