From 87c0ddbc6e6143680ded83b3b63a6029ebc3b8ba Mon Sep 17 00:00:00 2001 From: Luc Maisonobe Date: Sun, 22 Mar 2009 13:00:00 +0000 Subject: [PATCH] separated iteration counter from function evaluation counters, some optimizers are based on gradient/jacobian only and cannot reliably be protected by monitoring the objective function calls. We now have two or three counters for each algorithm: - iteration counter, which is checked against a max allowance to prevent infinite loops if no convergence is reached - objective function evaluations, for user information only - objective function gradient/jacobian if the function is differentiable, for user information only git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@757181 13f79535-47bb-0310-9956-ffa450edef68 --- .../commons/math/MessagesResources_fr.java | 3 +- ...ltiStartScalarDifferentiableOptimizer.java | 62 +++++++++++------ .../MultiStartScalarOptimizer.java | 45 +++++++----- ...StartVectorialDifferentiableOptimizer.java | 47 ++++++++----- .../optimization/OptimizationException.java | 10 ++- .../ScalarDifferentiableOptimizer.java | 51 ++++++++------ .../math/optimization/ScalarOptimizer.java | 39 +++++------ .../VectorialDifferentiableOptimizer.java | 29 +++----- .../direct/DirectSearchOptimizer.java | 64 ++++++++++------- .../optimization/direct/MultiDirectional.java | 9 +-- .../math/optimization/direct/NelderMead.java | 5 +- .../AbstractLeastSquaresOptimizer.java | 68 +++++++++++-------- .../general/GaussNewtonOptimizer.java | 9 +-- .../general/LevenbergMarquardtOptimizer.java | 6 +- .../direct/MultiDirectionalTest.java | 14 ++-- .../optimization/direct/NelderMeadTest.java | 14 ++-- .../general/GaussNewtonOptimizerTest.java | 30 ++++---- .../LevenbergMarquardtOptimizerTest.java | 2 +- .../optimization/general/MinpackTest.java | 4 +- 19 files changed, 293 insertions(+), 218 deletions(-) diff --git a/src/java/org/apache/commons/math/MessagesResources_fr.java b/src/java/org/apache/commons/math/MessagesResources_fr.java index 6492e4c98..4855b960c 100644 --- a/src/java/org/apache/commons/math/MessagesResources_fr.java +++ b/src/java/org/apache/commons/math/MessagesResources_fr.java @@ -118,8 +118,7 @@ public class MessagesResources_fr { "equals vertices {0} and {1} in simplex configuration", "sommets {0} et {1} \u00e9gaux dans la configuration du simplex" }, - // org.apache.commons.math.optimization.direct.DirectSearchOptimizer - // org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer + // org.apache.commons.math.estimation.AbstractEstimation { "maximal number of evaluations exceeded ({0})", "nombre maximal d''\u00e9valuations d\u00e9pass\u00e9 ({0})" }, diff --git a/src/java/org/apache/commons/math/optimization/MultiStartScalarDifferentiableOptimizer.java b/src/java/org/apache/commons/math/optimization/MultiStartScalarDifferentiableOptimizer.java index 7ebd4db20..5aa7d2d9f 100644 --- a/src/java/org/apache/commons/math/optimization/MultiStartScalarDifferentiableOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/MultiStartScalarDifferentiableOptimizer.java @@ -38,16 +38,22 @@ import org.apache.commons.math.random.RandomVectorGenerator; public class MultiStartScalarDifferentiableOptimizer implements ScalarDifferentiableOptimizer { /** Serializable version identifier. */ - private static final long serialVersionUID = 9008747186334431824L; + private static final long serialVersionUID = 6185821146433609962L; /** Underlying classical optimizer. */ private final ScalarDifferentiableOptimizer optimizer; + /** Maximal number of iterations allowed. */ + private int maxIterations; + + /** Number of iterations already performed for all starts. */ + private int totalIterations; + /** Number of evaluations already performed for all starts. */ private int totalEvaluations; - /** Maximal number of evaluations allowed. */ - private int maxEvaluations; + /** Number of gradient evaluations already performed for all starts. */ + private int totalGradientEvaluations; /** Number of starts to go. */ private int starts; @@ -69,12 +75,14 @@ public class MultiStartScalarDifferentiableOptimizer implements ScalarDifferenti public MultiStartScalarDifferentiableOptimizer(final ScalarDifferentiableOptimizer optimizer, final int starts, final RandomVectorGenerator generator) { - this.optimizer = optimizer; - this.totalEvaluations = 0; - this.maxEvaluations = Integer.MAX_VALUE; - this.starts = starts; - this.generator = generator; - this.optima = null; + this.optimizer = optimizer; + this.maxIterations = Integer.MAX_VALUE; + this.totalIterations = 0; + this.totalEvaluations = 0; + this.totalGradientEvaluations = 0; + this.starts = starts; + this.generator = generator; + this.optima = null; } /** Get all the optima found during the last call to {@link @@ -110,19 +118,29 @@ public class MultiStartScalarDifferentiableOptimizer implements ScalarDifferenti return (ScalarPointValuePair[]) optima.clone(); } + /** {@inheritDoc} */ + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; + } + + /** {@inheritDoc} */ + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return totalIterations; + } + /** {@inheritDoc} */ public int getEvaluations() { return totalEvaluations; } /** {@inheritDoc} */ - public void setMaxEvaluations(int maxEvaluations) { - this.maxEvaluations = maxEvaluations; - } - - /** {@inheritDoc} */ - public int getMaxEvaluations() { - return maxEvaluations; + public int getGradientEvaluations() { + return totalGradientEvaluations; } /** {@inheritDoc} */ @@ -141,14 +159,16 @@ public class MultiStartScalarDifferentiableOptimizer implements ScalarDifferenti double[] startPoint) throws ObjectiveException, OptimizationException { - optima = new ScalarPointValuePair[starts]; - totalEvaluations = 0; + optima = new ScalarPointValuePair[starts]; + totalIterations = 0; + totalEvaluations = 0; + totalGradientEvaluations = 0; // multi-start loop for (int i = 0; i < starts; ++i) { try { - optimizer.setMaxEvaluations(maxEvaluations - totalEvaluations); + optimizer.setMaxIterations(maxIterations - totalIterations); optima[i] = optimizer.optimize(f, goalType, (i == 0) ? startPoint : generator.nextVector()); } catch (ObjectiveException obe) { @@ -157,7 +177,9 @@ public class MultiStartScalarDifferentiableOptimizer implements ScalarDifferenti optima[i] = null; } - totalEvaluations += optimizer.getEvaluations(); + totalIterations += optimizer.getIterations(); + totalEvaluations += optimizer.getEvaluations(); + totalGradientEvaluations += optimizer.getGradientEvaluations(); } diff --git a/src/java/org/apache/commons/math/optimization/MultiStartScalarOptimizer.java b/src/java/org/apache/commons/math/optimization/MultiStartScalarOptimizer.java index 234367c65..4c6043337 100644 --- a/src/java/org/apache/commons/math/optimization/MultiStartScalarOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/MultiStartScalarOptimizer.java @@ -38,17 +38,20 @@ import org.apache.commons.math.random.RandomVectorGenerator; public class MultiStartScalarOptimizer implements ScalarOptimizer { /** Serializable version identifier. */ - private static final long serialVersionUID = 6648351778723282863L; + private static final long serialVersionUID = -7333253288301713047L; /** Underlying classical optimizer. */ private final ScalarOptimizer optimizer; + /** Maximal number of iterations allowed. */ + private int maxIterations; + + /** Number of iterations already performed for all starts. */ + private int totalIterations; + /** Number of evaluations already performed for all starts. */ private int totalEvaluations; - /** Maximal number of evaluations allowed. */ - private int maxEvaluations; - /** Number of starts to go. */ private int starts; @@ -69,8 +72,9 @@ public class MultiStartScalarOptimizer implements ScalarOptimizer { public MultiStartScalarOptimizer(final ScalarOptimizer optimizer, final int starts, final RandomVectorGenerator generator) { this.optimizer = optimizer; + this.maxIterations = Integer.MAX_VALUE; + this.totalIterations = 0; this.totalEvaluations = 0; - this.maxEvaluations = Integer.MAX_VALUE; this.starts = starts; this.generator = generator; this.optima = null; @@ -109,21 +113,26 @@ public class MultiStartScalarOptimizer implements ScalarOptimizer { return (ScalarPointValuePair[]) optima.clone(); } + /** {@inheritDoc} */ + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; + } + + /** {@inheritDoc} */ + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return totalIterations; + } + /** {@inheritDoc} */ public int getEvaluations() { return totalEvaluations; } - /** {@inheritDoc} */ - public void setMaxEvaluations(int maxEvaluations) { - this.maxEvaluations = maxEvaluations; - } - - /** {@inheritDoc} */ - public int getMaxEvaluations() { - return maxEvaluations; - } - /** {@inheritDoc} */ public void setConvergenceChecker(ScalarConvergenceChecker checker) { optimizer.setConvergenceChecker(checker); @@ -140,14 +149,15 @@ public class MultiStartScalarOptimizer implements ScalarOptimizer { double[] startPoint) throws ObjectiveException, OptimizationException { - optima = new ScalarPointValuePair[starts]; + optima = new ScalarPointValuePair[starts]; + totalIterations = 0; totalEvaluations = 0; // multi-start loop for (int i = 0; i < starts; ++i) { try { - optimizer.setMaxEvaluations(maxEvaluations - totalEvaluations); + optimizer.setMaxIterations(maxIterations - totalIterations); optima[i] = optimizer.optimize(f, goalType, (i == 0) ? startPoint : generator.nextVector()); } catch (ObjectiveException obe) { @@ -156,6 +166,7 @@ public class MultiStartScalarOptimizer implements ScalarOptimizer { optima[i] = null; } + totalIterations += optimizer.getIterations(); totalEvaluations += optimizer.getEvaluations(); } diff --git a/src/java/org/apache/commons/math/optimization/MultiStartVectorialDifferentiableOptimizer.java b/src/java/org/apache/commons/math/optimization/MultiStartVectorialDifferentiableOptimizer.java index b92fb9c0e..31fe83cb7 100644 --- a/src/java/org/apache/commons/math/optimization/MultiStartVectorialDifferentiableOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/MultiStartVectorialDifferentiableOptimizer.java @@ -38,20 +38,23 @@ import org.apache.commons.math.random.RandomVectorGenerator; public class MultiStartVectorialDifferentiableOptimizer implements VectorialDifferentiableOptimizer { /** Serializable version identifier. */ - private static final long serialVersionUID = -6671992853686531955L; + private