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Adding overloads on setObservations and addObservations for MI and TE calculators to handle one variable univariate and one variable multivariate

This commit is contained in:
Joseph Lizier 2021-11-15 10:58:59 +11:00
parent 8e55cf05d9
commit b02760ddd3
4 changed files with 236 additions and 0 deletions
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94
java/source/infodynamics/measures/continuous/ChannelCalculatorMultiVariate.java
View File

@ -73,6 +73,46 @@ public interface ChannelCalculatorMultiVariate extends ChannelCalculatorCommon {
*/
public void setObservations(double[][] source, double[][] destination) throws Exception;
/**
* Sets a single series from which to compute the PDF for the channel measure --
* available ONLY if sourceDimensions was initialised
* to 1.
* Cannot be called in conjunction with other methods for setting/adding
* observations.
*
* <p>The supplied series are certainly (multivariate) time-series for time-series measures
* such as transfer entropy, however may be simply a set of separate observations
* for the mutual information without a time interpretation.
*
* @param source series of univariate observations for the source variable
* (first index is time or observation index, second is variable number)
* @param destination series of multivariate observations for the destination variable
* (first index is time or observation index, second is variable number).
* Length must match <code>source</code>, and their indices must correspond.
* @throws Exception
*/
public void setObservations(double[] source, double[][] destination) throws Exception;
/**
* Sets a single series from which to compute the PDF for the channel measure --
* available ONLY if destDimensions was initialised
* to 1.
* Cannot be called in conjunction with other methods for setting/adding
* observations.
*
* <p>The supplied series are certainly (multivariate) time-series for time-series measures
* such as transfer entropy, however may be simply a set of separate observations
* for the mutual information without a time interpretation.
*
* @param source series of multivariate observations for the source variable
* (first index is time or observation index, second is variable number)
* @param destination series of univariate observations for the destination variable
* (first index is time or observation index, second is variable number).
* Length must match <code>source</code>, and their indices must correspond.
* @throws Exception
*/
public void setObservations(double[][] source, double[] destination) throws Exception;
/**
* Sets a single pair of univariate series from which to compute the PDF for the channel measure --
* available ONLY if both sourceDimensions and destDimensions were initialised
@ -126,6 +166,60 @@ public interface ChannelCalculatorMultiVariate extends ChannelCalculatorCommon {
*/
public void addObservations(double[][] source, double[][] destination) throws Exception;
/**
* <p>Adds a new set of observations to update the PDFs with - is
* intended to be called multiple times.
* Available ONLY if sourceDimensions was initialised to 1.
* Must be called after {@link #startAddObservations()}; call
* {@link #finaliseAddObservations()} once all observations have
* been supplied.</p>
*
* <p><b>Important:</b> this does not append these observations to the previously
* supplied observations, but treats them independently - i.e. measurements
* such as the transfer entropy will not join them up to examine k
* consecutive values in time.</p>
*
* <p>Note that the arrays source and destination must not be over-written by the user
* until after finaliseAddObservations() has been called
* (they are not copied by this method necessarily, but the method
* may simply hold a pointer to them).</p>
*
* @param source series of uniivariate observations for the source variable
* (first index is time or observation index, second is variable number)
* @param destination series of multivariate observations for the destination variable
* (first index is time or observation index, second is variable number).
* Length must match <code>source</code>, and their indices must correspond.
* @throws Exception
*/
public void addObservations(double[] source, double[][] destination) throws Exception;
/**
* <p>Adds a new set of observations to update the PDFs with - is
* intended to be called multiple times.
* Available ONLY if destDimensions was initialised to 1.
* Must be called after {@link #startAddObservations()}; call
* {@link #finaliseAddObservations()} once all observations have
* been supplied.</p>
*
* <p><b>Important:</b> this does not append these observations to the previously
* supplied observations, but treats them independently - i.e. measurements
* such as the transfer entropy will not join them up to examine k
* consecutive values in time.</p>
*
* <p>Note that the arrays source and destination must not be over-written by the user
* until after finaliseAddObservations() has been called
* (they are not copied by this method necessarily, but the method
* may simply hold a pointer to them).</p>
*
* @param source series of multivariate observations for the source variable
* (first index is time or observation index, second is variable number)
* @param destination series of uniivariate observations for the destination variable
* (first index is time or observation index, second is variable number).
* Length must match <code>source</code>, and their indices must correspond.
* @throws Exception
*/
public void addObservations(double[][] source, double[] destination) throws Exception;
/**
* <p>Adds a new set of univariate observations to update the PDFs with.
* available ONLY if both sourceDimensions and destDimensions were initialised

40
java/source/infodynamics/measures/continuous/MutualInfoMultiVariateCommon.java
View File

