nag_zhetrf (f07mrc) (PDF version)
f07 Chapter Contents
f07 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_zhetrf (f07mrc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_zhetrf (f07mrc) computes the Bunch–Kaufman factorization of a complex Hermitian indefinite matrix.

2  Specification

#include <nag.h>
#include <nagf07.h>
void  nag_zhetrf (Nag_OrderType order, Nag_UploType uplo, Integer n, Complex a[], Integer pda, Integer ipiv[], NagError *fail)

3  Description

nag_zhetrf (f07mrc) factorizes a complex Hermitian matrix A, using the Bunch–Kaufman diagonal pivoting method. A is factorized either as A=PUDUHPT if uplo=Nag_Upper or A=PLDLHPT if uplo=Nag_Lower, where P is a permutation matrix, U (or L) is a unit upper (or lower) triangular matrix and D is an Hermitian block diagonal matrix with 1 by 1 and 2 by 2 diagonal blocks; U (or L) has 2 by 2 unit diagonal blocks corresponding to the 2 by 2 blocks of D. Row and column interchanges are performed to ensure numerical stability while keeping the matrix Hermitian.
This method is suitable for Hermitian matrices which are not known to be positive definite. If A is in fact positive definite, no interchanges are performed and no 2 by 2 blocks occur in D.

4  References

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

5  Arguments

1:     orderNag_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:     uploNag_UploTypeInput
On entry: specifies whether the upper or lower triangular part of A is stored and how A is to be factorized.
uplo=Nag_Upper
The upper triangular part of A is stored and A is factorized as PUDUHPT, where U is upper triangular.
uplo=Nag_Lower
The lower triangular part of A is stored and A is factorized as PLDLHPT, where L is lower triangular.
Constraint: uplo=Nag_Upper or Nag_Lower.
3:     nIntegerInput
On entry: n, the order of the matrix A.
Constraint: n0.
4:     a[dim]ComplexInput/Output
Note: the dimension, dim, of the array a must be at least max1,pda×n.
On entry: the n by n Hermitian indefinite 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 details of the block diagonal matrix D and the multipliers used to obtain the factor U or L as specified by uplo.
5:     pdaIntegerInput
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.
6:     ipiv[dim]IntegerOutput
Note: the dimension, dim, of the array ipiv must be at least max1,n.
On exit: details of the interchanges and the block structure of D. More precisely,
  • if ipiv[i-1]=k>0, dii is a 1 by 1 pivot block and the ith row and column of A were interchanged with the kth row and column;
  • if uplo=Nag_Upper and ipiv[i-2]=ipiv[i-1]=-l<0, di-1,i-1d-i,i-1 d-i,i-1dii  is a 2 by 2 pivot block and the i-1th row and column of A were interchanged with the lth row and column;
  • if uplo=Nag_Lower and ipiv[i-1]=ipiv[i]=-m<0, diidi+1,idi+1,idi+1,i+1 is a 2 by 2 pivot block and the i+1th row and column of A were interchanged with the mth row and column.
7:     failNagError *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.
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.
NE_INT_2
On entry, pda=value and n=value.
Constraint: pdamax1,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.
NE_SINGULAR
Dvalue,value is exactly zero. The factorization has been completed, but the block diagonal matrix D is exactly singular, and division by zero will occur if it is used to solve a system of equations.

7  Accuracy

If uplo=Nag_Upper, the computed factors U and D are the exact factors of a perturbed matrix A+E, where
EcnεPUDUHPT ,
cn is a modest linear function of n, and ε is the machine precision.
If uplo=Nag_Lower, a similar statement holds for the computed factors L and D.

8  Parallelism and Performance

nag_zhetrf (f07mrc) is not threaded by NAG in any implementation.
nag_zhetrf (f07mrc) 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 Users' Note for your implementation for any additional implementation-specific information.

9  Further Comments

The elements of D overwrite the corresponding elements of A; if D has 2 by 2 blocks, only the upper or lower triangle is stored, as specified by uplo.
The unit diagonal elements of U or L and the 2 by 2 unit diagonal blocks are not stored. The remaining elements of U or L are stored in the corresponding columns of the array a, but additional row interchanges must be applied to recover U or L explicitly (this is seldom necessary). If ipiv[i-1]=i, for i=1,2,,n (as is the case when A is positive definite), then U or L is stored explicitly (except for its unit diagonal elements which are equal to 1).
The total number of real floating-point operations is approximately 43n3.
A call to nag_zhetrf (f07mrc) may be followed by calls to the functions:
The real analogue of this function is nag_dsytrf (f07mdc).

10  Example

This example computes the Bunch–Kaufman factorization of the matrix A, where
A= -1.36+0.00i 1.58+0.90i 2.21-0.21i 3.91+1.50i 1.58-0.90i -8.87+0.00i -1.84-0.03i -1.78+1.18i 2.21+0.21i -1.84+0.03i -4.63+0.00i 0.11+0.11i 3.91-1.50i -1.78-1.18i 0.11-0.11i -1.84+0.00i .

10.1  Program Text

Program Text (f07mrce.c)

10.2  Program Data

Program Data (f07mrce.d)

10.3  Program Results

Program Results (f07mrce.r)


nag_zhetrf (f07mrc) (PDF version)
f07 Chapter Contents
f07 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014