Golang linalg.GetParameters函数代码示例

// See function Gbmv.
func GbmvFloat(A, X, Y *matrix.FloatMatrix, alpha, beta 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, fgbmv, X, Y, A, params)
	if err != nil {
		return
	}
	if ind.M == 0 && ind.N == 0 {
		return
	}

	Xa := X.FloatArray()
	Ya := Y.FloatArray()
	Aa := A.FloatArray()
	if params.Trans == linalg.PNoTrans && ind.N == 0 {
		dscal(ind.M, beta, Ya[ind.OffsetY:], ind.IncY)
	} else if params.Trans == linalg.PTrans && ind.M == 0 {
		dscal(ind.N, beta, Ya[ind.OffsetY:], ind.IncY)
	} else {
		trans := linalg.ParamString(params.Trans)
		dgbmv(trans, ind.M, ind.N, ind.Kl, ind.Ku,
			alpha, Aa[ind.OffsetA:], ind.LDa, Xa[ind.OffsetX:], ind.IncX,
			beta, Ya[ind.OffsetY:], ind.IncY)
	}
	return
}

/*
 Symmetric rank-2 update.
 syr2(x, y, A, uplo='L', alpha=1.0, n=A.size[0], incx=1, incy=1,
     ldA=max(1,A.size[0]), offsetx=0, offsety=0, offsetA=0)
 PURPOSE
 Computes A := A + alpha*(x*y^T + y*x^T) with A real symmetric matrix of order n.
 ARGUMENTS
 x         float matrix
 y         float matrix
 A         float matrix
 alpha     real number (int or float)

 OPTIONS
 uplo      'L' or 'U'
 n         integer.  If negative, the default value is used.
 incx      nonzero integer
 incy      nonzero integer
 ldA       nonnegative integer.  ldA >= max(1,n).
           If zero the default value is used.
 offsetx   nonnegative integer
 offsety   nonnegative integer
 offsetA   nonnegative integer;
*/
func Syr2(X, Y, A matrix.Matrix, alpha matrix.Scalar, 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, fsyr2, X, Y, A, params)
	if err != nil {
		return
	}
	if !matrix.EqualTypes(A, X, Y) {
		return errors.New("Parameters not of same type")
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Ya := X.FloatArray()
		Aa := A.FloatArray()
		aval := alpha.Float()
		if math.IsNaN(aval) {
			return errors.New("alpha not a number")
		}
		uplo := linalg.ParamString(params.Uplo)
		dsyr2(uplo, ind.N, aval, Xa[ind.OffsetX:], ind.IncX,
			Ya[ind.OffsetY:], ind.IncY,
			Aa[ind.OffsetA:], ind.LDa)
	case *matrix.ComplexMatrix:
		return errors.New("Not implemented yet for complx.Matrix")
	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}

// See function Gemm.
func GemmFloat(A, B, 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, fgemm, A, B, C, params)
	if err != nil {
		return
	}
	if ind.M == 0 || ind.N == 0 {
		return
	}
	Aa := A.FloatArray()
	Ba := B.FloatArray()
	Ca := C.FloatArray()
	transB := linalg.ParamString(params.TransB)
	transA := linalg.ParamString(params.TransA)
	//diag := linalg.ParamString(params.Diag)
	dgemm(transA, transB, ind.M, ind.N, ind.K, alpha,
		Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb, beta,
		Ca[ind.OffsetC:], ind.LDc)
	return
}

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 errors.New(fmt.Sprintf("Gbtrs: call error: %d", info))
	}
	return nil
}

// See function Symm.
func SymmFloat(A, B, 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, fsymm, A, B, C, params)
	if err != nil {
		return
	}
	if ind.M == 0 || ind.N == 0 {
		return
	}
	Aa := A.FloatArray()
	Ba := B.FloatArray()
	Ca := C.FloatArray()
	uplo := linalg.ParamString(params.Uplo)
	side := linalg.ParamString(params.Side)
	dsymm(side, uplo, ind.M, ind.N, alpha, Aa[ind.OffsetA:], ind.LDa,
		Ba[ind.OffsetB:], ind.LDb, beta, Ca[ind.OffsetC:], ind.LDc)

	return
}

// See function Syrk2.
func Syr2kFloat(A, B, 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, fsyr2k, A, B, C, params)
	if err != nil {
		return
	}
	if ind.N == 0 {
		return
	}
	Aa := A.FloatArray()
	Ba := B.FloatArray()
	Ca := C.FloatArray()
	uplo := linalg.ParamString(params.Uplo)
	trans := linalg.ParamString(params.Trans)
	//diag := linalg.ParamString(params.Diag)
	dsyr2k(uplo, trans, ind.N, ind.K, alpha, Aa[ind.OffsetA:], ind.LDa,
		Ba[ind.OffsetB:], ind.LDb, beta, Ca[ind.OffsetC:], ind.LDc)
	return
}

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 errors.New("GesvdFloat not implemented yet")
	}
	return nil
}

/*
 Solution of a triangular and banded set of equations.

