/*
* ARX: Powerful Data Anonymization
* Copyright 2012 - 2017 Fabian Prasser, Florian Kohlmayer and contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.deidentifier.arx.metric;
import org.deidentifier.arx.ARXConfiguration;
import org.deidentifier.arx.DataDefinition;
import org.deidentifier.arx.certificate.elements.ElementData;
import org.deidentifier.arx.framework.check.groupify.HashGroupify;
import org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry;
import org.deidentifier.arx.framework.data.Data;
import org.deidentifier.arx.framework.data.DataManager;
import org.deidentifier.arx.framework.data.GeneralizationHierarchy;
import org.deidentifier.arx.framework.lattice.Transformation;
/**
* This class provides an implementation of a monotonic weighted precision metric.
* This metric will respect attribute weights defined in the configuration.
*
* @author Fabian Prasser
* @author Florian Kohlmayer
*/
public class MetricPrecision extends MetricWeighted<InformationLossDefault> {
/** SVUID. */
private static final long serialVersionUID = -7612335677779934529L;
/** Height. */
private int[] maxLevels;
/**
* Creates a new instance.
*/
protected MetricPrecision() {
super(true, true, true);
}
@Override
public InformationLoss<?> createMaxInformationLoss() {
return new InformationLossDefault(1d);
}
@Override
public InformationLoss<?> createMinInformationLoss() {
return new InformationLossDefault(0d);
}
@Override
public ElementData render(ARXConfiguration config) {
ElementData result = new ElementData("Precision");
result.addProperty("Monotonic", this.isMonotonic(config.getMaxOutliers()));
return result;
}
@Override
public String toString() {
return "Monotonic Precision";
}
/**
* Returns the number of cells.
*
* @return
*/
protected double getCells() {
return 0d;
}
/**
* @return the heights
*/
protected int[] getHeights() {
return maxLevels;
}
@Override
protected InformationLossWithBound<InformationLossDefault> getInformationLossInternal(final Transformation node, final HashGroupify g) {
double result = 0;
final int[] transformation = node.getGeneralization();
for (int i = 0; i < transformation.length; i++) {
double weight = weights != null ? weights[i] : 1d;
double level = (double) transformation[i];
result += maxLevels[i] == 0 ? 0 : (level / (double) maxLevels[i]) * weight;
}
result /= (double) transformation.length;
return new InformationLossDefaultWithBound(result, result);
}
@Override
protected InformationLossWithBound<InformationLossDefault> getInformationLossInternal(Transformation node, HashGroupifyEntry entry) {
return new InformationLossDefaultWithBound(entry.count, entry.count);
}
@Override
protected InformationLossDefault getLowerBoundInternal(Transformation node) {
return this.getInformationLossInternal(node, (HashGroupify)null).getLowerBound();
}
@Override
protected InformationLossDefault getLowerBoundInternal(Transformation node,
HashGroupify groupify) {
return getLowerBoundInternal(node);
}
@Override
protected void initializeInternal(final DataManager manager,
final DataDefinition definition,
final Data input,
final GeneralizationHierarchy[] hierarchies,
final ARXConfiguration config) {
super.initializeInternal(manager, definition, input, hierarchies, config);
// Initialize maximum levels
maxLevels = new int[hierarchies.length];
for (int j = 0; j < maxLevels.length; j++) {
maxLevels[j] = hierarchies[j].getArray()[0].length - 1;
}
}
}