[med-svn] [Git][med-team/python-leidenalg][upstream] New upstream version 0.11.0
Nilesh Patra (@nilesh)
gitlab at salsa.debian.org
Sat Nov 1 16:33:12 GMT 2025
Nilesh Patra pushed to branch upstream at Debian Med / python-leidenalg
Commits:
de0c8afc by Nilesh Patra at 2025-11-01T21:51:13+05:30
New upstream version 0.11.0
- - - - -
16 changed files:
- − .github/dependabot.yml
- − .github/workflows/build.yml
- CHANGELOG
- README.rst
- build-doc.yml
- doc/source/conf.py
- doc/source/intro.rst
- pyproject.toml
- scripts/build_igraph.bat
- scripts/build_igraph.sh
- scripts/build_libleidenalg.bat
- scripts/build_libleidenalg.sh
- setup.py
- src/leidenalg/Optimiser.py
- src/leidenalg/VertexPartition.py
- src/leidenalg/python_optimiser_interface.cpp
Changes:
=====================================
.github/dependabot.yml deleted
=====================================
@@ -1,6 +0,0 @@
-version: 2
-updates:
- - package-ecosystem: "github-actions"
- directory: "/"
- schedule:
- interval: "weekly"
=====================================
.github/workflows/build.yml deleted
=====================================
@@ -1,257 +0,0 @@
-name: Build and test, upload to PyPI on release
-
-on:
- push:
- branches:
- - master
- - '*'
- tags:
- - '*'
- pull_request:
- branches:
- - master
-
-env:
- CIBW_TEST_REQUIRES: ddt
- CIBW_TEST_COMMAND: "cd {project} && python -m unittest -v"
- CIBW_MANYLINUX_X86_64_IMAGE: "manylinux2014"
- CIBW_MANYLINUX_I686_IMAGE: "manylinux2014"
- CIBW_MANYLINUX_PYPY_X86_64_IMAGE: "manylinux2014"
- CIBW_MANYLINUX_PYPY_I686_IMAGE: "manylinux2014"
- CIBW_SKIP: "cp36-*"
- MACOSX_DEPLOYMENT_TARGET: "10.9"
-
-jobs:
- build_wheel_linux:
- name: Build wheels on Linux (${{ matrix.wheel_arch }})
- runs-on: ubuntu-20.04
- strategy:
- fail-fast: false
- matrix:
- wheel_arch: [x86_64, i686]
-
- steps:
- - uses: actions/checkout at v4
- with:
- submodules: true
- fetch-depth: 0
-
- - uses: actions/setup-python at v5
- name: Install Python
- with:
- python-version: '3.8'
-
- - name: Build wheels (manylinux)
- uses: pypa/cibuildwheel at v2.16.2
- env:
- CIBW_BEFORE_BUILD: "yum install -y flex bison &&
- pip install cmake wheel &&
- {package}/scripts/build_igraph.sh &&
- {package}/scripts/build_libleidenalg.sh "
- CIBW_ARCHS_LINUX: ${{ matrix.wheel_arch }}
- CIBW_BUILD: "*-manylinux_${{ matrix.wheel_arch }}"
- CIBW_ENVIRONMENT: >
- CFLAGS='-I/project/build-deps/install/include/ -L/project/build-deps/install/lib64/ -L/project/build-deps/install/lib/'
- LD_LIBRARY_PATH='/project/build-deps/install/lib64/:/project/build-deps/install/lib/'
-
- - name: Build wheels (musllinux)
- uses: pypa/cibuildwheel at v2.16.2
- env:
- CIBW_BEFORE_BUILD: "apk add flex bison zlib-dev &&
- pip install cmake wheel &&
- {package}/scripts/build_igraph.sh &&
- {package}/scripts/build_libleidenalg.sh"
- CIBW_BUILD: "*-musllinux_${{ matrix.wheel_arch }}"
- CIBW_TEST_EXTRAS: "test-musl"
- CIBW_ENVIRONMENT: >
- CFLAGS='-I/project/build-deps/install/include/ -L/project/build-deps/install/lib64/ -L/project/build-deps/install/lib/'
- LD_LIBRARY_PATH='/project/build-deps/install/lib64/:/project/build-deps/install/lib/'
-
- - uses: actions/upload-artifact at v4
- with:
- name: wheels-linux-${{ matrix.wheel_arch }}
