mirror of https://github.com/jlizier/jidt
Added addObservations-related methods to multivariate TE calculators.
This is needed to implement auto-embedding methods later.
This commit is contained in:
Pedro Martinez Mediano
parent
fa0bc96a6f
commit
75bb2c814a
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@ -18,10 +18,11 @@
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package infodynamics.measures.continuous;
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import java.util.Vector;
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import infodynamics.utils.MatrixUtils;
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import java.util.Iterator;
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import java.util.Vector;
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/**
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* A Multivariate Transfer Entropy (TE) calculator (implementing
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* {@link TransferEntropyCalculatorMultiVariate})
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@ -85,6 +86,15 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
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* Number of dimensions of the source
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*/
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protected int sourceDimensions = 1;
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/**
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* Storage for source observations supplied via {@link #addObservations(double[][], double[][])} etc.
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*/
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protected Vector<double[][]> vectorOfMultiVariateSourceTimeSeries;
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/**
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* Storage for destination observations supplied via {@link #addObservations(double[][], double[][])} etc.
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*/
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protected Vector<double[][]> vectorOfMultiVariateDestinationTimeSeries;
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/**
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* Construct a transfer entropy calculator using an instance of
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@ -239,7 +249,10 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
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return;
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}
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// Otherwise initialise ourselves:
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condMiCalc.startAddObservations();
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vectorOfMultiVariateSourceTimeSeries = new Vector<double[][]>();
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vectorOfMultiVariateDestinationTimeSeries = new Vector<double[][]>();
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vectorOfValidityOfSource = new Vector<boolean[]>();
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vectorOfValidityOfDestination = new Vector<boolean[]>();
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}
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/**
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@ -263,43 +276,92 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
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}
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super.addObservations(source, destination);
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}
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/* (non-Javadoc)
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* @see infodynamics.measures.continuous.ChannelCalculatorMultiVariate#addObservations(double[][], double[][])
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*/
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@Override
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public void addObservations(double[][] source, double[][] destination)
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throws Exception {
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if (source.length != destination.length) {
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throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
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source.length, destination.length));
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}
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if ((sourceDimensions == 1) && (destDimensions == 1)) {
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// We'll be using the superclass for the computation
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super.addObservations(MatrixUtils.selectColumn(source, 0),
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MatrixUtils.selectColumn(destination, 0));
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return;
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}
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if (source.length < startTimeForFirstDestEmbedding + 2) {
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// There are no observations to add here, the time series is too short
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// Don't throw an exception, do nothing since more observations
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// can be added later.
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return;
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}
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double[][] currentDestPastVectors =
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MatrixUtils.makeDelayEmbeddingVector(destination, k, k_tau,
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startTimeForFirstDestEmbedding,
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destination.length - startTimeForFirstDestEmbedding - 1);
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double[][] currentDestNextVectors =
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MatrixUtils.makeDelayEmbeddingVector(destination, 1,
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startTimeForFirstDestEmbedding + 1,
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destination.length - startTimeForFirstDestEmbedding - 1);
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double[][] currentSourcePastVectors =
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MatrixUtils.makeDelayEmbeddingVector(source, l, l_tau,
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startTimeForFirstDestEmbedding + 1 - delay,
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source.length - startTimeForFirstDestEmbedding - 1);
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condMiCalc.addObservations(currentSourcePastVectors, currentDestNextVectors, currentDestPastVectors);
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}
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@Override
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public void addObservations(double[][] source, double[][] destination)
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throws Exception {
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// Store these observations in our vector for now
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vectorOfMultiVariateSourceTimeSeries.add(source);
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vectorOfMultiVariateDestinationTimeSeries.add(destination);
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vectorOfValidityOfSource.add(null); // All observations were valid
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vectorOfValidityOfDestination.add(null); // All observations were valid
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}
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/**
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* Protected method to internally parse and submit observations through
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* to the underlying conditional MI calculator once any internal parameter settings
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* have been finalised (in the case of automatically determining the embedding
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* parameters)
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*
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* @param source time series of source observations
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* @param destination time series of destination observations
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* @return the number of observations added
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* @throws Exception
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*/
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protected int addObservationsAfterParamsDetermined(double[][] source, double[][] destination) throws Exception {
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if (source.length != destination.length) {
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throw new Exception(String.format("Source and destination lengths (%d and %d) must match!",
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source.length, destination.length));
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}
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if (source.length < startTimeForFirstDestEmbedding + 2) {
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// There are no observations to add here, the time series is too short
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// Don't throw an exception, do nothing since more observations
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// can be added later.