 Tbsv(A, X, uplo=PLower, trans=PNoTrans, diag=PNonDiag, n=A.Cols,
 k=max(0,A.Rows-1), ldA=A.size[0], incx=1, offsetA=0, offsetx=0)

PURPOSE
  X := A^{-1}*X, if trans is PNoTrans
  X := A^{-T}*X, if trans is PTrans
  X := A^{-H}*X, if trans is PConjTrans

 A is banded triangular of order n and with bandwidth k.

 ARGUMENTS
  A         float or complex m*k matrix.
  X         float or complex k*1 matrix. Must have the same type as A.

 OPTIONS
  uplo      PLower   or PUpper
  trans     PNoTrans, PTrans or PConjTrans
  diag      PNoNUnit or PUnit
  n         nonnegative integer.  If negative, the default value is used.
  k         nonnegative integer.  If negative, the default value is used.
  ldA       nonnegative integer.  ldA >= 1+k.
            If zero the default value is used.
  incx      nonzero integer
  offsetA   nonnegative integer
  offsetx   nonnegative integer;
*/
func Tbsv(A, X matrix.Matrix, opts ...linalg.Option) (err error) {

	var params *linalg.Parameters
	if !matrix.EqualTypes(A, X) {
		err = errors.New("Parameters not of same type")
		return
	}
	params, err = linalg.GetParameters(opts...)
	if err != nil {
		return
	}
	ind := linalg.GetIndexOpts(opts...)
	err = check_level2_func(ind, ftbsv, X, nil, A, params)
	if err != nil {
		return
	}
	if ind.N == 0 {
		return
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Aa := A.FloatArray()
		uplo := linalg.ParamString(params.Uplo)
		trans := linalg.ParamString(params.Trans)
		diag := linalg.ParamString(params.Diag)
		dtbsv(uplo, trans, diag, ind.N, ind.K,
			Aa[ind.OffsetA:], ind.LDa, Xa[ind.OffsetX:], ind.IncX)
	case *matrix.ComplexMatrix:
		return errors.New("Not implemented yet for complx.Matrix")
	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}

// 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
}

/*
 Solves a real symmetric or complex Hermitian positive definite set
 of linear equations, given the Cholesky factorization computed by
 potrf() or posv().

 Potrs(A, B, uplo=PLower, n=A.Rows, nrhs=B.Cols,
 ldA=max(1,A.Rows), ldB=max(1,B.Rows), offsetA=0, offsetB=0)

 PURPOSE

 Solves
   A*X = B

 where A is n by n, real symmetric or complex Hermitian and positive definite,
 and B is n by nrhs. On entry, A contains the Cholesky factor, as
 returned by Posv() or Potrf().  On exit B is replaced by the solution X.

 ARGUMENTS
  A         float or complex matrix
  B         float or complex matrix.  Must have the same type as A.

 OPTIONS
  uplo      PLower or PUpper
  n         nonnegative integer.  If negative, the default value is used.
  nrhs      nonnegative integer.  If negative, the default value is used.
  ldA       positive integer.  ldA >= max(1,n).  If zero, the default
            value is used.
  ldB       positive integer.  ldB >= max(1,n).  If zero, the default
            value is used.
  offsetA   nonnegative integer
  offsetB   nonnegative integer;

