Пример #1
0
// See function Trsm.
func TrsmFloat(A, B *matrix.FloatMatrix, alpha float64, opts ...linalg.Option) (err error) {

	params, e := linalg.GetParameters(opts...)
	if e != nil {
		err = e
		return
	}
	ind := linalg.GetIndexOpts(opts...)
	err = check_level3_func(ind, ftrsm, A, B, nil, params)
	if err != nil {
		return
	}
	if ind.N == 0 || ind.M == 0 {
		return
	}
	Aa := A.FloatArray()
	Ba := B.FloatArray()
	uplo := linalg.ParamString(params.Uplo)
	transA := linalg.ParamString(params.TransA)
	side := linalg.ParamString(params.Side)
	diag := linalg.ParamString(params.Diag)
	dtrsm(side, uplo, transA, diag, ind.M, ind.N, alpha,
		Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb)
	return
}
Пример #2
0
func GbtrsFloat(A, B *matrix.FloatMatrix, ipiv []int32, KL int, opts ...linalg.Option) error {
	pars, err := linalg.GetParameters(opts...)
	if err != nil {
		return err
	}
	ind := linalg.GetIndexOpts(opts...)

	ind.Kl = KL
	err = checkGbtrs(ind, A, B, ipiv)
	if err != nil {
		return err
	}
	if ind.N == 0 || ind.Nrhs == 0 {
		return nil
	}
	Aa := A.FloatArray()
	Ba := B.FloatArray()
	trans := linalg.ParamString(pars.Trans)
	info := dgbtrs(trans, ind.N, ind.Kl, ind.Ku, ind.Nrhs,
		Aa[ind.OffsetA:], ind.LDa, ipiv, Ba[ind.OffsetB:], ind.LDb)
	if info != 0 {
		return onError(fmt.Sprintf("Gbtrs: lapack error: %d", info))
	}
	return nil
}
Пример #3
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// See function Syrk.
func SyrkFloat(A, C *matrix.FloatMatrix, alpha, beta float64, opts ...linalg.Option) (err error) {

	params, e := linalg.GetParameters(opts...)
	if e != nil {
		err = e
		return
	}
	ind := linalg.GetIndexOpts(opts...)
	err = check_level3_func(ind, fsyrk, A, nil, C, params)
	if e != nil || err != nil {
		return
	}
	if ind.N == 0 {
		return
	}
	Aa := A.FloatArray()
	Ca := C.FloatArray()
	uplo := linalg.ParamString(params.Uplo)
	trans := linalg.ParamString(params.Trans)
	//diag := linalg.ParamString(params.Diag)
	dsyrk(uplo, trans, ind.N, ind.K, alpha, Aa[ind.OffsetA:], ind.LDa, beta,
		Ca[ind.OffsetC:], ind.LDc)

	return
}
Пример #4
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func solveMVTest(t *testing.T, A, X0 *matrix.FloatMatrix, flags Flags, bN, bNB int) {
	X1 := X0.Copy()

	uplo := linalg.OptUpper
	diag := linalg.OptNonUnit
	if flags&LOWER != 0 {
		uplo = linalg.OptLower
	}
	if flags&UNIT != 0 {
		diag = linalg.OptUnit
	}

	blas.TrsvFloat(A, X0, uplo, diag)

	Ar := A.FloatArray()
	Xr := X1.FloatArray()
	if bN == bNB {
		DSolveUnblkMV(Xr, Ar, flags, 1, A.LeadingIndex(), bN)
	} else {
		DSolveBlkMV(Xr, Ar, flags, 1, A.LeadingIndex(), bN, bNB)
	}
	ok := X1.AllClose(X0)
	t.Logf("X1 == X0: %v\n", ok)
	if !ok && bN < 8 {
		t.Logf("A=\n%v\n", A)
		t.Logf("X0=\n%v\n", X0)
		t.Logf("blas: X0\n%v\n", X0)
		t.Logf("X1:\n%v\n", X1)
	}
}
Пример #5
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// Solve multiple right sides. If flags&UNIT then A diagonal is assumed to
// to unit and is not referenced. (blas.TRSM)
//      alpha*B = A.-1*B if flags&LEFT
//      alpha*B = A.-T*B if flags&(LEFT|TRANS)
//      alpha*B = B*A.-1 if flags&RIGHT
//      alpha*B = B*A.-T if flags&(RIGHT|TRANS)
//
// Matrix A is N*N triangular matrix defined with flags bits as follow
//  LOWER       non-unit lower triangular
//  LOWER|UNIT  unit lower triangular
//  UPPER       non-unit upper triangular
//  UPPER|UNIT  unit upper triangular
//
// Matrix B is N*P if flags&LEFT or P*N if flags&RIGHT.
//
func SolveTrm(B, A *matrix.FloatMatrix, alpha float64, flags Flags) error {

