chore: Update vendored sources to igraph/igraph@bd9306d

chore: improve changelog
fix: eigenvector centralization now always assumes scaled vertex-level centrality scores
doc: more cross-linking for harmonic centrality
doc: add reference to betweenness docs
ci: apt-get update to work around outdated index
ci: test with clang 20
doc: doc cleanup in centralization functions
refactor: minor cleanup / IDE-friendliness for community_to_membership()
ci: re-enable travis on ppc64 / s390x

src/vendor/cigraph/.travis.yml

@@ -76,17 +76,17 @@ jobs:
         - mkdir build && cd build
         - cmake .. -DIGRAPH_USE_INTERNAL_BLAS=OFF -DIGRAPH_USE_INTERNAL_LAPACK=OFF -DIGRAPH_USE_INTERNAL_ARPACK=OFF -DIGRAPH_USE_INTERNAL_GLPK=OFF -DIGRAPH_USE_INTERNAL_GMP=OFF -DIGRAPH_VERIFY_FINALLY_STACK=OFF -DCMAKE_BUILD_TYPE=Debug -DIGRAPH_PRINT_ARITH_HEADER=ON -DUSE_SANITIZER=Address
 
-    # - name: "Linux ppc64"
-    #   os: linux
-    #   arch: ppc64le
+    - name: "Linux ppc64"
+      os: linux
+      arch: ppc64le
 
-    # - name: "Linux s390x"
-    #   os: linux
-    #   arch: s390x
-    #   # Do not enable ASan, as it leads to linking errors.
-    #   before_script:
-    #     - mkdir build && cd build
-    #     - cmake .. -DIGRAPH_USE_INTERNAL_BLAS=ON -DIGRAPH_USE_INTERNAL_LAPACK=ON -DIGRAPH_USE_INTERNAL_ARPACK=ON -DIGRAPH_USE_INTERNAL_GLPK=ON -DIGRAPH_USE_INTERNAL_GMP=ON -DIGRAPH_VERIFY_FINALLY_STACK=ON -DCMAKE_BUILD_TYPE=Debug -DIGRAPH_PRINT_ARITH_HEADER=ON
+    - name: "Linux s390x"
+      os: linux
+      arch: s390x
+      # Do not enable ASan, as it leads to linking errors.
+      before_script:
+        - mkdir build && cd build
+        - cmake .. -DIGRAPH_USE_INTERNAL_BLAS=ON -DIGRAPH_USE_INTERNAL_LAPACK=ON -DIGRAPH_USE_INTERNAL_ARPACK=ON -DIGRAPH_USE_INTERNAL_GLPK=ON -DIGRAPH_USE_INTERNAL_GMP=ON -DIGRAPH_VERIFY_FINALLY_STACK=ON -DCMAKE_BUILD_TYPE=Debug -DIGRAPH_PRINT_ARITH_HEADER=ON
 
 #notifications:
 #  email:

src/vendor/cigraph/CHANGELOG.md

@@ -17,6 +17,7 @@
 
  - `igraph_feedback_arc_set()` uses a much faster method for solving the exact minimum feedback arc set problem. The new method (`IGRAPH_FAS_EXACT_IP_CG`) is used by default (i.e. with `IGRAPH_FAS_EXACT_IP`), but the previous method is also kept available (`IGRAPH_FAS_EXACT_IP_TI`).
  - `igraph_motifs_randesu()`, `igraph_motifs_randesu_callback()`, `igraph_motifs_randesu_estimate()` and `igraph_motifs_randesu_no()` now accept `NULL` for their `cut_prob` parameter, signifying that a complete search should be performed.
+ - `igraph_centralization_eigenvector_centrality_tmax()` and `igraph_centralization_eigenvector_centrality()` cannot produce meaningful results without normalizing vertex-level eigenvector centrality in a well-defined way. This was not the case when using `scale=false`. These functions now ignore the value of the `scale` parameter and always scale vertex-level centrality scores to have a maximum of 1. If you require a different type of normalization for the vertex-level eigenvector centrality scores, perform this normalization manually, and call `igraph_centralization()` to compute the centralization.
 
