MATH-1672: Remove stat.ranking package

Functionality has been transferred to the Commons Statistics ranking
module.

Author: aherbert

commons-math-legacy/pom.xml

@@ -51,6 +51,11 @@
       <artifactId>commons-statistics-distribution</artifactId>
     </dependency>
 
+    <dependency>
+      <groupId>org.apache.commons</groupId>
+      <artifactId>commons-statistics-ranking</artifactId>
+    </dependency>
+
     <dependency>
       <groupId>org.apache.commons</groupId>
       <artifactId>commons-numbers-core</artifactId>

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/correlation/SpearmansCorrelation.java

@@ -22,9 +22,9 @@
 import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
 import org.apache.commons.math4.legacy.linear.BlockRealMatrix;
 import org.apache.commons.math4.legacy.linear.RealMatrix;
-import org.apache.commons.math4.legacy.stat.ranking.NaNStrategy;
-import org.apache.commons.math4.legacy.stat.ranking.NaturalRanking;
-import org.apache.commons.math4.legacy.stat.ranking.RankingAlgorithm;
+import org.apache.commons.statistics.ranking.NaNStrategy;
+import org.apache.commons.statistics.ranking.NaturalRanking;
+import org.apache.commons.statistics.ranking.RankingAlgorithm;
 
 /**
  * Spearman's rank correlation. This implementation performs a rank
@@ -179,8 +179,8 @@ public double correlation(final double[] xArray, final double[] yArray) {
             throw new MathIllegalArgumentException(LocalizedFormats.INSUFFICIENT_DIMENSION,
                                                    xArray.length, 2);
         } else {
-            return new PearsonsCorrelation().correlation(rankingAlgorithm.rank(xArray),
-                                                         rankingAlgorithm.rank(yArray));
+            return new PearsonsCorrelation().correlation(rankingAlgorithm.apply(xArray),
+                                                         rankingAlgorithm.apply(yArray));
         }
     }
 
@@ -194,7 +194,7 @@ public double correlation(final double[] xArray, final double[] yArray) {
     private RealMatrix rankTransform(final RealMatrix matrix) {
         RealMatrix transformed = matrix.copy();
         for (int i = 0; i < transformed.getColumnDimension(); i++) {
-            transformed.setColumn(i, rankingAlgorithm.rank(transformed.getColumn(i)));
+            transformed.setColumn(i, rankingAlgorithm.apply(transformed.getColumn(i)));
         }
 
         return transformed;

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/descriptive/rank/Median.java

@@ -18,7 +18,7 @@
 
 import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
 import org.apache.commons.math4.legacy.exception.NullArgumentException;
-import org.apache.commons.math4.legacy.stat.ranking.NaNStrategy;
+import org.apache.commons.statistics.ranking.NaNStrategy;
 
 
 /**

commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/stat/descriptive/rank/Percentile.java

@@ -28,9 +28,9 @@
 import org.apache.commons.math4.legacy.exception.OutOfRangeException;
 import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
 import org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic;
-import org.apache.commons.math4.legacy.stat.ranking.NaNStrategy;
 import org.apache.commons.math4.core.jdkmath.JdkMath;
 import org.apache.commons.math4.legacy.core.MathArrays;
+import org.apache.commons.statistics.ranking.NaNStrategy;
 
 /**
  * Provides percentile computation.