Example usage for java.util.stream IntStream range

List of usage examples for java.util.stream IntStream range

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Introduction

In this page you can find the example usage for java.util.stream IntStream range.

Prototype

public static IntStream range(int startInclusive, int endExclusive)

Source Link

Document

Returns a sequential ordered IntStream from startInclusive (inclusive) to endExclusive (exclusive) by an incremental step of 1 .

Usage

From source file:it.greenvulcano.gvesb.gviamx.service.internal.SignUpManager.java

public void createSignUpRequest(String email, byte[] request) throws UserExistException {

    if (email == null || !email.matches(UserActionRequest.EMAIL_PATTERN)) {
        throw new IllegalArgumentException("Invalid email: " + email);
    }/*from  ww w .ja v  a2 s.com*/

    try {
        usersManager.getUser(email.toLowerCase());
        throw new UserExistException(email);
    } catch (UserNotFoundException e) {

        if (usersManager.searchUsers(SearchCriteria.builder().byEmail(email.toLowerCase()).limitedTo(1).build())
                .getTotalCount() > 0) {
            throw new UserExistException(email);
        }
    }

    SignUpRequest signUpRequest = signupRepository.get(email.toLowerCase(), SignUpRequest.class)
            .orElseGet(SignUpRequest::new);
    signUpRequest.setEmail(email.toLowerCase());
    signUpRequest.setIssueTime(new Date());
    signUpRequest.setExpireTime(expireTime);
    signUpRequest.setRequest(request);
    signUpRequest.setNotificationStatus(NotificationStatus.PENDING);

    byte[] token = new byte[4];
    secureRandom.nextBytes(token);

    String clearTextToken = String.format(Locale.US, "%02x%02x%02x%02x",
            IntStream.range(0, token.length).mapToObj(i -> Byte.valueOf(token[i])).toArray());
    signUpRequest.setToken(DigestUtils.sha256Hex(clearTextToken));

    signupRepository.add(signUpRequest);

    signUpRequest.setClearToken(clearTextToken);
    notificationServices.stream()
            .map(n -> new NotificationManager.NotificationTask(n, signUpRequest, signupRepository, "signup"))
            .forEach(executor::submit);

}

From source file:delfos.rs.collaborativefiltering.als.ALSRecommender.java

@Override
public MatrixFactorizationModel buildRecommendationModel(DatasetLoader<? extends Rating> datasetLoader)
        throws CannotLoadRatingsDataset, CannotLoadContentDataset, CannotLoadUsersDataset {

    int numIter = 1;
    int dimension = 5;
    long seed = getSeedValue();

    final double lambda = 0.1;

    Bias bias = new Bias(datasetLoader);

    Map<User, List<Double>> randomUserVectors = datasetLoader.getUsersDataset().parallelStream()
            .collect(Collectors.toMap(user -> user, user -> {
                Random random = new Random(seed + user.getId());
                List<Double> vector = random.doubles(-10, 10).limit(dimension).boxed()
                        .collect(Collectors.toList());
                return vector;
            }));/*from   w w  w. ja va2 s  .c om*/

    Map<Item, List<Double>> randomItemVectors = datasetLoader.getContentDataset().parallelStream()
            .collect(Collectors.toMap(item -> item, item -> {
                Random random = new Random(seed + item.getId());
                List<Double> vector = random.doubles(-10, 10).limit(dimension).boxed()
                        .collect(Collectors.toList());
                return vector;
            }));

    MatrixFactorizationModel model = new MatrixFactorizationModel(randomUserVectors, randomItemVectors, bias);

    for (int iterationIndex = 0; iterationIndex < numIter; iterationIndex++) {

        final int iteration = iterationIndex;
        final MatrixFactorizationModel initialModel = model;

        double error = getModelError(bias, datasetLoader, initialModel);

        System.out.println("Error in iteration " + iterationIndex + " is " + error);

        ProgressChangedController userProgress = new ProgressChangedController(
                getAlias() + " for dataset " + datasetLoader.getAlias() + " userOptimization iteration "
                        + iteration,
                datasetLoader.getUsersDataset().size(), this::fireBuildingProgressChangedEvent);

