com.github.javacliparser.IntOption Java Examples

/**
 * The main method.
 * 
 * @param args
 *          the arguments
 */
public static void main(String[] args) {

  // ArrayList<String> tmpArgs = new ArrayList<String>(Arrays.asList(args));

  // args = tmpArgs.toArray(new String[0]);

  FlagOption suppressStatusOutOpt = new FlagOption("suppressStatusOut", 'S', SUPPRESS_STATUS_OUT_MSG);

  FlagOption suppressResultOutOpt = new FlagOption("suppressResultOut", 'R', SUPPRESS_RESULT_OUT_MSG);

  IntOption statusUpdateFreqOpt = new IntOption("statusUpdateFrequency", 'F', STATUS_UPDATE_FREQ_MSG, 1000, 0,
      Integer.MAX_VALUE);

  Option[] extraOptions = new Option[] { suppressStatusOutOpt, suppressResultOutOpt, statusUpdateFreqOpt };

  StringBuilder cliString = new StringBuilder();
  for (String arg : args) {
    cliString.append(" ").append(arg);
  }
  logger.debug("Command line string = {}", cliString.toString());
  System.out.println("Command line string = " + cliString.toString());

  Task task;
  try {
    task = ClassOption.cliStringToObject(cliString.toString(), Task.class, extraOptions);
    logger.info("Successfully instantiating {}", task.getClass().getCanonicalName());
  } catch (Exception e) {
    logger.error("Fail to initialize the task", e);
    System.out.println("Fail to initialize the task" + e);
    return;
  }
  task.setFactory(new SimpleComponentFactory());
  task.init();
  SimpleEngine.submitTopology(task.getTopology());
}
 

public AbstractClusterer() {
  if (isRandomizable()) {
    this.randomSeedOption = new IntOption("randomSeed", 'r',
        "Seed for random behaviour of the Clusterer.", 1);
  }

  if (implementsMicroClusterer()) {
    this.evaluateMicroClusteringOption =
        new FlagOption("evaluateMicroClustering", 'M',
            "Evaluate the underlying microclustering instead of the macro clustering");
  }
}
 

/**
 * Creates an classifier and setups the random seed option if the classifier is randomizable.
 */
public AbstractClassifier() {
  if (isRandomizable()) {
    this.randomSeedOption = new IntOption("randomSeed", 'r',
        "Seed for random behaviour of the classifier.", 1);
  }
}
 

public AbstractClusterer() {
	if (isRandomizable()) {
		this.randomSeedOption = new IntOption("randomSeed", 'r',
				"Seed for random behaviour of the Clusterer.", 1);
	}

       if( implementsMicroClusterer()){
           this.evaluateMicroClusteringOption =
                   new FlagOption("evaluateMicroClustering", 'M',
                   "Evaluate the underlying microclustering instead of the macro clustering");
       }
}
 

/**
 * Creates an classifier and setups the random seed option
 * if the classifier is randomizable.
 */
public AbstractClassifier() {
    if (isRandomizable()) {
        this.randomSeedOption = new IntOption("randomSeed", 'r',
                "Seed for random behaviour of the classifier.", 1);
    }
}
 

/**
 * The main method.
 * 
 * @param args
 *            the arguments
 */
public static void main(String[] args) {

    // ArrayList<String> tmpArgs = new ArrayList<String>(Arrays.asList(args));

    // args = tmpArgs.toArray(new String[0]);

    FlagOption suppressStatusOutOpt = new FlagOption("suppressStatusOut", 'S', SUPPRESS_STATUS_OUT_MSG);

    FlagOption suppressResultOutOpt = new FlagOption("suppressResultOut", 'R', SUPPRESS_RESULT_OUT_MSG);

    IntOption statusUpdateFreqOpt = new IntOption("statusUpdateFrequency", 'F', STATUS_UPDATE_FREQ_MSG, 1000, 0, Integer.MAX_VALUE);

