Package java.io

Examples of java.io.BufferedInputStream


        ChannelBuffer encoded = bout.buffer();
        encoded.setInt(0, encoded.writerIndex() - 4);
        write(ctx, e.getFuture(), encoded, e.getRemoteAddress());
    for (InputStream is : oout.getStreams()) {
      Channels.write(ctx.getChannel(), new AnonymousChunkedStream(new BufferedInputStream(is, CHUNK_SIZE)));
    }
    }
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      }
      int returnVal = m_FileChooser.showOpenDialog(this);
      if (returnVal == JFileChooser.APPROVE_OPTION) {
  File selected = m_FileChooser.getSelectedFile();
  try {
    ObjectInputStream oi = new ObjectInputStream(new BufferedInputStream(new FileInputStream(selected)));
    Object obj = oi.readObject();
    oi.close();
    if (!m_ClassType.isAssignableFrom(obj.getClass())) {
      throw new Exception("Object not of type: " + m_ClassType.getName());
    }
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      }
        }
    }
 
      is = new LimitedBandwidthStream(
    new BufferedInputStream(httpConn.getInputStream(), 256),
          bandwidth);
      bwrite = new BufferedWriter(
           new OutputStreamWriter(httpConn.getOutputStream()));

      if (callback != null) {
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    printMargins = false, printComplexityStatistics = false,
    printGraph = false, classStatistics = false, printSource = false;
    StringBuffer text = new StringBuffer();
    DataSource trainSource = null, testSource = null;
    ObjectInputStream objectInputStream = null;
    BufferedInputStream xmlInputStream = null;
    CostMatrix costMatrix = null;
    StringBuffer schemeOptionsText = null;
    long trainTimeStart = 0, trainTimeElapsed = 0,
    testTimeStart = 0, testTimeElapsed = 0;
    String xml = "";
    String[] optionsTmp = null;
    Classifier classifierBackup;
    Classifier classifierClassifications = null;
    int actualClassIndex = -1// 0-based class index
    String splitPercentageString = "";
    double splitPercentage = -1;
    boolean preserveOrder = false;
    boolean trainSetPresent = false;
    boolean testSetPresent = false;
    String thresholdFile;
    String thresholdLabel;
    StringBuffer predsBuff = null; // predictions from cross-validation
    AbstractOutput classificationOutput = null;

    // help requested?
    if (Utils.getFlag("h", options) || Utils.getFlag("help", options)) {

      // global info requested as well?
      boolean globalInfo = Utils.getFlag("synopsis", options) ||
        Utils.getFlag("info", options);

      throw new Exception("\nHelp requested."
          + makeOptionString(classifier, globalInfo));
    }

    try {
      // do we get the input from XML instead of normal parameters?
      xml = Utils.getOption("xml", options);
      if (!xml.equals(""))
        options = new XMLOptions(xml).toArray();

      // is the input model only the XML-Options, i.e. w/o built model?
      optionsTmp = new String[options.length];
      for (int i = 0; i < options.length; i++)
        optionsTmp[i] = options[i];

      String tmpO = Utils.getOption('l', optionsTmp);
      //if (Utils.getOption('l', optionsTmp).toLowerCase().endsWith(".xml")) {
      if (tmpO.endsWith(".xml")) {
        // try to load file as PMML first
        boolean success = false;
        try {
          PMMLModel pmmlModel = PMMLFactory.getPMMLModel(tmpO);
          if (pmmlModel instanceof PMMLClassifier) {
            classifier = ((PMMLClassifier)pmmlModel);
            success = true;
          }
        } catch (IllegalArgumentException ex) {
          success = false;
        }
        if (!success) {
          // load options from serialized data  ('-l' is automatically erased!)
          XMLClassifier xmlserial = new XMLClassifier();
          OptionHandler cl = (OptionHandler) xmlserial.read(Utils.getOption('l', options));

