Metadata-Version: 2.1
Name: photonai-graph
Version: 0.2.4
Summary: PHOTON Graph - Graph machine learning with photonai.
Home-page: https://www.photon-ai.com/
Author: PHOTON Team
Author-email: hahnt@uni-muenster.de
License: MIT
Download-URL: https://pypi.org/project/photonai_graph/#files
Project-URL: Source Code, https://github.com/wwu-mmll/photonai_graph
Project-URL: Documentation, https://wwu-mmll.github.io/photonai_graph/
Project-URL: Bug Tracker, https://github.com/wwu-mmll/photonai_graph/issues
Keywords: machine learning,deep learning,graph convolutional neural networks,graphs
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/markdown
License-File: LICENSE

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# 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

```bash
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

```bash
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.

```bash
pip install nxt-gem
pip install tensorflow
```

For graph kernels the grakel package needs to be installed. You can install grakel via pip.

```bash
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

```bash
pip install torch
pip install dgl
```



