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MATH-924 

Avoid memory exhaustion for large number of unclorrelated observations.


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1426759 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski 2012-12-29 13:26:44 +00:00
parent b07ecae3d6
commit 2836a6f9ef
3 changed files with 41 additions and 8 deletions
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8
src/main/java/org/apache/commons/math3/optimization/Weight.java
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@ -18,7 +18,7 @@
package org.apache.commons.math3.optimization;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.Array2DRowRealMatrix;
import org.apache.commons.math3.linear.DiagonalMatrix;
import org.apache.commons.math3.linear.NonSquareMatrixException;
/**
@ -41,11 +41,7 @@ public class Weight implements OptimizationData {
* @param weight List of the values of the diagonal.
*/
public Weight(double[] weight) {
final int dim = weight.length;
weightMatrix = new Array2DRowRealMatrix(dim, dim);
for (int i = 0; i < dim; i++) {
weightMatrix.setEntry(i, i, weight[i]);
}
weightMatrix = new DiagonalMatrix(weight);
}
/**

14
src/main/java/org/apache/commons/math3/optimization/general/AbstractLeastSquaresOptimizer.java
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@ -26,6 +26,7 @@ import org.apache.commons.math3.exception.NumberIsTooSmallException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.linear.ArrayRealVector;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.DiagonalMatrix;
import org.apache.commons.math3.linear.DecompositionSolver;
import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.QRDecomposition;
@ -558,7 +559,16 @@ public abstract class AbstractLeastSquaresOptimizer
* @return the square-root of the weight matrix.
*/
private RealMatrix squareRoot(RealMatrix m) {
final EigenDecomposition dec = new EigenDecomposition(m);
return dec.getSquareRoot();
if (m instanceof DiagonalMatrix) {
final int dim = m.getRowDimension();
final RealMatrix sqrtM = new DiagonalMatrix(dim);
for (int i = 0; i < dim; i++) {
sqrtM.setEntry(i, i, FastMath.sqrt(m.getEntry(i, i)));
}
return sqrtM;
} else {
final EigenDecomposition dec = new EigenDecomposition(m);
return dec.getSquareRoot();
}
}
}

27
src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
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@ -223,6 +223,33 @@ public class PolynomialFitterTest {
checkUnsolvableProblem(new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-15, 1e-15)), false);
}
@Test
public void testLargeSample() {
Random randomizer = new Random(0x5551480dca5b369bl);
double maxError = 0;
for (int degree = 0; degree < 10; ++degree) {
PolynomialFunction p = buildRandomPolynomial(degree, randomizer);
PolynomialFitter fitter = new PolynomialFitter(new LevenbergMarquardtOptimizer());
for (int i = 0; i < 40000; ++i) {
double x = -1.0 + i / 20000.0;
fitter.addObservedPoint(1.0, x,
p.value(x) + 0.1 * randomizer.nextGaussian());
}
final double[] init = new double[degree + 1];
PolynomialFunction fitted = new PolynomialFunction(fitter.fit(init));
for (double x = -1.0; x < 1.0; x += 0.01) {
double error = FastMath.abs(p.value(x) - fitted.value(x)) /
(1.0 + FastMath.abs(p.value(x)));
maxError = FastMath.max(maxError, error);
Assert.assertTrue(FastMath.abs(error) < 0.01);
}
}
Assert.assertTrue(maxError > 0.001);
}
private void checkUnsolvableProblem(DifferentiableMultivariateVectorOptimizer optimizer,
boolean solvable) {
Random randomizer = new Random(1248788532l);