func _TestPartition1Dh(t *testing.T) {
var AL, AR, A0, a1, A2 matrix.FloatMatrix
A := matrix.FloatZeros(1, 6)
partition1x2(&AL, &AR, A, 0, pRIGHT)
t.Logf("m(AL)=%d, m(AR)=%d\n", AL.Cols(), AR.Cols())
for AL.Cols() < A.Cols() {
AR.Add(1.0)
t.Logf("m(AR)=%d; %v\n", AR.Cols(), AR)
repartition1x2to1x3(&AL, &A0, &a1, &A2, A, 1, pRIGHT)
t.Logf("m(A0)=%d, m(A2)=%d, a1=%.1f\n", A0.Cols(), A2.Cols(), a1.Float())
continue1x3to1x2(&AL, &AR, &A0, &a1, A, pRIGHT)
}
}
func (F *cpProg) F1(xa MatrixVariable) (f MatrixVariable, Df MatrixVarDf, err error) {
f = nil
Df = nil
err = nil
x, x_ok := xa.(*epigraph)
if !x_ok {
err = errors.New("'x' argument not an epigraph")
}
var f0, Df0 *matrix.FloatMatrix
f0, Df0, err = F.convexF.F1(x.m())
if err != nil {
fmt.Printf("'cpProg.F1' error: %v\n%s\n", err, x)
return
}
f0.Add(-x.t(), 0)
f = &matrixVar{f0}
Df = &epigraphDf{Df0}
return
}
func (F *cpProg) F2(xa MatrixVariable, z *matrix.FloatMatrix) (f MatrixVariable, Df MatrixVarDf, H MatrixVarH, err error) {
f = nil
Df = nil
H = nil
err = nil
x, x_ok := xa.(*epigraph)
if !x_ok {
err = errors.New("'x' argument not an epigraph")
return
}
var f0, Df0, H0 *matrix.FloatMatrix
f0, Df0, H0, err = F.convexF.F2(x.m(), z)
if err != nil {
return
}
f0.Add(-x.t(), 0)
f = &matrixVar{f0}
Df = &epigraphDf{Df0}
H = &epigraphH{H0}
return
}
func _TestPartition2D(t *testing.T) {
var ATL, ATR, ABL, ABR, As matrix.FloatMatrix
var A00, a01, A02, a10, a11, a12, A20, a21, A22 matrix.FloatMatrix
A := matrix.FloatZeros(6, 6)
As.SubMatrixOf(A, 1, 1, 4, 4)
As.SetIndexes(1.0)
partition2x2(&ATL, &ATR, &ABL, &ABR, &As, 0)
t.Logf("ATL:\n%v\n", &ATL)
for ATL.Rows() < As.Rows() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
&a10, &a11, &a12,
&A20, &a21, &A22, &As, 1)
t.Logf("m(a12)=%d [%d], m(a11)=%d\n", a12.Cols(), a12.NumElements(), a11.NumElements())
a11.Add(1.0)
a21.Add(-2.0)
continue3x3to2x2(&ATL, &ATR, &ABL, &ABR, &A00, &a11, &A22, &As)
}
t.Logf("A:\n%v\n", A)
}
// unblocked LU decomposition with pivots: FLAME LU variant 3
func unblockedLUpiv(A *matrix.FloatMatrix, p *pPivots) error {
var err error
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a10, a11, a12, A20, a21, A22 matrix.FloatMatrix
var AL, AR, A0, a1, A2, aB1, AB0 matrix.FloatMatrix
var pT, pB, p0, p1, p2 pPivots
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
partition1x2(
&AL, &AR, A, 0, pLEFT)
partitionPivot2x1(
&pT,
&pB, p, 0, pTOP)
for ATL.Rows() < A.Rows() && ATL.Cols() < A.Cols() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
&a10, &a11, &a12,
&A20, &a21, &A22 /**/, A, 1, pBOTTOMRIGHT)
repartition1x2to1x3(&AL,
&A0, &a1, &A2 /**/, A, 1, pRIGHT)
repartPivot2x1to3x1(&pT,
&p0, &p1, &p2 /**/, p, 1, pBOTTOM)
// apply previously computed pivots
applyPivots(&a1, &p0)
// a01 = trilu(A00) \ a01 (TRSV)
MVSolveTrm(&a01, &A00, 1.0, LOWER|UNIT)
// a11 = a11 - a10 *a01
a11.Add(Dot(&a10, &a01, -1.0))
// a21 = a21 -A20*a01
MVMult(&a21, &A20, &a01, -1.0, 1.0, NOTRANS)
// pivot index on current column [a11, a21].T
aB1.SubMatrixOf(&ABR, 0, 0, ABR.Rows(), 1)
pivotIndex(&aB1, &p1)
// pivots to current column
applyPivots(&aB1, &p1)
// a21 = a21 / a11
InvScale(&a21, a11.Float())
// apply pivots to previous columns
AB0.SubMatrixOf(&ABL, 0, 0)
applyPivots(&AB0, &p1)
// scale last pivots to origin matrix row numbers
p1.pivots[0] += ATL.Rows()
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
continue1x3to1x2(
&AL, &AR, &A0, &a1, A, pRIGHT)
contPivot3x1to2x1(
&pT,
