diff --git a/java/source/infodynamics/measures/discrete/DualTotalCorrelationCalculatorDiscrete.java b/java/source/infodynamics/measures/discrete/DualTotalCorrelationCalculatorDiscrete.java new file mode 100755 index 0000000..8bcbc93 --- /dev/null +++ b/java/source/infodynamics/measures/discrete/DualTotalCorrelationCalculatorDiscrete.java @@ -0,0 +1,84 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.MathsUtils; +import infodynamics.utils.MatrixUtils; + +/** + *

Computes the dual total correlation (DTC) of a given multivariate + * int[][] set of + * observations (extending {@link MultiVariateInfoMeasureCalculatorDiscrete}).

+ * + *

Usage is as per the paradigm outlined for {@link MultiVariateInfoMeasureCalculatorDiscrete}. + *

+ * + *

References:
+ *

+ * + * @author Pedro A.M. Mediano (email, + * www) + */ +public class DualTotalCorrelationCalculatorDiscrete + extends MultiVariateInfoMeasureCalculatorDiscrete { + + /** + * Construct an instance. + * + * @param base number of symbols for each variable. + * E.g. binary variables are in base-2. + * @param numVars numbers of joint variables that DTC + * will be computed over. + */ + public DualTotalCorrelationCalculatorDiscrete(int base, int numVars) { + super(base, numVars); + } + + protected double computeLocalValueForTuple(int[] tuple, int jointValue) { + + if (jointCount[jointValue] == 0) { + // This joint state does not occur, so it makes no contribution here + return 0; + } + + double jointProb = (double) jointCount[jointValue] / (double) observations; + double logValue = (numVars - 1) * Math.log(jointProb); + + for (int i = 0; i < numVars; i++) { + int marginalState = computeBigMarginalState(jointValue, i, tuple[i]); + double marginalProb = (double) bigMarginalCounts[i][marginalState] / (double) observations; + logValue -= Math.log(marginalProb); + } + + double localValue = logValue / log_2; + + if (jointProb > 0.0) { + checkLocals(localValue); + } + + return localValue; + } + +} + diff --git a/java/source/infodynamics/measures/discrete/OInfoCalculatorDiscrete.java b/java/source/infodynamics/measures/discrete/OInfoCalculatorDiscrete.java new file mode 100755 index 0000000..118df47 --- /dev/null +++ b/java/source/infodynamics/measures/discrete/OInfoCalculatorDiscrete.java @@ -0,0 +1,85 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.MathsUtils; +import infodynamics.utils.MatrixUtils; + +/** + *

Computes the O-information of a given multivariate + * int[][] set of + * observations (extending {@link MultiVariateInfoMeasureCalculatorDiscrete}).

+ * + *

Usage is as per the paradigm outlined for {@link MultiVariateInfoMeasureCalculatorDiscrete}. + *

+ * + *

References:
+ *

+ * + * @author Pedro A.M. Mediano (email, + * www) + */ +public class OInfoCalculatorDiscrete + extends MultiVariateInfoMeasureCalculatorDiscrete { + + /** + * Construct an instance. + * + * @param base number of symbols for each variable. + * E.g. binary variables are in base-2. + * @param numVars numbers of joint variables that DTC + * will be computed over. + */ + public OInfoCalculatorDiscrete(int base, int numVars) { + super(base, numVars); + } + + protected double computeLocalValueForTuple(int[] tuple, int jointValue) { + + if (jointCount[jointValue] == 0) { + // This joint state does not occur, so it makes no contribution here + return 0; + } + + double jointProb = (double) jointCount[jointValue] / (double) observations; + double logValue = (2 - numVars) * Math.log(jointProb); + + for (int i = 0; i < numVars; i++) { + int bigMarginalState = computeBigMarginalState(jointValue, i, tuple[i]); + double bigMarginalProb = (double) bigMarginalCounts[i][bigMarginalState] / (double) observations; + double smallMarginalProb = (double) smallMarginalCounts[i][tuple[i]] / (double) observations; + logValue += Math.log(bigMarginalProb) - Math.log(smallMarginalProb); + } + + double localValue = logValue / log_2; + + if (jointProb > 0.0) { + checkLocals(localValue); + } + + return localValue; + } + +} + diff --git a/java/source/infodynamics/measures/discrete/SInfoCalculatorDiscrete.java b/java/source/infodynamics/measures/discrete/SInfoCalculatorDiscrete.java new file mode 100755 index 0000000..150118d --- /dev/null +++ b/java/source/infodynamics/measures/discrete/SInfoCalculatorDiscrete.java @@ -0,0 +1,95 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.MathsUtils; +import infodynamics.utils.MatrixUtils; + +/** + *