        Map<User, List<Double>> trainedUserVectors = datasetLoader.getUsersDataset().parallelStream()
                .collect(Collectors.toMap(user -> user, (User user) -> {
                    Map<Integer, ? extends Rating> userRatings = datasetLoader.getRatingsDataset()
                            .getUserRatingsRated(user.getId());

                    ObjectiveFunction objectiveFunction = new ObjectiveFunction((double[] pu) -> {
                        List<Double> userVector = Arrays.stream(pu).boxed().collect(Collectors.toList());
                        double predictionError = userRatings.values().parallelStream()
                                .map(bias.getBiasApplier()).map(rating -> {
                                    List<Double> itemVector = initialModel.getItemFeatures(rating.getItem());
                                    double prediction = IntStream.range(0, userVector.size())
                                            .mapToDouble(index -> userVector.get(index) * itemVector.get(index))
                                            .sum();

                                    double value = rating.getRatingValue().doubleValue();

                                    double errorThisRating = prediction - value;

                                    return errorThisRating;
                                }).map(value -> Math.pow(value, 2)).mapToDouble(value -> value).sum();

                        double penalty = Arrays.stream(pu).map(value -> Math.pow(value, 2)).sum();
                        double objectiveFunctionValue = predictionError + lambda * penalty;
                        return objectiveFunctionValue;
                    });

                    SimplexOptimizer simplexOptimizer = new SimplexOptimizer(0, 0);

                    double[] initialGuess = new Random(seed + user.getId()).doubles(-10, 10).limit(dimension)
                            .toArray();

                    List<Double> initialGuessList = Arrays.stream(initialGuess).boxed()
                            .collect(Collectors.toList());

                    double initialGuessPenalty = objectiveFunction.getObjectiveFunction().value(initialGuess);

                    try {
                        PointValuePair optimize = simplexOptimizer.optimize(
                                new MultiDirectionalSimplex(dimension), new InitialGuess(initialGuess),
                                objectiveFunction, GoalType.MINIMIZE, MAX_EVAL, MAX_ITER);
                        double optimizedPenalty = optimize.getValue();
                        userProgress.setTaskFinished();

                        List<Double> optimizedUserVector = Arrays.stream(optimize.getPoint()).boxed()
                                .collect(Collectors.toList());
                        return optimizedUserVector;
                    } catch (Exception ex) {
                        System.out.println("Vector cannot be optimized for user " + user + " (numRatings="
                                + userRatings.size() + ")");
                        return initialModel.getUserFeatures(user);
                    }
                }));

        ProgressChangedController itemProgress = new ProgressChangedController(
                getAlias() + " for dataset " + datasetLoader.getAlias() + " item optimization iteration "
                        + iteration,
                datasetLoader.getContentDataset().size(), this::fireBuildingProgressChangedEvent);

        Map<Item, List<Double>> trainedItemVectors = datasetLoader.getContentDataset().parallelStream()
                .collect(Collectors.toMap(item -> item, item -> {
                    Map<Integer, ? extends Rating> itemRatings = datasetLoader.getRatingsDataset()
                            .getItemRatingsRated(item.getId());

                    ObjectiveFunction objectiveFunction = new ObjectiveFunction((double[] pu) -> {
                        List<Double> itemVector = Arrays.stream(pu).boxed().collect(Collectors.toList());
                        double predictionError = itemRatings.values().parallelStream()
                                .map(bias.getBiasApplier()).map(rating -> {
                                    List<Double> userVector = initialModel.getUserFeatures(rating.getUser());
                                    double prediction = IntStream.range(0, userVector.size())
                                            .mapToDouble(index -> userVector.get(index) * itemVector.get(index))
                                            .sum();

                                    double value = rating.getRatingValue().doubleValue();

                                    double errorThisRating = prediction - value;

                                    return errorThisRating;
                                }).map(value -> Math.pow(value, 2)).mapToDouble(value -> value).sum();

                        double penalty = Arrays.stream(pu).map(value -> Math.pow(value, 2)).sum();
                        double objectiveFunctionValue = predictionError + lambda * penalty;
                        return objectiveFunctionValue;
                    });

