PHOTON Graph - Graph machine learning with photonai.
Project description
photonai-graph
Photon Graph is an extension for the PHOTON framework that allows for the use of machine learning based on graphs. Furthermore, the Graph Utilities contain a wide variety of functions that allow for the visualization and converting of graphs.
Documentation
You can find a detailed documentation here: https://wwu-mmll.github.io/photonai_graph/
Installation
To install photonai-graph create a dedicated conda/python environment and activate it. Then install photonai-graph via
pip install photonai-graph
To be able to use all modules of the toolbox you will still need to install tensorflow, dgl, pytorch and grakel according to your system configuration, for example with
pip install tensorflow
pip install torch
pip install dgl
pip install grakel
For graph embeddings the gem python package is needed, along with tensorflow. Please install tensorflow according to your system.
pip install nxt-gem
pip install tensorflow
For graph kernels the grakel package needs to be installed. You can install grakel via pip.
pip install git+https://github.com/ysig/GraKeL.git@cfd14e0543075308d201327ac778a48643f81095'
For graph neural networks pytorch and deep graph library are required. You can install them via pip
pip install torch
pip install dgl
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
Built Distribution
Hashes for photonai_graph-0.2.4-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b98891b5ecded481e05598d2e5cf65419b402174f81e39ed4476b9587de1921d |
|
MD5 | f9433145068da08c92c295168d6d13c6 |
|
BLAKE2b-256 | b7bc37144667d0788d4f3506e28a1a339c17c19a0b7d037d950015048df26dab |