- path: ./wheelhouse/*.whl
-
- build_wheel_linux_aarch64:
- name: Build wheels on Linux (aarch64)
- runs-on: ubuntu-20.04
- steps:
- - uses: actions/checkout at v4
- with:
- submodules: true
- fetch-depth: 0
-
- - name: Set up QEMU
- id: qemu
- uses: docker/setup-qemu-action at v3
-
- - name: Build wheels (manylinux)
- uses: pypa/cibuildwheel at v2.16.2
- env:
- CIBW_BEFORE_BUILD: "yum install -y flex bison zlib-devel &&
- pip install cmake wheel &&
- {package}/scripts/build_igraph.sh &&
- {package}/scripts/build_libleidenalg.sh"
- CIBW_ARCHS_LINUX: aarch64
- CIBW_BUILD: "*-manylinux_aarch64"
- CIBW_ENVIRONMENT: >
- CFLAGS='-I/project/build-deps/install/include/ -L/project/build-deps/install/lib64/ -L/project/build-deps/install/lib/'
- LD_LIBRARY_PATH='/project/build-deps/install/lib64/:/project/build-deps/install/lib/'
-
- - uses: actions/upload-artifact at v4
- with:
- name: wheels-linux-aarch64
- path: ./wheelhouse/*.whl
-
- build_wheel_macos:
- name: Build wheels on macOS (${{ matrix.wheel_arch }})
- runs-on: macos-latest
- env:
- LLVM_VERSION: "14.0.5"
- strategy:
- matrix:
- include:
- - cmake_arch: x86_64
- wheel_arch: x86_64
- - cmake_arch: arm64
- extra_cmake_args: -DF2C_EXTERNAL_ARITH_HEADER=../../../etc/arith_apple_m1.h -DIEEE754_DOUBLE_ENDIANNESS_MATCHES=ON
- wheel_arch: arm64
-
- steps:
- - uses: actions/checkout at v4
- with:
- submodules: true
- fetch-depth: 0
-
- - name: Cache installed C core
- id: cache-c-core
- uses: actions/cache at v3
- with:
- path: build-deps
- key: C-core-cache-${{ runner.os }}-${{ matrix.cmake_arch }}-llvm${{ env.LLVM_VERSION }}-${{ hashFiles('scripts/build_igraph.sh') }}-${{ hashFiles('scripts/build_libleidenalg.sh') }}
-
- - uses: actions/setup-python at v5
- name: Install Python
- with:
- python-version: '3.8'
-
- - name: Install OS dependencies
- if: steps.cache-c-core.outputs.cache-hit != 'true' || steps.cache-c-deps.outputs.cache-hit != 'true' # Only needed when building the C core
- run:
- brew install ninja cmake
-
- - name: Build wheels
- uses: pypa/cibuildwheel at v2.16.2
- env:
- CIBW_ARCHS_MACOS: "${{ matrix.wheel_arch }}"
- CIBW_BEFORE_BUILD: "{package}/scripts/build_igraph.sh &&
- {package}/scripts/build_libleidenalg.sh"
- CIBW_ENVIRONMENT: >
- CFLAGS='-Wno-unused-command-line-argument -I/Users/runner/work/leidenalg/leidenalg/build-deps/install/include/ -L/Users/runner/work/leidenalg/leidenalg/build-deps/install/lib64/ -L/Users/runner/work/leidenalg/leidenalg/build-deps/install/lib/'
- REPAIR_LIBRARY_PATH="${DYLD_LIBRARY_PATH}:/Users/runner/work/leidenalg/leidenalg/build-deps/install/lib64/:/Users/runner/work/leidenalg/leidenalg/build-deps/install/lib/"
- EXTRA_CMAKE_ARGS="-DCMAKE_OSX_ARCHITECTURES=${{ matrix.cmake_arch }} ${{ matrix.extra_cmake_args }}"
- CIBW_REPAIR_WHEEL_COMMAND: >
- DYLD_LIBRARY_PATH=$REPAIR_LIBRARY_PATH delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel}
- - uses: actions/upload-artifact at v4
- with:
- name: wheels-macos-${{ matrix.wheel_arch }}
- path: ./wheelhouse/*.whl
-
- build_wheel_win:
- name: Build wheels on Windows (${{ matrix.cmake_arch }})
- runs-on: windows-2022
- strategy:
- fail-fast: false
- matrix:
- include:
- - cmake_arch: Win32
- wheel_arch: win32
- - cmake_arch: x64
