/*
* 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.data.history;
import org.grouplens.lenskit.data.event.Rating;
import org.grouplens.lenskit.data.event.RatingBuilder;
import org.grouplens.lenskit.data.event.Ratings;
import org.grouplens.lenskit.vectors.MutableSparseVector;
import org.grouplens.lenskit.vectors.SparseVector;
import org.junit.Test;
import java.util.ArrayList;
import java.util.Collection;
import static org.junit.Assert.assertEquals;
/**
* @author <a href="http://www.grouplens.org">GroupLens Research</a>
*/
public class ItemVectorTest {
private static final double EPSILON = 1.0e-6;
/**
* Test method for {@link org.grouplens.lenskit.data.event.Ratings#itemRatingVector(java.util.Collection)}.
*/
@Test
public void testItemRatingVector() {
Collection<Rating> ratings = new ArrayList<Rating>();
RatingBuilder rb = new RatingBuilder();
ratings.add(Ratings.make(7, 5, 3.5));
ratings.add(Ratings.make(3, 5, 1.5));
ratings.add(Ratings.make(8, 5, 2));
SparseVector v = Ratings.itemRatingVector(ratings);
assertEquals(3, v.size());
assertEquals(7, v.sum(), EPSILON);
long[] keys = {3, 7, 8};
double[] values = {1.5, 3.5, 2};
SparseVector sv = MutableSparseVector.wrap(keys, values);
assertEquals(sv, v);
}
}