f08cv: FL CL CPP AD

NAG CL Interface
f08cvc (zgerqf)

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NAG Library Manual, Mark 28.3

Interfaces: FL CL CPP AD

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F08 (Lapackeig) Chapter Contents

F08 (Lapackeig) Chapter Introduction

f08cv: FL CL CPP AD

▸▿ 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

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1 Purpose

f08cvc computes an

R Q

factorization of a complex

m \times n

matrix

A

2 Specification

#include <nag.h>

void	f08cvc (Nag_OrderType order, Integer m, Integer n, Complex a[], Integer pda, Complex tau[], NagError *fail)

The function may be called by the names: f08cvc, nag_lapackeig_zgerqf or nag_zgerqf.

3 Description

f08cvc forms the

R Q

factorization of an arbitrary rectangular real

m \times n

matrix. If

m \leq n

, the factorization is given by

A = (\begin{matrix} 0 & R \end{matrix}) Q,

where

R

is an

m \times m

lower triangular matrix and

Q

is an

n \times n

unitary matrix. If

m > n

the factorization is given by

A = R Q,

where

R

is an

m \times n

upper trapezoidal matrix and

Q

is again an

n \times n

unitary matrix. In the case where

m < n

the factorization can be expressed as

A = (\begin{matrix} 0 & R \end{matrix}) (\begin{matrix} Q_{1} \\ Q_{2} \end{matrix}) = R Q_{2},

where

Q_{1}

consists of the first

(n - m)

rows of

Q

and

Q_{2}

the remaining

m

rows.

The matrix

Q

is not formed explicitly, but is represented as a product of

\min (m, n)

elementary reflectors (see the F08 Chapter Introduction for details). Functions are provided to work with

Q

in this representation (see Section 9).

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 https://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_OrderType Input

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 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: $m$ – Integer Input

On entry:

m

, the number of rows of the matrix

A

Constraint:

m \geq 0

3: $n$ – Integer Input

On entry:

n

, the number of columns of the matrix

A

Constraint:

n \geq 0

4: $a [\dim]$ – Complex Input/Output

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

$\max (1, pda \times n)$ when $order = Nag_ColMajor$ ;
$\max (1, m \times pda)$ when $order = Nag_RowMajor$ .

where

A (i, j)

appears in this document, it refers to the array element

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

On entry: the

m \times n

matrix

A

On exit: if

m \leq n

, the upper triangle of the subarray

A (1 : m, n - m + 1 : n)

contains the

m \times m

upper triangular matrix

R

m \geq n

, the elements on and above the

(m - n)

th subdiagonal contain the

m \times n

upper trapezoidal matrix

R

; the remaining elements, with the array tau, represent the unitary matrix

Q

as a product of

\min (m, n)

elementary reflectors (see Section 3.4.6 in the F08 Chapter Introduction).

5: $pda$ – Integer Input

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

Constraints:

if $order = Nag_ColMajor$ , $pda \geq \max (1, m)$ ;
if $order = Nag_RowMajor$ , $pda \geq \max (1, n)$ .

6: $tau [\dim]$ – Complex Output

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

\max (1, \min (m, n))

On exit: the scalar factors of the elementary reflectors.

7: $fail$ – NagError * Input/Output

The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_INT: On entry, $m = ⟨ value ⟩$ .
Constraint: $m \geq 0$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .

On entry, $pda = ⟨ value ⟩$ .
Constraint: $pda > 0$ .
NE_INT_2: On entry, $pda = ⟨ value ⟩$ and $m = ⟨ value ⟩$ .
Constraint: $pda \geq \max (1, m)$ .

On entry, $pda = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $pda \geq \max (1, n)$ .
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.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.

7 Accuracy

The computed factorization is the exact factorization of a nearby matrix

A + E

, where

{‖ E ‖}_{2} = O ε {‖ A ‖}_{2}

and

ε

is the machine precision.

8 Parallelism and Performance

f08cvc 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 function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The total number of floating-point operations is approximately

\frac{2}{3} m^{2} (3 n - m)

m \leq n

, or

\frac{2}{3} n^{2} (3 m - n)

m > n

To form the unitary matrix

Q

f08cvc may be followed by a call to f08cwc :

nag_lapackeig_zungrq(order, n, n, minmn, a, pda, tau, &fail)

where

minmn = \min (m, n)

, but note that the first dimension of the array a must be at least n, which may be larger than was required by f08cvc. When

m \leq n

, it is often only the first

m

rows of

Q

that are required and they may be formed by the call:

nag_lapackeig_zungrq(order, m, n, m, a, pda, tau, c, pdc, &fail)

To apply

Q

to an arbitrary

n \times p

real rectangular matrix

C

, f08cvc may be followed by a call to f08cxc . For example:

nag_lapackeig_zunmrq(Nag_LeftSide, Nag_ConjTrans, n, p, minmn, a, pda, tau, c, pdc, &fail)

forms the matrix product

C = Q^{H} C

The real analogue of this function is f08chc.

10 Example

This example finds the minimum norm solution to the underdetermined equations

A x = b

where

A = (\begin{array}{r} 0.28 - 0.36 i & 0.50 - 0.86 i & - 0.77 - 0.48 i & 1.58 + 0.66 i \\ - 0.50 - 1.10 i & - 1.21 + 0.76 i & - 0.32 - 0.24 i & - 0.27 - 1.15 i \\ 0.36 - 0.51 i & - 0.07 + 1.33 i & - 0.75 + 0.47 i & - 0.08 + 1.01 i \end{array})

and

b = (\begin{array}{r} - 1.35 + 0.19 i \\ 9.41 - 3.56 i \\ - 7.57 + 6.93 i \end{array}) .

The solution is obtained by first obtaining an

R Q

factorization of the matrix

A

f08cv: FL CL CPP AD

NAG CL Interfacef08cvc (zgerqf)

▸▿ 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 CL Interface
f08cvc (zgerqf)