&pB, &p0, &p1, p, pBOTTOM)
}
if ATL.Cols() < A.Cols() {
applyPivots(&ATR, p)
SolveTrm(&ATR, &ATL, 1.0, LEFT|UNIT|LOWER)
}
return err
}
func coneqp_solver(P MatrixVarP, q MatrixVariable, G MatrixVarG, h *matrix.FloatMatrix,
A MatrixVarA, b MatrixVariable, dims *sets.DimensionSet, kktsolver KKTConeSolverVar,
solopts *SolverOptions, initvals *sets.FloatMatrixSet) (sol *Solution, err error) {
err = nil
EXPON := 3
STEP := 0.99
sol = &Solution{Unknown,
nil,
0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0}
//var kktsolver func(*sets.FloatMatrixSet)(KKTFunc, error) = nil
var refinement int
var correction bool = true
feasTolerance := FEASTOL
absTolerance := ABSTOL
relTolerance := RELTOL
maxIter := MAXITERS
if solopts.FeasTol > 0.0 {
feasTolerance = solopts.FeasTol
}
if solopts.AbsTol > 0.0 {
absTolerance = solopts.AbsTol
}
if solopts.RelTol > 0.0 {
relTolerance = solopts.RelTol
}
if solopts.MaxIter > 0 {
maxIter = solopts.MaxIter
}
if q == nil {
err = errors.New("'q' must be non-nil MatrixVariable with one column")
return
}
if h == nil {
h = matrix.FloatZeros(0, 1)
}
if h.Cols() != 1 {
err = errors.New("'h' must be non-nil matrix with one column")
return
}
if dims == nil {
dims = sets.NewDimensionSet("l", "q", "s")
dims.Set("l", []int{h.Rows()})
}
err = checkConeQpDimensions(dims)
if err != nil {
return
}
cdim := dims.Sum("l", "q") + dims.SumSquared("s")
//cdim_pckd := dims.Sum("l", "q") + dims.SumPacked("s")
cdim_diag := dims.Sum("l", "q", "s")
if h.Rows() != cdim {
err = errors.New(fmt.Sprintf("'h' must be float matrix of size (%d,1)", cdim))
return
}
// Data for kth 'q' constraint are found in rows indq[k]:indq[k+1] of G.
indq := make([]int, 0)
indq = append(indq, dims.At("l")[0])
for _, k := range dims.At("q") {
indq = append(indq, indq[len(indq)-1]+k)
}
// Data for kth 's' constraint are found in rows inds[k]:inds[k+1] of G.
inds := make([]int, 0)
inds = append(inds, indq[len(indq)-1])
for _, k := range dims.At("s") {
inds = append(inds, inds[len(inds)-1]+k*k)
}
if P == nil {
err = errors.New("'P' must be non-nil MatrixVarP interface.")
return
}
fP := func(u, v MatrixVariable, alpha, beta float64) error {
return P.Pf(u, v, alpha, beta)
}
if G == nil {
err = errors.New("'G' must be non-nil MatrixG interface.")
return
}
fG := func(x, y MatrixVariable, alpha, beta float64, trans la.Option) error {
return G.Gf(x, y, alpha, beta, trans)
}
// Check A and set defaults if it is nil
fA := func(x, y MatrixVariable, alpha, beta float64, trans la.Option) error {
return A.Af(x, y, alpha, beta, trans)
}
// Check b and set defaults if it is nil
if b == nil {
err = errors.New("'b' must be non-nil MatrixVariable interface.")
return
}
// kktsolver(W) returns a routine for solving 3x3 block KKT system
//
// [ 0 A' G'*W^{-1} ] [ ux ] [ bx ]
// [ A 0 0 ] [ uy ] = [ by ].
// [ G 0 -W' ] [ uz ] [ bz ]
if kktsolver == nil {
err = errors.New("nil kktsolver not allowed.")
return
}
ws3 := matrix.FloatZeros(cdim, 1)
wz3 := matrix.FloatZeros(cdim, 1)
checkpnt.AddMatrixVar("ws3", ws3)
checkpnt.AddMatrixVar("wz3", wz3)
//
res := func(ux, uy MatrixVariable, uz, us *matrix.FloatMatrix, vx, vy MatrixVariable, vz, vs *matrix.FloatMatrix, W *sets.FloatMatrixSet, lmbda *matrix.FloatMatrix) (err error) {
// Evaluates residual in Newton equations:
//
// [ vx ] [ vx ] [ 0 ] [ P A' G' ] [ ux ]
// [ vy ] := [ vy ] - [ 0 ] - [ A 0 0 ] * [ uy ]
// [ vz ] [ vz ] [ W'*us ] [ G 0 0 ] [ W^{-1}*uz ]
//
// vs := vs - lmbda o (uz + us).
