Clean-up.

Re-name "SimpleDistanceBased" to "NonHierarchicalDistanceBased"

library/src/com/google/maps/android/clustering/ClusterManager.java

@@ -8,7 +8,7 @@
 import com.google.maps.android.MarkerManager;
 import com.google.maps.android.clustering.algo.Algorithm;
 import com.google.maps.android.clustering.algo.PreCachingDecorator;
-import com.google.maps.android.clustering.algo.SimpleDistanceBased;
+import com.google.maps.android.clustering.algo.NonHierarchicalDistanceBased;
 import com.google.maps.android.clustering.view.ClusterView;
 import com.google.maps.android.clustering.view.DefaultClusterView;
 
@@ -20,7 +20,6 @@
  */
 public class ClusterManager<T extends ClusterItem> implements GoogleMap.OnCameraChangeListener {
     private static final String TAG = ClusterManager.class.getName();
-    private static final boolean ASYNC = true;
 
     private final MarkerManager mMarkerManager;
     private final MarkerManager.Collection mMarkers;
@@ -46,7 +45,7 @@ public ClusterManager(Context context, GoogleMap map, MarkerManager markerManage
         mClusterMarkers = markerManager.newCollection();
         mMarkers = markerManager.newCollection();
         mView = new DefaultClusterView<T>(context, map, this);
-        setAlgorithm(new SimpleDistanceBased<T>());
+        setAlgorithm(new NonHierarchicalDistanceBased<T>());
         mClusterTask = new ClusterTask();
     }
 
@@ -113,12 +112,7 @@ public void removeItem(T item) {
     public void cluster() {
         mClusterTask.cancel(true);
         mClusterTask = new ClusterTask();
-        if (ASYNC) {
-            mClusterTask.execute(mMap.getCameraPosition().zoom);
-        } else {
-            Set<? extends Cluster<T>> clusters = mClusterTask.doInBackground(mMap.getCameraPosition().zoom);
-            mClusterTask.onPostExecute(clusters);
-        }
+        mClusterTask.execute(mMap.getCameraPosition().zoom);
     }
 
     /**
@@ -141,7 +135,7 @@ public void onCameraChange(CameraPosition cameraPosition) {
 
     /**
      * Runs the clustering algorithm in a background thread, then re-paints when results come
-     * back..
+     * back.
      */
     private class ClusterTask extends AsyncTask<Float, Void, Set<? extends Cluster<T>>> {
         @Override
@@ -157,12 +151,12 @@ protected void onPostExecute(Set<? extends Cluster<T>> clusters) {
     }
 
     public void setOnClusterClickListener(OnClusterClickListener<T> listener) {
-        this.mOnClusterClickListener = listener;
+        mOnClusterClickListener = listener;
         mView.setOnClusterClickListener(listener);
     }
 
     public void setOnClusterItemClickListener(OnClusterItemClickListener<T> listener) {
-        this.mOnClusterItemClickListener = listener;
+        mOnClusterItemClickListener = listener;
         mView.setOnClusterItemClickListener(listener);
     }
 

library/src/com/google/maps/android/clustering/algo/SimpleDistanceBased.java → library/src/com/google/maps/android/clustering/algo/NonHierarchicalDistanceBased.java

@@ -19,19 +19,20 @@
 import java.util.Set;
 
 /**
- * A simple clustering algorithm.
+ * A simple clustering algorithm with O(nlog n) performance. Resulting clusters are not
+ * hierarchical.
  * <p>
  * High level algorithm:
  * 1. Iterate over items in the order they were added (candidate clusters).<br>
  * 2. Create a cluster with the center of the item. <br>
  * 3. Add all items that are within a certain distance to the cluster. <br>
- * 4. Remove those items from the list of candidate clusters.
+ * 4. Move any items out of an existing cluster if they are closer to another cluster. <br>
+ * 5. Remove those items from the list of candidate clusters.
  * <p/>
- * This means that items that were added first will tend to have more items in their cluster.
  * Clusters have the center of the first element (not the centroid of the items within it).
  */
-public class SimpleDistanceBased<T extends ClusterItem> implements Algorithm<T> {
-    public static final int MAX_DISTANCE_AT_ZOOM = 100;
+public class NonHierarchicalDistanceBased<T extends ClusterItem> implements Algorithm<T> {
+    public static final int MAX_DISTANCE_AT_ZOOM = 100; // essentially 100 dp.
 
     private final LinkedHashSet<QuadItem<T>> mItems = new LinkedHashSet<QuadItem<T>>();
     private final PointQuadTree<QuadItem<T>> mQuadTree = new PointQuadTree<QuadItem<T>>(0, 1, 0, 1);
@@ -60,30 +61,33 @@ public void clearItems() {
     @Override
     public void removeItem(T item) {
         // TODO: delegate QuadItem#hashCode and QuadItem#equals to its item.
-        throw new UnsupportedOperationException("SimpleDistanceBased.remove not implemented");
+        throw new UnsupportedOperationException("NonHierarchicalDistanceBased.remove not implemented");
     }
 
