Integer, Intent (In)	::	n, nrhs, ldb, ldx
Integer, Intent (Out)	::	info
Real (Kind=nag_wp), Intent (Out)	::	ferr(nrhs), berr(nrhs), rwork(n)
Complex (Kind=nag_wp), Intent (In)	::	ap(), b(ldb,), x(ldx,*)
Complex (Kind=nag_wp), Intent (Out)	::	work(2*n)
Character (1), Intent (In)	::	uplo, trans, diag

C Header Interface

#include <nag.h>

void

f07uvf_ (const char *uplo, const char *trans, const char *diag, const Integer *n, const Integer *nrhs, const Complex ap[], const Complex b[], const Integer *ldb, const Complex x[], const Integer *ldx, double ferr[], double berr[], Complex work[], double rwork[], Integer *info, const Charlen length_uplo, const Charlen length_trans, const Charlen length_diag)

The routine may be called by the names f07uvf, nagf_lapacklin_ztprfs or its LAPACK name ztprfs.

3 Description

f07uvf returns the backward errors and estimated bounds on the forward errors for the solution of a complex triangular system of linear equations with multiple right-hand sides

A X = B

A^{T} X = B

A^{H} X = B

, using packed storage. The routine handles each right-hand side vector (stored as a column of the matrix

B

) independently, so we describe the function of f07uvf in terms of a single right-hand side

b

and solution

x

Given a computed solution

x

, the routine computes the component-wise backward error

β

. This is the size of the smallest relative perturbation in each element of

A

and

b

such that

x

is the exact solution of a perturbed system

\begin{matrix} (A + δ A) x = b + δ b \\ | δ a_{i j} | \leq β | a_{i j} | and | δ b_{i} | \leq β | b_{i} | . \end{matrix}

Then the routine estimates a bound for the component-wise forward error in the computed solution, defined by:

\max_{i} | x_{i} - {\hat{x}}_{i} | / \max_{i} | x_{i} |

where

\hat{x}

is the true solution.

For details of the method, see the F07 Chapter Introduction.

4 References

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

5 Arguments

1: $uplo$ – Character(1) Input

On entry: specifies whether

A

is upper or lower triangular.

$uplo ='U'$: $A$ is upper triangular.
$uplo ='L'$: $A$ is lower triangular.

Constraint:

uplo ='U'

'L'

2: $trans$ – Character(1) Input

On entry: indicates the form of the equations.

$trans ='N'$: The equations are of the form $A X = B$ .
$trans ='T'$: The equations are of the form $A^{T} X = B$ .
$trans ='C'$: The equations are of the form $A^{H} X = B$ .

Constraint:

trans ='N'

'T'

'C'

3: $diag$ – Character(1) Input

On entry: indicates whether

A

is a nonunit or unit triangular matrix.

$diag ='N'$: $A$ is a nonunit triangular matrix.
$diag ='U'$: $A$ is a unit triangular matrix; the diagonal elements are not referenced and are assumed to be $1$ .

Constraint:

diag ='N'

'U'

4: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

5: $nrhs$ – Integer Input

On entry:

r

, the number of right-hand sides.

Constraint:

nrhs \geq 0

6: $ap (*)$ – Complex (Kind=nag_wp) array Input

Note: the dimension of the array ap must be at least

\max (1, n \times (n + 1) / 2)

On entry: the

n \times n

triangular matrix

A

, packed by columns.

More precisely,

if $uplo ='U'$ , the upper triangle of $A$ must be stored with element $A_{i j}$ in $ap (i + j (j - 1) / 2)$ for $i \leq j$ ;
if $uplo ='L'$ , the lower triangle of $A$ must be stored with element $A_{i j}$ in $ap (i + (2 n - j) (j - 1) / 2)$ for $i \geq j$ .

diag ='U'

, the diagonal elements of

A

are assumed to be

1

, and are not referenced; the same storage scheme is used whether

diag ='N'

or ‘U’.

7: $b (ldb, *)$ – Complex (Kind=nag_wp) array Input

Note: the second dimension of the array b must be at least

\max (1, nrhs)

On entry: the

n \times r

right-hand side matrix

B

8: $ldb$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which f07uvf is called.

Constraint:

ldb \geq \max (1, n)

9: $x (ldx, *)$ – Complex (Kind=nag_wp) array Input

Note: the second dimension of the array x must be at least

\max (1, nrhs)

On entry: the

n \times r

solution matrix

X

, as returned by f07usf.

10: $ldx$ – Integer Input

On entry: the first dimension of the array x as declared in the (sub)program from which f07uvf is called.

Constraint:

ldx \geq \max (1, n)

11: $ferr (nrhs)$ – Real (Kind=nag_wp) array Output

On exit:

ferr (j)

contains an estimated error bound for the

j

th solution vector, that is, the

j

th column of

X

, for

j = 1, 2, \dots, r

12: $berr (nrhs)$ – Real (Kind=nag_wp) array Output

On exit:

berr (j)

contains the component-wise backward error bound

β

for the

j

th solution vector, that is, the

j

th column of

X

, for

j = 1, 2, \dots, r

13: $work (2 \times n)$ – Complex (Kind=nag_wp) array Workspace

14: $rwork (n)$ – Real (Kind=nag_wp) array Workspace

15: $info$ – Integer Output

On exit:

info = 0

unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

$info < 0$: If $info = - i$ , argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.

7 Accuracy

The bounds returned in ferr are not rigorous, because they are estimated, not computed exactly; but in practice they almost always overestimate the actual error.

8 Parallelism and Performance

f07uvf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f07uvf 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 X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

A call to f07uvf, for each right-hand side, involves solving a number of systems of linear equations of the form

A x = b

A^{H} x = b

; the number is usually

5

and never more than

11

. Each solution involves approximately

4 n^{2}

real floating-point operations.

The real analogue of this routine is f07uhf.

10 Example

This example solves the system of equations

A X = B

and to compute forward and backward error bounds, where

A = (\begin{array}{r} 4.78 + 4.56 i & 0.00 + 0.00 i & 0.00 + 0.00 i & 0.00 + 0.00 i \\ 2.00 - 0.30 i & - 4.11 + 1.25 i & 0.00 + 0.00 i & 0.00 + 0.00 i \\ 2.89 - 1.34 i & 2.36 - 4.25 i & 4.15 + 0.80 i & 0.00 + 0.00 i \\ - 1.89 + 1.15 i & 0.04 - 3.69 i & - 0.02 + 0.46 i & 0.33 - 0.26 i \end{array})

and

B = (\begin{array}{r} - 14.78 - 32.36 i & - 18.02 + 28.46 i \\ 2.98 - 2.14 i & 14.22 + 15.42 i \\ - 20.96 + 17.06 i & 5.62 + 35.89 i \\ 9.54 + 9.91 i & - 16.46 - 1.73 i \end{array}),

using packed storage for

A

f07uv: FL CL CPP AD

NAG FL Interfacef07uvf (ztprfs)

▸▿ 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 FL Interface
f07uvf (ztprfs)