Example usage for java.util HashMap HashMap

List of usage examples for java.util HashMap HashMap

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Introduction

In this page you can find the example usage for java.util HashMap HashMap.

Prototype

public HashMap()

Source Link

Document

Constructs an empty HashMap with the default initial capacity (16) and the default load factor (0.75).

Usage

From source file:ch.epfl.lsir.xin.test.ItemBasedCFTest.java

/**
 * @param args/*from  www .j  av  a2s.c  o m*/
 */
public static void main(String[] args) throws Exception {
    // TODO Auto-generated method stub

    PrintWriter logger = new PrintWriter(".//results//ItemBasedCF");
    PropertiesConfiguration config = new PropertiesConfiguration();
    config.setFile(new File(".//conf//ItemBasedCF.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;
    double totalPrecision = 0;
    double totalRecall = 0;
    double totalMAP = 0;
    double totalNDCG = 0;
    double totalMRR = 0;
    double totalAUC = 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();
        trainRatingMatrix.calculateItemsMean();
        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 item based collaborative filtering recommendation model.");
        ItemBasedCF algo = new ItemBasedCF(trainRatingMatrix);
        algo.setLogger(logger);
        algo.build();//if read local model, no need to build the model
        algo.saveModel(".//localModels//" + config.getString("NAME"));
        logger.println("Save the model.");
        logger.flush();

        //rating prediction accuracy
        double RMSE = 0;
        double MAE = 0;
        double precision = 0;
        double recall = 0;
        double map = 0;
        double ndcg = 0;
        double mrr = 0;
        double auc = 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()), false);
            if (prediction > algo.getMaxRating())
                prediction = algo.getMaxRating();
            if (prediction < algo.getMinRating())
                prediction = algo.getMinRating();

            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);
        totalMAE = totalMAE + MAE;
        totalRMSE = totalRMSE + RMSE;
        System.out.println("Folder --- MAE: " + MAE + " RMSE: " + RMSE);
        logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Folder --- MAE: "
                + MAE + " RMSE: " + RMSE);

        //ranking accuracy
        if (algo.getTopN() > 0) {
            HashMap<Integer, ArrayList<ResultUnit>> results = new HashMap<Integer, ArrayList<ResultUnit>>();
            for (int i = 0; i < trainRatingMatrix.getRow(); i++) {
                //               ArrayList<ResultUnit> rec = algo.getRecommendationList(i);
                //               results.put(i, rec);
                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);
            precision = generator.getPrecisionN();
            totalPrecision = totalPrecision + precision;
            recall = generator.getRecallN();
            totalRecall = totalRecall + recall;
            map = generator.getMAPN();
            totalMAP = totalMAP + map;
            ndcg = generator.getNDCGN();
            totalNDCG = totalNDCG + ndcg;
            mrr = generator.getMRRN();
            totalMRR = totalMRR + mrr;
            auc = generator.getAUC();
            totalAUC = totalAUC + auc;
            System.out.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
            logger.append("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc + "\n");
        }
    }

    System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F);
    System.out.println("Precision@N: " + totalPrecision / F);
    System.out.println("Recall@N: " + totalRecall / F);
    System.out.println("MAP@N: " + totalMAP / F);
    System.out.println("MRR@N: " + totalMRR / F);
    System.out.println("NDCG@N: " + totalNDCG / F);
    System.out.println("AUC@N: " + totalAUC / F);
    System.out.println("similarity: " + config.getString("SIMILARITY"));
    //MAE: 0.7227232762922241 RMSE: 0.9225576790122603 (MovieLens 100K, shrinkage 2500, neighbor size 40, PCC)
    //MAE: 0.7250636319353241 RMSE: 0.9242305485411567 (MovieLens 100K, shrinkage 25, neighbor size 40, PCC)
    //MAE: 0.7477213243604459 RMSE: 0.9512195004171138 (MovieLens 100K, shrinkage 2500, neighbor size 40, COSINE)

    logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + "\n" + "MAE: "
            + totalMAE / F + " RMSE: " + totalRMSE / F + "\n" + "Precision@N: " + totalPrecision / F + "\n"
            + "Recall@N: " + totalRecall / F + "\n" + "MAP@N: " + totalMAP / F + "\n" + "MRR@N: " + totalMRR / F
            + "\n" + "NDCG@N: " + totalNDCG / F + "\n" + "AUC@N: " + totalAUC / F);
    logger.flush();
    logger.close();
}

From source file:fr.inria.atlanmod.kyanos.benchmarks.ase2015.NeoEMFMapQueryGrabats09.java

public static void main(String[] args) {
    Options options = new Options();

    Option inputOpt = OptionBuilder.create(IN);
    inputOpt.setArgName("INPUT");
    inputOpt.setDescription("Input Kyanos resource directory");
    inputOpt.setArgs(1);/*from w ww. j  ava  2 s .com*/
    inputOpt.setRequired(true);

    Option inClassOpt = OptionBuilder.create(EPACKAGE_CLASS);
    inClassOpt.setArgName("CLASS");
    inClassOpt.setDescription("FQN of EPackage implementation class");
    inClassOpt.setArgs(1);
    inClassOpt.setRequired(true);

