diff --git a/java/source/infodynamics/measures/continuous/MutualInfoCalculatorMultiVariate.java b/java/source/infodynamics/measures/continuous/MutualInfoCalculatorMultiVariate.java
index 666b199..8818840 100755
--- a/java/source/infodynamics/measures/continuous/MutualInfoCalculatorMultiVariate.java
+++ b/java/source/infodynamics/measures/continuous/MutualInfoCalculatorMultiVariate.java
@@ -92,6 +92,25 @@ public interface MutualInfoCalculatorMultiVariate
*/
public static final String PROP_ADD_NOISE = "NOISE_LEVEL_TO_ADD";
+ /**
+ * As per {@link #addObservations(double[][], double[][])};
+ * but also includes parameters to track which observation set
+ * the samples came from. Intended to only be used by other
+ * estimator classes here and not by users directly.
+ *
+ * @param source multivariate observations for variable 1
+ * (first index is time or observation index, second is variable number)
+ * @param destination multivariate observations for variable 2
+ * (first index is time or observation index, second is variable number)
+ * Length must match source, and their indices must correspond.
+ * @param observationSetIndexToUse which set of observations these came fmor
+ * @param startTimeIndex which was the first time index of these
+ * samples within that observation set.
+ * @throws Exception
+ */
+ public void addObservationsTrackObservationIDs(double[][] source, double[][] destination,
+ int observationSetIndexToUse, int startTimeIndex) throws Exception;
+
/**
* Compute the mutual information if the observations of the
* first variable (source)
@@ -130,4 +149,18 @@ public interface MutualInfoCalculatorMultiVariate
* @throws Exception for invalid property values
*/
public String getProperty(String propertyName) throws Exception;
+
+ /**
+ * Retrieve an array indicating which observation set each sample came from
+ *
+ * @return array of integers
+ */
+ public int[] getObservationSetIndices();
+
+ /**
+ * Retrieve an array indicating which time index within its observation set that sample came from
+ *
+ * @return array of integers
+ */
+ public int[] getObservationTimePoints();
}
diff --git a/java/source/infodynamics/measures/continuous/MutualInfoMultiVariateCommon.java b/java/source/infodynamics/measures/continuous/MutualInfoMultiVariateCommon.java
index ec45d02..3229b1d 100755
--- a/java/source/infodynamics/measures/continuous/MutualInfoMultiVariateCommon.java
+++ b/java/source/infodynamics/measures/continuous/MutualInfoMultiVariateCommon.java
@@ -23,6 +23,7 @@ import infodynamics.utils.EmpiricalMeasurementDistribution;
import infodynamics.utils.MatrixUtils;
import infodynamics.utils.RandomGenerator;
+import java.util.Arrays;
import java.util.Iterator;
import java.util.Random;
import java.util.Vector;
@@ -86,6 +87,16 @@ public abstract class MutualInfoMultiVariateCommon implements
*/
protected double[] destStdsBeforeNorm;
+ /**
+ * Track which observation set each sample came from
+ */
+ protected int[] observationSetIndices;
+
+ /**
+ * Track which sample index within an observation set that each sample came from
+ */
+ protected int[] observationTimePoints;
+
/**
* Total number of observations supplied.
* Only valid after {@link #finaliseAddObservations()} is called.
