func swarmsolver(fn bench.Func, db *sql.DB, n int) optim.Method {
low, up := fn.Bounds()
if n < 0 {
n = 30 + 1*len(low)
if n > maxeval/500 {
n = maxeval / 500
}
}
return swarm.New(
swarm.NewPopulationRand(n, low, up),
swarm.VmaxBounds(fn.Bounds()),
swarm.DB(db),
)
}
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),
)
}
}