func buildIter(lb, ub []float64) optim.Method {
mask := make([]bool, len(ub))
for i := range mask {
mask[i] = lb[i] < ub[i]
}
n := 30 + 1*len(lb)
if *npar != 0 {
n = *npar
} else if n < 30 {
n = 30
}
fmt.Printf("swarming with %v particles\n", n)
ev := optim.ParallelEvaler{}
if *addr == "" {
ev.NConcurrent = *ncpu
}
pop := swarm.NewPopulationRand(n, lb, ub)
swarm := swarm.New(
pop,
swarm.Evaler(ev),
swarm.VmaxBounds(lb, ub),
swarm.DB(db),
)
if *swarmonly {
return swarm
} else {
return pattern.New(pop[0].Point,
pattern.ResetStep(.01, 1.0),
pattern.NsuccessGrow(4),
pattern.Evaler(ev),
pattern.PollRandNMask(n, mask),
pattern.SearchMethod(swarm, pattern.Share),
pattern.DB(db),
)
}
}
func loadIter(lb, ub []float64, iter int) (md optim.Method, initstep float64) {
_, err := db.Exec("CREATE INDEX IF NOT EXISTS points_posid ON points (posid ASC);")
check(err)
query := "SELECT pt.dim,pt.val,pi.val FROM points AS pt JOIN patterninfo AS pi ON pi.posid=pt.posid WHERE pi.iter=?;"
initPoint := loadPoint(query, iter)
row := db.QueryRow("SELECT step FROM patterninfo WHERE iter=?;", iter)
err = row.Scan(&initstep)
check(err)
mask := make([]bool, len(ub))
for i := range mask {
mask[i] = lb[i] < ub[i]
}
row = db.QueryRow("SELECT COUNT(*) FROM swarmparticles WHERE iter=?;", iter)
var npar int
err = row.Scan(&npar)
check(err)
pop := make(swarm.Population, npar)
for i := 0; i < npar; i++ {
query := "SELECT pt.dim,pt.val,s.val FROM points AS pt JOIN swarmparticles AS s ON s.posid=pt.posid WHERE s.iter=? AND s.particle=?;"
pt := loadPoint(query, iter, i)
query = "SELECT pt.dim,pt.val,s.best FROM points AS pt JOIN swarmparticlesbest AS s ON s.posid=pt.posid WHERE s.iter=? AND s.particle=?;"
best := loadPoint(query, iter, i)
query = "SELECT pt.dim,pt.val,0 FROM points AS pt JOIN swarmparticles AS s ON s.velid=pt.posid WHERE s.iter=? AND s.particle=?;"
vel := loadPoint(query, iter, i)
par := &swarm.Particle{
Id: i,
Point: pt,
Best: best,
Vel: vel.Pos,
}
pop[i] = par
//fmt.Printf("DEBUG par %v: pos[10]=%v obj=%v bestpos[10]=%v bestobj=%v\n", i, par.Pos[10], par.Val, par.Best.Pos[10], par.Best.Val)
}
fmt.Printf("swarming with %v particles\n", len(pop))
ev := optim.ParallelEvaler{}
if *addr == "" {
ev.NConcurrent = runtime.NumCPU()
}
swarm := swarm.New(
pop,
swarm.Evaler(ev),
swarm.VmaxBounds(lb, ub),
swarm.DB(db),
swarm.InitIter(iter+1),
)
return pattern.New(initPoint,
pattern.ResetStep(.01, 1.0),
pattern.NsuccessGrow(4),
pattern.Evaler(ev),
pattern.PollRandNMask(npar, mask),
pattern.SearchMethod(swarm, pattern.Share),
pattern.DB(db),
), initstep
}