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Code Issues Releases Wiki Activity

Make manhattan support both col&row vectors.

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This commit is contained in:
Bert Chang 2014-05-03 22:47:41 +08:00
parent b045cf83a5
commit 9a61332551
5 changed files with 40 additions and 11 deletions
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5
metrics/pairwise/euclidean_test.go
View File

@ -8,11 +8,12 @@ import (
)
func TestEuclidean(t *testing.T) {
var vectorX, vectorY *mat64.Dense
euclidean := NewEuclidean()
Convey("Given two vectors", t, func() {
vectorX := mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY := mat64.NewDense(3, 1, []float64{2, 4, 5})
vectorX = mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY = mat64.NewDense(3, 1, []float64{2, 4, 5})
Convey("When doing inner product", func() {
result := euclidean.InnerProduct(vectorX, vectorY)

15
metrics/pairwise/manhattan.go
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@ -13,13 +13,24 @@ func NewManhattan() *Manhattan {
}
func (self *Manhattan) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
var length int
subVector := mat64.NewDense(0, 0, nil)
subVector.Sub(vectorX, vectorY)
r, _ := subVector.Dims()
r, c := subVector.Dims()
if r == 1 {
// Force transpose to column vector
subVector.TCopy(subVector)
length = c
} else if c == 1 {
length = r
} else {
panic(mat64.ErrShape)
}
result := .0
for i := 0; i < r; i++ {
for i := 0; i < length; i++ {
result += math.Abs(subVector.At(i, 0))
}

21
metrics/pairwise/manhattan_test.go
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@ -8,19 +8,34 @@ import (
)
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})
vectorX = mat64.NewDense(3, 1, []float64{2, 2, 3})
vectorY = mat64.NewDense(3, 1, []float64{1, 4, 5})
Convey("When calculating distance", func() {
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)
})
})

5
metrics/pairwise/poly_kernel_test.go
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@ -8,11 +8,12 @@ import (
)
func TestPolyKernel(t *testing.T) {
var vectorX, vectorY *mat64.Dense
polyKernel := NewPolyKernel(3)
Convey("Given two vectors", t, func() {
vectorX := mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY := mat64.NewDense(3, 1, []float64{2, 4, 5})
vectorX = mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY = mat64.NewDense(3, 1, []float64{2, 4, 5})
Convey("When doing inner product", func() {
result := polyKernel.InnerProduct(vectorX, vectorY)

5
metrics/pairwise/rbf_kernel_test.go
View File

@ -8,11 +8,12 @@ import (
)
func TestRBFKernel(t *testing.T) {
var vectorX, vectorY *mat64.Dense
rbfKernel := NewRBFKernel(0.1)
Convey("Given two vectors", t, func() {
vectorX := mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY := mat64.NewDense(3, 1, []float64{2, 4, 5})
vectorX = mat64.NewDense(3, 1, []float64{1, 2, 3})
vectorY = mat64.NewDense(3, 1, []float64{2, 4, 5})
Convey("When doing inner product", func() {
result := rbfKernel.InnerProduct(vectorX, vectorY)