func (o *PrincStrainsUp) dbg_end(s *State, ε []float64, eid, ipid int) func() {
if eid == o.DbgEid && ipid == o.DbgIpId {
o.DbgPco = append(o.DbgPco, utl.DblCopy(s.Sig))
return func() {
o.DbgRes = append(o.DbgRes, s.GetCopy())
o.DbgSts = append(o.DbgSts, ε)
o.DbgPco = append(o.DbgPco, utl.DblCopy(s.Sig))
}
}
return func() {}
}
// Append adds a new entry {x, id} to the bins structure
func (o *Bins) Append(x []float64, id int) (err error) {
idx := o.CalcIdx(x)
if idx < 0 {
return chk.Err("point %v is out of range", x)
}
bin := o.FindBinByIndex(idx)
if bin == nil {
return chk.Err("bin index %v is out of range", idx)
}
xcopy := utl.DblCopy(x)
entry := BinEntry{id, xcopy}
bin.Entries = append(bin.Entries, &entry)
return
}
// Run runs optimisations
func (o *SimpleFltProb) Run(verbose bool) {
// benchmark
if verbose {
time0 := time.Now()
defer func() {
io.Pfblue2("\ncpu time = %v\n", time.Now().Sub(time0))
}()
}
// run all trials
for itrial := 0; itrial < o.C.Ntrials; itrial++ {
// reset populations
if itrial > 0 {
for id, isl := range o.Evo.Islands {
isl.Pop = o.C.PopFltGen(id, o.C)
isl.CalcOvs(isl.Pop, 0)
isl.CalcDemeritsAndSort(isl.Pop)
}
}
// run evolution
o.Evo.Run()
// results
xbest := o.Evo.Best.GetFloats()
o.Fcn(o.ff[0], o.gg[0], o.hh[0], xbest)
// check if best is unfeasible
unfeasible := false
for _, g := range o.gg[0] {
if g < 0 {
unfeasible = true
break
}
}
for _, h := range o.hh[0] {
if math.Abs(h) > o.C.Eps1 {
unfeasible = true
break
}
}
// feasible results
if !unfeasible {
for i, x := range xbest {
o.Xbest[o.Nfeasible][i] = x
}
o.Nfeasible++
}
// message
if verbose {
io.Pfyel("%3d x*="+o.NumfmtX+" f="+o.NumfmtF, itrial, xbest, o.ff[0])
if unfeasible {
io.Pfred(" unfeasible\n")
} else {
io.Pfgreen(" ok\n")
}
}
// best populations
if o.C.DoPlot {
if o.Nfeasible == 1 {
o.PopsBest = o.Evo.GetPopulations()
} else {
fcur := utl.DblCopy(o.ff[0])
o.Fcn(o.ff[0], o.gg[0], o.hh[0], o.Xbest[o.Nfeasible-1])
cur_dom, _ := utl.DblsParetoMin(fcur, o.ff[0])
if cur_dom {
o.PopsBest = o.Evo.GetPopulations()
}
}
}
}
}