/*
Copy x to y using packed storage.
The vector x is an element of S, with the 's' components stored in
unpacked storage. On return, x is copied to y with the 's' components
stored in packed storage and the off-diagonal entries scaled by
sqrt(2).
*/
func pack(x, y *matrix.FloatMatrix, dims *sets.DimensionSet, opts ...la_.Option) (err error) {
/*DEBUGGED*/
err = nil
mnl := la_.GetIntOpt("mnl", 0, opts...)
offsetx := la_.GetIntOpt("offsetx", 0, opts...)
offsety := la_.GetIntOpt("offsety", 0, opts...)
nlq := mnl + dims.At("l")[0] + dims.Sum("q")
blas.Copy(x, y, &la_.IOpt{"n", nlq}, &la_.IOpt{"offsetx", offsetx},
&la_.IOpt{"offsety", offsety})
iu, ip := offsetx+nlq, offsety+nlq
for _, n := range dims.At("s") {
for k := 0; k < n; k++ {
blas.Copy(x, y, &la_.IOpt{"n", n - k}, &la_.IOpt{"offsetx", iu + k*(n+1)},
&la_.IOpt{"offsety", ip})
y.SetIndex(ip, (y.GetIndex(ip) / math.Sqrt(2.0)))
ip += n - k
}
iu += n * n
}
np := dims.SumPacked("s")
blas.ScalFloat(y, math.Sqrt(2.0), &la_.IOpt{"n", np}, &la_.IOpt{"offset", offsety + nlq})
return
}
// Solves a pair of primal and dual cone programs using custom KKT solver and constraint
// interfaces MatrixG and MatrixA
//
func ConeLpCustomMatrix(c *matrix.FloatMatrix, G MatrixG, h *matrix.FloatMatrix,
A MatrixA, b *matrix.FloatMatrix, dims *sets.DimensionSet, kktsolver KKTConeSolver,
solopts *SolverOptions, primalstart, dualstart *sets.FloatMatrixSet) (sol *Solution, err error) {
err = nil
if c == nil || c.Cols() > 1 {
err = errors.New("'c' must be matrix with 1 column")
return
}
if h == nil || h.Cols() > 1 {
err = errors.New("'h' must be matrix with 1 column")
return
}
if err = checkConeLpDimensions(dims); 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)
}
// Check b and set defaults if it is nil
if b == nil {
b = matrix.FloatZeros(0, 1)
}
if b.Cols() != 1 {
estr := fmt.Sprintf("'b' must be a matrix with 1 column")
err = errors.New(estr)
return
}
if b.Rows() > c.Rows() || b.Rows()+cdim_pckd < c.Rows() {
err = errors.New("Rank(A) < p or Rank([G; A]) < n")
return
}
if kktsolver == nil {
err = errors.New("nil kktsolver not allowed.")
return
}
var mA MatrixVarA
var mG MatrixVarG
if G == nil {
mG = &matrixVarG{matrix.FloatZeros(0, c.Rows()), dims}
} else {
mG = &matrixIfG{G}
}
if A == nil {
mA = &matrixVarA{matrix.FloatZeros(0, c.Rows())}
} else {
mA = &matrixIfA{A}
}
var mc = &matrixVar{c}
var mb = &matrixVar{b}
return conelp_problem(mc, mG, h, mA, mb, dims, kktsolver, solopts, primalstart, dualstart)
}
// Solves a pair of primal and dual cone programs using custom KKT solver.
