コード例 #1
0
ファイル: tmult_test.go プロジェクト: sguzwf/algorithm
func _TestMultMVTransA(t *testing.T) {
	bM := 1000 * M
	bN := 1000 * N
	A := matrix.FloatNormal(bN, bM)
	X := matrix.FloatWithValue(bN, 1, 1.0)
	Y1 := matrix.FloatZeros(bM, 1)
	Y0 := matrix.FloatZeros(bM, 1)

	Ar := A.FloatArray()
	Xr := X.FloatArray()
	Y1r := Y1.FloatArray()

	blas.GemvFloat(A, X, Y0, 1.0, 1.0, linalg.OptTrans)

	DMultMV(Y1r, Ar, Xr, 1.0, 1.0, TRANSA, 1, A.LeadingIndex(), 1, 0, bN, 0, bM, 4, 4)
	ok := Y0.AllClose(Y1)
	t.Logf("Y0 == Y1: %v\n", ok)
	if !ok {
		var y1, y0 matrix.FloatMatrix
		Y1.SubMatrix(&y1, 0, 0, 5, 1)
		t.Logf("Y1[0:5]:\n%v\n", y1)
		Y0.SubMatrix(&y0, 0, 0, 5, 1)
		t.Logf("Y0[0:5]:\n%v\n", y0)
	}
}
コード例 #2
0
ファイル: gp.go プロジェクト: sguzwf/algorithm
func (gp *gpConvexProg) F1(x *matrix.FloatMatrix) (f, Df *matrix.FloatMatrix, err error) {
    f = nil
    Df = nil
    err = nil
    f = matrix.FloatZeros(gp.mnl+1, 1)
    Df = matrix.FloatZeros(gp.mnl+1, gp.n)
    y := gp.g.Copy()
    blas.GemvFloat(gp.F, x, y, 1.0, 1.0)

    for i, s := range gp.ind {
        start := s[0]
        stop := s[1]
        // yi := exp(yi) = exp(Fi*x+gi)
        ymax := maxvec(y.FloatArray()[start:stop])
        // ynew = exp(y[start:stop] - ymax)
        ynew := matrix.Exp(matrix.FloatVector(y.FloatArray()[start:stop]).Add(-ymax))
        y.SetIndexesFromArray(ynew.FloatArray(), matrix.Indexes(start, stop)...)

        // fi = log sum yi = log sum exp(Fi*x+gi)
        ysum := blas.AsumFloat(y, &la.IOpt{"n", stop - start}, &la.IOpt{"offset", start})
        f.SetIndex(i, ymax+math.Log(ysum))

        blas.ScalFloat(y, 1.0/ysum, &la.IOpt{"n", stop - start}, &la.IOpt{"offset", start})
        blas.GemvFloat(gp.F, y, Df, 1.0, 0.0, la.OptTrans, &la.IOpt{"m", stop - start},
            &la.IOpt{"incy", gp.mnl + 1}, &la.IOpt{"offseta", start},
            &la.IOpt{"offsetx", start}, &la.IOpt{"offsety", i})
    }
    return
}
コード例 #3
0
ファイル: tmult_test.go プロジェクト: sguzwf/algorithm
func _TestMultSymmLowerSmall(t *testing.T) {
	//bM := 5
	bN := 7
	bP := 7
	Adata := [][]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, 2.0, 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}}

	A := matrix.FloatMatrixFromTable(Adata, matrix.RowOrder)
	B := matrix.FloatNormal(bN, bP)
	C0 := matrix.FloatZeros(bN, bP)
	C1 := matrix.FloatZeros(bN, bP)

	Ar := A.FloatArray()
	Br := B.FloatArray()
	C1r := C1.FloatArray()

	blas.SymmFloat(A, B, C0, 1.0, 1.0, linalg.OptLower, linalg.OptRight)

	DMultSymm(C1r, Ar, Br, 1.0, 1.0, LOWER|RIGHT, bN, A.LeadingIndex(), bN,
		bN, 0, bP, 0, bN, 2, 2, 2)
	ok := C0.AllClose(C1)
	t.Logf("C0 == C1: %v\n", ok)
	if !ok {
		t.Logf("A=\n%v\n", A)
		t.Logf("blas: C=A*B\n%v\n", C0)
		t.Logf("C1: C1 = A*X\n%v\n", C1)
	}
}
コード例 #4
0
ファイル: decomp_test.go プロジェクト: sguzwf/algorithm
func TestQRSmal(t *testing.T) {
	data := [][]float64{
		[]float64{12.0, -51.0, 4.0},
		[]float64{6.0, 167.0, -68.0},
		[]float64{-4.0, 24.0, -41.0}}

