Package opennlp.tools.cmdline

Examples of opennlp.tools.cmdline.PerformanceMonitor

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    TokenNameFinderEvaluator evaluator = new TokenNameFinderEvaluator(
        new NameFinderME(model),
        listeners.toArray(new TokenNameFinderEvaluationMonitor[listeners.size()]));

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<NameSample> measuredSampleStream = new ObjectStream<NameSample>() {

      public NameSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      throw new TerminateToolException(-1, "IO error while reading test data: " + e.getMessage(), e);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    if(detailedFListener == null) {
      System.out.println(evaluator.getFMeasure());
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      }

//      ObjectStream<String> untokenizedLineStream =
//          new PlainTextByLineStream(new InputStreamReader(System.in));
      ObjectStream<String> untokenizedLineStream;
      PerformanceMonitor perfMon = new PerformanceMonitor(System.err, "sent");
      perfMon.start();

      try {
        untokenizedLineStream =
                new PlainTextByLineStream(new SystemInputStreamFactory(), SystemInputStreamFactory.encoding());
        String line;
        while ((line = untokenizedLineStream.read()) != null) {
          String whitespaceTokenizerLine[] = WhitespaceTokenizer.INSTANCE.tokenize(line);

          // A new line indicates a new document,
          // adaptive data must be cleared for a new document

          if (whitespaceTokenizerLine.length == 0) {
            for (NameFinderME nameFinder : nameFinders) {
              nameFinder.clearAdaptiveData();
            }
          }

          List<Span> names = new ArrayList<Span>();

          for (TokenNameFinder nameFinder : nameFinders) {
            Collections.addAll(names, nameFinder.find(whitespaceTokenizerLine));
          }

          // Simple way to drop intersecting spans, otherwise the
          // NameSample is invalid
          Span reducedNames[] = NameFinderME.dropOverlappingSpans(
                  names.toArray(new Span[names.size()]));

          NameSample nameSample = new NameSample(whitespaceTokenizerLine,
                  reducedNames, false);

          System.out.println(nameSample.toString());

          perfMon.incrementCounter();
        }
      } catch (IOException e) {
        CmdLineUtil.handleStdinIoError(e);
      }

      perfMon.stopAndPrintFinalResult();
    }
  }
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    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model,
        ChunkerME.DEFAULT_BEAM_SIZE),
        listeners.toArray(new ChunkerEvaluationMonitor[listeners.size()]));

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      throw new TerminateToolException(-1, "IO error while reading test data: " + e.getMessage(), e);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    if (detailedFMeasureListener == null) {
      System.out.println(evaluator.getFMeasure());
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      ChunkerModel model = new ChunkerModelLoader().load(new File(args[0]));

      ChunkerME chunker = new ChunkerME(model, ChunkerME.DEFAULT_BEAM_SIZE);

      ObjectStream<String> lineStream = null;
      PerformanceMonitor perfMon = null;

      try {
        lineStream = new PlainTextByLineStream(new SystemInputStreamFactory(), SystemInputStreamFactory.encoding());
        perfMon = new PerformanceMonitor(System.err, "sent");
        String line;
        while ((line = lineStream.read()) != null) {

          POSSample posSample;
          try {
            posSample = POSSample.parse(line);
          } catch (InvalidFormatException e) {
            System.err.println("Invalid format:");
            System.err.println(line);
            continue;
          }

          String[] chunks = chunker.chunk(posSample.getSentence(),
                  posSample.getTags());

          System.out.println(new ChunkSample(posSample.getSentence(),
                  posSample.getTags(), chunks).nicePrint());

          perfMon.incrementCounter();
        }
      } catch (IOException e) {
        CmdLineUtil.handleStdinIoError(e);
      }

      perfMon.stopAndPrintFinalResult();
    }
  }
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      opennlp.tools.parser.Parser parser =
              ParserFactory.create(model, beamSize, advancePercentage);


