mirror of https://github.com/jlizier/jidt
40 lines
1.3 KiB
Matlab
40 lines
1.3 KiB
Matlab
% Add JIDT jar library to the path, and disable warnings that it's already there:
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warning('off','MATLAB:Java:DuplicateClass');
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javaaddpath('/home/joseph/temp/JIDT/JIDT-copy/infodynamics.jar');
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% Add utilities to the path
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addpath('/home/joseph/temp/JIDT/JIDT-copy/demos/octave');
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% 0. Load/prepare the data:
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data = load('/home/joseph/temp/JIDT/JIDT-copy/demos/data/2coupledRandomCols-1.txt');
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% Column indices start from 1 in Matlab:
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source = octaveToJavaDoubleArray(data(:,1));
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destination = octaveToJavaDoubleArray(data(:,2));
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% 1. Construct the calculator:
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calc = javaObject('infodynamics.measures.continuous.kraskov.MutualInfoCalculatorMultiVariateKraskov2');
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results = [];
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kNNs = 4:15;
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for kNN = kNNs
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% 2. Set any properties to non-default values:
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calc.setProperty('TIME_DIFF', '1');
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calc.setProperty('k', string(kNN));
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% 3. Initialise the calculator for (re-)use:
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calc.initialise();
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% 4. Supply the sample data:
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calc.setObservations(source, destination);
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% 5. Compute the estimate:
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result = calc.computeAverageLocalOfObservations();
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results(end+1) = result;
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fprintf('MI_Kraskov (KSG) alg. 2(col_0 -> col_1, k=%d) = %.4f nats\n', ...
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kNN, result);
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end
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plot(kNNs, results, 'x-');
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title("MI versus k nearest neighbours");
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xlabel("kNNs");
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ylabel("MI (nats)");
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axis([4, 16, 0, max(results)*1.1]);
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