package de.lmu.ifi.dbs.elki.datasource.filter.normalization;
/*
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 .
*/
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.logging.Logging;
import de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution;
/**
* Attribute-wise Normalization using the error function. This mostly makes
* sense when you have data that has been mean-variance normalized before.
*
* @author Erich Schubert
*
* @param Object type
*
* @apiviz.uses NumberVector
*/
public class AttributeWiseErfNormalization> extends AbstractNormalization {
/**
* Class logger.
*/
private static final Logging LOG = Logging.getLogger(AttributeWiseErfNormalization.class);
/**
* Constructor.
*/
public AttributeWiseErfNormalization() {
super();
}
@Override
public O restore(O featureVector) {
throw new UnsupportedOperationException("Not implemented yet.");
}
@Override
protected O filterSingleObject(O obj) {
double[] val = new double[obj.getDimensionality()];
for (int i = 0; i < val.length; i++) {
val[i] = NormalDistribution.erf(obj.doubleValue(i));
}
return factory.newNumberVector(val);
}
@Override
protected SimpleTypeInformation super O> getInputTypeRestriction() {
return TypeUtil.NUMBER_VECTOR_FIELD;
}
@Override
protected Logging getLogger() {
return LOG;
}
}