func TestSymm() {
x := matrix.FloatNew(3, 3, []float64{1, 2, 3, 4, 5, 6, 7, 8, 9})
r := matrix.FloatNew(3, 3, []float64{1, 2, 3, 2, 5, 6, 3, 6, 9})
fmt.Printf("x=\n%v\n", x)
cvx.Symm(x, 3, 0)
fmt.Printf("x=\n%v\n", x)
if x.Equal(r) {
fmt.Printf("OK\n")
} else {
fmt.Printf("FAILED\n")
}
}
func TestDGetrf(t *testing.T) {
ipiv := make([]int32, 3)
A := matrix.FloatNew(3, 2, []float64{1, 2, 3, 4, 5, 6})
fmt.Printf("pre A:\n%s\n", A)
err := Getrf(A, ipiv)
fmt.Printf("err=%s, ipiv=%s\n", err, ipiv)
fmt.Printf("post A:\n%s\n", A)
}
func TestDgemv(t *testing.T) {
fmt.Printf("* L2 * test gemv: Y = alpha * A * X + beta * Y\n")
A := matrix.FloatNew(3, 2, []float64{1, 1, 1, 2, 2, 2})
X := matrix.FloatVector([]float64{1, 1})
Y := matrix.FloatVector([]float64{0, 0, 0})
alpha := matrix.FScalar(1.0)
beta := matrix.FScalar(0.0)
fmt.Printf("before: alpha=1.0, beta=0.0\nA=\n%v\nX=\n%v\nY=\n%v\n", A, X, Y)
err := Gemv(A, X, Y, alpha, beta)
fmt.Printf("after:\nA=\n%v\nX=\n%v\nY=\n%v\n", A, X, Y)
fmt.Printf("* L2 * test gemv: X = alpha * A.T * Y + beta * X\n")
err = Gemv(A, Y, X, alpha, beta, linalg.OptTrans)
if err != nil {
fmt.Printf("error: %s\n", err)
}
fmt.Printf("after:\nA=\n%v\nX=\n%v\nY=\n%v\n", A, X, Y)
}
func main() {
Sdata := [][]float64{
[]float64{ 4e-2, 6e-3, -4e-3, 0.0 },
[]float64{ 6e-3, 1e-2, 0.0, 0.0 },
[]float64{-4e-3, 0.0, 2.5e-3, 0.0 },
[]float64{ 0.0, 0.0, 0.0, 0.0 }}
pbar := matrix.FloatVector([]float64{.12, .10, .07, .03})
S := matrix.FloatMatrixStacked(Sdata)
n := pbar.Rows()
G := matrix.FloatDiagonal(n, -1.0)
h := matrix.FloatZeros(n, 1)
A := matrix.FloatWithValue(1, n, 1.0)
b := matrix.FloatNew(1,1, []float64{1.0})
var solopts cvx.SolverOptions
solopts.MaxIter = 30
solopts.ShowProgress = true
mu := 1.0
Smu := S.Copy().Scale(mu)
pbarNeg := pbar.Copy().Scale(-1.0)
fmt.Printf("Smu=\n%v\n", Smu.String())
fmt.Printf("-pbar=\n%v\n", pbarNeg.String())
sol, err := cvx.Qp(Smu, pbarNeg, G, h, A, b, &solopts, nil)
fmt.Printf("status: %v\n", err)
if sol != nil && sol.Status == cvx.Optimal {
x := sol.Result.At("x")[0]
ret := blas.DotFloat(x, pbar)
risk := math.Sqrt(blas.DotFloat(x, S.Times(x)))
fmt.Printf("ret=%.3f, risk=%.3f\n", ret, risk)
fmt.Printf("x=\n%v\n", x)
}
}
// Solves a pair of primal and dual SDPs
//
// minimize c'*x
// subject to Gl*x + sl = hl
// mat(Gs[k]*x) + ss[k] = hs[k], k = 0, ..., N-1
// A*x = b
// sl >= 0, ss[k] >= 0, k = 0, ..., N-1
//
// maximize -hl'*z - sum_k trace(hs[k]*zs[k]) - b'*y
// subject to Gl'*zl + sum_k Gs[k]'*vec(zs[k]) + A'*y + c = 0
// zl >= 0, zs[k] >= 0, k = 0, ..., N-1.
//
// The inequalities sl >= 0 and zl >= 0 are elementwise vector
// inequalities. The inequalities ss[k] >= 0, zs[k] >= 0 are matrix
// inequalities, i.e., the symmetric matrices ss[k] and zs[k] must be
// positive semidefinite. mat(Gs[k]*x) is the symmetric matrix X with
// X[:] = Gs[k]*x. For a symmetric matrix, zs[k], vec(zs[k]) is the
// vector zs[k][:].
