mirror of https://github.com/jlizier/jidt
79 lines
2.9 KiB
Java
Executable File
79 lines
2.9 KiB
Java
Executable File
/*
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* Java Information Dynamics Toolkit (JIDT)
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* Copyright (C) 2012, Joseph T. Lizier
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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package infodynamics.measures.continuous;
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/**
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* Interface for implementations of
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* entropy estimators on continuous univariate data
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* (ie <code>double[]</code> arrays).
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*
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* <p>
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* Usage of the child classes implementing this interface is intended to follow this paradigm:
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* </p>
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* <ol>
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* <li>Construct the calculator;</li>
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* <li>Set properties using {@link #setProperty(String, String)};</li>
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* <li>Initialise the calculator {@link #initialise()};</li>
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* <li>Provide the observations/samples for the calculator
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* to set up the PDFs, using: {@link #setObservations(double[])};</li>
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* <li>Compute the entropy using:
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* {@link #computeAverageLocalOfObservations()};</li>
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* <li>Return to step 2 or 3 to re-use the calculator on a new data set.</li>
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* </ol>
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*
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* <p><b>References:</b><br/>
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* <ul>
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* <li>T. M. Cover and J. A. Thomas, 'Elements of Information
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Theory' (John Wiley & Sons, New York, 1991).</li>
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* </ul>
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*
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* @author Joseph Lizier (<a href="joseph.lizier at gmail.com">email</a>,
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* <a href="http://lizier.me/joseph/">www</a>)
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*/
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public interface EntropyCalculator extends InfoMeasureCalculatorContinuous {
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// TODO Add addObservations() methods for entropy calculator.
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// It's currently in EntropyCalculatorMultivariate; bring in
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// here when we make all univariate entropy calculators use their
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// underlying multivariate form.
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/**
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* Sets the samples from which to compute the PDF for the entropy.
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* Should only be called once, the last call contains the
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* observations that are used (they are not accumulated).
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*
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* @param observations array of (univariate) samples
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* @throws Exception
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*/
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public void setObservations(double observations[]) throws Exception;
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/**
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* Compute the local entropy values for each of the
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* previously-supplied samples.
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*
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* <p>PDFs are computed using all of the previously supplied
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* observations.</p>
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*
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* @return the array of local entropy values corresponding to each
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* previously supplied observation.
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*/
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public double[] computeLocalOfPreviousObservations() throws Exception;
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}
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