	A := matrix.FloatMatrixFromTable(data, matrix.RowOrder)
	T := matrix.FloatZeros(A.Cols(), A.Cols())
	T0 := T.Copy()

	M := A.Rows()
	//N := A.Cols()
	Tau := matrix.FloatZeros(M, 1)
	X, _ := DecomposeQR(A.Copy(), Tau, nil, 0)
	t.Logf("A\n%v\n", A)
	t.Logf("X\n%v\n", X)
	t.Logf("Tau\n%v\n", Tau)

	Tau0 := matrix.FloatZeros(M, 1)
	lapack.Geqrf(A, Tau0)
	t.Logf("lapack X\n%v\n", A)
	t.Logf("lapack Tau\n%v\n", Tau0)

	unblkQRBlockReflector(X, Tau, T)
	t.Logf("T:\n%v\n", T)

	V := TriLU(X.Copy())
	lapack.LarftFloat(V, Tau, T0)
	t.Logf("T0:\n%v\n", T0)

}
コード例 #5
0
ファイル: tmult_test.go プロジェクト: sguzwf/algorithm
func _TestMultMV(t *testing.T) {
	bM := 100 * M
	bN := 100 * N
	A := matrix.FloatNormal(bM, bN)
	X := matrix.FloatNormal(bN, 1)
	Y1 := matrix.FloatZeros(bM, 1)
	Y0 := matrix.FloatZeros(bM, 1)

	Ar := A.FloatArray()
	Xr := X.FloatArray()
	Y1r := Y1.FloatArray()

	blas.GemvFloat(A, X, Y0, 1.0, 1.0)

	DMultMV(Y1r, Ar, Xr, 1.0, 1.0, NOTRANS, 1, A.LeadingIndex(), 1, 0, bN, 0, bM, 32, 32)
	t.Logf("Y0 == Y1: %v\n", Y0.AllClose(Y1))
	/*
	   if ! Y0.AllClose(Y1) {
	       y0 := Y0.SubMatrix(0, 0, 2, 1)
	       y1 := Y1.SubMatrix(0, 0, 2, 1)
	       t.Logf("y0=\n%v\n", y0)
	       t.Logf("y1=\n%v\n", y1)
	   }
	*/
}
コード例 #6
0
ファイル: qr_test.go プロジェクト: sguzwf/algorithm
func TestMultQT(t *testing.T) {
	M := 60
	N := 40
	K := 30
	nb := 12
	A := matrix.FloatUniform(M, N)
	B := matrix.FloatUniform(M, K)
	W := matrix.FloatZeros(N, nb)
	T := matrix.FloatZeros(N, N)

	// QR = Q*R
	QR, err := DecomposeQRT(A.Copy(), T, W, nb)
	if err != nil {
		t.Logf("decompose-err: %v\n", err)
	}

	// compute: B - Q*Q.T*B = 0

	// X = Q*Q.T*B
	X := B.Copy()
	MultQT(X, QR, T, W, LEFT|TRANS, nb)
	MultQT(X, QR, T, W, LEFT, nb)
	B.Minus(X)

	// ||B - Q*Q.T*B||_1
	nrm := NormP(B, NORM_ONE)
	t.Logf("||B - Q*Q.T*B||_1: %e\n", nrm)
}
コード例 #7
0
ファイル: tmult_test.go プロジェクト: sguzwf/algorithm
func TestUpdateTrmMV(t *testing.T) {
	//bM := 5
	bN := 8
	//bP := 4
	nb := 4
	X := matrix.FloatNormal(bN, 1)
	//B := matrix.FloatNormal(bP, bN)
	Y := X.Copy()
	C0 := matrix.FloatZeros(bN, bN)
	C2 := matrix.FloatZeros(bN, bN)
	C1 := matrix.FloatZeros(bN, bN)

	Xr := X.FloatArray()
	Yr := Y.FloatArray()
	C1r := C1.FloatArray()
	C0r := C0.FloatArray()
	C2r := C2.FloatArray()

	// no transpose
	DRankMV(C1r, Xr, Yr, 1.0, C1.LeadingIndex(), 1, 1,
		0, bN, 0, bN, nb, nb)
	DTrmUpdMV(C0r, Xr, Yr, 1.0, LOWER, C0.LeadingIndex(), 1, 1,
		0, bN, nb)
	DTrmUpdMV(C2r, Xr, Yr, 1.0, UPPER, C2.LeadingIndex(), 1, 1,
		0, bN, nb)

	t.Logf("C1:\n%v\nC0:\n%v\nC2:\n%v\n", C1, C0, C2)
	// C0 == C2.T
	t.Logf("C0 == C2.T: %v\n", C0.AllClose(C2.Transpose()))
	// C1 == C1 - C2 + C0.T
	Cn := matrix.Minus(C1, C2)
	Cn.Plus(C0.Transpose())
	t.Logf("C1 == C1 - C2 + C0.T: %v\n", Cn.AllClose(C1))

