Golang io.Pfred函数代码示例

func main() {

	// input matrix in Triplet format
	// including repeated positions. e.g. (0,0)
	var A la.Triplet
	A.Init(5, 5, 13)
	A.Put(0, 0, 1.0) // << repeated
	A.Put(0, 0, 1.0) // << repeated
	A.Put(1, 0, 3.0)
	A.Put(0, 1, 3.0)
	A.Put(2, 1, -1.0)
	A.Put(4, 1, 4.0)
	A.Put(1, 2, 4.0)
	A.Put(2, 2, -3.0)
	A.Put(3, 2, 1.0)
	A.Put(4, 2, 2.0)
	A.Put(2, 3, 2.0)
	A.Put(1, 4, 6.0)
	A.Put(4, 4, 1.0)

	// right-hand-side
	b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}

	// allocate solver
	lis := la.GetSolver("umfpack")
	defer lis.Clean()

	// info
	symmetric := false
	verbose := false
	timing := false

	// initialise solver (R)eal
	err := lis.InitR(&A, symmetric, verbose, timing)
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// factorise
	err = lis.Fact()
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// solve (R)eal
	var dummy bool
	x := make([]float64, len(b))
	err = lis.SolveR(x, b, dummy) // x := inv(a) * b
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// output
	la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
	la.PrintVec("b", b, "%v ", false)
	la.PrintVec("x", x, "%v ", false)
}

func Test_spo751re(tst *testing.T) {

	//verbose()
	chk.PrintTitle("spo751re. Richardson extrapolation")

	// run simulation
	if !Start("data/spo751re.sim", true, chk.Verbose) {
		io.Pfred("start failed\n")
		return
	}

	// make sure to flush log
	defer End()

	// run simulation
	if !Run() {
		io.Pfred("run failed\n")
	}

	// plot
	//if true {
	if false {
		plot_spo751("spo751re")
	}
}

// StatF computes statistical information corresponding to objective function idxF
func StatF(o *Optimiser, idxF int, verbose bool) (fmin, fave, fmax, fdev float64, F []float64) {
	nsamples := len(o.BestOvas[idxF])
	if nsamples == 0 {
		if verbose {
			io.Pfred("there are no samples for statistical analysis\n")
		}
		return
	}
	F = make([]float64, nsamples)
	if nsamples == 1 {
		F[0] = o.BestOvas[idxF][0]
		fmin, fave, fmax = F[0], F[0], F[0]
		return
	}
	for i, f := range o.BestOvas[idxF] {
		F[i] = f
	}
	fmin, fave, fmax, fdev = rnd.StatBasic(F, true)
	if verbose {
		str := "\n"
		if len(o.RptFref) == o.Nova {
			str = io.Sf(" (%g)\n", o.RptFref[idxF])
		}
		io.Pf("fmin = %g\n", fmin)
		io.Pf("fave = %g"+str, fave)
		io.Pf("fmax = %g\n", fmax)
		io.Pf("fdev = %g\n", fdev)
		o.fix_formatting_data()
		io.Pf(rnd.BuildTextHist(nice(fmin, o.HistNdig)-o.HistDelFmin, nice(fmax, o.HistNdig)+o.HistDelFmax,
			o.HistNsta, F, o.HistFmt, o.HistLen))
	}
	return
}

// StatMulti prints statistical analysis for multi-objective problems
//  emin, eave, emax, edev -- errors on f1(f0)
//  key -- "IGD" if IGD values are available. In this case e{...} are IGD values
func StatMulti(o *Optimiser, verbose bool) (key string, emin, eave, emax, edev float64, E []float64) {
	if len(o.Multi_err) < 2 && len(o.Multi_IGD) < 2 {
		io.Pfred("there are no samples for statistical analysis\n")
		return
	}
	o.fix_formatting_data()
	n := len(o.Multi_err)
	key = "E"
	if n < 2 {
		n = len(o.Multi_IGD)
		key = "IGD"
	}
	E = make([]float64, n)
	if key == "E" {
		copy(E, o.Multi_err)
	} else {
		copy(E, o.Multi_IGD)
	}
	emin, eave, emax, edev = rnd.StatBasic(E, true)
	if verbose {
		io.Pf("\nerror on Pareto front (multi)\n")
		io.Pf("%smin = %g\n", key, emin)
		io.Pf("%save = %g\n", key, eave)
		io.Pf("%smax = %g\n", key, emax)
		io.Pf("%sdev = %g\n", key, edev)
		io.Pf(rnd.BuildTextHist(nice(emin, o.HistNdig)-o.HistDelEmin, nice(emax, o.HistNdig)+o.HistDelEmax,
			o.HistNsta, E, o.HistFmt, o.HistLen))
	}
	return
}