*/
func Potrs(A, B matrix.Matrix, opts ...linalg.Option) error {
	pars, err := linalg.GetParameters(opts...)
	if err != nil {
		return err
	}
	ind := linalg.GetIndexOpts(opts...)
	if ind.N < 0 {
		ind.N = A.Rows()
	}
	if ind.Nrhs < 0 {
		ind.Nrhs = B.Cols()
	}
	if ind.N == 0 || ind.Nrhs == 0 {
		return nil
	}
	if ind.LDa == 0 {
		ind.LDa = max(1, A.Rows())
	}
	if ind.LDa < max(1, ind.N) {
		return errors.New("lda")
	}
	if ind.LDb == 0 {
		ind.LDb = max(1, B.Rows())
	}
	if ind.LDb < max(1, ind.N) {
		return errors.New("ldb")
	}
	if ind.OffsetA < 0 {
		return errors.New("offsetA")
	}
	if A.NumElements() < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
		return errors.New("sizeA")
	}
	if ind.OffsetB < 0 {
		return errors.New("offsetB")
	}
	if B.NumElements() < ind.OffsetB+(ind.Nrhs-1)*ind.LDb+ind.N {
		return errors.New("sizeB")
	}
	if !matrix.EqualTypes(A, B) {
		return errors.New("types")
	}
	info := -1
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.FloatArray()
		Ba := B.FloatArray()
		uplo := linalg.ParamString(pars.Uplo)
		info = dpotrs(uplo, ind.N, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa,
			Ba[ind.OffsetB:], ind.LDb)
	case *matrix.ComplexMatrix:
		return errors.New("ComplexMatrx: not implemented yet")
	}
	if info != 0 {
		return errors.New("Potrs failed")
	}
	return nil
}

/*
 General matrix-matrix product. (L3)

 PURPOSE
 Computes
  C := alpha*A*B + beta*C     if transA = PNoTrans   and transB = PNoTrans.
  C := alpha*A^T*B + beta*C   if transA = PTrans     and transB = PNoTrans.
  C := alpha*A^H*B + beta*C   if transA = PConjTrans and transB = PNoTrans.
  C := alpha*A*B^T + beta*C   if transA = PNoTrans   and transB = PTrans.
  C := alpha*A^T*B^T + beta*C if transA = PTrans     and transB = PTrans.
  C := alpha*A^H*B^T + beta*C if transA = PConjTrans and transB = PTrans.
  C := alpha*A*B^H + beta*C   if transA = PNoTrans   and transB = PConjTrans.
  C := alpha*A^T*B^H + beta*C if transA = PTrans     and transB = PConjTrans.
  C := alpha*A^H*B^H + beta*C if transA = PConjTrans and transB = PConjTrans.

 The number of rows of the matrix product is m.  The number of  columns is n.
 The inner dimension is k.  If k=0, this reduces  to C := beta*C.

 ARGUMENTS
  A         float or complex matrix, m*k
  B         float or complex matrix, k*n
  C         float or complex matrix, m*n
  alpha     number (float or complex singleton matrix)
  beta      number (float or complex singleton matrix)

 OPTIONS
  transA    PNoTrans, PTrans or PConjTrans
  transB    PNoTrans, PTrans or PConjTrans
  m         integer.  If negative, the default value is used. The default value is
            m = A.Rows of if transA != PNoTrans m = A.Cols.
  n         integer.  If negative, the default value is used. The default value is
            n = (transB == PNoTrans) ? B.Cols : B.Rows.
  k         integer.  If negative, the default value is used. The default value is
            k=A.Cols or if transA != PNoTrans) k = A.Rows, transA=PNoTrans.
            If the default value is used it should also be equal to
            (transB == PNoTrans) ? B.Rows : B.Cols.
  ldA       nonnegative integer.  ldA >= max(1,m) of if transA != NoTrans max(1,k).
            If zero, the default value is used.
  ldB       nonnegative integer.  ldB >= max(1,k) or if transB != NoTrans max(1,n).
            If zero, the default value is used.
  ldC       nonnegative integer.  ldC >= max(1,m).
            If zero, the default value is used.
  offsetA   nonnegative integer
  offsetB   nonnegative integer
  offsetC   nonnegative integer;
*/
func Gemm(A, B, C matrix.Matrix, alpha, beta matrix.Scalar, 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, fgemm, A, B, C, params)
	if err != nil {
		return
	}
	if ind.M == 0 || ind.N == 0 {
		return
	}
	if !matrix.EqualTypes(A, B, C) {
		return errors.New("Parameters not of same type")
	}
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.FloatArray()
		Ba := B.FloatArray()
		Ca := C.FloatArray()
		aval := alpha.Float()
		bval := beta.Float()
		if math.IsNaN(aval) || math.IsNaN(bval) {
			return errors.New("alpha or beta not a number")
		}
		transB := linalg.ParamString(params.TransB)
		transA := linalg.ParamString(params.TransA)
		dgemm(transA, transB, ind.M, ind.N, ind.K, aval,
			Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb, bval,
			Ca[ind.OffsetC:], ind.LDc)

	case *matrix.ComplexMatrix:
		Aa := A.ComplexArray()
		Ba := B.ComplexArray()
		Ca := C.ComplexArray()
		aval := alpha.Complex()
		if cmplx.IsNaN(aval) {
			return errors.New("alpha not a number")
		}
		bval := beta.Complex()
		if cmplx.IsNaN(bval) {
			return errors.New("beta not a number")
		}
		transB := linalg.ParamString(params.TransB)
		transA := linalg.ParamString(params.TransA)
		zgemm(transA, transB, ind.M, ind.N, ind.K, aval,
			Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb, bval,
			Ca[ind.OffsetC:], ind.LDc)
	default:
		return errors.New("Unknown type, not implemented")
	}
//.........这里部分代码省略.........

