// StrMutation performs the mutation of genetic data from A
// Output: modified individual 'A'
func StrMutation(A []string, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
A[i] = "TODO" // TODO: improve this
}
}
// KeyMutation performs the mutation of genetic data from A
// Output: modified individual 'A'
func KeyMutation(A []byte, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
v := rnd.Int(0, 100)
A[i] = byte(v) // TODO: improve this
}
}
// FunMutation performs the mutation of genetic data from A
// Output: modified individual 'A'
func FunMutation(A []Func_t, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
// TODO: improve this
A[i] = func(ind *Individual) string { return "mutated" }
}
}
// MtIntBin performs the mutation of a binary chromosome
// Output: modified individual 'A'
func MtIntBin(A []int, prms *Parameters) {
size := len(A)
if !rnd.FlipCoin(prms.IntPm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, prms.IntNchanges)
for _, i := range pos {
if A[i] == 0 {
A[i] = 1
} else {
A[i] = 0
}
}
}
// IntBinMutation performs the mutation of a binary chromosome
// Output: modified individual 'A'
func IntBinMutation(A []int, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
if A[i] == 0 {
A[i] = 1
} else {
A[i] = 0
}
}
}
// IntMutation performs the mutation of genetic data from A
// Output: modified individual 'A'
func IntMutation(A []int, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
m := rnd.Int(1, int(ops.Mmax))
if rnd.FlipCoin(0.5) {
A[i] += m * A[i]
} else {
A[i] -= m * A[i]
}
}
}
// GenerateCxEnds randomly computes the end positions of cuts in chromosomes
// Input:
// size -- size of chromosome
// ncuts -- number of cuts to be used, unless cuts != nil
// cuts -- cut positions. can be nil => use ncuts instead
// Output:
// ends -- end positions where the last one equals size
// Example:
// 0 1 2 3 4 5 6 7
// A = a b c d e f g h size = 8
// ↑ ↑ ↑ cuts = [1, 5]
// 1 5 8 ends = [1, 5, 8]
func GenerateCxEnds(size, ncuts int, cuts []int) (ends []int) {
// handle small slices
if size < 2 {
return
}
if size == 2 {
return []int{1, size}
}
// cuts slice is given
if len(cuts) > 0 {
ncuts = len(cuts)
ends = make([]int, ncuts+1)
ends[ncuts] = size
for i, cut := range cuts {
if cut < 1 || cut >= size {
chk.Panic("cut=%d is outside the allowed range: 1 ≤ cut ≤ size-1", cut)
}
if i > 0 {
if cut == cuts[i-1] {
chk.Panic("repeated cut values are not allowed: cuts=%v", cuts)
}
}
ends[i] = cut
}
sort.Ints(ends)
return
}
// randomly generate cuts
if ncuts < 1 {
ncuts = 1
}
if ncuts >= size {
ncuts = size - 1
}
ends = make([]int, ncuts+1)
ends[ncuts] = size
// pool of values for selections
pool := rnd.IntGetUniqueN(1, size, ncuts)
sort.Ints(pool)
for i := 0; i < ncuts; i++ {
ends[i] = pool[i]
}
return
}
// MtInt performs the mutation of genetic data from A
// Output: modified individual 'A'
func MtInt(A []int, prms *Parameters) {
size := len(A)
if !rnd.FlipCoin(prms.IntPm) || size < 1 {
return
}
mmax := 2
pos := rnd.IntGetUniqueN(0, size, prms.IntNchanges)
for _, i := range pos {
m := rnd.Int(1, mmax)
if rnd.FlipCoin(0.5) {
A[i] += m * A[i]
} else {
A[i] -= m * A[i]
}
}
}
func Test_int01(tst *testing.T) {
//verbose()
chk.PrintTitle("int01. organise sequence of ints")
io.Pf("\n")
// initialise random numbers generator
rnd.Init(0) // 0 => use current time as seed
// parameters
C := NewConfParams()
C.Nova = 1
C.Noor = 0
C.Nisl = 1
C.Ninds = 20
C.RegTol = 0
C.NumInts = 20
//C.GAtype = "crowd"
C.CrowdSize = 2
C.Tf = 50
C.Verbose = chk.Verbose
C.CalcDerived()
// mutation function
C.Ops.MtInt = func(A []int, time int, ops *OpsData) {
size := len(A)
if !rnd.FlipCoin(ops.Pm) || size < 1 {
return
}
pos := rnd.IntGetUniqueN(0, size, ops.Nchanges)
for _, i := range pos {
if A[i] == 1 {
A[i] = 0
}
if A[i] == 0 {
A[i] = 1
}
}
}
// generation function
C.PopIntGen = func(id int, cc *ConfParams) Population {
o := make([]*Individual, cc.Ninds)
genes := make([]int, cc.NumInts)
for i := 0; i < cc.Ninds; i++ {
for j := 0; j < cc.NumInts; j++ {
genes[j] = rand.Intn(2)
}
o[i] = NewIndividual(cc.Nova, cc.Noor, cc.Nbases, genes)
}
return o
}
// objective function
C.OvaOor = func(ind *Individual, idIsland, time int, report *bytes.Buffer) {
score := 0.0
count := 0
for _, val := range ind.Ints {
if val == 0 && count%2 == 0 {
score += 1.0
}
if val == 1 && count%2 != 0 {
score += 1.0
}
count++
}
ind.Ovas[0] = 1.0 / (1.0 + score)
return
}
// run optimisation
evo := NewEvolver(C)
evo.Run()
// results
ideal := 1.0 / (1.0 + float64(C.NumInts))
io.PfGreen("\nBest = %v\nBestOV = %v (ideal=%v)\n", evo.Best.Ints, evo.Best.Ovas[0], ideal)
}