List of usage examples for org.apache.commons.cli2.builder DefaultOptionBuilder DefaultOptionBuilder
public DefaultOptionBuilder()
From source file:org.apache.mahout.utils.vectors.lucene.SeqFilePrint.java
public static void main(String[] args) throws OptionException { DefaultOptionBuilder obuilder = new DefaultOptionBuilder(); ArgumentBuilder abuilder = new ArgumentBuilder(); GroupBuilder gbuilder = new GroupBuilder(); Option inputOpt = obuilder.withLongName("inputFile").withRequired(true) .withArgument(abuilder.withName("inputFile").withMinimum(1).withMaximum(1).create()) .withDescription("The output of the dictionary as sequence file").withShortName("inputFile") .create();//from w w w . jav a 2 s.c o m Option outFileOpt = obuilder.withLongName("outFile").withRequired(true) .withArgument(abuilder.withName("outfolder").withMinimum(1).withMaximum(1).create()) .withDescription("The output of the dictionary as sequence file").withShortName("outFile").create(); Group group = gbuilder.withName("Options").withOption(inputOpt).withOption(outFileOpt).create(); SeqFilePrint seqFilePrint = new SeqFilePrint(); Parser parser = new Parser(); parser.setGroup(group); CommandLine cmdLine = parser.parse(args); if (cmdLine.hasOption(inputOpt)) { seqFilePrint.setInputSeqFile(cmdLine.getValue(inputOpt).toString()); } if (cmdLine.hasOption(outFileOpt)) { seqFilePrint.setOutFile(cmdLine.getValue(outFileOpt).toString()); } try { seqFilePrint.run(args); } catch (Exception ex) { Logger.getLogger(SeqFilePrint.class.getName()).log(Level.SEVERE, null, ex); } }
From source file:org.apache.mahout.vectorizer.SparseVectorsFromSequenceFiles.java
@Override public int run(String[] args) throws Exception { DefaultOptionBuilder obuilder = new DefaultOptionBuilder(); ArgumentBuilder abuilder = new ArgumentBuilder(); GroupBuilder gbuilder = new GroupBuilder(); Option inputDirOpt = DefaultOptionCreator.inputOption().create(); Option outputDirOpt = DefaultOptionCreator.outputOption().create(); Option minSupportOpt = obuilder.withLongName("minSupport") .withArgument(abuilder.withName("minSupport").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) Minimum Support. Default Value: 2").withShortName("s").create(); Option analyzerNameOpt = obuilder.withLongName("analyzerName") .withArgument(abuilder.withName("analyzerName").withMinimum(1).withMaximum(1).create()) .withDescription("The class name of the analyzer").withShortName("a").create(); Option chunkSizeOpt = obuilder.withLongName("chunkSize") .withArgument(abuilder.withName("chunkSize").withMinimum(1).withMaximum(1).create()) .withDescription("The chunkSize in MegaBytes. Default Value: 100MB").withShortName("chunk") .create();/*from w w w .j a v a2s .c o m*/ Option weightOpt = obuilder.withLongName("weight").withRequired(false) .withArgument(abuilder.withName("weight").withMinimum(1).withMaximum(1).create()) .withDescription("The kind of weight to use. Currently TF or TFIDF. Default: TFIDF") .withShortName("wt").create(); Option minDFOpt = obuilder.withLongName("minDF").withRequired(false) .withArgument(abuilder.withName("minDF").withMinimum(1).withMaximum(1).create()) .withDescription("The minimum document frequency. Default is 1").withShortName("md").create(); Option maxDFPercentOpt = obuilder.withLongName("maxDFPercent").withRequired(false) .withArgument(abuilder.withName("maxDFPercent").withMinimum(1).withMaximum(1).create()) .withDescription( "The max percentage of docs for the DF. Can be used to remove really high frequency terms." + " Expressed as an integer between 0 and 100. Default is 99. If maxDFSigma is also set, " + "it