Computes the S-information of a given multivariate + * int[][] set of + * observations (extending {@link MultiVariateInfoMeasureCalculatorDiscrete}).

+ * + *

Usage is as per the paradigm outlined for {@link MultiVariateInfoMeasureCalculatorDiscrete}. + *

+ * + *

References:
+ *

+ * + * @author Pedro A.M. Mediano (email, + * www) + */ +public class SInfoCalculatorDiscrete + extends MultiVariateInfoMeasureCalculatorDiscrete { + + /** + * Construct an instance. + * + * @param base number of symbols for each variable. + * E.g. binary variables are in base-2. + * @param numVars numbers of joint variables that DTC + * will be computed over. + */ + public SInfoCalculatorDiscrete(int base, int numVars) { + super(base, numVars); + } + + protected double computeLocalValueForTuple(int[] tuple, int jointValue) { + + if (jointCount[jointValue] == 0) { + // This joint state does not occur, so it makes no contribution here + return 0; + } + + double jointProb = (double) jointCount[jointValue] / (double) observations; + + // Local TC value + double localTC = Math.log(jointProb); + for (int i = 0; i < numVars; i++) { + int marginalState = tuple[i]; + double marginalProb = (double) smallMarginalCounts[i][marginalState] / (double) observations; + localTC -= Math.log(marginalProb); + } + + // Local DTC value + double localDTC = (numVars - 1) * Math.log(jointProb); + for (int i = 0; i < numVars; i++) { + int marginalState = computeBigMarginalState(jointValue, i, tuple[i]); + double marginalProb = (double) bigMarginalCounts[i][marginalState] / (double) observations; + localDTC -= Math.log(marginalProb); + } + + // Combine local TC and DTC into S-info + double logValue = localTC + localDTC; + double localValue = logValue / log_2; + + if (jointProb > 0.0) { + checkLocals(localValue); + } + + return localValue; + } + +} + diff --git a/java/unittests/infodynamics/measures/discrete/DualTotalCorrelationTester.java b/java/unittests/infodynamics/measures/discrete/DualTotalCorrelationTester.java new file mode 100755 index 0000000..5557e6b --- /dev/null +++ b/java/unittests/infodynamics/measures/discrete/DualTotalCorrelationTester.java @@ -0,0 +1,108 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.RandomGenerator; +import infodynamics.utils.MatrixUtils; +import infodynamics.utils.MathsUtils; + +import java.util.Arrays; +import junit.framework.TestCase; + + +public class DualTotalCorrelationTester extends TestCase { + + public void testIndependent() throws Exception { + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 3); + double dtc = dtcCalc.compute(new int[][] {{0,0,0},{0,0,1},{0,1,0},{0,1,1},{1,0,0},{1,0,1},{1,1,0},{1,1,1}}); + assertEquals(0.0, dtc, 0.000001); + } + + public void testXor() throws Exception { + // 3 variables + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 3); + double dtc = dtcCalc.compute(new int[][] {{0,0,1},{0,1,0},{1,0,0},{1,1,1}}); + assertEquals(2.0, dtc, 0.000001); + + // 4 variables + dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 4); + dtc = dtcCalc.compute(new int[][] {{0,0,0,1},{0,0,1,0},{0,1,0,0},{1,0,0,0},{1,1,1,0},{1,1,0,1},{1,0,1,1},{0,1,1,1}}); + assertEquals(3.0, dtc, 0.000001); + } + + public void testCopy() throws Exception { + // 3 variables + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 3); + double dtc = dtcCalc.compute(new int[][] {{0,0,0},{1,1,1}}); + assertEquals(1.0, dtc, 