//
func Sdp(c, Gl, hl, A, b *matrix.FloatMatrix, Ghs *FloatMatrixSet, solopts *SolverOptions, primalstart, dualstart *FloatMatrixSet) (sol *Solution, err error) {
if c == nil {
err = errors.New("'c' must a column matrix")
return
}
n := c.Rows()
if n < 1 {
err = errors.New("Number of variables must be at least 1")
return
}
if Gl == nil {
Gl = matrix.FloatZeros(0, n)
}
if Gl.Cols() != n {
err = errors.New(fmt.Sprintf("'G' must be matrix with %d columns", n))
return
}
ml := Gl.Rows()
if hl == nil {
hl = matrix.FloatZeros(0, 1)
}
if !hl.SizeMatch(ml, 1) {
err = errors.New(fmt.Sprintf("'hl' must be matrix of size (%d,1)", ml))
return
}
Gsset := Ghs.At("Gs")
ms := make([]int, 0)
for i, Gs := range Gsset {
if Gs.Cols() != n {
err = errors.New(fmt.Sprintf("'Gs' must be list of matrices with %d columns", n))
return
}
sz := int(math.Sqrt(float64(Gs.Rows())))
if Gs.Rows() != sz*sz {
err = errors.New(fmt.Sprintf("the squareroot of the number of rows of 'Gq[%d]' is not an integer", i))
return
}
ms = append(ms, sz)
}
hsset := Ghs.At("hs")
if len(Gsset) != len(hsset) {
err = errors.New(fmt.Sprintf("'hs' must be a list of %d matrices", len(Gsset)))
return
}
for i, hs := range hsset {
if !hs.SizeMatch(ms[i], ms[i]) {
s := fmt.Sprintf("hq[%d] has size (%d,%d). Expected size is (%d,%d)",
i, hs.Rows(), hs.Cols(), ms[i], ms[i])
err = errors.New(s)
return
}
}
if A == nil {
A = matrix.FloatZeros(0, n)
}
if A.Cols() != n {
err = errors.New(fmt.Sprintf("'A' must be matrix with %d columns", n))
return
}
p := A.Rows()
if b == nil {
b = matrix.FloatZeros(0, 1)
}
if !b.SizeMatch(p, 1) {
err = errors.New(fmt.Sprintf("'b' must be matrix of size (%d,1)", p))
return
}
dims := DSetNew("l", "q", "s")
dims.Set("l", []int{ml})
dims.Set("s", ms)
N := dims.Sum("l") + dims.SumSquared("s")
// Map hs matrices to h vector
h := matrix.FloatZeros(N, 1)
h.SetIndexes(matrix.MakeIndexSet(0, ml, 1), hl.FloatArray()[:ml])
ind := ml
for k, hs := range hsset {
h.SetIndexes(matrix.MakeIndexSet(ind, ind+ms[k]*ms[k], 1), hs.FloatArray())
ind += ms[k] * ms[k]
}
Gargs := make([]*matrix.FloatMatrix, 0)
Gargs = append(Gargs, Gl)
Gargs = append(Gargs, Gsset...)
G, sizeg := matrix.FloatMatrixCombined(matrix.StackDown, Gargs...)
var pstart, dstart *FloatMatrixSet = nil, nil
if primalstart != nil {
pstart = FloatSetNew("x", "s")
pstart.Set("x", primalstart.At("x")[0])
slset := primalstart.At("sl")
margs := make([]*matrix.FloatMatrix, 0, len(slset)+1)
margs = append(margs, primalstart.At("s")[0])
margs = append(margs, slset...)
sl, _ := matrix.FloatMatrixCombined(matrix.StackDown, margs...)
pstart.Set("s", sl)
}
if dualstart != nil {
dstart = FloatSetNew("y", "z")
dstart.Set("y", dualstart.At("y")[0])
zlset := primalstart.At("zl")
margs := make([]*matrix.FloatMatrix, 0, len(zlset)+1)
margs = append(margs, dualstart.At("z")[0])
margs = append(margs, zlset...)
zl, _ := matrix.FloatMatrixCombined(matrix.StackDown, margs...)
dstart.Set("z", zl)
}
sol, err = ConeLp(c, G, h, A, b, dims, solopts, pstart, dstart)
// unpack sol.Result
if err == nil {
s := sol.Result.At("s")[0]
sl := matrix.FloatVector(s.FloatArray()[:ml])
sol.Result.Append("sl", sl)
ind := ml
for _, m := range ms {
sk := matrix.FloatNew(m, m, s.FloatArray()[ind:ind+m*m])
sol.Result.Append("ss", sk)
ind += m * m
}
z := sol.Result.At("z")[0]
zl := matrix.FloatVector(s.FloatArray()[:ml])
sol.Result.Append("zl", zl)
ind = ml
for i, k := range sizeg[1:] {
zk := matrix.FloatNew(ms[i], ms[i], z.FloatArray()[ind:ind+k])
sol.Result.Append("zs", zk)
ind += k
}
}
sol.Result.Remove("s")
sol.Result.Remove("z")
return
}