NAG Library Function Document

nag_ztgsja (f08ysc)

 Contents

    1  Purpose
    7  Accuracy

1
Purpose

nag_ztgsja (f08ysc) computes the generalized singular value decomposition (GSVD) of two complex upper trapezoidal matrices A and B, where A is an m by n matrix and B is a p by n matrix.
A and B are assumed to be in the form returned by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc).

2
Specification

#include <nag.h>
#include <nagf08.h>
void  nag_ztgsja (Nag_OrderType order, Nag_ComputeUType jobu, Nag_ComputeVType jobv, Nag_ComputeQType jobq, Integer m, Integer p, Integer n, Integer k, Integer l, Complex a[], Integer pda, Complex b[], Integer pdb, double tola, double tolb, double alpha[], double beta[], Complex u[], Integer pdu, Complex v[], Integer pdv, Complex q[], Integer pdq, Integer *ncycle, NagError *fail)

3
Description

nag_ztgsja (f08ysc) computes the GSVD of the matrices A and B which are assumed to have the form as returned by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc)
A= n-k-lklk0A12A13l00A23m-k-l000() ,   if ​ m-k-l 0; n-k-lklk0A12A13m-k00A23() ,   if ​ m-k-l < 0 ; B= n-k-lkll00B13p-l000() ,  
where the k by k matrix A12 and the l by l matrix B13 are nonsingular upper triangular, A23 is l by l upper triangular if m-k-l0 and is m-k by l upper trapezoidal otherwise.
nag_ztgsja (f08ysc) computes unitary matrices Q, U and V, diagonal matrices D1 and D2, and an upper triangular matrix R such that
UHAQ = D1 0 R ,   VHBQ = D2 0 R .  
Optionally Q, U and V may or may not be computed, or they may be premultiplied by matrices Q1, U1 and V1 respectively.
If m-k-l0 then D1, D2 and R have the form
D1= klkI0l0Cm-k-l00() ,  
D2= kll0Sp-l00() ,  
R = klkR11R12l0R22() ,  
where C=diagαk+1,,,,,,αk+l,  S=diagβk+1,,,,,,βk+l.
If m-k-l<0 then D1, D2 and R have the form
D1= km-kk+l-mkI00m-k0C0() ,  
D2= km-kk+l-mm-k0S0k+l-m00Ip-l000() ,  
R = km-kk+l-mkR11R12R13m-k0R22R23k+l-m00R33() ,  
where C=diagαk+1,,,,,,αm,  S=diagβk+1,,,,,,βm.
In both cases the diagonal matrix C has real non-negative diagonal elements, the diagonal matrix S has real positive diagonal elements, so that S is nonsingular, and C2+S2=1. See Section 2.3.5.3 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 3.3.1.3 in How to Use the NAG Library and its Documentation for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     jobu Nag_ComputeUTypeInput
On entry: if jobu=Nag_AllU, u must contain a unitary matrix U1 on entry, and the product U1U is returned.
If jobu=Nag_InitU, u is initialized to the unit matrix, and the unitary matrix U is returned.
If jobu=Nag_NotU, U is not computed.
Constraint: jobu=Nag_AllU, Nag_InitU or Nag_NotU.
3:     jobv Nag_ComputeVTypeInput
On entry: if jobv=Nag_ComputeV, v must contain a unitary matrix V1 on entry, and the product V1V is returned.
If jobv=Nag_InitV, v is initialized to the unit matrix, and the unitary matrix V is returned.
If jobv=Nag_NotV, V is not computed.
Constraint: jobv=Nag_ComputeV, Nag_InitV or Nag_NotV.
4:     jobq Nag_ComputeQTypeInput
On entry: if jobq=Nag_ComputeQ, q must contain a unitary matrix Q1 on entry, and the product Q1Q is returned.
If jobq=Nag_InitQ, q is initialized to the unit matrix, and the unitary matrix Q is returned.
If jobq=Nag_NotQ, Q is not computed.
Constraint: jobq=Nag_ComputeQ, Nag_InitQ or Nag_NotQ.
5:     m IntegerInput
On entry: m, the number of rows of the matrix A.
Constraint: m0.
6:     p IntegerInput
On entry: p, the number of rows of the matrix B.
Constraint: p0.
7:     n IntegerInput
On entry: n, the number of columns of the matrices A and B.
Constraint: n0.
8:     k IntegerInput
9:     l IntegerInput
On entry: k and l specify the sizes, k and l, of the subblocks of A and B, whose GSVD is to be computed by nag_ztgsja (f08ysc).
10:   a[dim] ComplexInput/Output
Note: the dimension, dim, of the array a must be at least
  • max1,pda×n when order=Nag_ColMajor;
  • max1,m×pda when order=Nag_RowMajor.
Where Ai,j appears in this document, it refers to the array element
  • a[j-1×pda+i-1] when order=Nag_ColMajor;
  • a[i-1×pda+j-1] when order=Nag_RowMajor.
On entry: the m by n matrix A.
On exit: if m-k-l0, A1:k+l,n-k-l+1:n  contains the k+l by k+l upper triangular matrix R.
