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From t.@apache.org
Subject [14/18] [math] Remove deprecated optimization package.
Date Wed, 25 Feb 2015 21:49:42 GMT
http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java
b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java
deleted file mode 100644
index 8af7c47..0000000
--- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java
+++ /dev/null
@@ -1,318 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.commons.math4.optimization.direct;
-
-import org.apache.commons.math4.analysis.MultivariateFunction;
-import org.apache.commons.math4.exception.DimensionMismatchException;
-import org.apache.commons.math4.exception.MaxCountExceededException;
-import org.apache.commons.math4.exception.NumberIsTooLargeException;
-import org.apache.commons.math4.exception.NumberIsTooSmallException;
-import org.apache.commons.math4.exception.TooManyEvaluationsException;
-import org.apache.commons.math4.optimization.BaseMultivariateOptimizer;
-import org.apache.commons.math4.optimization.ConvergenceChecker;
-import org.apache.commons.math4.optimization.GoalType;
-import org.apache.commons.math4.optimization.InitialGuess;
-import org.apache.commons.math4.optimization.OptimizationData;
-import org.apache.commons.math4.optimization.PointValuePair;
-import org.apache.commons.math4.optimization.SimpleBounds;
-import org.apache.commons.math4.optimization.SimpleValueChecker;
-import org.apache.commons.math4.util.Incrementor;
-
-/**
- * Base class for implementing optimizers for multivariate scalar functions.
- * This base class handles the boiler-plate methods associated to thresholds,
- * evaluations counting, initial guess and simple bounds settings.
- *
- * @param <FUNC> Type of the objective function to be optimized.
- *
- * @deprecated As of 3.1 (to be removed in 4.0).
- * @since 2.2
- */
-@Deprecated
-public abstract class BaseAbstractMultivariateOptimizer<FUNC extends MultivariateFunction>
-    implements BaseMultivariateOptimizer<FUNC> {
-    /** Evaluations counter. */
-    protected final Incrementor evaluations = new Incrementor();
-    /** Convergence checker. */
-    private ConvergenceChecker<PointValuePair> checker;
-    /** Type of optimization. */
-    private GoalType goal;
-    /** Initial guess. */
-    private double[] start;
-    /** Lower bounds. */
-    private double[] lowerBound;
-    /** Upper bounds. */
-    private double[] upperBound;
-    /** Objective function. */
-    private MultivariateFunction function;
-
-    /**
-     * Simple constructor with default settings.
-     * The convergence check is set to a {@link SimpleValueChecker}.
-     * @deprecated See {@link SimpleValueChecker#SimpleValueChecker()}
-     */
-    @Deprecated
-    protected BaseAbstractMultivariateOptimizer() {
-        this(new SimpleValueChecker());
-    }
-    /**
-     * @param checker Convergence checker.
-     */
-    protected BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair>
checker) {
-        this.checker = checker;
-    }
-
-    /** {@inheritDoc} */
-    public int getMaxEvaluations() {
-        return evaluations.getMaximalCount();
-    }
-
-    /** {@inheritDoc} */
-    public int getEvaluations() {
-        return evaluations.getCount();
-    }
-
-    /** {@inheritDoc} */
-    public ConvergenceChecker<PointValuePair> getConvergenceChecker() {
-        return checker;
-    }
-
-    /**
-     * Compute the objective function value.
-     *
-     * @param point Point at which the objective function must be evaluated.
-     * @return the objective function value at the specified point.
-     * @throws TooManyEvaluationsException if the maximal number of
-     * evaluations is exceeded.
-     */
-    protected double computeObjectiveValue(double[] point) {
-        try {
-            evaluations.incrementCount();
-        } catch (MaxCountExceededException e) {
-            throw new TooManyEvaluationsException(e.getMax());
-        }
-        return function.value(point);
-    }
-
-    /**
-     * {@inheritDoc}
-     *
-     * @deprecated As of 3.1. Please use
-     * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
-     * instead.
-     */
-    @Deprecated
-    public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType,
-                                   double[] startPoint) {
-        return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
-    }
-
-    /**
-     * Optimize an objective function.