@@ -127,6 +138,22 @@ public abstract class MutualInfoMultiVariateCommon implements
* type calls
*/
protected Vector vectorOfDestinationObservations;
+ /**
+ * Tracks separate (time-series) observation sets
+ * we are taking samples from
+ */
+ protected int observationSetIndex = 0;
+ /**
+ * Storage for which observation set each
+ * block of samples comes from
+ */
+ protected Vector vectorOfObservationSetIndices;
+ /**
+ * Storage for start time point for the observation
+ * set within its block of samples
+ */
+ protected Vector vectorOfObservationStartTimePoints;
+
/**
* Whether the user has supplied more than one (disjoint) set of samples
*/
@@ -163,6 +190,11 @@ public abstract class MutualInfoMultiVariateCommon implements
sourceStdsBeforeNorm = null;
destMeansBeforeNorm = null;
destStdsBeforeNorm = null;
+ observationSetIndices = null;
+ observationTimePoints = null;
+ observationSetIndex = 0;
+ vectorOfObservationSetIndices = null;
+ vectorOfObservationStartTimePoints = null;
addedMoreThanOneObservationSet = false;
}
@@ -296,14 +328,54 @@ public abstract class MutualInfoMultiVariateCommon implements
finaliseAddObservations();
}
+ @Override
+ public void setObservations(double[][] source, double[][] destination,
+ boolean[] sourceValid, boolean[] destValid) throws Exception {
+ startAddObservations();
+ addObservations(source, destination, sourceValid, destValid);
+ finaliseAddObservations();
+ }
+
+ @Override
+ public void setObservations(double[] source, double[] destination,
+ boolean[] sourceValid, boolean[] destValid) throws Exception {
+
+ if ((dimensionsDest != 1) || (dimensionsSource != 1)) {
+ throw new Exception("The number of source and dest dimensions (having been initialised to " +
+ dimensionsSource + " and " + dimensionsDest + ") can only be 1 when " +
+ "the univariate addObservations(double[],double[]) and " +
+ "setObservations(double[],double[]) methods are called");
+ }
+ setObservations(MatrixUtils.reshape(source, source.length, 1),
+ MatrixUtils.reshape(destination, destination.length, 1),
+ sourceValid, destValid);
+ }
+
+ @Override
+ public void setObservations(double[][] source, double[][] destination,
+ boolean[][] sourceValid, boolean[][] destValid) throws Exception {
+
+ boolean[] allSourceValid = MatrixUtils.andRows(sourceValid);
+ boolean[] allDestValid = MatrixUtils.andRows(destValid);
+ setObservations(source, destination, allSourceValid, allDestValid);
+ }
+
@Override
public void startAddObservations() {
vectorOfSourceObservations = new Vector();
vectorOfDestinationObservations = new Vector();
+ vectorOfObservationSetIndices = new Vector();
+ vectorOfObservationStartTimePoints = new Vector();
}
@Override
public void addObservations(double[][] source, double[][] destination) throws Exception {
+ // Use the current observationSetIndex and increment for next use:
+ addObservationsTrackObservationIDs(source, destination, observationSetIndex++, 0);
+ }
+
+ public void addObservationsTrackObservationIDs(double[][] source, double[][] destination,
+ int observationSetIndexToUse, int startTimeIndex) throws Exception {
if (vectorOfSourceObservations == null) {
// startAddObservations was not called first
throw new RuntimeException("User did not call startAddObservations before addObservations");
@@ -326,6 +398,8 @@ public abstract class MutualInfoMultiVariateCommon implements
}
vectorOfSourceObservations.add(source);
vectorOfDestinationObservations.add(destination);
+ vectorOfObservationSetIndices.add(observationSetIndexToUse);
+ vectorOfObservationStartTimePoints.add(startTimeIndex);
}
/**
@@ -391,8 +465,14 @@ public abstract class MutualInfoMultiVariateCommon implements
MatrixUtils.reshape(destination, destination.length, 1));
}
+ @Override
public void addObservations(double[][] source, double[][] destination,
int startTime, int numTimeSteps) throws Exception {
+ addObservations(source, destination, startTime, numTimeSteps, observationSetIndex++);
+ }
+
+ protected void addObservations(double[][] source, double[][] destination,
+ int startTime, int numTimeSteps, int observationSetIndexToUse) throws Exception {
if (vectorOfSourceObservations == null) {
// startAddObservations was not called first
throw new RuntimeException("User did not call startAddObservations before addObservations");
@@ -403,12 +483,12 @@ public abstract class MutualInfoMultiVariateCommon implements
