/*
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
}
func checkSyevd(ind *linalg.IndexOpts, A, W matrix.Matrix) error {
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return errors.New("Syevd: A not square")
}
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return errors.New("Syevd: lda")
}
if ind.OffsetA < 0 {
return errors.New("Syevd: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("Syevd: sizeA")
}
if ind.OffsetW < 0 {
return errors.New("Syevd: offsetW")
}
sizeW := W.NumElements()
if sizeW < ind.OffsetW+ind.N {
return errors.New("Syevd: sizeW")
}
return nil
}
func checkSytrf(ind *linalg.IndexOpts, A matrix.Matrix, ipiv []int32) error {
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return errors.New("A not square")
}
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return errors.New("Sytrf: lda")
}
if ind.OffsetA < 0 {
return errors.New("Sytrf: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("Sytrf: sizeA")
}
if ipiv != nil && len(ipiv) < ind.N {
return errors.New("Sytrf: size ipiv")
}
return nil
}
/*
QR factorization.
Geqrf(A, tau, m=A.Rows, n=A.Cols, ldA=max(1,A.Rows), offsetA=0)
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...)
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.M < 0 {
ind.M = A.Cols()
}
if ind.N == 0 || ind.M == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return errors.New("lda")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
if A.NumElements() < ind.OffsetA+ind.K*ind.LDa {
return errors.New("sizeA")
}
if tau.NumElements() < min(ind.M, ind.N) {
return errors.New("sizeTau")
}
if !matrix.EqualTypes(A, tau) {
return errors.New("not same type")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.FloatArray()
taua := tau.FloatArray()
info = dgeqrf(ind.M, ind.N, Aa[ind.OffsetA:], ind.LDa, taua)
case *matrix.ComplexMatrix:
return errors.New("ComplexMatrx: not implemented yet")
}
if info != 0 {
return errors.New("Geqrf failed")
}
return nil
}
func checkPotri(ind *linalg.IndexOpts, A matrix.Matrix) error {
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return errors.New("Potri: lda")
}
if ind.OffsetA < 0 {
return errors.New("Potri: offsetA")
}
if A.NumElements() < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("Potri: sizeA")
}
return nil
}
/*
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
}
func checkGbtrs(ind *linalg.IndexOpts, A, B matrix.Matrix, ipiv []int32) error {
if ind.Kl < 0 {
return errors.New("Gbtrs: invalid kl")
}
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.Nrhs < 0 {
ind.Nrhs = A.Cols()
}
if ind.N == 0 || ind.Nrhs == 0 {
return nil
}
if ind.Ku < 0 {
ind.Ku = A.Rows() - 2*ind.Kl - 1
}
if ind.Ku < 0 {
return errors.New("Gbtrs: invalid ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < 2*ind.Kl+ind.Ku+1 {
return errors.New("Gbtrs: lda")
}
if ind.OffsetA < 0 {
return errors.New("Gbtrs: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+2*ind.Kl+ind.Ku+1 {
return errors.New("Gbtrs: sizeA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.OffsetB < 0 {
return errors.New("Gbtrs: offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*ind.LDb+ind.N {
return errors.New("Gbtrs: sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return errors.New("Gbtrs: size ipiv")
}
return nil
}
func checkGbtrf(ind *linalg.IndexOpts, A matrix.Matrix, ipiv []int32) error {
if ind.M < 0 {
return errors.New("Gbtrf: illegal m")
}
if ind.Kl < 0 {
return errors.New("GBtrf: illegal kl")
}
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.M == 0 || ind.N == 0 {
return nil
}
if ind.Ku < 0 {
ind.Ku = A.Rows() - 2*ind.Kl - 1
}
if ind.Ku < 0 {
return errors.New("Gbtrf: invalid ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < 2*ind.Kl+ind.Ku+1 {
return errors.New("Gbtrf: lda")
}
if ind.OffsetA < 0 {
return errors.New("Gbtrf: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+2*ind.Kl+ind.Ku+1 {
return errors.New("Gbtrf: sizeA")
}
if ipiv != nil && len(ipiv) < min(ind.N, ind.M) {
return errors.New("Gbtrf: size ipiv")
}
return nil
}
func SyevrFloat(A, W, Z matrix.Matrix, abstol float64, vlimit []float64, ilimit []int, opts ...linalg.Option) error {
var vl, vu float64
var il, iu int
pars, err := linalg.GetParameters(opts...)
if err != nil {
return err
}
ind := linalg.GetIndexOpts(opts...)
