# Documentation

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# prunedata

Prune data for consistency with pruned network

## Syntax

```[Xp,Xip,Aip,Tp] = prunedata(pi,pl,po,X,Xi,Ai,T) ```

## Description

This function prunes data to be consistent with a network whose zero-sized inputs, layers, and outputs have been removed with `prune`.

One use for this simplification is to prepare a network with zero-sized subobjects for Simulink®, where zero-sized signals are not supported.

`[Xp,Xip,Aip,Tp] = prunedata(pi,pl,po,X,Xi,Ai,T)` takes these arguments,

 `pi` Indices of pruned inputs `pl` Indices of pruned layers `po` Indices of pruned outputs `X` Input data `Xi` Initial input delay states `Ai` Initial layer delay states `T` Target data

and returns the pruned inputs, input and layer delay states, and targets.

## Examples

Here a NARX dynamic network is created which has one external input and a second input which feeds back from the output.

```net = narxnet(20); view(net) ```

The network is then trained on a single random time-series problem with 50 timesteps. The external input happens to have no elements.

```X = nndata(0,1,50); T = nndata(1,1,50); [Xs,Xi,Ai,Ts] = preparets(net,X,{},T); net = train(net,Xs,Ts); ```

The network and data are then pruned before generating a Simulink diagram and initializing its input and layer states.

```[net2,pi,pl,po] = prune(net); view(net) [Xs2,Xi2,Ai2,Ts2] = prunedata(net,pi,pl,po,Xs,Xi,Ai,Ts) [sysName,netName] = gensim(net); setsiminit(sysName,netName,Xi2,Ai2) ```