// vx := vx - P*ux - A'*uy - G'*W^{-1}*uz
minor := checkpnt.MinorTop()
checkpnt.Check("00res", minor)
fP(ux, vx, -1.0, 1.0)
fA(uy, vx, -1.0, 1.0, la.OptTrans)
blas.Copy(uz, wz3)
scale(wz3, W, true, false)
fG(&matrixVar{wz3}, vx, -1.0, 1.0, la.OptTrans)
// vy := vy - A*ux
fA(ux, vy, -1.0, 1.0, la.OptNoTrans)
checkpnt.Check("50res", minor)
// vz := vz - G*ux - W'*us
fG(ux, &matrixVar{vz}, -1.0, 1.0, la.OptNoTrans)
blas.Copy(us, ws3)
scale(ws3, W, true, false)
blas.AxpyFloat(ws3, vz, -1.0)
// vs := vs - lmbda o (uz + us)
blas.Copy(us, ws3)
blas.AxpyFloat(uz, ws3, 1.0)
sprod(ws3, lmbda, dims, 0, la.OptDiag)
blas.AxpyFloat(ws3, vs, -1.0)
checkpnt.Check("90res", minor)
return
}
resx0 := math.Max(1.0, math.Sqrt(q.Dot(q)))
resy0 := math.Max(1.0, math.Sqrt(b.Dot(b)))
resz0 := math.Max(1.0, snrm2(h, dims, 0))
//fmt.Printf("resx0: %.17f, resy0: %.17f, resz0: %.17f\n", resx0, resy0, resz0)
var x, y, dx, dy, rx, ry MatrixVariable
var z, s, ds, dz, rz *matrix.FloatMatrix
var lmbda, lmbdasq, sigs, sigz *matrix.FloatMatrix
var W *sets.FloatMatrixSet
var f, f3 KKTFuncVar
var resx, resy, resz, step, sigma, mu, eta float64
var gap, pcost, dcost, relgap, pres, dres, f0 float64
if cdim == 0 {
// Solve
//
// [ P A' ] [ x ] [ -q ]
// [ ] [ ] = [ ].
// [ A 0 ] [ y ] [ b ]
//
Wtmp := sets.NewFloatSet("d", "di", "beta", "v", "r", "rti")
Wtmp.Set("d", matrix.FloatZeros(0, 1))
Wtmp.Set("di", matrix.FloatZeros(0, 1))
f3, err = kktsolver(Wtmp)
if err != nil {
s := fmt.Sprintf("kkt error: %s", err)
err = errors.New("2: Rank(A) < p or Rank(([P; A; G;]) < n : " + s)
return
}
x = q.Copy()
x.Scal(0.0)
y = b.Copy()
f3(x, y, matrix.FloatZeros(0, 1))
// dres = || P*x + q + A'*y || / resx0
rx = q.Copy()
fP(x, rx, 1.0, 1.0)
pcost = 0.5 * (x.Dot(rx) + x.Dot(q))
fA(y, rx, 1.0, 1.0, la.OptTrans)
dres = math.Sqrt(rx.Dot(rx) / resx0)
ry = b.Copy()
fA(x, ry, 1.0, -1.0, la.OptNoTrans)
pres = math.Sqrt(ry.Dot(ry) / resy0)
relgap = 0.0
if pcost == 0.0 {
relgap = math.NaN()
}
sol.Result = sets.NewFloatSet("x", "y", "s", "z")
sol.Result.Set("x", x.Matrix())
sol.Result.Set("y", y.Matrix())
sol.Result.Set("s", matrix.FloatZeros(0, 1))
sol.Result.Set("z", matrix.FloatZeros(0, 1))
sol.Status = Optimal
sol.Gap = 0.0
sol.RelativeGap = relgap
sol.PrimalObjective = pcost
sol.DualObjective = pcost
sol.PrimalInfeasibility = pres
sol.DualInfeasibility = dres
sol.PrimalSlack = 0.0
sol.DualSlack = 0.0
return
}
x = q.Copy()
y = b.Copy()
s = matrix.FloatZeros(cdim, 1)
z = matrix.FloatZeros(cdim, 1)
checkpnt.AddVerifiable("x", x)
checkpnt.AddVerifiable("y", y)
checkpnt.AddMatrixVar("s", s)
checkpnt.AddMatrixVar("z", z)
var ts, tz, nrms, nrmz float64
if initvals == nil {
// Factor
//
// [ 0 A' G' ]
// [ A 0 0 ].
// [ G 0 -I ]
//
W = sets.NewFloatSet("d", "di", "v", "beta", "r", "rti")
W.Set("d", matrix.FloatOnes(dims.At("l")[0], 1))
W.Set("di", matrix.FloatOnes(dims.At("l")[0], 1))
W.Set("beta", matrix.FloatOnes(len(dims.At("q")), 1))
for _, n := range dims.At("q") {
vm := matrix.FloatZeros(n, 1)
vm.SetIndex(0, 1.0)
W.Append("v", vm)
}
for _, n := range dims.At("s") {
W.Append("r", matrix.FloatIdentity(n))
W.Append("rti", matrix.FloatIdentity(n))
}
checkpnt.AddScaleVar(W)
f, err = kktsolver(W)
if err != nil {
s := fmt.Sprintf("kkt error: %s", err)
err = errors.New("3: Rank(A) < p or Rank([P; G; A]) < n : " + s)
return
}
// Solve
//
// [ P A' G' ] [ x ] [ -q ]
// [ A 0 0 ] * [ y ] = [ b ].
