jidt/java/source/infodynamics/measures/continuous/TransferEntropyCalculatorVi...

525 lines
20 KiB
Java
Executable File

/*
* Java Information Dynamics Toolkit (JIDT)
* Copyright (C) 2012, Joseph T. Lizier
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package infodynamics.measures.continuous;
import infodynamics.utils.EmpiricalMeasurementDistribution;
import infodynamics.utils.MatrixUtils;
import java.util.Vector;
/**
*
* <p>Transfer entropy calculator which is implemented using a
* Conditional Mutual Information calculator.
* </p>
*
* TODO Delete TransferEntropyCalculatorCommon once we've switched everything over to use this?
* Might be useful to leave it after all, and move common functionality from here to there.
*
* TODO Switch the properties like l etc into TransferEntropyCalculator
* once all TE calculators follow this class.
*
* @see "Schreiber, Physical Review Letters 85 (2) pp.461-464, 2000;
* <a href='http://dx.doi.org/10.1103/PhysRevLett.85.461'>download</a>
* (for definition of transfer entropy)"
* @see "Lizier, Prokopenko and Zomaya, Physical Review E 77, 026110, 2008;
* <a href='http://dx.doi.org/10.1103/PhysRevE.77.026110'>download</a>
* (for definition of <i>local</i> transfer entropy and qualification
* of naming it as <i>apparent</i> transfer entropy)"
*
* @author Joseph Lizier, <a href="joseph.lizier at gmail.com">email</a>,
* <a href="http://lizier.me/joseph/">www</a>
*/
public abstract class TransferEntropyCalculatorViaCondMutualInfo implements
TransferEntropyCalculator {
/**
* Underlying conditional mutual information calculator
*/
protected ConditionalMutualInfoCalculatorMultiVariate condMiCalc;
/**
* Length of past destination history to consider (embedding length)
*/
protected int k = 1;
/**
* Embedding delay to use between elements of the destination embeding vector.
* We're hard-coding a delay of 1 between the history vector and the next
* observation however.
*/
protected int k_tau = 1;
/**
* Length of past source history to consider (embedding length)
*/
protected int l = 1;
/**
* Embedding delay to use between elements of the source embeding vector.
*/
protected int l_tau = 1;
/**
* Source-destination next observation delay
*/
protected int delay = 1;
/**
* Time index of the last point in the destination embedding of the first
* (destination past, source past, destination next) tuple than can be
* taken from any set of time-series observations.
*/
protected int startTimeForFirstDestEmbedding;
protected boolean debug = false;
// TODO Move these properties up the TransferEntropyCalculator once all the calcs use them
/**
* Embedding delay for the destination past history vector
*/
public static final String K_TAU_PROP_NAME = "k_TAU";
/**
* Embedding length for the source past history vector
*/
public static final String L_PROP_NAME = "l_HISTORY";
/**
* Embedding delay for the source past history vector
*/
public static final String L_TAU_PROP_NAME = "l_TAU";
/**
* Source-destination delay
*/
public static final String DELAY_PROP_NAME = "DELAY";
/**
* Construct a transfer entropy calculator using an instance of
* condMiCalculatorClassName as the underlying conditional mutual information calculator.
*
* @param condMiCalculatorClassName name of the class which must implement
* {@link ConditionalMutualInfoCalculatorMultiVariate}
* @throws InstantiationException if the given class cannot be instantiated
* @throws IllegalAccessException if illegal access occurs while trying to create an instance
* of the class
* @throws ClassNotFoundException if the given class is not found
*/
public TransferEntropyCalculatorViaCondMutualInfo(String condMiCalculatorClassName)
throws InstantiationException, IllegalAccessException, ClassNotFoundException {
@SuppressWarnings("unchecked")
Class<ConditionalMutualInfoCalculatorMultiVariate> condMiClass =
(Class<ConditionalMutualInfoCalculatorMultiVariate>) Class.forName(condMiCalculatorClassName);
ConditionalMutualInfoCalculatorMultiVariate condMiCalc = condMiClass.newInstance();
construct(condMiCalc);
}
/**
* Construct a transfer entropy calculator using an instance of
* condMiCalcClass as the underlying conditional mutual information calculator.
*
* @param condMiCalcClass the class which must implement
* {@link ConditionalMutualInfoCalculatorMultiVariate}
* @throws InstantiationException if the given class cannot be instantiated
* @throws IllegalAccessException if illegal access occurs while trying to create an instance
* of the class
* @throws ClassNotFoundException if the given class is not found
*/
public TransferEntropyCalculatorViaCondMutualInfo(Class<ConditionalMutualInfoCalculatorMultiVariate> condMiCalcClass)
throws InstantiationException, IllegalAccessException, ClassNotFoundException {
ConditionalMutualInfoCalculatorMultiVariate condMiCalc = condMiCalcClass.newInstance();
construct(condMiCalc);
}
/**
* Construct this calculator by passing in a constructed but not initialised
* underlying Conditional Mutual information calculator.
