func TestScatterRatio(t *testing.T) {
points := []*matrix.DenseMatrix{
matrix.MakeDenseMatrix([]float64{-1, 0}, 2, 1),
matrix.MakeDenseMatrix([]float64{1, 0}, 2, 1),
matrix.MakeDenseMatrix([]float64{0, 1}, 2, 1),
matrix.MakeDenseMatrix([]float64{0, -1}, 2, 1),
}
iw1 := NewIWPosterior(1, matrix.Eye(2))
iw2 := NewIWPosterior(1, matrix.Eye(2))
scatter1 := NewScatter(2)
scatter2 := NewScatter(2)
for _, point := range points {
scatter1.Insert(point)
offset, _ := point.PlusDense(matrix.MakeDenseMatrix([]float64{5, 0}, 2, 1))
scatter2.Insert(offset)
}
iw1.InsertScatter(scatter1)
iw2.InsertScatter(scatter2)
fmt.Printf("%f\n", iw1.InsertScatterLogRatio(scatter1))
fmt.Printf("%f\n", iw1.InsertScatterLogRatio(scatter2))
fmt.Printf("%f\n", iw2.InsertScatterLogRatio(scatter1))
fmt.Printf("%f\n", iw2.InsertScatterLogRatio(scatter2))
}
func TestIW(t *testing.T) {
psi := matrix.MakeDenseMatrix([]float64{1, 0, 0, 1}, 2, 2)
iwp := NewIWPosterior(1, psi)
iwp.Insert(matrix.MakeDenseMatrix([]float64{1, 1}, 2, 1))
iwp.Insert(matrix.MakeDenseMatrix([]float64{2, 1}, 2, 1))
lr := iwp.InsertLogRatio(matrix.MakeDenseMatrix([]float64{1, 2}, 2, 1))
println(lr)
}
func (this *ROARAgent) AgentStep(reward float64, obs rlglue.Observation) rlglue.Action {
last := matrix.MakeDenseMatrix(this.LastObs.Doubles(), this.numFeatures, 1)
current := matrix.MakeDenseMatrix(obs.Doubles(), this.numFeatures, 1)
rm := matrix.MakeDenseMatrix([]float64{reward}, 1, 1)
outcome, _ := current.MinusDense(last)
sor, _ := last.Augment(outcome)
sor, _ = sor.Augment(rm)
actionIndex := this.task.Act.Ints.Index(this.LastAct.Ints())
this.rpost[actionIndex].Insert(sor)
this.LastObs = obs
return this.GetAction()
}
func (this *Posterior) ConditionalSample(x1 *matrix.DenseMatrix) (x2 *matrix.DenseMatrix) {
this.block <- true
defer func() { <-this.block }()
//first we choose one
plls := CRPPrior(this.Cfg.Calpha, this.C)
//fmt.Printf("plls = %v\n", plls)
for i, pll := range plls {
if pll == NegInf {
continue
}
plls[i] += this.SmallClusterLoglihoodRatio(x1, i)
}
chosenCluster := LogChoice(plls)
newCluster := this.C.Count(chosenCluster) == 0
chosenGroup := this.G.Get(chosenCluster)
if chosenGroup == -1 || newCluster {
glls := CRPPrior(this.Cfg.Galpha, this.G)
chosenGroup = LogChoice(glls)
}
this.PrepareGroup(chosenGroup)
theV := this.V[chosenGroup]
Sigma := theV.NextCovar()
x2f := stat.NextMVNormal(theV.S.Mean.Array(), Sigma.Arrays())
x2 = matrix.MakeDenseMatrix(x2f, Sigma.Rows(), 1)
return
}
func TestScatterNeg(t *testing.T) {
points := []*matrix.DenseMatrix{
matrix.MakeDenseMatrix([]float64{-5}, 1, 1),
matrix.MakeDenseMatrix([]float64{-3}, 1, 1),
matrix.MakeDenseMatrix([]float64{-4}, 1, 1),
matrix.MakeDenseMatrix([]float64{-6}, 1, 1),
}
s1 := NewScatter(1)
s2 := NewScatter(1)
for _, point := range points {
s1.Insert(point)
}
fmt.Printf("%v\n", s1)
for _, point := range points {
offset, _ := point.PlusDense(matrix.MakeDenseMatrix([]float64{10}, 1, 1))
s2.Insert(offset)
//s1.Insert(offset)
}
s1.InsertScatter(s2)
s1.RemoveScatter(s2)
fmt.Printf("%v\n", s1)
}
func drawField() {
scr := window.Screen()
min, max := scr.Bounds().Min, scr.Bounds().Max
for dx := min.X; dx < max.X; dx += 3 {
for dy := min.Y; dy < max.Y; dy += 3 {
rx := float64(dx) / spanX
ry := float64(dy) / spanY
x := matrix.MakeDenseMatrix([]float64{rx, ry}, 2, 1)
clusterIndex := rpost.BestCluster(x)
var clusterColor image.RGBAColor
if clusterIndex == -1 {
continue
} else {
clusterColor = colors[clusterIndex%len(colors)]
}
window.Screen().Set(dx, dy, clusterColor)
}
}
}
func rclick(x float64) {
x1 := matrix.MakeDenseMatrix([]float64{x}, 1, 1)
x2 := rpost.ConditionalSample(x1)
click(x1.Get(0, 0), x2.Get(0, 0))
}
func click(x, y float64) {
x_t := matrix.MakeDenseMatrix([]float64{x, y}, 2, 1)
rpost.Insert(x_t)
}