blob: 79668d24a1f3cee48c19eda3a649dfec5c9aa95b [file] [log] [blame]
/*
* 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.ignite.ml.composition.predictionsaggregator;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
/** */
public class WeightedPredictionsAggregatorTest {
/** */
public static final double[] EMPTY_DOUBLE_ARRAY = {};
/** */
@Test
public void testApply1() {
WeightedPredictionsAggregator aggregator = new WeightedPredictionsAggregator(new double[] {});
assertEquals(0.0, aggregator.apply(new double[] {}), 0.001);
}
/** */
@Test
public void testApply2() {
WeightedPredictionsAggregator aggregator = new WeightedPredictionsAggregator(new double[] {1.0, 0.5, 0.25});
assertEquals(3.0, aggregator.apply(new double[] {1.0, 2.0, 4.0}), 0.001);
}
/** Non-equal weight vector and predictions case */
@Test(expected = IllegalArgumentException.class)
public void testIllegalArguments() {
WeightedPredictionsAggregator aggregator = new WeightedPredictionsAggregator(new double[] {1.0, 0.5, 0.25});
aggregator.apply(new double[] { });
}
/** */
@Test
public void testToString() {
PredictionsAggregator aggr = (PredictionsAggregator)doubles -> null;
assertTrue(!aggr.toString().isEmpty());
assertTrue(!aggr.toString(true).isEmpty());
assertTrue(!aggr.toString(false).isEmpty());
WeightedPredictionsAggregator aggregator = new WeightedPredictionsAggregator(EMPTY_DOUBLE_ARRAY);
assertTrue(!aggregator.toString().isEmpty());
assertTrue(!aggregator.toString(true).isEmpty());
assertTrue(!aggregator.toString(false).isEmpty());
}
}