- wheel_arch: win_amd64
-
- steps:
- - uses: actions/checkout at v4
- with:
- submodules: true
- fetch-depth: 0
-
- - uses: actions/setup-python at v5
- name: Install Python
- with:
- python-version: '3.8'
-
- - name: Cache installed C core
- id: cache-c-core
- uses: actions/cache at v3
- with:
- path: build-deps
- key: C-core-cache-${{ runner.os }}-${{ matrix.cmake_arch }}-llvm${{ env.LLVM_VERSION }}-${{ hashFiles('scripts/build_igraph.sh') }}-${{ hashFiles('scripts/build_libleidenalg.sh') }}
-
- - name: Install build dependencies
- if: steps.cache-c-core.outputs.cache-hit != 'true' # Only needed when building the C core
- run: choco install winflexbison3 cmake ninja
-
- - name: Build wheels
- uses: pypa/cibuildwheel at v2.16.2
- env:
- CIBW_BEFORE_BUILD: "{package}/scripts/build_igraph.bat &&
- {package}/scripts/build_libleidenalg.bat &&
- pip install delvewheel"
- CIBW_BUILD: "*-${{ matrix.wheel_arch }}"
- CIBW_TEST_COMMAND: "cd /d {project} && python -m unittest -v"
- CIBW_SKIP: "cp36-* pp*"
- CIBW_ENVIRONMENT: >
- LIB="D:/a/leidenalg/leidenalg/build-deps/install/lib;$LIB"
- INCLUDE="D:/a/leidenalg/leidenalg/build-deps/install/include/;$INCLUDE"
- PATH="D:/a/leidenalg/leidenalg/build-deps/install/bin;$PATH"
- EXTRA_CMAKE_ARGS="-A ${{ matrix.cmake_arch }}"
- CIBW_REPAIR_WHEEL_COMMAND: "delvewheel repair -w {dest_dir} {wheel}"
- - uses: actions/upload-artifact at v4
- with:
- name: wheels-win-${{ matrix.wheel_arch }}
- path: ./wheelhouse/*.whl
-
- build_sdist:
- name: Build sdist
- runs-on: ubuntu-latest
- steps:
- - uses: actions/checkout at v4
- with:
- submodules: true
- fetch-depth: 0
-
- - uses: actions/setup-python at v5
- name: Install Python
- with:
- python-version: '3.8'
-
- - name: Install pypa/build
- run: pip3 install build
-
- - name: Build sdist
- run: |
- python3 -m build --sdist
-
- - uses: actions/upload-artifact at v4
- with:
- name: wheels-sdist
- path: dist/*.tar.gz
-
- upload_pypi:
- needs: [build_wheel_linux, build_wheel_linux_aarch64, build_wheel_macos, build_wheel_win, build_sdist]
- runs-on: ubuntu-latest
- # upload to PyPI on every push from the master branch
- if: github.event_name == 'push' &&
- startsWith(github.ref, 'refs/tags')
- steps:
- - uses: actions/download-artifact at v4
- with:
- pattern: wheels-*
- merge-multiple: true
- path: dist
-
- # Upload tagged versions to production PyPI
- - name: Publish distribution 📦 to PyPI
- uses: pypa/gh-action-pypi-publish at release/v1
- with:
- password: ${{ secrets.PYPI_API_TOKEN }}
\ No newline at end of file
=====================================
CHANGELOG
=====================================
@@ -1,3 +1,7 @@
+0.11.0
+- Update to libleidenalg 0.12.0
+- Update to igraph 1.0
+
0.10.2
- Also allow python-igraph >= 0.11
- Upgrade C core to 0.10.8 for binary wheels
=====================================
README.rst
=====================================
@@ -39,7 +39,7 @@ Installation
------------
In short: ``pip install leidenalg``. All major platforms are supported on
-Python>=3.6, earlier versions of Python are no longer supported. Alternatively,
+Python>=3.9, earlier versions of Python are no longer supported. Alternatively,
you can install from Anaconda (channel ``conda-forge``).