// [ G 0 -I ] [ z ] [ h ]
mCopy(q, x)
x.Scal(-1.0)
mCopy(b, y)
blas.Copy(h, z)
checkpnt.Check("00init", 1)
err = f(x, y, z)
if err != nil {
s := fmt.Sprintf("kkt error: %s", err)
err = errors.New("4: Rank(A) < p or Rank([P; G; A]) < n : " + s)
return
}
blas.Copy(z, s)
blas.ScalFloat(s, -1.0)
checkpnt.Check("05init", 1)
nrms = snrm2(s, dims, 0)
ts, _ = maxStep(s, dims, 0, nil)
//fmt.Printf("nrms = %.7f, ts = %.7f\n", nrms, ts)
if ts >= -1e-8*math.Max(nrms, 1.0) {
// a = 1.0 + ts
a := 1.0 + ts
is := make([]int, 0)
// indexes s[:dims['l']]
is = append(is, matrix.MakeIndexSet(0, dims.At("l")[0], 1)...)
// indexes s[indq[:-1]]
is = append(is, indq[:len(indq)-1]...)
ind := dims.Sum("l", "q")
// indexes s[ind:ind+m*m:m+1] (diagonal)
for _, m := range dims.At("s") {
is = append(is, matrix.MakeIndexSet(ind, ind+m*m, m+1)...)
ind += m * m
}
for _, k := range is {
s.SetIndex(k, a+s.GetIndex(k))
}
}
nrmz = snrm2(z, dims, 0)
tz, _ = maxStep(z, dims, 0, nil)
//fmt.Printf("nrmz = %.7f, tz = %.7f\n", nrmz, tz)
if tz >= -1e-8*math.Max(nrmz, 1.0) {
a := 1.0 + tz
is := make([]int, 0)
is = append(is, matrix.MakeIndexSet(0, dims.At("l")[0], 1)...)
is = append(is, indq[:len(indq)-1]...)
ind := dims.Sum("l", "q")
for _, m := range dims.At("s") {
is = append(is, matrix.MakeIndexSet(ind, ind+m*m, m+1)...)
ind += m * m
}
for _, k := range is {
z.SetIndex(k, a+z.GetIndex(k))
}
}
} else {
ix := initvals.At("x")[0]
if ix != nil {
mCopy(&matrixVar{ix}, x)
} else {
x.Scal(0.0)
}
is := initvals.At("s")[0]
if is != nil {
blas.Copy(is, s)
} else {
iset := make([]int, 0)
iset = append(iset, matrix.MakeIndexSet(0, dims.At("l")[0], 1)...)
iset = append(iset, indq[:len(indq)-1]...)
ind := dims.Sum("l", "q")
for _, m := range dims.At("s") {
iset = append(iset, matrix.MakeIndexSet(ind, ind+m*m, m+1)...)
ind += m * m
}
for _, k := range iset {
s.SetIndex(k, 1.0)
}
}
iy := initvals.At("y")[0]
if iy != nil {
mCopy(&matrixVar{iy}, y)
} else {
y.Scal(0.0)
}
iz := initvals.At("z")[0]
if iz != nil {
blas.Copy(iz, z)
} else {
iset := make([]int, 0)
iset = append(iset, matrix.MakeIndexSet(0, dims.At("l")[0], 1)...)
iset = append(iset, indq[:len(indq)-1]...)
ind := dims.Sum("l", "q")
for _, m := range dims.At("s") {
iset = append(iset, matrix.MakeIndexSet(ind, ind+m*m, m+1)...)
ind += m * m
}
for _, k := range iset {
z.SetIndex(k, 1.0)
}
}
}
rx = q.Copy()
ry = b.Copy()
rz = matrix.FloatZeros(cdim, 1)
dx = x.Copy()
dy = y.Copy()
dz = matrix.FloatZeros(cdim, 1)
ds = matrix.FloatZeros(cdim, 1)
lmbda = matrix.FloatZeros(cdim_diag, 1)
lmbdasq = matrix.FloatZeros(cdim_diag, 1)
sigs = matrix.FloatZeros(dims.Sum("s"), 1)
sigz = matrix.FloatZeros(dims.Sum("s"), 1)
checkpnt.AddVerifiable("rx", rx)
checkpnt.AddVerifiable("ry", ry)
checkpnt.AddVerifiable("dx", dx)
checkpnt.AddVerifiable("dy", dy)
//checkpnt.AddMatrixVar("rs", rs)
checkpnt.AddMatrixVar("rz", rz)
checkpnt.AddMatrixVar("ds", ds)
checkpnt.AddMatrixVar("dz", dz)
checkpnt.AddMatrixVar("lmbda", lmbda)
checkpnt.AddMatrixVar("lmbdasq", lmbdasq)
//var resx, resy, resz, step, sigma, mu, eta float64
//var gap, pcost, dcost, relgap, pres, dres, f0 float64
checkpnt.AddFloatVar("resx", &resx)
checkpnt.AddFloatVar("resy", &resy)
checkpnt.AddFloatVar("resz", &resz)
checkpnt.AddFloatVar("step", &step)
checkpnt.AddFloatVar("gap", &gap)
checkpnt.AddFloatVar("dcost", &dcost)
checkpnt.AddFloatVar("pcost", &pcost)
checkpnt.AddFloatVar("dres", &dres)
checkpnt.AddFloatVar("pres", &pres)
checkpnt.AddFloatVar("relgap", &relgap)
checkpnt.AddFloatVar("sigma", &sigma)
var WS fVarClosure
gap = sdot(s, z, dims, 0)
for iter := 0; iter < maxIter+1; iter++ {
checkpnt.MajorNext()
checkpnt.Check("loopstart", 10)
// f0 = (1/2)*x'*P*x + q'*x + r and rx = P*x + q + A'*y + G'*z.