          // merge options
          optionsTmp = new String[options.length + cl.getOptions().length];
          System.arraycopy(cl.getOptions(), 0, optionsTmp, 0, cl.getOptions().length);
          System.arraycopy(options, 0, optionsTmp, cl.getOptions().length, options.length);
          options = optionsTmp;
        }
      }

      noCrossValidation = Utils.getFlag("no-cv", options);
      // Get basic options (options the same for all schemes)
      classIndexString = Utils.getOption('c', options);
      if (classIndexString.length() != 0) {
        if (classIndexString.equals("first"))
          classIndex = 1;
        else if (classIndexString.equals("last"))
          classIndex = -1;
        else
          classIndex = Integer.parseInt(classIndexString);
      }
      trainFileName = Utils.getOption('t', options);
      objectInputFileName = Utils.getOption('l', options);
      objectOutputFileName = Utils.getOption('d', options);
      testFileName = Utils.getOption('T', options);
      foldsString = Utils.getOption('x', options);
      if (foldsString.length() != 0) {
        folds = Integer.parseInt(foldsString);
      }
      seedString = Utils.getOption('s', options);
      if (seedString.length() != 0) {
        seed = Integer.parseInt(seedString);
      }
      if (trainFileName.length() == 0) {
        if (objectInputFileName.length() == 0) {
          throw new Exception("No training file and no object input file given.");
        }
        if (testFileName.length() == 0) {
          throw new Exception("No training file and no test file given.");
        }
      } else if ((objectInputFileName.length() != 0) &&
          ((!(classifier instanceof UpdateableClassifier)) ||
           (testFileName.length() == 0))) {
        throw new Exception("Classifier not incremental, or no " +
            "test file provided: can't "+
            "use both train and model file.");
      }
      try {
        if (trainFileName.length() != 0) {
          trainSetPresent = true;
          trainSource = new DataSource(trainFileName);
        }
        if (testFileName.length() != 0) {
          testSetPresent = true;
          testSource = new DataSource(testFileName);
        }
        if (objectInputFileName.length() != 0) {
          if (objectInputFileName.endsWith(".xml")) {
            // if this is the case then it means that a PMML classifier was
            // successfully loaded earlier in the code
            objectInputStream = null;
            xmlInputStream = null;
          } else {
            InputStream is = new FileInputStream(objectInputFileName);
            if (objectInputFileName.endsWith(".gz")) {
              is = new GZIPInputStream(is);
            }
            // load from KOML?
            if (!(objectInputFileName.endsWith(".koml") && KOML.isPresent()) ) {
              objectInputStream = new ObjectInputStream(is);
              xmlInputStream    = null;
            }
            else {
              objectInputStream = null;
              xmlInputStream    = new BufferedInputStream(is);
            }
          }
        }
      } catch (Exception e) {
        throw new Exception("Can't open file " + e.getMessage() + '.');
      }
      if (testSetPresent) {
        template = test = testSource.getStructure();
        if (classIndex != -1) {
          test.setClassIndex(classIndex - 1);
        } else {
          if ( (test.classIndex() == -1) || (classIndexString.length() != 0) )
            test.setClassIndex(test.numAttributes() - 1);
        }
        actualClassIndex = test.classIndex();
      }
      else {
        // percentage split
        splitPercentageString = Utils.getOption("split-percentage", options);
        if (splitPercentageString.length() != 0) {
          if (foldsString.length() != 0)
            throw new Exception(
                "Percentage split cannot be used in conjunction with "
                + "cross-validation ('-x').");
          splitPercentage = Double.parseDouble(splitPercentageString);
          if ((splitPercentage <= 0) || (splitPercentage >= 100))
            throw new Exception("Percentage split value needs be >0 and <100.");
        }
        else {
          splitPercentage = -1;
        }
        preserveOrder = Utils.getFlag("preserve-order", options);
        if (preserveOrder) {
          if (splitPercentage == -1)
            throw new Exception("Percentage split ('-percentage-split') is missing.");
        }
        // create new train/test sources
        if (splitPercentage > 0) {
          testSetPresent = true;
          Instances tmpInst = trainSource.getDataSet(actualClassIndex);
          if (!preserveOrder)
            tmpInst.randomize(new Random(seed));
          int trainSize =
            (int) Math.round(tmpInst.numInstances() * splitPercentage / 100);
          int testSize  = tmpInst.numInstances() - trainSize;
          Instances trainInst = new Instances(tmpInst, 0, trainSize);
          Instances testInst  = new Instances(tmpInst, trainSize, testSize);
          trainSource = new DataSource(trainInst);
          testSource  = new DataSource(testInst);
          template = test = testSource.getStructure();
          if (classIndex != -1) {
            test.setClassIndex(classIndex - 1);
          } else {
            if ( (test.classIndex() == -1) || (classIndexString.length() != 0) )
              test.setClassIndex(test.numAttributes() - 1);
          }
          actualClassIndex = test.classIndex();
        }
      }
      if (trainSetPresent) {
        template = train = trainSource.getStructure();
        if (classIndex != -1) {
          train.setClassIndex(classIndex - 1);
        } else {
          if ( (train.classIndex() == -1) || (classIndexString.length() != 0) )
            train.setClassIndex(train.numAttributes() - 1);
        }
        actualClassIndex = train.classIndex();
        if (!(classifier instanceof weka.classifiers.misc.InputMappedClassifier)) {
          if ((testSetPresent) && !test.equalHeaders(train)) {
            throw new IllegalArgumentException("Train and test file not compatible!\n" + test.equalHeadersMsg(train));
          }
        }
      }
      if (template == null) {
        throw new Exception("No actual dataset provided to use as template");
      }
      costMatrix = handleCostOption(
          Utils.getOption('m', options), template.numClasses());