For Unix like systems it is possible to install from source. For Windows this is
@@ -55,11 +55,11 @@ that not only ``gcc`` is installed, but also ``g++``, as the ``leidenalg``
package is programmed in ``C++``. Note that there are build scripts included in
the ``scripts/`` directory. These are also used to build the binary wheels.
-1. Compile (and install) the C core of ``igraph`` (version >= 0.10). You can use
+1. Compile (and install) the C core of ``igraph`` (version >= 1.0.0). You can use
the file ``build_igraph.sh`` (on Unix-like systems) or ``build_igraph.bat``
(on Windows) in the ``scripts/`` directory to do this. For more details, see
https://igraph.org/c/doc/igraph-Installation.html.
-2. Compile (and install) the C core of ``libleidenalg`` (version >= 0.10). You
+2. Compile (and install) the C core of ``libleidenalg`` (version >= 0.12). You
can use the file ``build_libleidenalg.sh`` (on Unix-like systems) or
``build_libleidenalg.bat`` (on Windows) in the ``scripts/`` directory to do
this. For more details, see https://github.com/vtraag/libleidenalg.
=====================================
build-doc.yml
=====================================
@@ -3,9 +3,9 @@ channels:
- conda-forge
dependencies:
- python
- - igraph>=0.10,<0.11
- - libleidenalg>=0.11,<0.12
- - python-igraph>=0.10,<0.11
+ - igraph>=1.0.0,<2
+ - libleidenalg>=0.12,<0.13
+ - python-igraph>=1.0.0,<2
- ddt
- sphinx
- sphinx_rtd_theme
=====================================
doc/source/conf.py
=====================================
@@ -63,11 +63,10 @@ author = u'V.A. Traag'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
-from pkg_resources import get_distribution
+import importlib.metadata as md
# The full version, including alpha/beta/rc tags.
-release = get_distribution('leidenalg').version
-del get_distribution
+release = md.version('leidenalg')
# The short X.Y version.
version = '.'.join(release.split('.')[:2])
=====================================
doc/source/intro.rst
=====================================
@@ -23,7 +23,7 @@ That's it.
The result ``partition`` is in this case a
:class:`~leidenalg.ModularityVertexPartition` which is derived from the
:mod:`igraph` type :class:`ig.VertexClustering`, see the `documentation
-<https://igraph.org/python/api/latest/igraph.clustering.VertexClustering.html>`_
+<https://python.igraph.org/en/stable/api/igraph.VertexClustering.html>`_
for more details.
