find_partition

Finds the optimal partition using the Leiden algorithm

An R interface to the Leiden algorithm, an iterative community detection algorithm on networks. The algorithm is designed to converge to a partition in which all subsets of all communities are locally optimally assigned, yielding communities guaranteed to be connected. The implementation proves to be fast, scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The original implementation was constructed as a python interface "leidenalg" found here: <https://github.com/vtraag/leidenalg>. The algorithm was originally described in Traag, V.A., Waltman, L. & van Eck, N.J. "From Louvain to Leiden: guaranteeing well-connected communities". Sci Rep 9, 5233 (2019) <doi:10.1038/s41598-019-41695-z>.

Evan Biederstedt

leidenAlg

Implements the Leiden Algorithm via an R Interface

Peter Kharchenko

Viktor Petukhov

Yichen Wang

V.A. Traag

Gábor Csárdi

Tamás Nepusz

Minh Van Nguyen

find_partition function

<dl><dt>graph</dt>
<dd>The igraph graph to define the partition on</dd>
<dt>edge_weights</dt>
<dd>Vector of edge weights. In weighted graphs, a real number is assigned to each (directed or undirected) edge. For an unweighted graph, this is set to 1. Refer to igraph, weighted graphs.</dd>
<dt>resolution</dt>
<dd>Numeric scalar, resolution parameter controlling communities detected (default=1.0) Higher resolutions lead to more communities, while lower resolutions lead to fewer communities.</dd>
<dt>niter</dt>
<dd>Number of iterations that the algorithm should be run for (default=2)</dd></dl>

Arguments

Finds the optimal partition using the Leiden algorithm — find_partition

<dl>

<dt>graph</dt>
<dd>The igraph graph to define the partition on</dd>


<dt>edge_weights</dt>
<dd>Vector of edge weights. In weighted graphs, a real number is assigned to each (directed or undirected) edge. For an unweighted graph, this is set to 1. Refer to igraph, weighted graphs.</dd>


<dt>resolution</dt>
<dd>Numeric scalar, resolution parameter controlling communities detected (default=1.0) Higher resolutions lead to more communities, while lower resolutions lead to fewer communities.</dd>


<dt>niter</dt>
<dd>Number of iterations that the algorithm should be run for (default=2)</dd>

</dl>

find_partition: Finds the optimal partition using the Leiden algorithm

Description

Usage

Value

Arguments

Examples