1 files changed, 219 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/datasource/filter/cleaning/VectorDimensionalityFilter.java b/src/de/lmu/ifi/dbs/elki/datasource/filter/cleaning/VectorDimensionalityFilter.java
new file mode 100644
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+++ b/src/de/lmu/ifi/dbs/elki/datasource/filter/cleaning/VectorDimensionalityFilter.java
@@ -0,0 +1,219 @@
+package de.lmu.ifi.dbs.elki.datasource.filter.cleaning;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2014
+ Ludwig-Maximilians-Universität München
+ Lehr- und Forschungseinheit für Datenbanksysteme
+ ELKI Development Team
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU Affero General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ GNU Affero General Public License for more details.
+
+ You should have received a copy of the GNU Affero General Public License
+ along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+import de.lmu.ifi.dbs.elki.data.NumberVector;
+import de.lmu.ifi.dbs.elki.data.type.SimpleTypeInformation;
+import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
+import de.lmu.ifi.dbs.elki.data.type.VectorFieldTypeInformation;
+import de.lmu.ifi.dbs.elki.data.type.VectorTypeInformation;
+import de.lmu.ifi.dbs.elki.datasource.bundle.BundleMeta;
+import de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamFilter;
+import de.lmu.ifi.dbs.elki.datasource.filter.FilterUtil;
+import de.lmu.ifi.dbs.elki.logging.Logging;
+import de.lmu.ifi.dbs.elki.utilities.Alias;
+import de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.IntParameter;
+
+/**
+ * Filter to remove all vectors that do not have the desired dimensionality.
+ * 
+ * @author Erich Schubert
+ * 
+ * @param <V> Vector type
+ */
+@Alias({ "de.lmu.ifi.dbs.elki.datasource.filter.normalization.VectorDimensionalityFilter" })
+public class VectorDimensionalityFilter<V extends NumberVector> extends AbstractStreamFilter {
+  /**
+   * Class logger.
+   */
+  private static final Logging LOG = Logging.getLogger(VectorDimensionalityFilter.class);
+
+  /**
+   * The filtered meta.
+   */
+  BundleMeta meta;
+
+  /**
+   * The column to filter.
+   */
+  int column = -1;
+
+  /**
+   * Desired dimensionality.
+   */
+  int dim = -1;
+
+  /**
+   * Constructor.
+   * 
+   * @param dim Dimensionality to enforce (use -1 to use the dimensionality of
+   *        the first vector in the data set)
+   */
+  public VectorDimensionalityFilter(int dim) {
+    super();
+    this.dim = dim;
+  }
+
+  @Override
+  public BundleMeta getMeta() {
+    if(meta == null) {
+      updateMeta();
+    }
+    return source.getMeta();
+  }
+
+  @Override
+  public Object data(int rnum) {
+    return source.data(rnum);
+  }
+
+  @Override
+  public Event nextEvent() {
+    while(true) {
+      Event ev = source.nextEvent();
+      switch(ev){
+      case END_OF_STREAM:
+        return ev;
+      case META_CHANGED:
+        meta = null;
+        return ev;
+      case NEXT_OBJECT:
+        if(meta == null) {
+          updateMeta();
+        }
+        if(column >= 0 && dim >= 0) {
+          @SuppressWarnings("unchecked")
+          V vec = (V) source.data(column);
+          if(vec == null) {
+            if(LOG.isVeryVerbose()) {
+              LOG.veryverbose("Skipping null vector.");
+            }
+            continue;
+          }
+          if(vec.getDimensionality() != dim) {
+            if(LOG.isVeryVerbose()) {
+              StringBuilder buf = new StringBuilder();
+              buf.append("Skipping vector of wrong dimensionality ");
+              buf.append(vec.getDimensionality());
+              buf.append(':');
+              for(int i = 0; i < meta.size(); i++) {
+                buf.append(' ');
+                buf.append(source.data(i));
+              }
+              LOG.veryverbose(buf.toString());
+            }
+            continue;
+          }
+        }
+        return ev;
+      }
+    }
+  }
+
+  /**
+   * Update metadata.
+   */
+  private void updateMeta() {
+    meta = new BundleMeta();
+    BundleMeta origmeta = source.getMeta();
+    for(int i = 0; i < origmeta.size(); i++) {
+      SimpleTypeInformation<?> type = origmeta.get(i);
+      if(column < 0) {
+        // Test whether this type matches
+        if(TypeUtil.NUMBER_VECTOR_VARIABLE_LENGTH.isAssignableFromType(type)) {
+          if(type instanceof VectorFieldTypeInformation) {
+            @SuppressWarnings("unchecked")
+            final VectorFieldTypeInformation<V> castType = (VectorFieldTypeInformation<V>) type;
+            if(dim != -1 && castType.mindim() > dim) {
+              throw new AbortException("Would filter all vectors: minimum dimensionality " + castType.mindim() + " > desired dimensionality " + dim);
+            }
+            if(dim != -1 && castType.maxdim() < dim) {
+              throw new AbortException("Would filter all vectors: maximum dimensionality " + castType.maxdim() + " < desired dimensionality " + dim);
+            }
+            if(dim == -1) {
+              dim = castType.mindim();
+            }
+            if(castType.mindim() == castType.maxdim()) {
+              meta.add(castType);
+              column = i;
+              continue;
+            }
+          }
+          @SuppressWarnings("unchecked")
+          final VectorTypeInformation<V> castType = (VectorTypeInformation<V>) type;
+          if(dim != -1) {
+            meta.add(new VectorFieldTypeInformation<>(FilterUtil.guessFactory(castType), dim, dim, castType.getSerializer()));
+          }
+          else {
+            LOG.warning("No dimensionality yet for column " + i);
+            meta.add(castType);
+          }
+          column = i;
+          continue;
+        }
+      }
+      meta.add(type);
+    }
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   * 
+   * @param <V> Vector type
+   */
+  public static class Parameterizer<V extends NumberVector> extends AbstractParameterizer {
+    /**
+     * Parameter for specifying the dimensionality.
+     */
+    private static final OptionID DIM_P = new OptionID("filter.dim", "Dimensionality of vectors to retain.");
+
+    /**
+     * Desired dimensionality.
+     */
+    int dim = -1;
+
+    @Override
+    protected void makeOptions(Parameterization config) {
+      super.makeOptions(config);
+      IntParameter dimP = new IntParameter(DIM_P)//
+      .setOptional(true)//
+      .addConstraint(CommonConstraints.GREATER_EQUAL_ONE_INT);
+      dim = config.grab(dimP) ? dimP.intValue() : -1;
+    }
+
+    @Override
+    protected VectorDimensionalityFilter<V> makeInstance() {
+      return new VectorDimensionalityFilter<>(dim);
+    }
+  }
+}