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return 0;
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}
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double[][] currentDestPastVectors =
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MatrixUtils.makeDelayEmbeddingVector(destination, k, k_tau,
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startTimeForFirstDestEmbedding,
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destination.length - startTimeForFirstDestEmbedding - 1);
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double[][] currentDestNextVectors =
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MatrixUtils.makeDelayEmbeddingVector(destination, 1,
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startTimeForFirstDestEmbedding + 1,
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destination.length - startTimeForFirstDestEmbedding - 1);
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double[][] currentSourcePastVectors =
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MatrixUtils.makeDelayEmbeddingVector(source, l, l_tau,
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startTimeForFirstDestEmbedding + 1 - delay,
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source.length - startTimeForFirstDestEmbedding - 1);
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condMiCalc.addObservations(currentSourcePastVectors, currentDestNextVectors, currentDestPastVectors);
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return destination.length - startTimeForFirstDestEmbedding - 1;
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}
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/**
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* Protected method to internally parse and submit observations through
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* to the underlying conditional MI calculator once any internal parameter settings
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* have been finalised (in the case of automatically determining the embedding
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* parameters)
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* This is done given time-series of booleans indicating whether each entry
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* is valid
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*
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* @param source time series of source observations
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* @param destination time series of destination observations
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* @param sourceValid array (with indices the same as source) indicating whether
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* the source at that index is valid.
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* @param destValid array (with indices the same as destination) indicating whether
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* the destination at that index is valid.
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* @return total number of observations added
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* @throws Exception
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*/
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protected int addObservationsAfterParamsDetermined(double[][] source, double[][] destination,
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boolean[] sourceValid, boolean[] destValid) throws Exception {
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// Compute the start and end time pairs using our embedding parameters:
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Vector<int[]> startAndEndTimePairs = computeStartAndEndTimePairs(sourceValid, destValid);
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int totalObservationsAdded = 0;
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for (int[] timePair : startAndEndTimePairs) {
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int startTime = timePair[0];
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int endTime = timePair[1];
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totalObservationsAdded += addObservationsAfterParamsDetermined(
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MatrixUtils.selectRows(source, startTime, endTime - startTime + 1),
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MatrixUtils.selectRows(destination, startTime, endTime - startTime + 1));
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}
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return totalObservationsAdded;
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}
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/**
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* <p>Adds a new sub-series of <b>univariate</b> observations to compute the PDFs from.
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@ -384,7 +446,7 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
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sourceValid, destValid);
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return;
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}
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Vector<int[]> startAndEndTimePairs = computeStartAndEndTimePairs(sourceValid, destValid);
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// We've found the set of start and end times for this pair
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@ -425,6 +487,39 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
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return;
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}
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// Otherwise finalise ourselves:
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// Auto embed if required
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preFinaliseAddObservations();
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// Initialise the conditional MI calculator, including any auto-embedding length
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condMiCalc.initialise(l*sourceDimensions, destDimensions, k*destDimensions);
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condMiCalc.startAddObservations();
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// Send all of the observations through:
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Iterator<double[][]> destIterator = vectorOfMultiVariateDestinationTimeSeries.iterator();
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Iterator<boolean[]> sourceValidityIterator = vectorOfValidityOfSource.iterator();
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Iterator<boolean[]> destValidityIterator = vectorOfValidityOfDestination.iterator();
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separateNumObservations = new int[vectorOfMultiVariateDestinationTimeSeries.size()];
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int setNum = 0;
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for (double[][] source : vectorOfMultiVariateSourceTimeSeries) {
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double[][] destination = destIterator.next();
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boolean[] sourceValidity = sourceValidityIterator.next();
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boolean[] destValidity = destValidityIterator.next();
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int observationsAddedThisTime = 0;
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if (sourceValidity == null) {
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// Add the whole time-series
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observationsAddedThisTime = addObservationsAfterParamsDetermined(source, destination);
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} else {
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observationsAddedThisTime = addObservationsAfterParamsDetermined(source, destination,
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sourceValidity, destValidity);
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}
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separateNumObservations[setNum++] = observationsAddedThisTime;
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}
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vectorOfMultiVariateSourceTimeSeries = null; // No longer required
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vectorOfMultiVariateDestinationTimeSeries = null; // No longer required
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vectorOfValidityOfSource = null;
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vectorOfValidityOfDestination = null;
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// TODO do we need to throw an exception if there are no observations to add?
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condMiCalc.finaliseAddObservations();
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}
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