fixed checkstyle and findbugs errors

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@754765 13f79535-47bb-0310-9956-ffa450edef68

findbugs-exclude-filter.xml

@@ -55,12 +55,12 @@
 
   <!-- the following expositions of internal representation are intentional and documented -->
   <Match>
-    <Class name="org.apache.commons.math.optimization.PointValuePair"/>
+    <Class name="org.apache.commons.math.optimization.ScalarPointValuePair"/>
     <Method name="getPointRef" params="" returns="double[]" />
     <Bug pattern="EI_EXPOSE_REP" />
   </Match>
   <Match>
-    <Class name="org.apache.commons.math.optimization.PointValuePair"/>
+    <Class name="org.apache.commons.math.optimization.ScalarPointValuePair"/>
     <Method name="&lt;init>" params="double[],double,boolean" returns="void" />
     <Bug pattern="EI_EXPOSE_REP2" />
   </Match>

src/java/org/apache/commons/math/optimization/ScalarDifferentiableOptimizer.java

@@ -68,7 +68,7 @@ public interface ScalarDifferentiableOptimizer extends Serializable {
     void setConvergenceChecker(ScalarConvergenceChecker checker);
 
     /** Get the convergence checker.
-     * @param checker object to use to check for convergence
+     * @return object used to check for convergence
      */
     ScalarConvergenceChecker getConvergenceChecker();
 

src/java/org/apache/commons/math/optimization/ScalarOptimizer.java

@@ -68,7 +68,7 @@ public interface ScalarOptimizer extends Serializable {
     void setConvergenceChecker(ScalarConvergenceChecker checker);
 
     /** Get the convergence checker.
-     * @param checker object to use to check for convergence
+     * @return object used to check for convergence
      */
     ScalarConvergenceChecker getConvergenceChecker();
 

src/java/org/apache/commons/math/optimization/ScalarPointValuePair.java

@@ -56,7 +56,7 @@ public class ScalarPointValuePair implements Serializable {
      * it will be referenced
      */
     public ScalarPointValuePair(final double[] point, final double value,
-                          final boolean copyArray) {
+                                final boolean copyArray) {
         this.point = copyArray ? point.clone() : point;
         this.value  = value;
     }

src/java/org/apache/commons/math/optimization/VectorialDifferentiableOptimizer.java

@@ -78,7 +78,7 @@ public interface VectorialDifferentiableOptimizer extends Serializable {
     void setConvergenceChecker(VectorialConvergenceChecker checker);
 
     /** Get the convergence checker.
-     * @param checker object to use to check for convergence
+     * @return object used to check for convergence
      */
     VectorialConvergenceChecker getConvergenceChecker();
 

src/java/org/apache/commons/math/optimization/direct/DirectSearchOptimizer.java

@@ -313,7 +313,8 @@ public abstract class DirectSearchOptimizer implements ScalarOptimizer {
 
     /** Build an initial simplex.
      * @param startPoint the start point for optimization
-     * @exception IllegalArgumentException
+     * @exception IllegalArgumentException if the start point does not match
+     * simplex dimension
      */
     private void buildSimplex(final double[] startPoint)
         throws IllegalArgumentException {

src/java/org/apache/commons/math/optimization/general/AbstractLeastSquaresOptimizer.java

@@ -303,8 +303,8 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen
 
         // store least squares problem characteristics
         this.f         = f;
-        this.target    = target;
+        this.target    = target.clone();
-        this.weights   = weights;
+        this.weights   = weights.clone();
         this.variables = startPoint.clone();
         this.residuals = new double[target.length];
 
@@ -320,6 +320,11 @@ public abstract class AbstractLeastSquaresOptimizer implements VectorialDifferen
     }
 
     /** Perform the bulk of optimization algorithm.
+     * @return the point/value pair giving the optimal value for objective function
+     * @exception ObjectiveException if the objective function throws one during
+     * the search
+     * @exception OptimizationException if the algorithm failed to converge
+     * @exception IllegalArgumentException if the start point dimension is wrong
      */
     abstract protected VectorialPointValuePair doOptimize()
     throws ObjectiveException, OptimizationException, IllegalArgumentException;

src/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java

@@ -55,7 +55,7 @@ public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer {
      * and the maximal number of evaluation is set to
      * {@link AbstractLeastSquaresOptimizer#DEFAULT_MAX_EVALUATIONS}.
      * @param useLU if true, the normal equations will be solved using LU
-     * decomposition, otherwise it will be solved using QR decomposition
+     * decomposition, otherwise they will be solved using QR decomposition
      */
     public GaussNewtonOptimizer(final boolean useLU) {
         this.useLU = useLU;

src/java/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.java

@@ -60,7 +60,10 @@ import org.apache.commons.math.linear.decomposition.NotPositiveDefiniteMatrixExc
  */
 
 public class CorrelatedRandomVectorGenerator
-implements RandomVectorGenerator {
+    implements RandomVectorGenerator {
+
+    /** Serializable version identifier. */
+    private static final long serialVersionUID = -7162933284241468177L;
 