static final long serialVersionUID = -9109278856437190136L; /** Underlying classical optimizer. */ private final VectorialDifferentiableOptimizer optimizer; + /** Maximal number of iterations allowed. */ + private int maxIterations; + + /** Number of iterations already performed for all starts. */ + private int totalIterations; + /** Number of evaluations already performed for all starts. */ private int totalEvaluations; /** Number of jacobian evaluations already performed for all starts. */ private int totalJacobianEvaluations; - /** Maximal number of evaluations allowed. */ - private int maxEvaluations; - /** Number of starts to go. */ private int starts; @@ -73,9 +76,10 @@ public class MultiStartVectorialDifferentiableOptimizer implements VectorialDiff final int starts, final RandomVectorGenerator generator) { this.optimizer = optimizer; + this.maxIterations = Integer.MAX_VALUE; + this.totalIterations = 0; this.totalEvaluations = 0; this.totalJacobianEvaluations = 0; - this.maxEvaluations = Integer.MAX_VALUE; this.starts = starts; this.generator = generator; this.optima = null; @@ -114,6 +118,21 @@ public class MultiStartVectorialDifferentiableOptimizer implements VectorialDiff return (VectorialPointValuePair[]) optima.clone(); } + /** {@inheritDoc} */ + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; + } + + /** {@inheritDoc} */ + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return totalIterations; + } + /** {@inheritDoc} */ public int getEvaluations() { return totalEvaluations; @@ -124,16 +143,6 @@ public class MultiStartVectorialDifferentiableOptimizer implements VectorialDiff return totalJacobianEvaluations; } - /** {@inheritDoc} */ - public void setMaxEvaluations(int maxEvaluations) { - this.maxEvaluations = maxEvaluations; - } - - /** {@inheritDoc} */ - public int getMaxEvaluations() { - return maxEvaluations; - } - /** {@inheritDoc} */ public void setConvergenceChecker(VectorialConvergenceChecker checker) { optimizer.setConvergenceChecker(checker); @@ -150,15 +159,16 @@ public class MultiStartVectorialDifferentiableOptimizer implements VectorialDiff final double[] startPoint) throws ObjectiveException, OptimizationException, IllegalArgumentException { - optima = new VectorialPointValuePair[starts]; - totalEvaluations = 0; + optima = new VectorialPointValuePair[starts]; + totalIterations = 0; + totalEvaluations = 0; totalJacobianEvaluations = 0; // multi-start loop for (int i = 0; i < starts; ++i) { try { - optimizer.setMaxEvaluations(maxEvaluations - totalEvaluations); + optimizer.setMaxIterations(maxIterations - totalIterations); optima[i] = optimizer.optimize(f, target, weights, (i == 0) ? startPoint : generator.nextVector()); } catch (ObjectiveException obe) { @@ -167,6 +177,7 @@ public class MultiStartVectorialDifferentiableOptimizer implements VectorialDiff optima[i] = null; } + totalIterations += optimizer.getIterations(); totalEvaluations += optimizer.getEvaluations(); totalJacobianEvaluations += optimizer.getJacobianEvaluations(); diff --git a/src/java/org/apache/commons/math/optimization/OptimizationException.java b/src/java/org/apache/commons/math/optimization/OptimizationException.java index bf93cfec7..e44aa003d 100644 --- a/src/java/org/apache/commons/math/optimization/OptimizationException.java +++ b/src/java/org/apache/commons/math/optimization/OptimizationException.java @@ -30,7 +30,7 @@ import org.apache.commons.math.ConvergenceException; public class OptimizationException extends ConvergenceException { /** Serializable version identifier. */ - private static final long serialVersionUID = -781139167958631145L; + private static final long serialVersionUID = -357696069587075016L; /** * Simple constructor. @@ -42,4 +42,12 @@ public class OptimizationException extends ConvergenceException { super(specifier, parts); } + /** + * Create an exception with a given root cause. + * @param cause the exception or error that caused this exception to be thrown + */ + public OptimizationException(Throwable cause) { + super(cause); + } + } diff --git a/src/java/org/apache/commons/math/optimization/ScalarDifferentiableOptimizer.java b/src/java/org/apache/commons/math/optimization/ScalarDifferentiableOptimizer.java index b7cb6a36f..9385c30a1 100644 --- a/src/java/org/apache/commons/math/optimization/ScalarDifferentiableOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/ScalarDifferentiableOptimizer.java @@ -29,38 +29,45 @@ import java.io.Serializable; */ public interface ScalarDifferentiableOptimizer extends Serializable { - /** Set the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @param maxEvaluations maximal number of function calls - * . + /** Set the maximal number of iterations of the algorithm. + * @param maxIterations maximal number of function calls */ - void setMaxEvaluations(int maxEvaluations); + void setMaxIterations(int maxIterations); - /** Get the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @return maximal number of function calls + /** Get the maximal number of iterations of the algorithm. + * @return maximal number of iterations */ - int getMaxEvaluations(); + int getMaxIterations(); + + /** Get the number of iterations realized by the algorithm. + *

