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Chapter Introduction
NAG Toolbox

# NAG Toolbox: nag_sort_realmat_rank_rows (m01de)

## Purpose

nag_sort_realmat_rank_rows (m01de) ranks the rows of a matrix of double numbers in ascending or descending order.

## Syntax

[irank, ifail] = m01de(rm, m1, n1, order, 'm2', m2, 'n2', n2)
[irank, ifail] = nag_sort_realmat_rank_rows(rm, m1, n1, order, 'm2', m2, 'n2', n2)
Note: the interface to this routine has changed since earlier releases of the toolbox:
Mark 22: m2 has been made optional
.

## Description

nag_sort_realmat_rank_rows (m01de) ranks rows m1 to m2 of a matrix, using the data in columns n1 to n2 of those rows. The ordering is determined by first ranking the data in column n1, then ranking any tied rows according to the data in column n1 + 1${\mathbf{n1}}+1$, and so on up to column n2.
nag_sort_realmat_rank_rows (m01de) uses a variant of list-merging, as described on pages 165–166 in Knuth (1973). The function takes advantage of natural ordering in the data, and uses a simple list insertion in a preparatory pass to generate ordered lists of length at least 10$10$. The ranking is stable: equal rows preserve their ordering in the input data.

## References

Knuth D E (1973) The Art of Computer Programming (Volume 3) (2nd Edition) Addison–Wesley

## Parameters

### Compulsory Input Parameters

1:     rm(ldm,n2) – double array
ldm, the first dimension of the array, must satisfy the constraint ldmm2$\mathit{ldm}\ge {\mathbf{m2}}$.
Columns n1 to n2 of rows m1 to m2 of rm must contain double data to be ranked.
2:     m1 – int64int32nag_int scalar
The index of the first row of rm to be ranked.
Constraint: m1 > 0${\mathbf{m1}}>0$.
3:     n1 – int64int32nag_int scalar
The index of the first column of rm to be used.
Constraint: n1 > 0${\mathbf{n1}}>0$.
4:     order – string (length ≥ 1)
If order = 'A'${\mathbf{order}}=\text{'A'}$, the rows will be ranked in ascending (i.e., nondecreasing) order.
If order = 'D'${\mathbf{order}}=\text{'D'}$, into descending order.
Constraint: order = 'A'${\mathbf{order}}=\text{'A'}$ or 'D'$\text{'D'}$.

### Optional Input Parameters

1:     m2 – int64int32nag_int scalar
Default: The first dimension of the array rm.
The index of the last row of rm to be ranked.
Constraint: m2m1${\mathbf{m2}}\ge {\mathbf{m1}}$.
2:     n2 – int64int32nag_int scalar
Default: The second dimension of the array rm.
The index of the last column of rm to be used.
Constraint: n2n1${\mathbf{n2}}\ge {\mathbf{n1}}$.

ldm

### Output Parameters

1:     irank(m2) – int64int32nag_int array
Elements m1 to m2 of irank contain the ranks of the corresponding rows of rm. Note that the ranks are in the range m1 to m2: thus, if the i$i$th row of rm is the first in the rank order, irank(i)${\mathbf{irank}}\left(i\right)$ is set to m1.
2:     ifail – int64int32nag_int scalar
${\mathrm{ifail}}={\mathbf{0}}$ unless the function detects an error (see [Error Indicators and Warnings]).

## Error Indicators and Warnings

Errors or warnings detected by the function:
ifail = 1${\mathbf{ifail}}=1$
 On entry, m2 < 1${\mathbf{m2}}<1$, or n2 < 1${\mathbf{n2}}<1$, or m1 < 1${\mathbf{m1}}<1$, or m1 > m2${\mathbf{m1}}>{\mathbf{m2}}$, or n1 < 1${\mathbf{n1}}<1$, or n1 > n2${\mathbf{n1}}>{\mathbf{n2}}$, or ldm < m2$\mathit{ldm}<{\mathbf{m2}}$.
ifail = 2${\mathbf{ifail}}=2$
 On entry, order is not 'A' or 'D'.

## Accuracy

Not applicable.

The average time taken by the function is approximately proportional to n × log(n)$n×\mathrm{log}\left(n\right)$, where n = m2m1 + 1$n={\mathbf{m2}}-{\mathbf{m1}}+1$.

## Example

```function nag_sort_realmat_rank_rows_example
rm = [6, 5, 4;
5, 2, 1;
2, 4, 9;
4, 9, 6;
4, 9, 5;
4, 1, 2;
3, 4, 1;
2, 4, 6;
1, 6, 4;
9, 3, 2;
6, 2, 5;
4, 9, 6];
m1 = int64(1);
n1 = int64(1);
order = 'Ascending';
[irank, ifail] = nag_sort_realmat_rank_rows(rm, m1, n1, order)
```
```

irank =

11
9
3
7
6
5
4
2
1
12
10
8

ifail =

0

```
```function m01de_example
rm = [6, 5, 4;
5, 2, 1;
2, 4, 9;
4, 9, 6;
4, 9, 5;
4, 1, 2;
3, 4, 1;
2, 4, 6;
1, 6, 4;
9, 3, 2;
6, 2, 5;
4, 9, 6];
m1 = int64(1);
n1 = int64(1);
order = 'Ascending';
[irank, ifail] = m01de(rm, m1, n1, order)
```
```

irank =

11
9
3
7
6
5
4
2
1
12
10
8

ifail =

0

```