MATH-1671: Update stat.descriptive to use Commons Statistics

commons-math-legacy/pom.xml

@@ -56,6 +56,11 @@
       <artifactId>commons-statistics-ranking</artifactId>
     </dependency>
 
+    <dependency>
+      <groupId>org.apache.commons</groupId>
+      <artifactId>commons-statistics-descriptive</artifactId>
+    </dependency>
+
     <dependency>
       <groupId>org.apache.commons</groupId>
       <artifactId>commons-numbers-core</artifactId>

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/ml/clustering/KMeansPlusPlusClusterer.java

@@ -24,10 +24,9 @@
 import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
 import org.apache.commons.math4.legacy.ml.distance.DistanceMeasure;
 import org.apache.commons.math4.legacy.ml.distance.EuclideanDistance;
-import org.apache.commons.math4.legacy.stat.descriptive.moment.Variance;
 import org.apache.commons.rng.UniformRandomProvider;
 import org.apache.commons.rng.simple.RandomSource;
-
+import org.apache.commons.statistics.descriptive.Variance;
 import java.util.ArrayList;
 import java.util.Collection;
 import java.util.Collections;
@@ -431,11 +430,11 @@ private T getPointFromLargestVarianceCluster(final Collection<CentroidCluster<T>
 
                 // compute the distance variance of the current cluster
                 final Clusterable center = cluster.getCenter();
-                final Variance stat = new Variance();
+                final Variance stat = Variance.create();
                 for (final T point : cluster.getPoints()) {
-                    stat.increment(distance(point, center));
+                    stat.accept(distance(point, center));
                 }
-                final double variance = stat.getResult();
+                final double variance = stat.getAsDouble();
 
                 // select the cluster with the largest variance
                 if (variance > maxVariance) {

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/ml/clustering/evaluation/SumOfClusterVariances.java

@@ -23,7 +23,7 @@
 import org.apache.commons.math4.legacy.ml.clustering.Clusterable;
 import org.apache.commons.math4.legacy.ml.clustering.ClusterEvaluator;
 import org.apache.commons.math4.legacy.ml.distance.DistanceMeasure;
-import org.apache.commons.math4.legacy.stat.descriptive.moment.Variance;
+import org.apache.commons.statistics.descriptive.Variance;
 
 /**
  * Computes the sum of intra-cluster distance variances according to the formula:
@@ -56,12 +56,12 @@ public double score(List<? extends Cluster<? extends Clusterable>> clusters) {
                 final Clusterable center = cluster.centroid();
 
                 // compute the distance variance of the current cluster
-                final Variance stat = new Variance();
+                final Variance stat = Variance.create();
                 for (final Clusterable point : cluster.getPoints()) {
-                    stat.increment(distance(point, center));
+                    stat.accept(distance(point, center));
                 }
 
-                varianceSum += stat.getResult();
+                varianceSum += stat.getAsDouble();
             }
         }
         return varianceSum;

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/optim/nonlinear/scalar/SimulatedAnnealing.java

@@ -19,7 +19,7 @@
 import java.util.function.BiFunction;
 import java.util.function.DoublePredicate;
 import org.apache.commons.rng.UniformRandomProvider;
-import org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation;
+import org.apache.commons.statistics.descriptive.StandardDeviation;
 import org.apache.commons.math4.legacy.optim.OptimizationData;
 import org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex;
 
@@ -164,11 +164,11 @@ static CoolingSchedule aarstAndVanLaarhoven(final double delta) {
 
             return (previousTemperature, simplex) -> {
                 // Standard deviation of the values of the objective function.
-                final StandardDeviation stddev = new StandardDeviation();
+                final StandardDeviation stddev = StandardDeviation.create();
                 for (int i = 0; i < simplex.getSize(); i++) {
-                    stddev.increment(simplex.get(i).getValue());
+                    stddev.accept(simplex.get(i).getValue());
                 }
-                final double sigma = stddev.getResult();
+                final double sigma = stddev.getAsDouble();
 
                 final double a = previousTemperature * Math.log(1 + delta);
                 final double b = 3 * sigma;