//
func ConeLpCustomKKT(c, G, h, A, b *matrix.FloatMatrix, dims *sets.DimensionSet,
kktsolver KKTConeSolver, solopts *SolverOptions, primalstart,
dualstart *sets.FloatMatrixSet) (sol *Solution, err error) {
if c == nil || c.Cols() > 1 {
err = errors.New("'c' must be matrix with 1 column")
return
}
if h == nil {
h = matrix.FloatZeros(0, 1)
}
if h.Cols() > 1 {
err = errors.New("'h' must be matrix with 1 column")
return
}
if dims == nil {
dims = sets.NewDimensionSet("l", "q", "s")
dims.Set("l", []int{h.Rows()})
}
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 G == nil {
G = matrix.FloatZeros(0, c.Rows())
}
if !G.SizeMatch(cdim, c.Rows()) {
estr := fmt.Sprintf("'G' must be of size (%d,%d)", cdim, c.Rows())
err = errors.New(estr)
return
}
// Check A and set defaults if it is nil
if A == nil {
// zeros rows reduces Gemv to vector products
A = matrix.FloatZeros(0, c.Rows())
}
if A.Cols() != c.Rows() {
estr := fmt.Sprintf("'A' must have %d columns", c.Rows())
err = errors.New(estr)
return
}
// Check b and set defaults if it is nil
if b == nil {
b = matrix.FloatZeros(0, 1)
}
if b.Cols() != 1 {
estr := fmt.Sprintf("'b' must be a matrix with 1 column")
err = errors.New(estr)
return
}
if b.Rows() != A.Rows() {
estr := fmt.Sprintf("'b' must have length %d", A.Rows())
err = errors.New(estr)
return
}
if b.Rows() > c.Rows() || b.Rows()+cdim_pckd < c.Rows() {
err = errors.New("Rank(A) < p or Rank([G; A]) < n")
return
}
mA := &matrixVarA{A}
mG := &matrixVarG{G, dims}
mc := &matrixVar{c}
mb := &matrixVar{b}
return conelp_problem(mc, mG, h, mA, mb, dims, kktsolver, solopts, primalstart, dualstart)
}
// Solves a pair of primal and dual cone programs
//
// minimize c'*x
// subject to G*x + s = h
// A*x = b
// s >= 0
//
// maximize -h'*z - b'*y
// subject to G'*z + A'*y + c = 0
// z >= 0.
//
// The inequalities are with respect to a cone C defined as the Cartesian
// product of N + M + 1 cones:
//
// C = C_0 x C_1 x .... x C_N x C_{N+1} x ... x C_{N+M}.
//
// The first cone C_0 is the nonnegative orthant of dimension ml.
// The next N cones are second order cones of dimension r[0], ..., r[N-1].
// The second order cone of dimension m is defined as
//
// { (u0, u1) in R x R^{m-1} | u0 >= ||u1||_2 }.
//
// The next M cones are positive semidefinite cones of order t[0], ..., t[M-1] >= 0.
//
// The structure of C is specified by DimensionSet dims which holds following sets
//
// dims.At("l") l, the dimension of the nonnegative orthant (array of length 1)
// dims.At("q") r[0], ... r[N-1], list with the dimesions of the second-order cones
// dims.At("s") t[0], ... t[M-1], array with the dimensions of the positive
// semidefinite cones
//
// The default value for dims is l: []int{G.Rows()}, q: []int{}, s: []int{}.
//
// Arguments primalstart, dualstart are optional starting points for primal and
// dual problems. If non-nil then primalstart is a FloatMatrixSet having two entries.
//
// primalstart.At("x")[0] starting point for x
// primalstart.At("s")[0] starting point for s
// dualstart.At("y")[0] starting point for y
// dualstart.At("z")[0] starting point for z
//
// On exit Solution contains the result and information about the accurancy of the
// solution. if SolutionStatus is Optimal then Solution.Result contains solutions
// for the problems.