}
コード例 #8
0
ファイル: qr_test.go プロジェクト: sguzwf/algorithm
func TestSolveLeastSquaresQRT(t *testing.T) {
	M := 60
	N := 40
	K := 30
	nb := 12

	A := matrix.FloatUniform(M, N)
	B := matrix.FloatZeros(M, K)
	X0 := matrix.FloatUniform(N, K)

	// B = A*X0
	Mult(B, A, X0, 1.0, 0.0, NOTRANS)
	W := matrix.FloatZeros(N, nb)
	T := matrix.FloatZeros(N, N)

	QR, err := DecomposeQRT(A, T, W, nb)
	if err != nil {
		t.Logf("decompose error: %v\n", err)
	}
	// B' = A.-1*B
	err = SolveQRT(B, QR, T, W, NOTRANS, nb)

	// expect B[0:N, 0:K] == X0, B[N:M, 0:K] == 0.0
	var Xref matrix.FloatMatrix
	Bref := matrix.FloatZeros(M, K)
	Bref.SubMatrix(&Xref, 0, 0, N, K)
	Xref.Plus(X0)
	Bref.Minus(B)
	t.Logf("\nmin ||B - A*X0||\n\twhere B = A*X0\n")
	t.Logf("||B - A*X0||_1 ~~ 0.0: %e\n", NormP(Bref, NORM_ONE))
}
コード例 #9
0
ファイル: perf_qr.go プロジェクト: sguzwf/algorithm
func runTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
	var W *matrix.FloatMatrix = nil
	var mintime time.Duration

	N := A.Cols()
	tau := matrix.FloatZeros(N, 1)
	if LB > 0 {
		W = matrix.FloatZeros(A.Rows(), LB)
	}
	fnc := func() {
		_, ERRmatops = matops.DecomposeQR(A, tau, W, LB)
	}

	A0 := A.Copy()
	for n := 0; n < ntest; n++ {
		if n > 0 {
			// restore original A
			A0.CopyTo(A)
			tau.Scale(0.0)
		}
		mperf.FlushCache()
		time0 := mperf.Timeit(fnc)
		if n == 0 || time0 < mintime {
			mintime = time0
		}
		if verbose {
			fmt.Printf("%.4f ms\n", time0.Seconds()*1000.0)
		}
	}
	return mintime
}
コード例 #10
0
ファイル: gp.go プロジェクト: sguzwf/algorithm
//
// Solves a geometric program
//
//   minimize    log sum exp (F0*x+g0)
//   subject to  log sum exp (Fi*x+gi) <= 0,  i=1,...,m
//               G*x <= h      
//               A*x = b
//
func Gp(K []int, F, g, G, h, A, b *matrix.FloatMatrix, solopts *SolverOptions) (sol *Solution, err error) {

    if err = checkArgK(K); err != nil {
        return
    }
    l := sumdim(K)

    if F == nil || F.Rows() != l {
        err = errors.New(fmt.Sprintf("'F' must matrix with %d rows", l))
        return
    }

    if g == nil || !g.SizeMatch(l, 1) {
        err = errors.New(fmt.Sprintf("'g' must matrix with size (%d,1)", l))
        return
    }
    n := F.Cols()

    if G == nil {
        G = matrix.FloatZeros(0, n)
    }
    if h == nil {
        h = matrix.FloatZeros(0, 1)
    }
    if G.Cols() != n {
        err = errors.New(fmt.Sprintf("'G' must matrix with size %d columns", n))
        return
    }
    ml := G.Rows()
    if h == nil || !h.SizeMatch(ml, 1) {
        err = errors.New(fmt.Sprintf("'h' must matrix with size (%d,1)", ml))
        return
    }

    if A == nil {
        A = matrix.FloatZeros(0, n)
    }
    if b == nil {
        b = matrix.FloatZeros(0, 1)
    }
    if A.Cols() != n {
        err = errors.New(fmt.Sprintf("'A' must matrix with size %d columns", n))
        return
    }
    p := A.Rows()
    if b == nil || !b.SizeMatch(p, 1) {
        err = errors.New(fmt.Sprintf("'b' must matrix with size (%d,1)", p))
        return
    }

    dims := sets.NewDimensionSet("l", "q", "s")
    dims.Set("l", []int{ml})
    gpProg := createGpProg(K, F, g)