/*
 Rank-k update of symmetric matrix. (L3)

 Herk(A, C, alpha, beta, uplo=PLower, trans=PNoTrans,  n=-1,
 k=-1, ldA=max(1,A.Rows), ldC=max(1,C.Rows), offsetA=0, offsetB=0)

 Computes
  C := alpha*A*A^T + beta*C, if trans is PNoTrans
  C := alpha*A^T*A + beta*C, if trans is PTrans

 C is symmetric (real or complex) of order n. The inner dimension of the matrix
 product is k.  If k=0 this is interpreted as C := beta*C.

 ARGUMENTS
  A         float or complex matrix.
  C         float or complex matrix.  Must have the same type as A.
  alpha     number (float or complex singleton matrix).  Complex alpha is only
            allowed if A is complex.
  beta      number (float or complex singleton matrix).  Complex beta is only
            allowed if A is complex.

 OPTIONS
  uplo      PLower or PUpper
  trans     PNoTrans or PTrans
  n         integer.  If negative, the default value is used.
            The default value is n = A.Rows or if trans == PNoTrans n = A.Cols.
  k         integer.  If negative, the default value is used.
            The default value is k =  A.Cols, or if trans == PNoTrans k = A.Rows.
  ldA       nonnegative integer.
            ldA >= max(1,n) or if trans != PNoTrans ldA >= max(1,k).
            If zero, the default value is used.
  ldC       nonnegative integer.  ldC >= max(1,n).
            If zero, the default value is used.
  offsetA   nonnegative integer
  offsetC   nonnegative integer;
*/
func Herk(A, C matrix.Matrix, alpha, beta matrix.Scalar, 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 !matrix.EqualTypes(A, C) {
		return errors.New("Parameters not of same type")
	}
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.FloatArray()
		Ca := C.FloatArray()
		aval := alpha.Float()
		bval := beta.Float()
		if math.IsNaN(aval) || math.IsNaN(bval) {
			return errors.New("alpha or beta not a number")
		}
		uplo := linalg.ParamString(params.Uplo)
		trans := linalg.ParamString(params.Trans)
		dsyrk(uplo, trans, ind.N, ind.K, aval, Aa[ind.OffsetA:], ind.LDa, bval,
			Ca[ind.OffsetC:], ind.LDc)
	case *matrix.ComplexMatrix:
		Aa := A.ComplexArray()
		Ca := C.ComplexArray()
		aval := alpha.Complex()
		if cmplx.IsNaN(aval) {
			return errors.New("alpha not a real or complex number")
		}
		bval := beta.Float()
		if math.IsNaN(bval) {
			return errors.New("beta not a real number")
		}
		uplo := linalg.ParamString(params.Uplo)
		trans := linalg.ParamString(params.Trans)
		zherk(uplo, trans, ind.N, ind.K, aval, Aa[ind.OffsetA:], ind.LDa, bval,
			Ca[ind.OffsetC:], ind.LDc)
	default:
		return errors.New("Unknown type, not implemented")
	}

	return
}

/*
 Matrix-vector product with a real symmetric or complex hermitian band matrix.

 Computes with A real symmetric and  banded of order n and with bandwidth k.
  Y := alpha*A*X + beta*Y

 ARGUMENTS
  A         float or complex n*n matrix
  X         float or complex n*1 matrix
  Y         float or complex n*1 matrix
  alpha     number (float or complex singleton matrix)
  beta      number (float or complex singleton matrix)

 OPTIONS
  uplo      PLower or PUpper
  n         integer.  If negative, the default value is used.
  k         integer.  If negative, the default value is used.
            The default value is k = max(0,A.Rows()-1).
  ldA       nonnegative integer.  ldA >= k+1.
            If zero, the default vaule is used.
  incx      nonzero integer
  incy      nonzero integer
  offsetA   nonnegative integer
  offsetx   nonnegative integer
  offsety   nonnegative integer

