List of usage examples for org.apache.commons.configuration ConfigurationException printStackTrace
public void printStackTrace()
From source file:com.kantenkugel.kanzebot.core.config.GlobalConfigImpl.java
public static void main(String[] args) { try {//from w w w . j a v a 2 s . com Injector.inject(GlobalConfig.class, "instance", new GlobalConfigImpl(), null); System.out.println(GlobalConfig.getInstance().inAuthMode()); } catch (ConfigurationException e) { e.printStackTrace(); } }
From source file:edu.uw.sig.frames2owl.util.BatchConverter.java
/** * @param args//from w w w . j a v a 2 s. c o m */ public static void main(String[] args) { BatchConverter converter; try { converter = new BatchConverter("resource/ocdm/ocdm_batch.xml"); converter.runBatch(); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } }
From source file:com.github.ipaas.ideploy.plugin.util.XmlUtil.java
public static void main(String[] args) throws IOException { System.out.println(XmlUtil.getString( "D:/Users/TY-Chenql/runtime-EclipseApplication/crs_mave_ice/script/assembly.xml", "id", "sc")); try {//from w ww .j av a2s . co m XMLConfiguration config = new XMLConfiguration("D:/Users/TY-Chenql/workspace/crs_mave_ice/pom.xml"); // ?????? String str = config.getString("build.plugins.plugin.configuration.descriptors.descriptor"); // System.out.println(str); // // ?.???? // List<Object> names = config.getList("student.name"); // System.out.println(Arrays.toString(names.toArray())); // // ???a,b,c,d ??? // List<Object> titles = config.getList("title"); // System.out.println(Arrays.toString(titles.toArray())); // // ? ??[@??] ?? // String size = config.getString("ball[@size]"); // System.out.println(size); // // ???? ??(??) ?? // String id = config.getString("student(1)[@id]"); // System.out.println(id); // // String go = config.getString("student.name(0)[@go]"); // System.out.println(go); // /** // * ? tom [lily, lucy] [abc, cbc, bbc, bbs] 20 2 common1 // * // */ } catch (ConfigurationException e) { e.printStackTrace(); } }
From source file:edu.hawaii.soest.pacioos.text.TextSourceApp.java
/** * @param args/*from w w w . j a v a 2s . com*/ */ public static void main(String[] args) { String xmlConfiguration = null; if (args.length != 1) { log.error("Please provide the path to the instrument's XML configuration file " + "as a single parameter."); System.exit(1); } else { xmlConfiguration = args[0]; } try { textSource = TextSourceFactory.getSimpleTextSource(xmlConfiguration); if (textSource != null) { textSource.start(); } // Handle ctrl-c's and other abrupt death signals to the process Runtime.getRuntime().addShutdownHook(new Thread() { // stop the streaming process public void run() { log.info("Stopping the SimpleTextSource driver due to user request"); textSource.stop(); } }); } catch (ConfigurationException e) { if (log.isDebugEnabled()) { e.printStackTrace(); } log.error("There was a problem configuring the driver. The error message was: " + e.getMessage()); System.exit(1); } }
From source file:edu.uw.sig.frames2owl.util.BatchFromIncludeConverter.java
/** * @param args//from ww w .j a v a 2 s . c o m */ public static void main(String[] args) { BatchFromIncludeConverter converter; try { converter = new BatchFromIncludeConverter(args[0]); converter.runBatch(); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } }
From source file:mpaf.Main.java
public static void main(String[] args) { // Apache commons configuration CompositeConfiguration config = new CompositeConfiguration(); try {//from ww w . j a va 2s . c o m XMLConfiguration user = new XMLConfiguration("mpaf.properties.user.xml"); XMLConfiguration defaults = new XMLConfiguration("mpaf.properties.default.xml"); // careful configuration is read from top to bottom if you want a // config to overwrite the user config, add it as first element // also make it optional to load, check if the file exists and THEN // load it! if (user != null) config.addConfiguration(user); config.addConfiguration(defaults); } catch (ConfigurationException e1) { e1.printStackTrace(); } SqlHandler sqlH = null; sqlH = new