NAG Library Function Document

nag_zheevx (f08fpc)

1  Purpose

2  Specification

3  Description

4  References

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 $\mathbf{order}=\mathrm{Nag\_RowMajor}$. See Section 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.

Constraint: $\mathbf{order}=\mathrm{Nag\_RowMajor}$ or $\mathrm{Nag\_ColMajor}$.

2:     job – Nag_JobTypeInput

On entry: indicates whether eigenvectors are computed.

$\mathbf{job}=\mathrm{Nag\_EigVals}$

Only eigenvalues are computed.

$\mathbf{job}=\mathrm{Nag\_DoBoth}$

Eigenvalues and eigenvectors are computed.

Constraint: $\mathbf{job}=\mathrm{Nag\_EigVals}$ or $\mathrm{Nag\_DoBoth}$.

3:     range – Nag_RangeTypeInput

On entry: if $\mathbf{range}=\mathrm{Nag\_AllValues}$, all eigenvalues will be found.

If $\mathbf{range}=\mathrm{Nag\_Interval}$, all eigenvalues in the half-open interval $\left(\mathbf{vl},\mathbf{vu}\right]$ will be found.

If $\mathbf{range}=\mathrm{Nag\_Indices}$, the ilth to iuth eigenvalues will be found.

Constraint: $\mathbf{range}=\mathrm{Nag\_AllValues}$, $\mathrm{Nag\_Interval}$ or $\mathrm{Nag\_Indices}$.

4:     uplo – Nag_UploTypeInput

On entry: if $\mathbf{uplo}=\mathrm{Nag\_Upper}$, the upper triangular part of $A$ is stored.

If $\mathbf{uplo}=\mathrm{Nag\_Lower}$, the lower triangular part of $A$ is stored.

Constraint: $\mathbf{uplo}=\mathrm{Nag\_Upper}$ or $\mathrm{Nag\_Lower}$.

5:     n – IntegerInput

On entry: $n$, the order of the matrix $A$.

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

6:     a[$\mathit{dim}$] – ComplexInput/Output

Note: the dimension, dim, of the array a must be at least $\max \left(1,\mathbf{pda}\times \mathbf{n}\right)$.

On entry: the $n$ by $n$ Hermitian matrix $A$.

If $\mathbf{order}=\mathrm{Nag\_ColMajor}$, $A_{ij}$ is stored in $\mathbf{a}\left[\left(j-1\right)\times \mathbf{pda}+i-1\right]$.

If $\mathbf{order}=\mathrm{Nag\_RowMajor}$, $A_{ij}$ is stored in $\mathbf{a}\left[\left(i-1\right)\times \mathbf{pda}+j-1\right]$.

If $\mathbf{uplo}=\mathrm{Nag\_Upper}$, the upper triangular part of $A$ must be stored and the elements of the array below the diagonal are not referenced.

If $\mathbf{uplo}=\mathrm{Nag\_Lower}$, the lower triangular part of $A$ must be stored and the elements of the array above the diagonal are not referenced.

On exit: the lower triangle (if $\mathbf{uplo}=\mathrm{Nag\_Lower}$) or the upper triangle (if $\mathbf{uplo}=\mathrm{Nag\_Upper}$) of a, including the diagonal, is overwritten.

7:     pda – IntegerInput

On entry: the stride separating row or column elements (depending on the value of order) in the array a.

Constraint: $\mathbf{pda}\ge \max \left(1,\mathbf{n}\right)$.

8:     vl – doubleInput

9:     vu – doubleInput

On entry: if $\mathbf{range}=\mathrm{Nag\_Interval}$, the lower and upper bounds of the interval to be searched for eigenvalues.

If $\mathbf{range}=\mathrm{Nag\_AllValues}$ or $\mathrm{Nag\_Indices}$, vl and vu are not referenced.

Constraint: if $\mathbf{range}=\mathrm{Nag\_Interval}$, $\mathbf{vl}<\mathbf{vu}$.

10:   il – IntegerInput

11:   iu – IntegerInput

On entry: if $\mathbf{range}=\mathrm{Nag\_Indices}$, the indices (in ascending order) of the smallest and largest eigenvalues to be returned.

If $\mathbf{range}=\mathrm{Nag\_AllValues}$ or $\mathrm{Nag\_Interval}$, il and iu are not referenced.

Constraints:

• if $\mathbf{range}=\mathrm{Nag\_Indices}$ and $\mathbf{n}=0$, $\mathbf{il}=1$ and $\mathbf{iu}=0$;
• if $\mathbf{range}=\mathrm{Nag\_Indices}$ and $\mathbf{n}>0$, $1\le \mathbf{il}\le \mathbf{iu}\le \mathbf{n}$.

12:   abstol – doubleInput

On entry: the absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval $\left[a,b\right]$ of width less than or equal to

$$\mathbf{abstol}+\epsilon \max \left(\left|a\right|,\left|b\right|\right)\text{,}$$

where $\epsilon$ is the machine precision. If abstol is less than or equal to zero, then $\epsilon {‖T‖}_1$ will be used in its place, where $T$ is the tridiagonal matrix obtained by reducing $A$ to tridiagonal form. Eigenvalues will be computed most accurately when abstol is set to twice the underflow threshold $2\times \mathbf{nag\_real\_safe\_small\_number}$, not zero. If this function returns with $\mathbf{fail}\mathbf{.}\mathbf{code}=$ NE_CONVERGENCE, indicating that some eigenvectors did not converge, try setting abstol to $2\times \mathbf{nag\_real\_safe\_small\_number}$. See Demmel and Kahan (1990).