mCopy(q, rx)
fP(x, rx, 1.0, 1.0)
f0 = 0.5 * (x.Dot(rx) + x.Dot(q))
fA(y, rx, 1.0, 1.0, la.OptTrans)
fG(&matrixVar{z}, rx, 1.0, 1.0, la.OptTrans)
resx = math.Sqrt(rx.Dot(rx))
// ry = A*x - b
mCopy(b, ry)
fA(x, ry, 1.0, -1.0, la.OptNoTrans)
resy = math.Sqrt(ry.Dot(ry))
// rz = s + G*x - h
blas.Copy(s, rz)
blas.AxpyFloat(h, rz, -1.0)
fG(x, &matrixVar{rz}, 1.0, 1.0, la.OptNoTrans)
resz = snrm2(rz, dims, 0)
//fmt.Printf("resx: %.17f, resy: %.17f, resz: %.17f\n", resx, resy, resz)
// Statistics for stopping criteria.
// pcost = (1/2)*x'*P*x + q'*x
// dcost = (1/2)*x'*P*x + q'*x + y'*(A*x-b) + z'*(G*x-h) '
// = (1/2)*x'*P*x + q'*x + y'*(A*x-b) + z'*(G*x-h+s) - z'*s
// = (1/2)*x'*P*x + q'*x + y'*ry + z'*rz - gap
pcost = f0
dcost = f0 + y.Dot(ry) + sdot(z, rz, dims, 0) - gap
if pcost < 0.0 {
relgap = gap / -pcost
} else if dcost > 0.0 {
relgap = gap / dcost
} else {
relgap = math.NaN()
}
pres = math.Max(resy/resy0, resz/resz0)
dres = resx / resx0
if solopts.ShowProgress {
if iter == 0 {
// show headers of something
fmt.Printf("% 10s% 12s% 10s% 8s% 7s\n",
"pcost", "dcost", "gap", "pres", "dres")
}
// show something
fmt.Printf("%2d: % 8.4e % 8.4e % 4.0e% 7.0e% 7.0e\n",
iter, pcost, dcost, gap, pres, dres)
}
checkpnt.Check("stoptest", 100)
if pres <= feasTolerance && dres <= feasTolerance &&
(gap <= absTolerance || (!math.IsNaN(relgap) && relgap <= relTolerance)) ||
iter == maxIter {
ind := dims.Sum("l", "q")
for _, m := range dims.At("s") {
symm(s, m, ind)
symm(z, m, ind)
ind += m * m
}
ts, _ = maxStep(s, dims, 0, nil)
tz, _ = maxStep(z, dims, 0, nil)
if iter == maxIter {
// terminated on max iterations.
sol.Status = Unknown
err = errors.New("Terminated (maximum iterations reached)")
fmt.Printf("Terminated (maximum iterations reached)\n")
return
}
// optimal solution found
//fmt.Print("Optimal solution.\n")
err = nil
sol.Result = sets.NewFloatSet("x", "y", "s", "z")
sol.Result.Set("x", x.Matrix())
sol.Result.Set("y", y.Matrix())
sol.Result.Set("s", s)
sol.Result.Set("z", z)
sol.Status = Optimal
sol.Gap = gap
sol.RelativeGap = relgap
sol.PrimalObjective = pcost
sol.DualObjective = dcost
sol.PrimalInfeasibility = pres
sol.DualInfeasibility = dres
sol.PrimalSlack = -ts
sol.DualSlack = -tz
sol.PrimalResidualCert = math.NaN()
sol.DualResidualCert = math.NaN()
sol.Iterations = iter
return
}
// Compute initial scaling W and scaled iterates:
//
// W * z = W^{-T} * s = lambda.