      classStatistics = Utils.getFlag('i', options);
      noOutput = Utils.getFlag('o', options);
      trainStatistics = !Utils.getFlag('v', options);
      printComplexityStatistics = Utils.getFlag('k', options);
      printMargins = Utils.getFlag('r', options);
      printGraph = Utils.getFlag('g', options);
      sourceClass = Utils.getOption('z', options);
      printSource = (sourceClass.length() != 0);
      thresholdFile = Utils.getOption("threshold-file", options);
      thresholdLabel = Utils.getOption("threshold-label", options);

      String classifications = Utils.getOption("classifications", options);
      String classificationsOld = Utils.getOption("p", options);
      if (classifications.length() > 0) {
        noOutput = true;
        classificationOutput = AbstractOutput.fromCommandline(classifications);
        classificationOutput.setHeader(template);
      }
      // backwards compatible with old "-p range" and "-distribution" options
      else if (classificationsOld.length() > 0) {
        noOutput = true;
        classificationOutput = new PlainText();
        classificationOutput.setHeader(template);
        if (!classificationsOld.equals("0"))
          classificationOutput.setAttributes(classificationsOld);
        classificationOutput.setOutputDistribution(Utils.getFlag("distribution", options));
      }
      // -distribution flag needs -p option
      else {
        if (Utils.getFlag("distribution", options))
          throw new Exception("Cannot print distribution without '-p' option!");
      }

      // if no training file given, we don't have any priors
      if ( (!trainSetPresent) && (printComplexityStatistics) )
        throw new Exception("Cannot print complexity statistics ('-k') without training file ('-t')!");

      // If a model file is given, we can't process
      // scheme-specific options
      if (objectInputFileName.length() != 0) {
        Utils.checkForRemainingOptions(options);
      } else {

        // Set options for classifier
        if (classifier instanceof OptionHandler) {
          for (int i = 0; i < options.length; i++) {
            if (options[i].length() != 0) {
              if (schemeOptionsText == null) {
                schemeOptionsText = new StringBuffer();
              }
              if (options[i].indexOf(' ') != -1) {
                schemeOptionsText.append('"' + options[i] + "\" ");
              } else {
                schemeOptionsText.append(options[i] + " ");
              }
            }
          }
          ((OptionHandler)classifier).setOptions(options);
        }
      }

