From 9234156f6a17fc6c8d288c138bc156f33884f4e4 Mon Sep 17 00:00:00 2001
From: EdwardRaff <Raff.Edward@gmail.com>
Date: Sun, 12 Nov 2017 00:34:48 -0500
Subject: [PATCH] Replicating and fixing 2nd bug reported in issue #68

---
 .../jsat/clustering/kmeans/NaiveKMeans.java   | 26 ++++++++-----------
 .../DivisiveGlobalClustererTest.java          |  2 +-
 2 files changed, 12 insertions(+), 16 deletions(-)

diff --git a/JSAT/src/jsat/clustering/kmeans/NaiveKMeans.java b/JSAT/src/jsat/clustering/kmeans/NaiveKMeans.java
index 985dd5d8..c6acb9e4 100644
--- a/JSAT/src/jsat/clustering/kmeans/NaiveKMeans.java
+++ b/JSAT/src/jsat/clustering/kmeans/NaiveKMeans.java
@@ -8,7 +8,6 @@
 import java.util.concurrent.CountDownLatch;
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.atomic.AtomicInteger;
-import java.util.concurrent.atomic.AtomicIntegerArray;
 import java.util.logging.Level;
 import java.util.logging.Logger;
 import jsat.DataSet;
@@ -23,8 +22,8 @@
 import jsat.utils.FakeExecutor;
 import jsat.utils.SystemInfo;
 import jsat.utils.concurrent.AtomicDoubleArray;
+import jsat.utils.concurrent.ParallelUtils;
 import jsat.utils.random.RandomUtil;
-import jsat.utils.random.XORWOW;
 
 /**
  * An implementation of Lloyd's K-Means clustering algorithm using the 
@@ -40,13 +39,12 @@
 public class NaiveKMeans extends KMeans
 {
 
+    private static final long serialVersionUID = 6164910874898843069L;
 
-	private static final long serialVersionUID = 6164910874898843069L;
-
-	/**
-     * Creates a new naive k-Means cluster using 
-     * {@link SeedSelection#KPP k-means++} for the 
-     * seed selection and the {@link EuclideanDistance}
+    /**
+     * Creates a new naive k-Means cluster using
+     * {@link SeedSelection#KPP k-means++} for the seed selection and the
+     * {@link EuclideanDistance}
      */
     public NaiveKMeans()
     {
@@ -161,17 +159,17 @@ protected Vec[] initialValue()
             }
         };
         
+        final int N = dataSet.getSampleSize();
         Arrays.fill(assignment, -1);
         do
         {
             changes.set(0);
-            int extra = dataSet.getSampleSize() % SystemInfo.LogicalCores;
-            int start = 0;
             final CountDownLatch latch = new CountDownLatch(SystemInfo.LogicalCores);
-            while(start < dataSet.getSampleSize())
+            
+            for(int id = 0; id < SystemInfo.LogicalCores; id++)
             {
-                final int s = start;
-                final int end = start + blockSize + (extra-- > 0 ? 1 : 0);
+                final int s = ParallelUtils.getStartBlock(N, id);
+                final int end = ParallelUtils.getEndBlock(N, id);
                 threadpool.submit(new Runnable()
                 {
                     @Override
@@ -220,8 +218,6 @@ public void run()
                         latch.countDown();
                     }
                 });
-                
-                start = end;
             }
             
             try
diff --git a/JSAT/test/jsat/clustering/hierarchical/DivisiveGlobalClustererTest.java b/JSAT/test/jsat/clustering/hierarchical/DivisiveGlobalClustererTest.java
index 96d021d5..b4c53b8c 100644
--- a/JSAT/test/jsat/clustering/hierarchical/DivisiveGlobalClustererTest.java
+++ b/JSAT/test/jsat/clustering/hierarchical/DivisiveGlobalClustererTest.java
@@ -57,7 +57,7 @@ public static void tearDownClass() throws Exception
     public void setUp()
     {
         DistanceMetric dm = new EuclideanDistance();
-        dgc = new DivisiveGlobalClusterer(new HamerlyKMeans(), new DaviesBouldinIndex(dm));
+        dgc = new DivisiveGlobalClusterer(new NaiveKMeans(), new DaviesBouldinIndex(dm));
     }
     
     @After