                    SimplexOptimizer simplexOptimizer = new SimplexOptimizer(0, 0);

                    double[] initialGuess = new Random(seed + item.getId()).doubles(-10, 10).limit(dimension)
                            .toArray();

                    List<Double> initialGuessList = Arrays.stream(initialGuess).boxed()
                            .collect(Collectors.toList());

                    double initialGuessPenalty = objectiveFunction.getObjectiveFunction().value(initialGuess);

                    try {
                        PointValuePair optimize = simplexOptimizer.optimize(
                                new MultiDirectionalSimplex(dimension), new InitialGuess(initialGuess),
                                objectiveFunction, GoalType.MINIMIZE, MAX_EVAL, MAX_ITER);
                        double optimizedPenalty = optimize.getValue();
                        itemProgress.setTaskFinished();

                        List<Double> optimizedVector = Arrays.stream(optimize.getPoint()).boxed()
                                .collect(Collectors.toList());

                        return optimizedVector;
                    } catch (Exception ex) {
                        System.out.println("Vector cannot be optimized " + item
                                + " cannot be optimized (numRatings=" + itemRatings.size() + ")");
                        return initialModel.getItemFeatures(item);
                    }
                }));

        model = new MatrixFactorizationModel(trainedUserVectors, trainedItemVectors, bias);

    }
    return model;

}

From source file:com.simiacryptus.mindseye.applications.ArtistryUtil.java

/**
 * Paint lines.//from   w  w w  .j a  va  2  s. co  m
 *
 * @param canvas the canvas
 */
public static void paint_Lines(final Tensor canvas) {
    BufferedImage originalImage = canvas.toImage();
    BufferedImage newImage = new BufferedImage(originalImage.getWidth(), originalImage.getHeight(),
            BufferedImage.TYPE_INT_ARGB);
    Graphics2D graphics = (Graphics2D) newImage.getGraphics();
    IntStream.range(0, 100).forEach(i -> {
        Random random = new Random();
        graphics.setColor(new Color(random.nextInt(255), random.nextInt(255), random.nextInt(255)));
        graphics.drawLine(random.nextInt(originalImage.getWidth()), random.nextInt(originalImage.getHeight()),
                random.nextInt(originalImage.getWidth()), random.nextInt(originalImage.getHeight()));
    });
    canvas.set(Tensor.fromRGB(newImage));
}

From source file:com.vmware.photon.controller.cloudstore.xenon.entity.SchedulingConstantGeneratorTest.java

/**
 * Test distribution of scheduling constants, creating hosts concurrently on a
 * single Xenon host.//from  w  w  w. j  a  v  a2 s  . c o  m
 */
@Test(dataProvider = "HostCounts")
public void testSchedulingConstantVariationConcurrent(int hostCount) throws Throwable {
    List<Long> schedulingConstants = Collections.synchronizedList(new ArrayList<>());
    TestEnvironment env = TestEnvironment.create(1);
    List<Thread> threads = new ArrayList<>();
    ServiceHost xenonHost = env.getHosts()[0];

    IntStream.range(0, THREADS).forEach((threadId) -> {
        Thread t = new Thread(() -> {
            List<Long> thisThreadSchedulingConstants = createHosts(xenonHost, hostCount);
            schedulingConstants.addAll(thisThreadSchedulingConstants);
        });
        t.start();
        threads.add(t);
    });

    for (Thread t : threads) {
        t.join();
    }

    env.stop();

    assertThat(schedulingConstants.size(), equalTo(hostCount * THREADS));
    Collections.sort(schedulingConstants);

    double cv = schedulingConstantGapCV(schedulingConstants);
    logger.info("Scheduling constant gap coefficient of variation: {}", cv);
    assertThat(cv, lessThan(MAX_VARIATION));
}

From source file:nl.salp.warcraft4j.fileformat.dbc.DbcFile.java

/**
 * Get all entries from the DBC file.//from   w  ww.  j  a  v  a 2  s.c  o m
 *
 * @return The parsed entries.
 *
 * @throws DbcParsingException When the entries could not be parsed.
 */
public List<DbcEntry> getEntries() throws DbcParsingException {
    DbcHeader header = getHeader();
    try (DataReader reader = getDataReader()) {
        return IntStream.range(0, header.getEntryCount()).mapToObj(i -> getEntry(i, reader))
                .collect(Collectors.toList());
    } catch (IOException e) {
        throw new DbcParsingException(
                format("Error parsing entries for DBC file %d (%s)", filenameHash, filename), e);
    }
}