     /** Simple constructor.
      * <p>Build a correlated random vector generator from its mean

src/java/org/apache/commons/math/random/GaussianRandomGenerator.java

@@ -27,6 +27,9 @@ package org.apache.commons.math.random;
 
 public class GaussianRandomGenerator implements NormalizedRandomGenerator {
 
+    /** Serializable version identifier. */
+    private static final long serialVersionUID = -4698731518385853565L;
+
     /** Create a new generator.
      * @param generator underlying random generator to use
      */

src/java/org/apache/commons/math/random/NormalizedRandomGenerator.java

@@ -17,6 +17,8 @@
 
 package org.apache.commons.math.random;
 
+import java.io.Serializable;
+
 /** 
  * This interface represent a normalized random generator for
  * scalars.
@@ -24,7 +26,7 @@ package org.apache.commons.math.random;
  * @version $Revision$ $Date$
  * @since 1.2
  */
-public interface NormalizedRandomGenerator {
+public interface NormalizedRandomGenerator extends Serializable {
 
   /** Generate a random scalar with null mean and unit standard deviation.
    * <p>This method does <strong>not</strong> specify the shape of the

src/java/org/apache/commons/math/random/RandomVectorGenerator.java

@@ -17,6 +17,8 @@
 
 package org.apache.commons.math.random;
 
+import java.io.Serializable;
+
 /** This interface represents a random generator for whole vectors.
  * 
  * @since 1.2
@@ -24,7 +26,7 @@ package org.apache.commons.math.random;
  *
  */
 
-public interface RandomVectorGenerator {
+public interface RandomVectorGenerator extends Serializable {
 
   /** Generate a random vector.
    * @return a random vector as an array of double.

src/java/org/apache/commons/math/random/UncorrelatedRandomVectorGenerator.java

@@ -31,6 +31,9 @@ import java.util.Arrays;
 public class UncorrelatedRandomVectorGenerator
   implements RandomVectorGenerator {
 
+  /** Serializable version identifier. */
+  private static final long serialVersionUID = -3268228248001718811L;
+
   /** Simple constructor.
    * <p>Build an uncorrelated random vector generator from
    * its mean and standard deviation vectors.</p>

src/java/org/apache/commons/math/random/UniformRandomGenerator.java

@@ -31,6 +31,9 @@ package org.apache.commons.math.random;
 
 public class UniformRandomGenerator implements NormalizedRandomGenerator {
 
+    /** Serializable version identifier. */
+    private static final long serialVersionUID = 1569292426375546027L;
+
     /** Create a new generator.
      * @param generator underlying random generator to use
      */

src/java/org/apache/commons/math/util/MathUtils.java

@@ -549,8 +549,8 @@ public final class MathUtils {
      * <code>0</code>.</li>
      * </ul>
      * 
-     * @param u any number
+     * @param p any number
-     * @param v any number
+     * @param q any number
      * @return the greatest common divisor, never negative
      * @throws ArithmeticException
      *             if the result cannot be represented as a nonnegative int

src/test/org/apache/commons/math/optimization/general/GaussNewtonOptimizerTest.java

@@ -112,6 +112,7 @@ extends TestCase {
             optimizer.optimize(problem, problem.target, new double[] { 1 }, new double[] { 0 });
         assertEquals(0, optimizer.getRMS(), 1.0e-10);
         assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
+        assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
     }
 
     public void testColumnsPermutation() throws ObjectiveException, OptimizationException {
@@ -128,6 +129,9 @@ extends TestCase {
         assertEquals(0, optimizer.getRMS(), 1.0e-10);
         assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
         assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
+        assertEquals(4.0, optimum.getValue()[0], 1.0e-10);
+        assertEquals(6.0, optimum.getValue()[1], 1.0e-10);
+        assertEquals(1.0, optimum.getValue()[2], 1.0e-10);
 
     }
 

src/test/org/apache/commons/math/optimization/general/LevenbergMarquardtOptimizerTest.java

@@ -119,13 +119,14 @@ public class LevenbergMarquardtOptimizerTest
             fail("wrong exception caught");
         }
         assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
+        assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
     }
 
     public void testQRColumnsPermutation() throws ObjectiveException, OptimizationException {
 
         LinearProblem problem =
             new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
-                    new double[] { 4.0, 6.0, 1.0 });
+                              new double[] { 4.0, 6.0, 1.0 });
 
         LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
         VectorialPointValuePair optimum =
@@ -133,6 +134,9 @@ public class LevenbergMarquardtOptimizerTest
         assertEquals(0, optimizer.getRMS(), 1.0e-10);
         assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
         assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
+        assertEquals(4.0, optimum.getValue()[0], 1.0e-10);
+        assertEquals(6.0, optimum.getValue()[1], 1.0e-10);
+        assertEquals(1.0, optimum.getValue()[2], 1.0e-10);
 
     }