/*
* 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.metrics.predict;
import org.grouplens.lenskit.eval.traintest.MockTestUser;
import org.grouplens.lenskit.eval.traintest.TestUser;
import org.grouplens.lenskit.util.statistics.MeanAccumulator;
import org.grouplens.lenskit.vectors.MutableSparseVector;
import org.grouplens.lenskit.vectors.SparseVector;
import org.junit.Before;
import org.junit.Test;
import static org.hamcrest.Matchers.notNullValue;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertThat;
public class NDCGTest {
long[] items = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
double[] ratings1 = {5, 4, 4, 3, 5, 3, 4, 3, 2, 5};
double[] ratings2 = {5, 5, 4, 4, 4, 3, 2, 2, 3, 4};
double[] ratings3 = {4, 5, 4, 2, 3, 1, 3, 4, 5, 2};
double[] predictions1 = {5, 5, 4, 4, 4, 3, 2, 2, 3, 4};
double[] predictions2 = {4, 4, 5, 2, 3, 2, 3, 4, 4, 3};
double[] predictions3 = {4, 4, 5, 3, 3, 4, 5, 4, 4, 4};
SparseVector rv1 = MutableSparseVector.wrap(items, ratings1).freeze();
SparseVector rv2 = MutableSparseVector.wrap(items, ratings2).freeze();
SparseVector rv3 = MutableSparseVector.wrap(items, ratings3).freeze();
SparseVector pv1 = MutableSparseVector.wrap(items, predictions1).freeze();
SparseVector pv2 = MutableSparseVector.wrap(items, predictions2).freeze();
SparseVector pv3 = MutableSparseVector.wrap(items, predictions3).freeze();
TestUser user1, user2, user3;
@Before
public void createTestUsers() {
MockTestUser.Builder b1, b2, b3;
b1 = MockTestUser.newBuilder().setUserId(1);
b2 = MockTestUser.newBuilder().setUserId(2);
b3 = MockTestUser.newBuilder().setUserId(3);
for (int i = 0; i < 10; i++) {
b1.addTestRating(items[i], ratings1[i]);
b2.addTestRating(items[i], ratings2[i]);
b3.addTestRating(items[i], ratings3[i]);
}
user1 = b1.setPredictions(pv1).build();
user2 = b2.setPredictions(pv2).build();
user3 = b3.setPredictions(pv3).build();
}
@Test
public void testComputeDCG() {
// score rating vectors
assertEquals(22.0418,
NDCGPredictMetric.computeDCG(rv1.keysByValue(true), rv1),
0.0001);
assertEquals(21.0954,
NDCGPredictMetric.computeDCG(rv2.keysByValue(true), rv2),
0.0001);
assertEquals(20.0742,
NDCGPredictMetric.computeDCG(rv3.keysByValue(true), rv3),
0.0001);
// score prediction vectors
// note that the correctness of these tests depends on keysByValue using
// a stable sort.
assertEquals(21.0116,
NDCGPredictMetric.computeDCG(pv1.keysByValue(true), rv1),
0.0001);
assertEquals(20.2048,
NDCGPredictMetric.computeDCG(pv2.keysByValue(true), rv2),
0.0001);
assertEquals(17.9835,
NDCGPredictMetric.computeDCG(pv3.keysByValue(true), rv3),
0.0001);
}
@Test
public void testAccumulator() {
NDCGPredictMetric metric = new NDCGPredictMetric();
MeanAccumulator acc = metric.createContext(null, null, null);
assertThat(acc, notNullValue());
assert acc != null;
metric.measureUser(user1, acc);
assertEquals(1, acc.getCount());
assertEquals(0.9533, acc.getTotal(), 0.0001);
metric.measureUser(user2, acc);
assertEquals(2, acc.getCount());
assertEquals(1.9110, acc.getTotal(), 0.0001);
metric.measureUser(user3, acc);
assertEquals(3, acc.getCount());
assertEquals(2.8069, acc.getTotal(), 0.0001);
}
}