    Option optFileOpt = OptionBuilder.create(OPTIONS_FILE);
    optFileOpt.setArgName("FILE");
    optFileOpt.setDescription("Properties file holding the options to be used in the Kyanos Resource");
    optFileOpt.setArgs(1);

    options.addOption(inputOpt);
    options.addOption(inClassOpt);
    options.addOption(optFileOpt);

    CommandLineParser parser = new PosixParser();

    try {
        PersistenceBackendFactoryRegistry.getFactories().put(NeoMapURI.NEO_MAP_SCHEME,
                new MapPersistenceBackendFactory());

        CommandLine commandLine = parser.parse(options, args);

        URI uri = NeoMapURI.createNeoMapURI(new File(commandLine.getOptionValue(IN)));

        Class<?> inClazz = NeoEMFMapQueryGrabats09.class.getClassLoader()
                .loadClass(commandLine.getOptionValue(EPACKAGE_CLASS));
        inClazz.getMethod("init").invoke(null);

        ResourceSet resourceSet = new ResourceSetImpl();
        resourceSet.getResourceFactoryRegistry().getProtocolToFactoryMap().put(NeoMapURI.NEO_MAP_SCHEME,
                PersistentResourceFactory.eINSTANCE);

        Resource resource = resourceSet.createResource(uri);

        Map<String, Object> loadOpts = new HashMap<String, Object>();

        if (commandLine.hasOption(OPTIONS_FILE)) {
            Properties properties = new Properties();
            properties.load(new FileInputStream(new File(commandLine.getOptionValue(OPTIONS_FILE))));
            for (final Entry<Object, Object> entry : properties.entrySet()) {
                loadOpts.put((String) entry.getKey(), (String) entry.getValue());
            }
        }
        // Add the LoadedObjectCounter store
        List<StoreOption> storeOptions = new ArrayList<StoreOption>();
        //         storeOptions.add(PersistentResourceOptions.EStoreOption.LOADED_OBJECT_COUNTER_LOGGING);
        storeOptions.add(MapResourceOptions.EStoreMapOption.AUTOCOMMIT);
        storeOptions.add(PersistentResourceOptions.EStoreOption.ESTRUCUTRALFEATURE_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.IS_SET_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.SIZE_CACHING);
        loadOpts.put(PersistentResourceOptions.STORE_OPTIONS, storeOptions);
        resource.load(loadOpts);
        {
            Runtime.getRuntime().gc();
            long initialUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory before query: {0}",
                    MessageUtil.byteCountToDisplaySize(initialUsedMemory)));
            LOG.log(Level.INFO, "Start query");
            long begin = System.currentTimeMillis();
            EList<ClassDeclaration> list = ASE2015JavaQueries.grabats09(resource);
            long end = System.currentTimeMillis();
            LOG.log(Level.INFO, "End query");
            LOG.log(Level.INFO, MessageFormat.format("Query result contains {0} elements", list.size()));
            LOG.log(Level.INFO, MessageFormat.format("Time spent: {0}", MessageUtil.formatMillis(end - begin)));
            Runtime.getRuntime().gc();
            long finalUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory after query: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory)));
            LOG.log(Level.INFO, MessageFormat.format("Memory use increase: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory - initialUsedMemory)));
        }

        if (resource instanceof PersistentResourceImpl) {
            PersistentResourceImpl.shutdownWithoutUnload((PersistentResourceImpl) resource);
        } else {
            resource.unload();
        }

    } catch (ParseException e) {
        MessageUtil.showError(e.toString());
        MessageUtil.showError("Current arguments: " + Arrays.toString(args));
        HelpFormatter formatter = new HelpFormatter();
        formatter.printHelp("java -jar <this-file.jar>", options, true);
    } catch (Throwable e) {
        MessageUtil.showError(e.toString());
    }
}

From source file:fr.inria.atlanmod.kyanos.benchmarks.ase2015.NeoEMFMapQueryGetBranchStatements.java

public static void main(String[] args) {
    Options options = new Options();

    Option inputOpt = OptionBuilder.create(IN);
    inputOpt.setArgName("INPUT");
    inputOpt.setDescription("Input Kyanos resource directory");
    inputOpt.setArgs(1);//from   w  w w . j  a  va2 s.co  m
    inputOpt.setRequired(true);

    Option inClassOpt = OptionBuilder.create(EPACKAGE_CLASS);
    inClassOpt.setArgName("CLASS");
    inClassOpt.setDescription("FQN of EPackage implementation class");
    inClassOpt.setArgs(1);
    inClassOpt.setRequired(true);

    Option optFileOpt = OptionBuilder.create(OPTIONS_FILE);
    optFileOpt.setArgName("FILE");
    optFileOpt.setDescription("Properties file holding the options to be used in the Kyanos Resource");
    optFileOpt.setArgs(1);

    options.addOption(inputOpt);
    options.addOption(inClassOpt);
    options.addOption(optFileOpt);

