motifcluster¶
A Python package for motif-based spectral clustering of weighted directed networks.
Introduction¶
The motifcluster package provides implementations of motif-based spectral clustering of weighted directed networks in Python. These provide the capability for:
- Building motif adjacency matrices
- Sampling random weighted directed networks
- Spectral embedding with motif adjacency matrices
- Motif-based spectral clustering
The methods are all designed to run quickly on large sparse networks, and are easy to install and use. These methods are based on those described in [Underwood, Elliott and Cucuringu, 2020], which is available at arxiv:2004.01293.
Installation¶
From PyPI:
pip install motifcluster
With conda:
conda install -c conda-forge motifcluster
Dependencies¶
- Networkx
- Numpy
- Scipy
- Scikit-learn
Documentation¶
Documentation for the motifcluster package is available on Read the Docs.
Tutorial¶
A tutorial for the motifcluster package is available on Github in the tutorial directory.
Authors¶
- William George Underwood, Princeton University (maintainer)
- Andrew Elliott, The Alan Turing Institute
Links¶
- Source code repository on GitHub
- Package index page on PyPI
- Documentation on Read the Docs