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return errors.New("Syevr: A not square")
}
}
// Check indexes
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, A.Rows()) {
return errors.New("Syevr: lda")
}
if pars.Range == linalg.PRangeValue {
if vlimit == nil {
return errors.New("Syevr: vlimit is nil")
}
vl = vlimit[0]
vu = vlimit[1]
if vl >= vu {
return errors.New("Syevr: must be: vl < vu")
}
} else if pars.Range == linalg.PRangeInt {
if ilimit == nil {
return errors.New("Syevr: ilimit is nil")
}
il = ilimit[0]
iu = ilimit[1]
if il < 1 || il > iu || iu > ind.N {
return errors.New("Syevr: must be:1 <= il <= iu <= N")
}
}
if pars.Jobz == linalg.PJobValue {
if Z == nil {
return errors.New("Syevr: Z is nil")
}
if ind.LDz == 0 {
ind.LDz = max(1, Z.Rows())
}
if ind.LDz < max(1, ind.N) {
return errors.New("Syevr: ldz")
}
} else {
if ind.LDz == 0 {
ind.LDz = 1
}
if ind.LDz < 1 {
return errors.New("Syevr: ldz")
}
}
if ind.OffsetA < 0 {
return errors.New("Syevr: OffsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("Syevr: sizeA")
}
if ind.OffsetW < 0 {
return errors.New("Syevr: OffsetW")
}
sizeW := W.NumElements()
if sizeW < ind.OffsetW+ind.N {
return errors.New("Syevr: sizeW")
}
if pars.Jobz == linalg.PJobValue {
if ind.OffsetZ < 0 {
return errors.New("Syevr: OffsetW")
}
minZ := ind.OffsetZ + (ind.N-1)*ind.LDz + ind.N
if pars.Range == linalg.PRangeInt {
minZ = ind.OffsetZ + (iu-il)*ind.LDz + ind.N
}
if Z.NumElements() < minZ {
return errors.New("Syevr: sizeZ")
}
}
Aa := A.FloatArray()
Wa := W.FloatArray()
var Za []float64
if pars.Jobz == linalg.PJobValue {
Za = Z.FloatArray()
} else {
Za = nil
}
jobz := linalg.ParamString(pars.Jobz)
rnge := linalg.ParamString(pars.Range)
uplo := linalg.ParamString(pars.Uplo)
info := dsyevr(jobz, rnge, uplo, ind.N, Aa[ind.OffsetA:], ind.LDa,
vl, vu, il, iu, ind.M, Wa[ind.OffsetW:], Za, ind.LDz)
if info != 0 {
return errors.New(fmt.Sprintf("Syevr: call failed %d", info))
}
return nil
}
/*
Solves a real or complex set of linear equations with a banded
coefficient matrix, given the LU factorization computed by gbtrf()
or gbsv().