-     *
-     * @param maxEval Allowed number of evaluations of the objective function.
-     * @param f Objective function.
-     * @param goalType Optimization type.
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link InitialGuess}</li>
-     *  <li>{@link SimpleBounds}</li>
-     * </ul>
-     * @return the point/value pair giving the optimal value of the objective
-     * function.
-     * @since 3.1
-     */
-    public PointValuePair optimize(int maxEval,
-                                   FUNC f,
-                                   GoalType goalType,
-                                   OptimizationData... optData) {
-        return optimizeInternal(maxEval, f, goalType, optData);
-    }
-
-    /**
-     * Optimize an objective function.
-     *
-     * @param f Objective function.
-     * @param goalType Type of optimization goal: either
-     * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
-     * @param startPoint Start point for optimization.
-     * @param maxEval Maximum number of function evaluations.
-     * @return the point/value pair giving the optimal value for objective
-     * function.
-     * @throws org.apache.commons.math4.exception.DimensionMismatchException
-     * if the start point dimension is wrong.
-     * @throws org.apache.commons.math4.exception.TooManyEvaluationsException
-     * if the maximal number of evaluations is exceeded.
-     * @throws org.apache.commons.math4.exception.NullArgumentException if
-     * any argument is {@code null}.
-     * @deprecated As of 3.1. Please use
-     * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
-     * instead.
-     */
-    @Deprecated
-    protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType,
-                                              double[] startPoint) {
-        return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
-    }
-
-    /**
-     * Optimize an objective function.
-     *
-     * @param maxEval Allowed number of evaluations of the objective function.
-     * @param f Objective function.
-     * @param goalType Optimization type.
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link InitialGuess}</li>
-     *  <li>{@link SimpleBounds}</li>
-     * </ul>
-     * @return the point/value pair giving the optimal value of the objective
-     * function.
-     * @throws TooManyEvaluationsException if the maximal number of
-     * evaluations is exceeded.
-     * @since 3.1
-     */
-    protected PointValuePair optimizeInternal(int maxEval,
-                                              FUNC f,
-                                              GoalType goalType,
-                                              OptimizationData... optData)
-        throws TooManyEvaluationsException {
-        // Set internal state.
-        evaluations.setMaximalCount(maxEval);
-        evaluations.resetCount();
-        function = f;
-        goal = goalType;
-        // Retrieve other settings.
-        parseOptimizationData(optData);
-        // Check input consistency.
-        checkParameters();
-        // Perform computation.
-        return doOptimize();
-    }
-
-    /**
-     * Scans the list of (required and optional) optimization data that
-     * characterize the problem.
-     *
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link InitialGuess}</li>
-     *  <li>{@link SimpleBounds}</li>
-     * </ul>
-     */
-    private void parseOptimizationData(OptimizationData... optData) {
-        // The existing values (as set by the previous call) are reused if
-        // not provided in the argument list.
-        for (OptimizationData data : optData) {
-            if (data instanceof InitialGuess) {
-                start = ((InitialGuess) data).getInitialGuess();
-                continue;
-            }
-            if (data instanceof SimpleBounds) {
-                final SimpleBounds bounds = (SimpleBounds) data;
-                lowerBound = bounds.getLower();
-                upperBound = bounds.getUpper();
-                continue;
-            }
-        }
-    }
-
-    /**
-     * @return the optimization type.
-     */
-    public GoalType getGoalType() {
-        return goal;
-    }
-
-    /**
-     * @return the initial guess.
-     */
-    public double[] getStartPoint() {
-        return start == null ? null : start.clone();
-    }
-    /**
-     * @return the lower bounds.
-     * @since 3.1
-     */
-    public double[] getLowerBound() {
-        return lowerBound == null ? null : lowerBound.clone();
-    }
-    /**
-     * @return the upper bounds.
-     * @since 3.1
-     */
-    public double[] getUpperBound() {
-        return upperBound == null ? null : upperBound.clone();
-    }
-
-    /**
-     * Perform the bulk of the optimization algorithm.