0.000001); + + // 4 variables + dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 4); + dtc = dtcCalc.compute(new int[][] {{0,0,0,0},{1,1,1,1}}); + assertEquals(1.0, dtc, 0.000001); + } + + public void testCompareEntropy() throws Exception { + // Generate random data and check that it matches the explicit computation + // using entropy calculators + RandomGenerator rg = new RandomGenerator(); + int D = 4; + int[][] data = rg.generateRandomInts(10, D, 2); + + // DTC calculator + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, D); + double dtc_direct = dtcCalc.compute(data); + + // Entropy calculators + EntropyCalculatorDiscrete hCalc = new EntropyCalculatorDiscrete(MathsUtils.power(2, D)); + hCalc.initialise(); + hCalc.addObservations(MatrixUtils.computeCombinedValues(data, 2)); + double dtc_test = (1 - D) * hCalc.computeAverageLocalOfObservations(); + + hCalc = new EntropyCalculatorDiscrete(MathsUtils.power(2, D-1)); + for (int i = 0; i < 4; i++) { + hCalc.initialise(); + hCalc.addObservations(MatrixUtils.computeCombinedValues(MatrixUtils.selectColumns(data, allExcept(i, D)), 2)); + dtc_test += hCalc.computeAverageLocalOfObservations(); + } + + assertEquals(dtc_direct, dtc_test, 0.000001); + + } + + protected int[] allExcept(int idx, int N) { + boolean[] v = new boolean[N]; + Arrays.fill(v, true); + v[idx] = false; + + int[] v2 = new int[N - 1]; + int counter = 0; + for (int i = 0; i < N; i++) { + if (v[i]) { + v2[counter] = i; + counter++; + } + } + + return v2; + } + + +} + diff --git a/java/unittests/infodynamics/measures/discrete/OInfoTester.java b/java/unittests/infodynamics/measures/discrete/OInfoTester.java new file mode 100755 index 0000000..9d9c47b --- /dev/null +++ b/java/unittests/infodynamics/measures/discrete/OInfoTester.java @@ -0,0 +1,87 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.RandomGenerator; + +import junit.framework.TestCase; + +public class OInfoTester extends TestCase { + + public void testIndependent() throws Exception { + OInfoCalculatorDiscrete oCalc = new OInfoCalculatorDiscrete(2, 3); + double oinfo = oCalc.compute(new int[][] {{0,0,0},{0,0,1},{0,1,0},{0,1,1},{1,0,0},{1,0,1},{1,1,0},{1,1,1}}); + assertEquals(0.0, oinfo, 0.000001); + } + + public void testXor() throws Exception { + // 3 variables + OInfoCalculatorDiscrete oCalc = new OInfoCalculatorDiscrete(2, 3); + double oinfo = oCalc.compute(new int[][] {{0,0,1},{0,1,0},{1,0,0},{1,1,1}}); + assertEquals(-1.0, oinfo, 0.000001); + + // 4 variables + oCalc = new OInfoCalculatorDiscrete(2, 4); + oinfo = oCalc.compute(new int[][] {{0,0,0,1},{0,0,1,0},{0,1,0,0},{1,0,0,0},{1,1,1,0},{1,1,0,1},{1,0,1,1},{0,1,1,1}}); + assertEquals(-2.0, oinfo, 0.000001); + } + + public void testCopy() throws Exception { + // 3 variables + OInfoCalculatorDiscrete oCalc = new OInfoCalculatorDiscrete(2, 3); + double oinfo = oCalc.compute(new int[][] {{0,0,0},{1,1,1}}); + assertEquals(1.0, oinfo, 0.000001); + + // 4 variables + oCalc = new OInfoCalculatorDiscrete(2, 4); + oinfo = oCalc.compute(new int[][] {{0,0,0,0},{1,1,1,1}}); + assertEquals(2.0, oinfo, 0.000001); + } + + public void testPairwise() throws Exception { + // Variables 0 and 1 are correlated and independent from 2 and 3, that are + // also correlated + OInfoCalculatorDiscrete oCalc = new OInfoCalculatorDiscrete(2, 4); + double oinfo = oCalc.compute(new