Gbtrs(A, B, ipiv, kl, trans=PNoTrans, n=A.Cols, ku=A.Rows-2*kl-1,
nrhs=B.Cols, ldA=max(1,A.Rows), ldB=max(1,B.Rows), offsetA=0, offsetB=0)
PURPOSE
Solves linear equations
A*X = B, if trans is PNoTrans
A^T*X = B, if trans is PTrans
A^H*X = B, if trans is PConjTrans
On entry, A and ipiv contain the LU factorization of an n by n
band matrix A as computed by Getrf() or Gbsv(). 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.
ipiv int vector
kl nonnegative integer
OPTIONS
trans PNoTrans, PTrans or PConjTrans
n nonnegative integer. If negative, the default value is used.
ku nonnegative integer. If negative, the default value is used.
nrhs nonnegative integer. If negative, the default value is used.
ldA positive integer, ldA >= 2*kl+ku+1. 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 Gbtrs(A, B matrix.Matrix, ipiv []int32, KL int, opts ...linalg.Option) error {
pars, err := linalg.GetParameters(opts...)
if err != nil {
return err
}
ind := linalg.GetIndexOpts(opts...)
//err = lapack_check(ind, fgbtrs, A, B, ipiv, pars)
ind.Kl = KL
if ind.Kl < 0 {
return errors.New("invalid kl")
}
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.Nrhs < 0 {
ind.Nrhs = A.Cols()
}
if ind.N == 0 || ind.Nrhs == 0 {
return nil
}
if ind.Ku < 0 {
ind.Ku = A.Rows() - 2*ind.Kl - 1
}
if ind.Ku < 0 {
return errors.New("invalid ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < 2*ind.Kl+ind.Ku+1 {
return errors.New("lda")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+2*ind.Kl+ind.Ku+1 {
return errors.New("sizeA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.OffsetB < 0 {
return errors.New("offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*ind.LDb+ind.N {
return errors.New("sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return errors.New("size ipiv")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
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)
case *matrix.ComplexMatrix:
return errors.New("Gbtrs for complex not yet implemented")
}
if info != 0 {
return errors.New("gbtrs call error")
}
return nil
}
func Gtrrs(DL, D, DU, DU2, B matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
pars, err := linalg.GetParameters(opts...)
if err != nil {
return err
}
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 ind.Nrhs < 0 {
ind.Nrhs = B.Cols()
}
if ind.Nrhs == 0 {
return nil
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.LDb < max(1, ind.N) {
return errors.New("ldB")
}
if ind.OffsetB < 0 {
return errors.New("offset B")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*ind.LDb+ind.N {
return errors.New("sizeB")
}
if len(ipiv) < ind.N {
return errors.New("size ipiv")
}
DLa := DL.FloatArray()
Da := D.FloatArray()
DUa := DU.FloatArray()
DU2a := DU2.FloatArray()
Ba := B.FloatArray()
trans := linalg.ParamString(pars.Trans)
info := dgttrs(trans, ind.N, ind.Nrhs,
DLa[ind.OffsetDL:], Da[ind.OffsetD:], DUa[ind.OffsetDU:], DU2a,
ipiv, Ba[ind.OffsetB:], ind.LDb)
if info != 0 {
return errors.New("dgttrs call error")
}
return nil
}
/*
Solution of a triangular set of equations with multiple righthand
sides.
Trtrs(A, B, uplo=PLower, trans=PNoTrans, diag=PNonUnit, n=A.Rows,
nrhs=B.Cols, ldA=max(1,A.Rows), ldB=max(1,B.Rows), offsetA=0, offsetB=0)
PURPOSE
Solves set of equations
A*X = B, if trans is PNoTrans
A^T*X = B, if trans is PTrans
A^H*X = B, if trans is PConjTrans
B is n by nrhs and A is triangular of order n.
ARGUMENTS
A float or complex matrix
B float or complex matrix. Must have the same type as A.