-     *
-     * @return the point/value pair giving the optimal value of the
-     * objective function.
-     */
-    protected abstract PointValuePair doOptimize();
-
-    /**
-     * Check parameters consistency.
-     */
-    private void checkParameters() {
-        if (start != null) {
-            final int dim = start.length;
-            if (lowerBound != null) {
-                if (lowerBound.length != dim) {
-                    throw new DimensionMismatchException(lowerBound.length, dim);
-                }
-                for (int i = 0; i < dim; i++) {
-                    final double v = start[i];
-                    final double lo = lowerBound[i];
-                    if (v < lo) {
-                        throw new NumberIsTooSmallException(v, lo, true);
-                    }
-                }
-            }
-            if (upperBound != null) {
-                if (upperBound.length != dim) {
-                    throw new DimensionMismatchException(upperBound.length, dim);
-                }
-                for (int i = 0; i < dim; i++) {
-                    final double v = start[i];
-                    final double hi = upperBound[i];
-                    if (v > hi) {
-                        throw new NumberIsTooLargeException(v, hi, true);
-                    }
-                }
-            }
-
-            // If the bounds were not specified, the allowed interval is
-            // assumed to be [-inf, +inf].
-            if (lowerBound == null) {
-                lowerBound = new double[dim];
-                for (int i = 0; i < dim; i++) {
-                    lowerBound[i] = Double.NEGATIVE_INFINITY;
-                }
-            }
-            if (upperBound == null) {
-                upperBound = new double[dim];
-                for (int i = 0; i < dim; i++) {
-                    upperBound[i] = Double.POSITIVE_INFINITY;
-                }
-            }
-        }
-    }
-}

http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java
b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java
deleted file mode 100644
index d179202..0000000
--- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java
+++ /dev/null
@@ -1,82 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.commons.math4.optimization.direct;
-
-import org.apache.commons.math4.analysis.MultivariateFunction;
-import org.apache.commons.math4.optimization.BaseMultivariateOptimizer;
-import org.apache.commons.math4.optimization.BaseMultivariateSimpleBoundsOptimizer;
-import org.apache.commons.math4.optimization.ConvergenceChecker;
-import org.apache.commons.math4.optimization.GoalType;
-import org.apache.commons.math4.optimization.InitialGuess;
-import org.apache.commons.math4.optimization.PointValuePair;
-import org.apache.commons.math4.optimization.SimpleBounds;
-
-/**
- * Base class for implementing optimizers for multivariate scalar functions,
- * subject to simple bounds: The valid range of the parameters is an interval.
- * The interval can possibly be infinite (in one or both directions).
- * This base class handles the boiler-plate methods associated to thresholds
- * settings, iterations and evaluations counting.
- *
- * @param <FUNC> Type of the objective function to be optimized.
- *
- * @deprecated As of 3.1 (to be removed in 4.0).
- * @since 3.0
- * @deprecated As of 3.1 since the {@link BaseAbstractMultivariateOptimizer
- * base class} contains similar functionality.
- */
-@Deprecated
-public abstract class BaseAbstractMultivariateSimpleBoundsOptimizer<FUNC extends MultivariateFunction>
-    extends BaseAbstractMultivariateOptimizer<FUNC>
-    implements BaseMultivariateOptimizer<FUNC>,
-               BaseMultivariateSimpleBoundsOptimizer<FUNC> {
-    /**
-     * Simple constructor with default settings.
-     * The convergence checker is set to a
-     * {@link org.apache.commons.math4.optimization.SimpleValueChecker}.
-     *
-     * @see BaseAbstractMultivariateOptimizer#BaseAbstractMultivariateOptimizer()
-     * @deprecated See {@link org.apache.commons.math4.optimization.SimpleValueChecker#SimpleValueChecker()}
-     */
-    @Deprecated
-    protected BaseAbstractMultivariateSimpleBoundsOptimizer() {}
-
-    /**
-     * @param checker Convergence checker.
