// PostProcess performs a post-processing of the just read json file
func (o *Data) PostProcess(dir, fn string, erasefiles bool) {
o.FnameDir = os.ExpandEnv(dir)
o.FnameKey = io.FnKey(fn)
if o.DirOut == "" {
o.DirOut = "/tmp/gofem/" + o.FnameKey
}
if o.Encoder != "gob" && o.Encoder != "json" {
o.Encoder = "gob"
}
err := os.MkdirAll(o.DirOut, 0777)
if err != nil {
chk.Panic("cannot create directory for output results (%s): %v", o.DirOut, err)
}
if erasefiles {
io.RemoveAll(io.Sf("%s/%s_*.vtu", o.DirOut, o.FnameKey))
io.RemoveAll(io.Sf("%s/%s_*.log", o.DirOut, o.FnameKey))
io.RemoveAll(io.Sf("%s/%s_*.gob", o.DirOut, o.FnameKey))
io.RemoveAll(io.Sf("%s/%s_*.json", o.DirOut, o.FnameKey))
}
}
// RunMany runs many trials in order to produce statistical data
func (o *Optimiser) RunMany(dirout, fnkey string) {
// benchmark
t0 := time.Now()
defer func() {
o.SysTimeTot = time.Now().Sub(t0)
var tmp int64
for _, dur := range o.SysTimes {
tmp += dur.Nanoseconds()
}
tmp /= int64(o.Nsamples)
o.SysTimeAve = time.Duration(tmp)
}()
// disable verbose flag temporarily
if o.Verbose {
defer func() {
o.Verbose = true
}()
o.Verbose = false
}
// remove previous results
if fnkey != "" {
io.RemoveAll(dirout + "/" + fnkey + "-*.res")
}
// allocate variables
o.SysTimes = make([]time.Duration, o.Nsamples)
o.BestOvas = make([][]float64, o.Nova)
o.BestFlts = make([][]float64, o.Nflt)
o.BestInts = make([][]int, o.Nint)
o.BestOfBestOva = make([]float64, o.Nova)
o.BestOfBestFlt = make([]float64, o.Nflt)
o.BestOfBestInt = make([]int, o.Nint)
// perform trials
for itrial := 0; itrial < o.Nsamples; itrial++ {
// re-generate solutions
o.Nfeval = 0
if itrial > 0 {
o.generate_solutions(itrial)
}
// save initial solutions
if fnkey != "" {
WriteAllValues(dirout, io.Sf("%s-%04d_ini", fnkey, itrial), o)
}
// message
if o.VerbStat {
io.Pf(". . . running trial # %d\n", itrial)
}
// solve
timeIni := time.Now()
o.Solve()
o.SysTimes[itrial] = time.Now().Sub(timeIni)
// sort
if o.Nova > 1 { // multi-objective
SortByFrontThenOva(o.Solutions, 0)
} else { // single-objective
SortByOva(o.Solutions, 0)
}
// feasible solution
if o.Solutions[0].Feasible() {
// best solution
best := o.Solutions[0]
for i := 0; i < o.Nova; i++ {
o.BestOvas[i] = append(o.BestOvas[i], best.Ova[i])
}
for i := 0; i < o.Nflt; i++ {
o.BestFlts[i] = append(o.BestFlts[i], best.Flt[i])
}
for i := 0; i < o.Nint; i++ {
o.BestInts[i] = append(o.BestInts[i], best.Int[i])
}
// best of all trials
first_best := len(o.BestOvas[0]) == 1
if first_best {
copy(o.BestOfBestOva, best.Ova)
copy(o.BestOfBestFlt, best.Flt)
copy(o.BestOfBestInt, best.Int)
} else {
if best.Ova[0] < o.BestOfBestOva[0] {
copy(o.BestOfBestOva, best.Ova)
copy(o.BestOfBestFlt, best.Flt)
copy(o.BestOfBestInt, best.Int)
}
}
// check multi-objective results
if o.F1F0_func != nil {
var rms_err float64
var nfeasible int
for _, sol := range o.Solutions {
if sol.Feasible() && sol.FrontId == 0 {
f0, f1 := sol.Ova[0], sol.Ova[1]
f1_cor := o.F1F0_func(f0)
rms_err += math.Pow(f1-f1_cor, 2.0)
nfeasible++
}
}
if nfeasible > 0 {
rms_err = math.Sqrt(rms_err / float64(nfeasible))
o.F1F0_err = append(o.F1F0_err, rms_err)
}
}
// arc-length along Pareto front
if o.Nova == 2 {
if best.Feasible() && best.FrontId == 0 && o.Solutions[1].FrontId == 0 {
dist := 0.0
for i := 1; i < o.Nsol; i++ {
if o.Solutions[i].FrontId == 0 {
F0, F1 := o.Solutions[i-1].Ova[0], o.Solutions[i-1].Ova[1]
f0, f1 := o.Solutions[i].Ova[0], o.Solutions[i].Ova[1]
if o.F1F0_f0ranges != nil {
a := o.find_f0_spot(F0)
b := o.find_f0_spot(f0)
if a == -1 || b == -1 {
continue
}
if a != b {
//io.Pforan("\nF0=%g is in [%g,%g]\n", F0, o.F1F0_f0ranges[a][0], o.F1F0_f0ranges[a][1])
//io.Pfpink("f0=%g is in [%g,%g]\n", f0, o.F1F0_f0ranges[b][0], o.F1F0_f0ranges[b][1])
continue
}
}
dist += math.Sqrt(math.Pow(f0-F0, 2.0) + math.Pow(f1-F1, 2.0))
}
}
o.F1F0_arcLen = append(o.F1F0_arcLen, dist)
}
}
// multiple OVAs
if o.Nova > 1 && o.Multi_fcnErr != nil {
var rms_err float64
var nfeasible int
for _, sol := range o.Solutions {
if sol.Feasible() && sol.FrontId == 0 {
f_err := o.Multi_fcnErr(sol.Ova)
rms_err += f_err * f_err
nfeasible++
}
}
if nfeasible > 0 {
rms_err = math.Sqrt(rms_err / float64(nfeasible))
o.Multi_err = append(o.Multi_err, rms_err)
}
}
// IGD metric
if o.Nova > 1 && len(o.Multi_fStar) > 0 {
o.Multi_IGD = append(o.Multi_IGD, StatIgd(o, o.Multi_fStar))
}
// save final solutions
if fnkey != "" {
f0min := best.Ova[0]
for _, sol := range o.Solutions {
f0min = utl.Min(f0min, sol.Ova[0])
}
WriteAllValues(dirout, io.Sf("%s-%04d_f0min=%g", fnkey, itrial, f0min), o)
}
}
}
}