@ -282,6 +282,20 @@ public abstract class MutualInfoMultiVariateCommon implements
setObservations(source, destination);
}
@Override
public void setObservations(double[] source, double[][] destination) throws Exception {
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void setObservations(double[][] source, double[] destination) throws Exception {
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void startAddObservations() {
vectorOfSourceObservations = new Vector<double[][]>();
@ -351,6 +365,32 @@ public abstract class MutualInfoMultiVariateCommon implements
addObservations(source, destination);
}
@Override
public void addObservations(double[] source, double[][] destination) throws Exception {
if (dimensionsSource != 1) {
throw new Exception("The number of source dimensions (having been initialised to " +
dimensionsSource + ") can only be 1 when " +
"the partially univariate addObservations(double[],double[][]) and " +
"setObservations(double[],double[][]) methods are called");
}
addObservations(MatrixUtils.reshape(source, source.length, 1),
destination);
}
@Override
public void addObservations(double[][] source, double[] destination) throws Exception {
if (dimensionsDest != 1) {
throw new Exception("The number of dest dimensions (having been initialised to " +
dimensionsDest + ") can only be 1 when " +
"the partially univariate addObservations(double[][],double[]) and " +
"setObservations(double[][],double[]) methods are called");
}
addObservations(source,
MatrixUtils.reshape(destination, destination.length, 1));
}
public void addObservations(double[][] source, double[][] destination,
int startTime, int numTimeSteps) throws Exception {
if (vectorOfSourceObservations == null) {

52
java/source/infodynamics/measures/continuous/TransferEntropyCalculatorMultiVariateViaCondMutualInfo.java
View File

@ -257,6 +257,30 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
super.setObservations(source, destination);
}
@Override
public void setObservations(double[] source, double[][] destination)
throws Exception {
if (sourceDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for source");
}
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void setObservations(double[][] source, double[] destination)
throws Exception {
if (destDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for dest");
}
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void startAddObservations() {
if ((sourceDimensions == 1) && (destDimensions == 1)) {
@ -293,6 +317,34 @@ public class TransferEntropyCalculatorMultiVariateViaCondMutualInfo
super.addObservations(source, destination);
}
/* (non-Javadoc)
* @see infodynamics.measures.continuous.ChannelCalculatorMultiVariate#addObservations(double[], double[][])
*/
@Override
public void addObservations(double[] source, double[][] destination) throws Exception {
if (sourceDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for source");
}
addObservations(MatrixUtils.reshape(source, source.length, 1),
destination);
}
/* (non-Javadoc)
* @see infodynamics.measures.continuous.ChannelCalculatorMultiVariate#addObservations(double[][], double[])
*/
@Override
public void addObservations(double[][] source, double[] destination) throws Exception {
if (destDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for dest");
}
addObservations(source,
MatrixUtils.reshape(destination, destination.length, 1));
}
/* (non-Javadoc)
* @see infodynamics.measures.continuous.ChannelCalculatorMultiVariate#addObservations(double[][], double[][])
*/

50
java/source/infodynamics/measures/continuous/kernel/TransferEntropyCalculatorMultiVariateKernel.java
View File

@ -274,6 +274,30 @@ public class TransferEntropyCalculatorMultiVariateKernel
finaliseAddObservations();
}
@Override
public void setObservations(double[] source, double[][] destination)
throws Exception {
if (sourceDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for source");
}
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void setObservations(double[][] source, double[] destination)
throws Exception {
if (destDimensions != 1) {
throw new Exception("Cannot call the partially univariate addObservations if you " +
"have initialised with dimension > 1 for dest");
}
startAddObservations();
addObservations(source, destination);
finaliseAddObservations();
}
@Override
public void setObservations(double[][] source, double[][] destination,
boolean[] sourceValid, boolean[] destValid) throws Exception {
@ -358,6 +382,32 @@ public class TransferEntropyCalculatorMultiVariateKernel
vectorOfJointSourceObservations.add(source);
vectorOfJointDestinationObservations.add(destination);
}
@Override
public void addObservations(double[] source, double[][] destination) throws Exception {
if (sourceDimensions != 1) {
throw new Exception("The number of source dimensions (having been initialised to " +
sourceDimensions + ") can only be 1 when " +
"the partially univariate addObservations(double[],double[][]) and " +
"setObservations(double[],double[][]) methods are called");
}
addObservations(MatrixUtils.reshape(source, source.length, 1),
destination);
}
@Override
public void addObservations(double[][] source, double[] destination) throws Exception {
if (destDimensions != 1) {
throw new Exception("The number of dest dimensions (having been initialised to " +
destDimensions + ") can only be 1 when " +
"the partially univariate addObservations(double[][],double[]) and " +
"setObservations(double[][],double[]) methods are called");
}
addObservations(source,
MatrixUtils.reshape(destination, destination.length, 1));
}
@Override
public void addObservations(double[][] source, double[][] destination,