-     */
-    protected BaseAbstractMultivariateSimpleBoundsOptimizer(ConvergenceChecker<PointValuePair>
checker) {
-        super(checker);
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType,
-                                   double[] startPoint) {
-        return super.optimizeInternal(maxEval, f, goalType,
-                                      new InitialGuess(startPoint));
-    }
-
-    /** {@inheritDoc} */
-    public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType,
-                                   double[] startPoint,
-                                   double[] lower, double[] upper) {
-        return super.optimizeInternal(maxEval, f, goalType,
-                                      new InitialGuess(startPoint),
-                                      new SimpleBounds(lower, upper));
-    }
-}

http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java
b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java
deleted file mode 100644
index ccca86e..0000000
--- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java
+++ /dev/null
@@ -1,370 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.commons.math4.optimization.direct;
-
-import org.apache.commons.math4.analysis.MultivariateVectorFunction;
-import org.apache.commons.math4.exception.DimensionMismatchException;
-import org.apache.commons.math4.exception.MaxCountExceededException;
-import org.apache.commons.math4.exception.NullArgumentException;
-import org.apache.commons.math4.exception.TooManyEvaluationsException;
-import org.apache.commons.math4.linear.RealMatrix;
-import org.apache.commons.math4.optimization.BaseMultivariateVectorOptimizer;
-import org.apache.commons.math4.optimization.ConvergenceChecker;
-import org.apache.commons.math4.optimization.InitialGuess;
-import org.apache.commons.math4.optimization.OptimizationData;
-import org.apache.commons.math4.optimization.PointVectorValuePair;
-import org.apache.commons.math4.optimization.SimpleVectorValueChecker;
-import org.apache.commons.math4.optimization.Target;
-import org.apache.commons.math4.optimization.Weight;
-import org.apache.commons.math4.util.Incrementor;
-
-/**
- * Base class for implementing optimizers for multivariate scalar functions.
- * This base class handles the boiler-plate methods associated to thresholds
- * settings, iterations and evaluations counting.
- *
- * @param <FUNC> the type of the objective function to be optimized
- *
- * @deprecated As of 3.1 (to be removed in 4.0).
- * @since 3.0
- */
-@Deprecated
-public abstract class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
-    implements BaseMultivariateVectorOptimizer<FUNC> {
-    /** Evaluations counter. */
-    protected final Incrementor evaluations = new Incrementor();
-    /** Convergence checker. */
-    private ConvergenceChecker<PointVectorValuePair> checker;
-    /** Target value for the objective functions at optimum. */
-    private double[] target;
-    /** Weight matrix. */
-    private RealMatrix weightMatrix;
-    /** Weight for the least squares cost computation.
-     * @deprecated
-     */
-    @Deprecated
-    private double[] weight;
-    /** Initial guess. */
-    private double[] start;
-    /** Objective function. */
-    private FUNC function;
-
-    /**
-     * Simple constructor with default settings.
-     * The convergence check is set to a {@link SimpleVectorValueChecker}.
-     * @deprecated See {@link SimpleVectorValueChecker#SimpleVectorValueChecker()}
-     */
-    @Deprecated
-    protected BaseAbstractMultivariateVectorOptimizer() {
-        this(new SimpleVectorValueChecker());
-    }
-    /**
-     * @param checker Convergence checker.
-     */
-    protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair>
checker) {
-        this.checker = checker;
-    }
-
-    /** {@inheritDoc} */
-    public int getMaxEvaluations() {
-        return evaluations.getMaximalCount();
-    }
-
-    /** {@inheritDoc} */
-    public int getEvaluations() {
-        return evaluations.getCount();
-    }
-
-    /** {@inheritDoc} */
-    public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker() {
-        return checker;
-    }
-
-    /**
-     * Compute the objective function value.
-     *
-     * @param point Point at which the objective function must be evaluated.
-     * @return the objective function value at the specified point.
-     * @throws TooManyEvaluationsException if the maximal number of evaluations is
-     * exceeded.
