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Diffstat (limited to 'src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/IntegerRankTieNormalization.java')
| -rw-r--r-- | src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/IntegerRankTieNormalization.java | 150 |
1 files changed, 150 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/IntegerRankTieNormalization.java b/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/IntegerRankTieNormalization.java new file mode 100644 index 00000000..ca320ec6 --- /dev/null +++ b/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/IntegerRankTieNormalization.java @@ -0,0 +1,150 @@ +package de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise; + +/* + 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 java.util.ArrayList; +import java.util.List; + +import de.lmu.ifi.dbs.elki.data.IntegerVector; +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.datasource.bundle.MultipleObjectsBundle; +import de.lmu.ifi.dbs.elki.datasource.filter.ObjectFilter; +import de.lmu.ifi.dbs.elki.utilities.Alias; +import de.lmu.ifi.dbs.elki.utilities.datastructures.arrays.IntegerArrayQuickSort; +import de.lmu.ifi.dbs.elki.utilities.datastructures.arrays.IntegerComparator; + +/** + * Normalize vectors according to their rank in the attributes. + * + * Note: <b>ranks are multiplied by 2</b>, to be able to give ties an integer + * rank. (e.g. when the first two records are tied, they both have rank "1" + * then, followed by the next on "4") + * + * @author Erich Schubert + */ +@Alias({ "de.lmu.ifi.dbs.elki.datasource.filter.normalization.IntegerRankTieNormalization"}) +public class IntegerRankTieNormalization implements ObjectFilter { + /** + * Constructor. + */ + public IntegerRankTieNormalization() { + super(); + } + + @Override + public MultipleObjectsBundle filter(MultipleObjectsBundle objects) { + final int len = objects.dataLength(); + MultipleObjectsBundle bundle = new MultipleObjectsBundle(); + + int[] order = new int[len]; + for(int i = 0; i < len; i++) { + order[i] = i; + } + Sorter comparator = new Sorter(); + + for(int r = 0; r < objects.metaLength(); r++) { + final SimpleTypeInformation<?> type = objects.meta(r); + final List<?> column = objects.getColumn(r); + if(!TypeUtil.NUMBER_VECTOR_FIELD.isAssignableFromType(type)) { + bundle.appendColumn(type, column); + continue; + } + @SuppressWarnings("unchecked") + final List<? extends NumberVector> castColumn = (List<? extends NumberVector>) column; + // Get the replacement type information + final int dim = ((VectorFieldTypeInformation<?>) type).getDimensionality(); + final VectorFieldTypeInformation<IntegerVector> outType = new VectorFieldTypeInformation<>(IntegerVector.STATIC, dim); + + // Output vectors + int[][] posvecs = new int[len][dim]; + // Sort for each dimension + for(int d = 0; d < dim; d++) { + // Sort + comparator.setup(castColumn, d); + IntegerArrayQuickSort.sort(order, comparator); + // Transfer positions to output vectors + for(int sta = 0; sta < order.length;) { + double v = castColumn.get(order[sta]).doubleValue(d); + // Compute ties + int end = sta + 1; + while(end < order.length && !(v < castColumn.get(order[end]).doubleValue(d))) { + end++; + } + final int pos = (sta + end - 1); + for(int i = sta; i < end; i++) { + posvecs[order[i]][d] = pos; + } + sta = end; + } + } + + // Prepare output data + final List<IntegerVector> outColumn = new ArrayList<>(len); + for(int i = 0; i < len; i++) { + outColumn.add(new IntegerVector(posvecs[i])); + } + bundle.appendColumn(outType, outColumn); + } + return bundle; + } + + /** + * Class to sort an index array by a particular dimension. + * + * @author Erich Schubert + * + * @apiviz.exclude + */ + private static class Sorter implements IntegerComparator { + /** + * Column to use for sorting. + */ + List<? extends NumberVector> col; + + /** + * Dimension to use for sorting. + */ + int dim; + + /** + * Configure the sorting class. + * + * @param col Column to read + * @param dim Dimension to use. + */ + public void setup(List<? extends NumberVector> col, int dim) { + this.col = col; + this.dim = dim; + } + + @Override + public int compare(int x, int y) { + final double vx = col.get(x).doubleValue(dim), vy = col.get(y).doubleValue(dim); + return (vx < vy) ? -1 : (vx == vy) ? 0 : +1; + } + } +}
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