==========
graphtools
==========
.. image:: https://img.shields.io/pypi/v/graphtools.svg
:target: https://pypi.org/project/graphtools/
:alt: Latest PyPi version
.. image:: https://anaconda.org/conda-forge/graphtools/badges/version.svg
:target: https://anaconda.org/conda-forge/graphtools/
:alt: Latest Conda version
.. image:: https://img.shields.io/github/workflow/status/KrishnaswamyLab/graphtools/Unit%20Tests/master?label=Github%20Actions
:target: https://travis-ci.com/KrishnaswamyLab/graphtools
:alt: Github Actions Build
.. image:: https://img.shields.io/readthedocs/graphtools.svg
:target: https://graphtools.readthedocs.io/
:alt: Read the Docs
.. image:: https://coveralls.io/repos/github/KrishnaswamyLab/graphtools/badge.svg?branch=master
:target: https://coveralls.io/github/KrishnaswamyLab/graphtools?branch=master
:alt: Coverage Status
.. image:: https://img.shields.io/twitter/follow/KrishnaswamyLab.svg?style=social&label=Follow
:target: https://twitter.com/KrishnaswamyLab
:alt: Twitter
.. image:: https://img.shields.io/github/stars/KrishnaswamyLab/graphtools.svg?style=social&label=Stars
:target: https://github.com/KrishnaswamyLab/graphtools/
:alt: GitHub stars
.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
:target: https://github.com/psf/black
:alt: Code style: black
Tools for building and manipulating graphs in Python.
Installation
------------
graphtools is available on `pip`. Install by running the following in a terminal::
pip install --user graphtools
Alternatively, graphtools can be installed using `Conda <https://conda.io/docs/>`_ (most easily obtained via the `Miniconda Python distribution <https://conda.io/miniconda.html>`_)::
conda install -c conda-forge graphtools
Or, to install the latest version from github::
pip install --user git+git://github.com/KrishnaswamyLab/graphtools.git
Usage example
-------------
The `graphtools.Graph` class provides an all-in-one interface for k-nearest neighbors, mutual nearest neighbors, exact (pairwise distances) and landmark graphs.
Use it as follows::
from sklearn import datasets
import graphtools
digits = datasets.load_digits()
G = graphtools.Graph(digits['data'])
K = G.kernel
P = G.diff_op
G = graphtools.Graph(digits['data'], n_landmark=300)
L = G.landmark_op
Help
----
If you have any questions or require assistance using graphtools, please contact us at https://krishnaswamylab.org/get-help
Raw data
{
"_id": null,
"home_page": "https://github.com/KrishnaswamyLab/graphtools",
"name": "graphtools",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "graphs,big-data,signal processing,manifold-learning",
"author": "Scott Gigante, Daniel Burkhardt, and Jay Stanley, Yale University",
"author_email": "scott.gigante@yale.edu",
"download_url": "https://files.pythonhosted.org/packages/f2/cd/d1115be4cbd5cad8b1da4c4d92a6c35dd263d0f9b5eea47ed3d8d19674c7/graphtools-1.5.3.tar.gz",
"platform": null,
"description": "==========\ngraphtools\n==========\n\n.. image:: https://img.shields.io/pypi/v/graphtools.svg\n :target: https://pypi.org/project/graphtools/\n :alt: Latest PyPi version\n.. image:: https://anaconda.org/conda-forge/graphtools/badges/version.svg\n :target: https://anaconda.org/conda-forge/graphtools/\n :alt: Latest Conda version\n.. image:: https://img.shields.io/github/workflow/status/KrishnaswamyLab/graphtools/Unit%20Tests/master?label=Github%20Actions\n :target: https://travis-ci.com/KrishnaswamyLab/graphtools\n :alt: Github Actions Build\n.. image:: https://img.shields.io/readthedocs/graphtools.svg\n :target: https://graphtools.readthedocs.io/\n :alt: Read the Docs\n.. image:: https://coveralls.io/repos/github/KrishnaswamyLab/graphtools/badge.svg?branch=master\n :target: https://coveralls.io/github/KrishnaswamyLab/graphtools?branch=master\n :alt: Coverage Status\n.. image:: https://img.shields.io/twitter/follow/KrishnaswamyLab.svg?style=social&label=Follow\n :target: https://twitter.com/KrishnaswamyLab\n :alt: Twitter\n.. image:: https://img.shields.io/github/stars/KrishnaswamyLab/graphtools.svg?style=social&label=Stars\n :target: https://github.com/KrishnaswamyLab/graphtools/\n :alt: GitHub stars\n.. image:: https://img.shields.io/badge/code%20style-black-000000.svg\n :target: https://github.com/psf/black\n :alt: Code style: black\n\nTools for building and manipulating graphs in Python.