NAG FL Interface
f08bsf (zgeqpf)

Note: this routine is deprecated. Replaced by f08btf.
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1 Purpose

f08bsf computes the QR factorization, with column pivoting, of a complex m×n matrix. f08bsf is marked as deprecated by LAPACK; the replacement routine is f08btf which makes better use of Level 3 BLAS.

2 Specification

Fortran Interface
Subroutine f08bsf ( m, n, a, lda, jpvt, tau, work, rwork, info)
Integer, Intent (In) :: m, n, lda
Integer, Intent (Inout) :: jpvt(*)
Integer, Intent (Out) :: info
Real (Kind=nag_wp), Intent (Out) :: rwork(2*n)
Complex (Kind=nag_wp), Intent (Inout) :: a(lda,*)
Complex (Kind=nag_wp), Intent (Out) :: tau(min(m,n)), work(n)
C Header Interface
#include <nag.h>
void  f08bsf_ (const Integer *m, const Integer *n, Complex a[], const Integer *lda, Integer jpvt[], Complex tau[], Complex work[], double rwork[], Integer *info)
The routine may be called by the names f08bsf, nagf_lapackeig_zgeqpf or its LAPACK name zgeqpf.

3 Description

f08bsf forms the QR factorization, with column pivoting, of an arbitrary rectangular complex m×n matrix.
If mn, the factorization is given by:
AP= Q ( R 0 ) ,  
where R is an n×n upper triangular matrix (with real diagonal elements), Q is an m×m unitary matrix and P is an n×n permutation matrix. It is sometimes more convenient to write the factorization as
AP= ( Q1 Q2 ) ( R 0 ) ,  
which reduces to
AP= Q1 R ,  
where Q1 consists of the first n columns of Q, and Q2 the remaining m-n columns.
If m<n, R is trapezoidal, and the factorization can be written
AP= Q ( R1 R2 ) ,  
where R1 is upper triangular and R2 is rectangular.
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). Routines are provided to work with Q in this representation (see Section 9).
Note also that for any k<n, the information returned in the first k columns of the array a represents a QR factorization of the first k columns of the permuted matrix AP.
The routine allows specified columns of A to be moved to the leading columns of AP at the start of the factorization and fixed there. The remaining columns are free to be interchanged so that at the ith stage the pivot column is chosen to be the column which maximizes the 2-norm of elements i to m over columns i to n.

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 A.
Constraint: m0.
2: n Integer Input
On entry: n, the number of columns of the matrix A.
Constraint: n0.
3: a(lda,*) Complex (Kind=nag_wp) array Input/Output
Note: the second dimension of the array a must be at least max(1,n).
On entry: the m×n matrix A.
On exit: if mn, the elements below the diagonal are overwritten by details of the unitary matrix Q and the upper triangle is overwritten by the corresponding elements of the n×n upper triangular matrix R.
If m<n, the strictly lower triangular part is overwritten by details of the unitary matrix Q and the remaining elements are overwritten by the corresponding elements of the m×n upper trapezoidal matrix R.
The diagonal elements of R are real.
4: lda Integer Input
On entry: the first dimension of the array a as declared in the (sub)program from which f08bsf is called.
Constraint: ldamax(1,m).
5: jpvt(*) Integer array Input/Output
Note: the dimension of the array jpvt must be at least max(1,n).
On entry: if jpvt(i)0, the i th column of A is moved to the beginning of AP before the decomposition is computed and is fixed in place during the computation. Otherwise, the i th column of A is a free column (i.e., one which may be interchanged during the computation with any other free column).
On exit: details of the permutation matrix P. More precisely, if jpvt(i)=k, the kth column of A is moved to become the i th column of AP; in other words, the columns of AP are the columns of A in the order jpvt(1),jpvt(2),,jpvt(n).
6: tau(min(m,n)) Complex (Kind=nag_wp) array Output
On exit: further details of the unitary matrix Q.
7: work(n) Complex (Kind=nag_wp) array Workspace
8: rwork(2×n) Real (Kind=nag_wp) array Workspace
9: info Integer Output
On exit: info=0 unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

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 factorization is the exact factorization of a nearby matrix (A+E), where
E2 = O(ε) A2 ,  
and ε is the machine precision.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f08bsf 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 real floating-point operations is approximately 83 n2 (3m-n) if mn or 83 m2 (3n-m) if m<n.
To form the unitary matrix Q f08bsf may be followed by a call to f08atf :
Call zungqr(m,m,min(m,n),a,lda,tau,work,lwork,info)
but note that the second dimension of the array a must be at least m, which may be larger than was required by f08bsf.
When mn, it is often only the first n columns of Q that are required, and they may be formed by the call:
Call zungqr(m,n,n,a,lda,tau,work,lwork,info)
To apply Q to an arbitrary m×p complex rectangular matrix C, f08bsf may be followed by a call to f08auf . For example,
Call zunmqr('Left','Conjugate Transpose',m,p,min(m,n),a,lda,tau, &
forms the matrix product C=QHC.
To compute a QR factorization without column pivoting, use f08asf.
The real analogue of this routine is f08bef.

10 Example

This example solves the linear least squares problems
minimizeAxi-bi2 ,   i=1,2  
where b1 and b2 are the columns of the matrix B,
A = ( 0.47-0.34i -0.40+0.54i 0.60+0.01i 0.80-1.02i -0.32-0.23i -0.05+0.20i -0.26-0.44i -0.43+0.17i 0.35-0.60i -0.52-0.34i 0.87-0.11i -0.34-0.09i 0.89+0.71i -0.45-0.45i -0.02-0.57i 1.14-0.78i -0.19+0.06i 0.11-0.85i 1.44+0.80i 0.07+1.14i )  
B = ( -0.85-1.63i 2.49+4.01i -2.16+3.52i -0.14+7.98i 4.57-5.71i 8.36-0.28i 6.38-7.40i -3.55+1.29i 8.41+9.39i -6.72+5.03i ) .  
Here A is approximately rank-deficient, and hence it is preferable to use f08bsf rather than f08asf.

10.1 Program Text

Program Text (f08bsfe.f90)

10.2 Program Data

Program Data (f08bsfe.d)

10.3 Program Results

Program Results (f08bsfe.r)