Ejemplo n.º 1
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 errors.New("GesvdFloat not implemented yet")
	}
	return nil
}
Ejemplo n.º 2
0
// Copies a vector X to a vector Y (Y := X).
//
// ARGUMENTS
//  X         float or complex matrix
//  Y         float or complex matrix.  Must have the same type as X.
//
// OPTIONS
//  n         integer.  If n<0, the default value of n is used.
//            The default value is given by 1+(len(x)-offsetx-1)/incx or 0
//            if len(x) > offsetx+1
//  incx      nonzero integer
//  incy      nonzero integer
//  offsetx   nonnegative integer
//  offsety   nonnegative integer;
//
func Copy(X, Y matrix.Matrix, 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
	}
	sameType := matrix.EqualTypes(X, Y)
	if ! sameType {
		err = errors.New("arrays not same type")
		return
	}
	switch X.(type) {
	case *matrix.ComplexMatrix:
		Xa := X.ComplexArray()
		Ya := Y.ComplexArray()
		zcopy(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Ya := Y.FloatArray()
		dcopy(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	default:
		err = errors.New("not implemented for parameter types", )
	}
	return
}
Ejemplo n.º 3
0
// Scales a vector by a constant (X := alpha*X).
//
// ARGUMENTS
//  X         float or complex matrix
//  alpha     number (float or complex singleton matrix).  Complex alpha is only
//            allowed if X is complex.
// 
// OPTIONS
//  n         integer.  If n<0, the default value of n is used.
//            The default value is equal to 1+(len(x)-offset-1)/inc or 0
//            if len(x) > offset+1.
//  inc       positive integer, default = 1
//  offset    nonnegative integer, default = 0
//
func Scal(X matrix.Matrix, alpha matrix.Scalar, 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
	}
	switch X.(type) {
	case *matrix.ComplexMatrix:
		Xa := X.ComplexArray()
		cval := alpha.Complex()
		zscal(ind.Nx, cval, Xa[ind.OffsetX:], ind.IncX)
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		rval := alpha.Float()
		if math.IsNaN(rval) {
			return errors.New("alpha not float value")
		}
		dscal(ind.Nx, rval, Xa[ind.OffsetX:], ind.IncX)
	default:
		err = errors.New("not implemented for parameter types", )
	}
	return
}
Ejemplo n.º 4
0
/*
 Inverse of a real or complex matrix.

 Getri(A, ipiv, n=A.Rows, ldA = max(1,A.Rows), offsetA=0)

 PURPOSE

 Computes the inverse of real or complex matrix of order n.  On
 entry, A and ipiv contain the LU factorization, as returned by
 gesv() or getrf().  On exit A is replaced by the inverse.

 ARGUMENTS
  A         float or complex matrix
  ipiv      int vector

 OPTIONS
  n         nonnegative integer.  If negative, the default value is used.
  ldA       positive integer.  ldA >= max(1,n).  If zero, the default
            value is used.
  offsetA   nonnegative integer;
*/
func Getri(A matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
	ind := linalg.GetIndexOpts(opts...)
	if ind.N < 0 {
		ind.N = A.Cols()
	}
	if ind.N == 0 {
		return nil
	}
	if ind.LDa == 0 {
		ind.LDa = max(1, A.Rows())
	}
	if ind.OffsetA < 0 {
		return errors.New("lda")
	}
	sizeA := A.NumElements()
	if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
		return errors.New("sizeA")
	}
	if ipiv != nil && len(ipiv) < ind.N {
		return errors.New("size ipiv")
	}
	info := -1
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.FloatArray()
		info = dgetri(ind.N, Aa[ind.OffsetA:], ind.LDa, ipiv)
	case *matrix.ComplexMatrix:
	}
	if info != 0 {
		return errors.New("Getri call error")
	}
	return nil
}
Ejemplo n.º 5
0
// Returns Y = X^H*Y for real or complex X, Y.
//
// ARGUMENTS
//  X         float or complex matrix
//  Y         float or complex matrix.  Must have the same type as X.
//
// OPTIONS
//  n         integer.  If n<0, the default value of n is used.
//            The default value is equal to nx = 1+(len(x)-offsetx-1)/incx or 0 if
//            len(x) > offsetx+1.  If the default value is used, it must be equal to
//            ny = 1+(len(y)-offsetx-1)/|incy| or 0 if len(y) > offsety+1
//  incx      nonzero integer [default=1]
//  incy      nonzero integer [default=1]
//  offsetx   nonnegative integer [default=0]
//  offsety   nonnegative integer [default=0]
//
func Dot(X, Y matrix.Matrix, opts ...linalg.Option) (v matrix.Scalar) {
	v = matrix.FScalar(math.NaN())
	//cv = cmplx.NaN()
	ind := linalg.GetIndexOpts(opts...)
	err := check_level1_func(ind, fdot, X, Y)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		return matrix.FScalar(0.0)
	}
	sameType := matrix.EqualTypes(X, Y)
	if ! sameType {
		err = errors.New("arrays not of same type")
		return
	}
	switch X.(type) {
	case *matrix.ComplexMatrix:
		Xa := X.ComplexArray()
		Ya := Y.ComplexArray()
		v = matrix.CScalar(zdotc(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY))
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Ya := Y.FloatArray()
		v = matrix.FScalar(ddot(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY))
	//default:
	//	err = errors.New("not implemented for parameter types", )
	}
	return
}
Ejemplo n.º 6
0
/*
 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
}
Ejemplo n.º 7
0
// 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
}
Ejemplo n.º 8
0
// 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
}
Ejemplo n.º 9
0
// 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
}
Ejemplo n.º 10
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 errors.New(fmt.Sprintf("Gbtrs: call error: %d", info))
	}
	return nil
}
Ejemplo n.º 11
0
/*
 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
}
Ejemplo n.º 12
0
// 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
}
Ejemplo n.º 13
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
}
Ejemplo n.º 14
0
/*
 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
}
Ejemplo n.º 15
0
/*
 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")
	}
	return
}
Ejemplo n.º 16
0
func GbsvComplex(A, B *matrix.ComplexMatrix, 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
	}
	return errors.New("GbsvComplex not implemented yet")
}
Ejemplo n.º 17
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
}
Ejemplo n.º 18
0
/*
 LU factorization of a real or complex tridiagonal matrix.