    return Cp(gpProg, G, h, A, b, dims, solopts)
}
コード例 #11
0
ファイル: misc.go プロジェクト: sguzwf/algorithm
// Returns min {t | x + t*e >= 0}, where e is defined as follows
//
//  - For the nonlinear and 'l' blocks: e is the vector of ones.
//  - For the 'q' blocks: e is the first unit vector.
//  - For the 's' blocks: e is the identity matrix.
//
// When called with the argument sigma, also returns the eigenvalues
// (in sigma) and the eigenvectors (in x) of the 's' components of x.
func maxStep(x *matrix.FloatMatrix, dims *sets.DimensionSet, mnl int, sigma *matrix.FloatMatrix) (rval float64, err error) {
	/*DEBUGGED*/

	rval = 0.0
	err = nil
	t := make([]float64, 0, 10)
	ind := mnl + dims.Sum("l")
	if ind > 0 {
		t = append(t, -minvec(x.FloatArray()[:ind]))
	}
	for _, m := range dims.At("q") {
		if m > 0 {
			v := blas.Nrm2Float(x, &la_.IOpt{"offset", ind + 1}, &la_.IOpt{"n", m - 1})
			v -= x.GetIndex(ind)
			t = append(t, v)
		}
		ind += m
	}

	//var Q *matrix.FloatMatrix
	//var w *matrix.FloatMatrix
	ind2 := 0
	//if sigma == nil && len(dims.At("s")) > 0 {
	//	mx := dims.Max("s")
	//	Q = matrix.FloatZeros(mx, mx)
	//	w = matrix.FloatZeros(mx, 1)
	//}
	for _, m := range dims.At("s") {
		if sigma == nil {
			Q := matrix.FloatZeros(m, m)
			w := matrix.FloatZeros(m, 1)
			blas.Copy(x, Q, &la_.IOpt{"offsetx", ind}, &la_.IOpt{"n", m * m})
			err = lapack.SyevrFloat(Q, w, nil, 0.0, nil, []int{1, 1}, la_.OptRangeInt,
				&la_.IOpt{"n", m}, &la_.IOpt{"lda", m})
			if m > 0 && err == nil {
				t = append(t, -w.GetIndex(0))
			}
		} else {
			err = lapack.SyevdFloat(x, sigma, la_.OptJobZValue, &la_.IOpt{"n", m},
				&la_.IOpt{"lda", m}, &la_.IOpt{"offseta", ind}, &la_.IOpt{"offsetw", ind2})
			if m > 0 {
				t = append(t, -sigma.GetIndex(ind2))
			}
		}
		ind += m * m
		ind2 += m
	}

	if len(t) > 0 {
		rval = maxvec(t)
	}
	return
}
コード例 #12
0
ファイル: perf_qr.go プロジェクト: sguzwf/algorithm
// single invocation for matops and lapack functions
func runCheck(A *matrix.FloatMatrix, LB int) (bool, time.Duration, time.Duration) {

	var W *matrix.FloatMatrix = nil
	N := A.Cols()
	tau := matrix.FloatZeros(N, 1)
	if LB > 0 {
		W = matrix.FloatZeros(A.Rows(), LB)
	}
	fnc := func() {
		_, ERRmatops = matops.DecomposeQR(A, tau, W, LB)
	}

	if verbose && N < 10 {
		fmt.Fprintf(os.Stderr, "A start:\n%v\n", A)
	}
	A0 := A.Copy()
	tau0 := tau.Copy()

	mperf.FlushCache()
	time0 := mperf.Timeit(fnc)
	if verbose && N < 10 {
		fmt.Fprintf(os.Stderr, "A end:\n%v\n", A)
		tau.SetSize(1, N, 1)
		fmt.Fprintf(os.Stderr, "tau: %v\n", tau)
	}

	fn2 := func() {
		ERRlapack = lapack.Geqrf(A0, tau0)
	}

	mperf.FlushCache()
	time2 := mperf.Timeit(fn2)
	if verbose && N < 10 {
		fmt.Fprintf(os.Stderr, "A0 end:\n%v\n", A0)
		tau0.SetSize(1, N, 1) // row vector
		fmt.Fprintf(os.Stderr, "tau0: %v\n", tau0)
	}
	// now A == A0 && tau == tau0

	ok := A.AllClose(A0)
	oktau := tau.AllClose(tau0)
	if !ok || !oktau {
		// save result to globals
		Rlapack = A0
		Rmatops = A
		TAUlapack = tau0
		TAUmatops = tau
	}
	return ok && oktau, time0, time2
}
コード例 #13
0
ファイル: ldlbkl_test.go プロジェクト: sguzwf/algorithm
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))
}
コード例 #14
0
ファイル: perf_qr.go プロジェクト: sguzwf/algorithm
func runRefTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {

	var mintime time.Duration

	N := A.Cols()
	tau := matrix.FloatZeros(N, 1)

	fnc := func() {
		ERRlapack = lapack.Geqrf(A, tau)
	}

	A0 := A.Copy()
	for n := 0; n < ntest; n++ {
		if n > 0 {
			// restore original A
			A0.CopyTo(A)
			tau.Scale(0.0)
		}
		mperf.FlushCache()
		time0 := mperf.Timeit(fnc)
		if n == 0 || time0 < mintime {
			mintime = time0
		}
	}
	return mintime
}
コード例 #15
0
ファイル: ldl_test.go プロジェクト: sguzwf/algorithm
func _TestLDLnoPiv(t *testing.T) {
	N := 42
	nb := 8