*
* @param condMiCalc An instantiated conditional mutual information calculator.
* @throws Exception if the supplied calculator has not yet been instantiated.
*/
public TransferEntropyCalculatorViaCondMutualInfo(ConditionalMutualInfoCalculatorMultiVariate condMiCalc) throws Exception {
if (condMiCalc == null) {
throw new Exception("Conditional MI calculator used to construct ConditionalTransferEntropyCalculatorViaCondMutualInfo " +
" must have already been instantiated.");
}
construct(condMiCalc);
}
/**
* Internal method to set the conditional mutual information calculator.
* Can be overridden if anything else needs to be done with it by the child classes.
*
* @param condMiCalc
*/
protected void construct(ConditionalMutualInfoCalculatorMultiVariate condMiCalc) {
this.condMiCalc = condMiCalc;
}
/* (non-Javadoc)
* @see infodynamics.measures.continuous.ChannelCalculatorCommon#initialise()
*/
public void initialise() throws Exception {
initialise(k, k_tau, l, l_tau, delay);
}
public void initialise(int k) throws Exception {
initialise(k, k_tau, l, l_tau, delay);
}
/**
* Initialise the calculator
*
* @param k Length of destination past history to consider
* @param k_tau embedding delay for the destination variable
* @param l length of source past history to consider
* @param l_tau embedding delay for the source variable
* @param delay time lag between last element of source and destination next value
*/
public void initialise(int k, int k_tau, int l, int l_tau, int delay) throws Exception {
if (delay < 0) {
throw new Exception("Cannot compute TE with source-destination delay < 0");
}
this.k = k;
this.k_tau = k_tau;
this.l = l;
this.l_tau = l_tau;
this.delay = delay;
// Now check which point we can start taking observations from in any
// addObservations call. These two integers represent the last
// point of the destination embedding, in the cases where the destination
// embedding itself determines where we can start taking observations, or
// the case where the source embedding plus delay is longer and so determines
// where we can start taking observations.
int startTimeBasedOnDestPast = (k-1)*k_tau;
int startTimeBasedOnSourcePast = (l-1)*l_tau + delay - 1;
startTimeForFirstDestEmbedding = Math.max(startTimeBasedOnDestPast, startTimeBasedOnSourcePast);
condMiCalc.initialise(l, 1, k);
}
/**
* <p>Set the given property to the given value.
* New property values are not guaranteed to take effect until the next call
* to an initialise method.
* These can include:
* <ul>
* <li>{@link #K_PROP_NAME}</li>
* <li>{@link #K_TAU_PROP_NAME}</li>
* <li>{@link #L_PROP_NAME}</li>
* <li>{@link #L_TAU_PROP_NAME}</li>
* <li>{@link #DELAY_PROP_NAME}</li>
* </ul>
* Or else it is assumed the property
* is for the underlying {@link ConditionalMutualInfoCalculatorMultiVariate#setProperty(String, String)} implementation.
*
* @param propertyName name of the property
* @param propertyValue value of the property.
* @throws Exception if there is a problem with the supplied value
*/
public void setProperty(String propertyName, String propertyValue) throws Exception {
boolean propertySet = true;
if (propertyName.equalsIgnoreCase(K_PROP_NAME)) {
k = Integer.parseInt(propertyValue);
} else if (propertyName.equalsIgnoreCase(K_TAU_PROP_NAME)) {
k_tau = Integer.parseInt(propertyValue);
} else if (propertyName.equalsIgnoreCase(L_PROP_NAME)) {
l = Integer.parseInt(propertyValue);
} else if (propertyName.equalsIgnoreCase(L_TAU_PROP_NAME)) {
l_tau = Integer.parseInt(propertyValue);
} else if (propertyName.equalsIgnoreCase(DELAY_PROP_NAME)) {
delay = Integer.parseInt(propertyValue);
} else {
// No property was set on this class, assume it is for the underlying
// conditional MI calculator
condMiCalc.setProperty(propertyName, propertyValue);
propertySet = false;
}
if (debug && propertySet) {
System.out.println(this.getClass().getSimpleName() + ": Set property " + propertyName +
" to " + propertyValue);
}
}
/**
* <p>Sets the single set of observations to compute the PDFs from.
