jidt/java/source/infodynamics/measures/continuous/kraskov/MutualInfoCalculatorMultiVa...

134 lines
4.5 KiB
Java
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/>.
*/
package infodynamics.measures.continuous.kraskov;
import java.util.Calendar;
import java.util.PriorityQueue;
import infodynamics.measures.continuous.MutualInfoCalculatorMultiVariate;
import infodynamics.utils.MathsUtils;
import infodynamics.utils.NeighbourNodeData;
/**
* <p>Computes the differential mutual information of two given multivariate sets of
* observations (implementing {@link MutualInfoCalculatorMultiVariate}),
* using Kraskov-Stoegbauer-Grassberger (KSG) estimation (see Kraskov et al., below),
* <b>algorithm 2</b>.
* Most of the functionality is defined by the parent class
* {@link MutualInfoCalculatorMultiVariateKraskov}.</p>
*
* <p>Usage is as per the paradigm outlined for {@link MutualInfoCalculatorMultiVariate},
* and expanded on in {@link MutualInfoCalculatorMultiVariateKraskov}.
* </p>
*
* <p><b>References:</b><br/>
* <ul>
* <li>Kraskov, A., Stoegbauer, H., Grassberger, P.,
* <a href="http://dx.doi.org/10.1103/PhysRevE.69.066138">"Estimating mutual information"</a>,
* Physical Review E 69, (2004) 066138.</li>
* </ul>
*
* @author Joseph Lizier (<a href="joseph.lizier at gmail.com">email</a>,
* <a href="http://lizier.me/joseph/">www</a>)
* @author Ipek Özdemir
*/
public class MutualInfoCalculatorMultiVariateKraskov2
extends MutualInfoCalculatorMultiVariateKraskov {
public MutualInfoCalculatorMultiVariateKraskov2() {
super();
isAlgorithm1 = false;
}
protected double[] partialComputeFromObservations(
int startTimePoint, int numTimePoints, boolean returnLocals) throws Exception {
double startTime = Calendar.getInstance().getTimeInMillis();
double[] localMi = null;
if (returnLocals) {
localMi = new double[numTimePoints];
}
// Constants:
double invK = 1.0 / (double)k;
// Count the average number of points within eps_x and eps_y of each point
double sumDiGammas = 0;
double sumNx = 0;
double sumNy = 0;
for (int t = startTimePoint; t < startTimePoint + numTimePoints; t++) {
// Compute eps_x and eps_y for this time step by
// finding the kth closest neighbours for point t:
PriorityQueue<NeighbourNodeData> nnPQ =
kdTreeJoint.findKNearestNeighbours(k, t, dynCorrExclTime);
// Find eps_{x,y} as the maximum x and y norms amongst this set:
double eps_x = 0.0;
double eps_y = 0.0;
for (int j = 0; j < k; j++) {
// Take the furthest remaining of the nearest neighbours from the PQ:
NeighbourNodeData nnData = nnPQ.poll();
if (nnData.norms[0] > eps_x) {
eps_x = nnData.norms[0];
}
if (nnData.norms[1] > eps_y) {
eps_y = nnData.norms[1];
}
}
// Count the number of points whose x distance is less
// than or equal to eps_x, and whose y distance is less
// than or equal to eps_y
int n_x = nnSearcherSource.countPointsWithinOrOnR(
t, eps_x, dynCorrExclTime);
int n_y = nnSearcherDest.countPointsWithinOrOnR(
t, eps_y, dynCorrExclTime);
sumNx += n_x;
sumNy += n_y;
// And take the digammas:
double digammaNx = MathsUtils.digamma(n_x);
double digammaNy = MathsUtils.digamma(n_y);
sumDiGammas += digammaNx + digammaNy;
if (returnLocals) {
localMi[t-startTimePoint] = digammaK - invK - digammaNx - digammaNy + digammaN;
}
}
if (debug) {
Calendar rightNow2 = Calendar.getInstance();
long endTime = rightNow2.getTimeInMillis();
System.out.println("Subset " + startTimePoint + ":" +
(startTimePoint + numTimePoints) + " Calculation time: " +
((endTime - startTime)/1000.0) + " sec" );
}
// Select what to return:
if (returnLocals) {
return localMi;
} else {
return new double[] {sumDiGammas, sumNx, sumNy};
}
}
}