mirror of https://github.com/jlizier/jidt
44 lines
1.8 KiB
Matlab
Executable File
44 lines
1.8 KiB
Matlab
Executable File
%%
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%% Java Information Dynamics Toolkit (JIDT)
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%% Copyright (C) 2012, Joseph T. Lizier
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%%
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%% This program is free software: you can redistribute it and/or modify
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%% it under the terms of the GNU General Public License as published by
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%% the Free Software Foundation, either version 3 of the License, or
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%% (at your option) any later version.
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%%
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%% This program is distributed in the hope that it will be useful,
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%% but WITHOUT ANY WARRANTY; without even the implied warranty of
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%% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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%% GNU General Public License for more details.
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%%
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%% You should have received a copy of the GNU General Public License
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%% along with this program. If not, see <http://www.gnu.org/licenses/>.
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%%
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% = Example 1 - Transfer entropy on binary data =
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% Simple transfer entropy (TE) calculation on binary data using the discrete TE calculator:
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% Change location of jar to match yours:
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javaaddpath('../../infodynamics.jar');
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% Generate some random binary data.
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% Note that we need the *1 to make this a number not a Boolean,
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% otherwise this will not work (as it cannot match the method signature)
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sourceArray=(rand(100,1)>0.5)*1;
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destArray = [0; sourceArray(1:99)];
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sourceArray2=(rand(100,1)>0.5)*1;
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% Create a TE calculator and run it:
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teCalc=javaObject('infodynamics.measures.discrete.TransferEntropyCalculator', 2, 1);
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teCalc.initialise();
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% Since we have simple arrays of ints, we can directly pass these in:
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teCalc.addObservations(sourceArray, destArray);
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fprintf('For copied source, result should be close to 1 bit : ');
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result = teCalc.computeAverageLocalOfObservations()
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teCalc.initialise();
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teCalc.addObservations(sourceArray2, destArray);
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fprintf('For random source, result should be close to 0 bits: ');
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result2 = teCalc.computeAverageLocalOfObservations()
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