/* * 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; } } }