 ### Fixed
 

src/vendor/cigraph/azure-pipelines.yml

@@ -14,7 +14,9 @@ jobs:
   # In this test we install and generate locales so that igraph_enter/exit_safelocale() can be tested
   - job: linux_static_vendored
     steps:
-      - script: sudo apt-get install ninja-build ccache language-pack-de -y
+      - script: |
+          sudo apt-get update
+          sudo apt-get install ninja-build ccache language-pack-de -y
         displayName: Install dependencies
 
       - script: |
@@ -75,19 +77,19 @@ jobs:
           extra_cmake_args: '-DBLA_VENDOR=OpenBLAS'
           build_shared: true
 
-  - job: linux_clang_19
+  - job: linux_clang_20
     steps:
       - script: |
           sudo apt-get install ninja-build ccache -y
           wget https://apt.llvm.org/llvm.sh
           chmod +x llvm.sh
-          sudo ./llvm.sh 19
+          sudo ./llvm.sh 20
         displayName: Install dependencies
 
       - template: .azure/build.yml
         parameters:
           build_type: Debug
-          extra_cmake_args: '-DUSE_SANITIZER=Address\;Undefined -DCMAKE_C_FLAGS="-Og -fno-sanitize-recover=undefined -fno-sanitize=float-divide-by-zero" -DCMAKE_CXX_FLAGS="-Og -fno-sanitize-recover=undefined -fno-sanitize=float-divide-by-zero" -DCMAKE_C_COMPILER=clang-19  -DCMAKE_CXX_COMPILER=clang++-19'
+          extra_cmake_args: '-DUSE_SANITIZER=Address\;Undefined -DCMAKE_C_FLAGS="-Og -fno-sanitize-recover=undefined -fno-sanitize=float-divide-by-zero" -DCMAKE_CXX_FLAGS="-Og -fno-sanitize-recover=undefined -fno-sanitize=float-divide-by-zero" -DCMAKE_C_COMPILER=clang-20  -DCMAKE_CXX_COMPILER=clang++-20'
 
   - job: linux_x87
     steps:

src/vendor/cigraph/src/centrality/betweenness.c

@@ -461,6 +461,14 @@ static igraph_error_t igraph_i_betweenness_check_weights(
  * vertices, the value of these geodesics are weighted by one over the
  * number of geodesics.
  *
+ * </para><para>
+ * Reference:
+ *
+ * </para><para>
+ * Ulrik Brandes: A faster algorithm for betweenness centrality.
+ * The Journal of Mathematical Sociology, 25(2), 163–177 (2001).
+ * https://doi.org/10.1080/0022250X.2001.9990249
+ *
  * \param graph The graph object.
  * \param res The result of the computation, a vector containing the
  *        betweenness scores for the specified vertices.
@@ -695,6 +703,14 @@ igraph_error_t igraph_betweenness_cutoff(const igraph_t *graph, igraph_vector_t
  * vertices, the value of these geodesics are weighted by one over the
  * number of geodesics.
  *
+ * </para><para>
+ * Reference:
+ *
+ * </para><para>
+ * Ulrik Brandes: A faster algorithm for betweenness centrality.
+ * The Journal of Mathematical Sociology, 25(2), 163–177 (2001).
+ * https://doi.org/10.1080/0022250X.2001.9990249
+ *
  * \param graph The graph object.
  * \param result The result of the computation, vector containing the
  *        betweenness scores for the edges.

