/*
 * 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.v2;

import org.deidentifier.arx.ARXConfiguration;
import org.deidentifier.arx.certificate.elements.ElementData;
import org.deidentifier.arx.framework.check.groupify.HashGroupify;
import org.deidentifier.arx.framework.lattice.Transformation;
import org.deidentifier.arx.metric.MetricConfiguration;

/**
 * This class provides an implementation of a weighted precision metric as 
 * proposed in: <br>
 * Sweeney, L. (2002). Achieving k-anonymity privacy protection using generalization and suppression.<br> 
 * International Journal of Uncertainty Fuzziness and, 10(5), 2002.<br>
 * <br>
 * This metric will respect attribute weights defined in the configuration.
 * 
 * @author Fabian Prasser
 * @author Florian Kohlmayer
 */
public class MetricMDPrecision extends MetricMDNMPrecision {

    /** SVUID. */
    private static final long serialVersionUID = 8514706682676049814L;

    /**
     * Creates a new instance.
     */
    protected MetricMDPrecision() {
        super(true, true, true, AggregateFunction.ARITHMETIC_MEAN);
    }

    /**
     * Creates a new instance.
     *
     * @param function
     */
    protected MetricMDPrecision(AggregateFunction function){
        super(true, true, true, function);
    }
    /**
     * Creates a new instance.
     *
     * @param function
     */
    protected MetricMDPrecision(double gsFactor, AggregateFunction function){
        super(true, true, true, gsFactor, function);
    }

    /**
     * Returns the configuration of this metric.
     *
     * @return
     */
    public MetricConfiguration getConfiguration() {
        return new MetricConfiguration(true,                                      // monotonic
                                       this.getGeneralizationSuppressionFactor(), // gs-factor
                                       false,                                     // precomputed
                                       0.0d,                                      // precomputation threshold
                                       this.getAggregateFunction()                // aggregate function
                                       );
    }

    @Override
    public boolean isAbleToHandleMicroaggregation() {
        return false;
    }
    
    @Override
    public boolean isGSFactorSupported() {
        return true;
    }

    @Override
    public ElementData render(ARXConfiguration config) {
        ElementData result = new ElementData("Precision");
        result.addProperty("Aggregate function", super.getAggregateFunction().toString());
        result.addProperty("Monotonic", this.isMonotonic(config.getMaxOutliers()));
        result.addProperty("Generalization factor", this.getGeneralizationFactor());
        result.addProperty("Suppression factor", this.getSuppressionFactor());
        return result;
    }

    @Override
    public String toString() {
        return "Monotonic precision";
    }

    @Override
    protected ILMultiDimensionalWithBound getInformationLossInternal(final Transformation node, final HashGroupify g) {
        AbstractILMultiDimensional loss = super.getLowerBoundInternal(node);
        return new ILMultiDimensionalWithBound(loss, loss);
    }
}