    CommandLineParser parser = new PosixParser();

    try {
        PersistenceBackendFactoryRegistry.getFactories().put(NeoMapURI.NEO_MAP_SCHEME,
                new MapPersistenceBackendFactory());

        CommandLine commandLine = parser.parse(options, args);

        URI uri = NeoMapURI.createNeoMapURI(new File(commandLine.getOptionValue(IN)));

        Class<?> inClazz = NeoEMFMapQueryGetBranchStatements.class.getClassLoader()
                .loadClass(commandLine.getOptionValue(EPACKAGE_CLASS));
        inClazz.getMethod("init").invoke(null);

        ResourceSet resourceSet = new ResourceSetImpl();
        resourceSet.getResourceFactoryRegistry().getProtocolToFactoryMap().put(NeoMapURI.NEO_MAP_SCHEME,
                PersistentResourceFactory.eINSTANCE);

        Resource resource = resourceSet.createResource(uri);

        Map<String, Object> loadOpts = new HashMap<String, Object>();

        if (commandLine.hasOption(OPTIONS_FILE)) {
            Properties properties = new Properties();
            properties.load(new FileInputStream(new File(commandLine.getOptionValue(OPTIONS_FILE))));
            for (final Entry<Object, Object> entry : properties.entrySet()) {
                loadOpts.put((String) entry.getKey(), (String) entry.getValue());
            }
        }
        // Add the LoadedObjectCounter store
        List<StoreOption> storeOptions = new ArrayList<StoreOption>();
        //         storeOptions.add(PersistentResourceOptions.EStoreOption.LOADED_OBJECT_COUNTER_LOGGING);
        storeOptions.add(MapResourceOptions.EStoreMapOption.AUTOCOMMIT);
        storeOptions.add(PersistentResourceOptions.EStoreOption.ESTRUCUTRALFEATURE_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.IS_SET_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.SIZE_CACHING);
        loadOpts.put(PersistentResourceOptions.STORE_OPTIONS, storeOptions);
        resource.load(loadOpts);
        {
            Runtime.getRuntime().gc();
            long initialUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory before query: {0}",
                    MessageUtil.byteCountToDisplaySize(initialUsedMemory)));
            LOG.log(Level.INFO, "Start query");
            long begin = System.currentTimeMillis();
            Set<TextElement> list = ASE2015JavaQueries.getCommentsTagContent(resource);
            long end = System.currentTimeMillis();
            LOG.log(Level.INFO, "End query");
            LOG.log(Level.INFO, MessageFormat.format("Query result contains {0} elements", list.size()));
            LOG.log(Level.INFO, MessageFormat.format("Time spent: {0}", MessageUtil.formatMillis(end - begin)));
            Runtime.getRuntime().gc();
            long finalUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory after query: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory)));
            LOG.log(Level.INFO, MessageFormat.format("Memory use increase: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory - initialUsedMemory)));
        }

        if (resource instanceof PersistentResourceImpl) {
            PersistentResourceImpl.shutdownWithoutUnload((PersistentResourceImpl) resource);
        } else {
            resource.unload();
        }

    } catch (ParseException e) {
        MessageUtil.showError(e.toString());
        MessageUtil.showError("Current arguments: " + Arrays.toString(args));
        HelpFormatter formatter = new HelpFormatter();
        formatter.printHelp("java -jar <this-file.jar>", options, true);
    } catch (Throwable e) {
        MessageUtil.showError(e.toString());
    }
}

From source file:fr.inria.atlanmod.kyanos.benchmarks.ase2015.NeoEMFMapQueryThrownExceptions.java

public static void main(String[] args) {
    Options options = new Options();

    Option inputOpt = OptionBuilder.create(IN);
    inputOpt.setArgName("INPUT");
    inputOpt.setDescription("Input Kyanos resource directory");
    inputOpt.setArgs(1);//from   w ww.j  a va  2 s . c  o m
    inputOpt.setRequired(true);

    Option inClassOpt = OptionBuilder.create(EPACKAGE_CLASS);
    inClassOpt.setArgName("CLASS");
    inClassOpt.setDescription("FQN of EPackage implementation class");
    inClassOpt.setArgs(1);
    inClassOpt.setRequired(true);

    Option optFileOpt = OptionBuilder.create(OPTIONS_FILE);
    optFileOpt.setArgName("FILE");
    optFileOpt.setDescription("Properties file holding the options to be used in the Kyanos Resource");
    optFileOpt.setArgs(1);

    options.addOption(inputOpt);
    options.addOption(inClassOpt);
    options.addOption(optFileOpt);

    CommandLineParser parser = new PosixParser();

    try {
        PersistenceBackendFactoryRegistry.getFactories().put(NeoMapURI.NEO_MAP_SCHEME,
                new MapPersistenceBackendFactory());

        CommandLine commandLine = parser.parse(options, args);

        URI uri = NeoMapURI.createNeoMapURI(new File(commandLine.getOptionValue(IN)));