From source file:org.apache.sysml.runtime.controlprogram.paramserv.ParamservUtils.java

public static List<ExecutionContext> createExecutionContexts(ExecutionContext ec, LocalVariableMap varsMap,
        String updFunc, String aggFunc, int workerNum, int k) {

    FunctionProgramBlock updPB = getFunctionBlock(ec, updFunc);
    FunctionProgramBlock aggPB = getFunctionBlock(ec, aggFunc);

    Program prog = ec.getProgram();/*from   w  ww .  jav a2  s  .  c om*/

    // 1. Recompile the internal program blocks
    recompileProgramBlocks(k, prog.getProgramBlocks());
    // 2. Recompile the imported function blocks
    prog.getFunctionProgramBlocks()
            .forEach((fname, fvalue) -> recompileProgramBlocks(k, fvalue.getChildBlocks()));

    // 3. Copy function for workers
    List<ExecutionContext> workerECs = IntStream.range(0, workerNum).mapToObj(i -> {
        FunctionProgramBlock newUpdFunc = copyFunction(updFunc, updPB);
        FunctionProgramBlock newAggFunc = copyFunction(aggFunc, aggPB);
        Program newProg = new Program();
        putFunction(newProg, newUpdFunc);
        putFunction(newProg, newAggFunc);
        return ExecutionContextFactory.createContext(new LocalVariableMap(varsMap), newProg);
    }).collect(Collectors.toList());

    // 4. Copy function for agg service
    FunctionProgramBlock newAggFunc = copyFunction(aggFunc, aggPB);
    Program newProg = new Program();
    putFunction(newProg, newAggFunc);
    ExecutionContext aggEC = ExecutionContextFactory.createContext(new LocalVariableMap(varsMap), newProg);

    List<ExecutionContext> result = new ArrayList<>(workerECs);
    result.add(aggEC);
    return result;
}

From source file:no.imr.stox.functions.acoustic.PgNapesIO.java

public static void export2(String cruise, String country, String callSignal, String path, String fileName,
        List<DistanceBO> distances, Double groupThickness, Integer freqFilter, String specFilter,
        boolean withZeros) {
    Set<Integer> freqs = distances.stream().flatMap(dist -> dist.getFrequencies().stream())
            .map(FrequencyBO::getFreq).collect(Collectors.toSet());
    if (freqFilter == null && freqs.size() == 1) {
        freqFilter = freqs.iterator().next();
    }/*from  w  w w .  j a  v  a 2 s.co  m*/

