void	nag_dgeequ (Nag_OrderType order, Integer m, Integer n, const double a[], Integer pda, double r[], double c[], double rowcnd, double colcnd, double amax, NagError fail)

3

Description

nag_dgeequ (f07afc) computes the diagonal scaling matrices. The diagonal scaling matrices are chosen to try to make the elements of largest absolute value in each row and column of the matrix

B

given by

B = D_{R} A D_{C}

have absolute value

1

. The diagonal elements of

D_{R}

and

D_{C}

are restricted to lie in the safe range

(δ, 1 / δ)

, where

δ

is the value returned by function nag_real_safe_small_number (X02AMC). Use of these scaling factors is not guaranteed to reduce the condition number of

A

but works well in practice.

4

References

None.

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 3.3.1.3 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

Nag_ColMajor

2: $m$ – IntegerInput

On entry:

m

, the number of rows of the matrix

A

Constraint:

m \geq 0

3: $n$ – IntegerInput

On entry:

n

, the number of columns of the matrix

A

Constraint:

n \geq 0

4: $a [\dim]$ – const doubleInput

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

$\max (1, pda \times n)$ when $order = Nag_ColMajor$ ;
$\max (1, m \times pda)$ when $order = Nag_RowMajor$ .

The

(i, j)

th element of the matrix

A

is stored in

$a [(j - 1) \times pda + i - 1]$ when $order = Nag_ColMajor$ ;
$a [(i - 1) \times pda + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the matrix

A

whose scaling factors are to be computed.

5: $pda$ – IntegerInput

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

Constraints:

if $order = Nag_ColMajor$ , $pda \geq \max (1, m)$ ;
if $order = Nag_RowMajor$ , $pda \geq \max (1, n)$ .

6: $r [m]$ – doubleOutput

On exit: if

fail . code =

NE_NOERROR or

fail . code =

NE_MAT_COL_ZERO, r contains the row scale factors, the diagonal elements of

D_{R}

. The elements of r will be positive.

7: $c [n]$ – doubleOutput

On exit: if

fail . code =

NE_NOERROR, c contains the column scale factors, the diagonal elements of

D_{C}

. The elements of c will be positive.

8: $rowcnd$ – double *Output

On exit: if

fail . code =

NE_NOERROR or

fail . code =

NE_MAT_COL_ZERO, rowcnd contains the ratio of the smallest value of

r [i - 1]

to the largest value of

r [i - 1]

. If

rowcnd \geq 0.1

and amax is neither too large nor too small, it is not worth scaling by

D_{R}

9: $colcnd$ – double *Output

On exit: if

fail . code =

NE_NOERROR, colcnd contains the ratio of the smallest value of

c [i - 1]

to the largest value of

c [i - 1]

colcnd \geq 0.1

, it is not worth scaling by

D_{C}

10: $amax$ – double *Output

On exit:

\max |a_{i j}|

. If amax is very close to overflow or underflow, the matrix

A

should be scaled.

11: $fail$ – NagError *Input/Output

The NAG error argument (see Section 3.7 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, $m = 〈value〉$ .
Constraint: $m \geq 0$ .

On entry, $n = 〈value〉$ .
Constraint: $n \geq 0$ .

On entry, $pda = 〈value〉$ .
Constraint: $pda > 0$ .
NE_INT_2: On entry, $pda = 〈value〉$ and $m = 〈value〉$ .
Constraint: $pda \geq \max (1, m)$ .

On entry, $pda = 〈value〉$ and $n = 〈value〉$ .
Constraint: $pda \geq \max (1, n)$ .
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.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_MAT_COL_ZERO: Column $〈value〉$ of $A$ is exactly zero.
NE_MAT_ROW_ZERO: Row $〈value〉$ of $A$ is exactly zero.
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

The computed scale factors will be close to the exact scale factors.

8

Parallelism and Performance

nag_dgeequ (f07afc) is not threaded in any implementation.

9

Further Comments

The complex analogue of this function is nag_zgeequ (f07atc).

10

Example

This example equilibrates the general matrix

A

given by

A = (\begin{array}{l} 1.80 \times 10^{10} & 2.88 \times 10^{10} & 2.05 & - 8.90 \times 10^{9} \\ 5.25 & - 2.95 & - 9.50 \times 10^{- 9} & - 3.80 \\ 1.58 & - 2.69 & - 2.90 \times 10^{- 10} & - 1.04 \\ - 1.11 & - 0.66 & - 5.90 \times 10^{- 11} & 0.80 \end{array}) .

Details of the scaling factors, and the scaled matrix are output.

NAG Library Function Document

nag_dgeequ (f07afc)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

1

Purpose

2

Specification

3

Description

4

References

5

Arguments

6

Error Indicators and Warnings

7

Accuracy

8

Parallelism and Performance

9

Further Comments

10

Example

10.1

Program Text

10.2

Program Data

10.3

Program Results