        Class<?> inClazz = NeoEMFMapQueryThrownExceptions.class.getClassLoader()
                .loadClass(commandLine.getOptionValue(EPACKAGE_CLASS));
        inClazz.getMethod("init").invoke(null);

        ResourceSet resourceSet = new ResourceSetImpl();
        resourceSet.getResourceFactoryRegistry().getProtocolToFactoryMap().put(NeoMapURI.NEO_MAP_SCHEME,
                PersistentResourceFactory.eINSTANCE);

        Resource resource = resourceSet.createResource(uri);

        Map<String, Object> loadOpts = new HashMap<String, Object>();

        if (commandLine.hasOption(OPTIONS_FILE)) {
            Properties properties = new Properties();
            properties.load(new FileInputStream(new File(commandLine.getOptionValue(OPTIONS_FILE))));
            for (final Entry<Object, Object> entry : properties.entrySet()) {
                loadOpts.put((String) entry.getKey(), (String) entry.getValue());
            }
        }
        // Add the LoadedObjectCounter store
        List<StoreOption> storeOptions = new ArrayList<StoreOption>();
        //         storeOptions.add(PersistentResourceOptions.EStoreOption.LOADED_OBJECT_COUNTER_LOGGING);
        storeOptions.add(MapResourceOptions.EStoreMapOption.AUTOCOMMIT);
        storeOptions.add(PersistentResourceOptions.EStoreOption.ESTRUCUTRALFEATURE_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.IS_SET_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.SIZE_CACHING);
        loadOpts.put(PersistentResourceOptions.STORE_OPTIONS, storeOptions);
        resource.load(loadOpts);
        {
            Runtime.getRuntime().gc();
            long initialUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory before query: {0}",
                    MessageUtil.byteCountToDisplaySize(initialUsedMemory)));
            LOG.log(Level.INFO, "Start query");
            long begin = System.currentTimeMillis();
            EList<TypeAccess> list = ASE2015JavaQueries.getThrownExceptions(resource);
            long end = System.currentTimeMillis();
            LOG.log(Level.INFO, "End query");
            LOG.log(Level.INFO, MessageFormat.format("Query result contains {0} elements", list.size()));
            LOG.log(Level.INFO, MessageFormat.format("Time spent: {0}", MessageUtil.formatMillis(end - begin)));
            Runtime.getRuntime().gc();
            long finalUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory after query: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory)));
            LOG.log(Level.INFO, MessageFormat.format("Memory use increase: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory - initialUsedMemory)));
        }

        if (resource instanceof PersistentResourceImpl) {
            PersistentResourceImpl.shutdownWithoutUnload((PersistentResourceImpl) resource);
        } else {
            resource.unload();
        }

    } catch (ParseException e) {
        MessageUtil.showError(e.toString());
        MessageUtil.showError("Current arguments: " + Arrays.toString(args));
        HelpFormatter formatter = new HelpFormatter();
        formatter.printHelp("java -jar <this-file.jar>", options, true);
    } catch (Throwable e) {
        MessageUtil.showError(e.toString());
    }
}

From source file:org.kuali.student.git.importer.ConvertBuildTagBranchesToGitTags.java

/**
 * @param args/*  w ww .java  2 s. co m*/
 */
public static void main(String[] args) {

    if (args.length < 3 || args.length > 6) {
        System.err.println("USAGE: <git repository> <bare> <ref mode> [<ref prefix> <username> <password>]");
        System.err.println("\t<bare> : 0 (false) or 1 (true)");
        System.err.println("\t<ref mode> : local or name of remote");
        System.err.println("\t<ref prefix> : refs/heads (default) or say refs/remotes/origin (test clone)");
        System.exit(-1);
    }

    boolean bare = false;

    if (args[1].trim().equals("1")) {
        bare = true;
    }

    String remoteName = args[2].trim();

    String refPrefix = Constants.R_HEADS;

    if (args.length == 4)
        refPrefix = args[3].trim();

    String userName = null;
    String password = null;

    if (args.length == 5)
        userName = args[4].trim();

    if (args.length == 6)
        password = args[5].trim();

    try {

        Repository repo = GitRepositoryUtils.buildFileRepository(new File(args[0]).getAbsoluteFile(), false,
                bare);

        Git git = new Git(repo);

        ObjectInserter objectInserter = repo.newObjectInserter();

        Collection<Ref> repositoryHeads = repo.getRefDatabase().getRefs(refPrefix).values();

        RevWalk rw = new RevWalk(repo);

        Map<String, ObjectId> tagNameToTagId = new HashMap<>();

        Map<String, Ref> tagNameToRef = new HashMap<>();

        for (Ref ref : repositoryHeads) {

            String branchName = ref.getName().substring(refPrefix.length() + 1);

            if (branchName.contains("tag") && branchName.contains("builds")) {

                String branchParts[] = branchName.split("_");

                int buildsIndex = ArrayUtils.indexOf(branchParts, "builds");

                String moduleName = StringUtils.join(branchParts, "_", buildsIndex + 1, branchParts.length);

                RevCommit commit = rw.parseCommit(ref.getObjectId());