-     */
-    protected double[] computeObjectiveValue(double[] point) {
-        try {
-            evaluations.incrementCount();
-        } catch (MaxCountExceededException e) {
-            throw new TooManyEvaluationsException(e.getMax());
-        }
-        return function.value(point);
-    }
-
-    /** {@inheritDoc}
-     *
-     * @deprecated As of 3.1. Please use
-     * {@link #optimize(int,MultivariateVectorFunction,OptimizationData[])}
-     * instead.
-     */
-    @Deprecated
-    public PointVectorValuePair optimize(int maxEval, FUNC f, double[] t, double[] w,
-                                         double[] startPoint) {
-        return optimizeInternal(maxEval, f, t, w, startPoint);
-    }
-
-    /**
-     * Optimize an objective function.
-     *
-     * @param maxEval Allowed number of evaluations of the objective function.
-     * @param f Objective function.
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link Target}</li>
-     *  <li>{@link Weight}</li>
-     *  <li>{@link InitialGuess}</li>
-     * </ul>
-     * @return the point/value pair giving the optimal value of the objective
-     * function.
-     * @throws TooManyEvaluationsException if the maximal number of
-     * evaluations is exceeded.
-     * @throws DimensionMismatchException if the initial guess, target, and weight
-     * arguments have inconsistent dimensions.
-     *
-     * @since 3.1
-     */
-    protected PointVectorValuePair optimize(int maxEval,
-                                            FUNC f,
-                                            OptimizationData... optData)
-        throws TooManyEvaluationsException,
-               DimensionMismatchException {
-        return optimizeInternal(maxEval, f, optData);
-    }
-
-    /**
-     * Optimize an objective function.
-     * Optimization is considered to be a weighted least-squares minimization.
-     * The cost function to be minimized is
-     * <code>&sum;weight<sub>i</sub>(objective<sub>i</sub>
- target<sub>i</sub>)<sup>2</sup></code>
-     *
-     * @param f Objective function.
-     * @param t Target value for the objective functions at optimum.
-     * @param w Weights for the least squares cost computation.
-     * @param startPoint Start point for optimization.
-     * @return the point/value pair giving the optimal value for objective
-     * function.
-     * @param maxEval Maximum number of function evaluations.
-     * @throws org.apache.commons.math4.exception.DimensionMismatchException
-     * if the start point dimension is wrong.
-     * @throws org.apache.commons.math4.exception.TooManyEvaluationsException
-     * if the maximal number of evaluations is exceeded.
-     * @throws org.apache.commons.math4.exception.NullArgumentException if
-     * any argument is {@code null}.
-     * @deprecated As of 3.1. Please use
-     * {@link #optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])}
-     * instead.
-     */
-    @Deprecated
-    protected PointVectorValuePair optimizeInternal(final int maxEval, final FUNC f,
-                                                    final double[] t, final double[] w,
-                                                    final double[] startPoint) {
-        // Checks.
-        if (f == null) {
-            throw new NullArgumentException();
-        }
-        if (t == null) {
-            throw new NullArgumentException();
-        }
-        if (w == null) {
-            throw new NullArgumentException();
-        }
-        if (startPoint == null) {
-            throw new NullArgumentException();
-        }
-        if (t.length != w.length) {
-            throw new DimensionMismatchException(t.length, w.length);
-        }
-
-        return optimizeInternal(maxEval, f,
-                                new Target(t),
-                                new Weight(w),
-                                new InitialGuess(startPoint));
-    }
-
-    /**
-     * Optimize an objective function.
-     *
-     * @param maxEval Allowed number of evaluations of the objective function.
-     * @param f Objective function.
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link Target}</li>
-     *  <li>{@link Weight}</li>
-     *  <li>{@link InitialGuess}</li>
-     * </ul>
-     * @return the point/value pair giving the optimal value of the objective
-     * function.
-     * @throws TooManyEvaluationsException if the maximal number of
-     * evaluations is exceeded.
-     * @throws DimensionMismatchException if the initial guess, target, and weight
-     * arguments have inconsistent dimensions.
-     *
-     * @since 3.1
-     */
-    protected PointVectorValuePair optimizeInternal(int maxEval,
-                                                    FUNC f,
-                                                    OptimizationData... optData)
-        throws TooManyEvaluationsException,
-               DimensionMismatchException {
-        // Set internal state.