Why then should you use this package rather than for example the Louvain
=====================================
pyproject.toml
=====================================
@@ -16,14 +16,13 @@ keywords=[
"community detection",
"clustering"
]
-license = {text = "GPLv3+"}
+license = "GPL-3.0-or-later"
classifiers = [
"Development Status :: 4 - Beta",
"Environment :: Console",
"Intended Audience :: End Users/Desktop",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
- "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
"Operating System :: MacOS :: MacOS X",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
@@ -34,7 +33,7 @@ classifiers = [
"Topic :: Sociology"
]
dependencies = [
- "igraph >= 0.10.0,< 0.12",
+ "igraph >= 1.0.0,< 2.0",
]
dynamic = ["version"]
=====================================
scripts/build_igraph.bat
=====================================
@@ -1,6 +1,6 @@
@echo off
-set IGRAPH_VERSION=0.10.8
+set IGRAPH_VERSION=1.0.0
set ROOT_DIR=%cd%
echo Using root dir %ROOT_DIR%
=====================================
scripts/build_igraph.sh
=====================================
@@ -1,4 +1,4 @@
-IGRAPH_VERSION=0.10.4
+IGRAPH_VERSION=1.0.0
ROOT_DIR=`pwd`
echo "Using root dir ${ROOT_DIR}"
@@ -15,7 +15,7 @@ if [ ! -d "igraph" ]; then
echo ""
echo "Cloning igraph into ${ROOT_DIR}/build-deps/src/igraph"
# Clone repository if it does not exist yet
- git clone --branch ${IGRAPH_VERSION} https://github.com/igraph/igraph.git --single-branch
+ git clone --depth 1 --branch ${IGRAPH_VERSION} https://github.com/igraph/igraph.git --single-branch
fi
# Make sure the git repository points to the correct version
@@ -50,12 +50,13 @@ cmake ${ROOT_DIR}/build-deps/src/igraph \
-DIGRAPH_USE_INTERNAL_GMP=ON \
-DIGRAPH_WARNINGS_AS_ERRORS=OFF \
-DCMAKE_BUILD_TYPE=Release \
+ -DBUILD_TESTING=OFF \
${EXTRA_CMAKE_ARGS}
echo ""
echo "Build igraph"
-cmake --build .
+cmake --build . --config Release
echo ""
echo "Install igraph to ${ROOT_DIR}/build-deps/install/"
-cmake --build . --target install
+cmake --build . --target install --config Release
=====================================
scripts/build_libleidenalg.bat
=====================================
@@ -1,6 +1,6 @@
@echo off
-set LIBLEIDENALG_VERSION="0.11.0"
+set LIBLEIDENALG_VERSION="0.12.0"
set ROOT_DIR=%cd%
echo Using root dir %ROOT_DIR%
@@ -14,7 +14,7 @@ if not exist "libleidenalg\" (
echo.
echo Cloning libleidenalg into %ROOT_DIR%\build-deps\src\libleidenalg
REM Clone repository if it does not exist yet
- git clone --depth 1 --branch %libleidenalg_VERSION% https://github.com/vtraag/libleidenalg.git
+ git clone --branch %libleidenalg_VERSION% https://github.com/vtraag/libleidenalg.git
)
REM Make sure the git repository points to the correct version
=====================================
scripts/build_libleidenalg.sh
=====================================
@@ -1,4 +1,4 @@
-LIBLEIDENALG_VERSION=0.11.0
+LIBLEIDENALG_VERSION=0.12.0
ROOT_DIR=`pwd`
echo "Using root dir ${ROOT_DIR}"
@@ -45,8 +45,8 @@ cmake ${ROOT_DIR}/build-deps/src/libleidenalg \
echo ""
echo "Build libleidenalg"
-cmake --build .
+cmake --build . --config Release
echo ""
echo "Install libleidenalg to ${ROOT_DIR}/build-deps/install/"
-cmake --build . --target install
+cmake --build . --target install --config Release
=====================================
setup.py
=====================================
@@ -57,7 +57,7 @@ setup(
define_macros=macros,
libraries = ['libleidenalg', 'igraph'],
include_dirs=['include', 'build-deps/install/include'],
- library_dirs=['build-deps/install/lib']
+ library_dirs=['build-deps/install/lib', 'build-deps/install/lib64'],
)
],
cmdclass=cmdclass
=====================================
src/leidenalg/Optimiser.py
=====================================
@@ -4,7 +4,7 @@ from collections import namedtuple
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
@@ -24,19 +24,19 @@ class Optimiser(object):
algorithm that cannot be translated well in this framework: when merging
subcommunities in the refinement procedure, it does not consider whether they
are sufficiently well connected to the rest of the community. This
- implementation therefore does not guarantee subpartition :math:`\gamma`-density.