      Utils.checkForRemainingOptions(options);
    } catch (Exception e) {
      throw new Exception("\nWeka exception: " + e.getMessage()
          + makeOptionString(classifier, false));
    }

    if (objectInputFileName.length() != 0) {
      // Load classifier from file
      if (objectInputStream != null) {
        classifier = (Classifier) objectInputStream.readObject();
        // try and read a header (if present)
        Instances savedStructure = null;
        try {
          savedStructure = (Instances) objectInputStream.readObject();
        } catch (Exception ex) {
          // don't make a fuss
        }
        if (savedStructure != null) {
          // test for compatibility with template
          if (!template.equalHeaders(savedStructure)) {
            throw new Exception("training and test set are not compatible\n" + template.equalHeadersMsg(savedStructure));
          }
        }
        objectInputStream.close();
      }
      else if (xmlInputStream != null) {
        // whether KOML is available has already been checked (objectInputStream would null otherwise)!
        classifier = (Classifier) KOML.read(xmlInputStream);
        xmlInputStream.close();
      }
    }
   
    // Setup up evaluation objects
    Evaluation trainingEvaluation = new Evaluation(new Instances(template, 0), costMatrix);
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    if (canUndo()) {
      // load file
      tempFile = (File) m_UndoList.get(m_UndoList.size() - 1);
      try {
        // read serialized data
        ooi = new ObjectInputStream(new BufferedInputStream(new FileInputStream(tempFile)));
        inst = (Instances) ooi.readObject();
        ooi.close();
       
        // set instances
        setInstances(inst);
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    try {
      Properties expProps = new Properties();
      String explorerProps = getPackageHome().getAbsolutePath()
        + File.separator + installedPackageName + File.separator
        + "Explorer.props";
      BufferedInputStream bi = new BufferedInputStream(new FileInputStream(explorerProps));
      expProps.load(bi);
      bi.close();
      bi = null;
      Set keys = expProps.keySet();
      Iterator keysI = keys.iterator();
      while (keysI.hasNext()) {
        String key = (String)keysI.next();
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  }
 
  protected static void processGenericPropertiesCreatorProps(File propsFile) {
    try {
      Properties expProps = new Properties();
      BufferedInputStream bi = new BufferedInputStream(new FileInputStream(propsFile));
      expProps.load(bi);
      bi.close();
      bi = null;
      Properties GPCInputProps = GenericPropertiesCreator.getGlobalInputProperties();
     
      Set keys = expProps.keySet();
      Iterator keysI = keys.iterator();
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  }
 
  protected static void processExplorerProps(File propsFile) {
    try {
      Properties expProps = new Properties();
      BufferedInputStream bi = new BufferedInputStream(new FileInputStream(propsFile));
      expProps.load(bi);
      bi.close();
      bi = null;
      Set keys = expProps.keySet();
      Iterator keysI = keys.iterator();
      while (keysI.hasNext()) {
        String key = (String)keysI.next();
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  protected static void processGUIEditorsProps(File propsFile) {
    GenericObjectEditor.registerEditors();
    try {
      Properties editorProps = new Properties();
      BufferedInputStream bi = new BufferedInputStream(new FileInputStream(propsFile));
      editorProps.load(bi);
      bi.close();
      bi = null;
     
      Enumeration enm = editorProps.propertyNames();
      while (enm.hasMoreElements()) {
        String name = enm.nextElement().toString();
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            client.initGet(remoteFile);

            // get an input stream to read data from ... AFTER we have
            // the ok to go ahead AND AFTER we've successfully opened a
            // stream for the local file
            in = new BufferedInputStream(new DataInputStream(client.getInputStream()));

        }
        catch (IOException ex) {
            client.validateTransferOnError(ex);
            throw ex;
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