NAG Toolbox: nag_lapack_dspgvd (f08tc)

Purpose

Syntax

Description

References

Parameters

Compulsory Input Parameters

1:     $\mathrm{itype}$ – int64int32nag_int scalar

Specifies the problem type to be solved.

$\mathbf{itype}=1$

$Az=\lambda Bz$.

$\mathbf{itype}=2$

$ABz=\lambda z$.

$\mathbf{itype}=3$

$BAz=\lambda z$.

Constraint: $\mathbf{itype}=1$, $2$ or $3$.

2:     $\mathrm{jobz}$ – string (length ≥ 1)

Indicates whether eigenvectors are computed.

$\mathbf{jobz}=\text{'N'}$

Only eigenvalues are computed.

$\mathbf{jobz}=\text{'V'}$

Eigenvalues and eigenvectors are computed.

Constraint: $\mathbf{jobz}=\text{'N'}$ or $\text{'V'}$.

3:     $\mathrm{uplo}$ – string (length ≥ 1)

If $\mathbf{uplo}=\text{'U'}$, the upper triangles of $A$ and $B$ are stored.

If $\mathbf{uplo}=\text{'L'}$, the lower triangles of $A$ and $B$ are stored.

Constraint: $\mathbf{uplo}=\text{'U'}$ or $\text{'L'}$.

4:     $\mathrm{n}$ – int64int32nag_int scalar

$n$, the order of the matrices $A$ and $B$.

Constraint: $\mathbf{n}\ge 0$.

5:     $\mathrm{ap}\left(:\right)$ – double array

The dimension of the array ap must be at least $\max \left(1,\mathbf{n}\times \left(\mathbf{n}+1\right)/2\right)$

The upper or lower triangle of the $n$ by $n$ symmetric matrix $A$, packed by columns.

More precisely,

• if $\mathbf{uplo}=\text{'U'}$, the upper triangle of $A$ must be stored with element $A_{ij}$ in $\mathbf{ap}\left(i+j\left(j-1\right)/2\right)$ for $i\le j$;
• if $\mathbf{uplo}=\text{'L'}$, the lower triangle of $A$ must be stored with element $A_{ij}$ in $\mathbf{ap}\left(i+\left(2n-j\right)\left(j-1\right)/2\right)$ for $i\ge j$.

6:     $\mathrm{bp}\left(:\right)$ – double array

The dimension of the array bp must be at least $\max \left(1,\mathbf{n}\times \left(\mathbf{n}+1\right)/2\right)$

The upper or lower triangle of the $n$ by $n$ symmetric matrix $B$, packed by columns.

More precisely,

• if $\mathbf{uplo}=\text{'U'}$, the upper triangle of $B$ must be stored with element $B_{ij}$ in $\mathbf{bp}\left(i+j\left(j-1\right)/2\right)$ for $i\le j$;
• if $\mathbf{uplo}=\text{'L'}$, the lower triangle of $B$ must be stored with element $B_{ij}$ in $\mathbf{bp}\left(i+\left(2n-j\right)\left(j-1\right)/2\right)$ for $i\ge j$.

Optional Input Parameters

None.

Output Parameters

1:     $\mathrm{ap}\left(:\right)$ – double array

The dimension of the array ap will be $\max \left(1,\mathbf{n}\times \left(\mathbf{n}+1\right)/2\right)$

The contents of ap are destroyed.

2:     $\mathrm{bp}\left(:\right)$ – double array

The dimension of the array bp will be $\max \left(1,\mathbf{n}\times \left(\mathbf{n}+1\right)/2\right)$

The triangular factor $U$ or $L$ from the Cholesky factorization $B=U^{\mathrm{T}}U$ or $B=L{L}^{\mathrm{T}}$, in the same storage format as $B$.

3:     $\mathrm{w}\left(\mathbf{n}\right)$ – double array

The eigenvalues in ascending order.

4:     $\mathrm{z}\left(\mathit{ldz},:\right)$ – double array

The first dimension of the array z will be $\max \left(1,\mathbf{n}\right)$.