If m-k-l<0, A1:m,n-k-l+1:n  contains the first m rows of the k+l by k+l upper triangular matrix R, and the submatrix R33 is returned in Bm-k+1:l,n+m-k-l+1:n .
11:   pda IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraints:
  • if order=Nag_ColMajor, pdamax1,m;
  • if order=Nag_RowMajor, pdamax1,n.
12:   b[dim] ComplexInput/Output
Note: the dimension, dim, of the array b must be at least
  • max1,pdb×n when order=Nag_ColMajor;
  • max1,p×pdb when order=Nag_RowMajor.
Where Bi,j appears in this document, it refers to the array element
  • b[j-1×pdb+i-1] when order=Nag_ColMajor;
  • b[i-1×pdb+j-1] when order=Nag_RowMajor.
On entry: the p by n matrix B.
On exit: if m-k-l<0 , Bm-k+1:l,n+m-k-l+1:n  contains the submatrix R33 of R.
13:   pdb IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraints:
  • if order=Nag_ColMajor, pdbmax1,p;
  • if order=Nag_RowMajor, pdbmax1,n.
14:   tola doubleInput
15:   tolb doubleInput
On entry: tola and tolb are the convergence criteria for the Jacobi–Kogbetliantz iteration procedure. Generally, they should be the same as used in the preprocessing step performed by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc), say
tola=maxm,nAε, tolb=maxp,nBε,  
where ε  is the machine precision.
16:   alpha[n] doubleOutput
On exit: see the description of beta.
17:   beta[n] doubleOutput
On exit: alpha and beta contain the generalized singular value pairs of A and B;
  • alpha[i]=1 , beta[i]=0 , for i=0,1,,k-1, and
  • if m-k-l0 , alpha[i]=αi , beta[i]=βi , for i=k,,k+l-1, or
  • if m-k-l<0 , alpha[i]=αi , beta[i]=βi , for i=k,,m-1 and alpha[i]=0 , beta[i]=1 , for i=m,,k+l-1.
Furthermore, if k+l<n, alpha[i]= beta[i]=0 , for i=k+l,,n-1.
18:   u[dim] ComplexInput/Output
Note: the dimension, dim, of the array u must be at least
  • max1,pdu×m when jobu=Nag_AllU or Nag_InitU;
  • 1 otherwise.
The i,jth element of the matrix U is stored in
  • u[j-1×pdu+i-1] when order=Nag_ColMajor;
  • u[i-1×pdu+j-1] when order=Nag_RowMajor.
On entry: if jobu=Nag_AllU, u must contain an m by m matrix U1 (usually the unitary matrix returned by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc)).
On exit: if jobu=Nag_AllU, u contains the product U1U.
If jobu=Nag_InitU, u contains the unitary matrix U.
If jobu=Nag_NotU, u is not referenced.
19:   pdu IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array u.
Constraints:
  • if jobu=Nag_AllU or Nag_InitU, pdu max1,m ;
  • otherwise pdu1.
20:   v[dim] ComplexInput/Output
Note: the dimension, dim, of the array v must be at least
  • max1,pdv×p when jobv=Nag_ComputeV or Nag_InitV;
  • 1 otherwise.
The i,jth element of the matrix V is stored in
  • v[j-1×pdv+i-1] when order=Nag_ColMajor;
  • v[i-1×pdv+j-1] when order=Nag_RowMajor.
On entry: if jobv=Nag_ComputeV, v must contain an p by p matrix V1 (usually the unitary matrix returned by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc)).
On exit: if jobv=Nag_InitV, v contains the unitary matrix V.
If jobv=Nag_ComputeV, v contains the product V1V.
If jobv=Nag_NotV, v is not referenced.
21:   pdv IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array v.
Constraints:
  • if jobv=Nag_ComputeV or Nag_InitV, pdv max1,p ;
  • otherwise pdv1.
22:   q[dim] ComplexInput/Output
Note: the dimension, dim, of the array q must be at least
  • max1,pdq×n when jobq=Nag_ComputeQ or Nag_InitQ;
  • 1 otherwise.
The i,jth element of the matrix Q is stored in
  • q[j-1×pdq+i-1] when order=Nag_ColMajor;
  • q[i-1×pdq+j-1] when order=Nag_RowMajor.
On entry: if jobq=Nag_ComputeQ, q must contain an n by n matrix Q1 (usually the unitary matrix returned by nag_zggsvp (f08vsc) or nag_zggsvp3 (f08vuc)).
On exit: if jobq=Nag_InitQ, q contains the unitary matrix Q.
If jobq=Nag_ComputeQ, q contains the product Q1Q.
If jobq=Nag_NotQ, q is not referenced.
23:   pdq IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array q.
Constraints:
  • if jobq=Nag_ComputeQ or Nag_InitQ, pdq max1,n ;
  • otherwise pdq1.
24:   ncycle Integer *Output
On exit: the number of cycles required for convergence.
25:   fail NagError *Input/Output
The NAG error argument (see Section 3.7 in How to Use the NAG Library and its Documentation).

