Class name change:
  "MultivariateRealOptimizer" -> "MultivariateOptimizer"
  "DifferentiableMultivariateRealOptimizer" -> "DifferentiableMultivariateOptimizer"


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1212377 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski 2011-12-09 12:42:50 +00:00
parent 5fef93ec7d
commit e71093b8df
17 changed files with 37 additions and 37 deletions

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@ -24,8 +24,8 @@ import org.apache.commons.math.analysis.MultivariateFunction;
* Commons-FastMath. Users of the API are advised to base their code on
* the following interfaces:
* <ul>
* <li>{@link org.apache.commons.math.optimization.MultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.MultivariateOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateOptimizer}</li>
* </ul>
*
* @param <FUNC> Type of the objective function to be optimized.

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@ -24,8 +24,8 @@ import org.apache.commons.math.analysis.MultivariateFunction;
* Commons-FastMath. Users of the API are advised to base their code on
* the following interfaces:
* <ul>
* <li>{@link org.apache.commons.math.optimization.MultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.MultivariateOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateOptimizer}</li>
* </ul>
*
* @param <FUNC> Type of the objective function to be optimized.

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@ -22,8 +22,8 @@ package org.apache.commons.math.optimization;
* Commons-Math. Users of the API are advised to base their code on
* the following interfaces:
* <ul>
* <li>{@link org.apache.commons.math.optimization.MultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.MultivariateOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateVectorOptimizer}</li>
* <li>{@link org.apache.commons.math.optimization.univariate.UnivariateRealOptimizer}</li>
* </ul>

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@ -21,7 +21,7 @@ import org.apache.commons.math.analysis.DifferentiableMultivariateFunction;
import org.apache.commons.math.random.RandomVectorGenerator;
/**
* Special implementation of the {@link DifferentiableMultivariateRealOptimizer}
* Special implementation of the {@link DifferentiableMultivariateOptimizer}
* interface adding multi-start features to an existing optimizer.
*
* This class wraps a classical optimizer to use it several times in
@ -33,7 +33,7 @@ import org.apache.commons.math.random.RandomVectorGenerator;
*/
public class DifferentiableMultivariateMultiStartOptimizer
extends BaseMultivariateMultiStartOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateRealOptimizer {
implements DifferentiableMultivariateOptimizer {
/**
* Create a multi-start optimizer from a single-start optimizer.
*
@ -43,7 +43,7 @@ public class DifferentiableMultivariateMultiStartOptimizer
* equal to 1.
* @param generator Random vector generator to use for restarts.
*/
public DifferentiableMultivariateMultiStartOptimizer(final DifferentiableMultivariateRealOptimizer optimizer,
public DifferentiableMultivariateMultiStartOptimizer(final DifferentiableMultivariateOptimizer optimizer,
final int starts,
final RandomVectorGenerator generator) {
super(optimizer, starts, generator);

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@ -26,11 +26,11 @@ import org.apache.commons.math.analysis.DifferentiableMultivariateFunction;
* Optimization algorithms find the input point set that either {@link GoalType
* maximize or minimize} an objective function.
*
* @see MultivariateRealOptimizer
* @see MultivariateOptimizer
* @see DifferentiableMultivariateVectorOptimizer
*
* @version $Id$
* @since 2.0
*/
public interface DifferentiableMultivariateRealOptimizer
public interface DifferentiableMultivariateOptimizer
extends BaseMultivariateOptimizer<DifferentiableMultivariateFunction> {}

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@ -21,7 +21,7 @@ import org.apache.commons.math.analysis.MultivariateFunction;
import org.apache.commons.math.random.RandomVectorGenerator;
/**
* Special implementation of the {@link MultivariateRealOptimizer} interface adding
* Special implementation of the {@link MultivariateOptimizer} interface adding
* multi-start features to an existing optimizer.
*
* This class wraps a classical optimizer to use it several times in
@ -33,7 +33,7 @@ import org.apache.commons.math.random.RandomVectorGenerator;
*/
public class MultivariateMultiStartOptimizer
extends BaseMultivariateMultiStartOptimizer<MultivariateFunction>
implements MultivariateRealOptimizer {
implements MultivariateOptimizer {
/**
* Create a multi-start optimizer from a single-start optimizer.
*
@ -43,7 +43,7 @@ public class MultivariateMultiStartOptimizer
* equal to 1.
* @param generator Random vector generator to use for restarts.
*/
public MultivariateMultiStartOptimizer(final MultivariateRealOptimizer optimizer,
public MultivariateMultiStartOptimizer(final MultivariateOptimizer optimizer,
final int starts,
final RandomVectorGenerator generator) {
super(optimizer, starts, generator);