	ok := true
	empty := false
	br, bc := B.Size()
	ar, ac := A.Size()
	switch flags & (LEFT | RIGHT) {
	case LEFT:
		empty = br == 0
		ok = br == ac && ac == ar
	case RIGHT:
		empty = bc == 0
		ok = bc == ar && ac == ar
	}
	if empty {
		return nil
	}
	if !ok {
		return onError("A, B size mismatch")
	}

	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Br := B.FloatArray()
	ldB := B.LeadingIndex()

	E := bc
	if flags&RIGHT != 0 {
		E = br
	}
	// if more workers available can divide to tasks by B columns if flags&LEFT or by
	// B rows if flags&RIGHT.
	calgo.DSolveBlk(Br, Ar, alpha, calgo.Flags(flags), ldB, ldA, ac, 0, E, nB)
	return nil
}
Пример #6
0
func trmvTest(t *testing.T, A *matrix.FloatMatrix, flags Flags, nb int) bool {
	N := A.Cols()
	//S := 0
	//E := A.Cols()
	X0 := matrix.FloatWithValue(A.Rows(), 1, 2.0)
	X1 := X0.Copy()

	trans := linalg.OptNoTrans
	if flags&TRANS != 0 {
		trans = linalg.OptTrans
	}
	diag := linalg.OptNonUnit
	if flags&UNIT != 0 {
		diag = linalg.OptUnit
	}
	uplo := linalg.OptUpper
	if flags&LOWER != 0 {
		uplo = linalg.OptLower
	}

	blas.TrmvFloat(A, X0, uplo, diag, trans)

	Ar := A.FloatArray()
	Xr := X1.FloatArray()
	if nb == 0 {
		DTrimvUnblkMV(Xr, Ar, flags, 1, A.LeadingIndex(), N)
	}
	result := X0.AllClose(X1)
	t.Logf("   X0 == X1: %v\n", result)
	if !result && A.Rows() < 8 {
		t.Logf("  BLAS TRMV X0:\n%v\n", X0)
		t.Logf("  DTrmv X1:\n%v\n", X1)
	}
	return result
}
Пример #7
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func syrkTest(t *testing.T, C, A *matrix.FloatMatrix, flags Flags, vlen, nb int) bool {
	//var B0 *matrix.FloatMatrix
	P := A.Cols()
	S := 0
	E := C.Rows()
	C0 := C.Copy()

	trans := linalg.OptNoTrans
	if flags&TRANSA != 0 {
		trans = linalg.OptTrans
		P = A.Rows()
	}
	uplo := linalg.OptUpper
	if flags&LOWER != 0 {
		uplo = linalg.OptLower
	}

	blas.SyrkFloat(A, C0, 1.0, 1.0, uplo, trans)
	if A.Rows() < 8 {
		//t.Logf("..A\n%v\n", A)
		t.Logf("  BLAS C0:\n%v\n", C0)
	}

