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package de.lmu.ifi.dbs.elki.math.dimensionsimilarity;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2015
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.database.ids.DBIDs;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
/**
* Class to compute the dimension similarity based on covariances.
*
* @author Erich Schubert
*/
public class CovarianceDimensionSimilarity implements DimensionSimilarity<NumberVector> {
/**
* Static instance
*/
public static final CovarianceDimensionSimilarity STATIC = new CovarianceDimensionSimilarity();
/**
* Constructor. Use static instance.
*/
protected CovarianceDimensionSimilarity() {
super();
}
@Override
public void computeDimensionSimilarites(Relation<? extends NumberVector> relation, DBIDs subset, DimensionSimilarityMatrix matrix) {
final int dim = matrix.size();
// FIXME: Use only necessary dimensions!
CovarianceMatrix covmat = CovarianceMatrix.make(relation, subset);
double[][] mat = covmat.destroyToSampleMatrix().getArrayRef();
// Transform diagonal to 1 / stddev
for (int i = 0; i < mat.length; i++) {
mat[i][i] = 1. / Math.sqrt(mat[i][i]);
}
// Fill output matrix:
for (int x = 0; x < dim; x++) {
final int i = matrix.dim(x);
for (int y = x + 1; y < dim; y++) {
final int j = matrix.dim(y);
matrix.set(x, y, mat[i][j] * mat[i][i] * mat[j][j]);
}
}
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
@Override
protected CovarianceDimensionSimilarity makeInstance() {
return STATIC;
}
}
}
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