+ * The number of evaluations corresponds to the last call to the + * {@link #optimize(ScalarDifferentiableObjectiveFunction, GoalType, double[]) optimize} + * method. It is 0 if the method has not been called yet. + *

+ * @return number of iterations + */ + int getIterations(); /** Get the number of evaluations of the objective function. *

- * The number of evaluation correspond to the last call to the - * {@link #optimize(ScalarObjectiveFunction, GoalType, double[]) optimize} + * The number of evaluations corresponds to the last call to the + * {@link #optimize(ScalarDifferentiableObjectiveFunction, GoalType, double[]) optimize} * method. It is 0 if the method has not been called yet. *

* @return number of evaluations of the objective function */ - int getEvaluations(); + int getEvaluations(); + + /** Get the number of evaluations of the objective function gradient. + *

+ * The number of evaluations corresponds to the last call to the + * {@link #optimize(ScalarDifferentiableObjectiveFunction, GoalType, double[]) optimize} + * method. It is 0 if the method has not been called yet. + *

+ * @return number of evaluations of the objective function gradient + */ + int getGradientEvaluations(); /** Set the convergence checker. * @param checker object to use to check for convergence diff --git a/src/java/org/apache/commons/math/optimization/ScalarOptimizer.java b/src/java/org/apache/commons/math/optimization/ScalarOptimizer.java index 95f821164..63f1292e3 100644 --- a/src/java/org/apache/commons/math/optimization/ScalarOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/ScalarOptimizer.java @@ -29,38 +29,35 @@ import java.io.Serializable; */ public interface ScalarOptimizer extends Serializable { - /** Set the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @param maxEvaluations maximal number of function calls - * . + /** Set the maximal number of iterations of the algorithm. + * @param maxIterations maximal number of function calls */ - void setMaxEvaluations(int maxEvaluations); + void setMaxIterations(int maxIterations); - /** Get the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @return maximal number of function calls + /** Get the maximal number of iterations of the algorithm. + * @return maximal number of iterations */ - int getMaxEvaluations(); + int getMaxIterations(); + + /** Get the number of iterations realized by the algorithm. + *

+ * The number of evaluations corresponds to the last call to the + * {@link #optimize(ScalarObjectiveFunction, GoalType, double[]) optimize} + * method. It is 0 if the method has not been called yet. + *

+ * @return number of iterations + */ + int getIterations(); /** Get the number of evaluations of the objective function. *

- * The number of evaluation correspond to the last call to the + * The number of evaluations corresponds to the last call to the * {@link #optimize(ScalarObjectiveFunction, GoalType, double[]) optimize} * method. It is 0 if the method has not been called yet. *

* @return number of evaluations of the objective function */ - int getEvaluations(); + int getEvaluations(); /** Set the convergence checker. * @param checker object to use to check for convergence diff --git a/src/java/org/apache/commons/math/optimization/VectorialDifferentiableOptimizer.java b/src/java/org/apache/commons/math/optimization/VectorialDifferentiableOptimizer.java index 73d27584e..788e079c7 100644 --- a/src/java/org/apache/commons/math/optimization/VectorialDifferentiableOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/VectorialDifferentiableOptimizer.java @@ -29,28 +29,21 @@ import java.io.Serializable; */ public interface VectorialDifferentiableOptimizer extends Serializable { - /** Set the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @param maxEvaluations maximal number of function calls + /** Set the maximal number of iterations of the algorithm. + * @param maxIterations maximal number of function calls * . */ - void setMaxEvaluations(int maxEvaluations); + void setMaxIterations(int maxIterations); - /** Get the maximal number of objective function calls. - *

- * The number of objective function calls may be checked after a few - * related calls have been made. This implies that in some cases this number may - * be exceeded by a few units, depending on the dimension of the problem and kind - * of optimizer. - *

- * @return maximal number of function calls + /** Get the maximal number of iterations of the algorithm. + * @return maximal number of iterations */ - int getMaxEvaluations(); + int getMaxIterations(); + + /** Get the number of iterations realized by the algorithm. + * @return number of iterations + */ + int getIterations(); /** Get the number of evaluations of the objective function. *

diff --git a/src/java/org/apache/commons/math/optimization/direct/DirectSearchOptimizer.java b/src/java/org/apache/commons/math/optimization/direct/DirectSearchOptimizer.java index d69c856b3..c29c09e03 100644 --- a/src/java/org/apache/commons/math/optimization/direct/DirectSearchOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/direct/DirectSearchOptimizer.java @@ -21,6 +21,7 @@ import java.util.Arrays; import java.util.Comparator; import org.apache.commons.math.MathRuntimeException; +import org.apache.commons.math.MaxIterationsExceededException; import org.apache.commons.math.optimization.ScalarConvergenceChecker; import org.apache.commons.math.optimization.GoalType; import org.apache.commons.math.optimization.ObjectiveException; @@ -28,7 +29,7 @@ import org.apache.commons.math.optimization.ScalarObjectiveFunction; import org.apache.commons.math.optimization.OptimizationException; import org.apache.commons.math.optimization.ScalarOptimizer; import org.apache.commons.math.optimization.ScalarPointValuePair; -import org.apache.commons.math.optimization.SimpleValueChecker; +import org.apache.commons.math.optimization.SimpleScalarValueChecker; /** * This class implements simplex-based direct search optimization @@ -65,7 +66,7 @@ import org.apache.commons.math.optimization.SimpleValueChecker; * will occur.

* *

If {@link #setConvergenceChecker(ScalarConvergenceChecker)} is not called, - * a default {@link SimpleValueChecker} is used.

+ * a default {@link SimpleScalarValueChecker} is used.

* *

Convergence is checked by providing the worst points of * previous and current simplex to the convergence checker, not the best ones.