	Ar := A.FloatArray()
	Cr := C.FloatArray()
	DSymmRankBlk(Cr, Ar, 1.0, 1.0, flags, C.LeadingIndex(), A.LeadingIndex(),
		P, S, E, vlen, nb)
	result := C0.AllClose(C)
	t.Logf("   C0 == C: %v\n", result)
	if A.Rows() < 8 {
		t.Logf("  DMRank C:\n%v\n", C)
	}
	return result
}
Пример #8
0
func (p *floorPlan) F2(x, z *matrix.FloatMatrix) (f, Df, H *matrix.FloatMatrix, err error) {
	f, Df, err = p.F1(x)
	x17 := matrix.FloatVector(x.FloatArray()[17:])
	tmp := matrix.Div(p.Amin, matrix.Pow(x17, 3.0))
	tmp = matrix.Mul(z, tmp).Scale(2.0)
	diag := matrix.FloatDiagonal(5, tmp.FloatArray()...)
	H = matrix.FloatZeros(22, 22)
	H.SetSubMatrix(17, 17, diag)
	return
}
Пример #9
0
func sinv(x, y *matrix.FloatMatrix, dims *sets.DimensionSet, mnl int) (err error) {
	/*DEBUGGED*/

	err = nil

	// For the nonlinear and 'l' blocks:
	//
	//     yk o\ xk = yk .\ xk.

	ind := mnl + dims.At("l")[0]
	blas.Tbsv(y, x, &la_.IOpt{"n", ind}, &la_.IOpt{"k", 0}, &la_.IOpt{"ldA", 1})

	// For the 'q' blocks:
	//
	//                        [ l0   -l1'              ]
	//     yk o\ xk = 1/a^2 * [                        ] * xk
	//                        [ -l1  (a*I + l1*l1')/l0 ]
	//
	// where yk = (l0, l1) and a = l0^2 - l1'*l1.

	for _, m := range dims.At("q") {
		aa := blas.Nrm2Float(y, &la_.IOpt{"n", m - 1}, &la_.IOpt{"offset", ind + 1})
		ee := y.GetIndex(ind)
		aa = (ee + aa) * (ee - aa)
		cc := x.GetIndex(ind)
		dd := blas.DotFloat(x, y, &la_.IOpt{"n", m - 1}, &la_.IOpt{"offsetx", ind + 1},
			&la_.IOpt{"offsety", ind + 1})
		x.SetIndex(ind, cc*ee-dd)
		blas.ScalFloat(x, aa/ee, &la_.IOpt{"n", m - 1}, &la_.IOpt{"offset", ind + 1})
		blas.AxpyFloat(y, x, dd/ee-cc, &la_.IOpt{"n", m - 1},
			&la_.IOpt{"offsetx", ind + 1}, &la_.IOpt{"offsety", ind + 1})
		blas.ScalFloat(x, 1.0/aa, &la_.IOpt{"n", m}, &la_.IOpt{"offset", ind})
		ind += m
	}

	// For the 's' blocks:
	//
	//     yk o\ xk =  xk ./ gamma
	//
	// where gammaij = .5 * (yk_i + yk_j).

	ind2 := ind
	for _, m := range dims.At("s") {
		for j := 0; j < m; j++ {
			u := matrix.FloatVector(y.FloatArray()[ind2+j : ind2+m])
			u.Add(y.GetIndex(ind2 + j))
			u.Scale(0.5)
			blas.Tbsv(u, x, &la_.IOpt{"n", m - j}, &la_.IOpt{"k", 0}, &la_.IOpt{"lda", 1},
				&la_.IOpt{"offsetx", ind + j*(m+1)})
		}
		ind += m * m
		ind2 += m
	}
	return
}
Пример #10
0
// 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
}
Пример #11
0
// See function Scal.
func ScalFloat(X *matrix.FloatMatrix, alpha float64, opts ...linalg.Option) (err error) {
	ind := linalg.GetIndexOpts(opts...)
	err = check_level1_func(ind, fscal, X, nil)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		return
	}
	Xa := X.FloatArray()
	dscal(ind.Nx, alpha, Xa[ind.OffsetX:], ind.IncX)
	return
}
Пример #12
0
// A = alpha*A + beta*B
// A = alpha*A + beta*B.T  if flags&TRANSB
func ScalePlus(A, B *matrix.FloatMatrix, alpha, beta float64, flags Flags) error {

