Added @since tags.

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@925812 13f79535-47bb-0310-9956-ffa450edef68

src/main/java/org/apache/commons/math/analysis/solvers/BrentSolver.java

@@ -32,10 +32,15 @@ import org.apache.commons.math.analysis.UnivariateRealFunction;
  */
 public class BrentSolver extends UnivariateRealSolverImpl {
 
-    /** Default absolute accuracy */
+    /**
+     * Default absolute accuracy
+     * @since 2.1
+     */
     public static final double DEFAULT_ABSOLUTE_ACCURACY = 1E-6;
 
-    /** Default maximum number of iterations */
+    /** Default maximum number of iterations
+     * @since 2.1
+     */
     public static final int DEFAULT_MAXIMUM_ITERATIONS = 100;
 
     /** Error message for non-bracketing interval. */
@@ -71,6 +76,7 @@ public class BrentSolver extends UnivariateRealSolverImpl {
      * Construct a solver with the given absolute accuracy.
      *
      * @param absoluteAccuracy lower bound for absolute accuracy of solutions returned by the solver
+     * @since 2.1
      */
     public BrentSolver(double absoluteAccuracy) {
         super(DEFAULT_MAXIMUM_ITERATIONS, absoluteAccuracy);
@@ -81,6 +87,7 @@ public class BrentSolver extends UnivariateRealSolverImpl {
      *
      * @param maximumIterations maximum number of iterations
      * @param absoluteAccuracy lower bound for absolute accuracy of solutions returned by the solver
+     * @since 2.1
      */
     public BrentSolver(int maximumIterations, double absoluteAccuracy) {
         super(maximumIterations, absoluteAccuracy);

src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java

@@ -40,7 +40,10 @@ public abstract class AbstractContinuousDistribution
     /** Serializable version identifier */
     private static final long serialVersionUID = -38038050983108802L;
 
-    /** Solver absolute accuracy for inverse cum computation */
+    /**
+     * Solver absolute accuracy for inverse cum computation
+     * @since 2.1
+     */
     private double solverAbsoluteAccuracy = BrentSolver.DEFAULT_ABSOLUTE_ACCURACY;
 
     /**
@@ -55,6 +58,7 @@ public abstract class AbstractContinuousDistribution
      * @param x  The point at which the density should be computed.
      * @return  The pdf at point x.
      * @throws MathRuntimeException if the specialized class hasn't implemented this function
+     * @since 2.1
      */
     public double density(double x) throws MathRuntimeException {
         throw new MathRuntimeException(new UnsupportedOperationException(),
@@ -166,6 +170,7 @@ public abstract class AbstractContinuousDistribution
      * Returns the solver absolute accuracy for inverse cum computation.
      *
      * @return the maximum absolute error in inverse cumulative probability estimates
+     * @since 2.1
      */
     protected double getSolverAbsoluteAccuracy() {
         return solverAbsoluteAccuracy;

src/main/java/org/apache/commons/math/distribution/BetaDistributionImpl.java

@@ -114,6 +114,7 @@ public class BetaDistributionImpl
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     public double density(double x) {
         recomputeZ();

src/main/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java

@@ -89,6 +89,7 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {

src/main/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java

@@ -29,7 +29,10 @@ public class ChiSquaredDistributionImpl
     extends AbstractContinuousDistribution
     implements ChiSquaredDistribution, Serializable  {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accuracy
+     * @since 2.1
+     */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Serializable version identifier */
@@ -71,6 +74,7 @@ public class ChiSquaredDistributionImpl
      * @param df degrees of freedom.
      * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
      * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
+     * @since 2.1
      */
     public ChiSquaredDistributionImpl(double df, double inverseCumAccuracy) {
         super();
@@ -120,6 +124,7 @@ public class ChiSquaredDistributionImpl
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {
@@ -257,6 +262,7 @@ public class ChiSquaredDistributionImpl
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java