@@ -95,11 +96,14 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { /** Convergence checker. */ private ScalarConvergenceChecker checker; - /** Number of evaluations already performed for the current start. */ - private int evaluations; + /** Maximal number of iterations allowed. */ + private int maxIterations; - /** Maximal number of evaluations allowed. */ - private int maxEvaluations; + /** Number of iterations already performed. */ + private int iterations; + + /** Number of evaluations already performed. */ + private int evaluations; /** Start simplex configuration. */ private double[][] startConfiguration; @@ -107,8 +111,8 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { /** Simple constructor. */ protected DirectSearchOptimizer() { - setConvergenceChecker(new SimpleValueChecker()); - setMaxEvaluations(Integer.MAX_VALUE); + setConvergenceChecker(new SimpleScalarValueChecker()); + setMaxIterations(Integer.MAX_VALUE); } /** Set start configuration for simplex. @@ -208,13 +212,23 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { } /** {@inheritDoc} */ - public void setMaxEvaluations(int maxEvaluations) { - this.maxEvaluations = maxEvaluations; + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; } /** {@inheritDoc} */ - public int getMaxEvaluations() { - return maxEvaluations; + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return iterations; + } + + /** {@inheritDoc} */ + public int getEvaluations() { + return evaluations; } /** {@inheritDoc} */ @@ -229,7 +243,7 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { /** {@inheritDoc} */ public ScalarPointValuePair optimize(final ScalarObjectiveFunction f, final GoalType goalType, - final double[] startPoint) + final double[] startPoint) throws ObjectiveException, OptimizationException, IllegalArgumentException { if (startConfiguration == null) { @@ -251,15 +265,15 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { }; // initialize search + iterations = 0; evaluations = 0; buildSimplex(startPoint); evaluateSimplex(comparator); ScalarPointValuePair[] previous = new ScalarPointValuePair[simplex.length]; - int iterations = 0; - while (evaluations <= maxEvaluations) { + while (true) { - if (++iterations > 1) { + if (iterations > 0) { boolean converged = true; for (int i = 0; i < simplex.length; ++i) { converged &= checker.converged(iterations, previous[i], simplex[i]); @@ -276,22 +290,24 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer { } - throw new OptimizationException( - "maximal number of evaluations exceeded ({0})", - evaluations); - } - /** {@inheritDoc} */ - public int getEvaluations() { - return evaluations; + /** Increment the iterations counter by 1. + * @exception OptimizationException if the maximal number + * of iterations is exceeded + */ + protected void incrementIterationsCounter() + throws OptimizationException { + if (++iterations > maxIterations) { + throw new OptimizationException(new MaxIterationsExceededException(maxIterations)); + } } /** Compute the next simplex of the algorithm. * @param comparator comparator to use to sort simplex vertices from best to worst * @exception ObjectiveException if the function cannot be evaluated at * some point - * @exception OptimizationException if the algorithm failed to converge + * @exception OptimizationException if the algorithm fails to converge * @exception IllegalArgumentException if the start point dimension is wrong */ protected abstract void iterateSimplex(final Comparator comparator) diff --git a/src/java/org/apache/commons/math/optimization/direct/MultiDirectional.java b/src/java/org/apache/commons/math/optimization/direct/MultiDirectional.java index b9d2e8ec8..51c587078 100644 --- a/src/java/org/apache/commons/math/optimization/direct/MultiDirectional.java +++ b/src/java/org/apache/commons/math/optimization/direct/MultiDirectional.java @@ -62,8 +62,9 @@ public class MultiDirectional extends DirectSearchOptimizer { protected void iterateSimplex(final Comparator comparator) throws ObjectiveException, OptimizationException, IllegalArgumentException { - final int max = getMaxEvaluations(); - while (getEvaluations() < max) { + while (true) { + + incrementIterationsCounter(); // save the original vertex final ScalarPointValuePair[] original = simplex; @@ -94,10 +95,6 @@ public class MultiDirectional extends DirectSearchOptimizer { } - throw new OptimizationException( - "maximal number of evaluations exceeded ({0})", - getEvaluations()); - } /** Compute and evaluate a new simplex. diff --git a/src/java/org/apache/commons/math/optimization/direct/NelderMead.java b/src/java/org/apache/commons/math/optimization/direct/NelderMead.java index 27bad982c..96fe7bddf 100644 --- a/src/java/org/apache/commons/math/optimization/direct/NelderMead.java +++ b/src/java/org/apache/commons/math/optimization/direct/NelderMead.java @@ -20,6 +20,7 @@ package org.apache.commons.math.optimization.direct; import java.util.Comparator; import org.apache.commons.math.optimization.ObjectiveException; +import org.apache.commons.math.optimization.OptimizationException; import org.apache.commons.math.optimization.ScalarPointValuePair; /** @@ -73,7 +74,9 @@ public class NelderMead extends DirectSearchOptimizer { /** {@inheritDoc} */ protected void iterateSimplex(final Comparator comparator) - throws ObjectiveException { + throws ObjectiveException, OptimizationException { + + incrementIterationsCounter(); // the simplex has n+1 point if dimension is n final int n = simplex.length - 1; diff --git a/src/java/org/apache/commons/math/optimization/general/AbstractLeastSquaresOptimizer.java b/src/java/org/apache/commons/math/optimization/general/AbstractLeastSquaresOptimizer.java index 642b76fa4..8f096ac68 100644 --- a/src/java/org/apache/commons/math/optimization/general/AbstractLeastSquaresOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/general/AbstractLeastSquaresOptimizer.java @@ -17,6 +17,7 @@ package org.apache.commons.math.optimization.general; +import org.apache.commons.math.MaxIterationsExceededException; import org.apache.commons.math.linear.InvalidMatrixException; import org.apache.commons.math.linear.MatrixUtils; import org.apache.commons.math.linear.RealMatrix; @@ -40,20 +41,23 @@ import org.apache.commons.math.optimization.VectorialPointValuePair; public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferentiableOptimizer { /** Serializable version identifier */ - private static final long serialVersionUID = -3080152374642370722L; + private static final long serialVersionUID = 5413193243329026789L; - /** Default maximal number of objective function evaluations allowed. */ - public static final int DEFAULT_MAX_EVALUATIONS = 100; + /** Default maximal number of iterations allowed. */ + public static final int DEFAULT_MAX_ITERATIONS = 100; - /** Number of evaluations already performed for the current start. */ + /** Maximal number of iterations allowed. */ + private int maxIterations; + + /** Number of iterations already performed. */ + private int iterations; + + /** Number of evaluations already performed. */ private int objectiveEvaluations; /** Number of jacobian evaluations. */ private int jacobianEvaluations; - /** Maximal number of evaluations allowed. */ - private int maxEvaluations; - /** Convergence checker. */ protected VectorialConvergenceChecker checker; @@ -99,17 +103,22 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen */ protected AbstractLeastSquaresOptimizer() { setConvergenceChecker(new SimpleVectorialValueChecker()); - setMaxEvaluations(DEFAULT_MAX_EVALUATIONS); + setMaxIterations(DEFAULT_MAX_ITERATIONS); } /** {@inheritDoc} */ - public void setMaxEvaluations(int maxEvaluations) { - this.maxEvaluations = maxEvaluations; + public void setMaxIterations(int maxIterations) { + this.maxIterations = maxIterations; } /** {@inheritDoc} */ - public int getMaxEvaluations() { - return maxEvaluations; + public int getMaxIterations() { + return maxIterations; + } + + /** {@inheritDoc} */ + public int getIterations() { + return iterations; } /** {@inheritDoc} */ @@ -132,13 +141,26 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen return checker; } + /** Increment the iterations counter by 1. + * @exception OptimizationException if the maximal number + * of iterations is exceeded + */ + protected void incrementIterationsCounter() + throws OptimizationException { + if (++iterations > maxIterations) { + if (++iterations > maxIterations) { + throw new OptimizationException(new MaxIterationsExceededException(maxIterations)); + } + } + } + /** * Update the jacobian matrix. * @exception ObjectiveException if the function jacobian * cannot be evaluated or its dimension doesn't match problem dimension */ protected void updateJacobian() throws ObjectiveException { - incrementJacobianEvaluationsCounter(); + ++jacobianEvaluations; jacobian = f.jacobian(variables, objective); if (jacobian.length != rows) { throw new ObjectiveException("dimension mismatch {0} != {1}", @@ -153,28 +175,13 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen } } - /** - * Increment the jacobian evaluations counter. - */ - protected final void incrementJacobianEvaluationsCounter() { - ++jacobianEvaluations; - } - /** * Update the residuals array and cost function value. * @exception ObjectiveException if the function cannot be evaluated * or its dimension doesn't match problem dimension - * @exception OptimizationException if the number of cost evaluations - * exceeds the maximum allowed */ protected void updateResidualsAndCost() - throws ObjectiveException, OptimizationException { - - if (++objectiveEvaluations > maxEvaluations) { - throw new OptimizationException( - "maximal number of evaluations exceeded ({0})", - objectiveEvaluations); - } + throws ObjectiveException { objective = f.objective(variables); if (objective.length != rows) { @@ -298,6 +305,7 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen } // reset counters + iterations = 0; objectiveEvaluations = 0; jacobianEvaluations = 0; @@ -327,6 +335,6 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen * @exception IllegalArgumentException if the start point dimension is wrong */ abstract protected VectorialPointValuePair doOptimize() - throws ObjectiveException, OptimizationException, IllegalArgumentException; + throws ObjectiveException, OptimizationException, IllegalArgumentException; } \ No newline at end of file diff --git a/src/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java b/src/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java index a551b72ae..2d6e3929a 100644 --- a/src/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java @@ -53,7 +53,7 @@ public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer { /** Simple constructor with default settings. *