-        evaluations.setMaximalCount(maxEval);
-        evaluations.resetCount();
-        function = f;
-        // Retrieve other settings.
-        parseOptimizationData(optData);
-        // Check input consistency.
-        checkParameters();
-        // Allow subclasses to reset their own internal state.
-        setUp();
-        // Perform computation.
-        return doOptimize();
-    }
-
-    /**
-     * Gets the initial values of the optimized parameters.
-     *
-     * @return the initial guess.
-     */
-    public double[] getStartPoint() {
-        return start.clone();
-    }
-
-    /**
-     * Gets the weight matrix of the observations.
-     *
-     * @return the weight matrix.
-     * @since 3.1
-     */
-    public RealMatrix getWeight() {
-        return weightMatrix.copy();
-    }
-    /**
-     * Gets the observed values to be matched by the objective vector
-     * function.
-     *
-     * @return the target values.
-     * @since 3.1
-     */
-    public double[] getTarget() {
-        return target.clone();
-    }
-
-    /**
-     * Gets the objective vector function.
-     * Note that this access bypasses the evaluation counter.
-     *
-     * @return the objective vector function.
-     * @since 3.1
-     */
-    protected FUNC getObjectiveFunction() {
-        return function;
-    }
-
-    /**
-     * Perform the bulk of the optimization algorithm.
-     *
-     * @return the point/value pair giving the optimal value for the
-     * objective function.
-     */
-    protected abstract PointVectorValuePair doOptimize();
-
-    /**
-     * @return a reference to the {@link #target array}.
-     * @deprecated As of 3.1.
-     */
-    @Deprecated
-    protected double[] getTargetRef() {
-        return target;
-    }
-    /**
-     * @return a reference to the {@link #weight array}.
-     * @deprecated As of 3.1.
-     */
-    @Deprecated
-    protected double[] getWeightRef() {
-        return weight;
-    }
-
-    /**
-     * Method which a subclass <em>must</em> override whenever its internal
-     * state depend on the {@link OptimizationData input} parsed by this base
-     * class.
-     * It will be called after the parsing step performed in the
-     * {@link #optimize(int,MultivariateVectorFunction,OptimizationData[])
-     * optimize} method and just before {@link #doOptimize()}.
-     *
-     * @since 3.1
-     */
-    protected void setUp() {
-        // XXX Temporary code until the new internal data is used everywhere.
-        final int dim = target.length;
-        weight = new double[dim];
-        for (int i = 0; i < dim; i++) {
-            weight[i] = weightMatrix.getEntry(i, i);
-        }
-    }
-
-    /**
-     * Scans the list of (required and optional) optimization data that
-     * characterize the problem.
-     *
-     * @param optData Optimization data. The following data will be looked for:
-     * <ul>
-     *  <li>{@link Target}</li>
-     *  <li>{@link Weight}</li>
-     *  <li>{@link InitialGuess}</li>
-     * </ul>
-     */
-    private void parseOptimizationData(OptimizationData... optData) {
-        // The existing values (as set by the previous call) are reused if
-        // not provided in the argument list.
-        for (OptimizationData data : optData) {
-            if (data instanceof Target) {
-                target = ((Target) data).getTarget();
-                continue;
-            }
-            if (data instanceof Weight) {
-                weightMatrix = ((Weight) data).getWeight();
-                continue;
-            }
-            if (data instanceof InitialGuess) {
-                start = ((InitialGuess) data).getInitialGuess();
-                continue;
-            }
-        }
-    }
-
-    /**
-     * Check parameters consistency.
-     *
-     * @throws DimensionMismatchException if {@link #target} and
-     * {@link #weightMatrix} have inconsistent dimensions.
-     */
-    private void checkParameters() {
-        if (target.length != weightMatrix.getColumnDimension()) {
-            throw new DimensionMismatchException(target.length,
-                                                 weightMatrix.getColumnDimension());
-        }
-    }
-}


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