NAG FL Interface
f08ajf (dorglq)

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1 Purpose

f08ajf generates all or part of the real orthogonal matrix Q from an LQ factorization computed by f08ahf.

2 Specification

Fortran Interface
Subroutine f08ajf ( m, n, k, a, lda, tau, work, lwork, info)
Integer, Intent (In) :: m, n, k, lda, lwork
Integer, Intent (Out) :: info
Real (Kind=nag_wp), Intent (In) :: tau(*)
Real (Kind=nag_wp), Intent (Inout) :: a(lda,*)
Real (Kind=nag_wp), Intent (Out) :: work(max(1,lwork))
C Header Interface
#include <nag.h>
void  f08ajf_ (const Integer *m, const Integer *n, const Integer *k, double a[], const Integer *lda, const double tau[], double work[], const Integer *lwork, Integer *info)
The routine may be called by the names f08ajf, nagf_lapackeig_dorglq or its LAPACK name dorglq.

3 Description

f08ajf is intended to be used after a call to f08ahf, which performs an LQ factorization of a real matrix A. The orthogonal matrix Q is represented as a product of elementary reflectors.
This routine may be used to generate Q explicitly as a square matrix, or to form only its leading rows.
Usually Q is determined from the LQ factorization of a p×n matrix A with pn. The whole of Q may be computed by :
Call dorglq(n,n,p,a,lda,tau,work,lwork,info)
(note that the array a must have at least n rows) or its leading p rows by :
Call dorglq(p,n,p,a,lda,tau,work,lwork,info)
The rows of Q returned by the last call form an orthonormal basis for the space spanned by the rows of A; thus f08ahf followed by f08ajf can be used to orthogonalize the rows of A.
The information returned by the LQ factorization routines also yields the LQ factorization of the leading k rows of A, where k<p. The orthogonal matrix arising from this factorization can be computed by :
Call dorglq(n,n,k,a,lda,tau,work,lwork,info)
or its leading k rows by :
Call dorglq(k,n,k,a,lda,tau,work,lwork,info)

4 References

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

5 Arguments

1: m Integer Input
On entry: m, the number of rows of the matrix Q.
Constraint: m0.
2: n Integer Input
On entry: n, the number of columns of the matrix Q.
Constraint: nm.
3: k Integer Input
On entry: k, the number of elementary reflectors whose product defines the matrix Q.
Constraint: mk0.
4: a(lda,*) Real (Kind=nag_wp) array Input/Output
Note: the second dimension of the array a must be at least max(1,n).
On entry: details of the vectors which define the elementary reflectors, as returned by f08ahf.
On exit: the m×n matrix Q.
5: lda Integer Input
On entry: the first dimension of the array a as declared in the (sub)program from which f08ajf is called.
Constraint: ldamax(1,m).
6: tau(*) Real (Kind=nag_wp) array Input
Note: the dimension of the array tau must be at least max(1,k).
On entry: further details of the elementary reflectors, as returned by f08ahf.
7: work(max(1,lwork)) Real (Kind=nag_wp) array Workspace
On exit: if info=0, work(1) contains the minimum value of lwork required for optimal performance.
8: lwork Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f08ajf is called.
If lwork=−1, a workspace query is assumed; the routine only calculates the optimal size of the work array, returns this value as the first entry of the work array, and no error message related to lwork is issued.
Suggested value: for optimal performance, lworkm×nb, where nb is the optimal block size.
Constraint: lworkmax(1,m) or lwork=−1.
9: 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 computed matrix Q differs from an exactly orthogonal matrix by a matrix E such that
E2 = O(ε) ,  
where ε is the machine precision.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f08ajf 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

The total number of floating-point operations is approximately 4mnk-2 (m+n) k2 + 43 k3 ; when m=k, the number is approximately 23 m2 (3n-m) .
The complex analogue of this routine is f08awf.

10 Example

This example forms the leading 4 rows of the orthogonal matrix Q from the LQ factorization of the matrix A, where
A = ( -5.42 3.28 -3.68 0.27 2.06 0.46 -1.65 -3.40 -3.20 -1.03 -4.06 -0.01 -0.37 2.35 1.90 4.31 -1.76 1.13 -3.15 -0.11 1.99 -2.70 0.26 4.50 ) .  
The rows of Q form an orthonormal basis for the space spanned by the rows of A.

10.1 Program Text

Program Text (f08ajfe.f90)

10.2 Program Data

Program Data (f08ajfe.d)

10.3 Program Results

Program Results (f08ajfe.r)