The convergence check is set to a {@link SimpleVectorialValueChecker} * and the maximal number of evaluation is set to - * {@link AbstractLeastSquaresOptimizer#DEFAULT_MAX_EVALUATIONS}. + * {@link AbstractLeastSquaresOptimizer#DEFAULT_MAX_ITERATIONS}. * @param useLU if true, the normal equations will be solved using LU * decomposition, otherwise they will be solved using QR decomposition */ @@ -67,8 +67,9 @@ public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer { // iterate until convergence is reached VectorialPointValuePair current = null; - boolean converged = false; - for (int iteration = 1; ! converged; ++iteration) { + for (boolean converged = false; !converged;) { + + incrementIterationsCounter(); // evaluate the objective function and its jacobian VectorialPointValuePair previous = current; @@ -122,7 +123,7 @@ public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer { // check convergence if (previous != null) { - converged = checker.converged(++iteration, previous, current); + converged = checker.converged(getIterations(), previous, current); } } diff --git a/src/java/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizer.java b/src/java/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizer.java index 232901aaf..d36a5be0b 100644 --- a/src/java/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizer.java +++ b/src/java/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizer.java @@ -146,7 +146,7 @@ public class LevenbergMarquardtOptimizer extends AbstractLeastSquaresOptimizer { *

The default values for the algorithm settings are: *

    *
  • {@link #setInitialStepBoundFactor initial step bound factor}: 100.0
    • - *
  • {@link #setMaxCostEval maximal cost evaluations}: 1000
    • + *
  • {@link #setMaxIterations maximal iterations}: 1000
    • *
  • {@link #setCostRelativeTolerance cost relative tolerance}: 1.0e-10
    • *
  • {@link #setParRelativeTolerance parameters relative tolerance}: 1.0e-10
    • *
  • {@link #setOrthoTolerance orthogonality tolerance}: 1.0e-10
    • @@ -156,7 +156,7 @@ public class LevenbergMarquardtOptimizer extends AbstractLeastSquaresOptimizer { public LevenbergMarquardtOptimizer() { // set up the superclass with a default max cost evaluations setting - setMaxEvaluations(1000); + setMaxIterations(1000); // default values for the tuning parameters setInitialStepBoundFactor(100.0); @@ -237,6 +237,8 @@ public class LevenbergMarquardtOptimizer extends AbstractLeastSquaresOptimizer { boolean firstIteration = true; while (true) { + incrementIterationsCounter(); + // compute the Q.R. decomposition of the jacobian matrix updateJacobian(); qrDecomposition(); diff --git a/src/test/org/apache/commons/math/optimization/direct/MultiDirectionalTest.java b/src/test/org/apache/commons/math/optimization/direct/MultiDirectionalTest.java index 40b0f77ba..aea5aae21 100644 --- a/src/test/org/apache/commons/math/optimization/direct/MultiDirectionalTest.java +++ b/src/test/org/apache/commons/math/optimization/direct/MultiDirectionalTest.java @@ -27,7 +27,7 @@ import org.apache.commons.math.optimization.GoalType; import org.apache.commons.math.optimization.ObjectiveException; import org.apache.commons.math.optimization.ScalarObjectiveFunction; import org.apache.commons.math.optimization.ScalarPointValuePair; -import org.apache.commons.math.optimization.SimpleValueChecker; +import org.apache.commons.math.optimization.SimpleScalarValueChecker; public class MultiDirectionalTest extends TestCase { @@ -94,8 +94,8 @@ public class MultiDirectionalTest }; MultiDirectional optimizer = new MultiDirectional(); - optimizer.setConvergenceChecker(new SimpleValueChecker(1.0e-10, 1.0e-30)); - optimizer.setMaxEvaluations(200); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-10, 1.0e-30)); + optimizer.setMaxIterations(200); optimizer.setStartConfiguration(new double[] { 0.2, 0.2 }); ScalarPointValuePair optimum; @@ -147,8 +147,8 @@ public class MultiDirectionalTest count = 0; MultiDirectional optimizer = new MultiDirectional(); - optimizer.setConvergenceChecker(new SimpleValueChecker(-1, 1.0e-3)); - optimizer.setMaxEvaluations(100); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3)); + optimizer.setMaxIterations(100); optimizer.setStartConfiguration(new double[][] { { -1.2, 1.0 }, { 0.9, 1.2 } , { 3.5, -2.3 } }); @@ -180,8 +180,8 @@ public class MultiDirectionalTest count = 0; MultiDirectional optimizer = new MultiDirectional(); - optimizer.setConvergenceChecker(new SimpleValueChecker(-1.0, 1.0e-3)); - optimizer.setMaxEvaluations(1000); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-3)); + optimizer.setMaxIterations(1000); ScalarPointValuePair optimum = optimizer.optimize(powell, GoalType.MINIMIZE, new double[] { 3.0, -1.0, 0.0, 1.0 }); assertEquals(count, optimizer.getEvaluations()); diff --git a/src/test/org/apache/commons/math/optimization/direct/NelderMeadTest.java b/src/test/org/apache/commons/math/optimization/direct/NelderMeadTest.java index 580619cdf..80b22279a 100644 --- a/src/test/org/apache/commons/math/optimization/direct/NelderMeadTest.java +++ b/src/test/org/apache/commons/math/optimization/direct/NelderMeadTest.java @@ -27,7 +27,7 @@ import org.apache.commons.math.optimization.GoalType; import org.apache.commons.math.optimization.ObjectiveException; import org.apache.commons.math.optimization.ScalarObjectiveFunction; import org.apache.commons.math.optimization.ScalarPointValuePair; -import org.apache.commons.math.optimization.SimpleValueChecker; +import org.apache.commons.math.optimization.SimpleScalarValueChecker; public class NelderMeadTest extends TestCase { @@ -94,8 +94,8 @@ public class NelderMeadTest }; NelderMead optimizer = new NelderMead(); - optimizer.setConvergenceChecker(new SimpleValueChecker(1.0e-10, 1.0e-30)); - optimizer.setMaxEvaluations(100); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-10, 1.0e-30)); + optimizer.setMaxIterations(100); optimizer.setStartConfiguration(new double[] { 0.2, 0.2 }); ScalarPointValuePair optimum; @@ -147,8 +147,8 @@ public class NelderMeadTest count = 0; NelderMead