}
double[][] sourceToAdd = new double[numTimeSteps][];
System.arraycopy(source, startTime, sourceToAdd, 0, numTimeSteps);
- vectorOfSourceObservations.add(sourceToAdd);
double[][] destToAdd = new double[numTimeSteps][];
System.arraycopy(destination, startTime, destToAdd, 0, numTimeSteps);
- vectorOfDestinationObservations.add(destToAdd);
+ addObservationsTrackObservationIDs(sourceToAdd, destToAdd, observationSetIndexToUse, startTime);
}
+ @Override
public void addObservations(double[] source, double[] destination,
int startTime, int numTimeSteps) throws Exception {
@@ -423,8 +503,14 @@ public abstract class MutualInfoMultiVariateCommon implements
startTime, numTimeSteps);
}
-
- public void setObservations(double[][] source, double[][] destination,
+ public void addObservations(double[] source, double[] destination,
+ boolean[] sourceValid, boolean[] destValid) throws Exception {
+ addObservations(MatrixUtils.reshape(source, source.length, 1),
+ MatrixUtils.reshape(destination, destination.length, 1),
+ sourceValid, destValid);
+ }
+
+ public void addObservations(double[][] source, double[][] destination,
boolean[] sourceValid, boolean[] destValid) throws Exception {
Vector startAndEndTimePairs = computeStartAndEndTimePairs(sourceValid, destValid);
@@ -434,32 +520,18 @@ public abstract class MutualInfoMultiVariateCommon implements
for (int[] timePair : startAndEndTimePairs) {
int startTime = timePair[0];
int endTime = timePair[1];
- addObservations(source, destination, startTime, endTime - startTime + 1);
+ addObservations(source, destination, startTime, endTime - startTime + 1, observationSetIndex);
}
+ observationSetIndex++;
finaliseAddObservations();
}
- @Override
- public void setObservations(double[] source, double[] destination,
- boolean[] sourceValid, boolean[] destValid) throws Exception {
-
- if ((dimensionsDest != 1) || (dimensionsSource != 1)) {
- throw new Exception("The number of source and dest dimensions (having been initialised to " +
- dimensionsSource + " and " + dimensionsDest + ") can only be 1 when " +
- "the univariate addObservations(double[],double[]) and " +
- "setObservations(double[],double[]) methods are called");
- }
- setObservations(MatrixUtils.reshape(source, source.length, 1),
- MatrixUtils.reshape(destination, destination.length, 1),
- sourceValid, destValid);
- }
-
- public void setObservations(double[][] source, double[][] destination,
+ public void addObservations(double[][] source, double[][] destination,
boolean[][] sourceValid, boolean[][] destValid) throws Exception {
-
+
boolean[] allSourceValid = MatrixUtils.andRows(sourceValid);
boolean[] allDestValid = MatrixUtils.andRows(destValid);
- setObservations(source, destination, allSourceValid, allDestValid);
+ addObservations(source, destination, allSourceValid, allDestValid);
}
/**
@@ -482,11 +554,15 @@ public abstract class MutualInfoMultiVariateCommon implements
}
destObservations = new double[totalObservations][dimensionsDest];
sourceObservations = new double[totalObservations][dimensionsSource];
+ observationSetIndices = new int[totalObservations];
+ observationTimePoints = new int[totalObservations];
// Construct the joint vectors from the given observations
// (removing redundant data which is outside any timeDiff)
int startObservation = 0;
Iterator iterator = vectorOfDestinationObservations.iterator();
+ Iterator iteratorObsSetIndices = vectorOfObservationSetIndices.iterator();
+ Iterator iteratorObsStartTimePoints = vectorOfObservationStartTimePoints.iterator();
for (double[][] source : vectorOfSourceObservations) {
double[][] destination = iterator.next();
// Copy the data from these given observations into our master
@@ -497,7 +573,14 @@ public abstract class MutualInfoMultiVariateCommon implements
MatrixUtils.arrayCopy(destination, timeDiff, 0,
destObservations, startObservation, 0,
destination.length - timeDiff, dimensionsDest);
- startObservation += destination.length - timeDiff;
+ int numNewObservations = destination.length - timeDiff;
+ // And update which observation set and time index each sample came from:
+ Arrays.fill(observationSetIndices, startObservation, startObservation + numNewObservations, iteratorObsSetIndices.next());
+ int firstTimeSampleId = iteratorObsStartTimePoints.next(); // This is the first sample of the source; storing the time index for destination below.
