fix: based on PR comments and reference updated

Author: BeaMarton13

src/_igraph/graphobject.c

@@ -13748,6 +13748,38 @@ PyObject *igraphmodule_Graph_community_leiden(igraphmodule_GraphObject *self,
   return error ? NULL : Py_BuildValue("Nd", res, (double) quality);
 }
 
+ /**
+ * Fluid communities
+ */
+PyObject *igraphmodule_Graph_community_fluid_communities(igraphmodule_GraphObject *self,
+                                                        PyObject *args, PyObject *kwds) {
+    static char *kwlist[] = {"no_of_communities", NULL};
+    Py_ssize_t no_of_communities;
+    igraph_vector_int_t membership;
+    PyObject *result;
+
+    // Parse the Python integer argument
+    if (!PyArg_ParseTupleAndKeywords(args, kwds, "n", kwlist, &no_of_communities)) {
+        return NULL;
+    }
+
+    if (igraph_vector_int_init(&membership, 0)) {
+        igraphmodule_handle_igraph_error();
+        return NULL;
+    }
+
+    if (igraph_community_fluid_communities(&self->g, no_of_communities, &membership)) {
+        igraphmodule_handle_igraph_error();
+        igraph_vector_int_destroy(&membership);
+        return NULL;
+    }
+
+    result = igraphmodule_vector_int_t_to_PyList(&membership);
+    igraph_vector_int_destroy(&membership);
+
+    return result;
+}
+
 /**********************************************************************
  * Random walks                                                       *
  **********************************************************************/
@@ -13895,42 +13927,6 @@ PyObject *igraphmodule_Graph_random_walk(igraphmodule_GraphObject * self,
   }
 }
 
-/**********************************************************************
- * Other methods                                                      *
- **********************************************************************/
-
- /**
- * Fluid communities
- */
-PyObject *igraphmodule_Graph_community_fluid_communities(igraphmodule_GraphObject *self,
-                                                        PyObject *args, PyObject *kwds) {
-    static char *kwlist[] = {"no_of_communities", NULL};
-    Py_ssize_t no_of_communities;
-    igraph_vector_int_t membership;
-    PyObject *result;
-
-    // Parse the Python integer argument
-    if (!PyArg_ParseTupleAndKeywords(args, kwds, "n", kwlist, &no_of_communities)) {
-        return NULL;
-    }
-
-    if (igraph_vector_int_init(&membership, 0)) {
-        igraphmodule_handle_igraph_error();
-        return NULL;
-    }
-
-    if (igraph_community_fluid_communities(&self->g, no_of_communities, &membership)) {
-        igraphmodule_handle_igraph_error();
-        igraph_vector_int_destroy(&membership);
-        return NULL;
-    }
-
-    result = igraphmodule_vector_int_t_to_PyList(&membership);
-    igraph_vector_int_destroy(&membership);
-
-    return result;
-}
-
 /**********************************************************************
  * Special internal methods that you won't need to mess around with   *
  **********************************************************************/
@@ -18435,28 +18431,25 @@ struct PyMethodDef igraphmodule_Graph_methods[] = {
    "\n"
    "@see: modularity()\n"
   },
-  {"community_fluid_communities", 
-    (PyCFunction) igraphmodule_Graph_community_fluid_communities,
-    METH_VARARGS | METH_KEYWORDS,
-    "community_fluid_communities(no_of_communities)\n--\n\n"
-    "Community detection based on fluids interacting on the graph.\n\n"
-    "The algorithm is based on the simple idea of several fluids interacting\n"
-    "in a non-homogeneous environment (the graph topology), expanding and\n"
-    "contracting based on their interaction and density. Weighted graphs are\n"
-    "not supported.\n\n"
-    "This function implements the community detection method described in:\n"
-    "Parés F, Gasulla DG, et. al. (2018) Fluid Communities: A Competitive,\n"
-    "Scalable and Diverse Community Detection Algorithm. In: Complex Networks\n"
-    "& Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth\n"
-    "International Conference on Complex Networks and Their Applications),\n"
-    "Springer, vol 689, p 229. https://doi.org/10.1007/978-3-319-72150-7_19\n\n"
-    "@param no_of_communities: The number of communities to be found. Must be\n"
-    " greater than 0 and fewer than number of vertices in the graph.\n"
-    "@return: a list with the community membership of each vertex.\n"
-    "@note: The graph must be simple and connected. Edge directions will be\n"
-    " ignored if the graph is directed.\n"
-    "@note: Time complexity: O(|E|)\n"
-  },
+  {"community_fluid_communities",(PyCFunction) igraphmodule_Graph_community_fluid_communities,METH_VARARGS | METH_KEYWORDS,
+   "community_fluid_communities(no_of_communities)\n--\n\n"
+   "Community detection based on fluids interacting on the graph.\n\n"
+   "The algorithm is based on the simple idea of several fluids interacting\n"
+   "in a non-homogeneous environment (the graph topology), expanding and\n"
+   "contracting based on their interaction and density. Weighted graphs are\n"
+   "not supported.\n\n"
+   "B{Reference}\n\n"
+   "  - Parés F, Gasulla DG, et. al. (2018) Fluid Communities: A Competitive,\n"
+   "    Scalable and Diverse Community Detection Algorithm. In: Complex Networks\n"
+   "    & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth\n"
+   "    International Conference on Complex Networks and Their Applications),\n"
+   "    Springer, vol 689, p 229. https://doi.org/10.1007/978-3-319-72150-7_19\n\n"
+   "@param no_of_communities: The number of communities to be found. Must be\n"
+   " greater than 0 and fewer than number of vertices in the graph.\n"
+   "@return: a list with the community membership of each vertex.\n"
+   "@note: The graph must be simple and connected. Edge directions will be\n"
+   " ignored if the graph is directed.\n"
+   "@note: Time complexity: O(|E|)\n",
   {"community_infomap",
    (PyCFunction) igraphmodule_Graph_community_infomap,
    METH_VARARGS | METH_KEYWORDS,
@@ -18465,7 +18458,7 @@ struct PyMethodDef igraphmodule_Graph_methods[] = {
    "method of Martin Rosvall and Carl T. Bergstrom.\n\n"
    "See U{https://www.mapequation.org} for a visualization of the algorithm\n"
    "or one of the references provided below.\n"
-   "B{References}\n"
+   "B{Reference}: "
    "  - M. Rosvall and C. T. Bergstrom: I{Maps of information flow reveal\n"
    "    community structure in complex networks}. PNAS 105, 1118 (2008).\n"
    "    U{https://arxiv.org/abs/0707.0609}\n"