* Cannot be called in conjunction with
* {@link #startAddObservations()}/{@link #addObservations(double[], double[])} /
* {@link #finaliseAddObservations()}.</p>
*
* @param source observations for the source variable
* @param destination observations for the destination variable
* @throws Exception
*/
public void setObservations(double[] source, double[] destination) throws Exception {
if (source.length != destination.length) {
throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
source.length, destination.length));
}
if (source.length < startTimeForFirstDestEmbedding + 2) {
// There are no observations to add here, the time series is too short
throw new Exception("Not enough observations to set here given k, k_tau, l, l_tau and delay parameters");
}
double[][] currentDestPastVectors =
MatrixUtils.makeDelayEmbeddingVector(destination, k, k_tau,
startTimeForFirstDestEmbedding,
destination.length - startTimeForFirstDestEmbedding - 1);
double[][] currentDestNextVectors =
MatrixUtils.makeDelayEmbeddingVector(destination, 1,
startTimeForFirstDestEmbedding + 1,
destination.length - startTimeForFirstDestEmbedding - 1);
double[][] currentSourcePastVectors =
MatrixUtils.makeDelayEmbeddingVector(source, l, l_tau,
startTimeForFirstDestEmbedding + 1 - delay,
source.length - startTimeForFirstDestEmbedding - 1);
condMiCalc.setObservations(currentSourcePastVectors, currentDestNextVectors, currentDestPastVectors);
}
public void startAddObservations() {
condMiCalc.startAddObservations();
}
public void addObservations(double[] source, double[] destination) throws Exception {
if (source.length != destination.length) {
throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
source.length, destination.length));
}
if (source.length < startTimeForFirstDestEmbedding + 2) {
// There are no observations to add here, the time series is too short
// Don't throw an exception, do nothing since more observations
// can be added later.
return;
}
double[][] currentDestPastVectors =
MatrixUtils.makeDelayEmbeddingVector(destination, k, k_tau,
startTimeForFirstDestEmbedding,
destination.length - startTimeForFirstDestEmbedding - 1);
double[][] currentDestNextVectors =
MatrixUtils.makeDelayEmbeddingVector(destination, 1,
startTimeForFirstDestEmbedding + 1,
destination.length - startTimeForFirstDestEmbedding - 1);
double[][] currentSourcePastVectors =
MatrixUtils.makeDelayEmbeddingVector(source, l, l_tau,
startTimeForFirstDestEmbedding + 1 - delay,
source.length - startTimeForFirstDestEmbedding - 1);
condMiCalc.addObservations(currentSourcePastVectors, currentDestNextVectors, currentDestPastVectors);
}
public void addObservations(double[] source, double[] destination,
int startTime, int numTimeSteps) throws Exception {
if (source.length != destination.length) {
throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
source.length, destination.length));
}
if (source.length < startTime + numTimeSteps) {
// There are not enough observations given the arguments here
throw new Exception("Not enough observations to set here given startTime and numTimeSteps parameters");
}
addObservations(MatrixUtils.select(source, startTime, numTimeSteps),
MatrixUtils.select(destination, startTime, numTimeSteps));
}
public void finaliseAddObservations() throws Exception {
condMiCalc.finaliseAddObservations();
}
public void setObservations(double[] source, double[] destination,
boolean[] sourceValid, boolean[] destValid) throws Exception {
Vector<int[]> startAndEndTimePairs = computeStartAndEndTimePairs(sourceValid, destValid);
// We've found the set of start and end times for this pair
startAddObservations();
for (int[] timePair : startAndEndTimePairs) {
int startTime = timePair[0];
int endTime = timePair[1];
addObservations(source, destination, startTime, endTime - startTime + 1);
}
finaliseAddObservations();
}
/**
* Compute a vector of start and end pairs of time points, between which we have
* valid series of both source and destinations. (i.e. all points within the
* embedding vectors must be valid, even if the invalid points won't be included
* in any tuples)
*
* Made public so it can be used if one wants to compute the number of
* observations prior to setting the observations.