will override this value.") .withShortName("x").create(); Option maxDFSigmaOpt = obuilder.withLongName("maxDFSigma").withRequired(false) .withArgument(abuilder.withName("maxDFSigma").withMinimum(1).withMaximum(1).create()) .withDescription( "What portion of the tf (tf-idf) vectors to be used, expressed in times the standard deviation (sigma) " + "of the document frequencies of these vectors. Can be used to remove really high frequency terms." + " Expressed as a double value. Good value to be specified is 3.0. In case the value is less " + "than 0 no vectors will be filtered out. Default is -1.0. Overrides maxDFPercent") .withShortName("xs").create(); Option minLLROpt = obuilder.withLongName("minLLR").withRequired(false) .withArgument(abuilder.withName("minLLR").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional)The minimum Log Likelihood Ratio(Float) Default is " + LLRReducer.DEFAULT_MIN_LLR) .withShortName("ml").create(); Option numReduceTasksOpt = obuilder.withLongName("numReducers") .withArgument(abuilder.withName("numReducers").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) Number of reduce tasks. Default Value: 1").withShortName("nr") .create(); Option powerOpt = obuilder.withLongName("norm").withRequired(false) .withArgument(abuilder.withName("norm").withMinimum(1).withMaximum(1).create()) .withDescription( "The norm to use, expressed as either a float or \"INF\" if you want to use the Infinite norm. " + "Must be greater or equal to 0. The default is not to normalize") .withShortName("n").create(); Option logNormalizeOpt = obuilder.withLongName("logNormalize").withRequired(false) .withDescription("(Optional) Whether output vectors should be logNormalize. If set true else false") .withShortName("lnorm").create(); Option maxNGramSizeOpt = obuilder.withLongName("maxNGramSize").withRequired(false) .withArgument(abuilder.withName("ngramSize").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) The maximum size of ngrams to create" + " (2 = bigrams, 3 = trigrams, etc) Default Value:1") .withShortName("ng").create(); Option sequentialAccessVectorOpt = obuilder.withLongName("sequentialAccessVector").withRequired(false) .withDescription( "(Optional) Whether output vectors should be SequentialAccessVectors. If set true else false") .withShortName("seq").create(); Option namedVectorOpt = obuilder.withLongName("namedVector").withRequired(false) .withDescription("(Optional) Whether output vectors should be NamedVectors. If set true else false") .withShortName("nv").create(); Option overwriteOutput = obuilder.withLongName("overwrite").withRequired(false) .withDescription("If set, overwrite the output directory").withShortName("ow").create(); Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h") .create(); Group group = gbuilder.withName("Options").withOption(minSupportOpt).withOption(analyzerNameOpt) .withOption(chunkSizeOpt).withOption(outputDirOpt).withOption(inputDirOpt).withOption(minDFOpt) .withOption(maxDFSigmaOpt).withOption(maxDFPercentOpt).withOption(weightOpt).withOption(powerOpt) .withOption(minLLROpt).withOption(numReduceTasksOpt).withOption(maxNGramSizeOpt) .withOption(overwriteOutput).withOption(helpOpt).withOption(sequentialAccessVectorOpt) .withOption(namedVectorOpt).withOption(logNormalizeOpt).create(); try { Parser parser = new Parser(); parser.setGroup(group); parser.setHelpOption(helpOpt); CommandLine cmdLine = parser.parse(args); if (cmdLine.hasOption(helpOpt)) { CommandLineUtil.printHelp(group); return -1; } Path inputDir = new Path((String) cmdLine.getValue(inputDirOpt)); Path outputDir = new