Test and document that weights=NULL is supported for unweighted graphs.

CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.14)
 
 project(scran_graph_cluster
-    VERSION 0.1.2
+    VERSION 0.1.3
     DESCRIPTION "Cluster cells using graph-based methods"
     LANGUAGES CXX)
 

include/scran_graph_cluster/cluster_leiden.hpp

@@ -85,6 +85,7 @@ struct ClusterLeidenResults {
  * @param graph An existing graph.
  * @param weights Pointer to an array of weights of length equal to the number of edges in `graph`. 
  * This should be in the same order as the edge list in `graph`.
+ * Alternatively `NULL`, if the graph is unweighted.
  * @param options Further options.
  * @param[out] output On output, this is filtered with the clustering results.
  * The input value is ignored, so this object can be re-used across multiple calls to `cluster_leiden()`.

include/scran_graph_cluster/cluster_multilevel.hpp

@@ -78,6 +78,7 @@ struct ClusterMultilevelResults {
  * @param graph An existing graph.
  * @param weights Pointer to an array of weights of length equal to the number of edges in `graph`. 
  * This should be in the same order as the edge list in `graph`.
+ * Alternatively `NULL`, if the graph is unweighted.
  * @param options Further options.
  * @param[out] output On output, this is filtered with the clustering results.
  * The input value is ignored, so this object can be re-used across multiple calls to `cluster_multilevel()`.

include/scran_graph_cluster/cluster_walktrap.hpp

@@ -74,6 +74,7 @@ struct ClusterWalktrapResults {
  * @param graph An existing graph.
  * @param weights Pointer to an array of weights of length equal to the number of edges in `graph`. 
  * This should be in the same order as the edge list in `graph`.
+ * Alternatively `NULL`, if the graph is unweighted.
  * @param options Further options.
  * @param[out] output On output, this is filtered with the clustering results.
  * The input value is ignored, so this object can be re-used across multiple calls to `cluster_walktrap()`.

tests/src/cluster_leiden.cpp

@@ -70,3 +70,16 @@ TEST(ClusterLeiden, Sanity) {
         validate(output.membership, nclusters);
     }
 }
+
+TEST(ClusterLeiden, Unweighted) {
+    auto mock = mock_clusters(899, 6);
+
+    scran_graph_cluster::ClusterLeidenResults output;
+    scran_graph_cluster::ClusterLeidenOptions opts;
+    scran_graph_cluster::cluster_leiden(mock.first.get(), NULL, opts, output);
+    EXPECT_EQ(output.membership.size(), 899);
+
+    opts.modularity = true;
+    scran_graph_cluster::cluster_leiden(mock.first.get(), NULL, opts, output);
+    EXPECT_EQ(output.membership.size(), 899);
+}

tests/src/cluster_multilevel.cpp

@@ -82,3 +82,12 @@ TEST(ClusterMultilevel, Sanity) {
     auto output = scran_graph_cluster::cluster_multilevel(mock.first, mock.second, opts);
     validate(output.membership, nclusters);
 }
+
+TEST(ClusterMultilevel, Unweighted) {
+    auto mock = mock_clusters(899, 6);
+
+    scran_graph_cluster::ClusterMultilevelResults output;
+    scran_graph_cluster::ClusterMultilevelOptions opts;
+    scran_graph_cluster::cluster_multilevel(mock.first.get(), NULL, opts, output);
+    EXPECT_EQ(output.membership.size(), 899);
+}

tests/src/cluster_walktrap.cpp

@@ -59,3 +59,12 @@ TEST(ClusterWalktrap, Sanity) {
     auto output = scran_graph_cluster::cluster_walktrap(mock.first, mock.second, opts);
     validate(output.membership, nclusters);
 }
+
+TEST(ClusterWalktrap, Unweighted) {
+    auto mock = mock_clusters(899, 6);
+
+    scran_graph_cluster::ClusterWalktrapResults output;
+    scran_graph_cluster::ClusterWalktrapOptions opts;
+    scran_graph_cluster::cluster_walktrap(mock.first.get(), NULL, opts, output);
+    EXPECT_EQ(output.membership.size(), 899);
+}