*
* @param sourceValid
* @param destValid
* @return
* @throws Exception
*/
public Vector<int[]> computeStartAndEndTimePairs(boolean[] sourceValid, boolean[] destValid) throws Exception {
if (sourceValid.length != destValid.length) {
throw new Exception("Validity arrays must be of same length");
}
int lengthOfDestPastRequired = (k-1)*k_tau + 1;
int lengthOfSourcePastRequired = (l-1)*l_tau + 1;
// int numSourcePointsBeforeDestStart = delay - 1 + lengthOfSourcePastRequired
// - lengthOfDestPastRequired;
// Scan along the data avoiding invalid values
int startTime = 0;
Vector<int[]> startAndEndTimePairs = new Vector<int[]>();
// Simple solution -- this takes more complexity in time, but is
// much faster to code:
boolean previousWasOk = false;
for (int t = startTimeForFirstDestEmbedding; t < destValid.length - 1; t++) {
// Check the tuple with the history vector starting from
// t and running backwards
if (previousWasOk) {
// Just check the very next values of each:
if (destValid[t + 1] && sourceValid[t + 1 - delay]) {
// We can continue adding to this sequence
continue;
} else {
// We need to shut down this sequence now
previousWasOk = false;
int[] timePair = new int[2];
timePair[0] = startTime;
timePair[1] = t; // Previous time step was last valid one
startAndEndTimePairs.add(timePair);
continue;
}
}
// Otherwise we're trying to start a new sequence, so check all values
if (!destValid[t + 1]) {
continue;
}
boolean allOk = true;
for (int tBack = 0; tBack < lengthOfDestPastRequired; tBack++) {
if (!destValid[t - tBack]) {
allOk = false;
break;
}
}
if (!allOk) {
continue;
}
allOk = true;
for (int tBack = delay - 1; tBack < delay - 1 + lengthOfSourcePastRequired; tBack++) {
if (!sourceValid[t - tBack]) {
allOk = false;
break;
}
}
if (!allOk) {
continue;
}
// Postcondition: We've got a first valid tuple:
startTime = t - startTimeForFirstDestEmbedding;
previousWasOk = true;
}
// Now check if we were running a sequence and terminate it:
if (previousWasOk) {
// We need to shut down this sequence now
previousWasOk = false;
int[] timePair = new int[2];
timePair[0] = startTime;
timePair[1] = destValid.length - 1;
startAndEndTimePairs.add(timePair);
}
return startAndEndTimePairs;
}
public double computeAverageLocalOfObservations() throws Exception {
return condMiCalc.computeAverageLocalOfObservations();
}
/**
* Returns a time series of local TE values.
* Pads the first startTimeForFirstDestEmbedding elements with zeros (since local TE is undefined here)
* if only one time series of observations was used.
* Otherwise, local values for all separate series are concatenated, and without
* padding of zeros at the start.
*
* @return an array of local TE values of the previously submitted observations.
*/
public double[] computeLocalOfPreviousObservations() throws Exception {
double[] local = condMiCalc.computeLocalOfPreviousObservations();
if (!condMiCalc.getAddedMoreThanOneObservationSet()) {
double[] localsToReturn = new double[local.length + startTimeForFirstDestEmbedding + 1];
System.arraycopy(local, 0, localsToReturn, startTimeForFirstDestEmbedding + 1, local.length);
return localsToReturn;
} else {
return local;
}
}
public double[] computeLocalUsingPreviousObservations(double[] newSourceObservations, double[] newDestObservations) throws Exception {
if (newSourceObservations.length != newDestObservations.length) {
throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
newSourceObservations.length, newDestObservations.length));
}
if (newDestObservations.length < startTimeForFirstDestEmbedding + 2) {
// There are no observations to compute for here
return new double[newDestObservations.length];
}
double[][] newDestPastVectors =
MatrixUtils.makeDelayEmbeddingVector(newDestObservations, k, k_tau,
startTimeForFirstDestEmbedding,
newDestObservations.length - startTimeForFirstDestEmbedding - 1);
double[][] newDestNextVectors =
MatrixUtils.makeDelayEmbeddingVector(newDestObservations, 1,
startTimeForFirstDestEmbedding + 1,
newDestObservations.length - startTimeForFirstDestEmbedding - 1);
double[][] newSourcePastVectors =
MatrixUtils.makeDelayEmbeddingVector(newSourceObservations, l, l_tau,
startTimeForFirstDestEmbedding + 1 - delay,
newSourceObservations.length - startTimeForFirstDestEmbedding - 1);
double[] local = condMiCalc.computeLocalUsingPreviousObservations(
newSourcePastVectors, newDestNextVectors, newDestPastVectors);
// Pad the front of the array with zeros where local TE isn't defined:
double[] localsToReturn = new double[local.length + startTimeForFirstDestEmbedding + 1];
System.arraycopy(local, 0, localsToReturn, startTimeForFirstDestEmbedding + 1, local.length);
return localsToReturn;
}
public EmpiricalMeasurementDistribution computeSignificance(
int numPermutationsToCheck) throws Exception {
return condMiCalc.computeSignificance(1, numPermutationsToCheck); // Reorder the source
}
public EmpiricalMeasurementDistribution computeSignificance(
int[][] newOrderings) throws Exception {
return condMiCalc.computeSignificance(1, newOrderings); // Reorder the source
}
public double getLastAverage() {
return condMiCalc.getLastAverage();
}
public int getNumObservations() throws Exception {
return condMiCalc.getNumObservations();
}
public boolean getAddedMoreThanOneObservationSet() {
return condMiCalc.getAddedMoreThanOneObservationSet();
}
public void setDebug(boolean debug) {
this.debug = debug;
condMiCalc.setDebug(debug);
}
}