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README.md

build status license: GPLv3 DOI CRAN version PyPI version R coverage status python coverage status python docs status

motifcluster motifcluster sticker

Motif-based spectral clustering of weighted directed networks

Introduction

This repository provides implementations of motif-based spectral clustering of weighted directed networks in R and in Python. This code is based on methods detailed in [Underwood, Elliott and Cucuringu, 2020], which is available at arXiv:2004.01293. These packages 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.

Branches

The master branch contains stable versions. The develop branch may be unstable, and is for development purposes only.

Authors

License

This repository and its included R and Python packages are all licensed under GPLv3.

R package

The motifcluster R package is in the R directory.

Installation

The R package can be installed from CRAN with:

install.packages("motifcluster")

Dependencies

The R package has the following dependencies, available on CRAN:

  • igraph
  • LICORS
  • Matrix
  • RSpectra

Documentation

The package's manual is in the R/doc directory. R documentation files are provided for each function available in the package. An instructional vignette is in the R/vignettes directory.

Python package

The motifcluster Python package is in the python directory.

Installation

The Python package can be installed from PyPI with:

pip install motifcluster

Dependencies

The Python package has the following dependencies, available on PyPI:

  • Networkx
  • Numpy
  • Scipy
  • Scikit-learn

Documentation

Full documentation is available at motifcluster.readthedocs.io.

Performance

The performance directory contains scripts and plots relating to timing the construction of motif adjacency matrices, in both R and Python.

Sticker

A high-resolution hexagonal sticker is available in the sticker directory.

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Motif-based weighted spectral clustering in Python and R

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