Example usage for org.apache.commons.cli2.builder DefaultOptionBuilder DefaultOptionBuilder

Introduction

In this page you can find the example usage for org.apache.commons.cli2.builder DefaultOptionBuilder DefaultOptionBuilder.

Prototype

public DefaultOptionBuilder() 

Source Link

Document

Creates a new DefaultOptionBuilder using defaults

Usage

From source file:org.apache.mahout.clustering.syntheticcontrol.canopy.InputDriver.java

public static void main(String[] args) throws IOException {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = DefaultOptionCreator.inputOption().withRequired(false).create();
    Option outputOpt = DefaultOptionCreator.outputOption().withRequired(false).create();
    Option vectorOpt = obuilder.withLongName("vector").withRequired(false)
            .withArgument(abuilder.withName("v").withMinimum(1).withMaximum(1).create())
            .withDescription("The vector implementation to use.").withShortName("v").create();

    Option helpOpt = DefaultOptionCreator.helpOption();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(outputOpt).withOption(vectorOpt)
            .withOption(helpOpt).create();

    try {/*from   w w w.ja va 2  s . c  o m*/
        Parser parser = new Parser();
        parser.setGroup(group);
        CommandLine cmdLine = parser.parse(args);
        if (cmdLine.hasOption(helpOpt)) {
            CommandLineUtil.printHelp(group);
            return;
        }

        Path input = new Path(cmdLine.getValue(inputOpt, "testdata").toString());
        Path output = new Path(cmdLine.getValue(outputOpt, "output").toString());
        String vectorClassName = cmdLine.getValue(vectorOpt, "org.apache.mahout.math.RandomAccessSparseVector")
                .toString();
        runJob(input, output, vectorClassName);
    } catch (OptionException e) {
        InputDriver.LOG.error("Exception parsing command line: ", e);
        CommandLineUtil.printHelp(group);
    }
}

---

From source file:org.apache.mahout.clustering.syntheticcontrol.canopy.Job.java

public static void main(String[] args) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = obuilder.withLongName("input").withRequired(false)
            .withArgument(abuilder.withName("input").withMinimum(1).withMaximum(1).create())
            .withDescription("The Path for input Vectors. Must be a SequenceFile of Writable, Vector")
            .withShortName("i").create();
    Option outputOpt = obuilder.withLongName("output").withRequired(false)
            .withArgument(abuilder.withName("output").withMinimum(1).withMaximum(1).create())
            .withDescription("The Path to put the output in").withShortName("o").create();

    Option measureClassOpt = obuilder.withLongName("distance").withRequired(false)
            .withArgument(abuilder.withName("distance").withMinimum(1).withMaximum(1).create())
            .withDescription("The Distance Measure to use.  Default is SquaredEuclidean").withShortName("m")
            .create();/*from www  .j  a  va 2 s.  co m*/
    // Option vectorClassOpt = obuilder.withLongName("vectorClass").withRequired(false).withArgument(
    // abuilder.withName("vectorClass").withMinimum(1).withMaximum(1).create()).
    // withDescription("The Vector implementation class name.  Default is RandomAccessSparseVector.class")
    // .withShortName("v").create();

    Option t1Opt = obuilder.withLongName("t1").withRequired(false)
            .withArgument(abuilder.withName("t1").withMinimum(1).withMaximum(1).create()).withDescription("t1")
            .withShortName("t1").create();
    Option t2Opt = obuilder.withLongName("t2").withRequired(false)
            .withArgument(abuilder.withName("t2").withMinimum(1).withMaximum(1).create()).withDescription("t2")
            .withShortName("t2").create();

    Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h")
            .create();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(outputOpt)
            .withOption(measureClassOpt)// .withOption(vectorClassOpt)
            .withOption(t1Opt).withOption(t2Opt).withOption(helpOpt).create();

    try {
        Parser parser = new Parser();
        parser.setGroup(group);
        CommandLine cmdLine = parser.parse(args);

        if (cmdLine.hasOption(helpOpt)) {
            CommandLineUtil.printHelp(group);
            return;
        }

