NAG Library Function Document

nag_zggesx (f08xpc)

Nag_RCondType sense, Integer n, Complex a[], Integer pda, Complex b[], Integer pdb, Integer *sdim, Complex alpha[], Complex beta[], Complex vsl[], Integer pdvsl, Complex vsr[], Integer pdvsr, double rconde[], double rcondv[], NagError *fail)

3 Description

The generalized Schur factorization for a pair of complex matrices

(A, B)

is given by

A = Q S Z^{H}, B = Q T Z^{H},

where

Q

and

Z

are unitary,

T

and

S

are upper triangular. The generalized eigenvalues,

λ

, of

(A, B)

are computed from the diagonals of

T

and

S

and satisfy

A z = λ B z,

where

z

is the corresponding generalized eigenvector.

λ

is actually returned as the pair

(α, β)

such that

λ = α / β

since

β

, or even both

α

and

β

can be zero. The columns of

Q

and

Z

are the left and right generalized Schur vectors of

(A, B)

Optionally, nag_zggesx (f08xpc) can order the generalized eigenvalues on the diagonals of

(S, T)

so that selected eigenvalues are at the top left. The leading columns of

Q

and

Z

then form an orthonormal basis for the corresponding eigenspaces, the deflating subspaces.

nag_zggesx (f08xpc) computes

T

to have real non-negative diagonal entries. The generalized Schur factorization, before reordering, is computed by the

Q Z

algorithm.

The reciprocals of the condition estimates, the reciprocal values of the left and right projection norms, are returned in

rconde [0]

and

rconde [1]

respectively, for the selected generalized eigenvalues, together with reciprocal condition estimates for the corresponding left and right deflating subspaces, in

rcondv [0]

and

rcondv [1]

. See Section 4.11 of Anderson et al. (1999) for further information.

4 References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug

Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5 Arguments

1: order – Nag_OrderTypeInput

On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by

order = Nag_RowMajor

. See Section 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: jobvsl – Nag_LeftVecsTypeInput

On entry: if

jobvsl = Nag_NotLeftVecs

, do not compute the left Schur vectors.

jobvsl = Nag_LeftVecs

, compute the left Schur vectors.

Constraint:

jobvsl = Nag_NotLeftVecs

Nag_LeftVecs

3: jobvsr – Nag_RightVecsTypeInput

On entry: if

jobvsr = Nag_NotRightVecs

, do not compute the right Schur vectors.

jobvsr = Nag_RightVecs

, compute the right Schur vectors.

Constraint:

jobvsr = Nag_NotRightVecs

Nag_RightVecs

4: sort – Nag_SortEigValsTypeInput

On entry: specifies whether or not to order the eigenvalues on the diagonal of the generalized Schur form.

$sort = Nag_NoSortEigVals$: Eigenvalues are not ordered.
$sort = Nag_SortEigVals$: Eigenvalues are ordered (see selctg).

Constraint:

sort = Nag_NoSortEigVals

Nag_SortEigVals

5: selctg – function, supplied by the userExternal Function

sort = Nag_SortEigVals

, selctg is used to select generalized eigenvalues to the top left of the generalized Schur form.

sort = Nag_NoSortEigVals

, selctg is not referenced by nag_zggesx (f08xpc), and may be specified as NULLFN.

The specification of selctg is:

Nag_Boolean

selctg (Complex a, Complex b)

1: a – ComplexInput
2: b – ComplexInput: On entry: an eigenvalue $a [j - 1] / b [j - 1]$ is selected if $selctg (a [j - 1], b [j - 1])$ is Nag_TRUE.
Note that in the ill-conditioned case, a selected generalized eigenvalue may no longer satisfy $selctg (a [j - 1], b [j - 1]) = Nag_TRUE$ after ordering. $fail . code =$ NE_SCHUR_REORDER_SELECT in this case.

6: sense – Nag_RCondTypeInput

On entry: determines which reciprocal condition numbers are computed.

$sense = Nag_NotRCond$: None are computed.
$sense = Nag_RCondEigVals$: Computed for average of selected eigenvalues only.
$sense = Nag_RCondEigVecs$: Computed for selected deflating subspaces only.
$sense = Nag_RCondBoth$: Computed for both.

sense = Nag_RCondEigVals

Nag_RCondEigVecs

Nag_RCondBoth

sort = Nag_SortEigVals

Constraint:

sense = Nag_NotRCond

Nag_RCondEigVals

Nag_RCondEigVecs

Nag_RCondBoth

7: n – IntegerInput

On entry:

n

, the order of the matrices

A

and

B

Constraint:

n \geq 0

8: a[ $\dim$ ] – ComplexInput/Output

Note: the dimension, dim, of the array a must be at least

\max (1, pda \times n)

The

(i, j)

th element of the matrix

A

is stored in

$a [(j - 1) \times pda + i - 1]$ when $order = Nag_ColMajor$ ;
$a [(i - 1) \times pda + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the first of the pair of matrices,

A

On exit: a has been overwritten by its generalized Schur form

S

9: pda – IntegerInput

On entry: the stride separating row or column elements (depending on the value of order) in the array a.

