nag_dsygst (f08sec) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_dsygst (f08sec)

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_dsygst (f08sec) reduces a real symmetric-definite generalized eigenproblem Az=λBz, ABz=λz or BAz=λz to the standard form Cy=λy, where A is a real symmetric matrix and B has been factorized by nag_dpotrf (f07fdc).

2  Specification

#include <nag.h>
#include <nagf08.h>
void  nag_dsygst (Nag_OrderType order, Nag_ComputeType comp_type, Nag_UploType uplo, Integer n, double a[], Integer pda, const double b[], Integer pdb, NagError *fail)

3  Description

To reduce the real symmetric-definite generalized eigenproblem Az=λBz, ABz=λz or BAz=λz to the standard form Cy=λy, nag_dsygst (f08sec) must be preceded by a call to nag_dpotrf (f07fdc) which computes the Cholesky factorization of B; B must be positive definite.
The different problem types are specified by the argument comp_type, as indicated in the table below. The table shows how C is computed by the function, and also how the eigenvectors z of the original problem can be recovered from the eigenvectors of the standard form.
  order=Nag_ColMajor order=Nag_RowMajor
comp_type Problem uplo B C z B C z
1 Az=λBz Nag_Upper 
Nag_Lower
UTU 
LLT
U-TAU-1 
L-1AL-T
U-1y 
L-Ty
UUT 
LTL
U-1AU-T 
L-TAL-1
U-Ty 
L-1y
2 ABz=λz Nag_Upper 
Nag_Lower
UTU 
LLT
UAUT 
LTAL
U-1y 
L-Ty
UUT 
LTL
UTAU 
LALT
U-Ty 
L-1y
3 BAz=λz Nag_Upper 
Nag_Lower
UTU 
LLT
UAUT 
LTAL
UTy 
Ly
UUT 
LTL
UTAU 
LALT
Uy 
LTy

4  References

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 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     comp_type Nag_ComputeTypeInput
On entry: indicates how the standard form is computed.
comp_type=Nag_Compute_1
  • if uplo=Nag_Upper, C=U-TAU-1 when order=Nag_ColMajor and C=U-1AU-T when order=Nag_RowMajor;
  • if uplo=Nag_Lower, C=L-1AL-T when order=Nag_ColMajor and C=L-TAL-1 when order=Nag_RowMajor.
comp_type=Nag_Compute_2 or Nag_Compute_3
  • if uplo=Nag_Upper, C=UAUT when order=Nag_ColMajor and C=UTAU when order=Nag_RowMajor;
  • if uplo=Nag_Lower, C=LTAL when order=Nag_ColMajor and C=LALT when order=Nag_RowMajor.
Constraint: comp_type=Nag_Compute_1, Nag_Compute_2 or Nag_Compute_3.
3:     uplo Nag_UploTypeInput
On entry: indicates whether the upper or lower triangular part of A is stored and how B has been factorized.
uplo=Nag_Upper
The upper triangular part of A is stored and B=UTU when order=Nag_ColMajor and B=UUT when order=Nag_RowMajor.
uplo=Nag_Lower
The lower triangular part of A is stored and B=LLT when order=Nag_ColMajor and B=LTL when order=Nag_RowMajor.
Constraint: uplo=Nag_Upper or Nag_Lower.
4:     n IntegerInput
On entry: n, the order of the matrices A and B.
Constraint: n0.
5:     a[dim] doubleInput/Output
Note: the dimension, dim, of the array a must be at least max1,pda×n.
On entry: the n by n symmetric matrix A.
If order=Nag_ColMajor, Aij is stored in a[j-1×pda+i-1].
If order=Nag_RowMajor, Aij is stored in a[i-1×pda+j-1].
If uplo=Nag_Upper, the upper triangular part of A must be stored and the elements of the array below the diagonal are not referenced.
If uplo=Nag_Lower, the lower triangular part of A must be stored and the elements of the array above the diagonal are not referenced.
On exit: the upper or lower triangle of a is overwritten by the corresponding upper or lower triangle of C as specified by comp_type and uplo.
6:     pda IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) of the matrix A in the array a.
Constraint: pdamax1,n.
7:     b[dim] const doubleInput
Note: the dimension, dim, of the array b must be at least max1,pdb×n.
On entry: the Cholesky factor of B as specified by uplo and returned by nag_dpotrf (f07fdc).
8:     pdb IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) of the matrix B in the array b.
Constraint: pdbmax1,n.
9:     fail NagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.2.1.2 in the Essential Introduction for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INT
On entry, n=value.
Constraint: n0.
On entry, pda=value.
Constraint: pda>0.
On entry, pdb=value.
Constraint: pdb>0.
NE_INT_2
On entry, pda=value and n=value.
Constraint: pdamax1,n.
On entry, pdb=value and n=value.
Constraint: pdbmax1,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.
An unexpected error has been triggered by this function. Please contact NAG.
See Section 3.6.6 in the Essential Introduction for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 3.6.5 in the Essential Introduction for further information.

7  Accuracy

Forming the reduced matrix C is a stable procedure. However it involves implicit multiplication by B-1 (if comp_type=Nag_Compute_1) or B (if comp_type=Nag_Compute_2 or Nag_Compute_3). When nag_dsygst (f08sec) is used as a step in the computation of eigenvalues and eigenvectors of the original problem, there may be a significant loss of accuracy if B is ill-conditioned with respect to inversion.

8  Parallelism and Performance

nag_dsygst (f08sec) is not threaded by NAG in any implementation.
nag_dsygst (f08sec) 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 n3.
The complex analogue of this function is nag_zhegst (f08ssc).

10  Example

This example computes all the eigenvalues of Az=λBz, where
A = 0.24 0.39 0.42 -0.16 0.39 -0.11 0.79 0.63 0.42 0.79 -0.25 0.48 -0.16 0.63 0.48 -0.03   and   B= 4.16 -3.12 0.56 -0.10 -3.12 5.03 -0.83 1.09 0.56 -0.83 0.76 0.34 -0.10 1.09 0.34 1.18 .  
Here B is symmetric positive definite and must first be factorized by nag_dpotrf (f07fdc). The program calls nag_dsygst (f08sec) to reduce the problem to the standard form Cy=λy; then nag_dsytrd (f08fec) to reduce C to tridiagonal form, and nag_dsterf (f08jfc) to compute the eigenvalues.

10.1  Program Text

Program Text (f08sece.c)

10.2  Program Data

Program Data (f08sece.d)

10.3  Program Results

Program Results (f08sece.r)


nag_dsygst (f08sec) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2015