org.lenskit.mf.BiasedMFItemScorerTest.java Source code

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Here is the source code for org.lenskit.mf.BiasedMFItemScorerTest.java

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/*
 * LensKit, an open-source toolkit for recommender systems.
 * Copyright 2014-2017 LensKit contributors (see CONTRIBUTORS.md)
 * Copyright 2010-2014 Regents of the University of Minnesota
 *
 * Permission is hereby granted, free of charge, to any person obtaining
 * a copy of this software and associated documentation files (the
 * "Software"), to deal in the Software without restriction, including
 * without limitation the rights to use, copy, modify, merge, publish,
 * distribute, sublicense, and/or sell copies of the Software, and to
 * permit persons to whom the Software is furnished to do so, subject to
 * the following conditions:
 *
 * The above copyright notice and this permission notice shall be
 * included in all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
 * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
 * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
 * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
 * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
 * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 */
package org.lenskit.mf;

import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.RealMatrix;
import org.junit.Before;
import org.junit.Ignore;
import org.junit.Test;
import org.lenskit.api.ItemScorer;
import org.lenskit.api.Result;
import org.lenskit.basic.PrecomputedItemScorer;
import org.lenskit.util.keys.HashKeyIndex;

import static org.hamcrest.Matchers.*;
import static org.junit.Assert.*;

@Ignore("non-working for bias models")
public class BiasedMFItemScorerTest {
    private ItemScorer baseline;
    private MFModel model;
    private BiasedMFItemScorer scorer;

    @Before
    public void createModel() {
        baseline = PrecomputedItemScorer.newBuilder().addScore(1, 42, 3.0).addScore(1, 39, 2.5).addScore(1, 25, 4.2)
                .addScore(5, 42, 3.7).addScore(5, 39, 2.8).addScore(3, 42, 2.2).addScore(3, 39, 3.2)
                .addScore(17, 42, 2.5).build();

        RealMatrix umat = MatrixUtils.createRealMatrix(3, 2);
        umat.setRow(0, new double[] { 0.1, 0.3 });
        umat.setRow(1, new double[] { -0.2, 0.2 });
        umat.setRow(2, new double[] { 0.0, 0.15 });
        HashKeyIndex uidx = new HashKeyIndex();
        uidx.internId(1);
        uidx.internId(5);
        uidx.internId(3);

        RealMatrix imat = MatrixUtils.createRealMatrix(2, 2);
        imat.setRow(0, new double[] { 0.52, 0.29 });
        imat.setRow(1, new double[] { 0.3, -1.2 });
        HashKeyIndex iidx = new HashKeyIndex();
        iidx.internId(42);
        iidx.internId(39);

        model = new MFModel(umat, imat, uidx, iidx);

        // scorer = new BiasedMFItemScorer(model, baseline);
    }

    @Test
    public void testGoodRecs() {
        Result score = scorer.score(1, 42);
        assertThat(score, notNullValue());
        assertThat(score.getScore(), closeTo(3.0 + 0.1 * 0.52 + 0.3 * 0.29, 1.0e-6));

        score = scorer.score(3, 39);
        assertThat(score, notNullValue());
        assertThat(score.getScore(), closeTo(3.2 - 0.15 * 1.2, 1.0e-6));
    }

    @Test
    public void testSkipUnscorable() {
        Result score = scorer.score(1, 25);
        assertThat(score, nullValue());
    }

    @Test
    public void baselineForUser() {
        Result score = scorer.score(17, 42);
        assertThat(score, nullValue());
    }
}