func main() {

	// input matrix in Triplet format
	// including repeated positions. e.g. (0,0)
	var A la.Triplet
	A.Init(5, 5, 13)
	A.Put(0, 0, 1.0) // << repeated
	A.Put(0, 0, 1.0) // << repeated
	A.Put(1, 0, 3.0)
	A.Put(0, 1, 3.0)
	A.Put(2, 1, -1.0)
	A.Put(4, 1, 4.0)
	A.Put(1, 2, 4.0)
	A.Put(2, 2, -3.0)
	A.Put(3, 2, 1.0)
	A.Put(4, 2, 2.0)
	A.Put(2, 3, 2.0)
	A.Put(1, 4, 6.0)
	A.Put(4, 4, 1.0)

	// right-hand-side
	b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}

	// solve
	x, err := la.SolveRealLinSys(&A, b)
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// output
	la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
	la.PrintVec("b", b, "%v ", false)
	la.PrintVec("x", x, "%v ", false)
}

// Init initialises model
func (o *DruckerPrager) Init(ndim int, pstress bool, prms fun.Prms) (err error) {

	// parse parameters
	err = o.SmallElasticity.Init(ndim, pstress, prms)
	if err != nil {
		return
	}
	for _, p := range prms {
		switch p.N {
		case "M":
			o.M = p.V
		case "Mb":
			o.Mb = p.V
		case "qy0":
			o.qy0 = p.V
		case "H":
			o.H = p.V
		case "E", "nu", "l", "G", "K", "rho":
		case "c", "phi", "typ":
			io.Pfred("dp: warning: handling of 'c', 'phi' and 'typ' parameters is not implemented yet\n")
		default:
			return chk.Err("dp: parameter named %q is incorrect\n", p.N)
		}
	}

	// auxiliary structures
	o.ten = make([]float64, o.Nsig)
	return
}

func Test_cxint01(tst *testing.T) {

	//verbose()
	chk.PrintTitle("cxint01")

	var ops OpsData
	ops.SetDefault()
	ops.Pc = 1
	ops.Ncuts = 1

	A := []int{1, 2}
	B := []int{-1, -2}
	a := make([]int, len(A))
	b := make([]int, len(A))
	IntCrossover(a, b, A, B, 0, &ops)
	io.Pfred("A = %2d\n", A)
	io.PfRed("B = %2d\n", B)
	io.Pfcyan("a = %2d\n", a)
	io.Pfblue2("b = %2d\n", b)
	chk.Ints(tst, "a", a, []int{1, -2})
	chk.Ints(tst, "b", b, []int{-1, 2})
	io.Pf("\n")

	A = []int{1, 2, 3, 4, 5, 6, 7, 8}
	B = []int{-1, -2, -3, -4, -5, -6, -7, -8}
	a = make([]int, len(A))
	b = make([]int, len(A))
	ops.Cuts = []int{1, 3}
	IntCrossover(a, b, A, B, 0, &ops)
	io.Pfred("A = %2v\n", A)
	io.PfRed("B = %2v\n", B)
	io.Pfcyan("a = %2v\n", a)
	io.Pfblue2("b = %2v\n", b)
	chk.Ints(tst, "a", a, []int{1, -2, -3, 4, 5, 6, 7, 8})
	chk.Ints(tst, "b", b, []int{-1, 2, 3, -4, -5, -6, -7, -8})

	ops.Cuts = []int{5, 7}
	IntCrossover(a, b, A, B, 0, &ops)
	io.Pfred("A = %2v\n", A)
	io.PfRed("B = %2v\n", B)
	io.Pfcyan("a = %2v\n", a)
	io.Pfblue2("b = %2v\n", b)
	chk.Ints(tst, "a", a, []int{1, 2, 3, 4, 5, -6, -7, 8})
	chk.Ints(tst, "b", b, []int{-1, -2, -3, -4, -5, 6, 7, -8})
}

