graphtools
Project description
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 (most easily obtained via the Miniconda Python distribution):
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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
graphtools-1.3.1.tar.gz
(33.7 kB
view hashes)
Built Distribution
graphtools-1.3.1-py3-none-any.whl
(39.3 kB
view hashes)
Close
Hashes for graphtools-1.3.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b93b9823e6b72b6d98934067967c59fb3b785c7ff0d997322d1c6d5acbac1b33 |
|
MD5 | 087a8f34be6c938d567b880d86e2129e |
|
BLAKE2b-256 | 28d43e0f973b84b892bb39414a11818ed40cf460ee8e3e9b9d8dd28eda832022 |