# Documentation

### This is machine translation

Translated by
Mouseover text to see original. Click the button below to return to the English verison of the page.

# removerows

Process matrices by removing rows with specified indices

## Syntax

```[Y,PS] = removerows(X,'ind',ind) [Y,PS] = removerows(X,FP) Y = removerows('apply',X,PS) X = removerows('reverse',Y,PS) dx_dy = removerows('dx',X,Y,PS) dx_dy = removerows('dx',X,[],PS) name = removerows('name') fp = removerows('pdefaults') names = removerows('pdesc') removerows('pcheck',FP) ```

## Description

`removerows` processes matrices by removing rows with the specified indices.

`[Y,PS] = removerows(X,'ind',ind)` takes `X` and an optional parameter,

 `X` `N`-by-`Q` matrix `ind` Vector of row indices to remove (default is `[]`)

and returns

 `Y` `M`-by-`Q` matrix, where ```M == N-length(ind)``` `PS` Process settings that allow consistent processing of values

`[Y,PS] = removerows(X,FP)` takes parameters as a struct: `FP.ind`.

`Y = removerows('apply',X,PS)` returns `Y`, given `X` and settings `PS`.

`X = removerows('reverse',Y,PS)` returns `X`, given `Y` and settings `PS`.

`dx_dy = removerows('dx',X,Y,PS)` returns the `M`-by-`N`-by-`Q` derivative of `Y` with respect to `X`.

`dx_dy = removerows('dx',X,[],PS)` returns the derivative, less efficiently.

`name = removerows('name')` returns the name of this process method.

`fp = removerows('pdefaults')` returns the default process parameter structure.

`names = removerows('pdesc')` returns the process parameter descriptions.

`removerows('pcheck',FP)` throws an error if any parameter is illegal.

## Examples

Here is how to format a matrix so that rows 2 and 4 are removed:

```x1 = [1 2 4; 1 1 1; 3 2 2; 0 0 0] [y1,ps] = removerows(x1,'ind',[2 4]) ```

Next, apply the same processing settings to new values.

```x2 = [5 2 3; 1 1 1; 6 7 3; 0 0 0] y2 = removerows('apply',x2,ps) ```

Reverse the processing of `y1` to get `x1` again.

```x1_again = removerows('reverse',y1,ps) ```

## Algorithms

In the reverse calculation, the unknown values of replaced rows are represented with `NaN` values.