     @Override
     public Set<? extends Cluster<T>> getClusters(double zoom) {
-        int discreteZoom = (int) zoom;
+        final int discreteZoom = (int) zoom;
 
-        double zoomSpecificSpan = MAX_DISTANCE_AT_ZOOM / Math.pow(2, discreteZoom) / 256;
+        final double zoomSpecificSpan = MAX_DISTANCE_AT_ZOOM / Math.pow(2, discreteZoom) / 256;
 
-        Set<QuadItem<T>> visitedCandidates = new HashSet<QuadItem<T>>();
-        HashSet<Cluster<T>> results = new HashSet<Cluster<T>>();
-        Map<QuadItem<T>, Double> distanceToCluster = new HashMap<QuadItem<T>, Double>();
-        Map<QuadItem<T>, StaticCluster<T>> itemToCluster = new HashMap<QuadItem<T>, StaticCluster<T>>();
+        final Set<QuadItem<T>> visitedCandidates = new HashSet<QuadItem<T>>();
+        final Set<Cluster<T>> results = new HashSet<Cluster<T>>();
+        final Map<QuadItem<T>, Double> distanceToCluster = new HashMap<QuadItem<T>, Double>();
+        final Map<QuadItem<T>, StaticCluster<T>> itemToCluster = new HashMap<QuadItem<T>, StaticCluster<T>>();
 
-        // TODO: Investigate use of ConcurrentSkipListSet.
         for (QuadItem<T> candidate : mItems) {
-            if (visitedCandidates.contains(candidate)) continue;
+            if (visitedCandidates.contains(candidate)) {
+                // Candidate is already part of another cluster.
+                continue;
+            }
 
             Bounds searchBounds = createBoundsFromSpan(candidate.getPoint(), zoomSpecificSpan);
             Collection<QuadItem<T>> clusterItems = mQuadTree.search(searchBounds);
             if (clusterItems.size() == 1) {
-                // Only the current market is in range.
+                // Only the current marker is in range. Just add the single item to the results.
                 results.add(candidate);
                 visitedCandidates.add(candidate);
+                distanceToCluster.put(candidate, 0d);
                 continue;
             }
             StaticCluster<T> cluster = new StaticCluster<T>(candidate.mClusterItem.getPosition());
@@ -97,6 +101,7 @@ public Set<? extends Cluster<T>> getClusters(double zoom) {
                     if (existingDistance < distance) {
                         continue;
                     }
+                    // Move item to the closer cluster.
                     itemToCluster.get(clusterItem).remove(clusterItem.mClusterItem);
                 }
                 distanceToCluster.put(clusterItem, distance);
@@ -122,6 +127,8 @@ private double distanceSquared(Point a, Point b) {
     }
 
     private Bounds createBoundsFromSpan(Point p, double span) {
+        // TODO: Use a span that takes into account the visual size of the marker, not just its
+        // LatLng.
         double halfSpan = span / 2;
         return new Bounds(
                 p.x - halfSpan, p.x + halfSpan,

library/src/com/google/maps/android/quadtree/PointQuadTree.java

@@ -28,7 +28,6 @@
  * See http://en.wikipedia.org/wiki/Quadtree for details on the data structure.
  * This class is not thread safe.
  */
-@Deprecated // Experimental.
 public class PointQuadTree<T extends PointQuadTree.Item> {
     public interface Item {
         Point getPoint();
@@ -62,7 +61,7 @@ public interface Item {
     /**
      * Child quads.
      */
-    private PointQuadTree[] mChildren = null;
+    private PointQuadTree<T>[] mChildren = null;
 
     /**
      * Creates a new quad tree with specified bounds.
@@ -125,10 +124,10 @@ private boolean insert(double x, double y, T item) {
      */
     private void split() {
         mChildren = new PointQuadTree[]{
-                new PointQuadTree(mBounds.minX, mBounds.midX, mBounds.minY, mBounds.midY, mDepth + 1),
-                new PointQuadTree(mBounds.midX, mBounds.maxX, mBounds.minY, mBounds.midY, mDepth + 1),
-                new PointQuadTree(mBounds.minX, mBounds.midX, mBounds.midY, mBounds.maxY, mDepth + 1),
-                new PointQuadTree(mBounds.midX, mBounds.maxX, mBounds.midY, mBounds.maxY, mDepth + 1)
+                new PointQuadTree<T>(mBounds.minX, mBounds.midX, mBounds.minY, mBounds.midY, mDepth + 1),
+                new PointQuadTree<T>(mBounds.midX, mBounds.maxX, mBounds.minY, mBounds.midY, mDepth + 1),
+                new PointQuadTree<T>(mBounds.minX, mBounds.midX, mBounds.midY, mBounds.maxY, mDepth + 1),
+                new PointQuadTree<T>(mBounds.midX, mBounds.maxX, mBounds.midY, mBounds.maxY, mDepth + 1)
         };
 
         List<T> items = mItems;