    if (freqFilter == null) {
        System.out.println("Multiple frequencies, specify frequency filter as parameter");
        return;
    }
    Integer freqFilterF = freqFilter; // ef.final
    List<String> acList = distances.parallelStream().flatMap(dist -> dist.getFrequencies().stream())
            .filter(fr -> freqFilterF.equals(fr.getFreq())).map(f -> {
                DistanceBO d = f.getDistanceBO();
                LocalDateTime sdt = LocalDateTime.ofInstant(d.getStart_time().toInstant(), ZoneOffset.UTC);
                Double intDist = d.getIntegrator_dist();
                String month = StringUtils.leftPad(sdt.getMonthValue() + "", 2, "0");
                String day = StringUtils.leftPad(sdt.getDayOfMonth() + "", 2, "0");
                String hour = StringUtils.leftPad(sdt.getHour() + "", 2, "0");
                String minute = StringUtils.leftPad(sdt.getMinute() + "", 2, "0");
                String log = Conversion.formatDoubletoDecimalString(d.getLog_start(), "0.0");
                String acLat = Conversion.formatDoubletoDecimalString(d.getLat_start(), "0.000");
                String acLon = Conversion.formatDoubletoDecimalString(d.getLon_start(), "0.000");
                return Stream
                        .of(d.getNation(), d.getPlatform(), d.getCruise(), log, sdt.getYear(), month, day, hour,
                                minute, acLat, acLon, intDist, f.getFreq(), f.getThreshold())
                        .map(o -> o == null ? "" : o.toString()).collect(Collectors.joining("\t")) + "\t";
            }).collect(Collectors.toList());
    String fil1 = path + "/" + fileName + ".txt";
    acList.add(0, Stream.of("Country", "Vessel", "Cruise", "Log", "Year", "Month", "Day", "Hour", "Min",
            "AcLat", "AcLon", "Logint", "Frequency", "Sv_threshold").collect(Collectors.joining("\t")));
    try {
        Files.write(Paths.get(fil1), acList, StandardOpenOption.CREATE, StandardOpenOption.TRUNCATE_EXISTING);
    } catch (IOException ex) {
        Logger.getLogger(PgNapesIO.class.getName()).log(Level.SEVERE, null, ex);
    }
    acList.clear();
    // Acoustic values
    distances.stream().filter(d -> d.getPel_ch_thickness() != null)
            .flatMap(dist -> dist.getFrequencies().stream()).filter(fr -> freqFilterF.equals(fr.getFreq()))
            .forEachOrdered(f -> {
                try {
                    Double groupThicknessF = Math.max(f.getDistanceBO().getPel_ch_thickness(), groupThickness);
                    Map<String, Map<Integer, Double>> pivot = f.getSa().stream()
                            .filter(s -> s.getCh_type().equals("P")).map(s -> new SAGroup(s, groupThicknessF))
                            .filter(s -> s.getSpecies() != null
                                    && (specFilter == null || specFilter.equals(s.getSpecies())))
                            // create pivot table: species (dim1) -> depth interval index (dim2) -> sum sa (group aggregator)
                            .collect(Collectors.groupingBy(SAGroup::getSpecies, Collectors.groupingBy(
                                    SAGroup::getDepthGroupIdx, Collectors.summingDouble(SAGroup::sa))));
                    if (pivot.isEmpty() && specFilter != null && withZeros) {
                        pivot.put(specFilter, new HashMap<>());
                    }
                    Integer maxGroupIdx = pivot.entrySet().stream().flatMap(e -> e.getValue().keySet().stream())
                            .max(Integer::compare).orElse(null);
                    if (maxGroupIdx == null) {
                        return;
                    }
                    acList.addAll(pivot.entrySet().stream().sorted(Comparator.comparing(Map.Entry::getKey))
                            .flatMap(e -> {
                                return IntStream.range(0, maxGroupIdx + 1).boxed().map(groupIdx -> {
                                    Double chUpDepth = groupIdx * groupThicknessF;
                                    Double chLowDepth = (groupIdx + 1) * groupThicknessF;
                                    Double sa = e.getValue().get(groupIdx);
                                    if (sa == null) {
                                        sa = 0d;
                                    }
                                    String res = null;
                                    if (withZeros || sa > 0d) {
                                        DistanceBO d = f.getDistanceBO();
                                        String log = Conversion.formatDoubletoDecimalString(d.getLog_start(),
                                                "0.0");
                                        LocalDateTime sdt = LocalDateTime
                                                .ofInstant(d.getStart_time().toInstant(), ZoneOffset.UTC);
                                        String month = StringUtils.leftPad(sdt.getMonthValue() + "", 2, "0");
                                        String day = StringUtils.leftPad(sdt.getDayOfMonth() + "", 2, "0");
                                        //String sas = String.format(Locale.UK, "%11.5f", sa);
                                        res = Stream
                                                .of(d.getNation(), d.getPlatform(), d.getCruise(), log,
                                                        sdt.getYear(), month, day, e.getKey(), chUpDepth,
                                                        chLowDepth, sa)
                                                .map(o -> o == null ? "" : o.toString())
                                                .collect(Collectors.joining("\t"));
                                    }
                                    return res;
                                }).filter(s -> s != null);
                            }).collect(Collectors.toList()));
                } catch (Exception e) {
                    e.printStackTrace();
                }
            });