	A0 := matrix.FloatUniform(N, N)
	A := matrix.FloatZeros(N, N)
	Mult(A, A0, A0, 1.0, 1.0, TRANSB)

	B := matrix.FloatNormal(A.Rows(), 2)
	w := matrix.FloatWithValue(A.Rows(), 2, 1.0)

	// B0 = A*B
	B0 := B.Copy()

	nb = 2
	L, _ := DecomposeLDLnoPiv(A.Copy(), w, LOWER, nb)
	Mult(B0, A, B, 1.0, 0.0, NOTRANS)
	SolveLDLnoPiv(B0, L, LOWER)
	t.Logf("L*D*L.T: ||B - A*X||_1: %e\n", NormP(B0.Minus(B), NORM_ONE))

	U, _ := DecomposeLDLnoPiv(A.Copy(), w, UPPER, nb)
	Mult(B0, A, B, 1.0, 0.0, NOTRANS)
	SolveLDLnoPiv(B0, U, UPPER)
	t.Logf("U*D*U.T: ||B - A*X||_1: %e\n", NormP(B0.Minus(B), NORM_ONE))

}
コード例 #16
0
ファイル: perf_ldlbk.go プロジェクト: sguzwf/algorithm
func runTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {

	var flags matops.Flags
	var mintime time.Duration

	N := A.Rows()
	ipiv := make([]int, N, N)
	flags = matops.LOWER
	if testUpper {
		flags = matops.UPPER
	}

	W := matrix.FloatZeros(A.Rows(), LB+2)
	fnc := func() {
		_, ERRmatops = matops.DecomposeBK(A, W, ipiv, flags, LB)
	}

	A0 := A.Copy()
	for n := 0; n < ntest; n++ {
		if n > 0 {
			// restore original A
			A0.CopyTo(A)
		}
		mperf.FlushCache()
		time0 := mperf.Timeit(fnc)
		if n == 0 || time0 < mintime {
			mintime = time0
		}
		if verbose {
			fmt.Printf("%.4f ms\n", time0.Seconds()*1000.0)
		}
	}
	return mintime
}
コード例 #17
0
ファイル: misc.go プロジェクト: sguzwf/algorithm
// In-place version of pack(), which also accepts matrix arguments x.
// The columns of x are elements of S, with the 's' components stored
// in unpacked storage.  On return, the 's' components are stored in
// packed storage and the off-diagonal entries are scaled by sqrt(2).
//
func pack2(x *matrix.FloatMatrix, dims *sets.DimensionSet, mnl int) (err error) {
	if len(dims.At("s")) == 0 {
		return nil
	}

	const sqrt2 = 1.41421356237309504880

	iu := mnl + dims.Sum("l", "q")
	ip := iu
	row := matrix.FloatZeros(1, x.Cols())
	//fmt.Printf("x.size = %d %d\n", x.Rows(), x.Cols())
	for _, n := range dims.At("s") {
		for k := 0; k < n; k++ {
			cnt := n - k
			row = x.GetRow(iu+(n+1)*k, row)
			//fmt.Printf("%02d: %v\n", iu+(n+1)*k, x.FloatArray())
			x.SetRow(ip, row)
			for i := 1; i < n-k; i++ {
				row = x.GetRow(iu+(n+1)*k+i, row)
				//fmt.Printf("%02d: %v\n", iu+(n+1)*k+i, x.FloatArray())
				x.SetRow(ip+i, row.Scale(sqrt2))
			}
			ip += cnt
		}
		iu += n * n
	}
	return nil
}
コード例 #18
0
ファイル: simple_test.go プロジェクト: sguzwf/algorithm
func _TestViewUpdate(t *testing.T) {
	Adata2 := [][]float64{
		[]float64{4.0, 2.0, 2.0},
		[]float64{6.0, 4.0, 2.0},
		[]float64{4.0, 6.0, 1.0},
	}

	A := matrix.FloatMatrixFromTable(Adata2, matrix.RowOrder)
	N := A.Rows()

