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Renaming (Apparent) TE discrete calculator to remove "Apparent" in all of the non-Java demo code

This commit is contained in:
joseph.lizier 2014-08-05 05:19:21 +00:00
parent 515fdd1432
commit e44eba7199
9 changed files with 10 additions and 10 deletions
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4
demos/octave/CellularAutomata/plotLocalInfoMeasureForCA.m
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@ -14,7 +14,7 @@
% - timeSteps - number of rows to execute the CA for (including the random initial row)
% - measureId - which local info dynamics measure to plot - can be a string or an integer as follows:
% - 'active', 0 - active information storage (requires measureParams.k)
% - 'transfer', 1 - apparent transfer entropy (requires measureParams.k and j)
% - 'transfer', 1 - pairwise or apparent transfer entropy (requires measureParams.k and j)
% - 'transfercomplete', 2 - complete transfer entropy (requires measureParams.k and j)
% - 'separable', 3 - separable information (requires measureParams.k)
% - 'entropy', 4 - excess entropy (requires no params)
@ -154,7 +154,7 @@ function [caStates, localValues] = plotLocalInfoMeasureForCA(neighbourhood, base
if (measureParams.j == 0)
error('Cannot compute transfer entropy from a cell to itself (setting measureParams.j == 0)');
end
transferCalc = javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', base, measureParams.k);
transferCalc = javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', base, measureParams.k);
transferCalc.initialise();
transferCalc.addObservations(caStatesJInts, measureParams.j);
avTransfer = transferCalc.computeAverageLocalOfObservations();

2
demos/octave/DetectingInteractionLags/transferWithSourceMemory.m
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@ -75,7 +75,7 @@ function transferWithSourceMemory(savePlot)
y = [rand() < 0.5; x1(1:N)];
% Compute TEs
teCalc = javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 4, 1);
teCalc = javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 4, 1);
teCalc.initialise();
teCalc.addObservations(y, x);
teXnToYnplus1(deltaIndex) = teCalc.computeAverageLocalOfObservations();

2
demos/octave/SchreiberTransferEntropyExamples/runTentMap.m
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@ -28,7 +28,7 @@ function teValues = runTentMap()
tic;
% Construct for binary values, k=1 history length
teCalc=javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 2, 1);
teCalc=javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 2, 1);
teValues = zeros(numberOfRuns, length(couplings));
for couplingIndex = 1:length(couplings)

2
demos/octave/example1TeBinaryData.m
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@ -12,7 +12,7 @@ sourceArray=(rand(100,1)>0.5)*1;
destArray = [0; sourceArray(1:99)];
sourceArray2=(rand(100,1)>0.5)*1;
% Create a TE calculator and run it:
teCalc=javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 2, 1);
teCalc=javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 2, 1);
teCalc.initialise();
% Since we have simple arrays of ints, we can directly pass these in:
teCalc.addObservations(destArray, sourceArray);

2
demos/octave/example2TeMultidimBinaryData.m
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@ -22,7 +22,7 @@ twoDTimeSeriesOctave(2, :) = [twoDTimeSeriesOctave(1,100), twoDTimeSeriesOctave(
twoDTimeSeriesJavaInt = octaveToJavaIntMatrix(twoDTimeSeriesOctave);
% Create a TE calculator and run it:
teCalc=javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 2, 1);
teCalc=javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 2, 1);
teCalc.initialise();
% Add observations of transfer across one cell to the right per time step:
teCalc.addObservations(twoDTimeSeriesJavaInt, 1);

2
demos/octave/example5TeBinaryMultivarTransfer.m
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@ -15,7 +15,7 @@ sourceArray2=(rand(numObservations,2)>0.5)*1;
% and an XOR of the two bits of the source in bit 2:
destArray = [0, 0; sourceArray(1:numObservations-1, 1), xor(sourceArray(1:numObservations-1, 1), sourceArray(1:numObservations-1, 2))];
% Create a TE calculator and run it:
teCalc=javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 4, 1);
teCalc=javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 4, 1);
teCalc.initialise();
% We need to construct the joint values of the dest and source before we pass them in,
% and need to use the matrix conversion routine when calling from Matlab/Octave:

2
demos/python/example1TeBinaryData.py
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@ -16,7 +16,7 @@ destArray = [0] + sourceArray[0:99];
sourceArray2 = [random.randint(0,1) for r in xrange(100)]
# Create a TE calculator and run it:
teCalcClass = JPackage("infodynamics.measures.discrete").ApparentTransferEntropyCalculator
teCalcClass = JPackage("infodynamics.measures.discrete").TransferEntropyCalculator
teCalc = teCalcClass(2,1)
teCalc.initialise()
# Since we have simple arrays of ints, we can directly pass these in:

2
demos/python/example2TeMultidimBinaryData.py
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@ -26,7 +26,7 @@ twoDTimeSeriesPython.append(row2)
twoDTimeSeriesJavaInt = JArray(JInt, 2)(twoDTimeSeriesPython); # 2 indicating 2D array
# Create a TE calculator and run it:
teCalcClass = JPackage("infodynamics.measures.discrete").ApparentTransferEntropyCalculator
teCalcClass = JPackage("infodynamics.measures.discrete").TransferEntropyCalculator
teCalc = teCalcClass(2,1)
teCalc.initialise()
# Add observations of transfer across one cell to the right per time step:

2
demos/python/example5TeBinaryMultivarTransfer.py
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@ -22,7 +22,7 @@ for j in range(1,numObservations):
destArray.append([sourceArray[j-1][0], xor(sourceArray[j-1][0], sourceArray[j-1][1])])
# Create a TE calculator and run it:
teCalcClass = JPackage("infodynamics.measures.discrete").ApparentTransferEntropyCalculator
teCalcClass = JPackage("infodynamics.measures.discrete").TransferEntropyCalculator
teCalc = teCalcClass(4,1)
teCalc.initialise()
# We need to construct the joint values of the dest and source before we pass them in,