Path((String) cmdLine.getValue(outputDirOpt)); int chunkSize = 100; if (cmdLine.hasOption(chunkSizeOpt)) { chunkSize = Integer.parseInt((String) cmdLine.getValue(chunkSizeOpt)); } int minSupport = 2; if (cmdLine.hasOption(minSupportOpt)) { String minSupportString = (String) cmdLine.getValue(minSupportOpt); minSupport = Integer.parseInt(minSupportString); } int maxNGramSize = 1; if (cmdLine.hasOption(maxNGramSizeOpt)) { try { maxNGramSize = Integer.parseInt(cmdLine.getValue(maxNGramSizeOpt).toString()); } catch (NumberFormatException ex) { log.warn("Could not parse ngram size option"); } } log.info("Maximum n-gram size is: {}", maxNGramSize); if (cmdLine.hasOption(overwriteOutput)) { HadoopUtil.delete(getConf(), outputDir); } float minLLRValue = LLRReducer.DEFAULT_MIN_LLR; if (cmdLine.hasOption(minLLROpt)) { minLLRValue = Float.parseFloat(cmdLine.getValue(minLLROpt).toString()); } log.info("Minimum LLR value: {}", minLLRValue); int reduceTasks = 1; if (cmdLine.hasOption(numReduceTasksOpt)) { reduceTasks = Integer.parseInt(cmdLine.getValue(numReduceTasksOpt).toString()); } log.info("Number of reduce tasks: {}", reduceTasks); Class<? extends Analyzer> analyzerClass = StandardAnalyzer.class; if (cmdLine.hasOption(analyzerNameOpt)) { String className = cmdLine.getValue(analyzerNameOpt).toString(); analyzerClass = Class.forName(className).asSubclass(Analyzer.class); // try instantiating it, b/c there isn't any point in setting it if // you can't instantiate it AnalyzerUtils.createAnalyzer(analyzerClass); } boolean processIdf; if (cmdLine.hasOption(weightOpt)) { String wString = cmdLine.getValue(weightOpt).toString(); if ("tf".equalsIgnoreCase(wString)) { processIdf = false; } else if ("tfidf".equalsIgnoreCase(wString)) { processIdf = true; } else { throw new OptionException(weightOpt); } } else { processIdf = true; } int minDf = 1; if (cmdLine.hasOption(minDFOpt)) { minDf = Integer.parseInt(cmdLine.getValue(minDFOpt).toString()); } int maxDFPercent = 99; if (cmdLine.hasOption(maxDFPercentOpt)) { maxDFPercent = Integer.parseInt(cmdLine.getValue(maxDFPercentOpt).toString()); } double maxDFSigma = -1.0; if (cmdLine.hasOption(maxDFSigmaOpt)) { maxDFSigma = Double.parseDouble(cmdLine.getValue(maxDFSigmaOpt).toString()); } float norm = PartialVectorMerger.NO_NORMALIZING; if (cmdLine.hasOption(powerOpt)) { String power = cmdLine.getValue(powerOpt).toString(); if ("INF".equals(power)) { norm = Float.POSITIVE_INFINITY; } else { norm = Float.parseFloat(power); } } boolean logNormalize = false; if (cmdLine.hasOption(logNormalizeOpt)) { logNormalize = true; } log.info("Tokenizing documents in {}", inputDir); Configuration conf = getConf(); Path tokenizedPath = new Path(outputDir, DocumentProcessor.TOKENIZED_DOCUMENT_OUTPUT_FOLDER); //TODO: move this into DictionaryVectorizer , and then fold SparseVectorsFrom with EncodedVectorsFrom // to have one framework for all of this. DocumentProcessor.tokenizeDocuments(inputDir, analyzerClass, tokenizedPath, conf); boolean sequentialAccessOutput = false; if (cmdLine.hasOption(sequentialAccessVectorOpt)) { sequentialAccessOutput = true; } boolean namedVectors = false; if (cmdLine.hasOption(namedVectorOpt)) { namedVectors = true; } boolean shouldPrune = maxDFSigma >= 0.0 || maxDFPercent > 0.00; String tfDirName = shouldPrune ? DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER + "-toprune" : DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER; log.info("Creating Term Frequency Vectors"); if (processIdf) { DictionaryVectorizer.createTermFrequencyVectors(tokenizedPath, outputDir, tfDirName, conf, minSupport, maxNGramSize, minLLRValue, -1.0f, false, reduceTasks, chunkSize, sequentialAccessOutput, namedVectors); } else { DictionaryVectorizer.createTermFrequencyVectors(tokenizedPath, outputDir, tfDirName, conf, minSupport, maxNGramSize, minLLRValue, norm, logNormalize, reduceTasks, chunkSize, sequentialAccessOutput, namedVectors); } Pair<Long[], List<Path>> docFrequenciesFeatures = null; // Should document frequency features be processed if (shouldPrune || processIdf) { log.info("Calculating IDF"); docFrequenciesFeatures = TFIDFConverter.calculateDF(new Path(outputDir, tfDirName), outputDir, conf, chunkSize); } long maxDF = maxDFPercent; //if we are pruning by std dev, then this will get changed if (shouldPrune) { long vectorCount = docFrequenciesFeatures.getFirst()[1]; if (maxDFSigma >= 0.0) { Path dfDir = new Path(outputDir, TFIDFConverter.WORDCOUNT_OUTPUT_FOLDER); Path stdCalcDir = new Path(outputDir, HighDFWordsPruner.STD_CALC_DIR); // Calculate the standard deviation double stdDev = BasicStats.stdDevForGivenMean(dfDir, stdCalcDir, 0.0, conf); maxDF = (int) (100.0 * maxDFSigma * stdDev / vectorCount); } long maxDFThreshold = (long) (vectorCount * (maxDF / 100.0f)); // Prune the term frequency vectors Path tfDir = new Path(outputDir, tfDirName); Path prunedTFDir = new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER); Path prunedPartialTFDir = new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER + "-partial"); log.info("Pruning"); if (processIdf) { HighDFWordsPruner.pruneVectors(tfDir, prunedTFDir, prunedPartialTFDir, maxDFThreshold, minDf, conf, docFrequenciesFeatures, -1.0f, false, reduceTasks); } else { HighDFWordsPruner.pruneVectors(tfDir, prunedTFDir, prunedPartialTFDir, maxDFThreshold, minDf, conf, docFrequenciesFeatures, norm, logNormalize, reduceTasks); } HadoopUtil.delete(new Configuration(conf), tfDir); } if (processIdf) { TFIDFConverter.processTfIdf(new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER), outputDir, conf, docFrequenciesFeatures, minDf, maxDF, norm, logNormalize, sequentialAccessOutput, namedVectors, reduceTasks); } } catch (OptionException e) { log.error("Exception", e); CommandLineUtil.printHelp(group); } return 0; }
From source file:org.mzd.shap.spring.cli.CommandLineApplication.java
public static DefaultOptionBuilder buildOption() { return new DefaultOptionBuilder(); }
From source file:org.opencloudengine.flamingo.mapreduce.core.AbstractJob.java
/** * ? ? . ? ? .//w ww . j a va 2s . c o m * required. * * @param name ??? '--'? prefix ? ? * @param shortName ??? '--'? prefix ? ? ? * @param description ??? ? ? * @param hasArg ?? <tt>true</tt> * @param required ?? <tt>true</tt> * @param defaultValue ??? . <tt>null</tt>? . * @return */ protected static Option buildOption(String name, String shortName, String description, boolean hasArg, boolean required, String defaultValue) { DefaultOptionBuilder optBuilder = new DefaultOptionBuilder().withLongName(name).withDescription(description) .withRequired(required); if (shortName != null) { optBuilder.withShortName(shortName); } if (hasArg) { ArgumentBuilder argBuilder = new ArgumentBuilder().withName(name).withMinimum(1).withMaximum(1); if (defaultValue != null) { argBuilder = argBuilder.withDefault(defaultValue); } optBuilder.withArgument(argBuilder.create()); } return optBuilder.create(); }
From source file:org.opencloudengine.flamingo.mapreduce.util.DefaultOptionCreator.java
/** * ??? ?? ? ?.//ww w . j a v a 2 s. c o m * * @return ?? */ public static Option helpOption() { return new DefaultOptionBuilder().withLongName("help").withDescription("??? .") .withShortName("h").create(); }
