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<div class="subTitle">org.apache.commons.math3.ml.neuralnet.twod</div>
<h2 title="Class NeuronSquareMesh2D" class="title">Class NeuronSquareMesh2D</h2>
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<li>org.apache.commons.math3.ml.neuralnet.twod.NeuronSquareMesh2D</li>
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<pre>public class <span class="strong">NeuronSquareMesh2D</span>
extends <a href="http://docs.oracle.com/javase/6/docs/api/java/lang/Object.html?is-external=true" title="class or interface in java.lang">Object</a>
implements <a href="http://docs.oracle.com/javase/6/docs/api/java/io/Serializable.html?is-external=true" title="class or interface in java.io">Serializable</a></pre>
<div class="block">Neural network with the topology of a two-dimensional surface.
Each neuron defines one surface element.
<br/>
This network is primarily intended to represent a
<a href="http://en.wikipedia.org/wiki/Kohonen">
Self Organizing Feature Map</a>.</div>
<dl><dt><span class="strong">Since:</span></dt>
<dd>3.3</dd>
<dt><span class="strong">Version:</span></dt>
<dd>$Id: NeuronSquareMesh2D.java 1566396 2014-02-09 20:36:24Z tn $</dd>
<dt><span class="strong">See Also:</span></dt><dd><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/sofm/package-summary.html"><code>org.apache.commons.math3.ml.neuralnet.sofm</code></a>,
<a href="../../../../../../../serialized-form.html#org.apache.commons.math3.ml.neuralnet.twod.NeuronSquareMesh2D">Serialized Form</a></dd></dl>
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<th class="colOne" scope="col">Constructor and Description</th>
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<td class="colOne"><code><strong><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/twod/NeuronSquareMesh2D.html#NeuronSquareMesh2D(int, boolean, int, boolean, org.apache.commons.math3.ml.neuralnet.SquareNeighbourhood, org.apache.commons.math3.ml.neuralnet.FeatureInitializer[])">NeuronSquareMesh2D</a></strong>(int&nbsp;numRows,
boolean&nbsp;wrapRowDim,
int&nbsp;numCols,
boolean&nbsp;wrapColDim,
<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/SquareNeighbourhood.html" title="enum in org.apache.commons.math3.ml.neuralnet">SquareNeighbourhood</a>&nbsp;neighbourhoodType,
<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/FeatureInitializer.html" title="interface in org.apache.commons.math3.ml.neuralnet">FeatureInitializer</a>[]&nbsp;featureInit)</code>
<div class="block">Creates a two-dimensional network composed of square cells:
Each neuron not located on the border of the mesh has four
neurons linked to it.</div>
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<td class="colFirst"><code><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/Network.html" title="class in org.apache.commons.math3.ml.neuralnet">Network</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/twod/NeuronSquareMesh2D.html#getNetwork()">getNetwork</a></strong>()</code>
<div class="block">Retrieves the underlying network.</div>
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<td class="colFirst"><code><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/Neuron.html" title="class in org.apache.commons.math3.ml.neuralnet">Neuron</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/twod/NeuronSquareMesh2D.html#getNeuron(int, int)">getNeuron</a></strong>(int&nbsp;i,
int&nbsp;j)</code>
<div class="block">Retrieves the neuron at location <code>(i, j)</code> in the map.</div>
</td>
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<tr class="altColor">
<td class="colFirst"><code>int</code></td>
<td class="colLast"><code><strong><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/twod/NeuronSquareMesh2D.html#getNumberOfColumns()">getNumberOfColumns</a></strong>()</code>
<div class="block">Gets the number of neurons in each column of this map.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>int</code></td>
<td class="colLast"><code><strong><a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/twod/NeuronSquareMesh2D.html#getNumberOfRows()">getNumberOfRows</a></strong>()</code>
<div class="block">Gets the number of neurons in each row of this map.</div>
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<h3>Constructor Detail</h3>
<a name="NeuronSquareMesh2D(int, boolean, int, boolean, org.apache.commons.math3.ml.neuralnet.SquareNeighbourhood, org.apache.commons.math3.ml.neuralnet.FeatureInitializer[])">
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<h4>NeuronSquareMesh2D</h4>
<pre>public&nbsp;NeuronSquareMesh2D(int&nbsp;numRows,
boolean&nbsp;wrapRowDim,
int&nbsp;numCols,
boolean&nbsp;wrapColDim,
<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/SquareNeighbourhood.html" title="enum in org.apache.commons.math3.ml.neuralnet">SquareNeighbourhood</a>&nbsp;neighbourhoodType,
<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/FeatureInitializer.html" title="interface in org.apache.commons.math3.ml.neuralnet">FeatureInitializer</a>[]&nbsp;featureInit)</pre>
<div class="block">Creates a two-dimensional network composed of square cells:
Each neuron not located on the border of the mesh has four
neurons linked to it.
