jidt/demos/octave/example1TeBinaryData.m

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Matlab
Executable File

%%
%% Java Information Dynamics Toolkit (JIDT)
%% Copyright (C) 2012, Joseph T. Lizier
%%
%% This program is free software: you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation, either version 3 of the License, or
%% (at your option) any later version.
%%
%% This program is distributed in the hope that it will be useful,
%% but WITHOUT ANY WARRANTY; without even the implied warranty of
%% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
%% GNU General Public License for more details.
%%
%% You should have received a copy of the GNU General Public License
%% along with this program. If not, see <http://www.gnu.org/licenses/>.
%%
% = Example 1 - Transfer entropy on binary data =
% Simple transfer entropy (TE) calculation on binary data using the discrete TE calculator:
% Change location of jar to match yours:
javaaddpath('../../infodynamics.jar');
% Generate some random binary data.
% Note that we need the *1 to make this a number not a Boolean,
% otherwise this will not work (as it cannot match the method signature)
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.TransferEntropyCalculator', 2, 1);
teCalc.initialise();
% Since we have simple arrays of ints, we can directly pass these in:
teCalc.addObservations(sourceArray, destArray);
fprintf('For copied source, result should be close to 1 bit : ');
result = teCalc.computeAverageLocalOfObservations()
teCalc.initialise();
teCalc.addObservations(sourceArray2, destArray);
fprintf('For random source, result should be close to 0 bits: ');
result2 = teCalc.computeAverageLocalOfObservations()