diff options
Diffstat (limited to 'src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java')
| -rw-r--r-- | src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java | 28 |
1 files changed, 14 insertions, 14 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java b/src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java index 73462c2f..4a36036a 100644 --- a/src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java +++ b/src/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAFilteredAutotuningRunner.java @@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.math.linearalgebra.pca; This file is part of ELKI: Environment for Developing KDD-Applications Supported by Index-Structures - Copyright (C) 2012 + Copyright (C) 2013 Ludwig-Maximilians-Universität München Lehr- und Forschungseinheit für Datenbanksysteme ELKI Development Team @@ -30,13 +30,13 @@ import java.util.List; import de.lmu.ifi.dbs.elki.data.NumberVector; import de.lmu.ifi.dbs.elki.database.ids.DBIDIter; import de.lmu.ifi.dbs.elki.database.ids.DBIDs; +import de.lmu.ifi.dbs.elki.database.ids.distance.DistanceDBIDList; +import de.lmu.ifi.dbs.elki.database.ids.distance.DistanceDBIDListIter; +import de.lmu.ifi.dbs.elki.database.ids.distance.DoubleDistanceDBIDPairList; +import de.lmu.ifi.dbs.elki.database.ids.distance.ModifiableDistanceDBIDList; import de.lmu.ifi.dbs.elki.database.relation.Relation; import de.lmu.ifi.dbs.elki.database.relation.RelationUtil; -import de.lmu.ifi.dbs.elki.distance.distancefunction.EuclideanDistanceFunction; -import de.lmu.ifi.dbs.elki.distance.distanceresultlist.DistanceDBIDResult; -import de.lmu.ifi.dbs.elki.distance.distanceresultlist.DistanceDBIDResultIter; -import de.lmu.ifi.dbs.elki.distance.distanceresultlist.DoubleDistanceDBIDList; -import de.lmu.ifi.dbs.elki.distance.distanceresultlist.ModifiableDistanceDBIDResult; +import de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction; import de.lmu.ifi.dbs.elki.distance.distancevalue.NumberDistance; import de.lmu.ifi.dbs.elki.logging.LoggingUtil; import de.lmu.ifi.dbs.elki.math.linearalgebra.Centroid; @@ -76,7 +76,7 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF // Assume Euclidean distance. In the context of PCA, the neighborhood should // be L2-spherical to be unbiased. V center = Centroid.make(database, ids).toVector(database); - DoubleDistanceDBIDList dres = new DoubleDistanceDBIDList(ids.size()); + DoubleDistanceDBIDPairList dres = new DoubleDistanceDBIDPairList(ids.size()); for (DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { final double dist = EuclideanDistanceFunction.STATIC.doubleDistance(center, database.get(iter)); dres.add(dist, iter); @@ -117,11 +117,11 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF } @Override - public <D extends NumberDistance<D, ?>> PCAFilteredResult processQueryResult(DistanceDBIDResult<D> results, Relation<? extends V> database) { + public <D extends NumberDistance<D, ?>> PCAFilteredResult processQueryResult(DistanceDBIDList<D> results, Relation<? extends V> database) { assertSortedByDistance(results); final int dim = RelationUtil.dimensionality(database); - List<Matrix> best = new LinkedList<Matrix>(); + List<Matrix> best = new LinkedList<>(); for (int i = 0; i < dim; i++) { best.add(null); } @@ -131,7 +131,7 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF } int[] bestk = new int[dim]; // 'history' - LinkedList<Cand> prev = new LinkedList<Cand>(); + LinkedList<Cand> prev = new LinkedList<>(); // TODO: starting parameter shouldn't be hardcoded... int smooth = 3; int startk = 4; @@ -227,11 +227,11 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF * @param results Results to process * @param <D> distance type */ - private <D extends NumberDistance<D, ?>> void assertSortedByDistance(DistanceDBIDResult<D> results) { + private <D extends NumberDistance<D, ?>> void assertSortedByDistance(DistanceDBIDList<D> results) { // TODO: sort results instead? double dist = -1.0; boolean sorted = true; - for (DistanceDBIDResultIter<D> it = results.iter(); it.valid(); it.advance()) { + for (DistanceDBIDListIter<D> it = results.iter(); it.valid(); it.advance()) { double qr = it.getDistance().doubleValue(); if (qr < dist) { sorted = false; @@ -240,7 +240,7 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF } if (!sorted) { try { - ModifiableDistanceDBIDResult.class.cast(results).sort(); + ModifiableDistanceDBIDList.class.cast(results).sort(); } catch (ClassCastException e) { LoggingUtil.warning("WARNING: results not sorted by distance!", e); } catch (UnsupportedOperationException e) { @@ -259,7 +259,7 @@ public class PCAFilteredAutotuningRunner<V extends NumberVector<?>> extends PCAF public static class Parameterizer<V extends NumberVector<?>> extends PCAFilteredRunner.Parameterizer<V> { @Override protected PCAFilteredAutotuningRunner<V> makeInstance() { - return new PCAFilteredAutotuningRunner<V>(covarianceMatrixBuilder, eigenPairFilter, big, small); + return new PCAFilteredAutotuningRunner<>(covarianceMatrixBuilder, eigenPairFilter, big, small); } } } |