Examples of edu.umd.cloud9.io.map.HMapSFW

edu.umd.cloud9.io.map.HMapSFW
Writable representing a map where keys are Strings and values are floats. This class is specialized for String objects to avoid the overhead that comes with wrapping Strings inside Text objects. @author Jimmy Lin

    }
    return cnt;
  }


  private static HMapSFW array2Map(String[] array) {
    HMapSFW map = new HMapSFW();
    for ( int i = 0; i < array.length; i += 2 ) {
      map.put(array[i], Float.parseFloat(array[i+1]));
    }
    return map;
  }

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    return new JUnit4TestAdapter(EnAr_TREC02.class);
  }


  public static void main(String[] args) {
    //    HMapSFW gridAPMap = array2Map(Interp_AP);
    HMapSFW tenbestAPMap = array2Map(Nbest_AP.get(2));
    HMapSFW onebestAPMap = array2Map(Onebest_AP.get(1));
    HMapSFW grammarAPMap = array2Map(grammar_AP.get(0));
    HMapSFW tokenAPMap = array2Map(baseline_token_AP);
    //    System.out.println(countNumberOfImprovedTopics(tokenAPMap, gridAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tenbestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, onebestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, grammarAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tokenAPMap));

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    }
    return cnt;
  }


  private static HMapSFW array2Map(String[] array) {
    HMapSFW map = new HMapSFW();
    for ( int i = 0; i < array.length; i += 2 ) {
      map.put(array[i], Float.parseFloat(array[i+1]));
    }
    return map;
  }

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    return new JUnit4TestAdapter(EnFr_CLEF06.class);
  }


  public static void main(String[] args) {
    //    HMapSFW gridAPMap = array2Map(Gridbest_AP);
    HMapSFW tenbestAPMap = array2Map(Nbest_AP.get(2));
    HMapSFW onebestAPMap = array2Map(Onebest_AP.get(1));
    HMapSFW grammarAPMap = array2Map(grammar_AP.get(0));
    HMapSFW tokenAPMap = array2Map(baseline_token_AP);
    //    System.out.println(countNumberOfImprovedTopics(tokenAPMap, gridAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tenbestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, onebestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, grammarAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tokenAPMap));

View Full Code Here

    }
    return cnt;
  }


  private static HMapSFW array2Map(String[] array) {
    HMapSFW map = new HMapSFW();
    for ( int i = 0; i < array.length; i += 2 ) {
      map.put(array[i], Float.parseFloat(array[i+1]));
    }
    return map;
  }

View Full Code Here

      int numProcessed = 0;
      long time = 0;
      
      // classify each e-f sentence pair in the candidate set
      for (int f = 0; f < fVectors.size(); f++) {
        HMapSFW fVector = fVectors.get(f);
        int fSentLength = fSentences.get(f).getLength();


        for (int e = 0; e < eVectors.size(); e++) {
          HMapSFW eVector = eVectors.get(e);
          int eSentLength = eSentences.get(e).getLength();


          if (eSentLength > 2 * fSentLength || fSentLength > 2 * eSentLength) {
            reporter.incrCounter(Sentences.pairsFilteredBySentRatio, 1);
            continue;

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      // We simply use the source-language doc length since the ratio of doc length to average doc
      // length is unlikely to change significantly (not worth complicating the pipeline)
      int docLen = CLIRUtils.translateTFs(doc, tfS, eVocabSrc, eVocabTrg, fVocabSrc, fVocabTrg,
          e2f_Probs, f2e_Probs, tokenizer, LOG);


      HMapSFW v = CLIRUtils.createTermDocVector(docLen, tfS, eVocabTrg, model, dict, dfTable,
          isNormalize, LOG);


      // If no translation of any word is in the target vocab, remove document i.e., our model
      // wasn't capable of translating it.
      if (v.size() < MIN_SIZE) {
        reporter.incrCounter(Docs.SHORTAfterTranslation, 1);
        return;
      } else {
        reporter.incrCounter(Docs.Total, 1);
        output.collect(docno, v);

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    }


    try {
      sentence = new Text();
      sentence.readFields(in);
      vector = new HMapSFW();
      vector.readFields(in);
    } catch (IOException e) {
      throw new RuntimeException("Could not read vectors/sentences in WikiSentenceInfo");
    }
  }

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      sLogger.debug(fSentences.size()+","+eSentences.size());


      // classify each e-f sentence pair in the candidate set
      for (int f = 0; f < fVectors.size(); f++) {
        HMapSFW fVector = fVectors.get(f);
        int fSentLength = fSentences.get(f).getLength();


        for (int e = 0; e < eVectors.size(); e++) {
          HMapSFW eVector = eVectors.get(e);
          int eSentLength = eSentences.get(e).getLength();


          if (eSentLength > 2 * fSentLength || fSentLength > 2 * eSentLength) {
            // sLogger.debug("length filter");
            reporter.incrCounter(Sentences.pairsFilteredBySentRatio, 1);

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    return new JUnit4TestAdapter(EnZh_NTCIR8.class);
  }


  public static void main(String[] args) {
    //    HMapSFW gridAPMap = array2Map(Interp_AP);
    HMapSFW tenbestAPMap = array2Map(Nbest_AP.get(2));
    HMapSFW onebestAPMap = array2Map(Onebest_AP.get(1));
    HMapSFW grammarAPMap = array2Map(grammar_AP.get(0));
    HMapSFW tokenAPMap = array2Map(baseline_token_AP);
    //    System.out.println(countNumberOfImprovedTopics(tokenAPMap, gridAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tenbestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, onebestAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, grammarAPMap));
    System.out.println(countNumberOfImprovedTopics(tokenAPMap, tokenAPMap));

View Full Code Here

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