kmeans/kmeans_test.go

95 lines
2.0 KiB
Go

package kmeans
import (
"math/rand"
"testing"
"github.com/muesli/clusters"
)
var RANDOM_SEED = int64(42)
func TestNewErrors(t *testing.T) {
_, err := NewWithOptions(0.00, nil)
if err == nil {
t.Errorf("Expected invalid options to return an error, got nil")
}
_, err = NewWithOptions(1.00, nil)
if err == nil {
t.Errorf("Expected invalid options to return an error, got nil")
}
}
func TestPartitioningError(t *testing.T) {
km := New()
d := clusters.Observations{}
if _, err := km.Partition(d, 1); err == nil {
t.Errorf("Expected error partitioning with empty data set, got nil")
return
}
d = clusters.Observations{
clusters.Coordinates{
0.1,
0.1,
},
}
if _, err := km.Partition(d, 0); err == nil {
t.Errorf("Expected error partitioning with 0 clusters, got nil")
return
}
if _, err := km.Partition(d, 2); err == nil {
t.Errorf("Expected error partitioning with more clusters than data points, got nil")
return
}
}
func TestDimensions(t *testing.T) {
var d clusters.Observations
for x := 0; x < 255; x += 32 {
for y := 0; y < 255; y += 32 {
d = append(d, clusters.Coordinates{
float64(x) / 255.0,
float64(y) / 255.0,
})
}
}
k := 4
km := New()
clusters, err := km.Partition(d, k)
if err != nil {
t.Errorf("Unexpected error partitioning: %v", err)
return
}
if len(clusters) != k {
t.Errorf("Expected %d clusters, got: %d", k, len(clusters))
}
}
func benchmarkPartition(size, partitions int, b *testing.B) {
rand.Seed(RANDOM_SEED)
var d clusters.Observations
for i := 0; i < size; i++ {
d = append(d, clusters.Coordinates{
rand.Float64(),
rand.Float64(),
})
}
for j := 0; j < b.N; j++ {
km := New()
km.Partition(d, partitions)
}
}
func BenchmarkPartition32Points(b *testing.B) { benchmarkPartition(32, 16, b) }
func BenchmarkPartition512Points(b *testing.B) { benchmarkPartition(512, 16, b) }
func BenchmarkPartition4096Points(b *testing.B) { benchmarkPartition(4096, 16, b) }
func BenchmarkPartition65536Points(b *testing.B) { benchmarkPartition(65536, 16, b) }