The second dimension of the array z will be $\max \left(1,\mathbf{n}\right)$ if $\mathbf{jobz}=\text{'V'}$ and $1$ otherwise.

If $\mathbf{jobz}=\text{'V'}$, z contains the matrix $Z$ of eigenvectors. The eigenvectors are normalized as follows:

• if $\mathbf{itype}=1$ or $2$, $Z^{\mathrm{T}}BZ=I$;
• if $\mathbf{itype}=3$, $Z^{\mathrm{T}}{B}^{-1}Z=I$.

If $\mathbf{jobz}=\text{'N'}$, z is not referenced.

5:     $\mathrm{info}$ – int64int32nag_int scalar

$\mathbf{info}=0$ unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

   $\mathbf{info}=-i$

If $\mathbf{info}=-i$, parameter $i$ had an illegal value on entry. The parameters are numbered as follows:

1: itype, 2: jobz, 3: uplo, 4: n, 5: ap, 6: bp, 7: w, 8: z, 9: ldz, 10: work, 11: lwork, 12: iwork, 13: liwork, 14: info.

It is possible that info refers to a parameter that is omitted from the MATLAB interface. This usually indicates that an error in one of the other input parameters has caused an incorrect value to be inferred.

   $\mathbf{info}>0$

nag_lapack_dpptrf (f07gd) or nag_lapack_dspevd (f08gc) returned an error code:

$\le \mathbf{n}$	if $\mathbf{info}=i$, nag_lapack_dspevd (f08gc) failed to converge; $i$ off-diagonal elements of an intermediate tridiagonal form did not converge to zero;
$>\mathbf{n}$	if $\mathbf{info}=\mathbf{n}+i$, for $1\le i\le \mathbf{n}$, then the leading minor of order $i$ of $B$ is not positive definite. The factorization of $B$ could not be completed and no eigenvalues or eigenvectors were computed.

Accuracy

Further Comments

Example

Open in the MATLAB editor: f08tc_example

function f08tc_example


fprintf('f08tc example results\n\n');

% Symmetric matrices A and B stored in packed (Upper) format
n = int64(4);
uplo = 'U';
ap = [0.24;
      0.39; -0.11;
      0.42;  0.79; -0.25;
     -0.16;  0.63;  0.48; -0.03];
bp = [4.16;
     -3.12;  5.03;
      0.56; -0.83;  0.76;
      -0.10;  1.09;  0.34;  1.18];

% Generalized eigenvalues for ABz = lambda z
itype = int64(2);
jobz = 'No vectors';
[~, L, w, z, info] = f08tc( ...
                            itype, jobz, uplo, n, ap, bp);

disp('Eigenvalues');
disp(w');

% Calculate condition number and error estimates
% Unpack ap and bp to calculate 1 norms of A and B
[a, ap, ifail] = f01za( ...
                        'Unpack', uplo, 'N', zeros(n,n), ap);
[b, bp, ifail] = f01za( ...
                        'Unpack', uplo, 'N', zeros(n,n), bp);
anorm = norm(a + a' - diag(diag(a)),1);
bnorm = norm(b + b' - diag(diag(b)),1);

% Estimate condition number
[rcond, info] = f07ug( ...
                       '1', uplo, 'N', n, L);

rcondb = rcond^2;
fprintf('Estimate of reciprocal condition number for B\n%12.1e\n', rcondb);

% Error bounds
t1 = x02aj/rcondb;
t2 = anorm*bnorm;
errbnd(1:n) = x02aj*t2 + t1.*abs(w);

fprintf('\n');
disp('Error estimate for the eigenvalues');
fprintf('%12.1e',errbnd);
fprintf('\n');

f08tc example results

Eigenvalues
   -3.5411   -0.3347    0.2983    2.2544

Estimate of reciprocal condition number for B
     5.8e-03

Error estimate for the eigenvalues
     7.0e-14     8.6e-15     7.9e-15     4.6e-14