                ObjectId tag = GitRefUtils.insertTag(moduleName, commit, objectInserter);

                tagNameToTagId.put(moduleName, tag);

                tagNameToRef.put(moduleName, ref);

            }

        }

        BatchRefUpdate batch = repo.getRefDatabase().newBatchUpdate();

        List<RefSpec> branchesToDelete = new ArrayList<>();

        for (Entry<String, ObjectId> entry : tagNameToTagId.entrySet()) {

            String tagName = entry.getKey();

            // create the reference to the tag object
            batch.addCommand(
                    new ReceiveCommand(null, entry.getValue(), Constants.R_TAGS + tagName, Type.CREATE));

            // delete the original branch object

            Ref branch = tagNameToRef.get(entry.getKey());

            if (remoteName.equals("local")) {

                batch.addCommand(new ReceiveCommand(branch.getObjectId(), null, branch.getName(), Type.DELETE));

            } else {
                String adjustedBranchName = branch.getName().substring(refPrefix.length() + 1);

                branchesToDelete.add(new RefSpec(":" + Constants.R_HEADS + adjustedBranchName));
            }

        }

        // create the tags
        batch.execute(rw, new TextProgressMonitor());

        if (!remoteName.equals("local")) {
            // push the tag to the remote right now
            PushCommand pushCommand = git.push().setRemote(remoteName).setPushTags()
                    .setProgressMonitor(new TextProgressMonitor());

            if (userName != null)
                pushCommand.setCredentialsProvider(new UsernamePasswordCredentialsProvider(userName, password));

            Iterable<PushResult> results = pushCommand.call();

            for (PushResult pushResult : results) {

                if (!pushResult.equals(Result.NEW)) {
                    log.warn("failed to push tag " + pushResult.getMessages());
                }
            }

            // delete the branches from the remote
            results = git.push().setRemote(remoteName).setRefSpecs(branchesToDelete)
                    .setProgressMonitor(new TextProgressMonitor()).call();

            log.info("");

        }

        //         Result result = GitRefUtils.createTagReference(repo, moduleName, tag);
        //         
        //         if (!result.equals(Result.NEW)) {
        //            log.warn("failed to create tag {} for branch {}", moduleName, branchName);
        //            continue;
        //         }
        //         
        //         if (deleteMode) {
        //         result = GitRefUtils.deleteRef(repo, ref);
        //   
        //         if (!result.equals(Result.NEW)) {
        //            log.warn("failed to delete branch {}", branchName);
        //            continue;
        //         }

        objectInserter.release();

        rw.release();

    } catch (Exception e) {

        log.error("unexpected Exception ", e);
    }
}

From source file:ch.epfl.lsir.xin.test.SVDPPTest.java

/**
 * @param args/*  w w w  .j  a v a 2s.  c o  m*/
 */
public static void main(String[] args) throws Exception {
    // TODO Auto-generated method stub

    PrintWriter logger = new PrintWriter(".//results//SVDPP");

    PropertiesConfiguration config = new PropertiesConfiguration();
    config.setFile(new File("conf//SVDPlusPlus.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...");
    logger.flush();
    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;
    double totalPrecision = 0;
    double totalRecall = 0;
    double totalMAP = 0;
    double totalNDCG = 0;
    double totalMRR = 0;
    double totalAUC = 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);
        logger.flush();
        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++) {
            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 SVD++ recommendation model.");
        logger.flush();
        SVDPlusPlus algo = new SVDPlusPlus(trainRatingMatrix, false,
                ".//localModels//" + config.getString("NAME"));
        algo.setLogger(logger);
        algo.build();
        algo.saveModel(".//localModels//" + config.getString("NAME"));
        logger.println("Save the model.");
        logger.flush();

        //rating prediction accuracy
        double RMSE = 0;
        double MAE = 0;
        double precision = 0;
        double recall = 0;
        double map = 0;
        double ndcg = 0;
        double mrr = 0;
        double auc = 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()), false);
            if (prediction > algo.getMaxRating())
                prediction = algo.getMaxRating();
            if (prediction < algo.getMinRating())
                prediction = algo.getMinRating();
            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);
        totalMAE = totalMAE + MAE;
        totalRMSE = totalRMSE + RMSE;
        System.out.println("Folder --- MAE: " + MAE + " RMSE: " + RMSE);
        logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Folder --- MAE: "
                + MAE + " RMSE: " + RMSE);
        //ranking accuracy
        if (algo.getTopN() > 0) {
            HashMap<Integer, ArrayList<ResultUnit>> results = new HashMap<Integer, ArrayList<ResultUnit>>();
            for (int i = 0; i < trainRatingMatrix.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);
            precision = generator.getPrecisionN();
            totalPrecision = totalPrecision + precision;
            recall = generator.getRecallN();
            totalRecall = totalRecall + recall;
            map = generator.getMAPN();
            totalMAP = totalMAP + map;
            ndcg = generator.getNDCGN();
            totalNDCG = totalNDCG + ndcg;
            mrr = generator.getMRRN();
            totalMRR = totalMRR + mrr;
            auc = generator.getAUC();
            totalAUC = totalAUC + auc;
            System.out.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
            logger.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
        }