 Gttrf(dl, d, du, du2, ipiv, n=len(d)-offsetd, offsetdl=0, offsetd=0, offsetdu=0)

 PURPOSE

 Factors an n by n real or complex tridiagonal matrix A as A = P*L*U.

 A is specified by its lower diagonal dl, diagonal d, and upper
 diagonal du.  On exit dl, d, du, du2 and ipiv contain the details
 of the factorization.

 ARGUMENTS.
  DL        float or complex matrix
  D         float or complex matrix.  Must have the same type as DL.
  DU        float or complex matrix.  Must have the same type as DL.
  DU2       float or complex matrix of length at least n-2.  Must have the
            same type as DL.
  ipiv      int vector of length at least n

 OPTIONS
  n         nonnegative integer.  If negative, the default value is used.
  offsetdl  nonnegative integer
  offsetd   nonnegative integer
  offsetdu  nonnegative integer
*/
func Gtrrf(DL, D, DU, DU2 matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
	ind := linalg.GetIndexOpts(opts...)
	if ind.OffsetD < 0 {
		return errors.New("offset D")
	}
	if ind.N < 0 {
		ind.N = D.NumElements() - ind.OffsetD
	}
	if ind.N < 0 {
		return errors.New("size D")
	}
	if ind.N == 0 {
		return nil
	}
	if ind.OffsetDL < 0 {
		return errors.New("offset DL")
	}
	sizeDL := DL.NumElements()
	if sizeDL < ind.OffsetDL+ind.N-1 {
		return errors.New("sizeDL")
	}
	if ind.OffsetDU < 0 {
		return errors.New("offset DU")
	}
	sizeDU := DU.NumElements()
	if sizeDU < ind.OffsetDU+ind.N-1 {
		return errors.New("sizeDU")
	}
	sizeDU2 := DU2.NumElements()
	if sizeDU2 < ind.N-2 {
		return errors.New("sizeDU2")
	}
	if len(ipiv) < ind.N {
		return errors.New("size ipiv")
	}
	info := -1
	switch DL.(type) {
	case *matrix.FloatMatrix:
		DLa := DL.FloatArray()
		Da := D.FloatArray()
		DUa := DU.FloatArray()
		DU2a := DU2.FloatArray()
		info = dgttrf(ind.N, DLa[ind.OffsetDL:], Da[ind.OffsetD:], DUa[ind.OffsetDU:],
			DU2a, ipiv)
	case *matrix.ComplexMatrix:
	}
	if info != 0 {
		return errors.New("Gttrf call error")
	}
	return nil
}
Ejemplo n.º 19
0
// See function Asum.
func AsumComplex(X *matrix.ComplexMatrix, opts ...linalg.Option) (v float64, err error) {
	v = 0.0
	ind := linalg.GetIndexOpts(opts...)
	err = check_level1_func(ind, fasum, X, nil)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		return
	}
	Xa := X.ComplexArray()
	v = dzasum(ind.Nx, Xa[ind.OffsetX:], ind.IncX)
	return
}
Ejemplo n.º 20
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
}
Ejemplo n.º 21
0
/*
 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
}
Ejemplo n.º 22
0
/*
 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
}
Ejemplo n.º 23
0
// See function Dotc.
func DotcComplex(X, Y *matrix.ComplexMatrix, opts ...linalg.Option) (v complex128, err error) {
	v = 0.0
	ind := linalg.GetIndexOpts(opts...)
	err = check_level1_func(ind, fdot, X, Y)
	if err != nil {
		return
	}
	if ind.Nx == 0 {
		return
	}
	Xa := X.ComplexArray()
	Ya := Y.ComplexArray()
	v = zdotc(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	return
}
Ejemplo n.º 24
0
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")
}
Ejemplo n.º 25
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
}
Ejemplo n.º 26
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
}
Ejemplo n.º 27
0
/*
 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
}
Ejemplo n.º 28
0
/*
 General rank-1 update. (L2)

 Ger(X, Y, A, alpha=1.0, m=A.Rows, n=A.Cols, incx=1,
 incy=1, ldA=max(1,A.Rows), offsetx=0, offsety=0, offsetA=0)

 COMPUTES
  A := A + alpha*X*Y^H with A m*n, real or complex.