+ implementation therefore does not guarantee subpartition :math:`\\gamma`-density.
However, all other guarantees still hold:
After each iteration
- 1. :math:`\gamma`-separation
- 2. :math:`\gamma`-connectivity
+ 1. :math:`\\gamma`-separation
+ 2. :math:`\\gamma`-connectivity
After a stable iteration
3. Node optimality
4. Some subsets are locally optimally assigned
Asymptotically
- 5. Uniform :math:`\gamma`-density
+ 5. Uniform :math:`\\gamma`-density
6. Subset optimality
The optimiser class provides a number of different methods for optimising a
@@ -82,6 +82,8 @@ class Optimiser(object):
Nodes will only move to alternative communities that improve the given
quality function.
+ The default is :attr:`leidenalg.ALL_NEIGH_COMMS`.
+
Notes
-------
This attribute should be set to one of the following values
@@ -119,6 +121,8 @@ class Optimiser(object):
Nodes will only move to alternative communities that improve the given
quality function.
+ The default is :attr:`leidenalg.ALL_NEIGH_COMMS`.
+
Notes
-------
This attribute should be set to one of the following values
@@ -151,6 +155,7 @@ class Optimiser(object):
@property
def optimise_routine(self):
""" Determine the routine to use for *optimising* a partition.
+ The default is :attr:`leidenalg.MOVE_NODES`.
Notes
-------
@@ -173,16 +178,17 @@ class Optimiser(object):
@property
def refine_routine(self):
""" Determine the routine to use for *refining* a partition.
+ The default is :attr:`leidenalg.MERGE_NODES`.
Notes
-------
This attribute should be set to one of the following values
* :attr:`leidenalg.MOVE_NODES`
- Use :func:`move_nodes`.
+ Use :func:`move_nodes_constrained`.
* :attr:`leidenalg.MERGE_NODES`
- Use :func:`merge_nodes`.
+ Use :func:`merge_nodes_constrained`.
"""
return _c_leiden._Optimiser_get_refine_routine(self._optimiser)
@@ -285,6 +291,11 @@ class Optimiser(object):
itr = 0
diff = 0
continue_iteration = itr < n_iterations or n_iterations < 0
+
+ if is_membership_fixed is not None:
+ # Make sure it is a list
+ is_membership_fixed = list(is_membership_fixed)
+
while continue_iteration:
diff_inc = _c_leiden._Optimiser_optimise_partition(
self._optimiser,
@@ -302,7 +313,7 @@ class Optimiser(object):
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
----------
@@ -343,7 +354,7 @@ class Optimiser(object):
layer :math:`k` and the weight by :math:`\\lambda_k`, the overall quality
is then
- .. math:: Q = \sum_k \\lambda_k Q_k.
+ .. math:: Q = \\sum_k \\lambda_k Q_k.
This is particularly useful for graphs containing negative links. When
separating the graph in two graphs, the one containing only the positive
=====================================
src/leidenalg/VertexPartition.py
=====================================
@@ -5,7 +5,7 @@ from .functions import _get_py_capsule
class MutableVertexPartition(_ig.VertexClustering):
""" Contains a partition of a graph, derives from
:class:`ig.VertexClustering`. Please see the `documentation
- <https://igraph.org/python/api/latest/igraph.clustering.VertexClustering.html>`_
+ <https://python.igraph.org/en/stable/api/igraph.VertexClustering.html>`_
of :class:`ig.VertexClustering` for more details about its functionality.
This class contains the basic implementation for optimising a partition.
