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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.Schema-module.html">Module Schema</a> ::
Class SchemaFactory
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class SchemaFactory</h1><p class="nomargin-top"><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory">source code</a></span></p>
<pre class="base-tree">
object --+
|
<strong class="uidshort">SchemaFactory</strong>
</pre>
<hr />
<p>Generate Schema from inputs of Motifs or Signatures.</p>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Schema.SchemaFactory-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">ambiguity_symbol</span>=<span class="summary-sig-default"><code class="variable-quote">'</code><code class="variable-string">*</code><code class="variable-quote">'</code></span>)</span><br />
Initialize the SchemaFactory</td>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Schema.SchemaFactory-class.html#from_motifs" class="summary-sig-name">from_motifs</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">motif_repository</span>,
<span class="summary-sig-arg">motif_percent</span>,
<span class="summary-sig-arg">num_ambiguous</span>)</span><br />
Generate schema from a list of motifs.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory.from_motifs">source code</a></span>
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<td><span class="summary-sig"><a name="_get_num_motifs"></a><span class="summary-sig-name">_get_num_motifs</span>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">repository</span>,
<span class="summary-sig-arg">motif_list</span>)</span><br />
Return the number of motif counts for the list of motifs.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory._get_num_motifs">source code</a></span>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Schema.SchemaFactory-class.html#_get_unique_schema" class="summary-sig-name" onclick="show_private();">_get_unique_schema</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">cur_schemas</span>,
<span class="summary-sig-arg">motif_list</span>,
<span class="summary-sig-arg">num_ambiguous</span>)</span><br />
Retrieve a unique schema from a motif.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory._get_unique_schema">source code</a></span>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.Gene.Schema.SchemaFactory-class.html#_schema_from_motif" class="summary-sig-name" onclick="show_private();">_schema_from_motif</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">motif</span>,
<span class="summary-sig-arg">motif_list</span>,
<span class="summary-sig-arg">num_ambiguous</span>)</span><br />
Create a schema from a given starting motif.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory._schema_from_motif">source code</a></span>
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<td><span class="summary-sig"><a name="from_signatures"></a><span class="summary-sig-name">from_signatures</span>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">signature_repository</span>,
<span class="summary-sig-arg">num_ambiguous</span>)</span></td>
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<span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory.from_signatures">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>,
<code>__reduce__</code>,
<code>__reduce_ex__</code>,
<code>__repr__</code>,
<code>__setattr__</code>,
<code>__sizeof__</code>,
<code>__str__</code>,
<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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<a name="__init__"></a>
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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">ambiguity_symbol</span>=<span class="sig-default"><code class="variable-quote">'</code><code class="variable-string">*</code><code class="variable-quote">'</code></span>)</span>
<br /><em class="fname">(Constructor)</em>
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<p>Initialize the SchemaFactory</p>
<p>Arguments:</p>
<p>o ambiguity_symbol -- The symbol to use when specifying that a
position is arbitrary.</p>
<dl class="fields">
<dt>Overrides:
object.__init__
</dt>
</dl>
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<a name="from_motifs"></a>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">from_motifs</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">motif_repository</span>,
<span class="sig-arg">motif_percent</span>,
<span class="sig-arg">num_ambiguous</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory.from_motifs">source code</a></span>
</td>
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<p>Generate schema from a list of motifs.</p>
<p>Arguments:</p>
<p>o motif_repository - A MotifRepository class that has all of the
motifs we want to convert to Schema.</p>
<p>o motif_percent - The percentage of motifs in the motif bank which
should be matches. We'll try to create schema that match this percentage
of motifs.</p>
<p>o num_ambiguous - The number of ambiguous characters to include in
each schema. The positions of these ambiguous characters will be randomly
selected.</p>
<dl class="fields">
</dl>
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</div>
<a name="_get_unique_schema"></a>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">_get_unique_schema</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">cur_schemas</span>,
<span class="sig-arg">motif_list</span>,
<span class="sig-arg">num_ambiguous</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory._get_unique_schema">source code</a></span>
</td>
</tr></table>
<p>Retrieve a unique schema from a motif.</p>
<p>We don't want to end up with schema that match the same thing, since
this could lead to ambiguous results, and be messy. This tries to create
schema, and checks that they do not match any currently existing
schema.</p>
<dl class="fields">
</dl>
</td></tr></table>
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<a name="_schema_from_motif"></a>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">_schema_from_motif</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">motif</span>,
<span class="sig-arg">motif_list</span>,
<span class="sig-arg">num_ambiguous</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.NeuralNetwork.Gene.Schema-pysrc.html#SchemaFactory._schema_from_motif">source code</a></span>
</td>
</tr></table>
<p>Create a schema from a given starting motif.</p>
<p>Arguments:</p>
<p>o motif - A motif with the pattern we will start from.</p>
<p>o motif_list - The total motifs we have.to match to.</p>
<p>o num_ambiguous - The number of ambiguous characters that should be
present in the schema.</p>
<p>Returns:</p>
<p>o A string representing the newly generated schema.</p>
<p>o A list of all of the motifs in motif_list that match the schema.</p>
<dl class="fields">
</dl>
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