        Path input = new Path(cmdLine.getValue(inputOpt, "testdata").toString());
        Path output = new Path(cmdLine.getValue(outputOpt, "output").toString());
        String measureClass = cmdLine
                .getValue(measureClassOpt, "org.apache.mahout.common.distance.EuclideanDistanceMeasure")
                .toString();

        // String className = cmdLine.getValue(vectorClassOpt,
        // "org.apache.mahout.math.RandomAccessSparseVector").toString();
        // Class<? extends Vector> vectorClass = Class.forName(className).asSubclass(Vector.class);
        double t1 = Double.parseDouble(cmdLine.getValue(t1Opt, "80").toString());
        double t2 = Double.parseDouble(cmdLine.getValue(t2Opt, "55").toString());

        runJob(input, output, measureClass, t1, t2);
    } catch (OptionException e) {
        Job.log.error("Exception", e);
        CommandLineUtil.printHelp(group);
    }
}

---

From source file:org.apache.mahout.clustering.syntheticcontrol.dirichlet.Job.java

@Override
public int run(String[] args) throws Exception {
    addInputOption();//  w ww  .  j  a v  a 2  s  .  c  o m
    addOutputOption();
    addOption(DefaultOptionCreator.maxIterationsOption().create());
    addOption(DefaultOptionCreator.numClustersOption().withRequired(true).create());
    addOption(DefaultOptionCreator.overwriteOption().create());
    addOption(new DefaultOptionBuilder().withLongName(DirichletDriver.ALPHA_OPTION).withRequired(false)
            .withShortName("m")
            .withArgument(new ArgumentBuilder().withName(DirichletDriver.ALPHA_OPTION).withDefault("1.0")
                    .withMinimum(1).withMaximum(1).create())
            .withDescription("The alpha0 value for the DirichletDistribution. Defaults to 1.0").create());
    addOption(new DefaultOptionBuilder().withLongName(DirichletDriver.MODEL_DISTRIBUTION_CLASS_OPTION)
            .withRequired(false).withShortName("md")
            .withArgument(new ArgumentBuilder().withName(DirichletDriver.MODEL_DISTRIBUTION_CLASS_OPTION)
                    .withDefault(GaussianClusterDistribution.class.getName()).withMinimum(1).withMaximum(1)
                    .create())
            .withDescription("The ModelDistribution class name. Defaults to GaussianClusterDistribution")
            .create());
    addOption(new DefaultOptionBuilder().withLongName(DirichletDriver.MODEL_PROTOTYPE_CLASS_OPTION)
            .withRequired(false).withShortName("mp")
            .withArgument(new ArgumentBuilder().withName("prototypeClass")
                    .withDefault(RandomAccessSparseVector.class.getName()).withMinimum(1).withMaximum(1)
                    .create())
            .withDescription(
                    "The ModelDistribution prototype Vector class name. Defaults to RandomAccessSparseVector")
            .create());
    addOption(DefaultOptionCreator.distanceMeasureOption().withRequired(false).create());
    addOption(DefaultOptionCreator.emitMostLikelyOption().create());
    addOption(DefaultOptionCreator.thresholdOption().create());

    Map<String, List<String>> argMap = parseArguments(args);
    if (argMap == null) {
        return -1;
    }

    Path input = getInputPath();
    Path output = getOutputPath();
    if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
        HadoopUtil.delete(getConf(), output);
    }
    String modelFactory = getOption(DirichletDriver.MODEL_DISTRIBUTION_CLASS_OPTION);
    String modelPrototype = getOption(DirichletDriver.MODEL_PROTOTYPE_CLASS_OPTION);
    String distanceMeasure = getOption(DefaultOptionCreator.DISTANCE_MEASURE_OPTION);
    int numModels = Integer.parseInt(getOption(DefaultOptionCreator.NUM_CLUSTERS_OPTION));
    int maxIterations = Integer.parseInt(getOption(DefaultOptionCreator.MAX_ITERATIONS_OPTION));
    boolean emitMostLikely = Boolean.parseBoolean(getOption(DefaultOptionCreator.EMIT_MOST_LIKELY_OPTION));
    double threshold = Double.parseDouble(getOption(DefaultOptionCreator.THRESHOLD_OPTION));
    double alpha0 = Double.parseDouble(getOption(DirichletDriver.ALPHA_OPTION));
    DistributionDescription description = new DistributionDescription(modelFactory, modelPrototype,
            distanceMeasure, 60);

    run(input, output, description, numModels, maxIterations, alpha0, emitMostLikely, threshold);
    return 0;
}

