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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) 2013
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.List;
import de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs;
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.parameterization.Parameterization;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ObjectListParameter;
/**
* The <code>CompositeEigenPairFilter</code> can be used to build a chain of
* eigenpair filters.
*
* @author Elke Achtert
*/
// todo parameter comments
public class CompositeEigenPairFilter implements EigenPairFilter {
/**
* The list of filters to use.
*/
public static final OptionID EIGENPAIR_FILTER_COMPOSITE_LIST = new OptionID("pca.filter.composite.list", "A comma separated list of the class names of the filters to be used. " + "The specified filters will be applied sequentially in the given order.");
/**
* The filters to be applied.
*/
private List<EigenPairFilter> filters;
/**
* Constructor.
*
* @param filters Filters to use.
*/
public CompositeEigenPairFilter(List<EigenPairFilter> filters) {
super();
this.filters = filters;
}
/**
* Filters the specified eigenpairs into strong and weak eigenpairs, where
* strong eigenpairs having high variances and weak eigenpairs having small
* variances.
*
* @param eigenPairs the eigenPairs (i.e. the eigenvectors and
* @return the filtered eigenpairs
*/
@Override
public FilteredEigenPairs filter(SortedEigenPairs eigenPairs) {
FilteredEigenPairs result = null;
for(EigenPairFilter f : filters) {
result = f.filter(eigenPairs);
eigenPairs = new SortedEigenPairs(result.getStrongEigenPairs());
}
return result;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
/**
* The filters to be applied.
*/
private List<EigenPairFilter> filters = null;
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
ObjectListParameter<EigenPairFilter> filtersP = new ObjectListParameter<>(EIGENPAIR_FILTER_COMPOSITE_LIST, EigenPairFilter.class);
if(config.grab(filtersP)) {
filters = filtersP.instantiateClasses(config);
}
}
@Override
protected CompositeEigenPairFilter makeInstance() {
return new CompositeEigenPairFilter(filters);
}
}
}
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