SqlHandler(); sqlH.setDbtype(config.getString("db.type", "sqlite")); sqlH.setDbhost(config.getString("db.host", "127.0.0.1")); sqlH.setDbport(config.getString("db.port", "3306")); sqlH.setDbname(config.getString("db.name", "mpaf.db")); sqlH.setDbuser(config.getString("db.user")); sqlH.setDbpass(config.getString("db.password")); IceModel iceM = new IceModel(config); IceController iceC; try { iceC = new IceController(iceM, sqlH.getConnection()); } catch (ClassNotFoundException e1) { // TODO Auto-generated catch block e1.printStackTrace(); return; } catch (SQLException e1) { // TODO Auto-generated catch block e1.printStackTrace(); return; } Server server = new Server(); ConsoleParser parser = new ConsoleParser(iceC, iceM, server); new Thread(parser).start(); // will be called once a shutdown event is thrown(like ctrl+c or sigkill // etc.) ShutdownThread shutdown = new ShutdownThread(iceC); Runtime.getRuntime().addShutdownHook(new Thread(shutdown)); if (config.getBoolean("jetty.enabled")) { SocketConnector connector = new SocketConnector(); connector.setPort(config.getInt("jetty.ports.http", 10001)); server.setConnectors(new Connector[] { connector }); ServletContextHandler servletC = new ServletContextHandler(ServletContextHandler.SESSIONS); servletC.setContextPath("/"); servletC.setAttribute("sqlhandler", sqlH); servletC.setAttribute("iceController", iceC); servletC.setAttribute("iceModel", iceM); // To add a servlet: ServletHolder holder = new ServletHolder(new DefaultCacheServlet()); holder.setInitParameter("cacheControl", "max-age=3600,public"); holder.setInitParameter("resourceBase", "web"); servletC.addServlet(holder, "/"); servletC.addServlet(new ServletHolder(new ServerList()), "/serverlist"); servletC.addServlet(new ServletHolder(new ChannelList()), "/channellist"); servletC.addServlet(new ServletHolder(new HandlerList()), "/handlerlist"); servletC.addServlet(new ServletHolder(new ServerManage()), "/servermanage"); servletC.addServlet(new ServletHolder(new Login()), "/login"); servletC.addServlet(new ServletHolder(new Logout()), "/logout"); servletC.addServlet(new ServletHolder(new UserCreate()), "/usercreate"); servletC.addServlet(new ServletHolder(new UserInfo()), "/userinfo"); servletC.addServlet(new ServletHolder(new UserList()), "/userlist"); server.setHandler(servletC); try { server.start(); server.join(); } catch (Exception e) { e.printStackTrace(); } } }
From source file:ch.epfl.lsir.xin.test.MostPopularTest.java
/** * @param args//w w w .j a v a 2 s. c om */ public static void main(String[] args) throws Exception { // TODO Auto-generated method stub PrintWriter logger = new PrintWriter(".//results//MostPopular"); PropertiesConfiguration config = new PropertiesConfiguration(); config.setFile(new File(".//conf//MostPopular.properties")); try { config.load(); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Read rating data..."); DataLoaderFile loader = new DataLoaderFile(".//data//MoveLens100k.txt"); loader.readSimple(); DataSetNumeric dataset = loader.getDataset(); System.out.println("Number of ratings: " + dataset.getRatings().size() + " Number of users: " + dataset.getUserIDs().size() + " Number of items: " + dataset.getItemIDs().size()); logger.println("Number of ratings: " + dataset.getRatings().size() + ", Number of users: " + dataset.getUserIDs().size() + ", Number of items: " + dataset.getItemIDs().size()); logger.flush(); TrainTestSplitter splitter = new TrainTestSplitter(dataset); splitter.splitFraction(config.getDouble("TRAIN_FRACTION")); ArrayList<NumericRating> trainRatings = splitter.getTrain(); ArrayList<NumericRating> testRatings = splitter.getTest(); HashMap<String, Integer> userIDIndexMapping = new HashMap<String, Integer>(); HashMap<String, Integer> itemIDIndexMapping = new HashMap<String, Integer>(); //create rating matrix for (int i = 0; i < dataset.getUserIDs().size(); i++) { userIDIndexMapping.put(dataset.getUserIDs().get(i), i); } for (int i = 0; i < dataset.getItemIDs().size(); i++) { itemIDIndexMapping.put(dataset.getItemIDs().get(i), i); } RatingMatrix trainRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < trainRatings.size(); i++) { trainRatingMatrix.set(userIDIndexMapping.get(trainRatings.get(i).getUserID()), itemIDIndexMapping.get(trainRatings.get(i).getItemID()), trainRatings.get(i).getValue()); } RatingMatrix testRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < testRatings.size(); i++) { //only consider 5-star rating in the test set // if( testRatings.get(i).getValue() < 5 ) // continue; testRatingMatrix.set(userIDIndexMapping.get(testRatings.get(i).getUserID()), itemIDIndexMapping.get(testRatings.get(i).getItemID()), testRatings.get(i).getValue()); } System.out.println("Training: " + trainRatingMatrix.getTotalRatingNumber() + " vs Test: " + testRatingMatrix.getTotalRatingNumber()); logger.println("Initialize a most popular based recommendation model."); MostPopular algo = new MostPopular(trainRatingMatrix); algo.setLogger(logger); algo.build(); algo.saveModel(".//localModels//" + config.getString("NAME")); logger.println("Save the model."); logger.flush(); HashMap<Integer, ArrayList<ResultUnit>> results = new HashMap<Integer, ArrayList<ResultUnit>>(); for (int i = 0; i < testRatingMatrix.getRow(); i++) { ArrayList<ResultUnit> rec = algo.getRecommendationList(i); if (rec == null) continue; int total = testRatingMatrix.getUserRatingNumber(i); if (total == 0)//this user is ignored continue; results.put(i, rec); } RankResultGenerator generator = new RankResultGenerator(results, algo.getTopN(), testRatingMatrix, trainRatingMatrix); System.out.println("Precision@N: " + generator.getPrecisionN()); System.out.println("Recall@N: " + generator.getRecallN()); System.out.println("MAP@N: " + generator.getMAPN()); System.out.println("MRR@N: " + generator.getMRRN()); System.out.println("NDCG@N: " + generator.getNDCGN()); System.out.println("AUC@N: " + generator.getAUC()); logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + "\n" + "Precision@N: " + generator.getPrecisionN() + "\n" + "Recall@N: " + generator.getRecallN() + "\n" + "MAP@N: " + generator.getMAPN() + "\n" + "MRR@N: " + generator.getMRRN() + "\n" + "NDCG@N: " + generator.getNDCGN() + "\n" + "AUC@N: " + generator.getAUC()); logger.flush(); logger.close(); }
From source file:ch.epfl.lsir.xin.test.UserAverageTest.java
/** * @param args//w ww. j ava 2 s .c o m */ public static void main(String[] args) throws Exception { // TODO Auto-generated method stub PrintWriter logger = new PrintWriter(".//results//UserAverage"); PropertiesConfiguration config = new PropertiesConfiguration(); config.setFile(new File(".//conf//UserAverage.properties")); try { config.load(); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Read rating data..."); DataLoaderFile loader = new DataLoaderFile(".//data//MoveLens100k.txt"); loader.readSimple(); DataSetNumeric dataset = loader.getDataset(); System.out.println("Number of ratings: " + dataset.getRatings().size() + " Number of users: " + dataset.getUserIDs().size() + " Number of items: " + dataset.getItemIDs().size()); logger.println("Number of ratings: " + dataset.getRatings().size() + " Number of users: " + dataset.getUserIDs().size() + " Number of items: " + dataset.getItemIDs().size()); logger.flush(); double totalMAE = 0; double totalRMSE = 0; int F = 5; logger.println(F + "- folder cross validation."); ArrayList<ArrayList<NumericRating>> folders = new ArrayList<ArrayList<NumericRating>>(); for (int i = 0; i < F; i++) { folders.add(new ArrayList<NumericRating>()); } while (dataset.getRatings().size() > 0) { int index = new Random().nextInt(dataset.getRatings().size()); int r = new Random().nextInt(F); folders.get(r).add(dataset.getRatings().get(index)); dataset.getRatings().remove(index); } for (int folder = 1; folder <= F; folder++) { logger.println("Folder: " + folder); System.out.println("Folder: " + folder); ArrayList<NumericRating> trainRatings = new ArrayList<NumericRating>(); ArrayList<NumericRating> testRatings = new ArrayList<NumericRating>(); for (int i = 0; i < folders.size(); i++) { if (i == folder - 1)//test data { testRatings.addAll(folders.get(i)); } else {//training data trainRatings.addAll(folders.get(i)); } } //create rating matrix HashMap<String, Integer> userIDIndexMapping = new HashMap<String, Integer>(); HashMap<String, Integer> itemIDIndexMapping = new HashMap<String, Integer>(); for (int i = 0; i < dataset.getUserIDs().size(); i++) { userIDIndexMapping.put(dataset.getUserIDs().get(i), i); } for (int i = 0; i < dataset.getItemIDs().size(); i++) { itemIDIndexMapping.put(dataset.getItemIDs().get(i), i); } RatingMatrix trainRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < trainRatings.size(); i++) { trainRatingMatrix.set(userIDIndexMapping.get(trainRatings.get(i).getUserID()), itemIDIndexMapping.get(trainRatings.get(i).getItemID()), trainRatings.get(i).getValue()); } trainRatingMatrix.calculateGlobalAverage(); RatingMatrix testRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < testRatings.size(); i++) { testRatingMatrix.set(userIDIndexMapping.get(testRatings.get(i).getUserID()), itemIDIndexMapping.get(testRatings.get(i).getItemID()), testRatings.get(i).getValue()); } System.out.println("Training: " + trainRatingMatrix.getTotalRatingNumber() + " vs Test: " + testRatingMatrix.getTotalRatingNumber()); logger.println("Initialize a recommendation model based on user average method."); UserAverage algo = new UserAverage(trainRatingMatrix); algo.setLogger(logger); algo.build(); algo.saveModel(".//localModels//" + config.getString("NAME")); logger.println("Save the model."); System.out.println(trainRatings.size() + " vs. " + testRatings.size()); double RMSE = 0; double MAE = 0; int count = 0; for (int i = 0; i < testRatings.size(); i++) { NumericRating rating = testRatings.get(i); double prediction = algo.predict(userIDIndexMapping.get(rating.getUserID()), itemIDIndexMapping.get(rating.getItemID())); if (Double.isNaN(prediction)) { System.out.println("no prediction"); continue; } MAE = MAE + Math.abs(rating.getValue() - prediction); RMSE = RMSE + Math.pow((rating.getValue() - prediction), 2); count++; } MAE = MAE / count; RMSE = Math.sqrt(RMSE / count); logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " MAE: " + MAE + " RMSE: " + RMSE); logger.flush(); totalMAE = totalMAE + MAE; totalRMSE = totalRMSE + RMSE; } System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F); logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Final results: MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F); logger.flush(); logger.close(); //MAE: 0.8353035962363073 RMSE: 1.0422971886952053 (MovieLens 100k) }
From source file:integratedtoolkit.util.RuntimeConfigManager.java
public static void main(String[] args) { try {//w w w . java 2s .c o m RuntimeConfigManager config = new RuntimeConfigManager("/home/jorgee/it.properties"); config.setProjectFile("/home/jorgee/project.xml"); config.setResourcesFile("/home/jorgee/resources.xml"); config.setGraph(true); config.setTracing(false); config.setLog4jConfiguration("/home/jorgee/log4j.properties"); config.setGATBrokerAdaptor("sshtrilled"); config.setGATFileAdaptor("sshtrilled"); config.save(); config = new RuntimeConfigManager("/home/jorgee/it.properties"); System.out.println(ITConstants.IT_PROJ_FILE + "=" + config.getProjectFile()); System.out.println(ITConstants.IT_RES_FILE + "=" + config.getResourcesFile()); System.out.println(ITConstants.LOG4J + "=" + config.getLog4jConfiguration()); System.out.println(ITConstants.GAT_BROKER_ADAPTOR + config.getGATBrokerAdaptor()); System.out.println(ITConstants.GAT_FILE_ADAPTOR + "=" + config.getGATFileAdaptor()); System.out.println(ITConstants.IT_GRAPH + "=" + config.isGraph()); System.out.println(ITConstants.IT_TRACING + "=" + config.isTracing()); System.out.println(ITConstants.IT_TO_FILE + "=" + config.isToFile()); System.out.println(ITConstants.IT_LIB + "=" + config.getITLib()); System.out.println(ITConstants.IT_LANG + "=" + config.getLang()); System.out.println(ITConstants.IT_MONITOR + "=" + config.getMonitorInterval()); System.out.println(ITConstants.IT_INTERACT_PERIOD + "=" + config.getOptimisPeriod()); System.out.println(ITConstants.GAT_ADAPTOR + "=" + config.getGATAdaptor()); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } }
From source file:ch.epfl.lsir.xin.test.GlobalMeanTest.java
