/*
* Licensed to Elasticsearch under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch 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.elasticsearch.search.suggest.phrase;
import org.elasticsearch.common.xcontent.XContentParser;
import java.io.IOException;
import static org.hamcrest.Matchers.instanceOf;
public class LinearInterpolationModelTests extends SmoothingModelTestCase {
@Override
protected SmoothingModel createTestModel() {
return createRandomModel();
}
static LinearInterpolation createRandomModel() {
double trigramLambda = randomDoubleBetween(0.0, 10.0, false);
double bigramLambda = randomDoubleBetween(0.0, 10.0, false);
double unigramLambda = randomDoubleBetween(0.0, 10.0, false);
// normalize so parameters sum to 1
double sum = trigramLambda + bigramLambda + unigramLambda;
return new LinearInterpolation(trigramLambda / sum, bigramLambda / sum, unigramLambda / sum);
}
/**
* mutate the given model so the returned smoothing model is different
*/
@Override
protected LinearInterpolation createMutation(SmoothingModel input) {
LinearInterpolation original = (LinearInterpolation) input;
// swap two values permute original lambda values
switch (randomIntBetween(0, 2)) {
case 0:
// swap first two
return new LinearInterpolation(original.getBigramLambda(), original.getTrigramLambda(), original.getUnigramLambda());
case 1:
// swap last two
return new LinearInterpolation(original.getTrigramLambda(), original.getUnigramLambda(), original.getBigramLambda());
case 2:
default:
// swap first and last
return new LinearInterpolation(original.getUnigramLambda(), original.getBigramLambda(), original.getTrigramLambda());
}
}
@Override
void assertWordScorer(WordScorer wordScorer, SmoothingModel in) {
LinearInterpolation testModel = (LinearInterpolation) in;
LinearInterpolatingScorer testScorer = (LinearInterpolatingScorer) wordScorer;
assertThat(wordScorer, instanceOf(LinearInterpolatingScorer.class));
assertEquals(testModel.getTrigramLambda(), (testScorer).trigramLambda(), 1e-15);
assertEquals(testModel.getBigramLambda(), (testScorer).bigramLambda(), 1e-15);
assertEquals(testModel.getUnigramLambda(), (testScorer).unigramLambda(), 1e-15);
}
@Override
protected SmoothingModel fromXContent(XContentParser parser) throws IOException {
return LinearInterpolation.fromXContent(parser);
}
}