//
// lmbdasq = lambda o lambda.
if iter == 0 {
W, err = computeScaling(s, z, lmbda, dims, 0)
checkpnt.AddScaleVar(W)
}
ssqr(lmbdasq, lmbda, dims, 0)
f3, err = kktsolver(W)
if err != nil {
if iter == 0 {
s := fmt.Sprintf("kkt error: %s", err)
err = errors.New("5: Rank(A) < p or Rank([P; A; G]) < n : " + s)
return
} else {
ind := dims.Sum("l", "q")
for _, m := range dims.At("s") {
symm(s, m, ind)
symm(z, m, ind)
ind += m * m
}
ts, _ = maxStep(s, dims, 0, nil)
tz, _ = maxStep(z, dims, 0, nil)
// terminated (singular KKT matrix)
fmt.Printf("Terminated (singular KKT matrix).\n")
err = errors.New("Terminated (singular KKT matrix).")
sol.Result = sets.NewFloatSet("x", "y", "s", "z")
sol.Result.Set("x", x.Matrix())
sol.Result.Set("y", y.Matrix())
sol.Result.Set("s", s)
sol.Result.Set("z", z)
sol.Status = Unknown
sol.RelativeGap = relgap
sol.PrimalObjective = pcost
sol.DualObjective = dcost
sol.PrimalInfeasibility = pres
sol.DualInfeasibility = dres
sol.PrimalSlack = -ts
sol.DualSlack = -tz
sol.Iterations = iter
return
}
}
// f4_no_ir(x, y, z, s) solves
//
// [ 0 ] [ P A' G' ] [ ux ] [ bx ]
// [ 0 ] + [ A 0 0 ] * [ uy ] = [ by ]
// [ W'*us ] [ G 0 0 ] [ W^{-1}*uz ] [ bz ]
//
// lmbda o (uz + us) = bs.
//
// On entry, x, y, z, s contain bx, by, bz, bs.
// On exit, they contain ux, uy, uz, us.
f4_no_ir := func(x, y MatrixVariable, z, s *matrix.FloatMatrix) error {
// Solve
//
// [ P A' G' ] [ ux ] [ bx ]
// [ A 0 0 ] [ uy ] = [ by ]
// [ G 0 -W'*W ] [ W^{-1}*uz ] [ bz - W'*(lmbda o\ bs) ]
//
// us = lmbda o\ bs - uz.
//
// On entry, x, y, z, s contains bx, by, bz, bs.
// On exit they contain x, y, z, s.
minor := checkpnt.MinorTop()
checkpnt.Check("f4_no_ir_start", minor)
// s := lmbda o\ s
// = lmbda o\ bs
sinv(s, lmbda, dims, 0)
// z := z - W'*s
// = bz - W'*(lambda o\ bs)
blas.Copy(s, ws3)
scale(ws3, W, true, false)
blas.AxpyFloat(ws3, z, -1.0)
checkpnt.Check("f4_no_ir_f3", minor+50)
err := f3(x, y, z)
if err != nil {
return err
}
checkpnt.Check("f4_no_ir_f3", minor+60)
// s := s - z
// = lambda o\ bs - uz.
blas.AxpyFloat(z, s, -1.0)
checkpnt.Check("f4_no_ir_f3", minor+90)
return nil
}
if iter == 0 {
if refinement > 0 || solopts.Debug {
WS.wx = q.Copy()
WS.wy = y.Copy()
WS.ws = matrix.FloatZeros(cdim, 1)
WS.wz = matrix.FloatZeros(cdim, 1)
checkpnt.AddVerifiable("wx", WS.wx)
checkpnt.AddVerifiable("wy", WS.wy)
checkpnt.AddMatrixVar("ws", WS.ws)
checkpnt.AddMatrixVar("wz", WS.wz)
}
if refinement > 0 {
WS.wx2 = q.Copy()
WS.wy2 = y.Copy()
WS.ws2 = matrix.FloatZeros(cdim, 1)
WS.wz2 = matrix.FloatZeros(cdim, 1)
checkpnt.AddVerifiable("wx2", WS.wx2)
checkpnt.AddVerifiable("wy2", WS.wy2)
checkpnt.AddMatrixVar("ws2", WS.ws2)
checkpnt.AddMatrixVar("wz2", WS.wz2)
}
}
f4 := func(x, y MatrixVariable, z, s *matrix.FloatMatrix) (err error) {
minor := checkpnt.MinorTop()
checkpnt.Check("f4start", minor)
err = nil
if refinement > 0 || solopts.Debug {
mCopy(x, WS.wx)
mCopy(y, WS.wy)
blas.Copy(z, WS.wz)
blas.Copy(s, WS.ws)
}
checkpnt.MinorPush(minor + 100)
err = f4_no_ir(x, y, z, s)
checkpnt.MinorPop()
for i := 0; i < refinement; i++ {
mCopy(WS.wx, WS.wx2)
mCopy(WS.wy, WS.wy2)
blas.Copy(WS.wz, WS.wz2)
blas.Copy(WS.ws, WS.ws2)
checkpnt.MinorPush(minor + (i+1)*300)
res(x, y, z, s, WS.wx2, WS.wy2, WS.wz2, WS.ws2, W, lmbda)
checkpnt.MinorPop()
checkpnt.MinorPush(minor + (i+1)*500)
f4_no_ir(WS.wx2, WS.wy2, WS.wz2, WS.ws2)
checkpnt.MinorPop()
WS.wx2.Axpy(x, 1.0)
WS.wy2.Axpy(y, 1.0)
blas.AxpyFloat(WS.wz2, z, 1.0)
blas.AxpyFloat(WS.ws2, s, 1.0)
}
checkpnt.Check("f4end", minor+1500)
return
}
//var mu, sigma, eta float64
mu = gap / float64(dims.Sum("l", "s")+len(dims.At("q")))
sigma, eta = 0.0, 0.0
for i := 0; i < 2; i++ {
// Solve
//
// [ 0 ] [ P A' G' ] [ dx ]
// [ 0 ] + [ A 0 0 ] * [ dy ] = -(1 - eta) * r
// [ W'*ds ] [ G 0 0 ] [ W^{-1}*dz ]
//
// lmbda o (dz + ds) = -lmbda o lmbda + sigma*mu*e (i=0)
// lmbda o (dz + ds) = -lmbda o lmbda - dsa o dza
// + sigma*mu*e (i=1) where dsa, dza
// are the solution for i=0.
