func checkSyevd(ind *linalg.IndexOpts, A, W matrix.Matrix) error {
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("Syevd: A not square")
}
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Syevd: lda")
}
if ind.OffsetA < 0 {
return onError("Syevd: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Syevd: sizeA")
}
if ind.OffsetW < 0 {
return onError("Syevd: offsetW")
}
sizeW := W.NumElements()
if sizeW < ind.OffsetW+ind.N {
return onError("Syevd: sizeW")
}
return nil
}
func checkSytrf(ind *linalg.IndexOpts, A matrix.Matrix, ipiv []int32) error {
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("A not square")
}
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Sytrf: lda")
}
if ind.OffsetA < 0 {
return onError("Sytrf: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Sytrf: sizeA")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Sytrf: size ipiv")
}
return nil
}
func checkPotrf(ind *linalg.IndexOpts, A matrix.Matrix) error {
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("Potrf: not square")
}
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Potrf: lda")
}
if ind.OffsetA < 0 {
return onError("Potrf: offsetA")
}
if A.NumElements() < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Potrf: sizeA")
}
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 checkGbtrs(ind *linalg.IndexOpts, A, B matrix.Matrix, ipiv []int32) error {
arows := ind.LDa
brows := ind.LDb
if ind.Kl < 0 {
return onError("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 onError("Gbtrs: invalid ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < 2*ind.Kl+ind.Ku+1 {
return onError("Gbtrs: lda")
}
if ind.OffsetA < 0 {
return onError("Gbtrs: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+2*ind.Kl+ind.Ku+1 {
return onError("Gbtrs: sizeA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.OffsetB < 0 {
return onError("Gbtrs: offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Gbtrs: sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Gbtrs: size ipiv")
}
return nil
}
/*
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 checkPosv(ind *linalg.IndexOpts, A, B matrix.Matrix) error {
arows := ind.LDa
brows := ind.LDb
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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Posv: lda")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(1, ind.N) {
return onError("Posv: ldb")
}
if ind.OffsetA < 0 {
return onError("Posv: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Posv: sizeA")
}
if ind.OffsetB < 0 {
return onError("Posv: offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Posv: sizeB")
}
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
}
/*
Inverse of a real or complex matrix.
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...)
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Cols()
}
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.OffsetA < 0 {
return onError("Getri: offset")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Getri: sizeA")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Getri: size ipiv")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
info = dgetri(ind.N, Aa[ind.OffsetA:], ind.LDa, ipiv)
case *matrix.ComplexMatrix:
return onError("Getri: complex not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Getri lapack error: %d", info))
}
return nil
}
func checkGesvd(ind *linalg.IndexOpts, pars *linalg.Parameters, A, S, U, Vt matrix.Matrix) error {
arows := ind.LDa
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 onError("Gesvd: jobu and jobvt cannot both have value PJobO")
}
if pars.Jobu == linalg.PJobAll || pars.Jobu == linalg.PJobS {
if U == nil {
return onError("Gesvd: missing matrix U")
}
if ind.LDu == 0 {
ind.LDu = max(1, U.LeadingIndex())
}
if ind.LDu < max(1, ind.M) {
return onError("Gesvd: ldU")
}
} else {
if ind.LDu == 0 {
ind.LDu = 1
}
if ind.LDu < 1 {
return onError("Gesvd: ldU")
}
}
if pars.Jobvt == linalg.PJobAll || pars.Jobvt == linalg.PJobS {
if Vt == nil {
return onError("Gesvd: missing matrix Vt")
}
if ind.LDvt == 0 {
ind.LDvt = max(1, Vt.LeadingIndex())
}
if pars.Jobvt == linalg.PJobAll && ind.LDvt < max(1, ind.N) {
return onError("Gesvd: ldVt")
} else if pars.Jobvt != linalg.PJobAll && ind.LDvt < max(1, min(ind.M, ind.N)) {
return onError("Gesvd: ldVt")
}
} else {
if ind.LDvt == 0 {
ind.LDvt = 1
}
if ind.LDvt < 1 {
return onError("Gesvd: ldVt")
}
}
if ind.OffsetA < 0 {
return onError("Gesvd: offsetA")
}
sizeA := A.NumElements()
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.M {
return onError("Gesvd: sizeA")
}
if ind.OffsetS < 0 {
return onError("Gesvd: offsetS")
}
sizeS := S.NumElements()
if sizeS < ind.OffsetS+min(ind.M, ind.N) {
return onError("Gesvd: sizeA")
}
/*
if U != nil {
if ind.OffsetU < 0 {
return onError("Gesvd: OffsetU")
}
sizeU := U.NumElements()
if pars.Jobu == linalg.PJobAll && sizeU < ind.LDu*(ind.M-1) {
return onError("Gesvd: sizeU")
} else if pars.Jobu == linalg.PJobS && sizeU < ind.LDu*(min(ind.M,ind.N)-1) {
return onError("Gesvd: sizeU")
}
}
if Vt != nil {
if ind.OffsetVt < 0 {
return onError("Gesvd: OffsetVt")
}
sizeVt := Vt.NumElements()
if pars.Jobvt == linalg.PJobAll && sizeVt < ind.N {
return onError("Gesvd: sizeVt")
} else if pars.Jobvt == linalg.PJobS && sizeVt < min(ind.M, ind.N) {
return onError("Gesvd: sizeVt")
}
}
*/
return nil
}
/*
Solves a general real or complex set of linear equations.