---

From source file:org.apache.mahout.clustering.syntheticcontrol.fuzzykmeans.Job.java

@Override
public int run(String[] args) throws Exception {
    addInputOption();//from  w  w w.  j a va2  s.  c  o m
    addOutputOption();
    addOption(DefaultOptionCreator.distanceMeasureOption().create());
    addOption(DefaultOptionCreator.convergenceOption().create());
    addOption(DefaultOptionCreator.maxIterationsOption().create());
    addOption(DefaultOptionCreator.overwriteOption().create());
    addOption(DefaultOptionCreator.t1Option().create());
    addOption(DefaultOptionCreator.t2Option().create());
    addOption(M_OPTION, M_OPTION, "coefficient normalization factor, must be greater than 1", true);

    Map<String, List<String>> argMap = parseArguments(args);
    if (argMap == null) {
        return -1;
    }

    Path input = getInputPath();
    Path output = getOutputPath();
    String measureClass = getOption(DefaultOptionCreator.DISTANCE_MEASURE_OPTION);
    if (measureClass == null) {
        measureClass = SquaredEuclideanDistanceMeasure.class.getName();
    }
    double convergenceDelta = Double.parseDouble(getOption(DefaultOptionCreator.CONVERGENCE_DELTA_OPTION));
    int maxIterations = Integer.parseInt(getOption(DefaultOptionCreator.MAX_ITERATIONS_OPTION));
    float fuzziness = Float.parseFloat(getOption(M_OPTION));

    addOption(new DefaultOptionBuilder().withLongName(M_OPTION).withRequired(true)
            .withArgument(new ArgumentBuilder().withName(M_OPTION).withMinimum(1).withMaximum(1).create())
            .withDescription("coefficient normalization factor, must be greater than 1").withShortName(M_OPTION)
            .create());
    if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
        HadoopUtil.delete(getConf(), output);
    }
    DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);
    double t1 = Double.parseDouble(getOption(DefaultOptionCreator.T1_OPTION));
    double t2 = Double.parseDouble(getOption(DefaultOptionCreator.T2_OPTION));
    run(getConf(), input, output, measure, t1, t2, maxIterations, fuzziness, convergenceDelta);
    return 0;
}

---

From source file:org.apache.mahout.clustering.syntheticcontrol.kmeans.Job.java

public static void main(String[] args) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = DefaultOptionCreator.inputOption().withRequired(false).create();
    Option outputOpt = DefaultOptionCreator.outputOption().withRequired(false).create();
    Option convergenceDeltaOpt = DefaultOptionCreator.convergenceOption().withRequired(false).create();
    Option maxIterationsOpt = DefaultOptionCreator.maxIterationsOption().withRequired(false).create();

    Option measureClassOpt = obuilder.withLongName("distance").withRequired(false)
            .withArgument(abuilder.withName("distance").withMinimum(1).withMaximum(1).create())
            .withDescription("The Distance Measure to use.  Default is SquaredEuclidean").withShortName("m")
            .create();//from  ww w.j ava  2  s . c o  m

    Option t1Opt = obuilder.withLongName("t1").withRequired(false)
            .withArgument(abuilder.withName("t1").withMinimum(1).withMaximum(1).create())
            .withDescription("The t1 value to use.").withShortName("m").create();
    Option t2Opt = obuilder.withLongName("t2").withRequired(false)
            .withArgument(abuilder.withName("t2").withMinimum(1).withMaximum(1).create())
            .withDescription("The t2 value to use.").withShortName("m").create();
    Option vectorClassOpt = obuilder.withLongName("vectorClass").withRequired(false)
            .withArgument(abuilder.withName("vectorClass").withMinimum(1).withMaximum(1).create())
            .withDescription("The Vector implementation class name.  Default is RandomAccessSparseVector.class")
            .withShortName("v").create();