minor_base := (i + 1) * 2000
// ds = -lmbdasq + sigma * mu * e (if i is 0)
// = -lmbdasq - dsa o dza + sigma * mu * e (if i is 1),
// where ds, dz are solution for i is 0.
blas.ScalFloat(ds, 0.0)
if correction && i == 1 {
blas.AxpyFloat(ws3, ds, -1.0)
}
blas.AxpyFloat(lmbdasq, ds, -1.0, &la.IOpt{"n", dims.Sum("l", "q")})
ind := dims.At("l")[0]
ds.Add(sigma*mu, matrix.MakeIndexSet(0, ind, 1)...)
for _, m := range dims.At("q") {
ds.SetIndex(ind, sigma*mu+ds.GetIndex(ind))
ind += m
}
ind2 := ind
for _, m := range dims.At("s") {
blas.AxpyFloat(lmbdasq, ds, -1.0, &la.IOpt{"n", m}, &la.IOpt{"incy", m + 1},
&la.IOpt{"offsetx", ind2}, &la.IOpt{"offsety", ind})
ds.Add(sigma*mu, matrix.MakeIndexSet(ind, ind+m*m, m+1)...)
ind += m * m
ind2 += m
}
checkpnt.Check("00loop01", minor_base)
// (dx, dy, dz) := -(1 - eta) * (rx, ry, rz)
//blas.ScalFloat(dx, 0.0)
//blas.AxpyFloat(rx, dx, -1.0+eta)
dx.Scal(0.0)
rx.Axpy(dx, -1.0+eta)
dy.Scal(0.0)
ry.Axpy(dy, -1.0+eta)
blas.ScalFloat(dz, 0.0)
blas.AxpyFloat(rz, dz, -1.0+eta)
//fmt.Printf("== Calling f4 %d\n", i)
//fmt.Printf("dx=\n%v\n", dx.ToString("%.17f"))
//fmt.Printf("ds=\n%v\n", ds.ToString("%.17f"))
//fmt.Printf("dz=\n%v\n", dz.ToString("%.17f"))
//fmt.Printf("== Entering f4 %d\n", i)
checkpnt.MinorPush(minor_base)
err = f4(dx, dy, dz, ds)
checkpnt.MinorPop()
if err != nil {
if iter == 0 {
s := fmt.Sprintf("kkt error: %s", err)
err = errors.New("6: Rank(A) < p or Rank([P; A; G]) < n : " + s)
return
} else {
ind = dims.Sum("l", "q")
for _, m := range dims.At("s") {
symm(s, m, ind)
symm(z, m, ind)
ind += m * m
}
ts, _ = maxStep(s, dims, 0, nil)
tz, _ = maxStep(z, dims, 0, nil)
return
}
}
dsdz := sdot(ds, dz, dims, 0)
if correction && i == 0 {
blas.Copy(ds, ws3)
sprod(ws3, dz, dims, 0)
}
// Maximum step to boundary.
//
// If i is 1, also compute eigenvalue decomposition of the 's'
// blocks in ds, dz. The eigenvectors Qs, Qz are stored in
// dsk, dzk. The eigenvalues are stored in sigs, sigz.
scale2(lmbda, ds, dims, 0, false)
scale2(lmbda, dz, dims, 0, false)
checkpnt.Check("maxstep", minor_base+1500)
if i == 0 {
ts, _ = maxStep(ds, dims, 0, nil)
tz, _ = maxStep(dz, dims, 0, nil)
} else {
ts, _ = maxStep(ds, dims, 0, sigs)
tz, _ = maxStep(dz, dims, 0, sigz)
}
t := maxvec([]float64{0.0, ts, tz})
//fmt.Printf("== t=%.17f from %v\n", t, []float64{ts, tz})
if t == 0.0 {
step = 1.0
} else {
if i == 0 {
step = math.Min(1.0, 1.0/t)
} else {
step = math.Min(1.0, STEP/t)
}
}
if i == 0 {
m := math.Max(0.0, 1.0-step+dsdz/gap*(step*step))
sigma = math.Pow(math.Min(1.0, m), float64(EXPON))
eta = 0.0
}
//fmt.Printf("== step=%.17f sigma=%.17f dsdz=%.17f\n", step, sigma, dsdz)
}
checkpnt.Check("updatexy", 8000)
dx.Axpy(x, step)
dy.Axpy(y, step)
//fmt.Printf("x=\n%v\n", x.ConvertToString())
//fmt.Printf("y=\n%v\n", y.ConvertToString())
//fmt.Printf("ds=\n%v\n", ds.ConvertToString())
//fmt.Printf("dz=\n%v\n", dz.ConvertToString())
// We will now replace the 'l' and 'q' blocks of ds and dz with
// the updated iterates in the current scaling.
