Esempio n. 1
0
func TestClustererUniformVectors(t *testing.T) {
	//initilize data
	var numClusters = 2
	var numDataPoints = 8
	var dimensionality = 4
	data := make([][]float64, numDataPoints)
	for i := 0; i < numDataPoints; i++ {
		data[i] = make([]float64, dimensionality)
		for j := 0; j < dimensionality; j++ {
			data[i][j] = float64(i)
		}
	}

	//run test
	clusterer := clusterer.NewKMeansSimple(numClusters, data)
	clusterer.Run()
	var result = clusterer.GetCentroids()

	//Test Results
	if len(result) != numClusters {
		t.Errorf("Clusterer created %v clusters. When %v was input for k.", len(result), numClusters)
	}
	if len(result[0]) != dimensionality {
		t.Errorf("Cluster dimensionalioty of %v does not match the dimensionality of the input data, %v.", len(result[0]), dimensionality)
	}
	expectedResults := make([]float64, numClusters)
	expectedResults[0] = 1.5 // (0+1+2+3)/4 = 1.5
	expectedResults[1] = 5.5 //  (4+5+6+7)/4 = 5.5
	for i := 0; i < numClusters; i++ {
		for j := 0; j < dimensionality; j++ {
			if result[i][j] != expectedResults[i] {
				t.Errorf("Data did not cluster as expected. Data: %v, Clusters: %v. Failure at %v, %v.", data, result, i, j)
			}
		}
	}
}
Esempio n. 2
0
func NewKMeansSimple(k int, centroids [][]float64) types.Clusterer {
	return clusterer.NewKMeansSimple(k, centroids)
}