.. image:: https://github.com/jgosmann/goppy/actions/workflows/ci.yml/badge.svg
:target: https://github.com/jgosmann/goppy/actions/workflows/ci.yml
:alt: CI and release pipeline
.. image:: https://codecov.io/gh/jgosmann/goppy/branch/main/graph/badge.svg?token=mkgZs4nds5
:target: https://codecov.io/gh/jgosmann/goppy
.. image:: https://img.shields.io/pypi/v/goppy
:target: https://pypi.org/project/goppy/
:alt: PyPI
.. image:: https://img.shields.io/pypi/pyversions/goppy
:target: https://pypi.org/project/goppy/
:alt: PyPI - Python Version
.. image:: https://img.shields.io/pypi/l/goppy
:target: https://pypi.org/project/goppy/
:alt: PyPI - License
.. image:: https://github.com/jgosmann/goppy/blob/main/doc/_static/goppy-sm.png
:alt: GopPy logo
Overview
--------
GopPy (Gaussian Online Processes for Python) is a pure Python module providing
a Gaussian process implementation which allows to add new data efficiently
online. I wrote this module because all other Python implementations I knew did
not support efficient online updates.
The feature list:
* `scikit-learn <http://scikit-learn.org>`_ compatible interface.
* Efficient online updates.
* Prediction of first order derivatives.
* Estimation of the log likelihood and its derivative.
* Well documented.
* `Good test coverage. <https://app.codecov.io/gh/jgosmann/goppy>`_
* MIT license.
Documentation
-------------
The documentation can be found at https://goppy.readthedocs.io/en/latest/.
Installation
------------
You can install GopPy with pip::
pip install goppy
Raw data
{
"_id": null,
"home_page": "https://github.com/jgosmann/goppy",
"name": "goppy",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.9,<3.13",
"maintainer_email": "",
"keywords": "Gaussian processes,machine learning,online learning",
"author": "Jan Gosmann",
"author_email": "jan@hyper-world.de",
"download_url": "https://files.pythonhosted.org/packages/d2/0c/4485625a14f632ac7c5bdff6e1529fedbb78bbe1d95567ef07632e022e6a/goppy-1.1.1.tar.gz",
"platform": null,
"description": ".. image:: https://github.com/jgosmann/goppy/actions/workflows/ci.yml/badge.svg\n :target: https://github.com/jgosmann/goppy/actions/workflows/ci.yml\n :alt: CI and release pipeline\n.. image:: https://codecov.io/gh/jgosmann/goppy/branch/main/graph/badge.svg?token=mkgZs4nds5\n :target: https://codecov.io/gh/jgosmann/goppy\n.. image:: https://img.shields.io/pypi/v/goppy\n :target: https://pypi.org/project/goppy/\n :alt: PyPI\n.. image:: https://img.shields.io/pypi/pyversions/goppy\n :target: https://pypi.org/project/goppy/\n :alt: PyPI - Python Version\n.. image:: https://img.shields.io/pypi/l/goppy\n :target: https://pypi.org/project/goppy/\n :alt: PyPI - License\n\n\n.. image:: https://github.com/jgosmann/goppy/blob/main/doc/_static/goppy-sm.png\n :alt: GopPy logo\n\nOverview\n--------\n\nGopPy (Gaussian Online Processes for Python) is a pure Python module providing\na Gaussian process implementation which allows to add new data efficiently\nonline. I wrote this module because all other Python implementations I knew did\nnot support efficient online updates.\n\nThe feature list:\n\n* `scikit-learn <http://scikit-learn.org>`_ compatible interface.\n* Efficient online updates.\n* Prediction of first order derivatives.\n* Estimation of the log likelihood and its derivative.\n* Well documented.\n* `Good test coverage. <https://app.codecov.io/gh/jgosmann/goppy>`_\n* MIT license.\n\nDocumentation\n-------------\n\nThe documentation can be found at https://goppy.readthedocs.io/en/latest/.\n\nInstallation\n------------\n\nYou can install GopPy with pip::\n\n pip install goppy\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "GopPy (Gaussian Online Processes for Python) is a pure Python module providing a Gaussian process implementation which allows 'to efficiently add new data online.",
"version": "1.1.1",
"project_urls": {
"Documentation": "https://goppy.readthedocs.io/en/latest/",
"Homepage": "https://github.com/jgosmann/goppy",
"Repository": "https://github.com/jgosmann/goppy"
},
"split_keywords": [
"gaussian processes",
"machine learning",
"online learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "9b059f281af22ae99523e2545a67c077d9b79f1af1ca942e5187c15dc4e7e647",
"md5": "5385a6443195cfb9b69fb2e56eb1f261",
"sha256": "d9fe91af9b1a3e2aaae24860a3aca278996b28109927b1a13aa6e4d9b37dc7e4"
},
"downloads": -1,
"filename": "goppy-1.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "5385a6443195cfb9b69fb2e56eb1f261",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9,<3.13",
"size": 14173,
"upload_time": "2023-10-20T19:24:00",
"upload_time_iso_8601": "2023-10-20T19:24:00.366786Z",
"url": "https://files.pythonhosted.org/packages/9b/05/9f281af22ae99523e2545a67c077d9b79f1af1ca942e5187c15dc4e7e647/goppy-1.1.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d20c4485625a14f632ac7c5bdff6e1529fedbb78bbe1d95567ef07632e022e6a",
"md5": "2716105bef39c9f4837f2258b552a204",
"sha256": "4e14b933518f91b8f531aeec28214dc4f8fe71265f0a2a068876e3c1553d4d10"
},
"downloads": -1,
"filename": "goppy-1.1.1.tar.gz",
"has_sig": false,
"md5_digest": "2716105bef39c9f4837f2258b552a204",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9,<3.13",
"size": 12322,
"upload_time": "2023-10-20T19:24:02",
"upload_time_iso_8601": "2023-10-20T19:24:02.070473Z",
"url": "https://files.pythonhosted.org/packages/d2/0c/4485625a14f632ac7c5bdff6e1529fedbb78bbe1d95567ef07632e022e6a/goppy-1.1.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-10-20 19:24:02",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "jgosmann",
"github_project": "goppy",
"travis_ci": false,
"coveralls": true,
"github_actions": true,
"lcname": "goppy"
}
JSON