6
Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_CONVERGENCE
The procedure does not converge after 40 cycles.
NE_ENUM_INT_2
On entry, jobq=value, pdq=value and n=value.
Constraint: if jobq=Nag_ComputeQ or Nag_InitQ, pdq max1,n ;
otherwise pdq1.
On entry, jobu=value, pdu=value and m=value.
Constraint: if jobu=Nag_AllU or Nag_InitU, pdu max1,m ;
otherwise pdu1.
On entry, jobv=value, pdv=value and p=value.
Constraint: if jobv=Nag_ComputeV or Nag_InitV, pdv max1,p ;
otherwise pdv1.
NE_INT
On entry, m=value.
Constraint: m0.
On entry, n=value.
Constraint: n0.
On entry, p=value.
Constraint: p0.
On entry, pda=value.
Constraint: pda>0.
On entry, pdb=value.
Constraint: pdb>0.
On entry, pdq=value.
Constraint: pdq>0.
On entry, pdu=value.
Constraint: pdu>0.
On entry, pdv=value.
Constraint: pdv>0.
NE_INT_2
On entry, pda=value and m=value.
Constraint: pdamax1,m.
On entry, pda=value and n=value.
Constraint: pdamax1,n.
On entry, pdb=value and n=value.
Constraint: pdbmax1,n.
On entry, pdb=value and p=value.
Constraint: pdbmax1,p.
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 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.

7
Accuracy

The computed generalized singular value decomposition is nearly the exact generalized singular value decomposition for nearby matrices A+E and B+F, where
E2 = Oε A2   and   F2= Oε B2 ,  
and ε is the machine precision. See Section 4.12 of Anderson et al. (1999) for further details.

8
Parallelism and Performance

nag_ztgsja (f08ysc) 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 real analogue of this function is nag_dtgsja (f08yec).

10
Example

This example finds the generalized singular value decomposition
A = UΣ1 0 R QH ,   B= VΣ2 0 R QH ,  
of the matrix pair A,B, where
A = 0.96-0.81i -0.03+0.96i -0.91+2.06i -0.05+0.41i -0.98+1.98i -1.20+0.19i -0.66+0.42i -0.81+0.56i 0.62-0.46i 1.01+0.02i 0.63-0.17i -1.11+0.60i 0.37+0.38i 0.19-0.54i -0.98-0.36i 0.22-0.20i 0.83+0.51i 0.20+0.01i -0.17-0.46i 1.47+1.59i 1.08-0.28i 0.20-0.12i -0.07+1.23i 0.26+0.26i  
and
B = 1 0 -1 0 0 1 0 -1 .  

10.1
Program Text

Program Text (f08ysce.c)

10.2
Program Data

Program Data (f08ysce.d)

10.3
Program Results

Program Results (f08ysce.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017