mirror of https://github.com/jlizier/jidt
107 lines
4.7 KiB
Java
Executable File
107 lines
4.7 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 Active Information Storage estimators on
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* multivariate continuous time-series data. That is, it is applied to
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* <code>double[][]</code> data, indexed first by time then by variable number.
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*
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* <p>See definition of Active Information Storage (AIS) by Lizier et al. below.
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* Basically, AIS is the mutual information between the past <i>state</i>
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* of a time-series process <i>X</i> and its next value. The past <i>state</i> at time <code>n</code>
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* is represented by an embedding vector of <code>k</code> values from <code>X_n</code> backwards,
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* each separated by <code>\tau</code> steps, giving
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* <code><b>X^k_n</b> = [ X_{n-(k-1)\tau}, ... , X_{n-\tau}, X_n]</code>.
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* We call <code>k</code> the embedding dimension, and <code>\tau</code>
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* the embedding delay.
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* AIS is then the mutual information between <b>X^k_n</b> and X_{n+1}.</p>
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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 using {@link #initialise(int)} or
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* {@link #initialise(int, int)} or {@link #initialise(int, int, int)};
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* </li>
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* <li>Provide the observations/samples for the calculator
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* to set up the PDFs, using:
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* <ul>
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* <li>{@link #setObservations(double[][])} for calculations
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* based on single time-series, OR</li>
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* <li>The following sequence:<ol>
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* <li>{@link #startAddObservations()}, then</li>
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* <li>One or more calls to {@link #addObservations(double[][])} or
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* {@link #addObservations(double[][], int, int)}, then</li>
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* <li>{@link #finaliseAddObservations()};</li>
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* </ol></li>
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* </ul>
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* </li>
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* <li>Compute the required quantities, being one or more of:
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* <ul>
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* <li>the average AIS: {@link #computeAverageLocalOfObservations()};</li>
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* <li>the local AIS values for these samples: {@link #computeLocalOfPreviousObservations()}</li>
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* <li>local AIS values for a specific set of samples: {@link #computeLocalUsingPreviousObservations(double[])}</li>
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* <li>the distribution of AIS values under the null hypothesis
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* of no relationship between past sequences in the series
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* and the next value: {@link #computeSignificance(int)} or
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* {@link #computeSignificance(int[][])}.</li>
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* </ul>
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* </li>
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* <li>
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* Return to step 2 or 3 to re-use the calculator on a new data set.
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* </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>J.T. Lizier, M. Prokopenko and A.Y. Zomaya,
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* <a href="http://dx.doi.org/10.1016/j.ins.2012.04.016">
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* "Local measures of information storage in complex distributed computation"</a>,
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* Information Sciences, vol. 208, pp. 39-54, 2012.</li>
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* </ul>
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*
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* @author Pedro AM Mediano (<a href="pmediano at imperial.ac.uk">email</a>,
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* <a href="https://www.doc.ic.ac.uk/~pam213/">www</a>)
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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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* @see ActiveInfoStorageCalculator
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*/
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public interface ActiveInfoStorageCalculatorMultiVariate {
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/**
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* Initialise the calculator for re-use with new observations.
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* History length k, source and destination dimensions are
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* specified here; all other parameters remain unchanged.
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*
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* @param dimensions number of joint variables in the system.
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* @param k history embedding length to be considered.
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* @param tau history embedding delay to be considered.
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* @throws Exception
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*/
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public void initialise(int dimensions, int k, int tau) throws Exception;
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// TODO We seem to be missing a lot of functionality which should be defined here,
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// as implemented in the univariate measure. will have to go back and do this.
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}
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