// 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
}
// 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
}
// 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
}
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
}
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
}
// 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 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
}
// 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 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
}
// 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
}
/*
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")
}
return
}
/*
LU factorization of a real or complex tridiagonal matrix.
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 onError("Gttrf: offset D")
}
if ind.N < 0 {
ind.N = D.NumElements() - ind.OffsetD
}
if ind.N < 0 {
return onError("Gttrf: size D")
}
if ind.N == 0 {
return nil
}
if ind.OffsetDL < 0 {
return onError("Gttrf: offset DL")
}
sizeDL := DL.NumElements()
if sizeDL < ind.OffsetDL+ind.N-1 {
return onError("Gttrf: sizeDL")
}
if ind.OffsetDU < 0 {
return onError("Gttrf: offset DU")
}
sizeDU := DU.NumElements()
if sizeDU < ind.OffsetDU+ind.N-1 {
return onError("Gttrf: sizeDU")
}
sizeDU2 := DU2.NumElements()
if sizeDU2 < ind.N-2 {
return onError("Gttrf: sizeDU2")
}
if len(ipiv) < ind.N {
return onError("Gttrf: size ipiv")
}
info := -1
if !matrix.EqualTypes(DL, D, DU, DU2) {
return onError("Gttrf: arguments not same type")
}
switch DL.(type) {
case *matrix.FloatMatrix:
DLa := DL.(*matrix.FloatMatrix).FloatArray()
Da := D.(*matrix.FloatMatrix).FloatArray()
DUa := DU.(*matrix.FloatMatrix).FloatArray()
DU2a := DU2.(*matrix.FloatMatrix).FloatArray()
info = dgttrf(ind.N, DLa[ind.OffsetDL:], Da[ind.OffsetD:], DUa[ind.OffsetDU:],
DU2a, ipiv)
case *matrix.ComplexMatrix:
return onError("Gttrf: complex not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Gttrf lapack error: %d", info))
}
return nil
}
/*
Solves a general real or complex set of linear equations.
PURPOSE
Solves A*X=B with A m by n real or complex.
ARGUMENTS.
A float or complex matrix
B float or complex matrix. Must have the same type as A.
OPTIONS:
trans
m nonnegative integer. If negative, the default value is used.
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.
*/
func Gels(A, B matrix.Matrix, opts ...linalg.Option) error {
pars, _ := linalg.GetParameters(opts...)
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
brows := ind.LDb
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.Nrhs < 0 {
ind.Nrhs = B.Cols()
}
if ind.M == 0 || ind.N == 0 || ind.Nrhs == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return onError("Gesv: ldA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(ind.M, ind.N) {
return onError("Gesv: ldB")
}
if !matrix.EqualTypes(A, B) {
return onError("Gesv: arguments not of same type")
}
_, _ = arows, brows // todo!! something
info := -1
trans := linalg.ParamString(pars.Trans)
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Ba := B.(*matrix.FloatMatrix).FloatArray()
info = dgels(trans, ind.M, ind.N, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa,
Ba[ind.OffsetB:], ind.LDb)
case *matrix.ComplexMatrix:
Aa := A.(*matrix.ComplexMatrix).ComplexArray()
Ba := B.(*matrix.ComplexMatrix).ComplexArray()
info = zgels(trans, ind.M, ind.N, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa,
Ba[ind.OffsetB:], ind.LDb)
}
if info != 0 {
return onError(fmt.Sprintf("Gels: lapack error: %d", info))
}
return nil
}
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 onError("Gbsv: complex not implemented yet")
}
// 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 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
}
// 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
}
/*
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 onError("Parameters not of same type")
}
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*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")
}
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.(*matrix.ComplexMatrix).ComplexArray()
Ca := C.(*matrix.ComplexMatrix).ComplexArray()
aval := alpha.Complex()
if cmplx.IsNaN(aval) {
return onError("alpha not a real or complex number")
}
bval := beta.Float()
if math.IsNaN(bval) {
return onError("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 onError("Unknown type, not implemented")
}
return
}
// 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
}
// 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
}
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 onError("GesvdComplex not implemented yet")
}
// 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
}
/*
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 onError("Parameters not of same type")
}
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Ba := B.(*matrix.FloatMatrix).FloatArray()
aval := alpha.Float()
if math.IsNaN(aval) {
return onError("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.(*matrix.ComplexMatrix).ComplexArray()
Ba := B.(*matrix.ComplexMatrix).ComplexArray()
aval := alpha.Complex()
if cmplx.IsNaN(aval) {
return onError("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 onError("Unknown type, not implemented")
}
return
}
/*
QR factorization.
