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<a href="Bio-module.html">Package Bio</a> ::
<a href="Bio.NeuralNetwork-module.html">Package NeuralNetwork</a> ::
<a href="Bio.NeuralNetwork.Gene-module.html">Package Gene</a> ::
<a href="Bio.NeuralNetwork.Gene.Signature-module.html">Module Signature</a> ::
Class SignatureCoder
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class SignatureCoder</h1><p class="nomargin-top"><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Signature-pysrc.html#SignatureCoder">source code</a></span></p>
<pre class="base-tree">
object --+
|
<strong class="uidshort">SignatureCoder</strong>
</pre>
<hr />
<p>Convert a Sequence into its signature representatives.</p>
<p>This takes a sequence and a set of signatures, and converts the
sequence into a list of numbers representing the relative amounts each
signature is seen in the sequence. This allows a sequence to serve as
input into a neural network.</p>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Signature.SignatureCoder-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">signatures</span>,
<span class="summary-sig-arg">max_gap</span>)</span><br />
Initialize with the signatures to look for.</td>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Signature.SignatureCoder-class.html#representation" class="summary-sig-name">representation</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">sequence</span>)</span><br />
Convert a sequence into a representation of its signatures.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Signature-pysrc.html#SignatureCoder.representation">source code</a></span>
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<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__delattr__</code>,
<code>__format__</code>,
<code>__getattribute__</code>,
<code>__hash__</code>,
<code>__new__</code>,
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<code>__subclasshook__</code>
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<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__class__</code>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">__init__</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">signatures</span>,
<span class="sig-arg">max_gap</span>)</span>
<br /><em class="fname">(Constructor)</em>
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<p>Initialize with the signatures to look for.</p>
<p>Arguments:</p>
<p>o signatures - A complete list of signatures, in order, that are to be
searched for in the sequences. The signatures should be represented as a
tuple of (first part of the signature, second_part of the signature) --
('GATC', 'GATC').</p>
<p>o max_gap - The maximum gap we can have between the two elements of
the signature.</p>
<dl class="fields">
<dt>Overrides:
object.__init__
</dt>
</dl>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">representation</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">sequence</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Signature-pysrc.html#SignatureCoder.representation">source code</a></span>
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<p>Convert a sequence into a representation of its signatures.</p>
<p>Arguments:</p>
<p>o sequence - A Seq object we are going to convert into a set of
signatures.</p>
<p>Returns: A list of relative signature representations. Each item in
the list corresponds to the signature passed in to the initializer and is
the number of times that the signature was found, divided by the total
number of signatures found in the sequence.</p>
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