	// simple LU decomposition without pivoting
	var A11, a10, a01, a00 matrix.FloatMatrix
	for k := 1; k < N; k++ {
		a00.SubMatrixOf(A, k-1, k-1, 1, 1)
		a01.SubMatrixOf(A, k-1, k, 1, A.Cols()-k)
		a10.SubMatrixOf(A, k, k-1, A.Rows()-k, 1)
		A11.SubMatrixOf(A, k, k)
		//t.Logf("A11: %v  a01: %v\n", A11, a01)
		a10.Scale(1.0 / a00.Float())
		MVRankUpdate(&A11, &a10, &a01, -1.0)
	}

	Ld := TriLU(A.Copy())
	Ud := TriU(A)
	t.Logf("Ld:\n%v\nUd:\n%v\n", Ld, Ud)
	An := matrix.FloatZeros(N, N)
	Mult(An, Ld, Ud, 1.0, 1.0, NOTRANS)
	t.Logf("A == Ld*Ud: %v\n", An.AllClose(An))
}
コード例 #19
0
ファイル: perf_ldl.go プロジェクト: sguzwf/algorithm
func runRefTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {

	var flags matops.Flags
	var mintime time.Duration

	N := A.Rows()
	ipiv := make([]int, N, N)
	flags = matops.LOWER
	if testUpper {
		flags = matops.UPPER
	}

	W := matrix.FloatZeros(A.Rows(), LB+2)
	fnc := func() {
		_, ERRref = matops.DecomposeLDL(A, W, ipiv, flags, 0)
	}

	A0 := A.Copy()
	for n := 0; n < ntest; n++ {
		if n > 0 {
			// restore original A
			A0.CopyTo(A)
		}
		mperf.FlushCache()
		time0 := mperf.Timeit(fnc)
		if n == 0 || time0 < mintime {
			mintime = time0
		}
	}
	return mintime
}
コード例 #20
0
ファイル: qrwyk.go プロジェクト: sguzwf/algorithm
func blockedBuildQ(A, tau, W *matrix.FloatMatrix, nb int) error {
	var err error = nil
	var ATL, ATR, ABL, ABR, AL matrix.FloatMatrix
	var A00, A01, A02, A10, A11, A12, A20, A21, A22 matrix.FloatMatrix
	var tT, tB matrix.FloatMatrix
	var t0, tau1, t2, Tw, Wrk matrix.FloatMatrix
	var mb int

	mb = A.Rows() - A.Cols()
	Twork := matrix.FloatZeros(nb, nb)

	partition2x2(
		&ATL, &ATR,
		&ABL, &ABR, A, mb, 0, pBOTTOMRIGHT)
	partition2x1(
		&tT,
		&tB, tau, 0, pBOTTOM)

	// clearing of the columns of the right and setting ABR to unit diagonal
	// (only if not applying all reflectors, kb > 0)

	for ATL.Rows() > 0 && ATL.Cols() > 0 {
		repartition2x2to3x3(&ATL,
			&A00, &A01, &A02,
			&A10, &A11, &A12,
			&A20, &A21, &A22, A, nb, pTOPLEFT)
		repartition2x1to3x1(&tT,
			&t0,
			&tau1,
			&t2, tau, nb, pTOP)

		// --------------------------------------------------------

		// build block reflector from current block
		merge2x1(&AL, &A11, &A21)
		Twork.SubMatrix(&Tw, 0, 0, A11.Cols(), A11.Cols())
		unblkQRBlockReflector(&Tw, &AL, &tau1)

		// update with current block reflector (I - Y*T*Y.T)*Atrailing
		W.SubMatrix(&Wrk, 0, 0, A12.Cols(), A11.Cols())
		updateWithQT(&A12, &A22, &A11, &A21, &Tw, &Wrk, nb, false)

		// use unblocked version to compute current block
		W.SubMatrix(&Wrk, 0, 0, 1, A11.Cols())
		unblockedBuildQ(&AL, &tau1, &Wrk, 0)

		// zero upper part
		A01.SetIndexes(0.0)

		// --------------------------------------------------------
		continue3x3to2x2(
			&ATL, &ATR,
			&ABL, &ABR, &A00, &A11, &A22, A, pTOPLEFT)
		continue3x1to2x1(
			&tT,
			&tB, &t0, &tau1, tau, pTOP)
	}
	return err
}
コード例 #21
0
ファイル: ldl_test.go プロジェクト: sguzwf/algorithm
func TestLDLlower(t *testing.T) {
	/*
	   Ldata := [][]float64{
	    []float64{7.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0},
	    []float64{7.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0},
	    []float64{7.0, 6.0, 5.0, 0.0, 0.0, 0.0, 0.0},
	    []float64{7.0, 6.0, 5.0, 4.0, 0.0, 0.0, 0.0},
	    []float64{7.0, 6.0, 5.0, 4.0, 6.0, 0.0, 0.0},
	    []float64{7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 0.0},
	    []float64{7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0}}
	   A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
	   N := A.Rows()
	*/
	N := 7
	nb := 0

