Golang linalg.GetIndexOpts函數代碼示例

// 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.(*matrix.ComplexMatrix).ComplexArray()
		cval := alpha.Complex()
		zscal(ind.Nx, cval, Xa[ind.OffsetX:], ind.IncX)
	case *matrix.FloatMatrix:
		Xa := X.(*matrix.FloatMatrix).FloatArray()
		rval := alpha.Float()
		if math.IsNaN(rval) {
			return onError("alpha not float value")
		}
		dscal(ind.Nx, rval, Xa[ind.OffsetX:], ind.IncX)
	default:
		err = onError("not implemented for parameter types")
	}
	return
}

/*
 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 = onError("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.(*matrix.FloatMatrix).FloatArray()
		Aa := A.(*matrix.FloatMatrix).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 onError("Not implemented yet for complx.Matrix")
	default:
		return onError("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
}

// 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 = onError("arrays not same type")
		return
	}
	switch X.(type) {
	case *matrix.ComplexMatrix:
		Xa := X.(*matrix.ComplexMatrix).ComplexArray()
		Ya := Y.(*matrix.ComplexMatrix).ComplexArray()
		zcopy(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	case *matrix.FloatMatrix:
		Xa := X.(*matrix.FloatMatrix).FloatArray()
		Ya := Y.(*matrix.FloatMatrix).FloatArray()
		dcopy(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY)
	default:
		err = onError("not implemented for parameter types")
	}
	return
}

// 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 onError("Parameters not of same type")
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.(*matrix.FloatMatrix).FloatArray()
		Ya := X.(*matrix.FloatMatrix).FloatArray()
		Aa := A.(*matrix.FloatMatrix).FloatArray()
		aval := alpha.Float()
		if math.IsNaN(aval) {
			return onError("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 onError("Not implemented yet for complx.Matrix")
	default:
		return onError("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
}

// 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
}

// 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
}

// 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 = onError("arrays not of same type")
		return
	}
	switch X.(type) {
	case *matrix.ComplexMatrix:
		Xa := X.(*matrix.ComplexMatrix).ComplexArray()
		Ya := Y.(*matrix.ComplexMatrix).ComplexArray()
		v = matrix.CScalar(zdotc(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY))
	case *matrix.FloatMatrix:
		Xa := X.(*matrix.FloatMatrix).FloatArray()
		Ya := Y.(*matrix.FloatMatrix).FloatArray()
		v = matrix.FScalar(ddot(ind.Nx, Xa[ind.OffsetX:], ind.IncX, Ya[ind.OffsetY:], ind.IncY))
		//default:
		//	err = onError("not implemented for parameter types", )
	}
	return
}

/*
 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 onError("Parameters not of same type")
	}
	switch A.(type) {
	case *matrix.FloatMatrix:
		Aa := A.(*matrix.FloatMatrix).FloatArray()
		Ba := B.(*matrix.FloatMatrix).FloatArray()
		Ca := C.(*matrix.FloatMatrix).FloatArray()
		aval := alpha.Float()
		bval := beta.Float()
		if math.IsNaN(aval) || math.IsNaN(bval) {
			return onError("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.(*matrix.ComplexMatrix).ComplexArray()
		Ba := B.(*matrix.ComplexMatrix).ComplexArray()
		Ca := C.(*matrix.ComplexMatrix).ComplexArray()
		aval := alpha.Complex()
		if cmplx.IsNaN(aval) {
			return onError("alpha not a number")
		}
		bval := beta.Complex()
		if cmplx.IsNaN(bval) {
			return onError("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 onError("Unknown type, not implemented")
	}
//.........這裏部分代碼省略.........

// 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
}

// 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
}

// 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
}

/*
 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 onError("Parameters not of same type")
	}
	switch X.(type) {
	case *matrix.FloatMatrix:
		Xa := X.(*matrix.FloatMatrix).FloatArray()
		Ya := Y.(*matrix.FloatMatrix).FloatArray()
		Aa := A.(*matrix.FloatMatrix).FloatArray()
		aval := alpha.Float()
		bval := beta.Float()
		if math.IsNaN(aval) || math.IsNaN(bval) {
			return onError("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.(*matrix.ComplexMatrix).ComplexArray()
		Ya := Y.(*matrix.ComplexMatrix).ComplexArray()
		Aa := A.(*matrix.ComplexMatrix).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 onError("Unknown type, not implemented")
	}
	return
}