com.github.pmerienne.cf.recommendation.TopKItemsTest.java Source code

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Here is the source code for com.github.pmerienne.cf.recommendation.TopKItemsTest.java

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/**
 * Copyright 2013-2015 Pierre Merienne
 *
 * Licensed 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 com.github.pmerienne.cf.recommendation;

import static org.fest.assertions.Assertions.assertThat;

import org.apache.commons.lang.math.RandomUtils;
import org.junit.Test;

import com.github.pmerienne.cf.recommendation.Recommendation;
import com.github.pmerienne.cf.recommendation.TopKItems;

public class TopKItemsTest {

    @Test
    public void should_not_exceed_max_size() {
        // Given
        int maxSize = 10;
        TopKItems topKItems = new TopKItems(maxSize);
        for (int i = 0; i < maxSize * 2; i++) {
            topKItems.add(new Recommendation(RandomUtils.nextLong(), RandomUtils.nextDouble()));
        }

        // When
        topKItems.ensureSize();

        // Then
        assertThat(topKItems.size()).isLessThanOrEqualTo(maxSize);
    }

    @Test
    public void should_sort_recommendations() {
        // Given
        int maxSize = 10;

        // When
        TopKItems topKItems = new TopKItems(maxSize);
        for (int i = 0; i < maxSize; i++) {
            topKItems.add(new Recommendation(RandomUtils.nextLong(), RandomUtils.nextDouble()));
        }

        // Then
        double previousScore = Double.MAX_VALUE;
        for (Recommendation recommendation : topKItems) {
            assertThat(recommendation.getScore()).isLessThan(previousScore);
            previousScore = recommendation.getScore();
        }
    }
}