@@ -91,6 +91,7 @@ public class ExponentialDistributionImpl extends AbstractContinuousDistribution
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {

src/main/java/org/apache/commons/math/distribution/FDistributionImpl.java

@@ -32,7 +32,10 @@ public class FDistributionImpl
     extends AbstractContinuousDistribution
     implements FDistribution, Serializable  {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accurac
+     * @since 2.1
+     */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Message for non positive degrees of freddom. */
@@ -67,6 +70,7 @@ public class FDistributionImpl
      * @param denominatorDegreesOfFreedom the denominator degrees of freedom.
      * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
      * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
+     * @since 2.1
      */
     public FDistributionImpl(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom,
             double inverseCumAccuracy) {
@@ -81,6 +85,7 @@ public class FDistributionImpl
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {
@@ -269,6 +274,7 @@ public class FDistributionImpl
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/distribution/GammaDistributionImpl.java

@@ -30,7 +30,10 @@ import org.apache.commons.math.special.Gamma;
 public class GammaDistributionImpl extends AbstractContinuousDistribution
     implements GammaDistribution, Serializable  {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accuracy
+     * @since 2.1
+     */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Serializable version identifier */
@@ -60,6 +63,7 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
      * @param beta the scale parameter.
      * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
      * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
+     * @since 2.1
      */
     public GammaDistributionImpl(double alpha, double beta, double inverseCumAccuracy) {
         super();
@@ -285,6 +289,7 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/distribution/NormalDistributionImpl.java

@@ -33,7 +33,10 @@ import org.apache.commons.math.special.Erf;
 public class NormalDistributionImpl extends AbstractContinuousDistribution
         implements NormalDistribution, Serializable {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accuracy
+     * @since 2.1
+     */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Serializable version identifier */
@@ -67,6 +70,7 @@ public class NormalDistributionImpl extends AbstractContinuousDistribution
      * @param mean mean for this distribution
      * @param sd standard deviation for this distribution
      * @param inverseCumAccuracy inverse cumulative probability accuracy
+     * @since 2.1
      */
     public NormalDistributionImpl(double mean, double sd, double inverseCumAccuracy) {
         super();
@@ -156,6 +160,7 @@ public class NormalDistributionImpl extends AbstractContinuousDistribution
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     public double density(double x) {
         double x0 = x - mean;
@@ -190,6 +195,7 @@ public class NormalDistributionImpl extends AbstractContinuousDistribution
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/distribution/PoissonDistributionImpl.java

@@ -33,11 +33,13 @@ public class PoissonDistributionImpl extends AbstractIntegerDistribution
 
     /**
      * Default maximum number of iterations for cumulative probability calculations.
+     * @since 2.1
      */
     public static final int DEFAULT_MAX_ITERATIONS = 10000000;
 
     /**
-     * Default convergence criterion
+     * Default convergence criterion.
+     * @since 2.1
      */
     public static final double DEFAULT_EPSILON = 1E-12;
 
@@ -83,6 +85,7 @@ public class PoissonDistributionImpl extends AbstractIntegerDistribution
      * @param p the Poisson mean
      * @param epsilon the convergence criteria for cumulative probabilites
      * @param maxIterations the maximum number of iterations for cumulative probabilites
+     * @since 2.1
      */
     public PoissonDistributionImpl(double p, double epsilon, int maxIterations) {
         setMean(p);
@@ -95,6 +98,7 @@ public class PoissonDistributionImpl extends AbstractIntegerDistribution
      *
      * @param p the Poisson mean
      * @param epsilon the convergence criteria for cumulative probabilites
+     * @since 2.1
      */
     public PoissonDistributionImpl(double p, double epsilon) {
         setMean(p);
@@ -106,6 +110,7 @@ public class PoissonDistributionImpl extends AbstractIntegerDistribution
      *
      * @param p the Poisson mean
      * @param maxIterations the maximum number of iterations for cumulative probabilites
+     * @since 2.1
      */
     public PoissonDistributionImpl(double p, int maxIterations) {
         setMean(p);

src/main/java/org/apache/commons/math/distribution/TDistributionImpl.java

@@ -33,7 +33,10 @@ public class TDistributionImpl
     extends AbstractContinuousDistribution
     implements TDistribution, Serializable  {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accuracy
+     * @since 2.1
+    */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Serializable version identifier */
@@ -52,6 +55,7 @@ public class TDistributionImpl
      * @param degreesOfFreedom the degrees of freedom.
      * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
      * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
+     * @since 2.1
      */
     public TDistributionImpl(double degreesOfFreedom, double inverseCumAccuracy) {
         super();
@@ -102,6 +106,7 @@ public class TDistributionImpl
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {
@@ -210,6 +215,7 @@ public class TDistributionImpl
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java