src/vendor/cigraph/src/centrality/centralization.c

@@ -168,15 +168,15 @@ igraph_error_t igraph_centralization_degree(const igraph_t *graph, igraph_vector
  *
  * </para><para>
  * There are two ways to call this function, the first is to supply a
- * graph as the <code>graph</code> argument, and then the number of
+ * graph as the \p graph argument, and then the number of
  * vertices is taken from this object, and its directedness is
- * considered as well. The <code>nodes</code> argument is ignored in
- * this case. The <code>mode</code> argument is also ignored if the
+ * considered as well. The \p nodes argument is ignored in
+ * this case. The \p mode argument is also ignored if the
  * supplied graph is undirected.
  *
  * </para><para>
- * The other way is to supply a null pointer as the <code>graph</code>
- * argument. In this case the <code>nodes</code> and <code>mode</code>
+ * The other way is to supply a null pointer as the \p graph
+ * argument. In this case the \p nodes and \p mode
  * arguments are considered.
  *
  * </para><para>
@@ -187,11 +187,11 @@ igraph_error_t igraph_centralization_degree(const igraph_t *graph, igraph_vector
  * \param graph A graph object or a null pointer, see the description
  *     above.
  * \param nodes The number of nodes. This is ignored if the
- *     <code>graph</code> argument is not a null pointer.
+ *     \p graph argument is not a null pointer.
  * \param mode Constant, whether the calculation is based on in-degree
- *     (<code>IGRAPH_IN</code>), out-degree (<code>IGRAPH_OUT</code>)
- *     or total degree (<code>IGRAPH_ALL</code>). This is ignored if
- *     the <code>graph</code> argument is not a null pointer and the
+ *     (\c IGRAPH_IN), out-degree (\c IGRAPH_OUT)
+ *     or total degree (\c IGRAPH_ALL). This is ignored if
+ *     the \p graph argument is not a null pointer and the
  *     given graph is undirected.
  * \param loops Boolean scalar, whether to consider loop edges in the
  *     calculation.
@@ -324,15 +324,15 @@ igraph_error_t igraph_centralization_betweenness(const igraph_t *graph,
  *
  * </para><para>
  * There are two ways to call this function, the first is to supply a
- * graph as the <code>graph</code> argument, and then the number of
+ * graph as the \p graph argument, and then the number of
  * vertices is taken from this object, and its directedness is
- * considered as well. The <code>nodes</code> argument is ignored in
- * this case. The <code>directed</code> argument is also ignored if the
+ * considered as well. The \p nodes argument is ignored in
+ * this case. The \p directed argument is also ignored if the
  * supplied graph is undirected.
  *
  * </para><para>
- * The other way is to supply a null pointer as the <code>graph</code>
- * argument. In this case the <code>nodes</code> and <code>directed</code>
+ * The other way is to supply a null pointer as the \p graph
+ * argument. In this case the \p nodes and \p directed
  * arguments are considered.
  *
  * </para><para>
@@ -341,10 +341,10 @@ igraph_error_t igraph_centralization_betweenness(const igraph_t *graph,
  * \param graph A graph object or a null pointer, see the description
  *     above.
  * \param nodes The number of nodes. This is ignored if the
- *     <code>graph</code> argument is not a null pointer.
+ *     \p graph argument is not a null pointer.
  * \param directed Boolean scalar, whether to use directed paths in
  *     the betweenness calculation. This argument is ignored if
- *     <code>graph</code> is not a null pointer and it is undirected.
+ *     \p graph is not a null pointer and it is undirected.
  * \param res Pointer to a real variable, the result is stored here.
  * \return Error code.
  *
@@ -455,27 +455,28 @@ igraph_error_t igraph_centralization_closeness(const igraph_t *graph,
  *
  * </para><para>
  * There are two ways to call this function, the first is to supply a
- * graph as the <code>graph</code> argument, and then the number of
+ * graph as the \p graph argument, and then the number of
  * vertices is taken from this object, and its directedness is
- * considered as well. The <code>nodes</code> argument is ignored in
- * this case. The <code>mode</code> argument is also ignored if the
+ * considered as well. The \p nodes argument is ignored in
+ * this case. The \p mode argument is also ignored if the
  * supplied graph is undirected.
  *
  * </para><para>
- * The other way is to supply a null pointer as the <code>graph</code>
- * argument. In this case the <code>nodes</code> and <code>mode</code>
+ * The other way is to supply a null pointer as the \p graph
+ * argument. In this case the \p nodes and \p mode
  * arguments are considered.
  *
  * </para><para>
  * The most centralized structure is the star.
+ *
  * \param graph A graph object or a null pointer, see the description
  *     above.
  * \param nodes The number of nodes. This is ignored if the
- *     <code>graph</code> argument is not a null pointer.
- * \param mode Constant, specifies what kinf of distances to consider
- *     to calculate closeness. See the <code>mode</code> argument of
+ *     \p graph argument is not a null pointer.
+ * \param mode Constant, specifies what kind of distances to consider
+ *     to calculate closeness. See the \p mode argument of
  *     \ref igraph_closeness() for details. This argument is ignored
- *     if <code>graph</code> is not a null pointer and it is
+ *     if \p graph is not a null pointer and it is
  *     undirected.
  * \param res Pointer to a real variable, the result is stored here.
  * \return Error code.
@@ -518,13 +519,26 @@ igraph_error_t igraph_centralization_closeness_tmax(const igraph_t *graph,
  * by passing its arguments to \ref igraph_eigenvector_centrality);
  * and it calculates the graph level centralization index based on the
  * results by calling \ref igraph_centralization().
+ *
+ * </para><para>
+ * Note that vertex-level eigenvector centrality scores do not have
+ * a natural scale. As with any eigenvector, their interpretation is
+ * invariant to scaling by a constant factor. However, due to how
+ * graph-level \em centralization is defined, its value depends on the
+ * specific scale/normalization used for vertex-level scores. This is
+ * true even when the graph-level centralization itself is normalized
+ * by its theoretical maximum value. This function makes the specific
+ * choice of scaling vertex-level centrality scores by their maximum
+ * (i.e. it uses the ∞-norm). Other normalization choices, such as the
+ * 1-norm or 2-norm are not currently implemented.
+ *
  * \param graph The input graph.
  * \param vector A vector if you need the node-level eigenvector
  *      centrality scores, or a null pointer otherwise.
  * \param value If not a null pointer, then the leading eigenvalue is
  *      stored here.
- * \param scale If not zero then the result will be scaled, such that
- *     the absolute value of the maximum centrality is one.
+ * \param scale This parameter is deprecated and ignored since igraph 0.10.14.
+ *     Vertex-level centrality scores are always scaled to have a maximum of one.
  * \param options Options to ARPACK. See \ref igraph_arpack_options_t
  *    for details. Note that the function overwrites the
  *    <code>n</code> (number of vertices) parameter and
@@ -564,6 +578,14 @@ igraph_error_t igraph_centralization_eigenvector_centrality(
     igraph_real_t realvalue, *myvalue = value;
     igraph_real_t *tmax = theoretical_max, mytmax;
 
