Bug#1046633: ITP: libleidenalg -- implementation of the Leiden algorithm in C++

Étienne Mollier <[email protected]> Sun, 13 Aug 2023 22:54:55 +0200

Newsgroups	gmane.linux.debian.devel.medical
Message-ID	<ZNlDH/kOw05qL+HS__1261.75202183134$1691960378$gmane$org@fusion>

Package: wnpp
Severity: wishlist
Owner: Étienne Mollier <[email protected]>
X-Debbugs-Cc: [email protected]
X-Debbugs-Cc: [email protected]

* Package name    : libleidenalg
  Version         : 0.11.1
  Upstream Contact: V.A. Traag
* URL             : https://github.com/vtraag/libleidenalg
* License         : GPL-3+
  Programming Lang: C++
  Description     : implementation of the Leiden algorithm in C++

 This package implements the Leiden algorithm in C++.  It relies on igraph for
 it to function.  Besides the relative flexibility of the implementation, it
 also scales well, and can be run on graphs of millions of nodes (as long as
 they can fit in memory).  The core class is Optimiser which finds the optimal
 partition using the Leiden algorithm, which is an extension of the Louvain
 algorithm for a number of different methods.  The methods currently implemented
 are (1) modularity, (2) Reichardt and Bornholdt's model using the
 configuration null model and the Erdös-Rényi null model, (3) the Constant
 Potts model (CPM), (4) Significance, and finally (5) Surprise.  In addition,
 it supports multiplex partition optimisation allowing community detection on
 for example negative links or multiple time slices.  There is the possibility
 of only partially optimising a partition, so that some community assignments
 remain fixed.  It also provides some support for community detection on
 bipartite graphs.
 .
 Most people will find it easier to work with the Python interface provided by
 python3-leidenalg.

This package is necessary to further upgrade python-leidenalg.
It will be maintained within the Debian Med Team.  A packaging
stub is already available on Salsa[1].

[1]: https://salsa.debian.org/med-team/libleidenalg

Have a nice day,  :)
-- 
  .''`.  Étienne Mollier <[email protected]>
 : :' :  gpg: 8f91 b227 c7d6 f2b1 948c  8236 793c f67e 8f0d 11da
 `. `'   sent from /dev/pts/4, please excuse my verbosity
   `-    on air: Steve Rothery - Old Man Of The Sea

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