Added @since tags, cleaned up code. JIRA: MATH-1287
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@ -107,19 +107,17 @@ public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution {
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*
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* @param rng random number generator used for sampling
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* @param data input dataset
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* @since 3.6
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*/
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public EnumeratedIntegerDistribution(final RandomGenerator rng, final int[] data) {
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super(rng);
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final Map<Integer, Integer> dataMap = new HashMap<Integer, Integer>();
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for (int value : data) {
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Integer count = dataMap.get(value);
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if (count == null) {
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count = new Integer(1);
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} else {
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count = new Integer(count.intValue() + 1);
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count = 0;
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}
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dataMap.put(value, count);
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dataMap.put(value, ++count);
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}
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final int massPoints = dataMap.size();
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final double denom = data.length;
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@ -140,6 +138,7 @@ public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution {
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* with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,
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*
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* @param data input dataset
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* @since 3.6
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*/
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public EnumeratedIntegerDistribution(final int[] data) {
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this(new Well19937c(), data);
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@ -152,7 +151,7 @@ public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution {
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* @param probabilities probabilities
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* @return list of value/probability pairs
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*/
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private List<Pair<Integer, Double>> createDistribution(int[] singletons, double[] probabilities) {
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private static List<Pair<Integer, Double>> createDistribution(int[] singletons, double[] probabilities) {
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if (singletons.length != probabilities.length) {
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throw new DimensionMismatchException(probabilities.length, singletons.length);
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}
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@ -109,19 +109,17 @@ public class EnumeratedRealDistribution extends AbstractRealDistribution {
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*
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* @param rng random number generator used for sampling
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* @param data input dataset
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* @since 3.6
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*/
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public EnumeratedRealDistribution(final RandomGenerator rng, final double[] data) {
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super(rng);
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final Map<Double, Integer> dataMap = new HashMap<Double, Integer>();
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for (double value : data) {
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Integer count = dataMap.get(value);
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if (count == null) {
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count = new Integer(1);
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} else {
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count = new Integer(count.intValue() + 1);
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count = 0;
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}
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dataMap.put(value, count);
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dataMap.put(value, ++count);
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}
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final int massPoints = dataMap.size();
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final double denom = data.length;
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@ -142,6 +140,7 @@ public class EnumeratedRealDistribution extends AbstractRealDistribution {
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* with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,
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*
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* @param data input dataset
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* @since 3.6
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*/
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public EnumeratedRealDistribution(final double[] data) {
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this(new Well19937c(), data);
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@ -153,7 +152,7 @@ public class EnumeratedRealDistribution extends AbstractRealDistribution {
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* @param probabilities probabilities
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* @return list of value/probability pairs
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*/
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private List<Pair<Double, Double>> createDistribution(double[] singletons, double[] probabilities) {
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private static List<Pair<Double, Double>> createDistribution(double[] singletons, double[] probabilities) {
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if (singletons.length != probabilities.length) {
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throw new DimensionMismatchException(probabilities.length, singletons.length);
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}
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