	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Br := B.FloatArray()
	ldB := B.LeadingIndex()
	S := 0
	L := A.Cols()
	R := 0
	E := A.Rows()
	calgo.DScalePlus(Ar, Br, alpha, beta, calgo.Flags(flags), ldA, ldB, S, L, R, E)
	return nil
}
Пример #13
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// Return Complex(Real, Imag). Return a new matrix.
func Complex(Real, Imag *matrix.FloatMatrix) *matrix.ComplexMatrix {
	if !Real.SizeMatch(Imag.Size()) {
		return nil
	}
	C := matrix.ComplexZeros(Real.Size())
	Rr := Real.FloatArray()
	Ir := Imag.FloatArray()
	Cr := C.ComplexArray()
	for i, _ := range Rr {
		Cr[i] = complex(Rr[i], Ir[i])
	}
	return C
}
Пример #14
0
func trmmTest(t *testing.T, A *matrix.FloatMatrix, flags Flags, nb int) bool {
	var B0 *matrix.FloatMatrix
	N := A.Cols()
	S := 0
	E := A.Cols()
	side := linalg.OptLeft
	if flags&RIGHT != 0 {
		B0 = matrix.FloatWithValue(2, A.Rows(), 2.0)
		side = linalg.OptRight
		E = B0.Rows()
	} else {
		B0 = matrix.FloatWithValue(A.Rows(), 2, 2.0)
		E = B0.Cols()
	}
	B1 := B0.Copy()

	trans := linalg.OptNoTrans
	if flags&TRANSA != 0 {
		trans = linalg.OptTransA
	}
	diag := linalg.OptNonUnit
	if flags&UNIT != 0 {
		diag = linalg.OptUnit
	}
	uplo := linalg.OptUpper
	if flags&LOWER != 0 {
		uplo = linalg.OptLower
	}

	blas.TrmmFloat(A, B0, 1.0, uplo, diag, trans, side)
	if A.Rows() < 8 {
		//t.Logf("..A\n%v\n", A)
		t.Logf("  BLAS B0:\n%v\n", B0)
	}

	Ar := A.FloatArray()
	Br := B1.FloatArray()
	if nb != 0 {
		DTrmmBlk(Br, Ar, 1.0, flags, B1.LeadingIndex(), A.LeadingIndex(),
			N, S, E, nb)
	} else {
		DTrmmUnblk(Br, Ar, 1.0, flags, B1.LeadingIndex(), A.LeadingIndex(),
			N, S, E, 0)
	}
	result := B0.AllClose(B1)
	t.Logf("   B0 == B1: %v\n", result)
	if A.Rows() < 8 {
		t.Logf("  DTrmm B1:\n%v\n", B1)
	}
	return result
}
Пример #15
0
// See function Copy.
func CopyFloat(X, Y *matrix.FloatMatrix, opts ...linalg.Option) (err error) {
	ind := linalg.GetIndexOpts(opts...)
	err = check_level1_func(ind, fcopy, X, Y)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		return
	}
	Xa := X.FloatArray()
	Ya := Y.FloatArray()
	dcopy(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	return
}
Пример #16
0
func GesvdFloat(A, S, U, Vt *matrix.FloatMatrix, opts ...linalg.Option) error {
	pars, err := linalg.GetParameters(opts...)
	if err != nil {
		return err
	}
	ind := linalg.GetIndexOpts(opts...)
	err = checkGesvd(ind, pars, A, S, U, Vt)
	if err != nil {
		return err
	}
	if ind.M == 0 || ind.N == 0 {
		return nil
	}
	Aa := A.FloatArray()
	Sa := S.FloatArray()
	var Ua, Va []float64
	Ua = nil
	Va = nil
	if U != nil {
		Ua = U.FloatArray()[ind.OffsetU:]
	}
	if Vt != nil {
		Va = Vt.FloatArray()[ind.OffsetVt:]
	}
	info := dgesvd(linalg.ParamString(pars.Jobu), linalg.ParamString(pars.Jobvt),
		ind.M, ind.N, Aa[ind.OffsetA:], ind.LDa, Sa[ind.OffsetS:], Ua, ind.LDu, Va, ind.LDvt)
	if info != 0 {
		return onError(fmt.Sprintf("GesvdFloat lapack error: %d", info))
	}
	return nil
}
Пример #17
0
// See function Asum.
func AsumFloat(X *matrix.FloatMatrix, opts ...linalg.Option) (v float64) {
	v = math.NaN()
	ind := linalg.GetIndexOpts(opts...)
	err := check_level1_func(ind, fasum, X, nil)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		v = 0.0
		return
	}
	Xa := X.FloatArray()
	v = dasum(ind.Nx, Xa[ind.OffsetX:], ind.IncX)
	return
}
Пример #18
0
// See functin Dot.
func DotFloat(X, Y *matrix.FloatMatrix, opts ...linalg.Option) (v float64) {
	v = math.NaN()
	ind := linalg.GetIndexOpts(opts...)
	err := check_level1_func(ind, fdot, X, Y)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		v = 0.0
		return
	}
	Xa := X.FloatArray()
	Ya := Y.FloatArray()
	v = ddot(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	return
}
Пример #19
0
// A = A + alpha*X*Y.T; A is N*N symmetric, X is row or column vector of length N.
func MVSymmUpdateUpper(A, X *matrix.FloatMatrix, alpha float64) error {