Constraint:

pda \geq \max (1, n)

10: b[ $\dim$ ] – ComplexInput/Output

Note: the dimension, dim, of the array b must be at least

\max (1, pdb \times n)

The

(i, j)

th element of the matrix

B

is stored in

$b [(j - 1) \times pdb + i - 1]$ when $order = Nag_ColMajor$ ;
$b [(i - 1) \times pdb + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the second of the pair of matrices,

B

On exit: b has been overwritten by its generalized Schur form

T

11: pdb – IntegerInput

On entry: the stride separating row or column elements (depending on the value of order) in the array b.

Constraint:

pdb \geq \max (1, n)

12: sdim – Integer *Output

On exit: if

sort = Nag_NoSortEigVals

sdim = 0

sort = Nag_SortEigVals

sdim =

number of eigenvalues (after sorting) for which selctg is Nag_TRUE.

13: alpha[n] – ComplexOutput

On exit: see the description of beta.

14: beta[n] – ComplexOutput

On exit:

alpha [j - 1] / beta [j - 1]

, for

j = 1, 2, \dots, n

, will be the generalized eigenvalues.

alpha [j - 1]

and

beta [j - 1], j = 1, 2, \dots, n

are the diagonals of the complex Schur form

(S, T)

beta [j - 1]

will be non-negative real.

Note: the quotients

alpha [j - 1] / beta [j - 1]

may easily overflow or underflow, and

beta [j - 1]

may even be zero. Thus, you should avoid naively computing the ratio

α / β

. However, alpha will always be less than and usually comparable with

‖a‖

in magnitude, and beta will always be less than and usually comparable with

‖b‖

15: vsl[ $\dim$ ] – ComplexOutput

Note: the dimension, dim, of the array vsl must be at least

$\max (1, pdvsl \times n)$ when $jobvsl = Nag_LeftVecs$ ;
$1$ otherwise.

The

i

th element of the

j

th vector is stored in

$vsl [(j - 1) \times pdvsl + i - 1]$ when $order = Nag_ColMajor$ ;
$vsl [(i - 1) \times pdvsl + j - 1]$ when $order = Nag_RowMajor$ .

On exit: if

jobvsl = Nag_LeftVecs

, vsl will contain the left Schur vectors,

Q

jobvsl = Nag_NotLeftVecs

, vsl is not referenced.

16: pdvsl – IntegerInput

On entry: the stride used in the array vsl.

Constraints:

if $jobvsl = Nag_LeftVecs$ , $pdvsl \geq \max (1, n)$ ;
otherwise $pdvsl \geq 1$ .

17: vsr[ $\dim$ ] – ComplexOutput

Note: the dimension, dim, of the array vsr must be at least

$\max (1, pdvsr \times n)$ when $jobvsr = Nag_RightVecs$ ;
$1$ otherwise.

The

i

th element of the

j

th vector is stored in

$vsr [(j - 1) \times pdvsr + i - 1]$ when $order = Nag_ColMajor$ ;
$vsr [(i - 1) \times pdvsr + j - 1]$ when $order = Nag_RowMajor$ .

On exit: if

jobvsr = Nag_RightVecs

, vsr will contain the right Schur vectors,

Z

jobvsr = Nag_NotRightVecs

, vsr is not referenced.

18: pdvsr – IntegerInput

On entry: the stride used in the array vsr.

Constraints:

if $jobvsr = Nag_RightVecs$ , $pdvsr \geq \max (1, n)$ ;
otherwise $pdvsr \geq 1$ .

19: rconde[ $2$ ] – doubleOutput

On exit: if

sense = Nag_RCondEigVals

Nag_RCondBoth

rconde [0]

and

rconde [1]

contain the reciprocal condition numbers for the average of the selected eigenvalues.

sense = Nag_NotRCond

Nag_RCondEigVecs

, rconde is not referenced.