        logger.flush();
    }

    System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F);
    System.out.println("Precision@N: " + totalPrecision / F);
    System.out.println("Recall@N: " + totalRecall / F);
    System.out.println("MAP@N: " + totalMAP / F);
    System.out.println("MRR@N: " + totalMRR / F);
    System.out.println("NDCG@N: " + totalNDCG / F);
    System.out.println("AUC@N: " + totalAUC / F);

    logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + "\n" + "MAE: "
            + totalMAE / F + " RMSE: " + totalRMSE / F + "\n" + "Precision@N: " + totalPrecision / F + "\n"
            + "Recall@N: " + totalRecall / F + "\n" + "MAP@N: " + totalMAP / F + "\n" + "MRR@N: " + totalMRR / F
            + "\n" + "NDCG@N: " + totalNDCG / F + "\n" + "AUC@N: " + totalAUC / F);
    logger.flush();
    logger.close();
}

From source file:fr.inria.atlanmod.kyanos.benchmarks.ase2015.NeoEMFMapQueryInvisibleMethodDeclarations.java

public static void main(String[] args) {
    Options options = new Options();

    Option inputOpt = OptionBuilder.create(IN);
    inputOpt.setArgName("INPUT");
    inputOpt.setDescription("Input Kyanos resource directory");
    inputOpt.setArgs(1);/*  w  w  w .j ava  2 s. c  o m*/
    inputOpt.setRequired(true);

    Option inClassOpt = OptionBuilder.create(EPACKAGE_CLASS);
    inClassOpt.setArgName("CLASS");
    inClassOpt.setDescription("FQN of EPackage implementation class");
    inClassOpt.setArgs(1);
    inClassOpt.setRequired(true);

    Option optFileOpt = OptionBuilder.create(OPTIONS_FILE);
    optFileOpt.setArgName("FILE");
    optFileOpt.setDescription("Properties file holding the options to be used in the Kyanos Resource");
    optFileOpt.setArgs(1);

    options.addOption(inputOpt);
    options.addOption(inClassOpt);
    options.addOption(optFileOpt);

    CommandLineParser parser = new PosixParser();

    try {
        PersistenceBackendFactoryRegistry.getFactories().put(NeoMapURI.NEO_MAP_SCHEME,
                new MapPersistenceBackendFactory());

        CommandLine commandLine = parser.parse(options, args);

        URI uri = NeoMapURI.createNeoMapURI(new File(commandLine.getOptionValue(IN)));

        Class<?> inClazz = NeoEMFMapQueryInvisibleMethodDeclarations.class.getClassLoader()
                .loadClass(commandLine.getOptionValue(EPACKAGE_CLASS));
        inClazz.getMethod("init").invoke(null);

        ResourceSet resourceSet = new ResourceSetImpl();
        resourceSet.getResourceFactoryRegistry().getProtocolToFactoryMap().put(NeoMapURI.NEO_MAP_SCHEME,
                PersistentResourceFactory.eINSTANCE);

        Resource resource = resourceSet.createResource(uri);

        Map<String, Object> loadOpts = new HashMap<String, Object>();

        if (commandLine.hasOption(OPTIONS_FILE)) {
            Properties properties = new Properties();
            properties.load(new FileInputStream(new File(commandLine.getOptionValue(OPTIONS_FILE))));
            for (final Entry<Object, Object> entry : properties.entrySet()) {
                loadOpts.put((String) entry.getKey(), (String) entry.getValue());
            }
        }
        // Add the LoadedObjectCounter store
        List<StoreOption> storeOptions = new ArrayList<StoreOption>();
        //         storeOptions.add(PersistentResourceOptions.EStoreOption.LOADED_OBJECT_COUNTER_LOGGING);
        storeOptions.add(MapResourceOptions.EStoreMapOption.AUTOCOMMIT);
        storeOptions.add(PersistentResourceOptions.EStoreOption.ESTRUCUTRALFEATURE_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.IS_SET_CACHING);
        storeOptions.add(PersistentResourceOptions.EStoreOption.SIZE_CACHING);
        loadOpts.put(PersistentResourceOptions.STORE_OPTIONS, storeOptions);
        resource.load(loadOpts);
        {
            Runtime.getRuntime().gc();
            long initialUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory before query: {0}",
                    MessageUtil.byteCountToDisplaySize(initialUsedMemory)));
            LOG.log(Level.INFO, "Start query");
            long begin = System.currentTimeMillis();
            EList<MethodDeclaration> list = ASE2015JavaQueries.getInvisibleMethodDeclarations(resource);
            long end = System.currentTimeMillis();
            LOG.log(Level.INFO, "End query");
            LOG.log(Level.INFO, MessageFormat.format("Query result contains {0} elements", list.size()));
            LOG.log(Level.INFO, MessageFormat.format("Time spent: {0}", MessageUtil.formatMillis(end - begin)));
            Runtime.getRuntime().gc();
            long finalUsedMemory = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
            LOG.log(Level.INFO, MessageFormat.format("Used memory after query: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory)));
            LOG.log(Level.INFO, MessageFormat.format("Memory use increase: {0}",
                    MessageUtil.byteCountToDisplaySize(finalUsedMemory - initialUsedMemory)));
        }

        if (resource instanceof PersistentResourceImpl) {
            PersistentResourceImpl.shutdownWithoutUnload((PersistentResourceImpl) resource);
        } else {
            resource.unload();
        }