\n\nInstallation\n------------\n\ngraphtools is available on `pip`. Install by running the following in a terminal::\n\n pip install --user graphtools\n\nAlternatively, graphtools can be installed using `Conda <https://conda.io/docs/>`_ (most easily obtained via the `Miniconda Python distribution <https://conda.io/miniconda.html>`_)::\n\n conda install -c conda-forge graphtools\n\nOr, to install the latest version from github::\n\n pip install --user git+git://github.com/KrishnaswamyLab/graphtools.git\n\nUsage example\n-------------\n\nThe `graphtools.Graph` class provides an all-in-one interface for k-nearest neighbors, mutual nearest neighbors, exact (pairwise distances) and landmark graphs.\n\nUse it as follows::\n\n from sklearn import datasets\n import graphtools\n digits = datasets.load_digits()\n G = graphtools.Graph(digits['data'])\n K = G.kernel\n P = G.diff_op\n G = graphtools.Graph(digits['data'], n_landmark=300)\n L = G.landmark_op\n\nHelp\n----\n\nIf you have any questions or require assistance using graphtools, please contact us at https://krishnaswamylab.org/get-help\n",
"bugtrack_url": null,
"license": "GNU General Public License Version 2",
"summary": "graphtools",
"version": "1.5.3",
"split_keywords": [
"graphs",
"big-data",
"signal processing",
"manifold-learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "6bd483d43ec3f3c1921d81fea68f3ecc9acf7a979a930402713774be56f95a23",
"md5": "2d59569eb22bd2348714da3edafee411",
"sha256": "bb4477e98e8aa0dcd11ffd61b224853862f5fb1172db8a92d87a48e57436c11b"
},
"downloads": -1,
"filename": "graphtools-1.5.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "2d59569eb22bd2348714da3edafee411",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 45363,
"upload_time": "2023-01-03T06:39:15",
"upload_time_iso_8601": "2023-01-03T06:39:15.353933Z",
"url": "https://files.pythonhosted.org/packages/6b/d4/83d43ec3f3c1921d81fea68f3ecc9acf7a979a930402713774be56f95a23/graphtools-1.5.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f2cdd1115be4cbd5cad8b1da4c4d92a6c35dd263d0f9b5eea47ed3d8d19674c7",
"md5": "3022a207588b72ea62074dad10a1d4fe",
"sha256": "b35ae2974d24c507fe01b110d10b1d8c949e20bc49ff9d7d04f94849f9795907"
},
"downloads": -1,
"filename": "graphtools-1.5.3.tar.gz",
"has_sig": false,
"md5_digest": "3022a207588b72ea62074dad10a1d4fe",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 55733,
"upload_time": "2023-01-03T06:39:16",
"upload_time_iso_8601": "2023-01-03T06:39:16.843030Z",
"url": "https://files.pythonhosted.org/packages/f2/cd/d1115be4cbd5cad8b1da4c4d92a6c35dd263d0f9b5eea47ed3d8d19674c7/graphtools-1.5.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-03 06:39:16",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "KrishnaswamyLab",
"github_project": "graphtools",
"travis_ci": false,
"coveralls": true,
"github_actions": true,
"requirements": [
{
"name": "numpy",
"specs": [
[
">=",
"1.14.0"
]
]
},
{
"name": "scipy",
"specs": [
[
">=",
"1.1.0"
]
]
},
{
"name": "pygsp",
"specs": [
[
">=",
">=0.5.1"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
">=",
"0.20.0"
]
]
},
{
"name": "future",
"specs": []
},
{
"name": "tasklogger",
"specs": [
[
">=",
"1.0"
]
]
},
{
"name": "Deprecated",
"specs": []
}
],
"lcname": "graphtools"
}
JSON