// rjoint_DebugKb defines a global function to debug Kb for rjoint-elements
func rjoint_DebugKb(fem *FEM, o *testKb) {
	fem.DebugKb = func(d *Domain, it int) {

		elem := d.Elems[o.eid]
		if e, ok := elem.(*Rjoint); ok {

			// skip?
			o.it = it
			o.t = d.Sol.T
			if o.skip() {
				return
			}

			// copy states and solution
			nip := len(e.Rod.IpsElem)
			states := make([]*msolid.OnedState, nip)
			statesBkp := make([]*msolid.OnedState, nip)
			for i := 0; i < nip; i++ {
				states[i] = e.States[i].GetCopy()
				statesBkp[i] = e.StatesBkp[i].GetCopy()
			}
			o.aux_arrays(d)

			// make sure to restore states and solution
			defer func() {
				for i := 0; i < nip; i++ {
					e.States[i].Set(states[i])
					e.StatesBkp[i].Set(statesBkp[i])
				}
				copy(d.Sol.ΔY, o.ΔYbkp)
			}()

			// define restore function
			restore := func() {
				if it == 0 {
					for k := 0; k < nip; k++ {
						e.States[k].Set(states[k])
					}
					return
				}
				for k := 0; k < nip; k++ {
					e.States[k].Set(statesBkp[k])
				}
			}

			// check
			o.check("Krr", d, e, e.Rod.Umap, e.Rod.Umap, e.Krr, restore)
			o.check("Krs", d, e, e.Rod.Umap, e.Sld.Umap, e.Krs, restore)
			o.check("Ksr", d, e, e.Sld.Umap, e.Rod.Umap, e.Ksr, restore)
			o.check("Kss", d, e, e.Sld.Umap, e.Sld.Umap, e.Kss, restore)
		} else {
			io.Pfred("warning: eid=%d does not correspond to Rjoint element\n", o.eid)
		}
	}
	return
}

// DistPointLine computes the distance from p to line passing through a -> b
func DistPointLine(p, a, b *Point, tol float64, verbose bool) float64 {
	ns := NewSegment(a, b)
	vs := NewSegment(p, a)
	nn := ns.Len()
	if nn < tol { // point-point distance
		if verbose {
			io.Pfred("basicgeom.go: DistPointLine: __WARNING__ point-point distance too small:\n p=%v a=%v b=%v\n", p, a, b)
		}
		return vs.Len()
	}
	n := ns.Vector(1.0 / nn)
	v := vs.Vector(1.0)
	s := VecDot(v, n)
	l := VecNewAdd(1, v, -s, n) // l := v - dot(v,n) * n
	return VecNorm(l)
}

func Test_bspline02(tst *testing.T) {

	//verbose()
	chk.PrintTitle("bspline02")

	//               0 1 2 3 4 5 6 7 8 9 10
	T := []float64{0, 0, 0, 1, 2, 3, 4, 4, 5, 5, 5}
	sol := []int{2, 2, 3, 3, 4, 4, 5, 5, 7, 7, 7}
	var s Bspline
	s.Init(T, 2)
	s.SetControl([][]float64{{0, 0}, {0.5, 1}, {1, 0}, {1.5, 0}, {2, 1}, {2.5, 1}, {3, 0.5}, {3.5, 0}})

	tt := utl.LinSpace(0, 5, 11)
	for k, t := range tt {
		span := s.find_span(t)
		io.Pforan("t=%.4f  =>  span=%v\n", t, span)
		if span != sol[k] {
			chk.Panic("find_span failed: t=%v  span => %d != %d", t, span, sol[k])
		}
	}

	tol := 1e-14
	np := len(tt)
	xx, yy := make([]float64, np), make([]float64, np)
	for k, t := range tt {
		t0 := time.Now()
		pa := s.Point(t, 0) // 0 => CalcBasis
		io.Pf("Point(rec): dtime = %v\n", time.Now().Sub(t0))
		t0 = time.Now()
		pb := s.Point(t, 1) // 1 => RecursiveBasis
		io.Pf("Point:      dtime = %v\n", time.Now().Sub(t0))
		xx[k], yy[k] = pb[0], pb[1]
		io.Pfred("pa - pb = %v, %v\n", pa[0]-pb[0], pa[1]-pb[1])
		chk.Vector(tst, "Point", tol, pa, pb)
	}