//
// Result.At("x")[0] solution for x
// Result.At("y")[0] solution for y
// Result.At("s")[0] solution for s
// Result.At("z")[0] solution for z
//
func ConeLp(c, G, h, A, b *matrix.FloatMatrix, dims *sets.DimensionSet, solopts *SolverOptions,
primalstart, dualstart *sets.FloatMatrixSet) (sol *Solution, err error) {
if c == nil || c.Cols() > 1 {
err = errors.New("'c' must be matrix with 1 column")
return
}
if c.Rows() < 1 {
err = errors.New("No variables, 'c' must have at least one row")
return
}
if h == nil || h.Cols() > 1 {
err = errors.New("'h' must be matrix with 1 column")
return
}
if dims == nil {
dims = sets.NewDimensionSet("l", "q", "s")
dims.Set("l", []int{h.Rows()})
}
cdim := dims.Sum("l", "q") + dims.SumSquared("s")
cdim_pckd := dims.Sum("l", "q") + dims.SumPacked("s")
if h.Rows() != cdim {
err = errors.New(fmt.Sprintf("'h' must be float matrix of size (%d,1)", cdim))
return
}
if G == nil {
G = matrix.FloatZeros(0, c.Rows())
}
if !G.SizeMatch(cdim, c.Rows()) {
estr := fmt.Sprintf("'G' must be of size (%d,%d)", cdim, c.Rows())
err = errors.New(estr)
return
}
// Check A and set defaults if it is nil
if A == nil {
// zeros rows reduces Gemv to vector products
A = matrix.FloatZeros(0, c.Rows())
}
if A.Cols() != c.Rows() {
estr := fmt.Sprintf("'A' must have %d columns", c.Rows())
err = errors.New(estr)
return
}
// Check b and set defaults if it is nil
if b == nil {
b = matrix.FloatZeros(0, 1)
}
if b.Cols() != 1 {
estr := fmt.Sprintf("'b' must be a matrix with 1 column")
err = errors.New(estr)
return
}
if b.Rows() != A.Rows() {
estr := fmt.Sprintf("'b' must have length %d", A.Rows())
err = errors.New(estr)
return
}
if b.Rows() > c.Rows() || b.Rows()+cdim_pckd < c.Rows() {
err = errors.New("Rank(A) < p or Rank([G; A]) < n")
return
}
solvername := solopts.KKTSolverName
if len(solvername) == 0 {
if len(dims.At("q")) > 0 || len(dims.At("s")) > 0 {
solvername = "qr"
} else {
solvername = "chol2"
}
}
var factor kktFactor
var kktsolver KKTConeSolver = nil
if kktfunc, ok := lpsolvers[solvername]; ok {
// kkt function returns us problem spesific factor function.
factor, err = kktfunc(G, dims, A, 0)
if err != nil {
return nil, err
}
kktsolver = func(W *sets.FloatMatrixSet) (KKTFunc, error) {
return factor(W, nil, nil)
}
} else {
err = errors.New(fmt.Sprintf("solver '%s' not known", solvername))
return
}
//return ConeLpCustom(c, &mG, h, &mA, b, dims, kktsolver, solopts, primalstart, dualstart)
c_e := &matrixVar{c}
G_e := &matrixVarG{G, dims}
A_e := &matrixVarA{A}
b_e := &matrixVar{b}
return conelp_problem(c_e, G_e, h, A_e, b_e, dims, kktsolver, solopts, primalstart, dualstart)
}
// Solution of KKT equations by a dense LDL factorization of the
// 3 x 3 system.
//
// Returns a function that (1) computes the LDL factorization of
//
// [ H A' GG'*W^{-1} ]
// [ A 0 0 ],
// [ W^{-T}*GG 0 -I ]
//
// given H, Df, W, where GG = [Df; G], and (2) returns a function for
// solving
//
// [ H A' GG' ] [ ux ] [ bx ]
// [ A 0 0 ] * [ uy ] = [ by ].
// [ GG 0 -W'*W ] [ uz ] [ bz ]
//
// H is n x n, A is p x n, Df is mnl x n, G is N x n where
// N = dims['l'] + sum(dims['q']) + sum( k**2 for k in dims['s'] ).
//
func kktLdl(G *matrix.FloatMatrix, dims *sets.DimensionSet, A *matrix.FloatMatrix, mnl int) (kktFactor, error) {
p, n := A.Size()
ldK := n + p + mnl + dims.At("l")[0] + dims.Sum("q") + dims.SumPacked("s")
K := matrix.FloatZeros(ldK, ldK)
ipiv := make([]int32, ldK)
u := matrix.FloatZeros(ldK, 1)
g := matrix.FloatZeros(mnl+G.Rows(), 1)
//checkpnt.AddMatrixVar("u", u)
//checkpnt.AddMatrixVar("K", K)
factor := func(W *sets.FloatMatrixSet, H, Df *matrix.FloatMatrix) (KKTFunc, error) {
var err error = nil
// Zero K for each call.
blas.ScalFloat(K, 0.0)
if H != nil {
K.SetSubMatrix(0, 0, H)
}
K.SetSubMatrix(n, 0, A)
for k := 0; k < n; k++ {
// g is (mnl + G.Rows(), 1) matrix, Df is (mnl, n), G is (N, n)
if mnl > 0 {
// set values g[0:mnl] = Df[,k]
g.SetIndexesFromArray(Df.GetColumnArray(k, nil), matrix.MakeIndexSet(0, mnl, 1)...)