PURPOSE
Solves A*X=B with A n by n real or complex.
If ipiv is provided, then on exit A is overwritten with the details
of the LU factorization, and ipiv contains the permutation matrix.
If ipiv is not provided, then gesv() does not return the
factorization and does not modify A. On exit B is replaced with
the solution X.
ARGUMENTS.
A float or complex matrix
B float or complex matrix. Must have the same type as A.
ipiv int vector of length at least n
OPTIONS:
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
offsetA nonnegative integer;
*/
func Gesv(A, B matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
//pars, err := linalg.GetParameters(opts...)
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
brows := ind.LDb
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("Gesv: 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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Gesv: ldA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(1, ind.N) {
return onError("Gesv: ldB")
}
if ind.OffsetA < 0 {
return onError("Gesv: offsetA")
}
if ind.OffsetB < 0 {
return onError("Gesv: offsetB")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Gesv: sizeA")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Gesv: sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Gesv: size ipiv")
}
if !matrix.EqualTypes(A, B) {
return onError("Gesv: arguments not of same type")
}
info := -1
if ipiv == nil {
ipiv = make([]int32, ind.N)
// Do not overwrite A.
A = A.MakeCopy()
}
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Aa = Aa[ind.OffsetA:]
// Ensure there are sufficient elements in A.
Aa = Aa[:ind.LDa*ind.LDb]
Ba := B.(*matrix.FloatMatrix).FloatArray()
Ba = Ba[ind.OffsetB:]
info = dgesv(ind.N, ind.Nrhs, Aa, ind.LDa, ipiv, Ba, ind.LDb)
case *matrix.ComplexMatrix:
Aa := A.(*matrix.ComplexMatrix).ComplexArray()
Aa = Aa[ind.OffsetA:]
// Ensure there are sufficient elements in A.
Aa = Aa[:ind.LDa*ind.LDb]
Ba := B.(*matrix.ComplexMatrix).ComplexArray()
Ba = Ba[ind.OffsetB:]
info = zgesv(ind.N, ind.Nrhs, Aa, ind.LDa, ipiv, Ba, ind.LDb)
}
if info != 0 {
return onError(fmt.Sprintf("Gesv: lapack error: %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().
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...)
ind.Kl = KL
arows := ind.LDa
brows := ind.LDb
if ind.Kl < 0 {
return onError("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 onError("Gbtrs: invalid ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < 2*ind.Kl+ind.Ku+1 {
return onError("Gbtrs: ldA")
}
if ind.OffsetA < 0 {
return onError("Gbtrs: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+2*ind.Kl+ind.Ku+1 {
return onError("Gbtrs: sizeA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.OffsetB < 0 {
return onError("Gbtrs: offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Gbtrs: sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Gbtrs: size ipiv")
}
if !matrix.EqualTypes(A, B) {
return onError("Gbtrs: arguments not of same type")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Ba := B.(*matrix.FloatMatrix).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 onError("Gbtrs: complex not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Gbtrs lapack error: %d", info))
}
return nil
}
/*
Solves a real or complex tridiagonal set of linear equations,
given the LU factorization computed by gttrf().
PURPOSE
solves A*X=B, if trans is PNoTrans
solves A^T*X=B, if trans is PTrans
solves A^H*X=B, if trans is PConjTrans
On entry, DL, D, DU, DU2 and ipiv contain the LU factorization of
an n by n tridiagonal matrix A as computed by gttrf(). On exit B
is replaced by the solution X.