    Option helpOpt = DefaultOptionCreator.helpOption();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(outputOpt)
            .withOption(measureClassOpt).withOption(convergenceDeltaOpt).withOption(maxIterationsOpt)
            .withOption(vectorClassOpt).withOption(t1Opt).withOption(t2Opt).withOption(helpOpt).create();
    try {
        Parser parser = new Parser();
        parser.setGroup(group);
        CommandLine cmdLine = parser.parse(args);

        if (cmdLine.hasOption(helpOpt)) {
            CommandLineUtil.printHelp(group);
            return;
        }
        Path input = new Path(cmdLine.getValue(inputOpt, "testdata").toString());
        Path output = new Path(cmdLine.getValue(outputOpt, "output").toString());
        String measureClass = cmdLine
                .getValue(measureClassOpt, "org.apache.mahout.common.distance.EuclideanDistanceMeasure")
                .toString();
        double t1 = Double.parseDouble(cmdLine.getValue(t1Opt, "80").toString());
        double t2 = Double.parseDouble(cmdLine.getValue(t2Opt, "55").toString());
        double convergenceDelta = Double.parseDouble(cmdLine.getValue(convergenceDeltaOpt, "0.5").toString());
        int maxIterations = Integer.parseInt(cmdLine.getValue(maxIterationsOpt, 10).toString());

        runJob(input, output, measureClass, t1, t2, convergenceDelta, maxIterations);
    } catch (OptionException e) {
        log.error("Exception", e);
        CommandLineUtil.printHelp(group);
    }
}

---

From source file:org.apache.mahout.clustering.syntheticcontrol.meanshift.Job.java

public static void main(String[] args) throws Exception {
    DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
    ArgumentBuilder abuilder = new ArgumentBuilder();
    GroupBuilder gbuilder = new GroupBuilder();

    Option inputOpt = DefaultOptionCreator.inputOption().withRequired(false).create();
    Option outputOpt = DefaultOptionCreator.outputOption().withRequired(false).create();
    Option convergenceDeltaOpt = DefaultOptionCreator.convergenceOption().withRequired(false).create();
    Option maxIterOpt = DefaultOptionCreator.maxIterationsOption().withRequired(false).create();
    Option helpOpt = DefaultOptionCreator.helpOption();

    Option modelOpt = obuilder.withLongName("distanceClass").withRequired(false).withShortName("d")
            .withArgument(abuilder.withName("distanceClass").withMinimum(1).withMaximum(1).create())
            .withDescription("The distance measure class name.").create();

    Option threshold1Opt = obuilder.withLongName("threshold_1").withRequired(false).withShortName("t1")
            .withArgument(abuilder.withName("threshold_1").withMinimum(1).withMaximum(1).create())
            .withDescription("The T1 distance threshold.").create();

    Option threshold2Opt = obuilder.withLongName("threshold_2").withRequired(false).withShortName("t2")
            .withArgument(abuilder.withName("threshold_2").withMinimum(1).withMaximum(1).create())
            .withDescription("The T1 distance threshold.").create();

    Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(outputOpt).withOption(modelOpt)
            .withOption(helpOpt).withOption(convergenceDeltaOpt).withOption(threshold1Opt)
            .withOption(maxIterOpt).withOption(threshold2Opt).create();

    try {/*from  w ww.j a v  a  2  s.  c o  m*/
        Parser parser = new Parser();
        parser.setGroup(group);
        CommandLine cmdLine = parser.parse(args);
        if (cmdLine.hasOption(helpOpt)) {
            CommandLineUtil.printHelp(group);
            return;
        }

