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package org.apache.lucene.index;
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.List;
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import org.apache.lucene.analysis.MockAnalyzer;
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import org.apache.lucene.analysis.MockTokenizer;
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import org.apache.lucene.document.Document;
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import org.apache.lucene.document.Field;
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import org.apache.lucene.search.DefaultSimilarity;
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import org.apache.lucene.store.Directory;
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import org.apache.lucene.util.LuceneTestCase;
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import org.apache.lucene.util._TestUtil;
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* Tests the maxTermFrequency statistic in FieldInvertState
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public class TestMaxTermFrequency extends LuceneTestCase {
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/* expected maxTermFrequency values for our documents */
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ArrayList<Integer> expected = new ArrayList<Integer>();
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public void setUp() throws Exception {
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IndexWriterConfig config = newIndexWriterConfig(TEST_VERSION_CURRENT,
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new MockAnalyzer(random, MockTokenizer.SIMPLE, true)).setMergePolicy(newLogMergePolicy());
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config.setSimilarity(new TestSimilarity());
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RandomIndexWriter writer = new RandomIndexWriter(random, dir, config);
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Document doc = new Document();
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Field foo = newField("foo", "", Field.Store.NO, Field.Index.ANALYZED);
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for (int i = 0; i < 100; i++) {
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foo.setValue(addValue());
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writer.addDocument(doc);
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reader = writer.getReader();
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public void tearDown() throws Exception {
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public void test() throws Exception {
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byte fooNorms[] = reader.norms("foo");
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for (int i = 0; i < reader.maxDoc(); i++)
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assertEquals(expected.get(i).intValue(), fooNorms[i] & 0xff);
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* Makes a bunch of single-char tokens (the max freq will at most be 255).
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* shuffles them around, and returns the whole list with Arrays.toString().
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* This works fine because we use lettertokenizer.
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* puts the max-frequency term into expected, to be checked against the norm.
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private String addValue() {
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List<String> terms = new ArrayList<String>();
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int maxCeiling = _TestUtil.nextInt(random, 0, 255);
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for (char ch = 'a'; ch <= 'z'; ch++) {
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int num = _TestUtil.nextInt(random, 0, maxCeiling);
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for (int i = 0; i < num; i++)
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terms.add(Character.toString(ch));
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max = Math.max(max, num);
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Collections.shuffle(terms, random);
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return Arrays.toString(terms.toArray(new String[terms.size()]));
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* Simple similarity that encodes maxTermFrequency directly as a byte
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class TestSimilarity extends DefaultSimilarity {
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public byte encodeNormValue(float f) {
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public float decodeNormValue(byte b) {
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public float computeNorm(String field, FieldInvertState state) {
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return (float) state.getMaxTermFrequency();