Apache
/
commons-math
mirror of https://github.com/apache/commons-math.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Added @since tags, cleaned up code. JIRA: MATH-1287

This commit is contained in:
Phil Steitz 2015-11-15 10:56:43 -07:00
parent 29dfd9bb66
commit b38ce47047
2 changed files with 10 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

11
src/main/java/org/apache/commons/math3/distribution/EnumeratedIntegerDistribution.java
View File

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

11
src/main/java/org/apache/commons/math3/distribution/EnumeratedRealDistribution.java
View File

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