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<a href="Bio-module.html">Package Bio</a> ::
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<a href="Bio.GA.Selection-module.html">Package Selection</a> ::
<a href="Bio.GA.Selection.RouletteWheel-module.html">Module RouletteWheel</a> ::
Class RouletteWheelSelection
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class RouletteWheelSelection</h1><p class="nomargin-top"><span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection">source code</a></span></p>
<pre class="base-tree">
<a href="Bio.GA.Selection.Abstract.AbstractSelection-class.html">Abstract.AbstractSelection</a> --+
|
<strong class="uidshort">RouletteWheelSelection</strong>
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<p>Roulette wheel selection proportional to individuals fitness.</p>
<p>The implements a roulette wheel selector that selects individuals from
the population, and performs mutation and crossover on the selected
individuals.</p>
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<td><span class="summary-sig"><a href="Bio.GA.Selection.RouletteWheel.RouletteWheelSelection-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">mutator</span>,
<span class="summary-sig-arg">crossover</span>,
<span class="summary-sig-arg">repairer</span>=<span class="summary-sig-default">None</span>)</span><br />
Initialize the selector.</td>
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<span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection.__init__">source code</a></span>
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<td><span class="summary-sig"><a href="Bio.GA.Selection.RouletteWheel.RouletteWheelSelection-class.html#select" class="summary-sig-name">select</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">population</span>)</span><br />
Perform selection on the population based using a Roulette model.</td>
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<span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection.select">source code</a></span>
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<td><span class="summary-sig"><a href="Bio.GA.Selection.RouletteWheel.RouletteWheelSelection-class.html#_set_up_wheel" class="summary-sig-name" onclick="show_private();">_set_up_wheel</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">population</span>)</span><br />
Set up the roulette wheel based on the fitnesses.</td>
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<span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection._set_up_wheel">source code</a></span>
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<p class="indent-wrapped-lines"><b>Inherited from <code><a href="Bio.GA.Selection.Abstract.AbstractSelection-class.html">Abstract.AbstractSelection</a></code></b>:
<code><a href="Bio.GA.Selection.Abstract.AbstractSelection-class.html#mutate_and_crossover">mutate_and_crossover</a></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">mutator</span>,
<span class="sig-arg">crossover</span>,
<span class="sig-arg">repairer</span>=<span class="sig-default">None</span>)</span>
<br /><em class="fname">(Constructor)</em>
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<p>Initialize the selector.</p>
<p>Arguments:</p>
<p>o mutator -- A Mutation object which will perform mutation on an
individual.</p>
<p>o crossover -- A Crossover object which will take two individuals and
produce two new individuals which may have had crossover occur.</p>
<p>o repairer -- A class which can do repair on rearranged genomes to
eliminate infeasible individuals. If set at None, so repair will be
done.</p>
<dl class="fields">
<dt>Overrides:
<a href="Bio.GA.Selection.Abstract.AbstractSelection-class.html#__init__">Abstract.AbstractSelection.__init__</a>
</dt>
</dl>
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<a name="select"></a>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">select</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">population</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection.select">source code</a></span>
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<p>Perform selection on the population based using a Roulette model.</p>
<p>Arguments:</p>
<p>o population -- A population of organisms on which we will perform
selection. The individuals are assumed to have fitness values which are
due to their current genome.</p>
<dl class="fields">
<dt>Overrides:
<a href="Bio.GA.Selection.Abstract.AbstractSelection-class.html#select">Abstract.AbstractSelection.select</a>
</dt>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">_set_up_wheel</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">population</span>)</span>
</h3>
</td><td align="right" valign="top"
><span class="codelink"><a href="Bio.GA.Selection.RouletteWheel-pysrc.html#RouletteWheelSelection._set_up_wheel">source code</a></span>
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<p>Set up the roulette wheel based on the fitnesses.</p>
<p>This creates a fitness proportional 'wheel' that will be used for
selecting based on random numbers.</p>
<p>Returns:</p>
<p>o A dictionary where the keys are the 'high' value that an individual
will be selected. The low value is determined by the previous key in a
sorted list of keys. For instance, if we have a sorted list of keys
like:</p>
<p>[.1, .3, .7, 1]</p>
<p>Then the individual whose key is .1 will be selected if a number
between 0 and .1 is chosen, the individual whose key is .3 will be
selected if the number is between .1 and .3, and so on.</p>
<p>The values of the dictionary are the organism instances.</p>
<dl class="fields">
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