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Added runTentMap script for Schreiber TE Example 1

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joseph.lizier 2014-08-01 13:28:51 +00:00
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demos/octave/SchreiberTransferEntropyExamples/runTentMap.m Executable file
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% function Values = runTentMap()
%
% Version 1.0
% Joseph Lizier
% 1/8/14
%
% Used to explore information transfer in the testMap example of Schreiber's paper,
% recreating figure 1 in that paper.
%
% The code should take ~5 minutes run time for all repeats and couplings.
function teValues = runTentMap()
% Add utilities to the path (needed for octaveToJavaIntMatrix)
addpath('..');
% Octave is happy to have the path added multiple times; I'm unsure if this is true for matlab
javaaddpath('../../../infodynamics.jar');
% Number of cells (M), transients, iterates and number of runs
% used by Schreiber:
M = 100;
transientLength = 10000;
iterates = 10000;
numberOfRuns = 10;
couplings = 0:0.002:0.05;
tic;
% Construct for binary values, k=1 history length
teCalc=javaObject('infodynamics.measures.discrete.ApparentTransferEntropyCalculator', 2, 1);
teValues = zeros(numberOfRuns, length(couplings));
for couplingIndex = 1:length(couplings)
coupling = couplings(couplingIndex);
for r = 1:numberOfRuns
% Construct the map matrix with maps in columns, time in rows
% Initialise first row randomly
transientMapValues = rand(1, M);
% Run transients - no need to keep the transient values
for t = 2 : transientLength
transientMapValues = tentMap(coupling .* [ transientMapValues(M) , transientMapValues(1:M-1)] + ...
(1 - coupling) .* transientMapValues);
end
% Run iterates - now keep the iterated map values
mapValues = zeros(iterates, M);
mapValues(1,:) = transientMapValues;
for t = 2 : iterates
mapValues(t, :) = tentMap(coupling .* [ mapValues(t-1, M) , mapValues(t-1,1:M-1)] + ...
(1 - coupling) .* mapValues(t-1,:));
end
% Take binary values (need the *1 for now for Java conversion from boolean)
binaryValues = (mapValues >= 0.5)*1;
% Compute TE
teCalc.initialise();
% Add observations for TE across 1 column per time step:
teCalc.addObservations(octaveToJavaIntMatrix(binaryValues), 1);
teValues(r, couplingIndex) = teCalc.computeAverageLocalOfObservations();
% fprintf('teValues(r=%d, coupling=%.3f)=%.4f\n', r, coupling, teValues(r, couplingIndex));
end
end
meanTes = mean(teValues);
stdTes = std(teValues);
% Plot results
hold off;
h = errorbar(couplings, meanTes, stdTes./sqrt(numberOfRuns));
set(h, 'LineStyle', 'none');
set(h, 'MarkerEdgeColor', 'r');
set(h, 'Marker', 'x');
set(h, 'markersize', 14);
hold on;
% Add the curve that Schreiber fitted:
plot(couplings, 0.77^2*couplings.^2 ./ log(2), '-r');
hold off;
set (gca,'fontsize',26);
xlabel('coupling', 'FontSize', 36, 'FontWeight', 'bold');
ylabel('TE (bits)', 'FontSize', 36, 'FontWeight', 'bold');
axis([0 0.05 0 0.0025]);
print('tentMapResults.eps', '-depsc');
totaltime = toc;
fprintf('Total runtime was %.1f sec\n', totaltime);
end
function xOut = tentMap(xIn)
xOut = xIn .* 2 .* (xIn < 0.5) + (2 - 2 .* xIn) .* (xIn >= 0.5);
end