fix dbscan bug of task dispatch

csv_importer_test.go

@@ -29,9 +29,9 @@ func TestImportedLoadCorrectData(t *testing.T) {
 		f = "data/test.csv"
 		i = CsvImporter()
 		s = [][]float64{
-			[]float64{0.1, 0.2, 0.3},
-			[]float64{0.4, 0.5, 0.6},
-			[]float64{0.7, 0.8, 0.9},
+			{0.1, 0.2, 0.3},
+			{0.4, 0.5, 0.6},
+			{0.7, 0.8, 0.9},
 		}
 	)
 
@@ -41,7 +41,7 @@ func TestImportedLoadCorrectData(t *testing.T) {
 	}
 
 	if !fsliceEqual(d, s) {
-		t.Error("Imported data mismatch: %v vs %v\n", d, s)
+		t.Errorf("Imported data mismatch: %v vs %v\n", d, s)
 	}
 }
 

dbscan.go

@@ -11,16 +11,25 @@ type dbscanClusterer struct {
 	distance DistanceFunc
 
 	// slices holding the cluster mapping and sizes. Access is synchronized to avoid read during computation.
-	mu   sync.RWMutex
-	a, b []int
+	mu sync.RWMutex
+	// groups for dateset
+	a []int
+	b []int
 
 	// variables used for concurrent computation of nearest neighbours
-	l, s, o, f int
-	j          chan *rangeJob
-	m          *sync.Mutex
-	w          *sync.WaitGroup
-	r          *[]int
-	p          []float64
+	// dataset len
+	l int
+	// worker number
+	s int
+	// work number for per worker
+	f int
+	j chan *rangeJob
+	m *sync.Mutex
+	w *sync.WaitGroup
+	// current point near
+	r *[]int
+	// current point
+	p []float64
 
 	// visited points
 	v []bool
@@ -78,7 +87,6 @@ func (c *dbscanClusterer) Learn(data [][]float64) error {
 
 	c.l = len(data)
 	c.s = c.numWorkers()
-	c.o = c.s - 1
 	c.f = c.l / c.s
 
 	c.d = data
@@ -198,15 +206,14 @@ func (c *dbscanClusterer) nearest(p int, l *int, r *[]int) {
 	c.p = c.d[p]
 	c.r = r
 
-	c.w.Add(c.s)
-
 	for i := 0; i < c.l; i += c.f {
 		if c.l-i <= c.f {
-			b = c.l - 1
+			b = c.l
 		} else {
 			b = i + c.f
 		}
 
+		c.w.Add(1)
 		c.j <- &rangeJob{
 			a: i,
 			b: b,

dbscan_test.go

@@ -0,0 +1,72 @@
+package clusters
+
+import (
+	"reflect"
+	"testing"
+)
+
+func TestDBSCANCluster(t *testing.T) {
+	tests := []struct {
+		MinPts   int
+		Eps      float64
+		Points   [][]float64
+		Expected []int
+	}{
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}},
+			Expected: []int{1},
+		},
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}, {1.5}},
+			Expected: []int{1, 1},
+		},
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}, {1}},
+			Expected: []int{1, 1},
+		},
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}, {1}, {1}},
+			Expected: []int{1, 1, 1},
+		},
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}, {1.5}, {2}},
+			Expected: []int{1, 1, 1},
+		},
+		{
+			MinPts:   1,
+			Eps:      1,
+			Points:   [][]float64{{1}, {1.5}, {3}},
+			Expected: []int{1, 1, 2},
+		},
+		{
+			MinPts:   2,
+			Eps:      1,
+			Points:   [][]float64{{1}, {3}},
+			Expected: []int{-1, -1},
+		},
+	}
+	for _, test := range tests {
+		c, e := DBSCAN(test.MinPts, test.Eps, 0, EuclideanDistance)
+		if e != nil {
+			t.Errorf("Error initializing kmeans clusterer: %s\n", e.Error())
+		}
+
+		if e = c.Learn(test.Points); e != nil {
+			t.Errorf("Error learning data: %s\n", e.Error())
+		}
+
+		if !reflect.DeepEqual(c.Guesses(), test.Expected) {
+			t.Errorf("guesses does not match: %d vs %d\n", c.Guesses(), test.Expected)
+		}
+	}
+}

kmeans_test.go

@@ -4,7 +4,7 @@ import (
 	"testing"
 )
 
-func TestKmeansClusterNumerMatches(t *testing.T) {
+func TestKmeansClusterNumberMatches(t *testing.T) {
 	const (
 		C = 8
 	)