// We also replace the 's' blocks of ds and dz with the factors
// Ls, Lz in a factorization Ls*Ls', Lz*Lz' of the updated variables
// in the current scaling.
// ds := e + step*ds for nonlinear, 'l' and 'q' blocks.
// dz := e + step*dz for nonlinear, 'l' and 'q' blocks.
blas.ScalFloat(ds, step, &la.IOpt{"n", dims.Sum("l", "q")})
blas.ScalFloat(dz, step, &la.IOpt{"n", dims.Sum("l", "q")})
ind := dims.At("l")[0]
is := matrix.MakeIndexSet(0, ind, 1)
ds.Add(1.0, is...)
dz.Add(1.0, is...)
for _, m := range dims.At("q") {
ds.SetIndex(ind, 1.0+ds.GetIndex(ind))
dz.SetIndex(ind, 1.0+dz.GetIndex(ind))
ind += m
}
checkpnt.Check("updatedsdz", 8010)
// ds := H(lambda)^{-1/2} * ds and dz := H(lambda)^{-1/2} * dz.
//
// This replaces the 'l' and 'q' components of ds and dz with the
// updated variables in the current scaling.
// The 's' components of ds and dz are replaced with
//
// diag(lmbda_k)^{1/2} * Qs * diag(lmbda_k)^{1/2}
// diag(lmbda_k)^{1/2} * Qz * diag(lmbda_k)^{1/2}
scale2(lmbda, ds, dims, 0, true)
scale2(lmbda, dz, dims, 0, true)
checkpnt.Check("scale2", 8030)
// sigs := ( e + step*sigs ) ./ lambda for 's' blocks.
// sigz := ( e + step*sigz ) ./ lambda for 's' blocks.
blas.ScalFloat(sigs, step)
blas.ScalFloat(sigz, step)
sigs.Add(1.0)
sigz.Add(1.0)
sdimsum := dims.Sum("s")
qdimsum := dims.Sum("l", "q")
blas.TbsvFloat(lmbda, sigs, &la.IOpt{"n", sdimsum}, &la.IOpt{"k", 0},
&la.IOpt{"lda", 1}, &la.IOpt{"offseta", qdimsum})
blas.TbsvFloat(lmbda, sigz, &la.IOpt{"n", sdimsum}, &la.IOpt{"k", 0},
&la.IOpt{"lda", 1}, &la.IOpt{"offseta", qdimsum})
ind2 := qdimsum
ind3 := 0
sdims := dims.At("s")
for k := 0; k < len(sdims); k++ {
m := sdims[k]
for i := 0; i < m; i++ {
a := math.Sqrt(sigs.GetIndex(ind3 + i))
blas.ScalFloat(ds, a, &la.IOpt{"offset", ind2 + m*i}, &la.IOpt{"n", m})
a = math.Sqrt(sigz.GetIndex(ind3 + i))
blas.ScalFloat(dz, a, &la.IOpt{"offset", ind2 + m*i}, &la.IOpt{"n", m})
}
ind2 += m * m
ind3 += m
}
checkpnt.Check("updatescaling", 8050)
err = updateScaling(W, lmbda, ds, dz)
checkpnt.Check("afterscaling", 8060)
// Unscale s, z, tau, kappa (unscaled variables are used only to
// compute feasibility residuals).
ind = dims.Sum("l", "q")
ind2 = ind
blas.Copy(lmbda, s, &la.IOpt{"n", ind})
for _, m := range dims.At("s") {
blas.ScalFloat(s, 0.0, &la.IOpt{"offset", ind2})
blas.Copy(lmbda, s, &la.IOpt{"offsetx", ind}, &la.IOpt{"offsety", ind2},
&la.IOpt{"n", m}, &la.IOpt{"incy", m + 1})
ind += m
ind2 += m * m
}
scale(s, W, true, false)
ind = dims.Sum("l", "q")
ind2 = ind
blas.Copy(lmbda, z, &la.IOpt{"n", ind})
for _, m := range dims.At("s") {
blas.ScalFloat(z, 0.0, &la.IOpt{"offset", ind2})
blas.Copy(lmbda, z, &la.IOpt{"offsetx", ind}, &la.IOpt{"offsety", ind2},
&la.IOpt{"n", m}, &la.IOpt{"incy", m + 1})
ind += m
ind2 += m * m
}
scale(z, W, false, true)
gap = blas.DotFloat(lmbda, lmbda)
checkpnt.Check("eol", 8900)
//fmt.Printf("== gap = %.17f\n", gap)
}
return
}