/** * @param args/*from w ww . java2s. co m*/ */ public static void main(String[] args) throws Exception { // TODO Auto-generated method stub PrintWriter logger = new PrintWriter(".//results//GlobalMean"); PropertiesConfiguration config = new PropertiesConfiguration(); config.setFile(new File("conf//GlobalMean.properties")); try { config.load(); } catch (ConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Read rating data..."); DataLoaderFile loader = new DataLoaderFile(".//data//MoveLens100k.txt"); loader.readSimple(); DataSetNumeric dataset = loader.getDataset(); System.out.println("Number of ratings: " + dataset.getRatings().size() + " Number of users: " + dataset.getUserIDs().size() + " Number of items: " + dataset.getItemIDs().size()); logger.println("Number of ratings: " + dataset.getRatings().size() + ", Number of users: " + dataset.getUserIDs().size() + ", Number of items: " + dataset.getItemIDs().size()); double totalMAE = 0; double totalRMSE = 0; int F = 5; logger.println(F + "- folder cross validation."); logger.flush(); ArrayList<ArrayList<NumericRating>> folders = new ArrayList<ArrayList<NumericRating>>(); for (int i = 0; i < F; i++) { folders.add(new ArrayList<NumericRating>()); } while (dataset.getRatings().size() > 0) { int index = new Random().nextInt(dataset.getRatings().size()); int r = new Random().nextInt(F); folders.get(r).add(dataset.getRatings().get(index)); dataset.getRatings().remove(index); } for (int folder = 1; folder <= F; folder++) { System.out.println("Folder: " + folder); logger.println("Folder: " + folder); ArrayList<NumericRating> trainRatings = new ArrayList<NumericRating>(); ArrayList<NumericRating> testRatings = new ArrayList<NumericRating>(); for (int i = 0; i < folders.size(); i++) { if (i == folder - 1)//test data { testRatings.addAll(folders.get(i)); } else {//training data trainRatings.addAll(folders.get(i)); } } //create rating matrix HashMap<String, Integer> userIDIndexMapping = new HashMap<String, Integer>(); HashMap<String, Integer> itemIDIndexMapping = new HashMap<String, Integer>(); for (int i = 0; i < dataset.getUserIDs().size(); i++) { userIDIndexMapping.put(dataset.getUserIDs().get(i), i); } for (int i = 0; i < dataset.getItemIDs().size(); i++) { itemIDIndexMapping.put(dataset.getItemIDs().get(i), i); } RatingMatrix trainRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < trainRatings.size(); i++) { trainRatingMatrix.set(userIDIndexMapping.get(trainRatings.get(i).getUserID()), itemIDIndexMapping.get(trainRatings.get(i).getItemID()), trainRatings.get(i).getValue()); } RatingMatrix testRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(), dataset.getItemIDs().size()); for (int i = 0; i < testRatings.size(); i++) { testRatingMatrix.set(userIDIndexMapping.get(testRatings.get(i).getUserID()), itemIDIndexMapping.get(testRatings.get(i).getItemID()), testRatings.get(i).getValue()); } System.out.println("Training: " + trainRatingMatrix.getTotalRatingNumber() + " vs Test: " + testRatingMatrix.getTotalRatingNumber()); logger.println("Initialize a recommendation model based on global average method."); GlobalAverage algo = new GlobalAverage(trainRatingMatrix); algo.setLogger(logger); algo.build(); algo.saveModel(".//localModels//" + config.getString("NAME")); logger.println("Save the model."); logger.flush(); System.out.println(trainRatings.size() + " vs. " + testRatings.size()); double RMSE = 0; double MAE = 0; int count = 0; for (int i = 0; i < testRatings.size(); i++) { NumericRating rating = testRatings.get(i); double prediction = algo.predict(rating.getUserID(), rating.getItemID()); if (Double.isNaN(prediction)) { System.out.println("no prediction"); continue; } MAE = MAE + Math.abs(rating.getValue() - prediction); RMSE = RMSE + Math.pow((rating.getValue() - prediction), 2); count++; } MAE = MAE / count; RMSE = Math.sqrt(RMSE / count); // System.out.println("MAE: " + MAE + " RMSE: " + RMSE); logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " MAE: " + MAE + " RMSE: " + RMSE); logger.flush(); totalMAE = totalMAE + MAE; totalRMSE = totalRMSE + RMSE; } System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F); logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Final results: MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F); logger.flush(); logger.close(); //MAE: 0.9338607074893257 RMSE: 1.1170971131112037 (MovieLens1M) //MAE: 0.9446876509332618 RMSE: 1.1256517870920375 (MovieLens100K) }