int[][] {{0,0,0,0},{0,0,1,1},{1,1,0,0},{1,1,1,1}}); + assertEquals(0.0, oinfo, 0.000001); + } + + public void testCompareTCAndDTC() throws Exception { + // Generate random data and check that it matches the explicit computation + // using TC and DTC calculators + RandomGenerator rg = new RandomGenerator(); + int[][] data = rg.generateRandomInts(10, 4, 2); + + // O-info calculator + OInfoCalculatorDiscrete oCalc = new OInfoCalculatorDiscrete(2, 4); + double oinfo_direct = oCalc.compute(data); + + // TC and DTC calculators + MultiInformationCalculatorDiscrete tcCalc = new MultiInformationCalculatorDiscrete(2, 4); + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 4); + tcCalc.initialise(); + tcCalc.addObservations(data); + double oinfo_test = tcCalc.computeAverageLocalOfObservations() - dtcCalc.compute(data); + + assertEquals(oinfo_direct, oinfo_test, 0.000001); + + } + +} + diff --git a/java/unittests/infodynamics/measures/discrete/SInfoTester.java b/java/unittests/infodynamics/measures/discrete/SInfoTester.java new file mode 100755 index 0000000..959c18f --- /dev/null +++ b/java/unittests/infodynamics/measures/discrete/SInfoTester.java @@ -0,0 +1,79 @@ +/* + * 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 . + */ + +package infodynamics.measures.discrete; + +import infodynamics.utils.RandomGenerator; + +import junit.framework.TestCase; + +public class SInfoTester extends TestCase { + + public void testIndependent() throws Exception { + SInfoCalculatorDiscrete sCalc = new SInfoCalculatorDiscrete(2, 3); + double sinfo = sCalc.compute(new int[][] {{0,0,0},{0,0,1},{0,1,0},{0,1,1},{1,0,0},{1,0,1},{1,1,0},{1,1,1}}); + assertEquals(0.0, sinfo, 0.000001); + } + + public void testXor() throws Exception { + // 3 variables + SInfoCalculatorDiscrete sCalc = new SInfoCalculatorDiscrete(2, 3); + double sinfo = sCalc.compute(new int[][] {{0,0,1},{0,1,0},{1,0,0},{1,1,1}}); + assertEquals(3.0, sinfo, 0.000001); + + // 4 variables + sCalc = new SInfoCalculatorDiscrete(2, 4); + sinfo = sCalc.compute(new int[][] {{0,0,0,1},{0,0,1,0},{0,1,0,0},{1,0,0,0},{1,1,1,0},{1,1,0,1},{1,0,1,1},{0,1,1,1}}); + assertEquals(4.0, sinfo, 0.000001); + } + + public void testCopy() throws Exception { + // 3 variables + SInfoCalculatorDiscrete sCalc = new SInfoCalculatorDiscrete(2, 3); + double sinfo = sCalc.compute(new int[][] {{0,0,0},{1,1,1}}); + assertEquals(3.0, sinfo, 0.000001); + + // 4 variables + sCalc = new SInfoCalculatorDiscrete(2, 4); + sinfo = sCalc.compute(new int[][] {{0,0,0,0},{1,1,1,1}}); + assertEquals(4.0, sinfo, 0.000001); + } + + public void testCompareTCAndDTC() throws Exception { + // Generate random data and check that it matches the explicit computation + // using TC and DTC calculators + RandomGenerator rg = new RandomGenerator(); + int[][] data = rg.generateRandomInts(10, 4, 2); + + // O-info calculator + SInfoCalculatorDiscrete sCalc = new SInfoCalculatorDiscrete(2, 4); + double sinfo_direct = sCalc.compute(data); + + // TC and DTC calculators + MultiInformationCalculatorDiscrete tcCalc = new MultiInformationCalculatorDiscrete(2, 4); + DualTotalCorrelationCalculatorDiscrete dtcCalc = new DualTotalCorrelationCalculatorDiscrete(2, 4); + tcCalc.initialise(); + tcCalc.addObservations(data); + double sinfo_test = tcCalc.computeAverageLocalOfObservations() + dtcCalc.compute(data); + + assertEquals(sinfo_direct, sinfo_test, 0.000001); + + } + +} +