    } catch (ParseException e) {
        MessageUtil.showError(e.toString());
        MessageUtil.showError("Current arguments: " + Arrays.toString(args));
        HelpFormatter formatter = new HelpFormatter();
        formatter.printHelp("java -jar <this-file.jar>", options, true);
    } catch (Throwable e) {
        MessageUtil.showError(e.toString());
    }
}

From source file:ch.epfl.lsir.xin.test.BiasedMFTest.java

/**
 * @param args//from   ww w  . ja v  a 2  s.c om
 */
public static void main(String[] args) throws Exception {
    // TODO Auto-generated method stub

    PrintWriter logger = new PrintWriter(".//results//BiasedMF");

    PropertiesConfiguration config = new PropertiesConfiguration();
    config.setFile(new File("conf//biasedMF.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...");
    logger.flush();
    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;
    double totalPrecision = 0;
    double totalRecall = 0;
    double totalMAP = 0;
    double totalNDCG = 0;
    double totalMRR = 0;
    double totalAUC = 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);
        logger.flush();
        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++) {
            //            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 biased matrix factorization recommendation model.");
        logger.flush();
        BiasedMF algo = new BiasedMF(trainRatingMatrix, false, ".//localModels//" + config.getString("NAME"));
        algo.setLogger(logger);
        algo.build();
        algo.saveModel(".//localModels//" + config.getString("NAME"));
        logger.println("Save the model.");
        logger.flush();

        //rating prediction accuracy
        double RMSE = 0;
        double MAE = 0;
        double precision = 0;
        double recall = 0;
        double map = 0;
        double ndcg = 0;
        double mrr = 0;
        double auc = 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()), false);
            if (prediction > algo.getMaxRating())
                prediction = algo.getMaxRating();
            if (prediction < algo.getMinRating())
                prediction = algo.getMinRating();
            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);
        totalMAE = totalMAE + MAE;
        totalRMSE = totalRMSE + RMSE;
        System.out.println("Folder --- MAE: " + MAE + " RMSE: " + RMSE);
        logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Folder --- MAE: "
                + MAE + " RMSE: " + RMSE);
        //ranking accuracy
        if (algo.getTopN() > 0) {
            HashMap<Integer, ArrayList<ResultUnit>> results = new HashMap<Integer, ArrayList<ResultUnit>>();
            for (int i = 0; i < trainRatingMatrix.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);
            precision = generator.getPrecisionN();
            totalPrecision = totalPrecision + precision;
            recall = generator.getRecallN();
            totalRecall = totalRecall + recall;
            map = generator.getMAPN();
            totalMAP = totalMAP + map;
            ndcg = generator.getNDCGN();
            totalNDCG = totalNDCG + ndcg;
            mrr = generator.getMRRN();
            totalMRR = totalMRR + mrr;
            auc = generator.getAUC();
            totalAUC = totalAUC + auc;
            System.out.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
            logger.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
        }

        logger.flush();
    }

    System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F);
    System.out.println("Precision@N: " + totalPrecision / F);
    System.out.println("Recall@N: " + totalRecall / F);
    System.out.println("MAP@N: " + totalMAP / F);
    System.out.println("MRR@N: " + totalMRR / F);
    System.out.println("NDCG@N: " + totalNDCG / F);
    System.out.println("AUC@N: " + totalAUC / F);

    logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + "\n" + "MAE: "
            + totalMAE / F + " RMSE: " + totalRMSE / F + "\n" + "Precision@N: " + totalPrecision / F + "\n"
            + "Recall@N: " + totalRecall / F + "\n" + "MAP@N: " + totalMAP / F + "\n" + "MRR@N: " + totalMRR / F
            + "\n" + "NDCG@N: " + totalNDCG / F + "\n" + "AUC@N: " + totalAUC / F);
    logger.flush();
    logger.close();
}

From source file:ch.epfl.lsir.xin.test.UserBasedCFTest.java

/**
 * @param args/*from  w w  w  . j a  va  2 s .  c om*/
 */
public static void main(String[] args) throws Exception {
    // TODO Auto-generated method stub

