func TestRematchPointersToClusters(t *testing.T) {
c := RematchPointersToClusters([]*clustering.Cluster{}, []geo.Pointer{}, clustering.CentroidGeoDistance{}, 30)
if c == nil {
t.Errorf("result should not be nil")
}
if len(c) != 0 {
t.Errorf("zero cluster input should result in zero cluster output")
}
testClusters := []*clustering.Cluster{
clustering.NewClusterWithCentroid(geo.NewPoint(1, 1)),
clustering.NewClusterWithCentroid(geo.NewPoint(2, 2)),
}
testPointers := []geo.Pointer{
&event{Location: geo.NewPoint(1, 1)},
&event{Location: geo.NewPoint(1, 1)},
&event{Location: geo.NewPoint(2, 2)},
&event{Location: geo.NewPoint(3, 3)},
}
c = RematchPointersToClusters(testClusters, testPointers, clustering.CentroidDistance{}, 1)
if l := len(c[0].Pointers); l != 2 {
t.Errorf("wrong number of pointers, got %d", l)
}
if l := len(c[1].Pointers); l != 1 {
t.Errorf("wrong number of pointers, got %d", l)
}
c = RematchPointersToClusters(testClusters, testPointers, clustering.CentroidDistance{}, 2)
if l := len(c[0].Pointers); l != 2 {
t.Errorf("wrong number of pointers, got %d", l)
}
if l := len(c[1].Pointers); l != 2 {
t.Errorf("wrong number of pointers, got %d", l)
}
}
// RematchPointersToClusters will take a set of pointers and map them to the closest cluster.
// Basically creates a new cluster from that one point and does the ClusterDistance between them.
// Will return a new list.
func RematchPointersToClusters(
clusters []*clustering.Cluster,
pointers []geo.Pointer,
distancer clustering.ClusterDistancer,
threshold float64,
) []*clustering.Cluster {
if len(clusters) == 0 {
return []*clustering.Cluster{}
}
newClusters := make([]*clustering.Cluster, 0, len(clusters))
// clear the current members
for _, c := range clusters {
newClusters = append(newClusters, clustering.NewClusterWithCentroid(c.Centroid))
}
// remap all the groupers to these new groups
for _, pointer := range pointers {
minDist := math.MaxFloat64
index := 0
pointerCluster := clustering.NewCluster(pointer)
// find the closest group
for i, c := range newClusters {
if d := distancer.ClusterDistance(c, pointerCluster); d < minDist {
minDist = d
index = i
}
}
if minDist < threshold {
// leaves the center as found by the previous clustering
newClusters[index].Pointers = append(newClusters[index].Pointers, pointer)
}
}
return newClusters
}