+ for (int i = 0; i < numNewObservations; i++) {
+ observationTimePoints[startObservation + i] = firstTimeSampleId + timeDiff + i;
+ }
+ startObservation += numNewObservations;
}
if (vectorOfSourceObservations.size() > 1) {
addedMoreThanOneObservationSet = true;
@@ -834,4 +917,14 @@ public abstract class MutualInfoMultiVariateCommon implements
}
return startAndEndTimePairs;
}
+
+ @Override
+ public int[] getObservationSetIndices() {
+ return observationSetIndices;
+ }
+
+ @Override
+ public int[] getObservationTimePoints() {
+ return observationTimePoints;
+ }
}
diff --git a/java/unittests/infodynamics/measures/continuous/kraskov/MutualInfoMultiVariateTester.java b/java/unittests/infodynamics/measures/continuous/kraskov/MutualInfoMultiVariateTester.java
index bed843f..0ab5fae 100644
--- a/java/unittests/infodynamics/measures/continuous/kraskov/MutualInfoMultiVariateTester.java
+++ b/java/unittests/infodynamics/measures/continuous/kraskov/MutualInfoMultiVariateTester.java
@@ -21,6 +21,7 @@ package infodynamics.measures.continuous.kraskov;
import infodynamics.utils.ArrayFileReader;
import infodynamics.utils.MathsUtils;
import infodynamics.utils.MatrixUtils;
+import infodynamics.utils.RandomGenerator;
public class MutualInfoMultiVariateTester
extends infodynamics.measures.continuous.MutualInfoMultiVariateAbstractTester {
@@ -652,5 +653,78 @@ public class MutualInfoMultiVariateTester
assertEquals(expected_H_X_given_Y, conditionalEnt, 0.02);
}
+
+ /**
+ * Test that observationSetIndices and observationStartTimePoints are written properly
+ *
+ * @throws Exception
+ */
+ public void testObservationSetIndices() throws Exception {
+
+ int dimensions = 1;
+ int timeSteps = 100;
+
+ MutualInfoCalculatorMultiVariateKraskov miCalc = getNewCalc(1);
+ miCalc.initialise(dimensions, dimensions);
+
+ // generate some random data
+ RandomGenerator rg = new RandomGenerator();
+ double[][] sourceData = rg.generateNormalData(timeSteps, dimensions,
+ 0, 1);
+ double[][] destData = rg.generateNormalData(timeSteps, dimensions,
+ 0, 1);
+
+ // First check that for a simple single observation set everything works:
+ miCalc.setObservations(sourceData, destData);
+
+ int[] observationSetIds = miCalc.getObservationSetIndices();
+ int[] timeSeriesIndices = miCalc.getObservationTimePoints();
+ assert(observationSetIds.length == timeSteps);
+ for (int t = 0; t < timeSteps; t++) {
+ assertEquals(observationSetIds[t], 0);
+ assertEquals(timeSeriesIndices[t], t);
+ }
+
+ // Now add the same one twice:
+ miCalc.initialise(dimensions, dimensions);
+ miCalc.startAddObservations();
+ miCalc.addObservations(sourceData, destData);
+ miCalc.addObservations(sourceData, destData);
+ miCalc.finaliseAddObservations();
+ observationSetIds = miCalc.getObservationSetIndices();
+ timeSeriesIndices = miCalc.getObservationTimePoints();
+ assert(observationSetIds.length == 2*timeSteps);
+ for (int t = 0; t < timeSteps; t++) {
+ assertEquals(observationSetIds[t], 0);
+ assertEquals(timeSeriesIndices[t], t);
+ }
+ for (int t = 0; t < timeSteps; t++) {
+ assertEquals(observationSetIds[timeSteps + t], 1);
+ assertEquals(timeSeriesIndices[timeSteps + t], t);
+ }
+
+ // Now add NUM_SEGMENTS randomly chosen segments:
+ int NUM_SEGMENTS = 10;
+ int maxLength = 10;
+ int[] startPoints = rg.generateRandomInts(NUM_SEGMENTS, timeSteps - maxLength);
+ int[] lengthsMinus1 = rg.generateRandomInts(NUM_SEGMENTS, maxLength - 1); // ensures we don't add segments of length 0
+ miCalc.initialise(dimensions, dimensions);
+ miCalc.startAddObservations();
+ for (int r = 0; r < NUM_SEGMENTS; r++) {
+ miCalc.addObservations(sourceData, destData, startPoints[r], lengthsMinus1[r]+1);
+ }
+ miCalc.finaliseAddObservations();
+ observationSetIds = miCalc.getObservationSetIndices();
+ timeSeriesIndices = miCalc.getObservationTimePoints();
+ assert(observationSetIds.length == MatrixUtils.sum(lengthsMinus1) + NUM_SEGMENTS);
+ int t = 0;
+ for (int r = 0; r < NUM_SEGMENTS; r++) {
+ for (int i = 0; i < lengthsMinus1[r]+1; i++) {
+ assertEquals(observationSetIds[t], r);
+ assertEquals(timeSeriesIndices[t], startPoints[r] + i);
+ t++;
+ }
+ }
+ }
}