optimizer = new NelderMead(); - optimizer.setConvergenceChecker(new SimpleValueChecker(-1, 1.0e-3)); - optimizer.setMaxEvaluations(100); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3)); + optimizer.setMaxIterations(100); optimizer.setStartConfiguration(new double[][] { { -1.2, 1.0 }, { 0.9, 1.2 } , { 3.5, -2.3 } }); @@ -180,8 +180,8 @@ public class NelderMeadTest count = 0; NelderMead optimizer = new NelderMead(); - optimizer.setConvergenceChecker(new SimpleValueChecker(-1.0, 1.0e-3)); - optimizer.setMaxEvaluations(200); + optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-3)); + optimizer.setMaxIterations(200); ScalarPointValuePair optimum = optimizer.optimize(powell, GoalType.MINIMIZE, new double[] { 3.0, -1.0, 0.0, 1.0 }); assertEquals(count, optimizer.getEvaluations()); diff --git a/src/test/org/apache/commons/math/optimization/general/GaussNewtonOptimizerTest.java b/src/test/org/apache/commons/math/optimization/general/GaussNewtonOptimizerTest.java index 622155c61..ceb49405e 100644 --- a/src/test/org/apache/commons/math/optimization/general/GaussNewtonOptimizerTest.java +++ b/src/test/org/apache/commons/math/optimization/general/GaussNewtonOptimizerTest.java @@ -106,7 +106,7 @@ extends TestCase { LinearProblem problem = new LinearProblem(new double[][] { { 2 } }, new double[] { 3 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1 }, new double[] { 0 }); @@ -122,7 +122,7 @@ extends TestCase { new double[] { 4.0, 6.0, 1.0 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0 }); @@ -145,7 +145,7 @@ extends TestCase { { 0, 0, 0, 0, 0, 2 } }, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1, 1, 1, 1 }, @@ -164,7 +164,7 @@ extends TestCase { { 0, -1, 1 } }, new double[] { 1, 1, 1}); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0, 0 }); @@ -187,7 +187,7 @@ extends TestCase { }, new double[] { 2, -9, 2, 2, 1 + epsilon * epsilon, 2}); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1, 1, 1, 1 }, @@ -210,7 +210,7 @@ extends TestCase { { -3, 0, -9 } }, new double[] { 1, 1, 1 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); try { optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0, 0 }); @@ -230,7 +230,7 @@ extends TestCase { { 7.0, 5.0, 9.0, 10.0 } }, new double[] { 32, 23, 33, 31 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum1 = optimizer.optimize(problem1, problem1.target, new double[] { 1, 1, 1, 1 }, @@ -267,7 +267,7 @@ extends TestCase { }, new double[] { 7.0, 3.0, 5.0 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); try { optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, @@ -290,7 +290,7 @@ extends TestCase { { 0.0, 0.0, 0.0, -1.0, 1.0, 0.0 } }, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); try { optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1, 1, 1 }, @@ -311,7 +311,7 @@ extends TestCase { }, new double[] { 3.0, 1.0, 5.0 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, @@ -330,7 +330,7 @@ extends TestCase { }, new double[] { 3.0, 1.0, 4.0 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); optimizer.optimize(problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 1, 1 }); assertTrue(optimizer.getRMS() > 0.1); @@ -341,7 +341,7 @@ extends TestCase { LinearProblem problem = new LinearProblem(new double[][] { { 1, 0 }, { 0, 1 } }, new double[] { -1, 1 }); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); VectorialPointValuePair optimum = @@ -382,7 +382,7 @@ extends TestCase { circle.addPoint( 35.0, 15.0); circle.addPoint( 45.0, 97.0); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-15, 1.0e-15)); try { optimizer.optimize(circle, new double[] { 0, 0, 0, 0, 0 }, @@ -404,7 +404,7 @@ extends TestCase { circle.addPoint( 35.0, 15.0); circle.addPoint( 45.0, 97.0); GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-13, 1.0e-13)); VectorialPointValuePair optimum = optimizer.optimize(circle, new double[] { 0, 0, 0, 0, 0 }, @@ -458,7 +458,7 @@ extends TestCase { circle.addPoint(points[i][0], points[i][1]); } GaussNewtonOptimizer optimizer = new GaussNewtonOptimizer(true); - optimizer.setMaxEvaluations(100); + optimizer.setMaxIterations(100); optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6)); try { optimizer.optimize(circle, target, weights, new double[] { -12, -12 }); diff --git a/src/test/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizerTest.java b/src/test/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizerTest.java index 0b7a296a3..4d6f99e9a 100644 --- a/src/test/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizerTest.java +++ b/src/test/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizerTest.java @@ -379,7 +379,7 @@ public class LevenbergMarquardtOptimizerTest try { LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer(); optimizer.setInitialStepBoundFactor(initialStepBoundFactor); - optimizer.setMaxEvaluations(maxCostEval); + optimizer.setMaxIterations(maxCostEval); optimizer.setCostRelativeTolerance(costRelativeTolerance); optimizer.setParRelativeTolerance(parRelativeTolerance); optimizer.setOrthoTolerance(orthoTolerance); diff --git a/src/test/org/apache/commons/math/optimization/general/MinpackTest.java b/src/test/org/apache/commons/math/optimization/general/MinpackTest.java index c3f451e05..3a648fad1 100644 --- a/src/test/org/apache/commons/math/optimization/general/MinpackTest.java +++ b/src/test/org/apache/commons/math/optimization/general/MinpackTest.java @@ -219,7 +219,7 @@ public class MinpackTest extends TestCase { 0.188053165007911, 0.122430604321144, 0.134575665392506 - }), true); + }), false); } public void testMinpackMeyer() @@ -505,7 +505,7 @@ public class MinpackTest extends TestCase { private void minpackTest(MinpackFunction function, boolean exceptionExpected) { LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer(); - optimizer.setMaxEvaluations(100 * (function.getN() + 1)); + optimizer.setMaxIterations(100 * (function.getN() + 1)); optimizer.setCostRelativeTolerance(Math.sqrt(2.22044604926e-16)); optimizer.setParRelativeTolerance(Math.sqrt(2.22044604926e-16)); optimizer.setOrthoTolerance(2.22044604926e-16);