func TestOptimalAttackVectorSort(t *testing.T) {
rand.Seed(0)
predator := vpTesterAgent(0.0, 0.0)
predator.vsr = 1.0
predator.τ = colour.RGB{Red: 0.71, Green: 0.1, Blue: 0.39}
prey := []ColourPolymorphicPrey{}
for i := 1; i <= 10; i++ {
agentA := cpPreyTesterAgent(calc.RandFloatIn(-1, 1), calc.RandFloatIn(-1, 1))
agentB := cpPreyTesterAgent(calc.RandFloatIn(-1, 1), calc.RandFloatIn(-1, 1))
agentA.colouration = colour.RGB{Red: rand.Float64(), Green: rand.Float64(), Blue: rand.Float64()}
agentB.colouration = colour.RGB{Red: rand.Float64(), Green: rand.Float64(), Blue: rand.Float64()}
prey = append(prey, agentA)
prey = append(prey, agentB)
}
c := math.Pow(2, 3)
f := visualSignalStrength(c)
optimals := []visualRecognition{}
for i := range prey {
𝛘 := colour.RGBDistance(predator.τ, prey[i].colouration)
δ, _ := geometry.VectorDistance(predator.pos, prey[i].pos)
// fmt.Printf("%v\t%v\t%v\t%p\n", i, 𝛘, δ, &prey[i])
a := visualRecognition{δ, 𝛘, f, c, &prey[i]}
optimals = append(optimals, a)
}
// PreySearch – uses Visual Search to try to 'recognise' a nearby prey agent within model Environment to target
func (vp *VisualPredator) PreySearch(prey []ColourPolymorphicPrey) (*ColourPolymorphicPrey, error) {
c := vp.ετ
var 𝒇 = visualSignalStrength(c)
var 𝛘 float64 // colour sorting value - colour distance/difference between vp.imprimt and cpPrey.colouration
var δ float64 // position sorting value - vector distance between vp.pos and cpPrey.pos
var err error
var searchSet []visualRecognition
for i := range prey { // exhaustive search 😱
δ, err = geometry.VectorDistance(vp.pos, prey[i].pos)
if δ <= vp.vsr { // ∴ only include the prey agent for considertion if within visual range
𝛘 = colour.RGBDistance(vp.τ, prey[i].colouration)
if 𝛘 < vp.𝛄 { // i.e. if and only if colour distance falls within predator's current search tolerance
a := visualRecognition{δ, 𝛘, 𝒇, c, &prey[i]}
searchSet = append(searchSet, a)
}
}
}
func TestCPPComparitorSort(t *testing.T) {
rand.Seed(0)
predator := vpTesterAgent(0.0, 0.0)
predator.vsr = 1.0
predator.τ = colour.RGB{Red: 0.71, Green: 0.1, Blue: 0.39}
prey := []ColourPolymorphicPrey{}
for i := 1; i <= 10; i++ {
agentA := cpPreyTesterAgent(calc.RandFloatIn(-1, 1), calc.RandFloatIn(-1, 1))
agentB := cpPreyTesterAgent(calc.RandFloatIn(-1, 1), calc.RandFloatIn(-1, 1))
agentA.colouration = colour.RGB{Red: rand.Float64(), Green: rand.Float64(), Blue: rand.Float64()}
agentB.colouration = colour.RGB{Red: rand.Float64(), Green: rand.Float64(), Blue: rand.Float64()}
prey = append(prey, agentA)
prey = append(prey, agentB)
}
f := func(v geometry.Vector) func(geometry.Vector) float64 {
return func(u geometry.Vector) float64 {
dist, _ := geometry.VectorDistance(v, u)
return dist
}
}(predator.pos)
compers := []compCPP{}
for i := range prey {
// fmt.Printf("%v\t%v\t%p\n", i, prey[i].pos, &prey[i])
a := compCPP{f, &prey[i]}
compers = append(compers, a)
}
sort.Sort(byComparitor(compers))
// for i := range compers {
// fmt.Printf("%v\t%v\t%p\t%v\n", i, compers[i].pos, compers[i].ColourPolymorphicPrey, f(compers[i].pos))
// }
want := fmt.Sprintf("%p", &prey[19])
got := fmt.Sprintf("%p", &(*compers[0].ColourPolymorphicPrey))
if want != got {
t.Errorf("want:\n%q\ngot:\n%q\n", want, got)
}
}
// MateSearch implements Breeder interface method for ColourPolymorphicPrey:
// NEEDS BETTER HANDLING THAN JUST PUSHING THE ERROR UP!
func (c *ColourPolymorphicPrey) MateSearch(pop []ColourPolymorphicPrey, skip int) (mate *ColourPolymorphicPrey, err error) {
mate = nil
err = nil
dist := 0.0
for i := 0; i < len(pop); i++ {
if i == skip {
continue
}
dist, err = geometry.VectorDistance(c.pos, pop[i].pos)
if err != nil {
return
}
if dist <= c.sr {
mate = &pop[i]
return
}
}
return
}