    PrintWriter logger = new PrintWriter(".//results//UserBasedCF");
    PropertiesConfiguration config = new PropertiesConfiguration();
    config.setFile(new File(".//conf//UserBasedCF.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;
    double totalPrecision = 0;
    double totalRecall = 0;
    double totalMAP = 0;
    double totalNDCG = 0;
    double totalMRR = 0;
    double totalAUC = 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();
        trainRatingMatrix.calculateUsersMean();
        RatingMatrix testRatingMatrix = new RatingMatrix(dataset.getUserIDs().size(),
                dataset.getItemIDs().size());
        for (int i = 0; i < testRatings.size(); i++) {
            //            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());
        }
        logger.println("Initialize a user based collaborative filtering recommendation model.");
        UserBasedCF algo = new UserBasedCF(trainRatingMatrix, false,
                ".//localModels//" + config.getString("NAME"));
        algo.setLogger(logger);
        algo.build();//if read local model, no need to build the model
        algo.saveModel(".//localModels//" + config.getString("NAME"));
        logger.println("Save the model.");
        System.out.println(trainRatings.size() + " vs. " + testRatings.size());
        logger.flush();

        //rating prediction accuracy
        double RMSE = 0;
        double MAE = 0;
        double precision = 0;
        double recall = 0;
        double map = 0;
        double ndcg = 0;
        double mrr = 0;
        double auc = 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()), false);

            if (Double.isNaN(prediction)) {
                System.out.println("no prediction");
                continue;
            }
            if (prediction > algo.getMaxRating())
                prediction = algo.getMaxRating();
            if (prediction < algo.getMinRating())
                prediction = algo.getMinRating();
            MAE = MAE + Math.abs(rating.getValue() - prediction);
            RMSE = RMSE + Math.pow((rating.getValue() - prediction), 2);
            count++;
        }
        MAE = MAE / count;
        RMSE = Math.sqrt(RMSE / count);
        totalMAE = totalMAE + MAE;
        totalRMSE = totalRMSE + RMSE;
        System.out.println("Folder --- MAE: " + MAE + " RMSE: " + RMSE);
        logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + " Folder --- MAE: "
                + MAE + " RMSE: " + RMSE);
        logger.flush();
        //ranking accuracy
        if (algo.getTopN() > 0) {
            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);
                //               for( Map.Entry<Integer, Double> entry : testRatingMatrix.getRatingMatrix().get(i).entrySet() )
                //               {
                //                  System.out.print( entry.getKey() + "(" + entry.getValue() + ") , ");
                //               }
                //               System.out.println();
                //               for( int j = 0 ; j < rec.size() ; j++ )
                //               {
                //                  System.out.print(rec.get(j).getItemIndex() + "(" + rec.get(j).getPrediciton() +
                //                        ") , ");
                //               }
                //               System.out.println("**********");
            }
            RankResultGenerator generator = new RankResultGenerator(results, algo.getTopN(), testRatingMatrix,
                    trainRatingMatrix);
            precision = generator.getPrecisionN();
            totalPrecision = totalPrecision + precision;
            recall = generator.getRecallN();
            totalRecall = totalRecall + recall;
            map = generator.getMAPN();
            totalMAP = totalMAP + map;
            ndcg = generator.getNDCGN();
            totalNDCG = totalNDCG + ndcg;
            mrr = generator.getMRRN();
            totalMRR = totalMRR + mrr;
            auc = generator.getAUC();
            totalAUC = totalAUC + auc;
            System.out.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
            logger.println("Folder --- precision: " + precision + " recall: " + recall + " map: " + map
                    + " ndcg: " + ndcg + " mrr: " + mrr + " auc: " + auc);
        }
    }

    System.out.println("MAE: " + totalMAE / F + " RMSE: " + totalRMSE / F);
    System.out.println("Precision@N: " + totalPrecision / F);
    System.out.println("Recall@N: " + totalRecall / F);
    System.out.println("MAP@N: " + totalMAP / F);
    System.out.println("MRR@N: " + totalMRR / F);
    System.out.println("NDCG@N: " + totalNDCG / F);
    System.out.println("AUC@N: " + totalAUC / F);
    // MovieLens100k
    //MAE: 0.7343907480119425 RMSE: 0.9405808357192891 (MovieLens 100K, shrinkage 25, neighbor size 60, PCC)
    //MAE: 0.7522376630596646 RMSE: 0.9520931265724659 (MovieLens 100K, no shrinkage , neighbor size 40, COSINE)
    logger.println(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()) + "\n" + "MAE: "
            + totalMAE / F + " RMSE: " + totalRMSE / F + "\n" + "Precision@N: " + totalPrecision / F + "\n"
            + "Recall@N: " + totalRecall / F + "\n" + "MAP@N: " + totalMAP / F + "\n" + "MRR@N: " + totalMRR / F
            + "\n" + "NDCG@N: " + totalNDCG / F + "\n" + "AUC@N: " + totalAUC / F);
    logger.flush();
    logger.close();

}

From source file:com.bigdata.rockstor.console.RockStorSender.java

public static void main(String[] args) throws ClientProtocolException, URISyntaxException, IOException {

    HttpReq req = new HttpReq();
    req.setMethod("GET");
    req.setUrl("http://10.24.1.252:8080/rockstor/");
    req.setHead(new HashMap<String, String>());
    HttpResp resp = perform(req);/*from   www.  j  a v a2  s  .c om*/
    System.out.println(resp.getStatus());
    System.out.println(resp.getBody());
}