buggy files form Math #62

projects/Math/62/org/apache/commons/math/optimization/univariate/MultiStartUnivariateRealOptimizer.java

@@ -0,0 +1,206 @@
+/*
+ * 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.math.optimization.univariate;
+
+import java.util.Arrays;
+import java.util.Comparator;
+
+import org.apache.commons.math.FunctionEvaluationException;
+import org.apache.commons.math.analysis.UnivariateRealFunction;
+import org.apache.commons.math.exception.MathIllegalStateException;
+import org.apache.commons.math.exception.ConvergenceException;
+import org.apache.commons.math.exception.util.LocalizedFormats;
+import org.apache.commons.math.random.RandomGenerator;
+import org.apache.commons.math.optimization.GoalType;
+import org.apache.commons.math.optimization.ConvergenceChecker;
+import org.apache.commons.math.util.FastMath;
+
+/**
+ * Special implementation of the {@link UnivariateRealOptimizer} interface
+ * adding multi-start features to an existing optimizer.
+ *
+ * This class wraps a classical optimizer to use it several times in
+ * turn with different starting points in order to avoid being trapped
+ * into a local extremum when looking for a global one.
+ *
+ * @param <FUNC> Type of the objective function to be optimized.
+ *
+ * @version $Revision$ $Date$
+ * @since 3.0
+ */
+public class MultiStartUnivariateRealOptimizer<FUNC extends UnivariateRealFunction>
+    implements BaseUnivariateRealOptimizer<FUNC> {
+    /** Underlying classical optimizer. */
+    private final BaseUnivariateRealOptimizer<FUNC> optimizer;
+    /** Maximal number of evaluations allowed. */
+    private int maxEvaluations;
+    /** Number of evaluations already performed for all starts. */
+    private int totalEvaluations;
+    /** Number of starts to go. */
+    private int starts;
+    /** Random generator for multi-start. */
+    private RandomGenerator generator;
+    /** Found optima. */
+    private UnivariateRealPointValuePair[] optima;
+
+    /**
+     * Create a multi-start optimizer from a single-start optimizer.
+     *
+     * @param optimizer Single-start optimizer to wrap.
+     * @param starts Number of starts to perform (including the
+     * first one), multi-start is disabled if value is less than or
+     * equal to 1.
+     * @param generator Random generator to use for restarts.
+     */
+    public MultiStartUnivariateRealOptimizer(final BaseUnivariateRealOptimizer<FUNC> optimizer,
+                                             final int starts,
+                                             final RandomGenerator generator) {
+        this.optimizer = optimizer;
+        this.starts = starts;
+        this.generator = generator;
+    }
+
+    /**
+     * {@inheritDoc}
+     */
+    public void setConvergenceChecker(ConvergenceChecker<UnivariateRealPointValuePair> checker) {
+        optimizer.setConvergenceChecker(checker);
+    }
+
+    /**
+     * {@inheritDoc}
+     */
+    public ConvergenceChecker<UnivariateRealPointValuePair> getConvergenceChecker() {
+        return optimizer.getConvergenceChecker();
+    }
+
+    /** {@inheritDoc} */
+    public int getMaxEvaluations() {
+        return maxEvaluations;
+    }
+
+    /** {@inheritDoc} */
+    public int getEvaluations() {
+        return totalEvaluations;
+    }
+
+    /** {@inheritDoc} */
+    public void setMaxEvaluations(int maxEvaluations) {
+        this.maxEvaluations = maxEvaluations;
+        optimizer.setMaxEvaluations(maxEvaluations);
+    }
+
+    /**
+     * Get all the optima found during the last call to {@link
+     * #optimize(FUNC,GoalType,double,double) optimize}.
+     * The optimizer stores all the optima found during a set of
+     * restarts. The {@link #optimize(FUNC,GoalType,double,double) optimize}
+     * method returns the best point only. This method returns all the points
+     * found at the end of each starts, including the best one already
+     * returned by the {@link #optimize(FUNC,GoalType,double,double) optimize}
+     * method.
+     * <br/>
+     * The returned array as one element for each start as specified
+     * in the constructor. It is ordered with the results from the
+     * runs that did converge first, sorted from best to worst
+     * objective value (i.e in ascending order if minimizing and in
+     * descending order if maximizing), followed by {@code null} elements
+     * corresponding to the runs that did not converge. This means all
+     * elements will be {@code null} if the {@link
+     * #optimize(FUNC,GoalType,double,double) optimize} method did throw a
+     * {@link ConvergenceException}). This also means that if the first
+     * element is not {@code null}, it is the best point found across all
+     * starts.
+     *
+     * @return an array containing the optima.
+     * @throws MathIllegalStateException if {@link
+     * #optimize(FUNC,GoalType,double,double) optimize} has not been called.
+     */
+    public UnivariateRealPointValuePair[] getOptima() {
+        if (optima == null) {
+            throw new MathIllegalStateException(LocalizedFormats.NO_OPTIMUM_COMPUTED_YET);
+        }
+        return optima.clone();
+    }
+
+    /** {@inheritDoc} */
+    public UnivariateRealPointValuePair optimize(final FUNC f,
+                                                 final GoalType goal,
+                                                 final double min, final double max)
+        throws FunctionEvaluationException {
+        return optimize(f, goal, min, max, 0);
+    }
+
+    /** {@inheritDoc} */
+    public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
+                                                 final double min, final double max,
+                                                 final double startValue)
+        throws FunctionEvaluationException {
+        optima = new UnivariateRealPointValuePair[starts];
+        totalEvaluations = 0;
+
+        // Multi-start loop.
+        for (int i = 0; i < starts; ++i) {
+            try {
+                final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
+                final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
+                optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
+            } catch (FunctionEvaluationException fee) {
+                optima[i] = null;
+            } catch (ConvergenceException ce) {
+                optima[i] = null;
+            }
+
+            final int usedEvaluations = optimizer.getEvaluations();
+            optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
+            totalEvaluations += usedEvaluations;
+        }
+
+        sortPairs(goal);
+
+        if (optima[0] == null) {
+            throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
+                                           starts);
+        }
+
+        // Return the point with the best objective function value.
+        return optima[0];
+    }
+
+    /**
+     * Sort the optima from best to worst, followed by {@code null} elements.
+     *
+     * @param goal Goal type.
+     */
+    private void sortPairs(final GoalType goal) {
+        Arrays.sort(optima, new Comparator<UnivariateRealPointValuePair>() {
+                public int compare(final UnivariateRealPointValuePair o1,
+                                   final UnivariateRealPointValuePair o2) {
+                    if (o1 == null) {
+                        return (o2 == null) ? 0 : 1;
+                    } else if (o2 == null) {
+                        return -1;
+                    }
+                    final double v1 = o1.getValue();
+                    final double v2 = o2.getValue();
+                    return (goal == GoalType.MINIMIZE) ?
+                        Double.compare(v1, v2) : Double.compare(v2, v1);
+                }
+            });
+    }
+}