func run(name string, f func() *starter.Context) {
wg := new(sync.WaitGroup)
ch := make(chan float64, trials)
for i := 0; i < trials; i++ {
wg.Add(1)
go func() {
ctx := f()
exp := &neat.Experiment{ExperimentSettings: ctx}
exp.SetContext(ctx)
if err := neat.Run(exp); err != nil {
log.Fatalf("Fatal error in %s: %v\n", name, err)
}
if exp.Stopped() {
ch <- 0.0
} else {
ch <- 1.0
}
wg.Done()
}()
}
wg.Wait()
sum := 0.0
for i := 0; i < trials; i++ {
sum += <-ch
}
log.Println(name, "success rate:", sum/10.0)
}
func Run(f func(int) (*neat.Experiment, error)) error {
if *Profile {
defer profile.Start(profile.CPUProfile).Stop()
}
// Create the collection variables
n := *Trials
exps := make([]*neat.Experiment, n)
best := make([]neat.Genome, n)
noso := make([]bool, n)
fail := make([]bool, n)
skip := make([]bool, n)
errs := make([]error, n)
var secs stats.Float64Data = make([]float64, 0, n)
var fits stats.Float64Data = make([]float64, 0, n)
var iters stats.Float64Data = make([]float64, 0, n)
var nodes stats.Float64Data = make([]float64, 0, n)
var conns stats.Float64Data = make([]float64, 0, n)
var se, fi, it, no, co float64
// Begin the display
fmt.Printf("Beginning trials %v\n", time.Now().Format(time.RFC3339))
fmt.Printf("\t%d trials requested\n", *Trials)
if *CheckStop {
fmt.Println("\tstop signals successful trial")
}
if *SkipEvolve {
fmt.Println("\tskipping the evolution phase")
}
if *ShowWork {
fmt.Println("\tshowing the detailed evaluation of best in each generation")
}
fmt.Printf("Run Iters. Seconds Nodes Conns Fitness Fail Comment \n")
fmt.Printf("--- --------- --------- --------- --------- --------- ------ ---------\n")
// Iterate the trials
var showTime, showBest bool
var err error
for i := 0; i < n; i++ {
var t0, t1 time.Time
t0 = time.Now()
if exps[i], err = f(i); err != nil {
errs[i] = err
fail[i] = true
showBest = false
showTime = false
} else {
if *SkipEvolve && len(exps[i].Population().Genomes) > 0 {
skip[i] = true
} else if err = neat.Run(exps[i]); err != nil {
t1 = time.Now()
errs[i] = err
fail[i] = true
} else {
t1 = time.Now()
if *CheckStop && !exps[i].Stopped() {
errs[i] = fmt.Errorf("No solution found")
noso[i] = true
}
}
// Update the time stats
if exps[i].Iteration() > 0 {
showTime = true
it = float64(exps[i].Iteration())
se = t1.Sub(t0).Seconds()
if !fail[i] && !skip[i] {
iters = append(iters, it)
secs = append(secs, se)
}
} else {
showTime = false
}
// Find the best and update the results
if !fail[i] && len(exps[i].Population().Genomes) > 0 {
showBest = true
best[i] = findBest(exps[i].Population())
no = float64(len(best[i].Nodes))
co = float64(len(best[i].Conns))
fi = best[i].Fitness
if !noso[i] {
nodes = append(nodes, no)
conns = append(conns, co)
fits = append(fits, fi)
}
} else {
showBest = false
}
}
showTrial(padInt(i, 3), showTime, showBest, it, se, no, co, fi, fail[i] || noso[i], skip[i], errs[i])
}
// Display the summary
funcs := []func(stats.Float64Data) (float64, error){stats.Mean, stats.Median, stats.StdDevP, stats.Min, stats.Max}
labs := []string{"AVG", "MED", "SDV", "MIN", "MAX"} // 3 characters
var itm, sem, nom, com, fim [5]float64
if len(iters) > 0 {
showTime = true
for i := 0; i < len(funcs); i++ {
itm[i], _ = funcs[i](iters)
sem[i], _ = funcs[i](secs)
}
} else {
showTime = false
}
if len(nodes) > 0 {
showBest = true
for i := 0; i < len(funcs); i++ {
nom[i], _ = funcs[i](nodes)
com[i], _ = funcs[i](conns)
fim[i], _ = funcs[i](fits)
}
} else {
showBest = false
}
fmt.Printf("\nSummary for trials excluding failures (and time for skipped)\n")
fmt.Printf(" Iters. Seconds Nodes Conns Fitness\n")
fmt.Printf("--- --------- --------- --------- --------- ---------\n")
for i := 0; i < len(itm); i++ {
showTrial(labs[i], showTime, showBest, itm[i], sem[i], nom[i], com[i], fim[i], false, false, nil)
}
// Show the evaluations of the best
if *ShowWork {
for i := 0; i < len(exps); i++ {
if dh, ok := exps[i].Context().Evaluator().(neat.Demonstrable); ok {
dh.ShowWork(true)
if rst, ok := exps[i].Context().Archiver().(neat.Restorer); ok {
ctx := exps[i].Context()
if err := rst.Restore(ctx); err != nil {
fmt.Printf("Error restoring the context for trial %d: %v\n", i, err)
}
}
if p, err := exps[i].Context().Decoder().Decode(best[i]); err != nil {
fmt.Printf("Error decoding phenome in show work: %v\n", err)
} else {
evl := exps[i].Context().Evaluator()
if th, ok := evl.(neat.Trialable); ok {
th.SetTrial(i)
}
r := evl.Evaluate(p)
if r.Err() != nil {
fmt.Printf("Error demonstrating phenome: %v\n", r.Err())
}
}
}
}
}
return nil
}