	if X.Rows() != 1 && X.Cols() != 1 {
		return errors.New("X not a vector.")
	}

	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Xr := X.FloatArray()
	incX := 1
	if X.Rows() == 1 {
		// row vector
		incX = X.LeadingIndex()
	}
	// NOTE: This could diveded to parallel tasks per column.
	calgo.DSymmRankMV(Ar, Xr, alpha, calgo.UPPER, ldA, incX, 0, A.Cols(), 0)
	return nil
}
Пример #20
0
func GbtrfFloat(A *matrix.FloatMatrix, ipiv []int32, M, KL int, opts ...linalg.Option) error {
	ind := linalg.GetIndexOpts(opts...)
	ind.M = M
	ind.Kl = KL
	err := checkGbtrf(ind, A, ipiv)
	if err != nil {
		return err
	}
	if ind.M == 0 || ind.N == 0 {
		return nil
	}
	Aa := A.FloatArray()
	info := dgbtrf(ind.M, ind.N, ind.Kl, ind.Ku, Aa[ind.OffsetA:], ind.LDa, ipiv)
	if info != 0 {
		return onError(fmt.Sprintf("Gbtrf lapack error: %d", info))
	}
	return nil
}
Пример #21
0
func PotrfFloat(A *matrix.FloatMatrix, opts ...linalg.Option) error {
	pars, err := linalg.GetParameters(opts...)
	if err != nil {
		return err
	}
	ind := linalg.GetIndexOpts(opts...)
	err = checkPotrf(ind, A)
	if ind.N == 0 {
		return nil
	}
	Aa := A.FloatArray()
	uplo := linalg.ParamString(pars.Uplo)
	info := dpotrf(uplo, ind.N, Aa[ind.OffsetA:], ind.LDa)
	if info != 0 {
		return onError(fmt.Sprintf("Potrf: lapack error %d", info))
	}
	return nil
}
Пример #22
0
// Convert triangular band matrix S to new matrix R with elements stored in
// triangular-band-packed mode. Returned matrix has dimensions R.Rows() == K+1
// and R.Cols() == S.Cols(). Parameter flags must have either UPPER or LOWER bit set.
func BandedTrmMatrix(S *matrix.FloatMatrix, K int, flags Flags) (R *matrix.FloatMatrix) {
	if S.Rows() != S.Cols() {
		return nil
	}
	M := S.Rows()
	N := S.Cols()

