func main() {
seed := time.Now().UTC().UnixNano()
rand.Seed(seed)
fmt.Println("Using seed:", seed)
// Test expr
// The initialization function creates a tree with specified max depth
// And it's a closure over the primitives
exprInit := func(maxDep int) *node.Node {
return node.MakeTreeHalfAndHalf(maxDep, expr.Functionals, expr.Terminals)
}
exprMutate := node.MakeSubtreeMutation(MAX_D, exprInit)
fmt.Println("Testing representation: expr")
exprErrorAvg, exprErrorVar := testRepr(exprInit, exprMutate, expr.Draw)
fmt.Println("expr error avg:", exprErrorAvg, "var:", exprErrorVar)
// Test ts
tsInit := func(maxDep int) *node.Node {
return node.MakeTreeHalfAndHalf(maxDep, ts.Functionals, ts.Terminals)
}
tsMutate := node.MakeSubtreeMutation(MAX_D, tsInit)
fmt.Println("Testing representation: TS")
tsErrorAvg, tsErrorVar := testRepr(tsInit, tsMutate, ts.Draw)
fmt.Println("TS error avg:", tsErrorAvg, "var:", tsErrorVar)
// Test vhs
vhsInit := func(maxDep int) *node.Node {
return node.MakeTreeHalfAndHalf(maxDep, vhs.Functionals, vhs.Terminals)
}
vhsMutate := node.MakeSubtreeMutation(MAX_D, vhsInit)
fmt.Println("Testing representation: VHS")
vhsErrorAvg, vhsErrorVar := testRepr(vhsInit, vhsMutate, vhs.Draw)
fmt.Println("VHS error avg:", vhsErrorAvg, "var:", vhsErrorVar)
}
func (s *Solution) Mutate() {
subtrMut := node.MakeSubtreeMutation(s.Conf.MaxDepth, func(maxDep int) *node.Node {
return node.MakeTreeHalfAndHalf(maxDep, s.Conf.Functionals, s.Conf.Terminals)
})
subtrMut(s.Node)
}
func makeMultiMutation(s *base.Settings, multiMut, enbSin, enbNod, enbSub, enbAre, enbLsubt, enbLoc bool) func(float64, *base.Individual) bool {
// La mutazione a che profondità avviene?
// Quanto è profondo l'albero che vado a generare?
// Quanto è profondo l'albero che vado a sostituire?
// Separare foglie e nodi
countInt := func(name string, v int) {
if _, ok := s.IntCounters[name]; !ok {
s.IntCounters[name] = new(counter.IntCounter)
}
s.IntCounters[name].Count(v)
}
countBool := func(name string, v bool) {
if _, ok := s.Counters[name]; !ok {
s.Counters[name] = new(counter.BoolCounter)
}
s.Counters[name].Count(v)
}
statFuncSin := func(nDepth, replDepth int, isLeaf bool) {
countInt(mut_single_node_depth, nDepth)
countInt(mut_single_node_repld, replDepth)
countBool(mut_single_node_leaves, isLeaf)
}
statFuncNod := func(nDepth, replDepth int, isLeaf bool) {
countInt(mut_multi_node_depth, nDepth)
countInt(mut_multi_node_repld, replDepth)
countBool(mut_multi_node_leaves, isLeaf)
}
statFuncTree := func(nDepth, replDepth int, isLeaf bool) {
countInt(mut_tree_node_depth, nDepth)
countInt(mut_tree_node_repld, replDepth)
countBool(mut_tree_node_leaves, isLeaf)
}
statFuncArea := func(nDepth, replDepth int, isLeaf bool) {
countInt(mut_area_node_depth, nDepth)
countInt(mut_area_node_repld, replDepth)
countBool(mut_area_node_leaves, isLeaf)
}
statFuncLevSubtr := func(nDepth, replDepth int, isLeaf bool) {
countInt(mut_lsubt_node_depth, nDepth)
countInt(mut_lsubt_node_repld, replDepth)
countBool(mut_lsubt_node_leaves, isLeaf)
}
singleMut := node.MakeTreeSingleMutation(s.Functionals, s.Terminals, statFuncSin) // func(*Node)
nodeMut := node.MakeTreeNodeMutation(s.Functionals, s.Terminals, statFuncNod) // funcs, terms []gp.Primitive)// func(*Node) int {
subtrMut := node.MakeSubtreeMutation(s.MaxDepth, s.GenFunc, statFuncTree)
areaMut := node.MakeSubtreeMutationGuided(s.MaxDepth, s.GenFunc, node.ArityDepthProbComputer, statFuncArea)
subtLevelMut := node.MakeSubtreeMutationGuided(s.MaxDepth, s.GenFunc, node.UniformDepthProbComputer, statFuncLevSubtr)
const neighbSize = 5 // Neighborhood size for local search
return func(pMut float64, ind *base.Individual) bool {
perm := rand.Perm(6) // Randomly permutate the algorithms to pick
evCount := 0 // Number of events (mutations performed)
for _, v := range perm {
event := rand.Float64() < pMut // Perform mutation?
switch v {
case 0:
if enbSin {
ind.CountEvent(mut_single_event, event)
if event {
evCount++
fit := ind.Evaluate()
singleMut(ind.Node)
newFit := ind.Evaluate()
ind.CountEvent(mut_single_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
case 1:
if enbNod {
fit := ind.Evaluate()
event = nodeMut(pMut, ind.Node) != 0
ind.CountEvent(mut_multi_event, event)
if event {
evCount++
newFit := ind.Evaluate()
ind.CountEvent(mut_multi_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
case 2:
if enbSub {
ind.CountEvent(mut_tree_event, event)
if event {
evCount++
fit := ind.Evaluate()
subtrMut(ind.Node)
newFit := ind.Evaluate()
ind.CountEvent(mut_tree_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
case 3:
if enbAre {
ind.CountEvent(mut_area_event, event)
if event {
evCount++
fit := ind.Evaluate()
areaMut(ind.Node)
newFit := ind.Evaluate()
ind.CountEvent(mut_area_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
case 4:
if enbLsubt {
ind.CountEvent(mut_lsubt_event, event)
if event {
evCount++
fit := ind.Evaluate()
subtLevelMut(ind.Node)
newFit := ind.Evaluate()
ind.CountEvent(mut_lsubt_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
default:
if enbLoc {
// Local search
ind.CountEvent(mut_local_event, event)
if event {
evCount++
fit := ind.Evaluate()
for i := 0; i < neighbSize; i++ {
mutated := ind.Copy().(*base.Individual) // Copy individual
singleMut(mutated.Node) // Apply mutation
if s.BetterThan(mutated.Fitness(), ind.Fitness()) {
// If improved, save the individual
ind.Node = mutated.Node
// Invalidate!
ind.Invalidate()
}
}
// Perform singleMut K times
newFit := ind.Evaluate()
ind.CountEvent(mut_local_improv, s.BetterThan(newFit, fit))
}
if !multiMut {
return event
}
}
}
// In the case we don't execute anything, go to the next method
}
// If this happens, all the mutations were disabled, or all the mutations
// were performed when multi mutation was enabled
if multiMut {
countInt(mut_count_multi, evCount)
}
return evCount > 0
}
}