/*
* 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 the (normalized) average equivalence class size metric.
* We dont normailze the metric as proposed in the original publication [1], as this would only be possible for k-anonymity.
* [1] LeFevre K, DeWitt DJ, Ramakrishnan R. Mondrian Multidimensional K-Anonymity. IEEE; 2006:25-25.
*
* @author Fabian Prasser
* @author Florian Kohlmayer
*/
public class MetricAECS extends MetricDefault {
/** TODO */
private static final long serialVersionUID = -532478849890959974L;
/** Number of tuples. */
private double rowCount = 0;
/**
* Creates a new instance
*/
protected MetricAECS() {
super(true, false, false);
}
@Override
public InformationLoss<?> createMaxInformationLoss() {
if (rowCount == 0) {
throw new IllegalStateException("Metric must be initialized first");
} else {
return new InformationLossDefault(rowCount);
}
}
@Override
public InformationLoss<?> createMinInformationLoss() {
return new InformationLossDefault(1);
}
@Override
public ElementData render(ARXConfiguration config) {
ElementData result = new ElementData("Average equivalence class size");
result.addProperty("Monotonic", this.isMonotonic(config.getMaxOutliers()));
return result;
}
@Override
public String toString() {
return "Average Equivalence Class Size";
}
@Override
protected InformationLossWithBound<InformationLossDefault> getInformationLossInternal(final Transformation node, final HashGroupify g) {
// The total number of groups with suppression
int groupsWithSuppression = 0;
// The total number of groups without suppression
int groupsWithoutSuppression = 0;
// The total number of tuples
int tuples = 0;
// Are there suppressed tuples
boolean suppressed = false;
HashGroupifyEntry m = g.getFirstEquivalenceClass();
while (m != null) {
if (m.count > 0) {
tuples += m.count;
groupsWithSuppression += m.isNotOutlier ? 1 : 0;
groupsWithoutSuppression++;
suppressed |= !m.isNotOutlier;
}
m = m.nextOrdered;
}
// If there are suppressed tuples, they form one additional group
groupsWithSuppression += suppressed ? 1 : 0;
// Compute AECS
return new InformationLossDefaultWithBound((double)tuples / (double)groupsWithSuppression,
(double)tuples / (double)groupsWithoutSuppression);
}
@Override
protected InformationLossWithBound<InformationLossDefault> getInformationLossInternal(Transformation node, HashGroupifyEntry entry) {
return new InformationLossDefaultWithBound(entry.count, entry.count);
}
@Override
protected InformationLossDefault getLowerBoundInternal(Transformation node) {
return null;
}
@Override
protected InformationLossDefault getLowerBoundInternal(Transformation node,
HashGroupify groupify) {
// The total number of tuples
int tuples = 0;
int groups = 0;
HashGroupifyEntry m = groupify.getFirstEquivalenceClass();
while (m != null) {
if (m.count > 0) {
tuples += m.count;
groups++;
}
m = m.nextOrdered;
}
// Compute AECS
return new InformationLossDefault((double)tuples / (double)groups);
}
/**
* Returns the row count.
*
* @return
*/
protected double getRowCount() {
return rowCount;
}
@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);
rowCount = (double)super.getNumRecords(config, input);
}
}