        Path input = new Path(cmdLine.getValue(inputOpt, "testdata").toString());
        Path output = new Path(cmdLine.getValue(outputOpt, "output").toString());
        String measureClassName = cmdLine
                .getValue(modelOpt, "org.apache.mahout.common.distance.EuclideanDistanceMeasure").toString();
        double t1 = Double.parseDouble(cmdLine.getValue(threshold1Opt, "47.6").toString());
        double t2 = Double.parseDouble(cmdLine.getValue(threshold2Opt, "1").toString());
        double convergenceDelta = Double.parseDouble(cmdLine.getValue(convergenceDeltaOpt, "0.5").toString());
        int maxIterations = Integer.parseInt(cmdLine.getValue(maxIterOpt, "10").toString());
        runJob(input, output, measureClassName, t1, t2, convergenceDelta, maxIterations);
    } catch (OptionException e) {
        log.error("Exception parsing command line: ", e);
        CommandLineUtil.printHelp(group);
    }
}

---

From source file:org.apache.mahout.common.commandline.DefaultOptionCreator.java

/**
 * Returns a default command line option for clusters input directory
 * specification. Used by FuzzyKmeans, Kmeans
 *//*from  w  w  w . j  a  v a  2 s  . c  o m*/
public static DefaultOptionBuilder clustersInOption() {
    return new DefaultOptionBuilder().withLongName(CLUSTERS_IN_OPTION).withRequired(true)
            .withArgument(
                    new ArgumentBuilder().withName(CLUSTERS_IN_OPTION).withMinimum(1).withMaximum(1).create())
            .withDescription(
                    "The path to the initial clusters directory. Must be a SequenceFile of some type of Cluster")
            .withShortName("c");
}

---

From source file:org.apache.mahout.common.commandline.DefaultOptionCreator.java

/**
 * Returns a default command line option for specification of distance measure
 * class to use. Used by Canopy, FuzzyKmeans, Kmeans, MeanShift
 */// w ww  .  j  a va2  s  . com
public static DefaultOptionBuilder distanceMeasureOption() {
    return new DefaultOptionBuilder().withLongName(DISTANCE_MEASURE_OPTION).withRequired(false)
            .withShortName("dm")
            .withArgument(new ArgumentBuilder().withName(DISTANCE_MEASURE_OPTION)
                    .withDefault(SquaredEuclideanDistanceMeasure.class.getName()).withMinimum(1).withMaximum(1)
                    .create())
            .withDescription("The classname of the DistanceMeasure. Default is SquaredEuclidean");
}

---

From source file:org.apache.mahout.common.commandline.DefaultOptionCreator.java

/**
 * Returns a default command line option for specification of sequential or
 * parallel operation. Used by Canopy, FuzzyKmeans, Kmeans, MeanShift,
 * Dirichlet/* w w  w. j  a v a 2 s. c  o m*/
 */
public static DefaultOptionBuilder methodOption() {
    return new DefaultOptionBuilder().withLongName(METHOD_OPTION).withRequired(false).withShortName("xm")
            .withArgument(new ArgumentBuilder().withName(METHOD_OPTION).withDefault(MAPREDUCE_METHOD)
                    .withMinimum(1).withMaximum(1).create())
            .withDescription("The execution method to use: sequential or mapreduce. Default is mapreduce");
}

---

From source file:org.apache.mahout.common.commandline.DefaultOptionCreator.java

/**
 * Returns a default command line option for specification of T1. Used by
 * Canopy, MeanShift//from w  w  w .j  av a 2s  .  co  m
 */
public static DefaultOptionBuilder t1Option() {
    return new DefaultOptionBuilder().withLongName(T1_OPTION).withRequired(true)
            .withArgument(new ArgumentBuilder().withName(T1_OPTION).withMinimum(1).withMaximum(1).create())
            .withDescription("T1 threshold value").withShortName(T1_OPTION);
}

---

• «
• 1
• 2
• 3
• 4
• 5
• 6
• 7
• 8
• 9
• 10
• 11
• 12
• 13
• 14
• 15
• 16
• 17
• 18
• 19
• »