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@ -25,10 +25,10 @@ import org.apache.commons.math.analysis.MultivariateFunction;
* <p>Optimization algorithms find the input point set that either {@link GoalType
* maximize or minimize} an objective function.</p>
*
* @see DifferentiableMultivariateRealOptimizer
* @see DifferentiableMultivariateOptimizer
* @see DifferentiableMultivariateVectorOptimizer
* @version $Id$
* @since 2.0
*/
public interface MultivariateRealOptimizer
public interface MultivariateOptimizer
extends BaseMultivariateOptimizer<MultivariateFunction> {}

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@ -29,7 +29,7 @@ import org.apache.commons.math.linear.ArrayRealVector;
import org.apache.commons.math.linear.RealVector;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
/**
* Powell's BOBYQA algorithm. This implementation is translated and
@ -51,7 +51,7 @@ import org.apache.commons.math.optimization.MultivariateRealOptimizer;
*/
public class BOBYQAOptimizer
extends BaseAbstractMultivariateSimpleBoundsOptimizer<MultivariateFunction>
implements MultivariateRealOptimizer {
implements MultivariateOptimizer {
/** Minimum dimension of the problem: {@value} */
public static final int MINIMUM_PROBLEM_DIMENSION = 2;
/** Default value for {@link #initialTrustRegionRadius}: {@value} . */

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@ -33,7 +33,7 @@ import org.apache.commons.math.linear.MatrixUtils;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.optimization.ConvergenceChecker;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.optimization.SimpleScalarValueChecker;
import org.apache.commons.math.random.MersenneTwister;
@ -82,7 +82,7 @@ import org.apache.commons.math.util.MathArrays;
public class CMAESOptimizer
extends BaseAbstractMultivariateOptimizer<MultivariateFunction>
implements MultivariateRealOptimizer {
implements MultivariateOptimizer {
/** Default value for {@link #checkFeasableCount}: {@value}. */
public static final int DEFAULT_CHECKFEASABLECOUNT = 0;
/** Default value for {@link #stopFitness}: {@value}. */

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@ -26,7 +26,7 @@ import org.apache.commons.math.exception.NotStrictlyPositiveException;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.optimization.ConvergenceChecker;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
import org.apache.commons.math.optimization.univariate.BracketFinder;
import org.apache.commons.math.optimization.univariate.BrentOptimizer;
import org.apache.commons.math.optimization.univariate.UnivariateRealPointValuePair;
@ -47,7 +47,7 @@ import org.apache.commons.math.optimization.univariate.UnivariateRealPointValueP
*/
public class PowellOptimizer
extends BaseAbstractMultivariateOptimizer<MultivariateFunction>
implements MultivariateRealOptimizer {
implements MultivariateOptimizer {
/**
* Minimum relative tolerance.
*/

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@ -25,7 +25,7 @@ import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.ConvergenceChecker;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.optimization.SimpleScalarValueChecker;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
/**
* This class implements simplex-based direct search optimization.
@ -85,7 +85,7 @@ import org.apache.commons.math.optimization.MultivariateRealOptimizer;
*/
public class SimplexOptimizer
extends BaseAbstractMultivariateOptimizer<MultivariateFunction>
implements MultivariateRealOptimizer {
implements MultivariateOptimizer {
/** Simplex. */
private AbstractSimplex simplex;

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@ -19,7 +19,7 @@ package org.apache.commons.math.optimization.general;
import org.apache.commons.math.analysis.DifferentiableMultivariateFunction;
import org.apache.commons.math.analysis.MultivariateVectorFunction;
import org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer;
import org.apache.commons.math.optimization.DifferentiableMultivariateOptimizer;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.ConvergenceChecker;
import org.apache.commons.math.optimization.RealPointValuePair;
@ -35,7 +35,7 @@ import org.apache.commons.math.optimization.direct.BaseAbstractMultivariateOptim
*/
public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateRealOptimizer {
implements DifferentiableMultivariateOptimizer {
/**
* Objective function gradient.
*/

