// for each weighted input vector, calculate the (inputs * weights) dot product
// and sum all of these dot products together to produce a sum
func (neuron *Neuron) weightedInputDotProductSum(weightedInputs []*weightedInput) float64 {
var dotProductSummation float64
dotProductSummation = 0
for _, weightedInput := range weightedInputs {
inputs := weightedInput.inputs
weights := weightedInput.weights
inputVector := vector.NewFrom(inputs)
weightVector := vector.NewFrom(weights)
dotProduct, error := vector.DotProduct(inputVector, weightVector)
if error != nil {
t := "%T error performing dot product between %v and %v"
message := fmt.Sprintf(t, neuron, inputVector, weightVector)
panic(message)
}
dotProductSummation += dotProduct
}
return dotProductSummation
}
func (a *FLWMAgent) MoveRandomly(steplength float64) {
//random direction
bsize := float64(a.ls.Size)
v := vector.NewFrom([]float64{a.ls.random(-bsize, bsize), a.ls.random(-bsize, bsize)})
v.Normalize()
v.Scale(steplength)
x, _ := v.Get(0)
y, _ := v.Get(1)
x = x + a.X
y = y + a.Y
// check bounds
if x < 0 {
x = bsize + x // reenter world on the other side
}
if y < 0 {
y = bsize + y // reenter world on the other side
}
if x > bsize {
x = x - bsize
}
if y > bsize {
y = y - bsize
}
if x >= float64(a.ls.Size) || x < 0 || y >= float64(a.ls.Size) || y < 0 {
// just try again
fmt.Printf("out of bounds %f/%f of %f\n", x, y, bsize)
a.MoveRandomly(steplength)
return
}
//fmt.Printf("move from %f/%f to %f/%f\n",a.X,a.Y,x,y)
a.ls.tree.Move(a, qt.Twof{x, y})
a.X = x
a.Y = y
}
