Description: SyntaxWarnings: Invalid escape sequences.
 As seen at least with Python 3.13, a number of Python entities
 descriptions are raising warnings, caught in pytest's summary:
 .
         leidenalg/VertexPartition.py:388
           /build/reproducible-path/python-leidenalg-0.10.2/.pybuild/cpython3_3.13_leidenalg/build/leidenalg/VertexPartition.py:388: SyntaxWarning: invalid escape sequence '\m'
             """ Implements modularity. This quality function is well-defined only for positive edge weights.
 .
         leidenalg/VertexPartition.py:761
           /build/reproducible-path/python-leidenalg-0.10.2/.pybuild/cpython3_3.13_leidenalg/build/leidenalg/VertexPartition.py:761: SyntaxWarning: invalid escape sequence '\m'
             """ Implements Reichardt and Bornholdt's Potts model with a configuration null model.
 .
         leidenalg/Optimiser.py:7
           /build/reproducible-path/python-leidenalg-0.10.2/.pybuild/cpython3_3.13_leidenalg/build/leidenalg/Optimiser.py:7: SyntaxWarning: invalid escape sequence '\g'
             """ Class for doing community detection using the Leiden algorithm.
 .
         leidenalg/Optimiser.py:305
           /build/reproducible-path/python-leidenalg-0.10.2/.pybuild/cpython3_3.13_leidenalg/build/leidenalg/Optimiser.py:305: SyntaxWarning: invalid escape sequence '\s'
             """ Optimise the given partitions simultaneously.
 .
 This change declares the classes and function descriptions as raw
 strings, to avoid tripping the invalid escape sequence.

Author: Étienne Mollier <emollier@debian.org>
Bug-Debian: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1085929
Forwarded: https://github.com/vtraag/leidenalg/pull/194
Last-Update: 2024-12-06
---
This patch header follows DEP-3: http://dep.debian.net/deps/dep3/
--- python-leidenalg.orig/src/leidenalg/Optimiser.py
+++ python-leidenalg/src/leidenalg/Optimiser.py
@@ -4,7 +4,7 @@
 from math import log, sqrt
 
 class Optimiser(object):
-  """ Class for doing community detection using the Leiden algorithm.
+  r""" Class for doing community detection using the Leiden algorithm.
 
   The Leiden algorithm [1] derives from the Louvain algorithm [2]. The Louvain
   algorithm has an elegant formulation. It consists of two phases: (1) move
@@ -302,7 +302,7 @@
     return diff
 
   def optimise_partition_multiplex(self, partitions, layer_weights=None, n_iterations=2, is_membership_fixed=None):
-    """ Optimise the given partitions simultaneously.
+    r""" Optimise the given partitions simultaneously.
 
     Parameters
     ----------
--- python-leidenalg.orig/src/leidenalg/VertexPartition.py
+++ python-leidenalg/src/leidenalg/VertexPartition.py
@@ -385,7 +385,7 @@
     return _c_leiden._MutableVertexPartition_weight_from_comm(self._partition, v, comm)
 
 class ModularityVertexPartition(MutableVertexPartition):
-  """ Implements modularity. This quality function is well-defined only for positive edge weights.
+  r""" Implements modularity. This quality function is well-defined only for positive edge weights.
 
   Notes
   -----
@@ -758,7 +758,7 @@
     return new_partition
 
 class RBConfigurationVertexPartition(LinearResolutionParameterVertexPartition):
-  """ Implements Reichardt and Bornholdt's Potts model with a configuration null model.
+  r""" Implements Reichardt and Bornholdt's Potts model with a configuration null model.
   This quality function is well-defined only for positive edge weights.
   This quality function uses a linear resolution parameter.