 ARGUMENTS
  X         float or complex matrix.
  Y         float or complex matrix. Must have the same type as X.
  A         float or complex matrix. Must have the same type as X.
  alpha     number (float or complex singleton matrix).

 OPTIONS
  m         integer.  If negative, the default value is used.
  n         integer.  If negative, the default value is used.
  incx      nonzero integer
  incy      nonzero integer
  ldA       nonnegative integer.  ldA >= max(1,m).
            If zero, the default value is used.
  offsetx   nonnegative integer
  offsety   nonnegative integer
  offsetA   nonnegative integer;

*/
func Ger(X, Y, A matrix.Matrix, alpha matrix.Scalar, opts ...linalg.Option) (err error) {

	var params *linalg.Parameters
	if !matrix.EqualTypes(A, X, Y) {
		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, fger, X, Y, A, params)
	if err != nil {
		return
	}
	if ind.N == 0 || ind.M == 0 {
		return
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.FloatArray()
		Ya := Y.FloatArray()
		Aa := A.FloatArray()
		aval := alpha.Float()
		if math.IsNaN(aval) {
			return errors.New("alpha not a number")
		}
		dger(ind.M, ind.N, aval, Xa[ind.OffsetX:], ind.IncX,
			Ya[ind.OffsetY:], ind.IncY, Aa[ind.OffsetA:], ind.LDa)

	case *matrix.ComplexMatrix:
		Xa := X.ComplexArray()
		Ya := Y.ComplexArray()
		Aa := A.ComplexArray()
		aval := alpha.Complex()
		if cmplx.IsNaN(aval) {
			return errors.New("alpha not a number")
		}
		zgerc(ind.M, ind.N, aval, Xa[ind.OffsetX:], ind.IncX,
			Ya[ind.OffsetY:], ind.IncY, Aa[ind.OffsetA:], ind.LDa)

	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}
Ejemplo n.º 29
0
/*
 Matrix-vector product with a general banded matrix. (L2)

 Computes
   Y := alpha*A*X + beta*Y,   if trans = PNoTrans
   Y := alpha*A^T*X + beta*Y, if trans = PTrans
   Y := beta*y,               if n=0, m>0, and trans = PNoTrans
   Y := beta*y,               if n>0, m=0, and trans = PTrans

 The matrix A is m by n with upper bandwidth ku and lower bandwidth kl.
 Returns immediately if n=0 and trans is 'Trans', or if m=0 and trans is 'N'.


 ARGUMENTS
   X         float n*1 matrix.
   Y         float m*1 matrix
   A         float m*n matrix.
   alpha     number (float).
   beta      number (float).

 OPTIONS
   trans     NoTrans or Trans
   m         nonnegative integer, default A.Rows()
   kl        nonnegative integer
   n         nonnegative integer.  If negative, the default value is used.
   ku        nonnegative integer.  If negative, the default value is used.
   ldA       positive integer.  ldA >= kl+ku+1. If zero, the default value is used.
   incx      nonzero integer, default =1
   incy      nonzero integer, default =1
   offsetA   nonnegative integer, default =0
   offsetx   nonnegative integer, default =0
   offsety   nonnegative integer, default =0

*/
func Gbmv(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, fgbmv, X, Y, A, params)
	if err != nil {
		return
	}
	if ind.M == 0 && 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")
		}
		if params.Trans == linalg.PNoTrans && ind.N == 0 {
			dscal(ind.M, bval, Ya[ind.OffsetY:], ind.IncY)
		} else if params.Trans == linalg.PTrans && ind.M == 0 {
			dscal(ind.N, bval, Ya[ind.OffsetY:], ind.IncY)
		} else {
			trans := linalg.ParamString(params.Trans)
			dgbmv(trans, ind.M, ind.N, ind.Kl, ind.Ku,
				aval, Aa[ind.OffsetA:], ind.LDa, Xa[ind.OffsetX:], ind.IncX,
				bval, Ya[ind.OffsetY:], ind.IncY)
		}
	case *matrix.ComplexMatrix:
		return errors.New("Not implemented yet for complx.Matrix")
	default:
		return errors.New("Unknown type, not implemented")
	}
	return
}
Ejemplo n.º 30
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 errors.New(fmt.Sprintf("Potrf: call error %d", info))
	}
	return nil
}