fixed checkstyle and findbugs errors
git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@754765 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe
parent
77a6b785d2
commit
39647f7f30
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@ -55,12 +55,12 @@
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<!-- the following expositions of internal representation are intentional and documented -->
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<Match>
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<Class name="org.apache.commons.math.optimization.PointValuePair"/>
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<Class name="org.apache.commons.math.optimization.ScalarPointValuePair"/>
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<Method name="getPointRef" params="" returns="double[]" />
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<Bug pattern="EI_EXPOSE_REP" />
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</Match>
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<Match>
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<Class name="org.apache.commons.math.optimization.PointValuePair"/>
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<Class name="org.apache.commons.math.optimization.ScalarPointValuePair"/>
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<Method name="<init>" params="double[],double,boolean" returns="void" />
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<Bug pattern="EI_EXPOSE_REP2" />
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</Match>
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@ -68,7 +68,7 @@ public interface ScalarDifferentiableOptimizer extends Serializable {
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void setConvergenceChecker(ScalarConvergenceChecker checker);
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/** Get the convergence checker.
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* @param checker object to use to check for convergence
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* @return object used to check for convergence
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*/
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ScalarConvergenceChecker getConvergenceChecker();
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@ -68,7 +68,7 @@ public interface ScalarOptimizer extends Serializable {
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void setConvergenceChecker(ScalarConvergenceChecker checker);
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/** Get the convergence checker.
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* @param checker object to use to check for convergence
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* @return object used to check for convergence
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*/
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ScalarConvergenceChecker getConvergenceChecker();
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@ -56,7 +56,7 @@ public class ScalarPointValuePair implements Serializable {
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* it will be referenced
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*/
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public ScalarPointValuePair(final double[] point, final double value,
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final boolean copyArray) {
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final boolean copyArray) {
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this.point = copyArray ? point.clone() : point;
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this.value = value;
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}
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@ -78,7 +78,7 @@ public interface VectorialDifferentiableOptimizer extends Serializable {
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void setConvergenceChecker(VectorialConvergenceChecker checker);
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/** Get the convergence checker.
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* @param checker object to use to check for convergence
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* @return object used to check for convergence
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*/
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VectorialConvergenceChecker getConvergenceChecker();
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@ -313,7 +313,8 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer {
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/** Build an initial simplex.
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* @param startPoint the start point for optimization
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* @exception IllegalArgumentException
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* @exception IllegalArgumentException if the start point does not match
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* simplex dimension
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*/
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private void buildSimplex(final double[] startPoint)
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throws IllegalArgumentException {
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@ -303,8 +303,8 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen
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// store least squares problem characteristics
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this.f = f;
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this.target = target;
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this.weights = weights;
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this.target = target.clone();
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this.weights = weights.clone();
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this.variables = startPoint.clone();
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this.residuals = new double[target.length];
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@ -320,6 +320,11 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen
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}
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/** Perform the bulk of optimization algorithm.
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* @return the point/value pair giving the optimal value for objective function
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* @exception ObjectiveException if the objective function throws one during
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* the search
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* @exception OptimizationException if the algorithm failed to converge
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* @exception IllegalArgumentException if the start point dimension is wrong
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*/
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abstract protected VectorialPointValuePair doOptimize()
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throws ObjectiveException, OptimizationException, IllegalArgumentException;
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@ -55,7 +55,7 @@ public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer {
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* and the maximal number of evaluation is set to
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* {@link AbstractLeastSquaresOptimizer#DEFAULT_MAX_EVALUATIONS}.
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* @param useLU if true, the normal equations will be solved using LU
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* decomposition, otherwise it will be solved using QR decomposition
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* decomposition, otherwise they will be solved using QR decomposition
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*/
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public GaussNewtonOptimizer(final boolean useLU) {
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this.useLU = useLU;
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@ -60,7 +60,10 @@ import org.apache.commons.math.linear.decomposition.NotPositiveDefiniteMatrixExc
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*/
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public class CorrelatedRandomVectorGenerator
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implements RandomVectorGenerator {
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implements RandomVectorGenerator {
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/** Serializable version identifier. */
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private static final long serialVersionUID = -7162933284241468177L;
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/** Simple constructor.
