Ejemplo n.º 1
0
func _TestBKpivot1(t *testing.T) {
	Ldata := [][]float64{
		[]float64{1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0},
		[]float64{1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0},
		[]float64{1.0, 2.0, 3.0, 0.0, 0.0, 0.0, 0.0},
		[]float64{1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0},
		[]float64{1.0, 5.0, 3.0, 4.0, 5.0, 0.0, 0.0},
		[]float64{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 0.0},
		[]float64{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}}

	Bdata := [][]float64{
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0}}

	A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
	X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
	N := A.Rows()
	B := matrix.FloatZeros(N, 2)
	MultSym(B, A, X, 1.0, 0.0, LOWER|LEFT)
	t.Logf("initial B:\n%v\n", B)
	//N := 8
	//A := matrix.FloatUniformSymmetric(N)
	nb := 0

	W := matrix.FloatWithValue(A.Rows(), 5, 0.0)

	ipiv := make([]int, N, N)
	L, _ := DecomposeBK(A.Copy(), W, ipiv, LOWER, nb)
	t.Logf("ipiv: %v\n", ipiv)
	t.Logf("L:\n%v\n", L)

	ipiv0 := make([]int, N, N)
	nb = 4
	L0, _ := DecomposeBK(A.Copy(), W, ipiv0, LOWER, nb)
	t.Logf("ipiv: %v\n", ipiv0)
	t.Logf("L:\n%v\n", L0)
	B0 := B.Copy()
	SolveBK(B0, L0, ipiv0, LOWER)
	t.Logf("B0:\n%v\n", B0)

	ipiv2 := make([]int32, N, N)
	lapack.SytrfFloat(A, ipiv2, linalg.OptLower)
	t.Logf("ipiv2: %v\n", ipiv2)
	t.Logf("lapack A:\n%v\n", A)
	lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
	t.Logf("lapack B:\n%v\n", B)
	t.Logf("B == B0: %v\n", B.AllClose(B0))
}
Ejemplo n.º 2
0
func _TestBK2(t *testing.T) {
	Bdata := [][]float64{
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0},
		[]float64{10.0, 20.0}}

	N := 7

	A0 := matrix.FloatNormal(N, N)
	A := matrix.FloatZeros(N, N)
	// A is symmetric, posivite definite
	Mult(A, A0, A0, 1.0, 1.0, TRANSB)

	X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
	B := matrix.FloatZeros(N, 2)
	MultSym(B, A, X, 1.0, 0.0, LOWER|LEFT)
	t.Logf("initial B:\n%v\n", B)

	nb := 0
	W := matrix.FloatWithValue(A.Rows(), 5, 1.0)
	A.SetAt(4, 1, A.GetAt(4, 1)+1.0)
	A.SetAt(1, 4, A.GetAt(4, 1))

	ipiv := make([]int, N, N)
	L, _ := DecomposeBK(A.Copy(), W, ipiv, LOWER, nb)
	t.Logf("ipiv: %v\n", ipiv)
	t.Logf("L:\n%v\n", L)

	ipiv0 := make([]int, N, N)
	nb = 4
	L0, _ := DecomposeBK(A.Copy(), W, ipiv0, LOWER, nb)
	t.Logf("ipiv: %v\n", ipiv0)
	t.Logf("L:\n%v\n", L0)
	B0 := B.Copy()
	SolveBK(B0, L0, ipiv0, LOWER)
	t.Logf("B0:\n%v\n", B0)

	ipiv2 := make([]int32, N, N)
	lapack.Sytrf(A, ipiv2, linalg.OptLower)
	t.Logf("ipiv2: %v\n", ipiv2)
	t.Logf("lapack A:\n%v\n", A)
	lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
	t.Logf("lapack B:\n%v\n", B)
	t.Logf("B == B0: %v\n", B.AllClose(B0))
}
Ejemplo n.º 3
0
func _TestBKSolve(t *testing.T) {
	Ldata := [][]float64{
		[]float64{1.0, 2.0, 3.0, 4.0},
		[]float64{2.0, 2.0, 3.0, 4.0},
		[]float64{3.0, 3.0, 3.0, 4.0},
		[]float64{4.0, 4.0, 4.0, 4.0}}
	Xdata := [][]float64{
		[]float64{1.0, 2.0},
		[]float64{1.0, 2.0},
		[]float64{1.0, 2.0},
		[]float64{1.0, 2.0}}

	A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
	X := matrix.FloatMatrixFromTable(Xdata, matrix.RowOrder)
	N := A.Rows()
	B := matrix.FloatZeros(N, 2)
	Mult(B, A, X, 1.0, 0.0, NOTRANS)
	S := matrix.FloatZeros(N, 2)
	MultSym(S, A, X, 1.0, 0.0, LOWER|LEFT)
	t.Logf("B:\n%v\n", B)
	t.Logf("S:\n%v\n", S)
	//N := 8
	//A := matrix.FloatUniformSymmetric(N)
	nb := 0

	W := matrix.FloatWithValue(A.Rows(), 5, 0.0)

	ipiv := make([]int, N, N)
	L, _ := DecomposeBK(A.Copy(), W, ipiv, LOWER, nb)
	t.Logf("ipiv: %v\n", ipiv)
	t.Logf("L:\n%v\n", L)
	B0 := B.Copy()
	SolveBK(B0, L, ipiv, LOWER)
	t.Logf("B0:\n%v\n", B0)

	ipiv2 := make([]int32, N, N)
	lapack.Sytrf(A, ipiv2, linalg.OptLower)
	t.Logf("ipiv2: %v\n", ipiv2)
	t.Logf("lapack A:\n%v\n", A)
	lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
	t.Logf("lapack B:\n%v\n", B)
}
Ejemplo n.º 4
0
// 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
}