/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.apache.mahout.cf.taste.impl.recommender.slopeone;
import org.apache.mahout.cf.taste.common.Weighting;
import org.apache.mahout.cf.taste.impl.TasteTestCase;
import org.apache.mahout.cf.taste.impl.common.RunningAverage;
import org.apache.mahout.cf.taste.impl.model.GenericDataModel;
import org.apache.mahout.cf.taste.model.DataModel;
/**
* Tests {@link MemoryDiffStorage}.
*/
public class MemoryDiffStorageTest extends TasteTestCase {
public void testGetDiff() throws Exception {
DataModel model = new GenericDataModel(getMockUsers());
MemoryDiffStorage storage = new MemoryDiffStorage(model, Weighting.UNWEIGHTED, false, Long.MAX_VALUE);
RunningAverage average = storage.getDiff("1", "2");
assertEquals(0.23333333333333334, average.getAverage(), EPSILON);
assertEquals(3, average.getCount());
}
public void testUpdate() throws Exception {
DataModel model = new GenericDataModel(getMockUsers());
MemoryDiffStorage storage = new MemoryDiffStorage(model, Weighting.UNWEIGHTED, false, Long.MAX_VALUE);
storage.updateItemPref("1", 0.5, false);
RunningAverage average = storage.getDiff("1", "2");
assertEquals(0.06666666666666668, average.getAverage(), EPSILON);
assertEquals(3, average.getCount());
}
public void testRemove() throws Exception {
DataModel model = new GenericDataModel(getMockUsers());
MemoryDiffStorage storage = new MemoryDiffStorage(model, Weighting.UNWEIGHTED, false, Long.MAX_VALUE);
storage.updateItemPref("1", 0.5, true);
RunningAverage average = storage.getDiff("1", "2");
assertEquals(0.1, average.getAverage(), EPSILON);
assertEquals(2, average.getCount());
}
}