org.languagetool.dev.bigdata.AllConfusionRulesEvaluator.java Source code

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Here is the source code for org.languagetool.dev.bigdata.AllConfusionRulesEvaluator.java

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/* LanguageTool, a natural language style checker 
 * Copyright (C) 2015 Daniel Naber (http://www.danielnaber.de)
 * 
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301
 * USA
 */
package org.languagetool.dev.bigdata;

import org.apache.commons.lang3.StringUtils;
import org.languagetool.JLanguageTool;
import org.languagetool.Language;
import org.languagetool.Languages;
import org.languagetool.dev.eval.FMeasure;
import org.languagetool.languagemodel.LanguageModel;
import org.languagetool.languagemodel.LuceneLanguageModel;
import org.languagetool.rules.ConfusionPair;
import org.languagetool.rules.ConfusionSetLoader;
import org.languagetool.rules.ConfusionString;

import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.util.*;

final class AllConfusionRulesEvaluator {

    private static final int MAX_SENTENCES = 1000;

    private AllConfusionRulesEvaluator() {
    }

    public static void main(String[] args) throws IOException {
        if (args.length < 3 || args.length > 4) {
            System.err.println("Usage: " + ConfusionRuleEvaluator.class.getSimpleName()
                    + " <langCode> <languageModelTopDir> <wikipediaXml|tatoebaFile|dir>...");
            System.err.println(
                    "   <languageModelTopDir> is a directory with sub-directories '1grams', '2grams', and '3grams' with Lucene indexes");
            System.err
                    .println("   <wikipediaXml|tatoebaFile|dir> either a Wikipedia XML dump, or a Tatoeba file or");
            System.err.println(
                    "                      a directory with example sentences (where <word>.txt contains only the sentences for <word>).");
            System.err.println("                      You can specify both a Wikipedia file and a Tatoeba file.");
            System.exit(1);
        }
        Language lang;
        if ("en".equals(args[0])) {
            lang = new ConfusionRuleEvaluator.EnglishLight();
        } else {
            lang = Languages.getLanguageForShortCode(args[0]);
        }
        LanguageModel languageModel = new LuceneLanguageModel(new File(args[1]));
        List<String> inputsFiles = new ArrayList<>();
        inputsFiles.add(args[2]);
        if (args.length >= 4) {
            inputsFiles.add(args[3]);
        }
        ConfusionRuleEvaluator eval = new ConfusionRuleEvaluator(lang, languageModel, false, true); // TODO: consider bidirectional
        eval.setVerboseMode(false);
        ConfusionSetLoader confusionSetLoader = new ConfusionSetLoader();
        InputStream inputStream = JLanguageTool.getDataBroker()
                .getFromResourceDirAsStream("/en/confusion_sets.txt");
        Map<String, List<ConfusionPair>> confusionSetMap = confusionSetLoader.loadConfusionPairs(inputStream);
        Set<String> done = new HashSet<>();
        int fMeasureCount = 0;
        float fMeasureTotal = 0;
        for (List<ConfusionPair> entry : confusionSetMap.values()) {
            for (ConfusionPair confusionPair : entry) {
                List<ConfusionString> set = confusionPair.getTerms();
                if (set.size() != 2) {
                    System.out.println("Skipping confusion set with size != 2: " + confusionPair);
                } else {
                    Iterator<ConfusionString> iterator = set.iterator();
                    ConfusionString set1 = iterator.next();
                    ConfusionString set2 = iterator.next();
                    String word1 = set1.getString();
                    String word2 = set2.getString();
                    String key = word1 + " " + word2;
                    if (!done.contains(key)) {
                        Map<Long, RuleEvalResult> evalResults = eval.run(inputsFiles, word1, word2, MAX_SENTENCES,
                                Arrays.asList(confusionPair.getFactor()));
                        RuleEvalResult evalResult = evalResults.values().iterator().next();
                        String summary1 = set1.getDescription() != null ? word1 + "|" + set1.getDescription()
                                : word1;
                        String summary2 = set2.getDescription() != null ? word2 + "|" + set2.getDescription()
                                : word2;
                        String start;
                        if (summary1.compareTo(summary2) < 0) {
                            start = summary1 + "; " + summary2 + "; " + confusionPair.getFactor();
                        } else {
                            start = summary2 + "; " + summary1 + "; " + confusionPair.getFactor();
                        }
                        String spaces = StringUtils.repeat(" ", 82 - start.length());
                        System.out.println(start + spaces + "# " + evalResult.getSummary());
                        double fMeasure = FMeasure.getWeightedFMeasure(evalResult.getPrecision(),
                                evalResult.getRecall());
                        //System.out.println("f-measure: " + fMeasure);
                        fMeasureCount++;
                        fMeasureTotal += fMeasure;
                    }
                    done.add(key);
                }
            }
        }
        System.out.println("Average f-measure: " + (fMeasureTotal / fMeasureCount));
    }

}