@@ -31,7 +31,10 @@ import org.apache.commons.math.MathRuntimeException;
 public class WeibullDistributionImpl extends AbstractContinuousDistribution
         implements WeibullDistribution, Serializable {
 
-    /** Default inverse cumulative probability accuracy */
+    /**
+     * Default inverse cumulative probability accuracy
+     * @since 2.1
+     */
     public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
 
     /** Serializable version identifier */
@@ -63,6 +66,7 @@ public class WeibullDistributionImpl extends AbstractContinuousDistribution
      * @param beta the scale parameter.
      * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
      * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
+     * @since 2.1
      */
     public WeibullDistributionImpl(double alpha, double beta, double inverseCumAccuracy){
         super();
@@ -107,6 +111,7 @@ public class WeibullDistributionImpl extends AbstractContinuousDistribution
      *
      * @param x The point at which the density should be computed.
      * @return The pdf at point x.
+     * @since 2.1
      */
     @Override
     public double density(double x) {
@@ -246,6 +251,7 @@ public class WeibullDistributionImpl extends AbstractContinuousDistribution
      * inverse cumulative probabilities.
      *
      * @return the solver absolute accuracy
+     * @since 2.1
      */
     @Override
     protected double getSolverAbsoluteAccuracy() {

src/main/java/org/apache/commons/math/genetics/GeneticAlgorithm.java

@@ -219,6 +219,7 @@ public class GeneticAlgorithm {
      * reach {@link StoppingCondition} in the last run.
      *
      * @return number of generations evolved
+     * @since 2.1
      */
     public int getGenerationsEvolved() {
         return generationsEvolved;

src/main/java/org/apache/commons/math/linear/OpenMapRealVector.java

@@ -200,6 +200,7 @@ public class OpenMapRealVector extends AbstractRealVector implements SparseRealV
      * Determine if this value is within epsilon of zero.
      * @param value The value to test
      * @return <code>true</code> if this value is within epsilon to zero, <code>false</code> otherwise
+     * @since 2.1
      */
     protected boolean isDefaultValue(double value) {
         return Math.abs(value) < epsilon;
@@ -279,7 +280,10 @@ public class OpenMapRealVector extends AbstractRealVector implements SparseRealV
         return res;
     }
 
-    /** {@inheritDoc} */
+    /**
+     * {@inheritDoc}
+     * @since 2.1
+     */
     @Override
     public OpenMapRealVector copy() {
         return new OpenMapRealVector(this);

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

@@ -63,10 +63,16 @@ public abstract class AbstractLeastSquaresOptimizer implements DifferentiableMul
     /** Number of rows of the jacobian matrix. */
     protected int rows;
 
-    /** Target value for the objective functions at optimum. */
+    /**
+     * Target value for the objective functions at optimum.
+     * @since 2.1
+     */
     protected double[] targetValues;
 
-    /** Weight for the least squares cost computation. */
+    /**
+     * Weight for the least squares cost computation.
+     * @since 2.1
+     */
     protected double[] residualsWeights;
 
     /** Current point. */

src/main/java/org/apache/commons/math/optimization/general/AbstractScalarDifferentiableOptimizer.java

@@ -45,7 +45,10 @@ public abstract class AbstractScalarDifferentiableOptimizer
     /** Convergence checker. */
     protected RealConvergenceChecker checker;
 
-    /** Type of optimization. */
+    /**
+     * Type of optimization.
+     * @since 2.1
+     */
     protected GoalType goal;
 
     /** Current point set. */

src/main/java/org/apache/commons/math/optimization/linear/AbstractLinearOptimizer.java

@@ -37,16 +37,28 @@ public abstract class AbstractLinearOptimizer implements LinearOptimizer {
     /** Default maximal number of iterations allowed. */
     public static final int DEFAULT_MAX_ITERATIONS = 100;
 