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. Must have the same type as dl.
B float or complex matrix. Must have the same type oas dl.
ipiv int vector
OPTIONS
trans PNoTrans, PTrans, PConjTrans
n nonnegative integer. If negative, the default value is used.
nrhs nonnegative integer. If negative, the default value is used.
ldB positive integer, ldB >= max(1,n). If zero, the default value is used.
offsetdl nonnegative integer
offsetd nonnegative integer
offsetdu nonnegative integer
offsetB nonnegative integer
*/
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...)
brows := ind.LDb
if ind.OffsetD < 0 {
return onError("Gttrs: offset D")
}
if ind.N < 0 {
ind.N = D.NumElements() - ind.OffsetD
}
if ind.N < 0 {
return onError("Gttrs: size D")
}
if ind.N == 0 {
return nil
}
if ind.OffsetDL < 0 {
return onError("Gttrs: offset DL")
}
sizeDL := DL.NumElements()
if sizeDL < ind.OffsetDL+ind.N-1 {
return onError("Gttrs: sizeDL")
}
if ind.OffsetDU < 0 {
return onError("Gttrs: offset DU")
}
sizeDU := DU.NumElements()
if sizeDU < ind.OffsetDU+ind.N-1 {
return onError("Gttrs: sizeDU")
}
sizeDU2 := DU2.NumElements()
if sizeDU2 < ind.N-2 {
return onError("Gttrs: sizeDU2")
}
if ind.Nrhs < 0 {
ind.Nrhs = B.Cols()
}
if ind.Nrhs == 0 {
return nil
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(1, ind.N) {
return onError("Gttrs: ldB")
}
if ind.OffsetB < 0 {
return onError("Gttrs: offset B")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Gttrs: sizeB")
}
if len(ipiv) < ind.N {
return onError("Gttrs: size ipiv")
}
if !matrix.EqualTypes(DL, D, DU, DU2, B) {
return onError("Gttrs: matrix types")
}
var info int = -1
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()
Ba := B.(*matrix.FloatMatrix).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)
case *matrix.ComplexMatrix:
return onError("Gttrs: complex valued not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Gttrs lapack error: %d", info))
}
return nil
}
func check_level2_func(ind *linalg.IndexOpts, fn funcNum, X, Y, A matrix.Matrix, pars *linalg.Parameters) error {
if ind.IncX <= 0 {
return onError("incX")
}
if ind.IncY <= 0 {
return onError("incY")
}
sizeA := A.NumElements()
arows := ind.LDa
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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
if ind.N > 0 && ind.M > 0 &&
sizeA < ind.OffsetA+(ind.N-1)*arows+ind.M {
return onError("sizeA")
}
if ind.OffsetX < 0 {
return onError("offsetX")
}
if ind.OffsetY < 0 {
return onError("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 onError("sizeX")
}
if ind.M > 0 && sizeY < ind.OffsetY+(ind.M-1)*abs(ind.IncY)+1 {
return onError("sizeY")
}
} else {
if ind.M > 0 && sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return onError("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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.M) {
return onError("ldA")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.M {
return onError("sizeA")
}
if ind.OffsetX < 0 {
return onError("offsetX")
}
if ind.OffsetY < 0 {
return onError("offsetY")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return onError("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 onError("kl")
}
if ind.Ku < 0 {
ind.Ku = A.Rows() - 1 - ind.Kl
}
if ind.Ku < 0 {
return onError("ku")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < ind.Kl+ind.Ku+1 {
return onError("ldA")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
sizeA := A.NumElements()
if ind.N > 0 && ind.M > 0 &&
sizeA < ind.OffsetA+(ind.N-1)*arows+ind.Kl+ind.Ku+1 {
return onError("sizeA")
}
if ind.OffsetX < 0 {
return onError("offsetX")
}
if ind.OffsetY < 0 {
return onError("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 onError("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.M-1)*abs(ind.IncY)+1 {
return onError("sizeY")
}
} else {
if ind.N > 0 && sizeX < ind.OffsetX+(ind.M-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
if ind.N > 0 && sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return onError("sizeY")
}
}
case ftrmv, ftrsv:
// ftrmv = triangular
// ftrsv = triangular solve
if ind.N < 0 {
if A.Rows() != A.Cols() {
return onError("A not square")
}
ind.N = A.Rows()
}
if ind.N > 0 {
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("ldA")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("sizeA")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
