1 files changed, 156 insertions, 0 deletions
diff --git a/src/go/doc/testdata/examples/issue43658.golden b/src/go/doc/testdata/examples/issue43658.golden
new file mode 100644
index 0000000..5200d14
--- /dev/null
+++ b/src/go/doc/testdata/examples/issue43658.golden
@@ -0,0 +1,156 @@
+-- Profile_simple.Play --
+package main
+
+import (
+	"fmt"
+	"log"
+	"sort"
+
+	"golang.org/x/exp/rand"
+
+	"gonum.org/v1/gonum/graph/community"
+	"gonum.org/v1/gonum/graph/internal/ordered"
+	"gonum.org/v1/gonum/graph/simple"
+)
+
+func main() {
+	// Profile calls Modularize which implements the Louvain modularization algorithm.
+	// Since this is a randomized algorithm we use a defined random source to ensure
+	// consistency between test runs. In practice, results will not differ greatly
+	// between runs with different PRNG seeds.
+	src := rand.NewSource(1)
+
+	// Create dumbell graph:
+	//
+	//  0       4
+	//  |\     /|
+	//  | 2 - 3 |
+	//  |/     \|
+	//  1       5
+	//
+	g := simple.NewUndirectedGraph()
+	for u, e := range smallDumbell {
+		for v := range e {
+			g.SetEdge(simple.Edge{F: simple.Node(u), T: simple.Node(v)})
+		}
+	}
+
+	// Get the profile of internal node weight for resolutions
+	// between 0.1 and 10 using logarithmic bisection.
+	p, err := community.Profile(
+		community.ModularScore(g, community.Weight, 10, src),
+		true, 1e-3, 0.1, 10,
+	)
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	// Print out each step with communities ordered.
+	for _, d := range p {
+		comm := d.Communities()
+		for _, c := range comm {
+			sort.Sort(ordered.ByID(c))
+		}
+		sort.Sort(ordered.BySliceIDs(comm))
+		fmt.Printf("Low:%.2v High:%.2v Score:%v Communities:%v Q=%.3v\n",
+			d.Low, d.High, d.Score, comm, community.Q(g, comm, d.Low))
+	}
+
+}
+
+// intset is an integer set.
+type intset map[int]struct{}
+
+func linksTo(i ...int) intset {
+	if len(i) == 0 {
+		return nil
+	}
+	s := make(intset)
+	for _, v := range i {
+		s[v] = struct{}{}
+	}
+	return s
+}
+
+var smallDumbell = []intset{
+	0: linksTo(1, 2),
+	1: linksTo(2),
+	2: linksTo(3),
+	3: linksTo(4, 5),
+	4: linksTo(5),
+	5: nil,
+}
+
+-- Profile_simple.Output --
+Low:0.1 High:0.29 Score:14 Communities:[[0 1 2 3 4 5]] Q=0.9
+Low:0.29 High:2.3 Score:12 Communities:[[0 1 2] [3 4 5]] Q=0.714
+Low:2.3 High:3.5 Score:4 Communities:[[0 1] [2] [3] [4 5]] Q=-0.31
+Low:3.5 High:10 Score:0 Communities:[[0] [1] [2] [3] [4] [5]] Q=-0.607
+
+-- Profile_multiplex.Play --
+
+package main
+
+import (
+	"fmt"
+	"log"
+	"sort"
+
+	"golang.org/x/exp/rand"
+
+	"gonum.org/v1/gonum/graph/community"
+	"gonum.org/v1/gonum/graph/internal/ordered"
+	"gonum.org/v1/gonum/graph/simple"
+)
+
+var friends, enemies *simple.WeightedUndirectedGraph
+
+func main() {
+	// Profile calls ModularizeMultiplex which implements the Louvain modularization
+	// algorithm. Since this is a randomized algorithm we use a defined random source
+	// to ensure consistency between test runs. In practice, results will not differ
+	// greatly between runs with different PRNG seeds.
+	src := rand.NewSource(1)
+
+	// The undirected graphs, friends and enemies, are the political relationships
+	// in the Middle East as described in the Slate article:
+	// http://www.slate.com/blogs/the_world_/2014/07/17/the_middle_east_friendship_chart.html
+	g, err := community.NewUndirectedLayers(friends, enemies)
+	if err != nil {
+		log.Fatal(err)
+	}
+	weights := []float64{1, -1}
+
+	// Get the profile of internal node weight for resolutions
+	// between 0.1 and 10 using logarithmic bisection.
+	p, err := community.Profile(
+		community.ModularMultiplexScore(g, weights, true, community.WeightMultiplex, 10, src),
+		true, 1e-3, 0.1, 10,
+	)
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	// Print out each step with communities ordered.
+	for _, d := range p {
+		comm := d.Communities()
+		for _, c := range comm {
+			sort.Sort(ordered.ByID(c))
+		}
+		sort.Sort(ordered.BySliceIDs(comm))
+		fmt.Printf("Low:%.2v High:%.2v Score:%v Communities:%v Q=%.3v\n",
+			d.Low, d.High, d.Score, comm, community.QMultiplex(g, comm, weights, []float64{d.Low}))
+	}
+
+}
+-- Profile_multiplex.Output --
+Low:0.1 High:0.72 Score:26 Communities:[[0] [1 7 9 12] [2 8 11] [3 4 5 10] [6]] Q=[24.7 1.97]
+Low:0.72 High:1.1 Score:24 Communities:[[0 6] [1 7 9 12] [2 8 11] [3 4 5 10]] Q=[16.9 14.1]
+Low:1.1 High:1.2 Score:18 Communities:[[0 2 6 11] [1 7 9 12] [3 4 5 8 10]] Q=[9.16 25.1]
+Low:1.2 High:1.6 Score:10 Communities:[[0 3 4 5 6 10] [1 7 9 12] [2 8 11]] Q=[10.5 26.7]
+Low:1.6 High:1.6 Score:8 Communities:[[0 1 6 7 9 12] [2 8 11] [3 4 5 10]] Q=[5.56 39.8]
+Low:1.6 High:1.8 Score:2 Communities:[[0 2 3 4 5 6 10] [1 7 8 9 11 12]] Q=[-1.82 48.6]
+Low:1.8 High:2.3 Score:-6 Communities:[[0 2 3 4 5 6 8 10 11] [1 7 9 12]] Q=[-5 57.5]
+Low:2.3 High:2.4 Score:-10 Communities:[[0 1 2 6 7 8 9 11 12] [3 4 5 10]] Q=[-11.2 79]
+Low:2.4 High:4.3 Score:-52 Communities:[[0 1 2 3 4 5 6 7 8 9 10 11 12]] Q=[-46.1 117]
+Low:4.3 High:10 Score:-54 Communities:[[0 1 2 3 4 6 7 8 9 10 11 12] [5]] Q=[-82 254]