OPTIONS
uplo PLower or PUpper
trans PNoTrans, PTrans, PConjTrans
diag PNonUnit, PUnit
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 Trtrs(A, B matrix.Matrix, ipiv []int32, 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.N != A.Cols() {
return errors.New("A not square")
}
}
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")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("sizeA")
}
if ind.OffsetB < 0 {
return errors.New("offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*ind.LDb+ind.N {
return errors.New("sizeB")
}
info := -1
uplo := linalg.ParamString(pars.Uplo)
trans := linalg.ParamString(pars.Trans)
diag := linalg.ParamString(pars.Diag)
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.FloatArray()
Ba := B.FloatArray()
info = dtrtrs(uplo, trans, diag, ind.N, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa,
Ba[ind.OffsetB:], ind.LDb)
case *matrix.ComplexMatrix:
}
if info != 0 {
return errors.New("sytrf failed")
}
return nil
}
func check_level3_func(ind *linalg.IndexOpts, fn funcNum, A, B, C matrix.Matrix,
pars *linalg.Parameters) (err error) {
switch fn {
case fgemm:
if ind.M < 0 {
if pars.TransA == linalg.PNoTrans {
ind.M = A.Rows()
} else {
ind.M = A.Cols()
}
}
if ind.N < 0 {
if pars.TransB == linalg.PNoTrans {
ind.N = A.Cols()
} else {
ind.N = A.Rows()
}
}
if ind.K < 0 {
if pars.TransA == linalg.PNoTrans {
ind.K = A.Cols()
} else {
ind.K = A.Rows()
}
if pars.TransB == linalg.PNoTrans && ind.K != B.Rows() ||
pars.TransB != linalg.PNoTrans && ind.K != B.Cols() {
return errors.New("dimensions of A and B do not match")
}
}
if ind.OffsetB < 0 {
return errors.New("offsetB illegal, <0")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.K > 0 {
if (pars.TransA == linalg.PNoTrans && ind.LDa < max(1, ind.M)) ||
(pars.TransA != linalg.PNoTrans && ind.LDa < max(1, ind.K)) {
return errors.New("inconsistent ldA")
}
sizeA := A.NumElements()
if (pars.TransA == linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.K-1)*ind.LDa+ind.M) ||
(pars.TransA != linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.M-1)*ind.LDa+ind.K) {
return errors.New("sizeA")
}
}
// B matrix
if B != nil {
if ind.OffsetB < 0 {
return errors.New("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.K > 0 {
if (pars.TransB == linalg.PNoTrans && ind.LDb < max(1, ind.K)) ||
(pars.TransB != linalg.PNoTrans && ind.LDb < max(1, ind.N)) {
return errors.New("inconsistent ldB")
}
sizeB := B.NumElements()
if (pars.TransB == linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.N-1)*ind.LDb+ind.K) ||
(pars.TransB != linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.K-1)*ind.LDb+ind.N) {
return errors.New("sizeB")
}
}
}
// C matrix
if C != nil {
if ind.OffsetC < 0 {
return errors.New("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDb = max(1, C.Rows())
}
if ind.LDc < max(1, ind.M) {
return errors.New("inconsistent ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*ind.LDc+ind.M {
return errors.New("sizeC")
}
}
case fsymm, ftrmm, ftrsm:
if ind.M < 0 {
ind.M = B.Rows()
if pars.Side == linalg.PLeft && (ind.M != A.Rows() || ind.M != A.Cols()) {
return errors.New("dimensions of A and B do not match")
}
}
if ind.N < 0 {
ind.N = B.Cols()
if pars.Side == linalg.PRight && (ind.N != A.Rows() || ind.N != A.Cols()) {
return errors.New("dimensions of A and B do not match")
}
}
if ind.M == 0 || ind.N == 0 {
return
}
// check A
if ind.OffsetB < 0 {
return errors.New("offsetB illegal, <0")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if pars.Side == linalg.PLeft && ind.LDa < max(1, ind.M) || ind.LDa < max(1, ind.N) {
return errors.New("ldA")
}
sizeA := A.NumElements()
if (pars.Side == linalg.PLeft && sizeA < ind.OffsetA+(ind.M-1)*ind.LDa+ind.M) ||
(pars.Side == linalg.PRight && sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N) {
return errors.New("sizeA")
}
if B != nil {
if ind.OffsetB < 0 {
return errors.New("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.LDb < max(1, ind.M) {
