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Added unit test for TE continuous getSeparateNumObservations (in Kraskov class)

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jlizier 2016-10-18 15:05:15 +11:00
parent e2182c40c2
commit 4cac043aff
1 changed files with 66 additions and 0 deletions
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66
java/unittests/infodynamics/measures/continuous/kraskov/TransferEntropyTester.java
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@ -537,4 +537,70 @@ public class TransferEntropyTester
assertEquals(teOptimisedSingleThread, teOptimisedWithValidity, 0.00000001);
System.out.println("Answer unchanged by setting validity");
}
public void testGetSeparateNumObservations() throws Exception {
ArrayFileReader afr = new ArrayFileReader("demos/data/SFI-heartRate_breathVol_bloodOx.txt");
double[][] data = afr.getDouble2DMatrix();
TransferEntropyCalculatorKraskov teCalc = new TransferEntropyCalculatorKraskov();
teCalc.initialise();
teCalc.startAddObservations();
int timeStepsPerCall = 100;
int calls = 10;
for (int i = 0; i < calls; i++) {
// Add more samples
teCalc.addObservations(MatrixUtils.selectColumn(data, 0, i*timeStepsPerCall, timeStepsPerCall),
MatrixUtils.selectColumn(data, 1, i*timeStepsPerCall, timeStepsPerCall));
}
teCalc.finaliseAddObservations();
@SuppressWarnings("unused")
double result = teCalc.computeAverageLocalOfObservations();
// Now we want to check how many observations were added at each call:
int[] samplesPerCall = teCalc.getSeparateNumObservations();
assertEquals(calls, samplesPerCall.length);
for (int i = 0; i < calls; i++) {
// For k = l = 1, we should have timeStepsPerCall - 1 samples per addObservations() call:
assertEquals(timeStepsPerCall - 1, samplesPerCall[i]);
}
// =====================
// Now run it again with different k and l and embedding lags, etc:
teCalc.initialise();
teCalc.startAddObservations();
// auto embed destination only
teCalc.setProperty(TransferEntropyCalculatorKraskov.PROP_AUTO_EMBED_METHOD,
TransferEntropyCalculatorKraskov.AUTO_EMBED_METHOD_RAGWITZ_DEST_ONLY);
teCalc.setProperty(TransferEntropyCalculatorKraskov.PROP_K_SEARCH_MAX, "5");
teCalc.setProperty(TransferEntropyCalculatorKraskov.PROP_TAU_SEARCH_MAX, "5");
// Explicitly set the source embedding params
teCalc.setProperty(TransferEntropyCalculatorKraskov.L_PROP_NAME, "1");
teCalc.setProperty(TransferEntropyCalculatorKraskov.L_TAU_PROP_NAME, "1");
int[] timeStepsPerCallArray = new int[] {100, 200, 150, 300, 99, 54};
int startTime = 0;
for (int i = 0; i < timeStepsPerCallArray.length; i++) {
// Add more samples
teCalc.addObservations(MatrixUtils.selectColumn(data, 0, startTime, timeStepsPerCallArray[i]),
MatrixUtils.selectColumn(data, 1, startTime, timeStepsPerCallArray[i]));
startTime += timeStepsPerCallArray[i];
}
teCalc.finaliseAddObservations();
result = teCalc.computeAverageLocalOfObservations();
int optimisedK = Integer.parseInt(teCalc.getProperty(TransferEntropyCalculatorKraskov.K_PROP_NAME));
int optimisedKTau = Integer.parseInt(teCalc.getProperty(TransferEntropyCalculatorKraskov.K_TAU_PROP_NAME));
int timeOfFirstObservationPerSet = (optimisedK - 1)*optimisedKTau + 1;
System.out.printf("In testing tracking of observations per addObservations() call" +
" we have auto-embedding dimension %d and lag %d, timeOfFirstObservationPerSet %d\n",
optimisedK, optimisedKTau, timeOfFirstObservationPerSet);
// Now we want to check how many observations were added at each call:
samplesPerCall = teCalc.getSeparateNumObservations();
assertEquals(timeStepsPerCallArray.length, samplesPerCall.length);
for (int i = 0; i < timeStepsPerCallArray.length; i++) {
// For timeOfFirstObservationPerSet, we should have timeStepsPerCall - timeOfFirstObservationPerSet
// samples per addObservations() call:
assertEquals(timeStepsPerCallArray[i] - timeOfFirstObservationPerSet, samplesPerCall[i]);
}
}
}