	if chk.Verbose {
		npts := 201
		plt.SetForPng(0.75, 300, 150)
		str0 := ",lw=2"
		str1 := ",ls='none',marker='+',color='cyan',markevery=10"
		s.Draw2d(str0, "", npts, 0) // 0 => CalcBasis
		s.Draw2d(str1, "", npts, 1) // 1 => RecursiveBasis
		plt.Plot(xx, yy, "'bo', clip_on=0")
		plt.SaveD("/tmp/gosl/gm", "bspline02.png")
	}
}

func Test_bh14c(tst *testing.T) {

	//verbose()
	chk.PrintTitle("bh14c. using go-routines")

	// channels
	nch := 2
	done := make(chan int, nch)

	// allocate structures and set stage
	analyses := make([]*FEM, nch)
	for i := 0; i < nch; i++ {
		analyses[i] = NewFEM("data/bh14.sim", io.Sf("ch%d", i), true, true, false, false, false, i)
		err := analyses[i].SetStage(0)
		if err != nil {
			tst.Errorf("SetStage failed:\n%v", err)
			return
		}
	}

	// run all analyses
	for i := 0; i < nch; i++ {
		go func(analysis *FEM) {
			err := analysis.SolveOneStage(0, true)
			if err != nil {
				io.Pfred("SolveOneStage failed:\n%v", err)
			}
			done <- 1
		}(analyses[i])
	}

	// wait
	for i := 0; i < nch; i++ {
		<-done
	}

	// check
	skipK := false
	tolK := 1e-10
	tolu := 1e-15
	tols := 1e-13
	for i := 0; i < nch; i++ {
		TestingCompareResultsU(tst, "data/bh14.sim", "cmp/bh14.cmp", io.Sf("ch%d", i), tolK, tolu, tols, skipK, chk.Verbose)
	}
}

// StatF1F0 prints statistical analysis for two-objective problems
//  emin, eave, emax, edev -- errors on f1(f0)
//  lmin, lave, lmax, ldev -- arc-lengths along f1(f0) curve
func StatF1F0(o *Optimiser, verbose bool) (emin, eave, emax, edev float64, E []float64, lmin, lave, lmax, ldev float64, L []float64) {
	if len(o.F1F0_err) == 0 && len(o.F1F0_arcLen) == 0 {
		io.Pfred("there are no samples for statistical analysis\n")
		return
	}
	o.fix_formatting_data()
	if len(o.F1F0_err) > 2 {
		E = make([]float64, len(o.F1F0_err))
		copy(E, o.F1F0_err)
		emin, eave, emax, edev = rnd.StatBasic(E, true)
		if verbose {
			io.Pf("\nerror on Pareto front\n")
			io.Pf("emin = %g\n", emin)
			io.Pf("eave = %g\n", eave)
			io.Pf("emax = %g\n", emax)
			io.Pf("edev = %g\n", edev)
			io.Pf(rnd.BuildTextHist(nice(emin, o.HistNdig)-o.HistDelEmin, nice(emax, o.HistNdig)+o.HistDelEmax,
				o.HistNsta, E, o.HistFmt, o.HistLen))
		}
	}
	if len(o.F1F0_arcLen) > 2 {
		den := 1.0
		if o.F1F0_arcLenRef > 0 {
			den = o.F1F0_arcLenRef
		}
		L := make([]float64, len(o.F1F0_arcLen))
		for i, l := range o.F1F0_arcLen {
			L[i] = l / den
		}
		lmin, lave, lmax, ldev = rnd.StatBasic(L, true)
		if verbose {
			io.Pf("\nnormalised arc length along Pareto front (ref = %g)\n", o.F1F0_arcLenRef)
			io.Pf("lmin = %g\n", lmin)
			io.Pf("lave = %g\n", lave)
			io.Pf("lmax = %g\n", lmax)
			io.Pf("ldev = %g\n", ldev)
			io.Pf(rnd.BuildTextHist(nice(lmin, o.HistNdig)-o.HistDelEmin, nice(lmax, o.HistNdig)+o.HistDelEmax,
				o.HistNsta, L, o.HistFmt, o.HistLen))
		}
	}
	return
}