@@ -385,7 +385,7 @@ class MutableVertexPartition(_ig.VertexClustering):
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
-----
@@ -410,7 +410,7 @@ class ModularityVertexPartition(MutableVertexPartition):
Note that for directed graphs a slightly different formulation is used, as
proposed by Leicht and Newman [2]:
- .. math:: Q = \\frac{1}{m} \\sum_{ij} \\left(A_{ij} - \\frac{k_i^\mathrm{out} k_j^\mathrm{in}}{m} \\right)\\delta(\\sigma_i, \\sigma_j),
+ .. math:: Q = \\frac{1}{m} \\sum_{ij} \\left(A_{ij} - \\frac{k_i^\\mathrm{out} k_j^\\mathrm{in}}{m} \\right)\\delta(\\sigma_i, \\sigma_j),
where :math:`k_i^\\mathrm{out}` and :math:`k_i^\\mathrm{in}` refers to
respectively the outdegree and indegree of node :math:`i`, and :math:`A_{ij}`
@@ -758,7 +758,7 @@ class RBERVertexPartition(LinearResolutionParameterVertexPartition):
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.
@@ -785,7 +785,7 @@ class RBConfigurationVertexPartition(LinearResolutionParameterVertexPartition):
Note that for directed graphs a slightly different formulation is used, as
proposed by Leicht and Newman [2]:
- .. math:: Q = \\sum_{ij} \\left(A_{ij} - \\gamma \\frac{k_i^\mathrm{out} k_j^\mathrm{in}}{m} \\right)\\delta(\\sigma_i, \\sigma_j),
+ .. math:: Q = \\sum_{ij} \\left(A_{ij} - \\gamma \\frac{k_i^\\mathrm{out} k_j^\\mathrm{in}}{m} \\right)\\delta(\\sigma_i, \\sigma_j),
where :math:`k_i^\\mathrm{out}` and :math:`k_i^\\mathrm{in}` refers to
respectively the outdegree and indegree of node :math:`i`, and :math:`A_{ij}`
=====================================
src/leidenalg/python_optimiser_interface.cpp
=====================================
@@ -83,7 +83,7 @@ extern "C"
size_t nb_is_membership_fixed = PyList_Size(py_is_membership_fixed);
if (nb_is_membership_fixed != n)
{
- PyErr_SetString(PyExc_ValueError, "Node size vector not the same size as the number of nodes.");
+ PyErr_SetString(PyExc_ValueError, "Membership fixed vector not the same size as the number of nodes.");
return NULL;
}
@@ -188,7 +188,7 @@ extern "C"
size_t nb_is_membership_fixed = PyList_Size(py_is_membership_fixed);
if (nb_is_membership_fixed != n)
{
- PyErr_SetString(PyExc_TypeError, "Node size vector not the same size as the number of nodes.");
+ PyErr_SetString(PyExc_TypeError, "Membership fixed vector not the same size as the number of nodes.");
return NULL;
}
@@ -270,7 +270,7 @@ extern "C"
size_t nb_is_membership_fixed = PyList_Size(py_is_membership_fixed);
if (nb_is_membership_fixed != n)
{
- PyErr_SetString(PyExc_TypeError, "Node size vector not the same size as the number of nodes.");
+ PyErr_SetString(PyExc_TypeError, "Membership fixed vector not the same size as the number of nodes.");
return NULL;
}
@@ -346,7 +346,7 @@ extern "C"
size_t nb_is_membership_fixed = PyList_Size(py_is_membership_fixed);
if (nb_is_membership_fixed != n)
{
- PyErr_SetString(PyExc_TypeError, "Node size vector not the same size as the number of nodes.");
+ PyErr_SetString(PyExc_TypeError, "Membership fixed vector not the same size as the number of nodes.");
return NULL;
}
View it on GitLab: https://salsa.debian.org/med-team/python-leidenalg/-/commit/de0c8afc403cc6a4aa9894621327344f4c47762e
--
View it on GitLab: https://salsa.debian.org/med-team/python-leidenalg/-/commit/de0c8afc403cc6a4aa9894621327344f4c47762e
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