}
// set values g[mnl:] = G[,k]
g.SetIndexesFromArray(G.GetColumnArray(k, nil), matrix.MakeIndexSet(mnl, mnl+g.Rows(), 1)...)
scale(g, W, true, true)
if err != nil {
//fmt.Printf("scale error: %s\n", err)
}
pack(g, K, dims, &la.IOpt{"mnl", mnl}, &la.IOpt{"offsety", k*ldK + n + p})
}
setDiagonal(K, n+p, n+n, ldK, ldK, -1.0)
err = lapack.Sytrf(K, ipiv)
if err != nil {
return nil, err
}
solve := func(x, y, z *matrix.FloatMatrix) (err error) {
// Solve
//
// [ H A' GG'*W^{-1} ] [ ux ] [ bx ]
// [ A 0 0 ] * [ uy [ = [ by ]
// [ W^{-T}*GG 0 -I ] [ W*uz ] [ W^{-T}*bz ]
//
// and return ux, uy, W*uz.
//
// On entry, x, y, z contain bx, by, bz. On exit, they contain
// the solution ux, uy, W*uz.
err = nil
blas.Copy(x, u)
blas.Copy(y, u, &la.IOpt{"offsety", n})
err = scale(z, W, true, true)
if err != nil {
return
}
err = pack(z, u, dims, &la.IOpt{"mnl", mnl}, &la.IOpt{"offsety", n + p})
if err != nil {
return
}
err = lapack.Sytrs(K, u, ipiv)
if err != nil {
return
}
blas.Copy(u, x, &la.IOpt{"n", n})
blas.Copy(u, y, &la.IOpt{"n", p}, &la.IOpt{"offsetx", n})
err = unpack(u, z, dims, &la.IOpt{"mnl", mnl}, &la.IOpt{"offsetx", n + p})
return
}
return solve, err
}
return factor, nil
}
// Solution of KKT equations by reduction to a 2 x 2 system, a QR
// factorization to eliminate the equality constraints, and a dense
// Cholesky factorization of order n-p.
//
// Computes the QR factorization
//
// A' = [Q1, Q2] * [R; 0]
//
// and returns a function that (1) computes the Cholesky factorization
//
// Q_2^T * (H + GG^T * W^{-1} * W^{-T} * GG) * Q2 = L * L^T,
//
// given H, Df, W, where GG = [Df; G], and (2) returns a function for
// solving
//
// [ H A' GG' ] [ ux ] [ bx ]
// [ A 0 0 ] * [ uy ] = [ by ].
// [ GG 0 -W'*W ] [ uz ] [ bz ]
//
// H is n x n, A is p x n, Df is mnl x n, G is N x n where
// N = dims['l'] + sum(dims['q']) + sum( k**2 for k in dims['s'] ).
//
func kktChol(G *matrix.FloatMatrix, dims *sets.DimensionSet, A *matrix.FloatMatrix, mnl int) (kktFactor, error) {
p, n := A.Size()
cdim := mnl + dims.Sum("l", "q") + dims.SumSquared("s")
cdim_pckd := mnl + dims.Sum("l", "q") + dims.SumPacked("s")
QA := A.Transpose()
tauA := matrix.FloatZeros(p, 1)
lapack.Geqrf(QA, tauA)
Gs := matrix.FloatZeros(cdim, n)
K := matrix.FloatZeros(n, n)
bzp := matrix.FloatZeros(cdim_pckd, 1)
yy := matrix.FloatZeros(p, 1)
checkpnt.AddMatrixVar("tauA", tauA)
checkpnt.AddMatrixVar("Gs", Gs)
checkpnt.AddMatrixVar("K", K)
factor := func(W *sets.FloatMatrixSet, H, Df *matrix.FloatMatrix) (KKTFunc, error) {
// Compute
//
// K = [Q1, Q2]' * (H + GG' * W^{-1} * W^{-T} * GG) * [Q1, Q2]
//
// and take the Cholesky factorization of the 2,2 block
//
// Q_2' * (H + GG^T * W^{-1} * W^{-T} * GG) * Q2.