+    if (! scale) {
+        scale = true;
+        IGRAPH_WARNING("Computing eigenvector centralization requires normalized "
+                       "eigenvector centrality scores. Normalizing eigenvector centralities "
+                       "by their maximum even though 'scale=false' was requested. The 'scale' "
+                       "parameter will be removed in the future.");
+    }
+
     if (!tmax) {
         tmax = &mytmax;
     }
@@ -604,28 +626,42 @@ igraph_error_t igraph_centralization_eigenvector_centrality(
  *
  * </para><para>
  * There are two ways to call this function, the first is to supply a
- * graph as the <code>graph</code> argument, and then the number of
+ * graph as the \p graph argument, and then the number of
  * vertices is taken from this object, and its directedness is
- * considered as well. The <code>nodes</code> argument is ignored in
- * this case. The <code>directed</code> argument is also ignored if the
+ * considered as well. The \p nodes argument is ignored in
+ * this case. The \p directed argument is also ignored if the
  * supplied graph is undirected.
  *
  * </para><para>
- * The other way is to supply a null pointer as the <code>graph</code>
- * argument. In this case the <code>nodes</code> and <code>directed</code>
+ * The other way is to supply a null pointer as the \p graph
+ * argument. In this case the \p nodes and \p directed
  * arguments are considered.
  *
  * </para><para>
  * The most centralized directed structure is the in-star. The most
  * centralized undirected structure is the graph with a single edge.
+ *
+ * </para><para>
+ * Note that vertex-level eigenvector centrality scores do not have
+ * a natural scale. As with any eigenvector, their interpretation is
+ * invariant to scaling by a constant factor. However, due to how
+ * graph-level \em centralization is defined, its value depends on the
+ * specific scale/normalization used for vertex-level scores. This is
+ * true even when the graph-level centralization itself is normalized
+ * by its theoretical maximum value. This function makes the specific
+ * choice of scaling vertex-level centrality scores by their maximum
+ * (i.e. it uses the ∞-norm). Other normalization choices, such as the
+ * 1-norm or 2-norm are not currently implemented.
+ *
  * \param graph A graph object or a null pointer, see the description
  *     above.
  * \param nodes The number of nodes. This is ignored if the
- *     <code>graph</code> argument is not a null pointer.
+ *     \p graph argument is not a null pointer.
  * \param directed Boolean scalar, whether to consider edge
  *     directions. This argument is ignored if
- *     <code>graph</code> is not a null pointer and it is undirected.
- * \param scale Whether to rescale the node-level centrality scores to
+ *     \p graph is not a null pointer and it is undirected.
+ * \param scale This parameter is deprecated and ignored since igraph 0.10.14.
+ *     Vertex-level centrality scores are always assumed to be scaled to
  *     have a maximum of one.
  * \param res Pointer to a real variable, the result is stored here.
  * \return Error code.
@@ -643,6 +679,15 @@ igraph_error_t igraph_centralization_eigenvector_centrality_tmax(
     igraph_bool_t scale,
     igraph_real_t *res) {
 
+    if (! scale) {
+        scale = true;
+        IGRAPH_WARNING("Theoretical maximum for eigenvector centralization can "
+                       "only be computed with normalized eigenvector centrality "
+                       "scores. Assuming that eigenvector centralities are normalized "
+                       "by their maximum even though 'scale=false' was passed. The 'scale' "
+                       "parameter will be removed in the future.");
+    }
+
     if (graph) {
         nodes = igraph_vcount(graph);
         directed = directed && igraph_is_directed(graph);

src/vendor/cigraph/src/centrality/closeness.c

@@ -719,7 +719,8 @@ static igraph_error_t igraph_i_harmonic_centrality_weighted(const igraph_t *grap
  * and |E| is the number of edges in the graph. The timing decreases with smaller
  * cutoffs in a way that depends on the graph structure.
  *
- * \sa Other centrality types: \ref igraph_closeness(), \ref igraph_betweenness().
+ * \sa \ref igraph_harmonic_centrality() to calculate the exact harmonic centrality.
+ * Other centrality types: \ref igraph_closeness(), \ref igraph_betweenness().
  */
 
 igraph_error_t igraph_harmonic_centrality_cutoff(const igraph_t *graph, igraph_vector_t *res,