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<div class="subTitle">jcgp.backend.statistics</div>
<h2 title="Class StatisticsLogger" class="title">Class StatisticsLogger</h2>
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<li>java.lang.Object</li>
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<pre>public class <span class="typeNameLabel">StatisticsLogger</span>
extends java.lang.Object</pre>
<div class="block">This is a utility class for logging experiment statistics when doing multiple runs.
<br><br>
Information about each run is added via the <code>logRun()</code> method. The many getters
can be used to obtain statistics about the logged runs, such as success rate and average
fitness.
<br><br>
<code>JCGP</code> uses this class to perform its logging and print out experiment data at the end.</div>
<dl>
<dt><span class="simpleTagLabel">Author:</span></dt>
<dd>Eduardo Pedroni</dd>
</dl>
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#StatisticsLogger--">StatisticsLogger</a></span>()</code>
<div class="block">Create a new statistics logger, use this when resetting is necessary.</div>
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<th class="colFirst" scope="col">Modifier and Type</th>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageActiveNodes--">getAverageActiveNodes</a></span>()</code>
<div class="block">Averages the number of active nodes in the
best chromosomes obtained across all runs.</div>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageActiveNodesStdDev--">getAverageActiveNodesStdDev</a></span>()</code>
<div class="block">Calculates the standard deviation of
the number of active nodes in the best solution
in each run.</div>
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<tr id="i2" class="altColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageFitness--">getAverageFitness</a></span>()</code>
<div class="block">Averages the best fitness obtained in each run.</div>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageFitnessStdDev--">getAverageFitnessStdDev</a></span>()</code>
<div class="block">Calculates the standard deviation of
the best fitness obtained in each run.</div>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageGenerations--">getAverageGenerations</a></span>()</code>
<div class="block">Calculates the average generation out of all runs.</div>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageGenerationsStdDev--">getAverageGenerationsStdDev</a></span>()</code>
<div class="block">Calculates the standard deviation of
the average number of generations in
each run.</div>
</td>
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<tr id="i6" class="altColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageSuccessfulGenerations--">getAverageSuccessfulGenerations</a></span>()</code>
<div class="block">Calculates the average generation out of successful runs only.</div>
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<tr id="i7" class="rowColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getAverageSuccessfulGenerationsStdDev--">getAverageSuccessfulGenerationsStdDev</a></span>()</code>
<div class="block">Calculates the standard deviation of
the average number of generations in
each run where a perfect solution was found.</div>
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<tr id="i8" class="altColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getHighestFitness--">getHighestFitness</a></span>()</code> </td>
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<tr id="i9" class="rowColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getLowestFitness--">getLowestFitness</a></span>()</code> </td>
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<td class="colFirst"><code>int</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getSuccessfulRuns--">getSuccessfulRuns</a></span>()</code> </td>
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<tr id="i11" class="rowColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#getSuccessRate--">getSuccessRate</a></span>()</code>
<div class="block">Calculates the ratio of successful runs (runs where
a perfect solution was found) to total number of runs.</div>
</td>
</tr>
<tr id="i12" class="altColor">
<td class="colFirst"><code>void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../jcgp/backend/statistics/StatisticsLogger.html#logRun-int-double-int-boolean-">logRun</a></span>(int generation,
double fitness,
int active,
boolean successful)</code>
<div class="block">Log a new run.</div>
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<code>equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait</code></li>
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<h4>StatisticsLogger</h4>
<pre>public StatisticsLogger()</pre>
<div class="block">Create a new statistics logger, use this when resetting is necessary.</div>
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<h4>logRun</h4>
<pre>public void logRun(int generation,
double fitness,
int active,
boolean successful)</pre>
<div class="block">Log a new run. Calling any of the statistics getters will
now take this logged run into account as well as all previously
logged runs.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>generation</code> - the last generation when improvement occurred.</dd>
<dd><code>fitness</code> - the best fitness achieved in the run.</dd>
<dd><code>active</code> - the number of active nodes in the best chromosome found.</dd>
<dd><code>successful</code> - true if a perfect solution was found, false if otherwise.</dd>
</dl>
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<h4>getAverageFitness</h4>
<pre>public double getAverageFitness()</pre>
<div class="block">Averages the best fitness obtained in each run.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the average fitness.</dd>
</dl>
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<h4>getAverageFitnessStdDev</h4>
<pre>public double getAverageFitnessStdDev()</pre>
<div class="block">Calculates the standard deviation of
the best fitness obtained in each run.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the standard deviation of average fitnesses.</dd>
</dl>
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<h4>getAverageActiveNodes</h4>
<pre>public double getAverageActiveNodes()</pre>
<div class="block">Averages the number of active nodes in the
best chromosomes obtained across all runs.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the average number of active nodes.</dd>
</dl>
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<h4>getAverageActiveNodesStdDev</h4>
<pre>public double getAverageActiveNodesStdDev()</pre>
<div class="block">Calculates the standard deviation of
the number of active nodes in the best solution
in each run.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the standard deviation of active node counts.</dd>
</dl>
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<h4>getAverageGenerations</h4>
<pre>public double getAverageGenerations()</pre>
<div class="block">Calculates the average generation out of all runs.
The generation value in each run corresponds to the
last generation in which improvement happened.
<br><br>
Note that this method includes runs where no perfect
solution was found. For the average number of generations
for perfect solutions only, use <code>getAverageSuccessfulGenerations</code>.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the average number of generations.</dd>
</dl>
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<pre>public double getAverageGenerationsStdDev()</pre>
<div class="block">Calculates the standard deviation of
the average number of generations in
each run.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the standard deviation of the number of generations.</dd>
</dl>
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<pre>public double getHighestFitness()</pre>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the highest fitness across all runs.</dd>
</dl>
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<h4>getLowestFitness</h4>
<pre>public double getLowestFitness()</pre>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the lowest fitness across all runs.</dd>
</dl>
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<h4>getSuccessfulRuns</h4>
<pre>public int getSuccessfulRuns()</pre>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the number of runs in which a perfect solution was found.</dd>
</dl>
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<h4>getSuccessRate</h4>
<pre>public double getSuccessRate()</pre>
<div class="block">Calculates the ratio of successful runs (runs where
a perfect solution was found) to total number of runs.
A double-precision value between 0 and 1 is returned,
where 0 means 0% success rate and 1 means 100% success rate.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the success rate across all runs.</dd>
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<pre>public double getAverageSuccessfulGenerations()</pre>
<div class="block">Calculates the average generation out of successful runs only.
The generation value in each successful run corresponds to the
generation in which the perfect solution was found.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the average number of generations for perfect solutions.</dd>
</dl>
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<pre>public double getAverageSuccessfulGenerationsStdDev()</pre>
<div class="block">Calculates the standard deviation of
the average number of generations in
each run where a perfect solution was found.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>the standard deviation of the number of generations in successful runs.</dd>
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