	A0 := matrix.FloatUniform(N, N)
	A := matrix.FloatZeros(N, N)
	Mult(A, A0, A0, 1.0, 1.0, TRANSB)

	B := matrix.FloatNormal(A.Rows(), 2)
	B0 := B.Copy()
	B1 := B.Copy()
	Mult(B0, A, B, 1.0, 0.0, NOTRANS)
	_, _, _ = B0, B1, A0

	ipiv := make([]int, N, N)
	L, _ := DecomposeLDL(A.Copy(), nil, ipiv, LOWER, 0)
	//t.Logf("unblk: ipiv = %v\n", ipiv)
	//t.Logf("unblk: L\n%v\n", L)

	ApplyRowPivots(B, ipiv, FORWARD)
	MultTrm(B, L, 1.0, LOWER|UNIT|TRANSA)
	MultDiag(B, L, LEFT)
	MultTrm(B, L, 1.0, LOWER|UNIT)
	ApplyRowPivots(B0, ipiv, FORWARD)
	t.Logf(" unblk: L*D*L.T %d pivots: ||A*B - L*D*L.T*B||_1: %e\n",
		NumPivots(ipiv), NormP(B.Minus(B0), NORM_ONE))
	t.Logf("pivots: %v\n", ipiv)

	nb = 4
	w := matrix.FloatWithValue(A.Rows(), nb, 1.0)
	L, _ = DecomposeLDL(A.Copy(), w, ipiv, LOWER, nb)
	//t.Logf("blk: ipiv = %v\n", ipiv)
	//t.Logf("blk: L\n%v\n", L)

	// B2 = A*B1 == A*B
	B2 := B1.Copy()
	Mult(B2, A, B1, 1.0, 0.0, NOTRANS)

	ApplyRowPivots(B1, ipiv, FORWARD)
	MultTrm(B1, L, 1.0, LOWER|UNIT|TRANSA)
	MultDiag(B1, L, LEFT)
	MultTrm(B1, L, 1.0, LOWER|UNIT)
	ApplyRowPivots(B2, ipiv, FORWARD)
	t.Logf("   blk: L*D*L.T %d pivots: ||A*B - L*D*L.T*B||_1: %e\n",
		NumPivots(ipiv), NormP(B2.Minus(B1), NORM_ONE))
	t.Logf("pivots: %v\n", ipiv)
}
コード例 #22
0
ファイル: solvers.go プロジェクト: sguzwf/algorithm
// Solves a quadratic program
//
//        minimize    (1/2)*x'*P*x + q'*x
//        subject to  G*x <= h
//                    A*x = b.
//
//
func Qp(P, q, G, h, A, b *matrix.FloatMatrix, solopts *SolverOptions,
	initvals *sets.FloatMatrixSet) (sol *Solution, err error) {