<br/>
The links are bi-directional.
<br/>
The topology of the network can also be a cylinder (if one
of the dimensions is wrapped) or a torus (if both dimensions
are wrapped).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>numRows</code> - Number of neurons in the first dimension.</dd><dd><code>wrapRowDim</code> - Whether to wrap the first dimension (i.e the first
and last neurons will be linked together).</dd><dd><code>numCols</code> - Number of neurons in the second dimension.</dd><dd><code>wrapColDim</code> - Whether to wrap the second dimension (i.e the first
and last neurons will be linked together).</dd><dd><code>neighbourhoodType</code> - Neighbourhood type.</dd><dd><code>featureInit</code> - Array of functions that will initialize the
corresponding element of the features set of each newly created
neuron. In particular, the size of this array defines the size of
feature set.</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../../../org/apache/commons/math3/exception/NumberIsTooSmallException.html" title="class in org.apache.commons.math3.exception">NumberIsTooSmallException</a></code> - if <code>numRows &lt; 2</code> or
<code>numCols &lt; 2</code>.</dd></dl>
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<a name="getNetwork()">
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<h4>getNetwork</h4>
<pre>public&nbsp;<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/Network.html" title="class in org.apache.commons.math3.ml.neuralnet">Network</a>&nbsp;getNetwork()</pre>
<div class="block">Retrieves the underlying network.
A reference is returned (enabling, for example, the network to be
trained).
This also implies that calling methods that modify the <a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/Network.html" title="class in org.apache.commons.math3.ml.neuralnet"><code>Network</code></a>
topology may cause this class to become inconsistent.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the network.</dd></dl>
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<h4>getNumberOfRows</h4>
<pre>public&nbsp;int&nbsp;getNumberOfRows()</pre>
<div class="block">Gets the number of neurons in each row of this map.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the number of rows.</dd></dl>
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<h4>getNumberOfColumns</h4>
<pre>public&nbsp;int&nbsp;getNumberOfColumns()</pre>
<div class="block">Gets the number of neurons in each column of this map.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the number of column.</dd></dl>
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<h4>getNeuron</h4>
<pre>public&nbsp;<a href="../../../../../../../org/apache/commons/math3/ml/neuralnet/Neuron.html" title="class in org.apache.commons.math3.ml.neuralnet">Neuron</a>&nbsp;getNeuron(int&nbsp;i,
int&nbsp;j)</pre>
<div class="block">Retrieves the neuron at location <code>(i, j)</code> in the map.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>i</code> - Row index.</dd><dd><code>j</code> - Column index.</dd>
<dt><span class="strong">Returns:</span></dt><dd>the neuron at <code>(i, j)</code>.</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../../../org/apache/commons/math3/exception/OutOfRangeException.html" title="class in org.apache.commons.math3.exception">OutOfRangeException</a></code> - if <code>i</code> or <code>j</code> is
out of range.</dd></dl>
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