From source file:org.opencloudengine.flamingo.mapreduce.util.DefaultOptionCreator.java
/** * ??? ? ?./*from ww w. j av a2 s.com*/ * * @return */ public static DefaultOptionBuilder inputOption() { return new DefaultOptionBuilder().withLongName(INPUT_OPTION).withRequired(false).withShortName("i") .withArgument(new ArgumentBuilder().withName(INPUT_OPTION).withMinimum(1).withMaximum(1).create()) .withDescription("MapReduce Job? "); }
From source file:org.opencloudengine.flamingo.mapreduce.util.DefaultOptionCreator.java
/** * ??? ? ?.//from w ww. j a va 2s . c om * * @return */ public static DefaultOptionBuilder outputOption() { return new DefaultOptionBuilder().withLongName(OUTPUT_OPTION).withRequired(false).withShortName("o") .withArgument(new ArgumentBuilder().withName(OUTPUT_OPTION).withMinimum(1).withMaximum(1).create()) .withDescription("MapReduce Job? "); }
From source file:org.rvsnoop.ui.RvSnoopApplication.java
@Override protected void initialize(String[] args) { ensureJavaVersionIsValid();//from w ww . j a v a2s. c o m configureLookAndFeel(); logger.info(getString("info.appStarted")); Runtime.getRuntime().addShutdownHook(new Thread(new ShutdownHookTask(), "shutdownHook")); MultiLineToolTipUI.configure(); Option helpOption = new DefaultOptionBuilder().withShortName("h").withLongName("help") .withDescription(getString("CLI.helpDescription")).create(); Option projectOption = new DefaultOptionBuilder().withShortName("p").withLongName("project") .withDescription(getString("CLI.projectDescription")).create(); CommandLine line = parseCommandLine(args, helpOption, projectOption); injector = Guice.createInjector(new GuiModule()); injector.injectMembers(this); initialProjectFile = loadProjectIfValid(projectOption, line); }
From source file:org.rzo.yajsw.WrapperExe.java
/** * Parses the command./*www . j a v a2 s . c om*/ * * @param args * the args */ private static void parseCommand(String[] args) { Parser parser = new Parser(); // configure a HelpFormatter HelpFormatter hf = new HelpFormatter(); DefaultOptionBuilder oBuilder = new DefaultOptionBuilder(); ; // configure a parser Parser p = new Parser(); p.setGroup(group); p.setHelpFormatter(hf); p.setHelpOption(oBuilder.withLongName("help").withShortName("?").create()); cl = p.parseAndHelp(args); // abort application if no CommandLine was parsed if (cl == null) { System.exit(-1); } cmds = cl.getOptions(); try { confFile = (String) cl.getValue(CONF_FILE); } catch (Exception ex) { System.out.println("no wrapper config file found "); } try { defaultFile = (String) cl.getValue(cl.getOption("-d")); if (defaultFile != null) defaultFile = new File(defaultFile).getCanonicalPath(); } catch (Exception ex) { // no defaults -> maybe ok } properties = cl.getValues(PROPERTIES); }
From source file:parse_wikipedia.ParseWikipedia.java
public static void main(String[] args) throws IOException { DefaultOptionBuilder obuilder = new DefaultOptionBuilder(); GroupBuilder gbuilder = new GroupBuilder(); Option dirInputPathOpt = DefaultOptionCreator.inputOption().create(); Option dirOutputPathOpt = DefaultOptionCreator.outputOption().create(); Group group = gbuilder.withName("Options").withOption(dirInputPathOpt).withOption(dirOutputPathOpt) .create();//from w w w . ja v a 2 s .co m Parser parser = new Parser(); parser.setGroup(group); try { CommandLine cmdLine = parser.parse(args); String inputPath = (String) cmdLine.getValue(dirInputPathOpt); String outputPath = (String) cmdLine.getValue(dirOutputPathOpt); runJob(inputPath, outputPath); } catch (OptionException | InterruptedException | ClassNotFoundException e) { log.error("Exception", e); } }