Fixed demo of Kraskov TE on Schreiber heart-breath data to use new Kr…

…askov TE calculator properly. Added new demos to readme-template.
sanjobnth · Apr 17, 2014 · 4d1aac4 · 4d1aac4
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diff --git a/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m b/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m
@@ -10,13 +10,15 @@
 %
 %
 % Inputs
+% - kHistory - destination embedding length
+% - lHistory - source embedding length
 % - knns - a scalar specifying a single, or vector specifying multiple, value of K nearest neighbours to evaluate TE (Kraskov) with
 % Outputs
 % - teHeartToBreath - TE (heart -> breath) for each value of k nearest neighbours
 % - teBreathToHeart - TE (breath -> heart) for each value of k nearest neighbours
 
 
-function [teHeartToBreath, teBreathToHeart] = runHeartBreathRate(knns)
+function [teHeartToBreath, teBreathToHeart] = runHeartBreathRateKraskov(kHistory, lHistory, knns)
 
 	starttime = tic;
 
@@ -41,32 +43,36 @@
 	fprintf('TE for heart rate <-> breath rate for Kraskov estimation with %d samples:\n', timeSteps);
 
 	% Using a single conditional mutual information calculator is the least biased way to run this:
-	teCalc=javaObject('infodynamics.measures.continuous.kraskov.ConditionalMutualInfoCalculatorMultiVariateKraskov1');
+	teCalc=javaObject('infodynamics.measures.continuous.kraskov.TransferEntropyCalculatorKraskov');
 
 	for knnIndex = 1:length(knns)
 		knn = knns(knnIndex);
 		% Compute a TE value for knn nearest neighbours
 
 		% Perform calculation for heart -> breath (lag 1)
-		teCalc.initialise(1,1,1); % Use history length 1 (Schreiber k)
+		teCalc.initialise(kHistory,1,lHistory,1,1);
 		teCalc.setProperty('k', sprintf('%d',knn));
-		teCalc.setObservations(octaveToJavaDoubleMatrix(heart(1:timeSteps-1)), ...
-					octaveToJavaDoubleMatrix(chestVol(2:timeSteps)), ...
-					octaveToJavaDoubleMatrix(chestVol(1:timeSteps-1)));
+		teCalc.setObservations(octaveToJavaDoubleMatrix(heart), ...
+					octaveToJavaDoubleMatrix(chestVol));
 		teHeartToBreath(knnIndex) = teCalc.computeAverageLocalOfObservations();
 
 		% Perform calculation for breath -> heart (lag 1)
-		teCalc.initialise(1,1,1); % Use history length 1 (Schreiber k)
+		teCalc.initialise(kHistory,1,lHistory,1,1);
 		teCalc.setProperty('k', sprintf('%d',knn));
-		teCalc.setObservations(octaveToJavaDoubleMatrix(chestVol(1:timeSteps-1)), ...
-					octaveToJavaDoubleMatrix(heart(2:timeSteps)), ...
-					octaveToJavaDoubleMatrix(heart(1:timeSteps-1)));
+		teCalc.setObservations(octaveToJavaDoubleMatrix(chestVol), ...
+					octaveToJavaDoubleMatrix(heart));
 		teBreathToHeart(knnIndex) = teCalc.computeAverageLocalOfObservations();
 
 		fprintf('TE(k=%d): heart->breath = %.3f, breath->heart = %.3f\n', knn, teHeartToBreath(knnIndex), teBreathToHeart(knnIndex));
 	end
 
-	endtime = toc;
-	fprintf('Total runtime was %.1f sec\n', endtime - starttime);
+	tElapsed = toc(starttime);
+	fprintf('Total runtime was %.1f sec\n', tElapsed);
+
+	plot(knns, teHeartToBreath, 'rx');
+	hold on;
+	plot(knns, teBreathToHeart, 'mo');
+	hold off;
+	legend(['TE(heart->breath)'; 'TE(breath->heart)']);
 end
 
diff --git a/readme-template.txt b/readme-template.txt
@@ -71,14 +71,17 @@ Further documentation is provided by the Usage examples below.
 
 Several sets of demonstration code are distributed with the toolkit:
 
- a. demos/octave - basic examples on easily using the Java toolkit from Octave or Matlab environments - see description at http://code.google.com/p/information-dynamics-toolkit/wiki/OctaveMatlabExamples
-     Note that this also provides useful examples on how to use the Java code in general!
+ a. demos/java -- basic examples on easily using the Java toolkit -- run these from the shell scripts in this directory -- see description at http://code.google.com/p/information-dynamics-toolkit/wiki/SimpleJavaExamples
+
+ b. demos/octave -- basic examples on easily using the Java toolkit from Octave or Matlab environments -- see description at http://code.google.com/p/information-dynamics-toolkit/wiki/OctaveMatlabExamples
 
- b. demos/octave/CellularAutomata - using the Java toolkit to plot local information dynamics profiles in cellular automata; the toolkit is run under Octave or Matlab - see description at http://code.google.com/p/information-dynamics-toolkit/wiki/CellularAutomataDemos
+ c. demos/python -- basic examples on easily using the Java toolkit from Python -- see description at http://code.google.com/p/information-dynamics-toolkit/wiki/PythonExamples
+
+ d. demos/octave/CellularAutomata -- using the Java toolkit to plot local information dynamics profiles in cellular automata; the toolkit is run under Octave or Matlab -- see description at http://code.google.com/p/information-dynamics-toolkit/wiki/CellularAutomataDemos
 
- c. demos/octave/DetectingInteractionLags - brief examples using the transfer entropy to examine source-delay interaction lags. Documentation to come soon; in the interim, see header comments in the .m files.
+ e. demos/octave/DetectingInteractionLags -- brief examples using the transfer entropy to examine source-delay interaction lags. Documentation to come soon; in the interim, see header comments in the .m files.
 
- d. java/unittests - the JUnit test cases for the Java toolkit are included in the distribution - these case also be browsed to see simple use cases for the toolkit - see description at http://code.google.com/p/information-dynamics-toolkit/wiki/JUnitTestCases
+ f. java/unittests -- the JUnit test cases for the Java toolkit are included in the distribution -- these case also be browsed to see simple use cases for the various calculators in the toolkit -- see description at http://code.google.com/p/information-dynamics-toolkit/wiki/JUnitTestCases
 
 =============