return errors.New("ldB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.N-1)*ind.LDb+ind.M {
return errors.New("sizeB")
}
}
if C != nil {
if ind.OffsetC < 0 {
return errors.New("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.Rows())
}
if ind.LDc < max(1, ind.M) {
return errors.New("ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*ind.LDc+ind.M {
return errors.New("sizeC")
}
}
case fsyrk, fsyr2k:
if ind.N < 0 {
if pars.Trans == linalg.PNoTrans {
ind.N = B.Rows()
} else {
ind.N = B.Cols()
}
}
if ind.K < 0 {
if pars.Trans == linalg.PNoTrans {
ind.K = A.Cols()
} else {
ind.K = A.Rows()
}
}
if ind.N == 0 {
return
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.K > 0 {
if (pars.Trans == linalg.PNoTrans && ind.LDa < max(1, ind.N)) ||
(pars.Trans != linalg.PNoTrans && ind.LDa < max(1, ind.K)) {
return errors.New("inconsistent ldA")
}
sizeA := A.NumElements()
if (pars.Trans == linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.K-1)*ind.LDa+ind.N) ||
(pars.TransA != linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.K) {
return errors.New("sizeA")
}
}
if B != nil {
if ind.OffsetB < 0 {
return errors.New("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.Rows())
}
if ind.K > 0 {
if (pars.Trans == linalg.PNoTrans && ind.LDb < max(1, ind.N)) ||
(pars.Trans != linalg.PNoTrans && ind.LDb < max(1, ind.K)) {
return errors.New("ldB")
}
sizeB := B.NumElements()
if (pars.Trans == linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.K-1)*ind.LDb+ind.N) ||
(pars.Trans != linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.N-1)*ind.LDb+ind.K) {
return errors.New("sizeB")
}
}
}
if C != nil {
if ind.OffsetC < 0 {
return errors.New("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.Rows())
}
if ind.LDc < max(1, ind.N) {
return errors.New("ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*ind.LDc+ind.N {
return errors.New("sizeC")
}
}
}
err = nil
return
}
func check_level2_func(ind *linalg.IndexOpts, fn funcNum, X, Y, A matrix.Matrix, pars *linalg.Parameters) error {
if ind.IncX <= 0 {
return errors.New("incX")
}
if ind.IncY <= 0 {
return errors.New("incY")
}
sizeA := A.NumElements()
switch fn {
case fgemv: // general matrix
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
if ind.N > 0 && ind.M > 0 &&
sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.M {
return errors.New("sizeA")
}
if ind.OffsetX < 0 {
return errors.New("offsetX")
}
if ind.OffsetY < 0 {
return errors.New("offsetY")
}
sizeX := X.NumElements()
sizeY := Y.NumElements()
if pars.Trans == linalg.PNoTrans {
if ind.N > 0 && sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if ind.M > 0 && sizeY < ind.OffsetY+(ind.M-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
} else {
if ind.M > 0 && sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
}
case fger:
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.M == 0 || ind.N == 0 {
return nil
}
if ind.M > 0 && ind.N > 0 {
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return errors.New("ldA")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.M {
return errors.New("sizeA")
}
if ind.OffsetX < 0 {
return errors.New("offsetX")
}
if ind.OffsetY < 0 {
return errors.New("offsetY")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
}
case fgbmv: // general banded
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.Kl < 0 {
return errors.New("kl")
}
if ind.Ku < 0 {
ind.Ku = A.Rows() - 1 - ind.Kl
}
if ind.Ku < 0 {
return errors.New("ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < ind.Kl+ind.Ku+1 {
return errors.New("ldA")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
sizeA := A.NumElements()
if ind.N > 0 && ind.M > 0 &&
sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.Kl+ind.Ku+1 {
return errors.New("sizeA")
}
if ind.OffsetX < 0 {
return errors.New("offsetX")
}
if ind.OffsetY < 0 {
return errors.New("offsetY")
}
sizeX := X.NumElements()
sizeY := Y.NumElements()
if pars.Trans == linalg.PNoTrans {
if ind.N > 0 && sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.M-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