-    /** Linear objective function. */
+    /**
+     * Linear objective function.
+     * @since 2.1
+     */
     protected LinearObjectiveFunction function;
 
-    /** Linear constraints. */
+    /**
+     * Linear constraints.
+     * @since 2.1
+     */
     protected Collection<LinearConstraint> linearConstraints;
 
-    /** Type of optimization goal: either {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}. */
+    /**
+     * Type of optimization goal: either {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
+     * @since 2.1
+     */
     protected GoalType goal;
 
-    /** Whether to restrict the variables to non-negative values. */
+    /**
+     * Whether to restrict the variables to non-negative values.
+     * @since 2.1
+     */
     protected boolean nonNegative;
 
     /** Maximal number of iterations allowed. */

src/main/java/org/apache/commons/math/random/EmpiricalDistributionImpl.java

@@ -436,6 +436,7 @@ public class EmpiricalDistributionImpl implements Serializable, EmpiricalDistrib
      * bounds now returned by {@link #getGeneratorUpperBounds()}.</p>
      *
      * @return array of bin upper bounds
+     * @since 2.1
      */
     public double[] getUpperBounds() {
         double[] binUpperBounds = new double[binCount];

src/main/java/org/apache/commons/math/random/UnitSphereRandomVectorGenerator.java

@@ -21,6 +21,7 @@ package org.apache.commons.math.random;
 /**
  * Generate random vectors isotropically located on the surface of a sphere.
  *
+ * @since 2.1
  * @version $Revision$ $Date$
  */
 

src/main/java/org/apache/commons/math/stat/clustering/EuclideanIntegerPoint.java

@@ -99,7 +99,10 @@ public class EuclideanIntegerPoint implements Clusterable<EuclideanIntegerPoint>
         return hashCode;
     }
 
-    /** {@inheritDoc} */
+    /**
+     * {@inheritDoc}
+     * @since 2.1
+     */
     @Override
     public String toString() {
         final StringBuffer buff = new StringBuffer("(");

src/main/java/org/apache/commons/math/util/BigReal.java

@@ -192,6 +192,7 @@ public class BigReal implements FieldElement<BigReal>, Comparable<BigReal>, Seri
      * Gets the rounding mode for division operations
      * The default is {@code RoundingMode.HALF_UP}
      * @return the rounding mode.
+     * @since 2.1
      */
     public RoundingMode getRoundingMode() {
         return roundingMode;
@@ -200,6 +201,7 @@ public class BigReal implements FieldElement<BigReal>, Comparable<BigReal>, Seri
     /***
      * Sets the rounding mode for decimal divisions.
      * @param roundingMode rounding mode for decimal divisions
+     * @since 2.1
      */
     public void setRoundingMode(RoundingMode roundingMode) {
         this.roundingMode = roundingMode;
@@ -209,6 +211,7 @@ public class BigReal implements FieldElement<BigReal>, Comparable<BigReal>, Seri
      * Sets the scale for division operations.
      * The default is 64
      * @return the scale
+     * @since 2.1
      */
     public int getScale() {
         return scale;
@@ -217,6 +220,7 @@ public class BigReal implements FieldElement<BigReal>, Comparable<BigReal>, Seri
     /***
      * Sets the scale for division operations.
      * @param scale scale for division operations
+     * @since 2.1
      */
     public void setScale(int scale) {
         this.scale = scale;

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

@@ -38,7 +38,10 @@ public final class MathUtils {
      */
     public static final double SAFE_MIN = 0x1.0p-1022;
 
-    /** 2 π. */
+    /**
+     * 2 π.
+     * @since 2.1
+     */
     public static final double TWO_PI = 2 * Math.PI;
 
     /** -1.0 cast as a byte. */
@@ -1141,6 +1144,7 @@ public final class MathUtils {
       * @return normalized array
       * @throws ArithmeticException if the input array contains infinite elements or sums to zero
       * @throws IllegalArgumentException if the target sum is infinite or NaN
+      * @since 2.1
       */
      public static double[] normalizeArray(double[] values, double normalizedSum)
        throws ArithmeticException, IllegalArgumentException {