}
case ftbmv, ftbsv, fsbmv:
// ftbmv = triangular banded
// ftbsv = triangular banded solve
// fsbmv = symmetric banded product
arows := ind.LDa
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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < ind.K+1 {
return onError("ldA")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.K+1 {
return onError("sizeA")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
if Y != nil {
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return onError("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 onError("A not square")
}
ind.N = A.Rows()
}
arows := ind.LDa
if ind.N > 0 {
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("ldA")
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("sizeA")
}
if ind.OffsetX < 0 {
return onError("offsetX")
}
sizeX := X.NumElements()
if sizeX < ind.OffsetX+(ind.N-1)*abs(ind.IncX)+1 {
return onError("sizeX")
}
if Y != nil {
if ind.OffsetY < 0 {
return onError("offsetY")
}
sizeY := Y.NumElements()
if sizeY < ind.OffsetY+(ind.N-1)*abs(ind.IncY)+1 {
return onError("sizeY")
}
}
}
case fspr, fdspr2, ftpsv, fspmv, ftpmv:
// ftpsv = triangular packed solve
// fspmv = symmetric packed product
// ftpmv = triangular packed
}
return nil
}
func check_level3_func(ind *linalg.IndexOpts, fn funcNum, A, B, C matrix.Matrix,
pars *linalg.Parameters) (err error) {
// defaults for these
arows := ind.LDa
brows := ind.LDb
crows := ind.LDc
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 = B.Cols()
} else {
ind.N = B.Rows()
}
}
if ind.M == 0 || ind.N == 0 {
return nil
}
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 onError("dimensions of A and B do not match")
}
}
if ind.OffsetA < 0 {
return onError("offsetA illegal, <0")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = 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 onError("inconsistent ldA")
}
sizeA := A.NumElements()
if (pars.TransA == linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.K-1)*arows+ind.M) ||
(pars.TransA != linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.M-1)*arows+ind.K) {
return onError("sizeA")
}
}
// B matrix
if ind.OffsetB < 0 {
return onError("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = 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 onError("inconsistent ldB")
}
sizeB := B.NumElements()
if (pars.TransB == linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.N-1)*brows+ind.K) ||
(pars.TransB != linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.K-1)*brows+ind.N) {
return onError("sizeB")
}
}
// C matrix
if ind.OffsetC < 0 {
return onError("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.LeadingIndex())
crows = max(1, C.Rows())
}
if ind.LDc < max(1, ind.M) {
return onError("inconsistent ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*crows+ind.M {
return onError("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 onError("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 onError("dimensions of A and B do not match")
}
}
if ind.M == 0 || ind.N == 0 {
return
}
// check A
if ind.OffsetB < 0 {
return onError("offsetB illegal, <0")
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if pars.Side == linalg.PLeft && ind.LDa < max(1, ind.M) || ind.LDa < max(1, ind.N) {
return onError("ldA")
}
sizeA := A.NumElements()
if (pars.Side == linalg.PLeft && sizeA < ind.OffsetA+(ind.M-1)*arows+ind.M) ||
(pars.Side == linalg.PRight && sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N) {
return onError("sizeA")
}
if B != nil {
if ind.OffsetB < 0 {
return onError("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(1, ind.M) {
return onError("ldB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.N-1)*brows+ind.M {
return onError("sizeB")
}
}
if C != nil {
if ind.OffsetC < 0 {
return onError("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.LeadingIndex())
crows = max(1, C.Rows())
}
if ind.LDc < max(1, ind.M) {
return onError("ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*crows+ind.M {
return onError("sizeC")
}
}
case fsyrk:
if ind.N < 0 {
if pars.Trans == linalg.PNoTrans {
ind.N = A.Rows()
} else {
ind.N = A.Cols()
}
//ind.N = C.Rows()
}
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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.OffsetA < 0 {
return onError("offsetA")
}