} else {
if ind.N > 0 && sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
}
case ftrmv, ftrsv:
// ftrmv = triangular
// ftrsv = triangular solve
if ind.N < 0 {
if A.Rows() != A.Cols() {
return errors.New("A not square")
}
ind.N = A.Rows()
}
if ind.N > 0 {
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return errors.New("ldA")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("sizeA")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
}
case ftbmv, ftbsv, fsbmv:
// ftbmv = triangular banded
// ftbsv = triangular banded solve
// fsbmv = symmetric banded product
if ind.N < 0 {
ind.N = A.Rows()
}
if ind.N > 0 {
if ind.K < 0 {
ind.K = max(0, A.Rows()-1)
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < ind.K+1 {
return errors.New("ldA")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.K+1 {
return errors.New("sizeA")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if Y != nil {
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
}
}
case fsymv, fsyr, fsyr2:
// fsymv = symmetric product
// fsyr = symmetric rank update
// fsyr2 = symmetric rank-2 update
if ind.N < 0 {
if A.Rows() != A.Cols() {
return errors.New("A not square")
}
ind.N = A.Rows()
}
if ind.N > 0 {
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return errors.New("ldA")
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.N {
return errors.New("sizeA")
}
if ind.OffsetX < 0 {
return errors.New("offsetX")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return errors.New("sizeX")
}
if Y != nil {
if ind.OffsetY < 0 {
return errors.New("offsetY")
}
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return errors.New("sizeY")
}
}
}
case fspr, fdspr2, ftpsv, fspmv, ftpmv:
// ftpsv = triangular packed solve
// fspmv = symmetric packed product
// ftpmv = triangular packed
}
return nil
}
func checkGesvd(ind *linalg.IndexOpts, pars *linalg.Parameters, A, S, U, Vt matrix.Matrix) error {
if ind.M < 0 {
ind.M = A.Rows()
}
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.M == 0 || ind.N == 0 {
return nil
}
if pars.Jobu == linalg.PJobO && pars.Jobvt == linalg.PJobO {
return errors.New("Gesvd: jobu and jobvt cannot both have value PJobO")
}
if pars.Jobu == linalg.PJobAll || pars.Jobu == linalg.PJobS {
if U == nil {
return errors.New("Gesvd: missing matrix U")
}
if ind.LDu == 0 {
ind.LDu = max(1, U.Rows())
}
if ind.LDu < max(1, ind.M) {
return errors.New("Gesvd: ldU")
}
} else {
if ind.LDu == 0 {
ind.LDu = 1
}
if ind.LDu < 1 {
return errors.New("Gesvd: ldU")
}
}
if pars.Jobvt == linalg.PJobAll || pars.Jobvt == linalg.PJobS {
if Vt == nil {
return errors.New("Gesvd: missing matrix Vt")
}
if ind.LDvt == 0 {
ind.LDvt = max(1, Vt.Rows())
}
if pars.Jobvt == linalg.PJobAll && ind.LDvt < max(1, ind.N) {
return errors.New("Gesvd: ldVt")
} else if pars.Jobvt != linalg.PJobAll && ind.LDvt < max(1, min(ind.M, ind.N)) {
return errors.New("Gesvd: ldVt")
}
} else {
if ind.LDvt == 0 {
ind.LDvt = 1
}
if ind.LDvt < 1 {
return errors.New("Gesvd: ldVt")
}
}
if ind.OffsetA < 0 {
return errors.New("Gesvd: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*ind.LDa+ind.M {
return errors.New("Gesvd: sizeA")
}
if ind.OffsetS < 0 {
return errors.New("Gesvd: offsetS")
}
sizeS := S.NumElements()
if sizeS < ind.OffsetS+min(ind.M, ind.N) {
return errors.New("Gesvd: sizeA")
}
/*
if U != nil {
if ind.OffsetU < 0 {
return errors.New("Gesvd: OffsetU")
}
sizeU := U.NumElements()
if pars.Jobu == linalg.PJobAll && sizeU < ind.LDu*(ind.M-1) {
return errors.New("Gesvd: sizeU")
} else if pars.Jobu == linalg.PJobS && sizeU < ind.LDu*(min(ind.M,ind.N)-1) {
return errors.New("Gesvd: sizeU")
}
}
if Vt != nil {
if ind.OffsetVt < 0 {
return errors.New("Gesvd: OffsetVt")
}
sizeVt := Vt.NumElements()
if pars.Jobvt == linalg.PJobAll && sizeVt < ind.N {
return errors.New("Gesvd: sizeVt")
} else if pars.Jobvt == linalg.PJobS && sizeVt < min(ind.M, ind.N) {
return errors.New("Gesvd: sizeVt")
}
}
*/
return nil
}
/*
Product with a real orthogonal matrix.