	R = nil
	Sr := S.FloatArray()
	if flags&UPPER != 0 {
		// Upper triangular matrix
		R = matrix.FloatZeros(K+1, M)
		Rr := R.FloatArray()
		for j := 0; j < N; j++ {
			m := K + 1 - j
			// is = max(0, j-K)
			is := j - K
			if is < 0 {
				is = 0
			}
			for i := is; i <= j; i++ {
				Rr[j*(K+1)+m+i-1] = Sr[j*M+i]
			}
		}
	} else if flags&LOWER != 0 {
		// Lower triangular matrix
		R = matrix.FloatZeros(K+1, M)
		Rr := R.FloatArray()
		for j := 0; j < N; j++ {
			m := 1 - j
			// ie = min(N, j+K+1)
			ie := j + K + 1
			if ie >= N {
				ie = N
			}
			for i := j; i < ie; i++ {
				Rr[j*(K+1)+m+i-1] = Sr[j*M+i]
			}
		}
	}
	return
}
Пример #23
0
// Rank update for symmetric lower or upper matrix (blas.SYRK)
//      C = beta*C + alpha*A*A.T + alpha*A.T*A
func RankUpdateSym(C, A *matrix.FloatMatrix, alpha, beta float64, flags Flags) error {
	if C.Rows() != C.Cols() {
		return onError("C not a square matrix")
	}
	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Cr := C.FloatArray()
	ldC := C.LeadingIndex()
	S := 0
	E := C.Rows()
	P := A.Cols()
	if flags&TRANSA != 0 {
		P = A.Rows()
	}
	// if more workers available C can be divided to blocks [S:E, S:E] along diagonal
	// and updated in separate tasks.
	calgo.DSymmRankBlk(Cr, Ar, alpha, beta, calgo.Flags(flags), ldC, ldA, P, S, E,
		vpLen, nB)
	return nil
}
Пример #24
0
// See function Syr.
func SyrFloat(X, A *matrix.FloatMatrix, alpha float64, opts ...linalg.Option) (err error) {

	var params *linalg.Parameters
	params, err = linalg.GetParameters(opts...)
	if err != nil {
		return
	}
	ind := linalg.GetIndexOpts(opts...)
	err = check_level2_func(ind, fsyr, X, nil, A, params)
	if err != nil {
		return
	}
	if ind.N == 0 {
		return
	}
	Xa := X.FloatArray()
	Aa := A.FloatArray()
	uplo := linalg.ParamString(params.Uplo)
	dsyr(uplo, ind.N, alpha, Xa[ind.OffsetX:], ind.IncX, Aa[ind.OffsetA:], ind.LDa)
	return
}
Пример #25
0
func (p *floorPlan) F1(x *matrix.FloatMatrix) (f, Df *matrix.FloatMatrix, err error) {
	err = nil
	mn := x.Min(-1, -2, -3, -4, -5)
	if mn <= 0.0 {
		f, Df = nil, nil
		return
	}
	zeros := matrix.FloatZeros(5, 12)
	dk1 := matrix.FloatDiagonal(5, -1.0)
	dk2 := matrix.FloatZeros(5, 5)
	x17 := matrix.FloatVector(x.FloatArray()[17:])
	// -( Amin ./ (x17 .* x17) )
	diag := matrix.Div(p.Amin, matrix.Mul(x17, x17)).Scale(-1.0)
	dk2.SetIndexesFromArray(diag.FloatArray(), matrix.MakeDiagonalSet(5)...)
	Df, _ = matrix.FloatMatrixStacked(matrix.StackRight, zeros, dk1, dk2)

	x12 := matrix.FloatVector(x.FloatArray()[12:17])
	// f = -x[12:17] + div(Amin, x[17:]) == div(Amin, x[17:]) - x[12:17]
	f = matrix.Minus(matrix.Div(p.Amin, x17), x12)
	return
}
Пример #26
0
func GbsvFloat(A, B *matrix.FloatMatrix, ipiv []int32, kl int, opts ...linalg.Option) error {

	ind := linalg.GetIndexOpts(opts...)
	ind.Kl = kl
	err := checkGbsv(ind, A, B, ipiv)
	if err != nil {
		return err
	}
	if ind.N == 0 || ind.Nrhs == 0 {
		return nil
	}

	Aa := A.FloatArray()
	Ba := B.FloatArray()
	info := dgbsv(ind.N, ind.Kl, ind.Ku, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa,
		ipiv, Ba[ind.OffsetB:], ind.LDb)
	if info != 0 {
		return onError(fmt.Sprintf("Gbsv lapack error: %d", info))
	}
	return nil
}
Пример #27
0
// Calculate C = alpha*A*B.T + beta*C, C is M*N, A is M*P and B is N*P
func MMMultTransB(C, A, B *matrix.FloatMatrix, alpha, beta float64) error {
	psize := int64(C.NumElements() * A.Cols())
	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Br := B.FloatArray()
	ldB := B.LeadingIndex()
	Cr := C.FloatArray()
	ldC := C.LeadingIndex()
	if nWorker <= 1 || psize <= limitOne {
		calgo.DMult(Cr, Ar, Br, alpha, beta, calgo.TRANSB, ldC, ldA, ldB,
			B.Rows(), 0, C.Cols(), 0, C.Rows(), vpLen, nB, mB)
		return nil
	}

