diff --git a/build.xml b/build.xml
index ca0b6de..158bf57 100755
--- a/build.xml
+++ b/build.xml
@@ -5,7 +5,7 @@
-
+
diff --git a/demos/AutoAnalyser/README-AutoAnalyserDemo.pdf b/demos/AutoAnalyser/README-AutoAnalyserDemo.pdf
index 3442cb5..7032b39 100644
Binary files a/demos/AutoAnalyser/README-AutoAnalyserDemo.pdf and b/demos/AutoAnalyser/README-AutoAnalyserDemo.pdf differ
diff --git a/demos/java/README-SimpleJavaDemos.pdf b/demos/java/README-SimpleJavaDemos.pdf
index 344af19..2177807 100755
Binary files a/demos/java/README-SimpleJavaDemos.pdf and b/demos/java/README-SimpleJavaDemos.pdf differ
diff --git a/demos/octave/SchreiberTransferEntropyExamples/README-SchreiberTeDemos.pdf b/demos/octave/SchreiberTransferEntropyExamples/README-SchreiberTeDemos.pdf
index ca98df4..1467f22 100755
Binary files a/demos/octave/SchreiberTransferEntropyExamples/README-SchreiberTeDemos.pdf and b/demos/octave/SchreiberTransferEntropyExamples/README-SchreiberTeDemos.pdf differ
diff --git a/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m b/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m
index dbc4d76..3bf4dbd 100755
--- a/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m
+++ b/demos/octave/SchreiberTransferEntropyExamples/runHeartBreathRateKraskov.m
@@ -28,10 +28,10 @@
%
%
% Inputs
-% - kHistory - destination embedding length
-% - lHistory - source embedding length
+% - kHistory - destination embedding length, or "auto" for an auto-embedding (Ragwitz criteria, which takes a minute or two to run)
+% - lHistory - source embedding length, or "auto" for an auto-embedding (Ragwitz criteria, which takes a minute or two to run)
% - knns - a scalar specifying a single, or vector specifying multiple, value of K nearest neighbours to evaluate TE (Kraskov) with.
-% - numSurrogates - a scalar specifying the number of surrogates to evaluate TE from null distribution
+% - numSurrogates - a scalar specifying the number of surrogates to evaluate TE from null distribution (which further multiplies the runtime)
% Outputs
% - teHeartToBreath - TE (heart -> breath) for each value of k nearest neighbours
% - teBreathToHeart - TE (breath -> heart) for each value of k nearest neighbours
@@ -67,17 +67,44 @@ function [teHeartToBreath, teBreathToHeart] = runHeartBreathRateKraskov(kHistory
% Using a KSG estimator for TE is the least biased way to run this:
teCalc=javaObject('infodynamics.measures.continuous.kraskov.TransferEntropyCalculatorKraskov');
+ % Set up for any potential auto-embedding:
+ if (ischar(kHistory)) % Assume == 'auto'
+ % we're auto-embedding at least the destination:
+ if (ischar(lHistory)) % Assume == 'auto'
+ % we're auto embedding both source and destination
+ teCalc.setProperty(teCalc.PROP_AUTO_EMBED_METHOD, ...
+ teCalc.AUTO_EMBED_METHOD_RAGWITZ);
+ else
+ % we're auto embedding destination only
+ teCalc.setProperty(teCalc.PROP_AUTO_EMBED_METHOD, ...
+ teCalc.AUTO_EMBED_METHOD_RAGWITZ_DEST_ONLY);
+ end
+ teCalc.setProperty(teCalc.PROP_K_SEARCH_MAX, '10');
+ teCalc.setProperty(teCalc.PROP_TAU_SEARCH_MAX, '5');
+ end
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(kHistory,1,lHistory,1,1);
+ if (ischar(kHistory)) % Assume == 'auto'
+ % we're auto-embedding at least the destination:
+ teCalc.initialise();
+ else
+ % We're not auto embedding
+ teCalc.initialise(kHistory,1,lHistory,1,1);
+ end
teCalc.setProperty('k', sprintf('%d',knn));
teCalc.setObservations(octaveToJavaDoubleArray(heart), ...