Ormqr(A, tau, C, side='L', trans='N', m=C.Rows, n=C.Cols,
k=len(tau), ldA=max(1,A.Rows), ldC=max(1,C.Rows), offsetA=0, offsetC=0)
PURPOSE
Computes
C := Q*C if side = PLeft and trans = PNoTrans
C := Q^T*C if side = PLeft and trans = PTrans
C := C*Q if side = PRight and trans = PNoTrans
C := C*Q^T if side = PRight and trans = PTrans
C is m by n and Q is a square orthogonal matrix computed by geqrf.
Q is defined as a product of k elementary reflectors, stored as
the first k columns of A and the first k entries of tau.
ARGUMENTS
A float matrix
tau float matrix of length at least k
C float matrix
OPTIONS
side PLeft or PRight
trans PNoTrans or PTrans
m integer. If negative, the default value is used.
n integer. If negative, the default value is used.
k integer. k <= m if side = PRight and k <= n if side = PLeft.
If negative, the default value is used.
ldA nonnegative integer. ldA >= max(1,m) if side = PLeft
and ldA >= max(1,n) if side = PRight. 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
*/
func Ormqf(A, tau, C 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 = C.Cols()
}
if ind.M < 0 {
ind.M = C.Rows()
}
if ind.K < 0 {
ind.K = tau.NumElements()
}
if ind.N == 0 || ind.M == 0 || ind.K == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.Rows())
}
if ind.LDc == 0 {
ind.LDc = max(1, C.Rows())
}
switch pars.Side {
case linalg.PLeft:
if ind.K > ind.M {
errors.New("K")
}
if ind.LDa < max(1, ind.M) {
return errors.New("lda")
}
case linalg.PRight:
if ind.K > ind.N {
errors.New("K")
}
if ind.LDa < max(1, ind.N) {
return errors.New("lda")
}
}
if ind.OffsetA < 0 {
return errors.New("offsetA")
}
if A.NumElements() < ind.OffsetA+ind.K*ind.LDa {
return errors.New("sizeA")
}
if ind.OffsetC < 0 {
return errors.New("offsetC")
}
if C.NumElements() < ind.OffsetC+(ind.N-1)*ind.LDa+ind.M {
return errors.New("sizeC")
}
if tau.NumElements() < ind.K {
return errors.New("sizeTau")
}
if !matrix.EqualTypes(A, C, tau) {
return errors.New("not same type")
}
info := -1
side := linalg.ParamString(pars.Side)
trans := linalg.ParamString(pars.Trans)
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.FloatArray()
Ca := C.FloatArray()
taua := tau.FloatArray()
info = dormqr(side, trans, ind.M, ind.N, ind.K, Aa[ind.OffsetA:], ind.LDa,
taua, Ca[ind.OffsetC:], ind.LDc)
case *matrix.ComplexMatrix:
return errors.New("ComplexMatrx: not implemented yet")
}
if info != 0 {
return errors.New("Ormqr failed")
}
return nil
}