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Facilities for evaluating recommender algorithms.
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/*
 * LensKit, an open source recommender systems toolkit.
 * Copyright 2010-2014 LensKit Contributors.  See CONTRIBUTORS.md.
 * Work on LensKit has been funded by the National Science Foundation under
 * grants IIS 05-34939, 08-08692, 08-12148, and 10-17697.
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1 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 General Public License for more
 * details.
 *
 * You should have received a copy of the GNU General Public License along with
 * this program; if not, write to the Free Software Foundation, Inc., 51
 * Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
 */
package org.grouplens.lenskit.eval.traintest;

import com.google.common.collect.Lists;
import org.grouplens.lenskit.Recommender;
import org.grouplens.lenskit.data.event.Event;
import org.grouplens.lenskit.data.event.Ratings;
import org.grouplens.lenskit.data.history.History;
import org.grouplens.lenskit.data.history.UserHistory;
import org.grouplens.lenskit.eval.metrics.topn.ItemSelector;
import org.grouplens.lenskit.scored.ScoredId;
import org.grouplens.lenskit.vectors.SparseVector;

import javax.annotation.Nullable;
import java.util.List;

/**
 * @author GroupLens Research
 */
public class MockTestUser extends AbstractTestUser {
    private final UserHistory trainHistory;
    private final UserHistory testHistory;
    private final SparseVector predictions;
    private final List recommendations;
    private final Recommender recommender;

    public MockTestUser(UserHistory train, UserHistory test,
                        SparseVector preds, List recs, Recommender rec) {
        trainHistory = train;
        testHistory = test;
        predictions = preds;
        recommendations = recs;
        recommender = rec;
    }

    @Override
    public UserHistory getTrainHistory() {
        return trainHistory;
    }

    @Override
    public UserHistory getTestHistory() {
        return testHistory;
    }

    @Nullable
    @Override
    public SparseVector getPredictions() {
        return predictions;
    }

    @Nullable
    @Override
    public List getRecommendations(int n, ItemSelector candSel, ItemSelector exclSel) {
        return recommendations;
    }

    @Nullable
    @Override
    public Recommender getRecommender() {
        return recommender;
    }

    public static Builder newBuilder() {
        return new Builder();
    }

    public static class Builder {
        private long userId;
        private List trainEvents = Lists.newArrayList();
        private List testEvents = Lists.newArrayList();
        private SparseVector predictions;
        private List recommendations;
        private Recommender recommender;

        public Builder setUserId(long uid) {
            userId = uid;
            return this;
        }

        public Builder addTrainEvent(Event evt) {
            trainEvents.add(evt);
            return this;
        }

        public Builder addTrainRating(long item, double value) {
            return addTrainEvent(Ratings.make(userId, item, value));
        }

        public Builder addTestEvent(Event evt) {
            testEvents.add(evt);
            return this;
        }

        public Builder addTestRating(long item, double value) {
            return addTestEvent(Ratings.make(userId, item, value));
        }

        public SparseVector getPredictions() {
            return predictions;
        }

        public Builder setPredictions(SparseVector predictions) {
            this.predictions = predictions;
            return this;
        }

        public List getRecommendations() {
            return recommendations;
        }

        public Builder setRecommendations(List recommendations) {
            this.recommendations = recommendations;
            return this;
        }

        public Recommender getRecommender() {
            return recommender;
        }

        public Builder setRecommender(Recommender rec) {
            recommender = rec;
            return this;
        }

        public MockTestUser build() {
            return new MockTestUser(History.forUser(userId, trainEvents),
                                    History.forUser(userId, testEvents),
                                    predictions, recommendations, recommender);
        }
    }
}