func (o *RichardsonExtrap) divergence_control(d *Domain, name string) (docontinue bool) {
	if o.diverging {
		if Global.Verbose {
			io.Pfred(". . . %s: iterations diverging (%2d) . . .\n", name, o.ndiverg+1)
		}
		d.restore()
		o.Δtcpy = o.Δt
		o.Δt *= 0.5
		o.ndiverg += 1
		o.nreject += 1
		o.laststep = false
		o.prevdiv = true
		return true
	}
	if o.prevdiv && false {
		o.Δt = o.Δtcpy
		o.ndiverg = 0
		o.prevdiv = false
	}
	return false
}

// Update updates state
func (o *PrincStrainsUp) Update(s *State, ε, Δε []float64, eid, ipid int, time float64) (err error) {

	// debugging
	if o.DbgOn {
		o.dbg_init(s, ε, Δε, eid, ipid)
	}

	// trial strains
	for i := 0; i < o.Nsig; i++ {
		s.EpsE[i] += Δε[i]
	}
	copy(s.EpsTr, s.EpsE)

	// eigenvalues/projectors of trial elastic strain
	err = tsr.M_EigenValsProjsNum(o.P, o.Lεetr, s.EpsTr)
	if err != nil {
		return
	}

	// trial stresses
	o.Mdl.E_CalcSig(o.Lσ, o.Lεetr)

	// debugging
	if o.DbgOn {
		defer o.dbg_end(s, ε, eid, ipid)() // TODO: fix this
	}

	// check loading condition => elastic update?
	ftr := o.Mdl.L_YieldFunc(o.Lσ, s.Alp)
	if ftr <= o.Fzero {
		s.Dgam = 0
		s.Loading = false
		for i := 0; i < o.Nsig; i++ {
			s.Sig[i] = o.Lσ[0]*o.P[0][i] + o.Lσ[1]*o.P[1][i] + o.Lσ[2]*o.P[2][i]
		}
		return
	}

	// initial values
	for i := 0; i < 3; i++ {
		o.x[i] = o.Lεetr[i]
	}
	for i := 0; i < o.Nalp; i++ {
		o.αn[i] = s.Alp[i]
		o.x[3+i] = s.Alp[i]
	}
	o.x[3+o.Nalp] = 0 // Δγ

	// check Jacobian
	if o.ChkJac {
		var cnd float64
		cnd, err = o.nls.CheckJ(o.x, o.ChkJacTol, true, o.ChkSilent)
		io.Pfred("before: cnd(J) = %v\n", cnd)
	}

	// modify b
	bsmp := o.Mdl.Get_bsmp()
	if bsmp > 0 && o.Nbsmp > 1 {
		o.Mdl.Set_bsmp(0)
		defer func() { o.Mdl.Set_bsmp(bsmp) }()
		δb := bsmp / float64(o.Nbsmp-1)
		for i := 0; i < o.Nbsmp; i++ {
			b := float64(i) * δb
			err = o.do_solve(b, eid, ipid, time)
			if err != nil {
				return
			}
		}
	} else {
		err = o.do_solve(bsmp, eid, ipid, time)
		if err != nil {
			return
		}
	}

	// check Jacobian again
	if o.ChkJac {
		var cnd float64
		cnd, err = o.nls.CheckJ(o.x, o.ChkJacTol, true, o.ChkSilent)
		io.Pfred("after: cnd(J) = %v\n", cnd)
		if err != nil {
			return
		}
	}

	// set new state
	εe, α, Δγ := o.x[:3], o.x[3:3+o.Nalp], o.x[3+o.Nalp]
	o.Mdl.E_CalcSig(o.Lσ, εe)
	for i := 0; i < o.Nsig; i++ {
		s.Sig[i] = o.Lσ[0]*o.P[0][i] + o.Lσ[1]*o.P[1][i] + o.Lσ[2]*o.P[2][i]
		s.EpsE[i] = εe[0]*o.P[0][i] + εe[1]*o.P[1][i] + εe[2]*o.P[2][i]
	}
	copy(s.Alp, α)
	s.Dgam = Δγ
	s.Loading = true
	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()
				}
			}
		}
	}
}