python-leidenalg 0.10.1-1 source package in Ubuntu
Changelog
python-leidenalg (0.10.1-1) unstable; urgency=medium * New upstream version 0.10.1 * typos.patch: remove: affected files moved to the liblibleidenalg. * d/rules: adjust CPATH for igraph. (Closes: #1042119) * d/control: build depends on liblibleidenalg-dev. * d/control: build depends on pybuild-plugin-pyproject. -- Étienne Mollier <email address hidden> Wed, 16 Aug 2023 18:33:02 +0200
Upload details
- Uploaded by:
- Debian Med
- Uploaded to:
- Sid
- Original maintainer:
- Debian Med
- Architectures:
- any
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Mantic | release | universe | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
python-leidenalg_0.10.1-1.dsc | 2.5 KiB | fb842cd493e233f092385b5f9078332c2f314f3e32c2c6ad5c813b8e22f8d95d |
python-leidenalg_0.10.1.orig.tar.gz | 439.1 KiB | cab08c682ec6a388edcf5b1c5d0578972d439d46ef737852d1641abff2461cf1 |
python-leidenalg_0.10.1-1.debian.tar.xz | 3.6 KiB | 5f38ebfd1226db197105ee01c4f6abb79eacc528417466223d2eb880e5ec9c0a |
Available diffs
No changes file available.
Binary packages built by this source
- python3-leidenalg: Python3 implementation of the Leiden algorithm in C++
This package implements the Leiden algorithm in C++ and exposes it to
Python. 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 function is find_partition 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.
- python3-leidenalg-dbgsym: debug symbols for python3-leidenalg