20: rcondv[ $2$ ] – doubleOutput

On exit: if

sense = Nag_RCondEigVecs

Nag_RCondBoth

rcondv [0]

and

rcondv [1]

contain the reciprocal condition numbers for the selected deflating subspaces.

sense = Nag_NotRCond

Nag_RCondEigVals

, rcondv is not referenced.

21: fail – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
NE_BAD_PARAM: On entry, argument $⟨value⟩$ had an illegal value.
NE_ENUM_INT_2: On entry, $jobvsl = ⟨value⟩$ , $pdvsl = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: if $jobvsl = Nag_LeftVecs$ , $pdvsl \geq \max (1, n)$ ;
otherwise $pdvsl \geq 1$ .
On entry, $jobvsr = ⟨value⟩$ , $pdvsr = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: if $jobvsr = Nag_RightVecs$ , $pdvsr \geq \max (1, n)$ ;
otherwise $pdvsr \geq 1$ .
NE_INT: On entry, $n = ⟨value⟩$ .
Constraint: $n \geq 0$ .
On entry, $pda = ⟨value⟩$ .
Constraint: $pda > 0$ .
On entry, $pdb = ⟨value⟩$ .
Constraint: $pdb > 0$ .
On entry, $pdvsl = ⟨value⟩$ .
Constraint: $pdvsl > 0$ .
On entry, $pdvsr = ⟨value⟩$ .
Constraint: $pdvsr > 0$ .
NE_INT_2: On entry, $pda = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: $pda \geq \max (1, n)$ .
On entry, $pdb = ⟨value⟩$ and $n = ⟨value⟩$ .
Constraint: $pdb \geq \max (1, n)$ .
NE_INTERNAL_ERROR: An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
NE_ITERATION_QZ: The $Q Z$ iteration failed. $(A, B)$ are not in Schur form, but $alpha [j]$ and $beta [j]$ should be correct from element $⟨value⟩$ .
The $Q Z$ iteration failed with an unexpected error, please contact NAG.
NE_SCHUR_REORDER: The eigenvalues could not be reordered because some eigenvalues were too close to separate (the problem is very ill-conditioned).
NE_SCHUR_REORDER_SELECT: After reordering, roundoff changed values of some complex eigenvalues so that leading eigenvalues in the generalized Schur form no longer satisfy $selctg = Nag_TRUE$ . This could also be caused by underflow due to scaling.

7 Accuracy

The computed generalized Schur factorization satisfies

A + E = Q S Z^{T}, B + F = Q T Z^{T},

where

{‖(E, F)‖}_{F} = O (ε) {‖(A, B)‖}_{F}

and

ε

is the machine precision. See Section 4.11 of Anderson et al. (1999) for further details.

8 Parallelism and Performance

nag_zggesx (f08xpc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

nag_zggesx (f08xpc) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.

Please consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The total number of floating-point operations is proportional to

n^{3}

The real analogue of this function is nag_dggesx (f08xbc).

10 Example

This example finds the generalized Schur factorization of the matrix pair

(A, B)

, where

A = (\begin{array}{r} - 21.10 - 22.50 i & 53.50 - 50.50 i & - 34.50 + 127.50 i & 7.50 + 0.50 i \\ - 0.46 - 7.78 i & - 3.50 - 37.50 i & - 15.50 + 58.50 i & - 10.50 - 1.50 i \\ 4.30 - 5.50 i & 39.70 - 17.10 i & - 68.50 + 12.50 i & - 7.50 - 3.50 i \\ 5.50 + 4.40 i & 14.40 + 43.30 i & - 32.50 - 46.00 i & - 19.00 - 32.50 i \end{array})

and

B = (\begin{array}{r} 1.00 - 5.00 i & 1.60 + 1.20 i & - 3.00 + 0.00 i & 0.00 - 1.00 i \\ 0.80 - 0.60 i & 3.00 - 5.00 i & - 4.00 + 3.00 i & - 2.40 - 3.20 i \\ 1.00 + 0.00 i & 2.40 + 1.80 i & - 4.00 - 5.00 i & 0.00 - 3.00 i \\ 0.00 + 1.00 i & - 1.80 + 2.40 i & 0.00 - 4.00 i & 4.00 - 5.00 i \end{array}),

such that the eigenvalues of

(A, B)

for which

|λ| < 6

correspond to the top left diagonal elements of the generalized Schur form,

(S, T)

. Estimates of the condition numbers for the selected eigenvalue cluster and corresponding deflating subspaces are also returned.

NAG Library Function Documentnag_zggesx (f08xpc)

+− Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG Library Function Document

nag_zggesx (f08xpc)