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* <p>Build a correlated random vector generator from its mean
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@ -27,6 +27,9 @@ package org.apache.commons.math.random;
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public class GaussianRandomGenerator implements NormalizedRandomGenerator {
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/** Serializable version identifier. */
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private static final long serialVersionUID = -4698731518385853565L;
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/** Create a new generator.
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* @param generator underlying random generator to use
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*/
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@ -17,6 +17,8 @@
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package org.apache.commons.math.random;
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import java.io.Serializable;
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/**
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* This interface represent a normalized random generator for
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* scalars.
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@ -24,7 +26,7 @@ package org.apache.commons.math.random;
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* @version $Revision$ $Date$
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* @since 1.2
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*/
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public interface NormalizedRandomGenerator {
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public interface NormalizedRandomGenerator extends Serializable {
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/** Generate a random scalar with null mean and unit standard deviation.
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* <p>This method does <strong>not</strong> specify the shape of the
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@ -17,6 +17,8 @@
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package org.apache.commons.math.random;
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import java.io.Serializable;
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/** This interface represents a random generator for whole vectors.
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*
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* @since 1.2
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@ -24,7 +26,7 @@ package org.apache.commons.math.random;
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*
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*/
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public interface RandomVectorGenerator {
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public interface RandomVectorGenerator extends Serializable {
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/** Generate a random vector.
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* @return a random vector as an array of double.
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@ -31,6 +31,9 @@ import java.util.Arrays;
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public class UncorrelatedRandomVectorGenerator
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implements RandomVectorGenerator {
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/** Serializable version identifier. */
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private static final long serialVersionUID = -3268228248001718811L;
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/** Simple constructor.
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* <p>Build an uncorrelated random vector generator from
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* its mean and standard deviation vectors.</p>
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@ -31,6 +31,9 @@ package org.apache.commons.math.random;
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public class UniformRandomGenerator implements NormalizedRandomGenerator {
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/** Serializable version identifier. */
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private static final long serialVersionUID = 1569292426375546027L;
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/** Create a new generator.
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* @param generator underlying random generator to use
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*/
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@ -549,8 +549,8 @@ public final class MathUtils {
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* <code>0</code>.</li>
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* </ul>
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*
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* @param u any number
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* @param v any number
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* @param p any number
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* @param q any number
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* @return the greatest common divisor, never negative
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* @throws ArithmeticException
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* if the result cannot be represented as a nonnegative int
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@ -112,6 +112,7 @@ extends TestCase {
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optimizer.optimize(problem, problem.target, new double[] { 1 }, new double[] { 0 });
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assertEquals(0, optimizer.getRMS(), 1.0e-10);
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assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
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assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
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}
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public void testColumnsPermutation() throws ObjectiveException, OptimizationException {
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@ -128,6 +129,9 @@ extends TestCase {
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assertEquals(0, optimizer.getRMS(), 1.0e-10);
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assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
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assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
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assertEquals(4.0, optimum.getValue()[0], 1.0e-10);
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assertEquals(6.0, optimum.getValue()[1], 1.0e-10);
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assertEquals(1.0, optimum.getValue()[2], 1.0e-10);
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}
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@ -119,13 +119,14 @@ public class LevenbergMarquardtOptimizerTest
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fail("wrong exception caught");
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}
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assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
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assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
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}
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public void testQRColumnsPermutation() throws ObjectiveException, OptimizationException {
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LinearProblem problem =
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new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
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new double[] { 4.0, 6.0, 1.0 });
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new double[] { 4.0, 6.0, 1.0 });
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LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
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VectorialPointValuePair optimum =
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@ -133,6 +134,9 @@ public class LevenbergMarquardtOptimizerTest
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assertEquals(0, optimizer.getRMS(), 1.0e-10);
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assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
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assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
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assertEquals(4.0, optimum.getValue()[0], 1.0e-10);
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assertEquals(6.0, optimum.getValue()[1], 1.0e-10);
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assertEquals(1.0, optimum.getValue()[2], 1.0e-10);
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}
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