	sol = nil
	if P == nil || P.Rows() != P.Cols() {
		err = errors.New("'P' must a non-nil square matrix")
		return
	}
	if q == nil {
		err = errors.New("'q' must a non-nil matrix")
		return
	}
	if q.Rows() != P.Rows() || q.Cols() > 1 {
		err = errors.New(fmt.Sprintf("'q' must be matrix of size (%d,1)", P.Rows()))
		return
	}
	if G == nil {
		G = matrix.FloatZeros(0, P.Rows())
	}
	if G.Cols() != P.Rows() {
		err = errors.New(fmt.Sprintf("'G' must be matrix of %d columns", P.Rows()))
		return
	}
	if h == nil {
		h = matrix.FloatZeros(G.Rows(), 1)
	}
	if h.Rows() != G.Rows() || h.Cols() > 1 {
		err = errors.New(fmt.Sprintf("'h' must be matrix of size (%d,1)", G.Rows()))
		return
	}
	if A == nil {
		A = matrix.FloatZeros(0, P.Rows())
	}
	if A.Cols() != P.Rows() {
		err = errors.New(fmt.Sprintf("'A' must be matrix of %d columns", P.Rows()))
		return
	}
	if b == nil {
		b = matrix.FloatZeros(A.Rows(), 1)
	}
	if b.Rows() != A.Rows() {
		err = errors.New(fmt.Sprintf("'b' must be matrix of size (%d,1)", A.Rows()))
		return
	}
	return ConeQp(P, q, G, h, A, b, nil, solopts, initvals)
}
コード例 #23
0
ファイル: mvperf.go プロジェクト: sguzwf/algorithm
func CTestMVMultTransA(m, n, p int) (fnc func(), A, X, Y *matrix.FloatMatrix) {
	A = matrix.FloatNormal(n, m)
	X = matrix.FloatNormal(n, 1)
	Y = matrix.FloatZeros(m, 1)
	fnc = func() {
		matops.MVMultTransA(Y, A, X, 1.0, 1.0)
	}
	return
}
コード例 #24
0
ファイル: mvperf.go プロジェクト: sguzwf/algorithm
func TestTemplate(m, n, p int) (fnc func(), A, X, Y *matrix.FloatMatrix) {
	A = matrix.FloatNormal(m, n)
	X = matrix.FloatNormal(n, 1)
	Y = matrix.FloatZeros(m, 1)
	fnc = func() {
		// test core here
	}
	return
}
コード例 #25
0
ファイル: mvperf.go プロジェクト: sguzwf/algorithm
func CTestGemv(m, n, p int) (fnc func(), A, X, Y *matrix.FloatMatrix) {
	A = matrix.FloatNormal(m, n)
	X = matrix.FloatNormal(n, 1)
	Y = matrix.FloatZeros(m, 1)
	fnc = func() {
		blas.GemvFloat(A, X, Y, 1.0, 1.0)
	}
	return
}
コード例 #26
0
ファイル: mmperf.go プロジェクト: sguzwf/algorithm
func MMTestMultTransAB(m, n, p int) (fnc func(), A, B, C *matrix.FloatMatrix) {
	A = matrix.FloatNormal(p, m)
	B = matrix.FloatNormal(n, p)
	C = matrix.FloatZeros(m, n)
	fnc = func() {
		matops.Mult(C, A, B, 1.0, 1.0, matops.TRANSA|matops.TRANSB)
	}
	return
}
コード例 #27
0
ファイル: qrwy.go プロジェクト: sguzwf/algorithm
/*
 * Compute QR factorization of a M-by-N matrix A: A = Q * R.
 *
 * Arguments:
 *  A   On entry, the M-by-N matrix A. On exit, the elements on and above
 *      the diagonal contain the min(M,N)-by-N upper trapezoidal matrix R.
 *      The elements below the diagonal with the column vector 'tau', represent
 *      the ortogonal matrix Q as product of elementary reflectors.
 *
 * tau  On exit, the scalar factors of the elemenentary reflectors.
 *
 * W    Workspace, N-by-nb matrix used for work space in blocked invocations.
 *
 * nb   The block size used in blocked invocations. If nb is zero on N <= nb
 *      unblocked algorithm is used.
 *
 * Returns:
 *      Decomposed matrix A and error indicator.
 *
 * DecomposeQR is compatible with lapack.DGEQRF
 */
func DecomposeQR(A, tau, W *matrix.FloatMatrix, nb int) (*matrix.FloatMatrix, error) {
	var err error = nil

	if nb == 0 || A.Cols() <= nb {
		unblockedQR(A, tau)
	} else {
		Twork := matrix.FloatZeros(nb, nb)
		if W == nil {
			W = matrix.FloatZeros(A.Cols(), nb)
		} else if W.Cols() < nb || W.Rows() < A.Cols() {
			return nil, errors.New("work space too small")
		}
		var Wrk matrix.FloatMatrix
		Wrk.SubMatrixOf(W, 0, 0, A.Cols(), nb)
		blockedQR(A, tau, Twork, &Wrk, nb)
	}
	return A, err
}
コード例 #28
0
ファイル: symperf.go プロジェクト: sguzwf/algorithm
func CTestBlasUp(m, n, p int) (fnc func(), A, B, C *matrix.FloatMatrix) {
	A = matrix.FloatNormalSymmetric(m, matrix.Lower)
	B = matrix.FloatNormal(m, n)
	C = matrix.FloatZeros(m, n)
	fnc = func() {
		blas.SymmFloat(A, B, C, 1.0, 1.0, linalg.OptUpper)
	}
	return fnc, A, B, C
}
コード例 #29
0
ファイル: symperf.go プロジェクト: sguzwf/algorithm
func CTestSymmLower(m, n, p int) (fnc func(), A, B, C *matrix.FloatMatrix) {
	A = matrix.FloatNormalSymmetric(m, matrix.Upper)
	B = matrix.FloatNormal(m, n)
	C = matrix.FloatZeros(m, n)
	fnc = func() {
		matops.MultSym(C, A, B, 1.0, 1.0, matops.LEFT|matops.LOWER)
	}
	return fnc, A, B, C
}
コード例 #30
0
ファイル: symperf.go プロジェクト: sguzwf/algorithm
func TestTemplate(m, n, p int) (fnc func(), A, B, C *matrix.FloatMatrix) {
	A = matrix.FloatNormalSymmetric(m, matrix.Upper)
	B = matrix.FloatNormal(m, n)
	C = matrix.FloatZeros(m, n)
	fnc = func() {
		// test core here
	}
	return
}