fix: guard optimize_refine_core against float32 noise oscillation

.github/workflows/ci_checks.yml

@@ -26,7 +26,7 @@ jobs:
         python -m pip install --upgrade pip
         python -m pip install flake8
         python -m pip install -r requirements_dev.txt
-        python setup.py develop
+        pip install -e .
     - name: Test with pytest
       run: |
         py.test --doctest-modules --cov-report=xml --cov=sknetwork

.github/workflows/wheels_build.yml

@@ -23,6 +23,8 @@ jobs:
           CIBW_SKIP: cp*-musllinux* *-win32
           CIBW_ARCHS_MACOS: x86_64 arm64
           CIBW_BUILD_VERBOSITY: 3
+          CIBW_MANYLINUX_AARCH64_IMAGE: manylinux_2_28
+          CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28
           CIBW_BEFORE_BUILD: "pip install -r requirements_dev.txt && pip install ."
           CIBW_BUILD: cp310-* cp311-* cp312-* cp313-* cp314-*
 

sknetwork/clustering/leiden.py

@@ -163,7 +163,7 @@ def _optimize_refine(self, labels, adjacency, out_weights, in_weights):
         labels_refined = np.arange(len(labels)).astype(np.int32)
         return optimize_refine_core(labels, labels_refined, indices, indptr, data, out_weights, in_weights,
                                     out_cluster_weights, in_cluster_weights, cluster_weights, self_loops,
-                                    self.resolution)
+                                    self.resolution, self.tol_optimization)
 
     @staticmethod
     def _aggregate_refine(labels, labels_refined, adjacency, out_weights, in_weights):

sknetwork/clustering/leiden_core.pyx

@@ -13,7 +13,8 @@ ctypedef fused int_or_long:
 @cython.wraparound(False)
 def optimize_refine_core(int_or_long[:] labels, int_or_long[:] labels_refined, int_or_long[:] indices,
     int_or_long[:] indptr, float[:] data, float[:] out_weights, float[:] in_weights, float[:] out_cluster_weights,
-    float[:] in_cluster_weights, float[:] cluster_weights, float[:] self_loops, float resolution):  # pragma: no cover
+    float[:] in_cluster_weights, float[:] cluster_weights, float[:] self_loops, float resolution,
+    float tol_optimization):  # pragma: no cover
     """Refine clusters while maximizing modularity.
 
     Parameters
@@ -42,6 +43,8 @@ def optimize_refine_core(int_or_long[:] labels, int_or_long[:] labels_refined, i
         Weights of self loops.
     resolution :
         Resolution parameter (positive).
+    tol_optimization :
+        Minimum increase in modularity to enter a new optimization pass.
 
     Returns
     -------
@@ -102,7 +105,7 @@ def optimize_refine_core(int_or_long[:] labels, int_or_long[:] labels_refined, i
                     delta_local -= resolution * out_weight * in_cluster_weights[label_target]
                     delta_local -= resolution * in_weight * out_cluster_weights[label_target]
                     delta_local -= delta
-                    if delta_local > 0:
+                    if delta_local > tol_optimization:
                         label_target_set.insert(label_target)
                     cluster_weights[label_target] = 0