mirror of https://github.com/jlizier/jidt
151 lines
4.8 KiB
Java
Executable File
151 lines
4.8 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.discrete;
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/**
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* A base class for calculators computing measures for
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* a single variable which
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* require knowledge of the embedded past state of a univariate
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* discrete (ie int[]) variable.
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*
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* <p>This combines functionality for single agents from
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* {@link SingleAgentMeasureDiscrete} with functionality
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* required in the context of the past provided by
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* {@link ContextOfPastMeasureCalculatorDiscrete}.</p>
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*
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* <p>Usage is as defined in {@link InfoMeasureCalculatorDiscrete}, with
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* extra methods for supplying observations and making
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* calculations defined in {@link SingleAgentMeasureDiscrete}</p>.
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*
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* <p>Users should not need to deal with this class directly;
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* it is simply used to gather common functionality for several
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* child classes.
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* </p>
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*
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* TODO Make the Active info storage and entropy calculators inherit from this
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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 abstract class SingleAgentMeasureDiscreteInContextOfPastCalculator extends
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ContextOfPastMeasureCalculatorDiscrete implements SingleAgentMeasureDiscrete {
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/**
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* Construct the calculator with default base of 2 and history 1
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*/
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public SingleAgentMeasureDiscreteInContextOfPastCalculator() {
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super(2, 1);
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}
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/**
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* Construct the calculator
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*
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* @param base number of quantisation levels for each variable.
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* E.g. binary variables are in base-2.
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* @param history embedding length
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*/
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public SingleAgentMeasureDiscreteInContextOfPastCalculator(int base, int history) {
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super(base, history);
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}
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/**
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* Construct the calculator
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*
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* @param base number of quantisation levels for each variable.
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* E.g. binary variables are in base-2.
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* @param history embedding length
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* @param dontCreateObsStorage do not create storage
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* for observations of the embedded past (as the child
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* class is signalling that it does not need it)
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*/
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public SingleAgentMeasureDiscreteInContextOfPastCalculator(int base, int history, boolean dontCreateObsStorage) {
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super(base, history, dontCreateObsStorage);
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}
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@Override
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public final double[] computeLocal(int[] states) {
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initialise();
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addObservations(states);
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return computeLocalFromPreviousObservations(states);
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}
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@Override
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public final double[][] computeLocal(int[][] states) {
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initialise();
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addObservations(states);
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return computeLocalFromPreviousObservations(states);
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}
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@Override
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public final double[][][] computeLocal(int[][][] states) {
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initialise();
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addObservations(states);
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return computeLocalFromPreviousObservations(states);
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}
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@Override
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public final double computeAverageLocal(int[] states) {
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initialise();
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addObservations(states);
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return computeAverageLocalOfObservations();
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}
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@Override
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public final double computeAverageLocal(int[][] states) {
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initialise();
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addObservations(states);
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return computeAverageLocalOfObservations();
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}
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@Override
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public final double computeAverageLocal(int[][][] states) {
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initialise();
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addObservations(states);
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return computeAverageLocalOfObservations();
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}
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@Override
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public final double[] computeLocal(int[][] states, int col) {
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initialise();
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addObservations(states, col);
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return computeLocalFromPreviousObservations(states, col);
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}
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@Override
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public final double[] computeLocal(int[][][] states, int index1, int index2) {
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initialise();
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addObservations(states, index1, index2);
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return computeLocalFromPreviousObservations(states, index1, index2);
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}
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@Override
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public final double computeAverageLocal(int[][] states, int col) {
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initialise();
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addObservations(states, col);
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return computeAverageLocalOfObservations();
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}
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@Override
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public final double computeAverageLocal(int[][][] states, int index1, int index2) {
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initialise();
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addObservations(states, index1, index2);
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return computeAverageLocalOfObservations();
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}
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}
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