    String fil2 = path + "/" + fileName + "Values.txt";
    acList.add(0, Stream.of("Country", "Vessel", "Cruise", "Log", "Year", "Month", "Day", "Species",
            "ChUppDepth", "ChLowDepth", "SA").collect(Collectors.joining("\t")));
    try {
        Files.write(Paths.get(fil2), acList, StandardOpenOption.CREATE, StandardOpenOption.TRUNCATE_EXISTING);
    } catch (IOException ex) {
        Logger.getLogger(PgNapesIO.class.getName()).log(Level.SEVERE, null, ex);
    }
}

From source file:com.abixen.platform.service.businessintelligence.multivisualization.service.impl.JsonFilterServiceImpl.java

private Map<String, String> getColumnTypeMapping(ResultSetMetaData rsmd) throws SQLException {
    int columnCount = rsmd.getColumnCount();
    Map<String, String> columnTypeMapping = new HashMap<>();

    IntStream.range(1, columnCount + 1).forEach(i -> {
        try {/*from w w  w. j  av  a  2  s  .c  om*/
            String columnTypeName = rsmd.getColumnTypeName(i);
            if ("BIGINT".equals(columnTypeName)) {
                columnTypeName = "INTEGER";
            }
            if ("VARCHAR".equals(columnTypeName)) {
                columnTypeName = "STRING";
            }
            if ("FLOAT8".equals(columnTypeName)) {
                columnTypeName = "DOUBLE";
            }
            columnTypeMapping.put(rsmd.getColumnName(i).toUpperCase(), columnTypeName.toUpperCase());
        } catch (SQLException e) {
            e.printStackTrace();
        }
    });
    return columnTypeMapping;
}

From source file:org.apache.hadoop.hbase.tool.TestLoadIncrementalHFilesSplitRecovery.java

private TableDescriptor createTableDesc(TableName name, int cfs) {
    TableDescriptorBuilder builder = TableDescriptorBuilder.newBuilder(name);
    IntStream.range(0, cfs).mapToObj(i -> ColumnFamilyDescriptorBuilder.of(family(i)))
            .forEachOrdered(builder::addColumnFamily);
    return builder.build();
}

From source file:jp.co.opentone.bsol.linkbinder.view.admin.module.dataimport.MasterDataImportModule.java

/**
 * ???./*from  w w  w  .ja va2  s.  c  o  m*/
 * @param file ?
 * @param list ????.
 * @return ?
 * @throws IOException
 */
protected List<ValidationErrorInfo> validate(String file, List<T> list, MasterDataImportProcessType processType)
        throws IOException {
    List<ValidationErrorInfo> result = new ArrayList<>();

    // 
    CsvConfig config = createCsvConfig();
    List<String[]> lines = Csv.load(newInputStream(file), SystemConfig.getValue(Constants.KEY_CSV_ENCODING),
            config, new StringArrayListHandler());
    int expectedCount = getCsvColumnCount();
    String msgInvalidColumnCount = Messages.getMessage(ApplicationMessageCode.ERROR_INVALID_COLUMN_COUNT)
            .getMessage();
    IntStream.range(0, lines.size()).forEach(i -> {
        int rowNum = i + 1;
        if (lines.get(i).length != expectedCount) {
            result.add(new ValidationErrorInfo(rowNum, null, null, msgInvalidColumnCount));
        }
    });
    if (!result.isEmpty()) {
        return result;
    }

    // ??
    Class<?>[] validationGroups;
    switch (processType) {
    case CREATE_OR_UPDATE:
        validationGroups = new Class<?>[] { Default.class, CreateGroup.class };
        break;
    case DELETE:
        validationGroups = new Class<?>[] { Default.class };
        break;
    default:
        validationGroups = new Class<?>[] { Default.class };
    }

    ValidatorFactory factory = Validation.buildDefaultValidatorFactory();
    Validator validator = factory.getValidator();
    IntStream.range(0, list.size()).forEach(i -> {
        int rowNum = i + 1;
        Set<ConstraintViolation<T>> violations = validator.validate(list.get(i), validationGroups);
        List<ValidationErrorInfo> infoList = violations.stream().map(v -> new ValidationErrorInfo(rowNum,
                toViewName(v.getPropertyPath().toString()), v.getInvalidValue(), v.getMessage()))
                .collect(Collectors.toList());

        result.addAll(infoList);
    });

    return result;
}