*/
func Hbmv(A, X, Y matrix.Matrix, alpha, beta matrix.Scalar, 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, fsbmv, X, Y, A, params)
	if err != nil {
		return
	}
	if ind.N == 0 {
		return
	}
	if !matrix.EqualTypes(A, X, Y) {
		return errors.New("Parameters not of same type")
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Ya := Y.FloatArray()
		Aa := A.FloatArray()
		aval := alpha.Float()
		bval := beta.Float()
		if math.IsNaN(aval) || math.IsNaN(bval) {
			return errors.New("alpha or beta not a number")
		}
		uplo := linalg.ParamString(params.Uplo)
		dsbmv(uplo, ind.N, ind.K, aval, Aa[ind.OffsetA:], ind.LDa,
			Xa[ind.OffsetX:], ind.IncX, bval, Ya[ind.OffsetY:], ind.IncY)

	case *matrix.ComplexMatrix:
		Xa := X.ComplexArray()
		Ya := Y.ComplexArray()
		Aa := A.ComplexArray()
		aval := alpha.Complex()
		bval := beta.Complex()
		uplo := linalg.ParamString(params.Uplo)
		zhbmv(uplo, ind.N, ind.K, aval, Aa[ind.OffsetA:], ind.LDa,
			Xa[ind.OffsetX:], ind.IncX, bval, Ya[ind.OffsetY:], ind.IncY)
		//zhbmv(uplo, ind.N, aval, Aa[ind.OffsetA:], ind.LDa,
		//	Xa[ind.OffsetX:], ind.IncX,
		//	bval, Ya[ind.OffsetY:], ind.IncY)
	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}

func GesvdComplex(A, S, U, Vt *matrix.ComplexMatrix, 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
	}
	return errors.New("GesvdComplex not implemented yet")
}

/*
 Solution of a triangular system of equations with multiple righthand sides. (L3)

 Trsm(A, B, alpha, side=PLeft, uplo=PLower, transA=PNoTrans, diag=PNonUnit,
 m=-1, n=-1, ldA=max(1,A.Rows), ldB=max(1,B.Rows), offsetA=0, offsetB=0)

 Computes
  B := alpha*A^{-1}*B if transA is PNoTrans   and side = PLeft
  B := alpha*B*A^{-1} if transA is PNoTrans   and side = PRight
  B := alpha*A^{-T}*B if transA is PTrans     and side = PLeft
  B := alpha*B*A^{-T} if transA is PTrans     and side = PRight
  B := alpha*A^{-H}*B if transA is PConjTrans and side = PLeft
  B := alpha*B*A^{-H} if transA is PConjTrans and side = PRight

 B is m by n and A is triangular.  The code does not verify whether A is nonsingular.

 ARGUMENTS
  A         float or complex matrix.
  B         float or complex matrix.  Must have the same type as A.
  alpha     number (float or complex).  Complex alpha is only
            allowed if A is complex.

 OPTIONS
  side      PLeft or PRight
  uplo      PLower or PUpper
  transA    PNoTrans or PTrans
  diag      PNonUnit or PUnit
  m         integer.  If negative, the default value is used.
            The default value is m = A.Rows or if side == PRight m = B.Rows
            If the default value is used and side is PLeft, m must be equal to A.Cols.
  n         integer.  If negative, the default value is used.
            The default value is n = B.Cols or if side )= PRight n = A.Rows.
            If the default value is used and side is PRight, n must be equal to A.Cols.
  ldA       nonnegative integer.
            ldA >= max(1,m) of if  side == PRight lda >= max(1,n).
            If zero, the default value is used.
  ldB       nonnegative integer.  ldB >= max(1,m).
            If zero, the default value is used.
  offsetA   nonnegative integer
  offsetB   nonnegative integer
*/
func Trsm(A, B matrix.Matrix, alpha matrix.Scalar, 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 !matrix.EqualTypes(A, B) {
		return errors.New("Parameters not of same type")
	}
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.FloatArray()
		Ba := B.FloatArray()
		aval := alpha.Float()
		if math.IsNaN(aval) {
			return errors.New("alpha or beta not a number")
		}
		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, aval,
			Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb)
	case *matrix.ComplexMatrix:
		Aa := A.ComplexArray()
		Ba := B.ComplexArray()
		aval := alpha.Complex()
		if cmplx.IsNaN(aval) {
			return errors.New("alpha  not a number")
		}
		uplo := linalg.ParamString(params.Uplo)
		transA := linalg.ParamString(params.TransA)
		side := linalg.ParamString(params.Side)
		diag := linalg.ParamString(params.Diag)
		ztrsm(side, uplo, transA, diag, ind.M, ind.N, aval,
			Aa[ind.OffsetA:], ind.LDa, Ba[ind.OffsetB:], ind.LDb)
	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}