	// here we have more than one worker available
	worker := func(cstart, cend, rstart, rend int, ready chan int) {
		calgo.DMult(Cr, Ar, Br, alpha, beta, calgo.TRANSB, ldC, ldA, ldB, B.Rows(),
			cstart, cend, rstart, rend, vpLen, nB, mB)
		ready <- 1
	}
	colworks, rowworks := divideWork(C.Rows(), C.Cols(), nWorker)
	scheduleWork(colworks, rowworks, C.Cols(), C.Rows(), worker)
	//scheduleWork(colworks, rowworks, worker)
	return nil
}
Пример #28
0
func Mult0(C, A, B *matrix.FloatMatrix, alpha, beta float64, flags Flags) error {
	if A.Cols() != B.Rows() {
		return errors.New("A.cols != B.rows: size mismatch")
	}
	psize := int64(C.NumElements()) * int64(A.Cols())
	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Br := B.FloatArray()
	ldB := B.LeadingIndex()
	Cr := C.FloatArray()
	ldC := C.LeadingIndex()

	if nWorker <= 1 || psize <= limitOne {
		calgo.DMult0(Cr, Ar, Br, alpha, beta, calgo.Flags(flags), ldC, ldA, ldB, B.Rows(),
			0, C.Cols(), 0, C.Rows(),
			vpLen, nB, mB)
		return nil
	}
	// here we have more than one worker available
	worker := func(cstart, cend, rstart, rend int, ready chan int) {
		calgo.DMult0(Cr, Ar, Br, alpha, beta, calgo.Flags(flags), ldC, ldA, ldB, B.Rows(),
			cstart, cend, rstart, rend, vpLen, nB, mB)
		ready <- 1
	}
	colworks, rowworks := divideWork(C.Rows(), C.Cols(), nWorker)
	scheduleWork(colworks, rowworks, C.Cols(), C.Rows(), worker)
	return nil
}
Пример #29
0
func MVSymm2UpdateUpper(A, X, Y *matrix.FloatMatrix, alpha float64) error {

	if Y.Rows() != 1 && Y.Cols() != 1 {
		return errors.New("Y not a vector.")
	}
	if X.Rows() != 1 && X.Cols() != 1 {
		return errors.New("X not a vector.")
	}

	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Yr := Y.FloatArray()
	incY := 1
	if Y.Rows() == 1 {
		// row vector
		incY = Y.LeadingIndex()
	}
	Xr := X.FloatArray()
	incX := 1
	if X.Rows() == 1 {
		// row vector
		incX = X.LeadingIndex()
	}
	// NOTE: This could diveded to parallel tasks like matrix-matrix multiplication
	calgo.DSymmRank2MV(Ar, Xr, Yr, alpha, calgo.UPPER, ldA, incY, incX, 0, A.Cols(), 0)
	return nil
}
Пример #30
0
// Y = alpha*A.T*X + beta*Y
func MVMultTransA(Y, A, X *matrix.FloatMatrix, alpha, beta float64) error {

	if Y.Rows() != 1 && Y.Cols() != 1 {
		return errors.New("Y not a vector.")
	}
	if X.Rows() != 1 && X.Cols() != 1 {
		return errors.New("X not a vector.")
	}

	Ar := A.FloatArray()
	ldA := A.LeadingIndex()
	Yr := Y.FloatArray()
	incY := 1
	lenY := Y.Rows()
	if Y.Rows() == 1 {
		// row vector
		incY = Y.LeadingIndex()
		lenY = Y.Cols()
	}
	Xr := X.FloatArray()
	incX := 1
	lenX := X.Rows()
	if X.Rows() == 1 {
		// row vector
		incX = X.LeadingIndex()
		lenX = X.Cols()
	}
	calgo.DMultMV(Yr, Ar, Xr, alpha, beta, calgo.TRANSA, incY, ldA, incX,
		0, lenX, 0, lenY, vpLen, mB)
	return nil
}