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Robert Barta > AI-NeuralNet-SOM-0.07 > AI::NeuralNet::SOM::Rect
Module Version: 0.02

# NAME

AI::NeuralNet::SOM::Rect - Perl extension for Kohonen Maps (rectangular topology)

# SYNOPSIS

```  use AI::NeuralNet::SOM::Rect;
my \$nn = new AI::NeuralNet::SOM::Rect (output_dim => "5x6",
input_dim  => 3);
\$nn->initialize;
\$nn->train (30,
[ 3, 2, 4 ],
[ -1, -1, -1 ],
[ 0, 4, -3]);

print \$nn->as_data;```

# INTERFACE

## Constructor

The constructor takes the following arguments (additionally to those in the base class):

`output_dim` : (mandatory, no default)

A string of the form "3x4" defining the X and the Y dimensions.

Example:

```    my \$nn = new AI::NeuralNet::SOM::Rect (output_dim => "5x6",
input_dim  => 3);```

## Methods

map

\$m = \$nn->map

This method returns the 2-dimensional array of vectors in the grid (as a reference to an array of references to arrays of vectors). The representation of the 2-dimensional array is straightforward.

Example:

```   my \$m = \$nn->map;
for my \$x (0 .. 5) {
for my \$y (0 .. 4){
warn "vector at \$x, \$y: ". Dumper \$m->[\$x]->[\$y];
}
}```
as_data

print \$nn->as_data

This methods creates a string containing the raw vector data, row by row. This can be fed into gnuplot, for instance.

http://www.ai-junkie.com/ann/som/som1.html

# AUTHOR

Robert Barta, <rho@devc.at>