      ObjectStream<String> lineStream = null;
      PerformanceMonitor perfMon = null;
      try {
        lineStream = new PlainTextByLineStream(new SystemInputStreamFactory(), SystemInputStreamFactory.encoding());
        perfMon = new PerformanceMonitor(System.err, "sent");
        perfMon.start();
        String line;
        while ((line = lineStream.read()) != null) {
          if (line.trim().length() == 0) {
            System.out.println();
          } else {
            Parse[] parses = parseLine(line, parser, numParses);

            for (int pi = 0, pn = parses.length; pi < pn; pi++) {
              if (showTopK) {
                System.out.print(pi + " " + parses[pi].getProb() + " ");
              }

              parses[pi].show();

              perfMon.incrementCounter();
            }
          }
        }
      } catch (IOException e) {
        CmdLineUtil.handleStdinIoError(e);
      }

      perfMon.stopAndPrintFinalResult();
    }
  }
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        new NameFinderME(model));

    final ObjectStream<NameSample> sampleStream = TokenNameFinderTrainerTool.openSampleData("Test",
        testData, encoding);

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<NameSample> measuredSampleStream = new ObjectStream<NameSample>() {

      public NameSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      System.err.println("Reading test data error " + e.getMessage());
      throw new TerminateToolException(-1);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    System.out.println(evaluator.getFMeasure());
  }
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    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model));
   
    final ObjectStream<ChunkSample> sampleStream = ChunkerTrainerTool.openSampleData("Test",
        testData, encoding);

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      System.err.println("Reading test data error " + e.getMessage());
      throw new TerminateToolException(-1);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    System.out.println(evaluator.getFMeasure());
  }
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      TokenNameFinderEvaluator evaluator = new TokenNameFinderEvaluator(nameFinder);
     
      final NameSampleDataStream sampleStream = new NameSampleDataStream(
          new PlainTextByLineStream(new InputStreamReader(new FileInputStream(args[2]), args[1])));
     
      final PerformanceMonitor monitor = new PerformanceMonitor("sent");
     
      monitor.startAndPrintThroughput();
     
      ObjectStream<NameSample> iterator = new ObjectStream<NameSample>() {

        public NameSample read() throws IOException {
          monitor.incrementCounter();
          return sampleStream.read();
        }
       
        public void reset() throws IOException {
          sampleStream.reset();
        }
       
        public void close() throws IOException {
          sampleStream.close();
        }
      };
     
      evaluator.evaluate(iterator);
     
      monitor.stopAndPrintFinalResult();
     
      System.out.println();
      System.out.println("F-Measure: " + evaluator.getFMeasure().getFMeasure());
      System.out.println("Recall: " + evaluator.getFMeasure().getRecallScore());
      System.out.println("Precision: " + evaluator.getFMeasure().getPrecisionScore());
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        ParserFactory.create(model, beamSize, advancePercentage);

    ObjectStream<String> lineStream =
      new PlainTextByLineStream(new InputStreamReader(System.in));
   
    PerformanceMonitor perfMon = new PerformanceMonitor(System.err, "sent");
    perfMon.start();
   
    try {
      String line;
      while ((line = lineStream.read()) != null) {
        if (line.length() == 0) {
          System.out.println();
        }
        else {
          Parse[] parses = parseLine(line, parser, numParses);
         
          for (int pi=0,pn=parses.length;pi<pn;pi++) {
            if (showTopK) {
              System.out.print(pi+" "+parses[pi].getProb()+" ");
            }
           
            parses[pi].show();
           
            perfMon.incrementCounter();
          }
        }
      }
    }
    catch (IOException e) {
      CmdLineUtil.handleStdinIoError(e);
    }
   
    perfMon.stopAndPrintFinalResult();
  }
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Related Classes of opennlp.tools.cmdline.PerformanceMonitor

  • opennlp.tools.cmdline.chunker.ChunkerEvaluatorTool
  • opennlp.tools.cmdline.chunker.ChunkerMETool
  • opennlp.tools.cmdline.coref.CoreferencerTool
  • opennlp.tools.cmdline.doccat.DoccatEvaluatorTool
  • opennlp.tools.cmdline.doccat.DoccatTool
  • opennlp.tools.cmdline.entitylinker.EntityLinkerTool
  • opennlp.tools.cmdline.namefind.TokenNameFinderEvaluatorTool
  • opennlp.tools.cmdline.namefind.TokenNameFinderTool
  • opennlp.tools.cmdline.parser.ParserTool
  • opennlp.tools.cmdline.postag.POSTaggerTool
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