octaveToJavaDoubleArray(chestVol));
teHeartToBreath(knnIndex) = teCalc.computeAverageLocalOfObservations();
+ % Grab the embedding parameters (in case of auto-embedding), converting from Java to native strings
+ kUsedHB = char(teCalc.getProperty(teCalc.K_PROP_NAME));
+ kTauUsedHB = char(teCalc.getProperty(teCalc.K_TAU_PROP_NAME));
+ lUsedHB = char(teCalc.getProperty(teCalc.L_PROP_NAME));
+ lTauUsedHB = char(teCalc.getProperty(teCalc.L_TAU_PROP_NAME));
+ % And compare to surrogates if required
if (numSurrogates > 0)
teHeartToBreathNullDist = teCalc.computeSignificance(numSurrogates);
teHeartToBreathNullMean = teHeartToBreathNullDist.getMeanOfDistribution();
@@ -85,22 +112,34 @@ function [teHeartToBreath, teBreathToHeart] = runHeartBreathRateKraskov(kHistory
end
% Perform calculation for breath -> heart (lag 1)
- teCalc.initialise(kHistory,1,lHistory,1,1);
+ if (ischar(kHistory)) % Assume == 'auto'
+ % we're auto-embedding at least the destination:
+ teCalc.initialise();
+ else
+ % We're not auto embedding
+ teCalc.initialise(kHistory,1,lHistory,1,1);
+ end
teCalc.setProperty('k', sprintf('%d',knn));
teCalc.setObservations(octaveToJavaDoubleArray(chestVol), ...
octaveToJavaDoubleArray(heart));
teBreathToHeart(knnIndex) = teCalc.computeAverageLocalOfObservations();
+ % Grab the embedding parameters (in case of auto-embedding)
+ kUsedBH = char(teCalc.getProperty(teCalc.K_PROP_NAME));
+ kTauUsedBH = char(teCalc.getProperty(teCalc.K_TAU_PROP_NAME));
+ lUsedBH = char(teCalc.getProperty(teCalc.L_PROP_NAME));
+ lTauUsedBH = char(teCalc.getProperty(teCalc.L_TAU_PROP_NAME));
+ % And compare to surrogates if required
if (numSurrogates > 0)
teBreathToHeartNullDist = teCalc.computeSignificance(numSurrogates);
teBreathToHeartNullMean = teBreathToHeartNullDist.getMeanOfDistribution();
teBreathToHeartNullStd = teBreathToHeartNullDist.getStdOfDistribution();
end
- fprintf('TE(k=%d,l=%d,knn=%d): h->b = %.3f', kHistory, lHistory, knn, teHeartToBreath(knnIndex));
+ fprintf('TE(k=%s,kTau=%s,l=%s,lTau=%s,knn=%d): h->b = %.3f', kUsedHB, kTauUsedHB, lUsedHB, lTauUsedHB, knn, teHeartToBreath(knnIndex));
if (numSurrogates > 0)
fprintf(' (null = %.3f +/- %.3f)', teHeartToBreathNullMean, teHeartToBreathNullStd);
end
- fprintf(', b->h = %.3f nats', teBreathToHeart(knnIndex));
+ fprintf('; TE(k=%s,kTau=%s,l=%s,lTau=%s,knn=%d): b->h = %.3f nats', kUsedBH, kTauUsedBH, lUsedBH, lTauUsedBH, knn, teBreathToHeart(knnIndex));
if (numSurrogates > 0)
fprintf('(null = %.3f +/- %.3f)\n', teBreathToHeartNullMean, teBreathToHeartNullStd);
else
diff --git a/demos/python/README-PythonDemos.pdf b/demos/python/README-PythonDemos.pdf
index 9c0770b..d93b86a 100755
Binary files a/demos/python/README-PythonDemos.pdf and b/demos/python/README-PythonDemos.pdf differ
diff --git a/demos/r/README-R_Demos.pdf b/demos/r/README-R_Demos.pdf
index edb3221..39dbec0 100755
Binary files a/demos/r/README-R_Demos.pdf and b/demos/r/README-R_Demos.pdf differ
diff --git a/readme-template.txt b/readme-template.txt
index c612afe..c387a79 100755
--- a/readme-template.txt
+++ b/readme-template.txt
@@ -132,6 +132,15 @@ Notices for this software are found in the notices/JAMA directory.
Release notes
===============
+v1.3 10/7/2015 at r677
+----------------------
+Added AutoAnalyser (Code Generator) GUI demo;
+Added auto-embedding capability via Ragwitz criteria for AIS and TE calculators (KSG estimators);
+Added Java demo 9 for showcasing use of Ragwitz auto-embedding;
+Adding small amount of noise to data in all KSG estimators now by default (may be disabled via setProperty());
+Added getProperty() methods for all conditional MI and TE calculators;
+Upgraded Python demos for Python 3 compatibility;
+
v1.2.1 12/2/2015 at r621
------------------------
Added tutorial slides, description of exercises and sample exercise solutions;