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golearn/metrics/pairwise/manhattan_test.go
2014-05-03 22:47:41 +08:00

43 lines
1.0 KiB
Go

package pairwise
import (
"testing"
"github.com/gonum/matrix/mat64"
. "github.com/smartystreets/goconvey/convey"
)
func TestManhattan(t *testing.T) {
var vectorX, vectorY *mat64.Dense
manhattan := NewManhattan()
Convey("Given two vectors", t, func() {
vectorX = mat64.NewDense(3, 1, []float64{2, 2, 3})
vectorY = mat64.NewDense(3, 1, []float64{1, 4, 5})
Convey("When calculating distance with column vectors", func() {
result := manhattan.Distance(vectorX, vectorY)
Convey("The result should be 5", func() {
So(result, ShouldEqual, 5)
})
})
Convey("When calculating distance with row vectors", func() {
vectorX.TCopy(vectorX)
vectorY.TCopy(vectorY)
result := manhattan.Distance(vectorX, vectorY)
Convey("The result should be 5", func() {
So(result, ShouldEqual, 5)
})
})
Convey("When calculating distance with row and column vectors", func() {
vectorX.TCopy(vectorX)
So(func() { manhattan.Distance(vectorX, vectorY) }, ShouldPanicWith, mat64.ErrShape)
})
})
}