var err error = nil
minor := 0
if !checkpnt.MinorEmpty() {
minor = checkpnt.MinorTop()
}
// Gs = W^{-T} * GG in packed storage.
if mnl > 0 {
Gs.SetSubMatrix(0, 0, Df)
}
Gs.SetSubMatrix(mnl, 0, G)
checkpnt.Check("00factor_chol", minor)
scale(Gs, W, true, true)
pack2(Gs, dims, mnl)
//checkpnt.Check("10factor_chol", minor)
// K = [Q1, Q2]' * (H + Gs' * Gs) * [Q1, Q2].
blas.SyrkFloat(Gs, K, 1.0, 0.0, la.OptTrans, &la.IOpt{"k", cdim_pckd})
if H != nil {
K.SetSubMatrix(0, 0, matrix.Plus(H, K.GetSubMatrix(0, 0, H.Rows(), H.Cols())))
}
//checkpnt.Check("20factor_chol", minor)
symm(K, n, 0)
lapack.Ormqr(QA, tauA, K, la.OptLeft, la.OptTrans)
lapack.Ormqr(QA, tauA, K, la.OptRight)
//checkpnt.Check("30factor_chol", minor)
// Cholesky factorization of 2,2 block of K.
lapack.Potrf(K, &la.IOpt{"n", n - p}, &la.IOpt{"offseta", p * (n + 1)})
checkpnt.Check("40factor_chol", minor)
solve := func(x, y, z *matrix.FloatMatrix) (err error) {
// Solve
//
// [ 0 A' GG'*W^{-1} ] [ ux ] [ bx ]
// [ A 0 0 ] * [ uy ] = [ by ]
// [ W^{-T}*GG 0 -I ] [ W*uz ] [ W^{-T}*bz ]
//
// and return ux, uy, W*uz.
//
// On entry, x, y, z contain bx, by, bz. On exit, they contain
// the solution ux, uy, W*uz.
//
// If we change variables ux = Q1*v + Q2*w, the system becomes
//
// [ K11 K12 R ] [ v ] [Q1'*(bx+GG'*W^{-1}*W^{-T}*bz)]
// [ K21 K22 0 ] * [ w ] = [Q2'*(bx+GG'*W^{-1}*W^{-T}*bz)]
// [ R^T 0 0 ] [ uy ] [by ]
//
// W*uz = W^{-T} * ( GG*ux - bz ).
minor := 0
if !checkpnt.MinorEmpty() {
minor = checkpnt.MinorTop()
}
// bzp := W^{-T} * bz in packed storage
scale(z, W, true, true)
pack(z, bzp, dims, &la.IOpt{"mnl", mnl})
// x := [Q1, Q2]' * (x + Gs' * bzp)
// = [Q1, Q2]' * (bx + Gs' * W^{-T} * bz)
blas.GemvFloat(Gs, bzp, x, 1.0, 1.0, la.OptTrans, &la.IOpt{"m", cdim_pckd})
lapack.Ormqr(QA, tauA, x, la.OptLeft, la.OptTrans)
// y := x[:p]
// = Q1' * (bx + Gs' * W^{-T} * bz)
blas.Copy(y, yy)
blas.Copy(x, y, &la.IOpt{"n", p})
// x[:p] := v = R^{-T} * by
blas.Copy(yy, x)
lapack.Trtrs(QA, x, la.OptUpper, la.OptTrans, &la.IOpt{"n", p})
// x[p:] := K22^{-1} * (x[p:] - K21*x[:p])
// = K22^{-1} * (Q2' * (bx + Gs' * W^{-T} * bz) - K21*v)
blas.GemvFloat(K, x, x, -1.0, 1.0, &la.IOpt{"m", n - p}, &la.IOpt{"n", p},
&la.IOpt{"offseta", p}, &la.IOpt{"offsety", p})
lapack.Potrs(K, x, &la.IOpt{"n", n - p}, &la.IOpt{"offseta", p * (n + 1)},
&la.IOpt{"offsetb", p})
// y := y - [K11, K12] * x
// = Q1' * (bx + Gs' * W^{-T} * bz) - K11*v - K12*w
blas.GemvFloat(K, x, y, -1.0, 1.0, &la.IOpt{"m", p}, &la.IOpt{"n", n})
// y := R^{-1}*y
// = R^{-1} * (Q1' * (bx + Gs' * W^{-T} * bz) - K11*v
// - K12*w)
lapack.Trtrs(QA, y, la.OptUpper, &la.IOpt{"n", p})
// x := [Q1, Q2] * x
lapack.Ormqr(QA, tauA, x, la.OptLeft)
// bzp := Gs * x - bzp.