PURPOSE
QR factorization of an m by n real or complex matrix A:
A = Q*R = [Q1 Q2] * [R1; 0] if m >= n
A = Q*R = Q * [R1 R2] if m <= n,
where Q is m by m and orthogonal/unitary and R is m by n with R1
upper triangular. On exit, R is stored in the upper triangular
part of A. Q is stored as a product of k=min(m,n) elementary
reflectors. The parameters of the reflectors are stored in the
first k entries of tau and in the lower triangular part of the
first k columns of A.
ARGUMENTS
A float or complex matrix
tau float or complex matrix of length at least min(m,n). Must
have the same type as A.
m integer. If negative, the default value is used.
n integer. If negative, the default value is used.
ldA nonnegative integer. ldA >= max(1,m). If zero, the
default value is used.
offsetA nonnegative integer
*/
func Geqrf(A, tau matrix.Matrix, opts ...linalg.Option) error {
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N == 0 || ind.M == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return onError("Geqrf: ldA")
}
if ind.OffsetA < 0 {
return onError("Geqrf: offsetA")
}
if A.NumElements() < ind.OffsetA+ind.K*arows {
return onError("Geqrf: sizeA")
}
if tau.NumElements() < min(ind.M, ind.N) {
return onError("Geqrf: sizeTau")
}
if !matrix.EqualTypes(A, tau) {
return onError("Geqrf: arguments not of same type")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
taua := tau.(*matrix.FloatMatrix).FloatArray()
info = dgeqrf(ind.M, ind.N, Aa[ind.OffsetA:], ind.LDa, taua)
case *matrix.ComplexMatrix:
return onError("Geqrf: complex not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Geqrf lapack error: %d", info))
}
return nil
}
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
}
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
}
/*
LU factorization of a general real or complex m by n matrix.
PURPOSE
On exit, A is replaced with L, U in the factorization P*A = L*U
and ipiv contains the permutation:
P = P_min{m,n} * ... * P2 * P1 where Pi interchanges rows i and
ipiv[i] of A (using the Fortran convention, i.e., the first row
is numbered 1).
ARGUMENTS
A float or complex matrix
ipiv int vector of length at least min(m,n)
OPTIONS
m nonnegative integer. If negative, the default value is used.
n nonnegative integer. If negative, the default value is used.
ldA positive integer. ldA >= max(1,m). If zero, the default
value is used.
offsetA nonnegative integer
*/
func Getrf(A matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.N == 0 || ind.M == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return onError("lda")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.M {
return onError("sizeA")
}
if ipiv != nil && len(ipiv) < min(ind.N, ind.M) {
return onError("size ipiv")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
info = dgetrf(ind.M, ind.N, Aa[ind.OffsetA:], ind.LDa, ipiv)
case *matrix.ComplexMatrix:
}
if info != 0 {
return onError("Getrf call error")
}
return nil
}
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
}
// 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
}
// Returns ||Re x||_1 + ||Im x||_1.
//
// ARGUMENTS
// X float or complex matrix
//
// OPTIONS
// n integer. If n<0, the default value of n is used.
// The default value is equal to n = 1+(len(x)-offset-1)/inc or 0 if
// len(x) > offset+1
// inc positive integer
// offset nonnegative integer
//
func Asum(X matrix.Matrix, opts ...linalg.Option) (v matrix.Scalar) {
v = matrix.FScalar(math.NaN())
ind := linalg.GetIndexOpts(opts...)
err := check_level1_func(ind, fasum, X, nil)
if err != nil {
return
}
if ind.Nx == 0 {
return
}
switch X.(type) {
case *matrix.ComplexMatrix:
Xa := X.(*matrix.ComplexMatrix).ComplexArray()
v = matrix.FScalar(dzasum(ind.Nx, Xa[ind.OffsetX:], ind.IncX))
case *matrix.FloatMatrix:
Xa := X.(*matrix.FloatMatrix).FloatArray()
v = matrix.FScalar(dasum(ind.Nx, Xa[ind.OffsetX:], ind.IncX))
//default:
// err = onError("not implemented for parameter types", )
}
return
}