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 onError("inconsistent ldA")
}
sizeA := A.NumElements()
if (pars.Trans == linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.K-1)*arows+ind.N) ||
(pars.TransA != linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.N-1)*arows+ind.K) {
return onError("sizeA")
}
}
if ind.OffsetC < 0 {
return onError("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.LeadingIndex())
crows = max(1, C.Rows())
}
if ind.LDc < max(1, ind.N) {
return onError("ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*crows+ind.N {
return onError("sizeC")
}
case fsyr2k:
if ind.N < 0 {
if pars.Trans == linalg.PNoTrans {
ind.N = A.Rows()
if ind.N != B.Rows() {
return onError("dimensions of A and B do not match")
}
} else {
ind.N = A.Cols()
if ind.N != B.Cols() {
return onError("dimensions of A and B do not match")
}
}
}
if ind.N == 0 {
return
}
if ind.K < 0 {
if pars.Trans == linalg.PNoTrans {
ind.K = A.Cols()
if ind.K != B.Cols() {
return onError("dimensions of A and B do not match")
}
} else {
ind.K = A.Rows()
if ind.K != B.Rows() {
return onError("dimensions of A and B do not match")
}
}
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = 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 onError("inconsistent ldA")
}
sizeA := A.NumElements()
if (pars.Trans == linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.K-1)*arows+ind.N) ||
(pars.TransA != linalg.PNoTrans &&
sizeA < ind.OffsetA+(ind.N-1)*arows+ind.K) {
return onError("sizeA")
}
}
if ind.OffsetB < 0 {
return onError("offsetB illegal, <0")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = 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 onError("ldB")
}
sizeB := B.NumElements()
if (pars.Trans == linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.K-1)*brows+ind.N) ||
(pars.Trans != linalg.PNoTrans &&
sizeB < ind.OffsetB+(ind.N-1)*brows+ind.K) {
return onError("sizeB")
}
}
if ind.OffsetC < 0 {
return onError("offsetC illegal, <0")
}
if ind.LDc == 0 {
ind.LDc = max(1, C.LeadingIndex())
crows = max(1, C.Rows())
}
if ind.LDc < max(1, ind.N) {
return onError("ldC")
}
sizeC := C.NumElements()
if sizeC < ind.OffsetC+(ind.N-1)*crows+ind.N {
return onError("sizeC")
}
}
err = nil
return
}
/*
Solves a real or complex symmetric set of linear equations,
given the LDL^T factorization computed by sytrf() or sysv().
PURPOSE
Solves
A*X = B
where A is real or complex symmetric and n by n,
and B is n by nrhs. On entry, A and ipiv contain the
factorization of A as returned by Sytrf() or Sysv(). On exit, B is
replaced by the solution.
ARGUMENTS
A float or complex matrix
B float or complex matrix. Must have the same type as A.
ipiv int vector
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 nonnegative integer. ldB >= max(1,n). If zero, the
default value is used.
offsetA nonnegative integer
offsetB nonnegative integer;
*/
func Sytrs(A, B matrix.Matrix, ipiv []int32, opts ...linalg.Option) error {
pars, err := linalg.GetParameters(opts...)
if err != nil {
return err
}
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
brows := ind.LDb
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("Sytrs: 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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, ind.N) {
return onError("Sytrs: ldA")
}
if ind.LDb == 0 {
ind.LDb = max(1, B.LeadingIndex())
brows = max(1, B.Rows())
}
if ind.LDb < max(1, ind.N) {
return onError("Sytrs: ldB")
}
if ind.OffsetA < 0 {
return onError("Sytrs: offsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Sytrs: sizeA")
}
if ind.OffsetB < 0 {
return onError("Sytrs: offsetB")
}
sizeB := B.NumElements()
if sizeB < ind.OffsetB+(ind.Nrhs-1)*brows+ind.N {
return onError("Sytrs: sizeB")
}
if ipiv != nil && len(ipiv) < ind.N {
return onError("Sytrs: size ipiv")
}
if !matrix.EqualTypes(A, B) {
return onError("Sytrs: arguments not of same type")
}
info := -1
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Ba := B.(*matrix.FloatMatrix).FloatArray()
uplo := linalg.ParamString(pars.Uplo)
info = dsytrs(uplo, ind.N, ind.Nrhs, Aa[ind.OffsetA:], ind.LDa, ipiv,
Ba[ind.OffsetB:], ind.LDb)
case *matrix.ComplexMatrix:
return onError("Sytrs: complex not yet implemented")
}
if info != 0 {
return onError(fmt.Sprintf("Sytrs lapack error: %d", info))
}
return nil
}
/*
Product with a real orthogonal matrix.