// = W^{-T} * ( GG*ux - bz ) in packed storage.
// Unpack and copy to z.
blas.GemvFloat(Gs, x, bzp, 1.0, -1.0, &la.IOpt{"m", cdim_pckd})
unpack(bzp, z, dims, &la.IOpt{"mnl", mnl})
checkpnt.Check("90solve_chol", minor)
return nil
}
return solve, err
}
return factor, nil
}
// Solution of KKT equations with zero 1,1 block, by eliminating the
// equality constraints via a QR factorization, and solving the
// reduced KKT system by another QR factorization.
//
// Computes the QR factorization
//
// A' = [Q1, Q2] * [R1; 0]
//
// and returns a function that (1) computes the QR factorization
//
// W^{-T} * G * Q2 = Q3 * R3
//
// (with columns of W^{-T}*G in packed storage), and (2) returns a function for solving
//
// [ 0 A' G' ] [ ux ] [ bx ]
// [ A 0 0 ] * [ uy ] = [ by ].
// [ G 0 -W'*W ] [ uz ] [ bz ]
//
// A is p x n and G is N x n where N = dims['l'] + sum(dims['q']) +
// sum( k**2 for k in dims['s'] ).
//
func kktQr(G *matrix.FloatMatrix, dims *sets.DimensionSet, A *matrix.FloatMatrix, mnl int) (kktFactor, error) {
p, n := A.Size()
cdim := dims.Sum("l", "q") + dims.SumSquared("s")
cdim_pckd := dims.Sum("l", "q") + dims.SumPacked("s")
QA := A.Transpose()
tauA := matrix.FloatZeros(p, 1)
lapack.Geqrf(QA, tauA)
Gs := matrix.FloatZeros(cdim, n)
tauG := matrix.FloatZeros(n-p, 1)
u := matrix.FloatZeros(cdim_pckd, 1)
vv := matrix.FloatZeros(n, 1)
w := matrix.FloatZeros(cdim_pckd, 1)
checkpnt.AddMatrixVar("tauA", tauA)
checkpnt.AddMatrixVar("tauG", tauG)
checkpnt.AddMatrixVar("Gs", Gs)
checkpnt.AddMatrixVar("qr_u", u)
checkpnt.AddMatrixVar("qr_vv", vv)
factor := func(W *sets.FloatMatrixSet, H, Df *matrix.FloatMatrix) (KKTFunc, error) {
var err error = nil
minor := 0
if !checkpnt.MinorEmpty() {
minor = checkpnt.MinorTop()
}
// Gs = W^{-T}*G, in packed storage.
blas.Copy(G, Gs)
//checkpnt.Check("00factor_qr", minor)
scale(Gs, W, true, true)
//checkpnt.Check("01factor_qr", minor)
pack2(Gs, dims, 0)
//checkpnt.Check("02factor_qr", minor)
// Gs := [ Gs1, Gs2 ]
// = Gs * [ Q1, Q2 ]
lapack.Ormqr(QA, tauA, Gs, la.OptRight, &la.IOpt{"m", cdim_pckd})
//checkpnt.Check("03factor_qr", minor)
// QR factorization Gs2 := [ Q3, Q4 ] * [ R3; 0 ]
lapack.Geqrf(Gs, tauG, &la.IOpt{"n", n - p}, &la.IOpt{"m", cdim_pckd},
&la.IOpt{"offseta", Gs.Rows() * p})
checkpnt.Check("10factor_qr", minor)
solve := func(x, y, z *matrix.FloatMatrix) (err error) {
// On entry, x, y, z contain bx, by, bz. On exit, they
// contain the solution x, y, W*z of
//
// [ 0 A' G'*W^{-1} ] [ x ] [bx ]
// [ A 0 0 ] * [ y ] = [by ].