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@ -35,11 +35,11 @@
* <li>{@link org.apache.commons.math.optimization.univariate.UnivariateRealOptimizer
* UnivariateRealOptimizer} for {@link org.apache.commons.math.analysis.UnivariateFunction
* univariate real functions}</li>
* <li>{@link org.apache.commons.math.optimization.MultivariateRealOptimizer
* MultivariateRealOptimizer} for {@link org.apache.commons.math.analysis.MultivariateFunction
* <li>{@link org.apache.commons.math.optimization.MultivariateOptimizer
* MultivariateOptimizer} for {@link org.apache.commons.math.analysis.MultivariateFunction
* multivariate real functions}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
* DifferentiableMultivariateRealOptimizer} for {@link
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateOptimizer
* DifferentiableMultivariateOptimizer} for {@link
* org.apache.commons.math.analysis.DifferentiableMultivariateFunction
* differentiable multivariate real functions}</li>
* <li>{@link org.apache.commons.math.optimization.DifferentiableMultivariateVectorOptimizer
@ -57,7 +57,7 @@
* real function} thanks to the {@link
* org.apache.commons.math.optimization.LeastSquaresConverter LeastSquaresConverter} helper class.
* The transformed function can be optimized using any implementation of the {@link
* org.apache.commons.math.optimization.MultivariateRealOptimizer MultivariateRealOptimizer} interface.
* org.apache.commons.math.optimization.MultivariateOptimizer MultivariateOptimizer} interface.
* </p>
*
* <p>

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@ -792,7 +792,7 @@ public class BatteryNISTTest {
}
/* generic test runner */
private double[] run(MultivariateRealOptimizer optim, DifferentiableMultivariateFunction func, double[] start) {
private double[] run(MultivariateOptimizer optim, DifferentiableMultivariateFunction func, double[] start) {
return (optim.optimize(1000000, func, GoalType.MINIMIZE, start).getPointRef());
}
/* generic test runner for AbstractScalarDifferentiableOptimizer */

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@ -253,7 +253,7 @@ public class BOBYQAOptimizerTest {
System.out.println(func.getClass().getName() + " BEGIN"); // XXX
int dim = startPoint.length;
// MultivariateRealOptimizer optim =
// MultivariateOptimizer optim =
// new PowellOptimizer(1e-13, Math.ulp(1d));
// RealPointValuePair result = optim.optimize(100000, func, goal, startPoint);
final double[] lB = boundaries == null ? null : boundaries[0];

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@ -27,7 +27,7 @@ import org.apache.commons.math.exception.NoDataException;
import org.apache.commons.math.exception.NotPositiveException;
import org.apache.commons.math.exception.OutOfRangeException;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.apache.commons.math.random.MersenneTwister;
import org.junit.Assert;
@ -375,7 +375,7 @@ public class CMAESOptimizerTest {
RealPointValuePair expected) {
int dim = startPoint.length;
// test diagonalOnly = 0 - slow but normally fewer feval#
MultivariateRealOptimizer optim =
MultivariateOptimizer optim =
new CMAESOptimizer(
lambda, inSigma, boundaries, 30000,
stopValue, isActive, diagonalOnly, 0, new MersenneTwister(),false);

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@ -19,7 +19,7 @@ package org.apache.commons.math.optimization.direct;
import org.apache.commons.math.analysis.MultivariateFunction;
import org.apache.commons.math.analysis.SumSincFunction;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.MultivariateRealOptimizer;
import org.apache.commons.math.optimization.MultivariateOptimizer;
import org.apache.commons.math.optimization.RealPointValuePair;
import org.junit.Assert;
import org.junit.Test;
@ -131,7 +131,7 @@ public class PowellOptimizerTest {
GoalType goal,
double fTol,
double pointTol) {
final MultivariateRealOptimizer optim = new PowellOptimizer(fTol, Math.ulp(1d));
final MultivariateOptimizer optim = new PowellOptimizer(fTol, Math.ulp(1d));
final RealPointValuePair result = optim.optimize(1000, func, goal, init);
final double[] found = result.getPoint();