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 Ormqr(A, tau, C matrix.Matrix, opts ...linalg.Option) error {
pars, err := linalg.GetParameters(opts...)
if err != nil {
return err
}
ind := linalg.GetIndexOpts(opts...)
arows := ind.LDa
crows := ind.LDc
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.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDc == 0 {
ind.LDc = max(1, C.LeadingIndex())
crows = max(1, C.Rows())
}
switch pars.Side {
case linalg.PLeft:
if ind.K > ind.M {
onError("Ormqf: K")
}
if ind.LDa < max(1, ind.M) {
return onError("Ormqf: ldA")
}
case linalg.PRight:
if ind.K > ind.N {
onError("Ormqf: K")
}
if ind.LDa < max(1, ind.N) {
return onError("Ormqf: ldA")
}
}
if ind.OffsetA < 0 {
return onError("Ormqf: offsetA")
}
if A.NumElements() < ind.OffsetA+ind.K*arows {
return onError("Ormqf: sizeA")
}
if ind.OffsetC < 0 {
return onError("Ormqf: offsetC")
}
if C.NumElements() < ind.OffsetC+(ind.N-1)*crows+ind.M {
return onError("Ormqf: sizeC")
}
if tau.NumElements() < ind.K {
return onError("Ormqf: sizeTau")
}
if !matrix.EqualTypes(A, C, tau) {
return onError("Ormqf: arguments not of same type")
}
info := -1
side := linalg.ParamString(pars.Side)
trans := linalg.ParamString(pars.Trans)
switch A.(type) {
case *matrix.FloatMatrix:
Aa := A.(*matrix.FloatMatrix).FloatArray()
Ca := C.(*matrix.FloatMatrix).FloatArray()
taua := tau.(*matrix.FloatMatrix).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 onError("Ormqf: complex not implemented yet")
}
if info != 0 {
return onError(fmt.Sprintf("Ormqr: lapack error %d", info))
}
return nil
}
func SyevxFloat(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...)
arows := ind.LDa
if ind.N < 0 {
ind.N = A.Rows()
if ind.N != A.Cols() {
return onError("Syevr: A not square")
}
}
// Check indexes
if ind.N == 0 {
return nil
}
if ind.LDa == 0 {
ind.LDa = max(1, A.LeadingIndex())
arows = max(1, A.Rows())
}
if ind.LDa < max(1, A.Rows()) {
return onError("Syevr: lda")
}
if pars.Range == linalg.PRangeValue {
if vlimit == nil {
return onError("Syevx: vlimit is nil")
}
vl = vlimit[0]
vu = vlimit[1]
if vl >= vu {
return onError("Syevx: must be: vl < vu")
}
} else if pars.Range == linalg.PRangeInt {
if ilimit == nil {
return onError("Syevx: ilimit is nil")
}
il = ilimit[0]
iu = ilimit[1]
if il < 1 || il > iu || iu > ind.N {
return onError("Syevx: must be:1 <= il <= iu <= N")
}
}
if pars.Jobz == linalg.PJobValue {
if Z == nil {
return onError("Syevx: Z is nil")
}
if ind.LDz == 0 {
ind.LDz = max(1, Z.LeadingIndex())
}
if ind.LDz < max(1, ind.N) {
return onError("Syevx: ldz")
}
} else {
if ind.LDz == 0 {
ind.LDz = 1
}
if ind.LDz < 1 {
return onError("Syevx: ldz")
}
}
if ind.OffsetA < 0 {
return onError("Syevx: OffsetA")
}
sizeA := A.NumElements()
if sizeA < ind.OffsetA+(ind.N-1)*arows+ind.N {
return onError("Syevx: sizeA")
}
if ind.OffsetW < 0 {
return onError("Syevx: OffsetW")
}
sizeW := W.NumElements()
if sizeW < ind.OffsetW+ind.N {
return onError("Syevx: sizeW")
}
if pars.Jobz == linalg.PJobValue {
if ind.OffsetZ < 0 {
return onError("Syevx: OffsetW")
}
zrows := max(1, Z.Rows())
minZ := ind.OffsetZ + (ind.N-1)*zrows + ind.N
if pars.Range == linalg.PRangeInt {
minZ = ind.OffsetZ + (iu-il)*zrows + ind.N
}
if Z.NumElements() < minZ {
return onError("Syevx: sizeZ")
}
}
Aa := A.(*matrix.FloatMatrix).FloatArray()
Wa := W.(*matrix.FloatMatrix).FloatArray()
var Za []float64
if pars.Jobz == linalg.PJobValue {
Za = Z.(*matrix.FloatMatrix).FloatArray()
} else {
Za = nil
}
jobz := linalg.ParamString(pars.Jobz)
rnge := linalg.ParamString(pars.Range)
uplo := linalg.ParamString(pars.Uplo)
info := dsyevx(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 onError(fmt.Sprintf("Syevx: call failed %d", info))
}
return nil
}