// [ W^{-T}*G 0 -I ] [ W*z ] [W^{-T}*bz]
//
// The system is solved in five steps:
//
// w := W^{-T}*bz - Gs1*R1^{-T}*by
// u := R3^{-T}*Q2'*bx + Q3'*w
// W*z := Q3*u - w
// y := R1^{-1} * (Q1'*bx - Gs1'*(W*z))
// x := [ Q1, Q2 ] * [ R1^{-T}*by; R3^{-1}*u ]
minor := 0
if !checkpnt.MinorEmpty() {
minor = checkpnt.MinorTop()
}
// w := W^{-T} * bz in packed storage
scale(z, W, true, true)
pack(z, w, dims)
//checkpnt.Check("00solve_qr", minor)
// vv := [ Q1'*bx; R3^{-T}*Q2'*bx ]
blas.Copy(x, vv)
lapack.Ormqr(QA, tauA, vv, la.OptTrans)
lapack.Trtrs(Gs, vv, la.OptUpper, la.OptTrans, &la.IOpt{"n", n - p},
&la.IOpt{"offseta", Gs.Rows() * p}, &la.IOpt{"offsetb", p})
//checkpnt.Check("10solve_qr", minor)
// x[:p] := R1^{-T} * by
blas.Copy(y, x)
lapack.Trtrs(QA, x, la.OptUpper, la.OptTrans, &la.IOpt{"n", p})
//checkpnt.Check("20solve_qr", minor)
// w := w - Gs1 * x[:p]
// = W^{-T}*bz - Gs1*by
blas.GemvFloat(Gs, x, w, -1.0, 1.0, &la.IOpt{"n", p}, &la.IOpt{"m", cdim_pckd})
//checkpnt.Check("30solve_qr", minor)
// u := [ Q3'*w + v[p:]; 0 ]
// = [ Q3'*w + R3^{-T}*Q2'*bx; 0 ]
blas.Copy(w, u)
lapack.Ormqr(Gs, tauG, u, la.OptTrans, &la.IOpt{"k", n - p},
&la.IOpt{"offseta", Gs.Rows() * p}, &la.IOpt{"m", cdim_pckd})
blas.AxpyFloat(vv, u, 1.0, &la.IOpt{"offsetx", p}, &la.IOpt{"n", n - p})
blas.ScalFloat(u, 0.0, &la.IOpt{"offset", n - p})
//checkpnt.Check("40solve_qr", minor)
// x[p:] := R3^{-1} * u[:n-p]
blas.Copy(u, x, &la.IOpt{"offsety", p}, &la.IOpt{"n", n - p})
lapack.Trtrs(Gs, x, la.OptUpper, &la.IOpt{"n", n - p},
&la.IOpt{"offset", Gs.Rows() * p}, &la.IOpt{"offsetb", p})
//checkpnt.Check("50solve_qr", minor)
// x is now [ R1^{-T}*by; R3^{-1}*u[:n-p] ]
// x := [Q1 Q2]*x
lapack.Ormqr(QA, tauA, x)
//checkpnt.Check("60solve_qr", minor)
// u := [Q3, Q4] * u - w
// = Q3 * u[:n-p] - w
lapack.Ormqr(Gs, tauG, u, &la.IOpt{"k", n - p}, &la.IOpt{"m", cdim_pckd},
&la.IOpt{"offseta", Gs.Rows() * p})
blas.AxpyFloat(w, u, -1.0)
//checkpnt.Check("70solve_qr", minor)
// y := R1^{-1} * ( v[:p] - Gs1'*u )
// = R1^{-1} * ( Q1'*bx - Gs1'*u )
blas.Copy(vv, y, &la.IOpt{"n", p})
blas.GemvFloat(Gs, u, y, -1.0, 1.0, &la.IOpt{"m", cdim_pckd},
&la.IOpt{"n", p}, la.OptTrans)
lapack.Trtrs(QA, y, la.OptUpper, &la.IOpt{"n", p})
//checkpnt.Check("80solve_qr", minor)
unpack(u, z, dims)
checkpnt.Check("90solve_qr", minor)
return nil
}
return solve, err
}
return factor, nil
}