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Adding tests for determinant via Cholesky decomposition, and more tests for MI by Gaussian method

This commit is contained in:
joseph.lizier 2012-08-17 07:30:08 +00:00
parent 07ce2d0e24
commit 4a19b41a76
3 changed files with 96 additions and 5 deletions
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27
java/unittests/infodynamics/measures/continuous/gaussian/MutualInfoMultiVariateTester.java
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@ -2,11 +2,13 @@ package infodynamics.measures.continuous.gaussian;
import junit.framework.TestCase;
import infodynamics.utils.EmpiricalMeasurementDistribution;
import infodynamics.utils.MatrixUtils;
import infodynamics.utils.MatrixUtilsTest;
import infodynamics.utils.RandomGenerator;
public class MutualInfoMultiVariateTester extends TestCase {
public void testCovarianceDoesntMatchDimensions(){
public void testCovarianceDoesntMatchDimensions() throws Exception {
MutualInfoCalculatorMultiVariateGaussian miCalc =
new MutualInfoCalculatorMultiVariateGaussian();
miCalc.initialise(1, 1);
@ -44,8 +46,10 @@ public class MutualInfoMultiVariateTester extends TestCase {
caughtException = true;
}
assertFalse(caughtException);
// and that this covariance has been set:
assertEquals(goodCovariance, miCalc.covariance);
// and that this covariance has been set (by verifying the Cholesky
// decomposition of it is stored):
MatrixUtilsTest.checkMatrix(MatrixUtils.CholeskyDecomposition(goodCovariance),
miCalc.L, 0.00001);
}
public void testAnalyticMatchesCouplingValue() throws Exception {
@ -66,6 +70,23 @@ public class MutualInfoMultiVariateTester extends TestCase {
}
}
public void testMIfromSuppliedCovariance() throws Exception {
MutualInfoCalculatorMultiVariateGaussian miCalc =
new MutualInfoCalculatorMultiVariateGaussian();
double[][] covarianceMatrix = {{5, 3}, {3, 4}}; // det is 11
miCalc.initialise(1, 1);
miCalc.setCovariance(covarianceMatrix);
assertEquals(0.5 * Math.log(20.0 / 11.0),
miCalc.computeAverageLocalOfObservations(), 0.00000000001);
double[][] covarianceMatrix2 = {{5, 3, 1}, {3, 4, 1.5}, {1, 1.5, 2}}; // det is 15.75
miCalc.initialise(2, 1);
miCalc.setCovariance(covarianceMatrix2);
assertEquals(0.5 * Math.log(11.0 * 2.0 / 15.75), // marginal dets are 11 and 2
miCalc.computeAverageLocalOfObservations(), 0.00000000001);
}
public void testComputeSignificanceDoesntAlterAverage() throws Exception {

1
java/unittests/infodynamics/measures/continuous/gaussian/MutualInfoMultiVariateWithDiscreteTester.java
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@ -63,6 +63,7 @@ public class MutualInfoMultiVariateWithDiscreteTester extends TestCase {
miCalc.setObservations(contDataCorrect, discDataCorrect);
} catch (Exception e) {
caughtException = true;
e.printStackTrace();
}
assertFalse(caughtException);

73
java/unittests/infodynamics/utils/MatrixUtilsTest.java
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@ -136,8 +136,77 @@ public class MatrixUtilsTest extends TestCase {
// Check more complicated example
double[][] A2 = {{6, 2, 3, 1}, {2, 5, 1, 0.5}, {3, 1, 4, 2}, {1, 0.5, 2, 3}};
double[][] B2 = {{10, 5, 4, 12}, {4, 6, -1, 4.3}, {20, 1, 0, -5}, {6, 3, 2, 1}};
double[][] expectedX2 = {{-1.740519, 1.019960, 1.445110, 4.600798},
{0.247505, 0.942116, -0.590818, -0.042315},
{7.461078, -1.502994, -1.616766, -6.140120},
{-2.435130, 1.504990, 1.361277, 2.900200}};
double[][] X2 = MatrixUtils.solveViaCholeskyResult(
MatrixUtils.CholeskyDecomposition(A2), B2);
checkMatrix(expectedX2, X2, OCTAVE_RESOLUTION);
// Check error conditions
// TODO Check error conditions
}
public void testDeterminant() throws Exception {
// test some error conditions:
double[][] AnonSquare = {{6, 2}, {2, 5, 1}, {3, 1, 4}};
boolean flaggedException = false;
try {
MatrixUtils.determinant(AnonSquare);
} catch (Exception e) {
flaggedException = true;
}
assertTrue(flaggedException);
// Test some simple examples:
double[][] A1 = {{3.445454}};
assertEquals(3.445454, MatrixUtils.determinant(A1), OCTAVE_RESOLUTION);
double[][] A2 = {{6, 2}, {2, 5}};
assertEquals(26, MatrixUtils.determinant(A2), OCTAVE_RESOLUTION);
// Check against value computed by Octave:
double[][] A = {{6, 2, 3}, {2, 5, 1}, {3, 1, 4}};
assertEquals(65, MatrixUtils.determinant(A), OCTAVE_RESOLUTION);
// Check zero determinant case
double[][] AzeroDet = {{6, 2, 3}, {2, 5, 1}, {10, -14, 5}};
assertEquals(0, MatrixUtils.determinant(AzeroDet), OCTAVE_RESOLUTION);
}
public void testDeterminantSymmPosDef() throws Exception {
// Test some simple examples:
double[][] A1 = {{3.445454}};
assertEquals(3.445454,
MatrixUtils.determinantSymmPosDefMatrix(A1), OCTAVE_RESOLUTION);
double[][] A2 = {{6, 2}, {2, 5}};
assertEquals(26, MatrixUtils.determinantSymmPosDefMatrix(A2), OCTAVE_RESOLUTION);
// Check against value computed by Octave:
double[][] A = {{6, 2, 3}, {2, 5, 1}, {3, 1, 4}};
assertEquals(65, MatrixUtils.determinantSymmPosDefMatrix(A), OCTAVE_RESOLUTION);
// Now check that it picks up asymmetric A:
double[][] asymmetricA = {{6, 2, 3}, {2, 5, 1}, {3, 1.0001, 4}};
boolean flaggedException = false;
try {
MatrixUtils.determinantSymmPosDefMatrix(asymmetricA);
} catch (Exception e) {
flaggedException = true;
}
assertTrue(flaggedException);
// Now check that it picks up if A is not positive definite:
double[][] notpositiveDefiniteA = {{1, 2, 3}, {2, 4, 5}, {3, 5, 6}};
flaggedException = false;
try {
MatrixUtils.determinantSymmPosDefMatrix(notpositiveDefiniteA);
} catch (Exception e) {
flaggedException = true;
}
assertTrue(flaggedException);
}
/**
@ -148,7 +217,7 @@ public class MatrixUtilsTest extends TestCase {
* @param actual
* @param resolution
*/
protected void checkMatrix(double[][] expected, double[][] actual, double resolution) {
public static void checkMatrix(double[][] expected, double[][] actual, double resolution) {
for (int r = 0; r < expected.length; r++) {
for (int c = 0; c < expected[r].length; c++) {
assertEquals(expected[r][c], actual[r][c], resolution);