1 files changed, 51 insertions, 17 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/index/preprocessed/knn/AbstractMaterializeKNNPreprocessor.java b/src/de/lmu/ifi/dbs/elki/index/preprocessed/knn/AbstractMaterializeKNNPreprocessor.java
index 0579262b..b9b72d87 100644
--- a/src/de/lmu/ifi/dbs/elki/index/preprocessed/knn/AbstractMaterializeKNNPreprocessor.java
+++ b/src/de/lmu/ifi/dbs/elki/index/preprocessed/knn/AbstractMaterializeKNNPreprocessor.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.index.preprocessed.knn;
  This file is part of ELKI:
  Environment for Developing KDD-Applications Supported by Index-Structures
 
- Copyright (C) 2011
+ Copyright (C) 2012
  Ludwig-Maximilians-Universität München
  Lehr- und Forschungseinheit für Datenbanksysteme
  ELKI Development Team
@@ -23,14 +23,15 @@ package de.lmu.ifi.dbs.elki.index.preprocessed.knn;
  along with this program.  If not, see <http://www.gnu.org/licenses/>.
  */
 
-import java.util.List;
-
-import javax.swing.event.EventListenerList;
-
 import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
-import de.lmu.ifi.dbs.elki.database.query.DistanceResultPair;
+import de.lmu.ifi.dbs.elki.database.datastore.DataStoreFactory;
+import de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil;
+import de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore;
+import de.lmu.ifi.dbs.elki.database.ids.DBID;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
 import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
 import de.lmu.ifi.dbs.elki.database.query.knn.KNNQuery;
+import de.lmu.ifi.dbs.elki.database.query.knn.KNNResult;
 import de.lmu.ifi.dbs.elki.database.query.knn.PreprocessorKNNQuery;
 import de.lmu.ifi.dbs.elki.database.relation.Relation;
 import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
@@ -54,7 +55,7 @@ import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ObjectParameter;
  * @param <O> Object type
  * @param <D> Distance type
  */
-public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D>> extends AbstractPreprocessorIndex<O, List<DistanceResultPair<D>>> implements KNNIndex<O> {
+public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D>, T extends KNNResult<D>> extends AbstractPreprocessorIndex<O, T> implements KNNIndex<O> {
   /**
    * The query k value.
    */
@@ -71,11 +72,6 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
   protected final DistanceQuery<O, D> distanceQuery;
 
   /**
-   * Holds the listener.
-   */
-  protected final EventListenerList listenerList = new EventListenerList();
-
-  /**
    * Constructor.
    * 
    * @param relation Relation
@@ -121,6 +117,42 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
    */
   protected abstract void preprocess();
 
+  /**
+   * Get the k nearest neighbors.
+   * 
+   * @param objid Object ID
+   * @return Neighbors
+   */
+  public KNNResult<D> get(DBID objid) {
+    if(storage == null) {
+      if(getLogger().isDebugging()) {
+        getLogger().debug("Running kNN preprocessor: " + this.getClass());
+      }
+      preprocess();
+    }
+    return storage.get(objid);
+  }
+
+  /**
+   * Create the default storage.
+   */
+  void createStorage() {
+    WritableDataStore<T> s = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT, KNNResult.class);
+    storage = s;
+  }
+
+  @Override
+  public void insertAll(DBIDs ids) {
+    if(storage == null) {
+      if(ids.size() > 0) {
+        preprocess();
+      }
+    }
+    else {
+      throw new UnsupportedOperationException("Preprocessor already ran.");
+    }
+  }
+
   @SuppressWarnings("unchecked")
   @Override
   public <S extends Distance<S>> KNNQuery<O, S> getKNNQuery(DistanceQuery<O, S> distanceQuery, Object... hints) {
@@ -136,7 +168,9 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
         break;
       }
     }
-    return new PreprocessorKNNQuery<O, S>(relation, (MaterializeKNNPreprocessor<O, S>) this);
+    // To make compilers happy:
+    AbstractMaterializeKNNPreprocessor<?, ?, ?> tmp = this;
+    return new PreprocessorKNNQuery<O, S, KNNResult<S>>(relation, (AbstractMaterializeKNNPreprocessor<O, S, KNNResult<S>>) tmp);
   }
 
   /**
@@ -151,7 +185,7 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
    * @param <O> The object type
    * @param <D> The distance type
    */
-  public static abstract class Factory<O, D extends Distance<D>> implements IndexFactory<O, KNNIndex<O>> {
+  public static abstract class Factory<O, D extends Distance<D>, T extends KNNResult<D>> implements IndexFactory<O, KNNIndex<O>> {
     /**
      * Parameter to specify the number of nearest neighbors of an object to be
      * materialized. must be an integer greater than 1.
@@ -197,7 +231,7 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
     }
 
     @Override
-    abstract public AbstractMaterializeKNNPreprocessor<O, D> instantiate(Relation<O> relation);
+    abstract public AbstractMaterializeKNNPreprocessor<O, D, T> instantiate(Relation<O> relation);
 
     /**
      * Get the distance function.
@@ -217,7 +251,7 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
     public D getDistanceFactory() {
       return distanceFunction.getDistanceFactory();
     }
-    
+
     @Override
     public TypeInformation getInputTypeRestriction() {
       return distanceFunction.getInputTypeRestriction();
@@ -258,7 +292,7 @@ public abstract class AbstractMaterializeKNNPreprocessor<O, D extends Distance<D
       }
 
       @Override
-      abstract protected Factory<O, D> makeInstance();
+      abstract protected Factory<O, D, ?> makeInstance();
     }
   }
 }
\ No newline at end of file