nag_zhpgst (f08tsc) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_zhpgst (f08tsc)

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_zhpgst (f08tsc) reduces a complex Hermitian-definite generalized eigenproblem Az=λBz, ABz=λz or BAz=λz to the standard form Cy=λy, where A is a complex Hermitian matrix and B has been factorized by nag_zpptrf (f07grc), using packed storage.

2  Specification

#include <nag.h>
#include <nagf08.h>
void  nag_zhpgst (Nag_OrderType order, Nag_ComputeType comp_type, Nag_UploType uplo, Integer n, Complex ap[], const Complex bp[], NagError *fail)

3  Description

To reduce the complex Hermitian-definite generalized eigenproblem Az=λBz, ABz=λz or BAz=λz to the standard form Cy=λy using packed storage, nag_zhpgst (f08tsc) must be preceded by a call to nag_zpptrf (f07grc) 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.
comp_type Problem uplo B C z
Nag_Compute_1 Az=λBz Nag_Upper 
Nag_Lower
UHU 
LLH
U-HAU-1 
L-1AL-H
U-1y 
L-Hy
Nag_Compute_2 ABz=λz Nag_Upper 
Nag_Lower
UHU 
LLH
UAUH 
LHAL
U-1y 
L-Hy
Nag_Compute_3 BAz=λz Nag_Upper 
Nag_Lower
UHU 
LLH
UAUH 
LHAL
UHy 
Ly

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 2.3.1.3 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:     comp_type Nag_ComputeTypeInput
On entry: indicates how the standard form is computed.
comp_type=Nag_Compute_1
  • if uplo=Nag_Upper, C=U-HAU-1;
  • if uplo=Nag_Lower, C=L-1AL-H.
comp_type=Nag_Compute_2 or Nag_Compute_3
  • if uplo=Nag_Upper, C=UAUH;
  • if uplo=Nag_Lower, C=LHAL.
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=UHU.
uplo=Nag_Lower
The lower triangular part of A is stored and B=LLH.
Constraint: uplo=Nag_Upper or Nag_Lower.
4:     n IntegerInput
On entry: n, the order of the matrices A and B.
Constraint: n0.
5:     ap[dim] ComplexInput/Output
Note: the dimension, dim, of the array ap must be at least max1,n×n+1/2.
On entry: the upper or lower triangle of the n by n Hermitian matrix A, packed by rows or columns.
The storage of elements Aij depends on the order and uplo arguments as follows:
  • if order=Nag_ColMajor and uplo=Nag_Upper,
              Aij is stored in ap[j-1×j/2+i-1], for ij;
  • if order=Nag_ColMajor and uplo=Nag_Lower,
              Aij is stored in ap[2n-j×j-1/2+i-1], for ij;
  • if order=Nag_RowMajor and uplo=Nag_Upper,
              Aij is stored in ap[2n-i×i-1/2+j-1], for ij;
  • if order=Nag_RowMajor and uplo=Nag_Lower,
              Aij is stored in ap[i-1×i/2+j-1], for ij.
On exit: the upper or lower triangle of ap is overwritten by the corresponding upper or lower triangle of C as specified by comp_type and uplo, using the same packed storage format as described above.
6:     bp[dim] const ComplexInput
Note: the dimension, dim, of the array bp must be at least max1,n×n+1/2.
On entry: the Cholesky factor of B as specified by uplo and returned by nag_zpptrf (f07grc).
7:     fail NagError *Input/Output
The NAG error argument (see Section 2.7 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_INT
On entry, n=value.
Constraint: n0.
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 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

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_zhpgst (f08tsc) 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_zhpgst (f08tsc) 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 real floating-point operations is approximately 4n3.
The real analogue of this function is nag_dspgst (f08tec).

10  Example

This example computes all the eigenvalues of Az=λBz, where
A = -7.36+0.00i 0.77-0.43i -0.64-0.92i 3.01-6.97i 0.77+0.43i 3.49+0.00i 2.19+4.45i 1.90+3.73i -0.64+0.92i 2.19-4.45i 0.12+0.00i 2.88-3.17i 3.01+6.97i 1.90-3.73i 2.88+3.17i -2.54+0.00i  
and
B = 3.23+0.00i 1.51-1.92i 1.90+0.84i 0.42+2.50i 1.51+1.92i 3.58+0.00i -0.23+1.11i -1.18+1.37i 1.90-0.84i -0.23-1.11i 4.09+0.00i 2.33-0.14i 0.42-2.50i -1.18-1.37i 2.33+0.14i 4.29+0.00i ,  
using packed storage. Here B is Hermitian positive definite and must first be factorized by nag_zpptrf (f07grc). The program calls nag_zhpgst (f08tsc) to reduce the problem to the standard form Cy=λy; then nag_zhptrd (f08gsc) to reduce C to tridiagonal form, and nag_dsterf (f08jfc) to compute the eigenvalues.

10.1  Program Text

Program Text (f08tsce.c)

10.2  Program Data

Program Data (f08tsce.d)

10.3  Program Results

Program Results (f08tsce.r)


nag_zhpgst (f08tsc) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016