    Option[] extraOptions = new Option[] { suppressStatusOutOpt, suppressResultOutOpt, statusUpdateFreqOpt };

    StringBuilder cliString = new StringBuilder();
    for (String arg : args) {
        cliString.append(" ").append(arg);
    }
    logger.debug("Command line string = {}", cliString.toString());
    System.out.println("Command line string = " + cliString.toString());

    Task task;
    try {
        task = ClassOption.cliStringToObject(cliString.toString(), Task.class, extraOptions);
        logger.info("Successfully instantiating {}", task.getClass().getCanonicalName());
    } catch (Exception e) {
        logger.error("Fail to initialize the task", e);
        System.out.println("Fail to initialize the task" + e);
        return;
    }
    task.setFactory(new SimpleComponentFactory());
    task.init();
    SimpleEngine.submitTopology(task.getTopology());
}
 

public AbstractClusterer() {
	if (isRandomizable()) {
		this.randomSeedOption = new IntOption("randomSeed", 'r',
				"Seed for random behaviour of the Clusterer.", 1);
	}

       if( implementsMicroClusterer()){
           this.evaluateMicroClusteringOption =
                   new FlagOption("evaluateMicroClustering", 'M',
                   "Evaluate the underlying microclustering instead of the macro clustering");
       }
}
 

/**
 * Creates an classifier and setups the random seed option
 * if the classifier is randomizable.
 */
public AbstractClassifier() {
    if (isRandomizable()) {
        this.randomSeedOption = new IntOption("randomSeed", 'r',
                "Seed for random behaviour of the classifier.", 1);
    }
}
 

@Override
public void setEditState(String cliString) {
    this.spinner.setValue(IntOption.cliStringToInt(cliString));
}
 

@Override
public void restart() {
	try {
		if (fileReader != null) {
			fileReader.close();
		}
		InputStream fileStream = new FileInputStream(
				this.csvFileOption.getFile());
		this.fileProgressMonitor = new InputStreamProgressMonitor(
				fileStream);
		this.fileReader = new BufferedReader(new InputStreamReader(
				fileProgressMonitor));

		String line;
		do {
			line = this.fileReader.readLine();
			if (line == null) {
				break;
			}
			line = line.trim();
		} while (line.isEmpty() || line.charAt(0) == '%'
				|| line.charAt(0) == '@');

		if (line != null) {
			StringTokenizer token = new StringTokenizer(line,
					splitCharOption.getValue());
			this.numTokens = token.countTokens();
			this.numAttributes = this.numTokens
					- (classIndexOption.isSet() ? 1 : 0) + 1;

			ArrayList<Attribute> attributes = new ArrayList<Attribute>(
					this.numAttributes);
			for (int i = 1; i < this.numAttributes; i++) {
				attributes.add(new Attribute("Dim " + i));
			}
			ArrayList<String> classLabels = new ArrayList<String>();
			classLabels.add("0");
	        attributes.add(new Attribute("class", classLabels));
			this.dataset = new Instances(csvFileOption.getFile().getName(),
					attributes, 0);
			this.dataset.setClassIndex(this.numAttributes - 1);
			numAttsOption = new IntOption("numAtts", 'a', "",
					this.numAttributes);

			double[] value = new double[this.numAttributes];
			for (int i = 0; i < this.numTokens && token.hasMoreTokens(); i++) {
				value[i] = Double.valueOf(token.nextToken());
			}
			this.lastInstanceRead = new InstanceExample(new DenseInstance(1, value));
			this.lastInstanceRead.getData().setDataset(this.dataset);
			this.numInstancesRead = 0;
			this.hitEndOfFile = false;
		} else {
			this.lastInstanceRead = null;
			this.numInstancesRead = 0;
			this.hitEndOfFile = true;
		}
	} catch (IOException ioe) {
		throw new RuntimeException("SimpleCSVStream restart failed.", ioe);
	}
}