13:   m – Integer *Output

On exit: the total number of eigenvalues found. $0\le \mathbf{m}\le \mathbf{n}$.

If $\mathbf{range}=\mathrm{Nag\_AllValues}$, $\mathbf{m}=\mathbf{n}$.

If $\mathbf{range}=\mathrm{Nag\_Indices}$, $\mathbf{m}=\mathbf{iu}-\mathbf{il}+1$.

14:   w[$\mathit{dim}$] – doubleOutput

Note: the dimension, dim, of the array w must be at least $\max \left(1,\mathbf{n}\right)$.

On exit: the first m elements contain the selected eigenvalues in ascending order.

15:   z[$\mathit{dim}$] – ComplexOutput

Note: the dimension, dim, of the array z must be at least

• $\max \left(1,\mathbf{pdz}\times \mathbf{n}\right)$ when $\mathbf{job}=\mathrm{Nag\_DoBoth}$;
• $1$ otherwise.

The $i$th element of the $j$th vector $Z$ is stored in

• $\mathbf{z}\left[\left(j-1\right)\times \mathbf{pdz}+i-1\right]$ when $\mathbf{order}=\mathrm{Nag\_ColMajor}$;
• $\mathbf{z}\left[\left(i-1\right)\times \mathbf{pdz}+j-1\right]$ when $\mathbf{order}=\mathrm{Nag\_RowMajor}$.

On exit: if $\mathbf{job}=\mathrm{Nag\_DoBoth}$, then

• if $\mathbf{fail}\mathbf{.}\mathbf{code}=$ NE_NOERROR, the first m columns of $Z$ contain the orthonormal eigenvectors of the matrix $A$ corresponding to the selected eigenvalues, with the $i$th column of $Z$ holding the eigenvector associated with $\mathbf{w}\left[i-1\right]$;
• if an eigenvector fails to converge ($\mathbf{fail}\mathbf{.}\mathbf{code}=$ NE_CONVERGENCE), then that column of $Z$ contains the latest approximation to the eigenvector, and the index of the eigenvector is returned in jfail.

If $\mathbf{job}=\mathrm{Nag\_EigVals}$, z is not referenced.

16:   pdz – IntegerInput

On entry: the stride used in the array z.

Constraints:

• if $\mathbf{job}=\mathrm{Nag\_DoBoth}$, $\mathbf{pdz}\ge \max \left(1,\mathbf{n}\right)$;
• otherwise $\mathbf{pdz}\ge 1$.

17:   jfail[$\mathit{dim}$] – IntegerOutput

Note: the dimension, dim, of the array jfail must be at least $\max \left(1,\mathbf{n}\right)$.

On exit: if $\mathbf{job}=\mathrm{Nag\_DoBoth}$, then

• if $\mathbf{fail}\mathbf{.}\mathbf{code}=$ NE_NOERROR, the first m elements of jfail are zero;
• if $\mathbf{fail}\mathbf{.}\mathbf{code}=$ NE_CONVERGENCE, jfail contains the indices of the eigenvectors that failed to converge.

If $\mathbf{job}=\mathrm{Nag\_EigVals}$, jfail is not referenced.

18:   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.

NE_BAD_PARAM

On entry, argument $⟨\mathit{\text{value}}⟩$ had an illegal value.

NE_CONVERGENCE

The algorithm failed to converge; $⟨\mathit{\text{value}}⟩$ eigenvectors did not converge.

NE_ENUM_INT_2

On entry, $\mathbf{job}=⟨\mathit{\text{value}}⟩$, $\mathbf{pdz}=⟨\mathit{\text{value}}⟩$ and $\mathbf{n}=⟨\mathit{\text{value}}⟩$.
Constraint: if $\mathbf{job}=\mathrm{Nag\_DoBoth}$, $\mathbf{pdz}\ge \max \left(1,\mathbf{n}\right)$;
otherwise $\mathbf{pdz}\ge 1$.

NE_ENUM_INT_3

On entry, $\mathbf{range}=⟨\mathit{\text{value}}⟩$, $\mathbf{il}=⟨\mathit{\text{value}}⟩$, $\mathbf{iu}=⟨\mathit{\text{value}}⟩$ and $\mathbf{n}=⟨\mathit{\text{value}}⟩$.
Constraint: if $\mathbf{range}=\mathrm{Nag\_Indices}$ and $\mathbf{n}=0$, $\mathbf{il}=1$ and $\mathbf{iu}=0$;
if $\mathbf{range}=\mathrm{Nag\_Indices}$ and $\mathbf{n}>0$, $1\le \mathbf{il}\le \mathbf{iu}\le \mathbf{n}$.

NE_ENUM_REAL_2

On entry, $\mathbf{range}=⟨\mathit{\text{value}}⟩$, $\mathbf{vl}=⟨\mathit{\text{value}}⟩$ and $\mathbf{vu}=⟨\mathit{\text{value}}⟩$.
Constraint: if $\mathbf{range}=\mathrm{Nag\_Interval}$, $\mathbf{vl}<\mathbf{vu}$.

NE_INT

On entry, $\mathbf{n}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{n}\ge 0$.

On entry, $\mathbf{pda}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{pda}>0$.

On entry, $\mathbf{pdz}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{pdz}>0$.

NE_INT_2

On entry, $\mathbf{pda}=⟨\mathit{\text{value}}⟩$ and $\mathbf{n}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{pda}\ge \max \left(1,\mathbf{n}\right)$.

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.

7  Accuracy

8  Parallelism and Performance

9  Further Comments

10  Example

10.1  Program Text

Program Text (f08fpce.c)

10.2  Program Data

Program Data (f08fpce.d)

10.3  Program Results

Program Results (f08fpce.r)