Java 类weka.core.SerializedObject 实例源码

项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
DelValueAction(int nTargetNode, String sValue) {
  try {
    m_nTargetNode = nTargetNode;
    m_sValue = sValue;
    m_att = m_Instances.attribute(nTargetNode);
    SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
    m_CPT = (Estimator[]) so.getObject();
    ;
    m_children = new ArrayList<Integer>();
    for (int iNode = 0; iNode < getNrOfNodes(); iNode++) {
      if (m_ParentSets[iNode].contains(nTargetNode)) {
        m_children.add(iNode);
      }
    }
    m_childAtts = new Estimator[m_children.size()][];
    for (int iChild = 0; iChild < m_children.size(); iChild++) {
      int nChild = m_children.get(iChild);
      m_childAtts[iChild] = m_Distributions[nChild];
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:Kernel.java   
/**
 * Creates a given number of deep or shallow (if the kernel implements
 * Copyable) copies of the given kernel using serialization.
 * 
 * @param model the kernel to copy
 * @param num the number of kernel copies to create.
 * @return an array of kernels.
 * @throws Exception if an error occurs
 */
public static Kernel[] makeCopies(Kernel model, int num) throws Exception {
  if (model == null) {
    throw new Exception("No model kernel set");
  }

  Kernel[] kernels = new Kernel[num];
  if (model instanceof Copyable) {
    for (int i = 0; i < kernels.length; i++) {
      kernels[i] = (Kernel) ((Copyable) model).copy();
    }
  } else {
    SerializedObject so = new SerializedObject(model);
    for (int i = 0; i < kernels.length; i++) {
      kernels[i] = (Kernel) so.getObject();
    }
  }

  return kernels;
}
项目:repo.kmeanspp.silhouette_score    文件:KnowledgeFlowApp.java   
/**
 * Gets the current flow being edited. The flow is returned as a single Vector
 * containing two other Vectors: the beans and the connections. These two
 * vectors are deep-copied via serialization before being returned.
 * 
 * @return the current flow being edited
 * @throws Exception if a problem occurs
 */
public Vector<Vector<?>> getFlow() throws Exception {
  Vector<Vector<?>> v = new Vector<Vector<?>>();
  Vector<Object> beans = BeanInstance.getBeanInstances(m_mainKFPerspective
    .getCurrentTabIndex());
  Vector<BeanConnection> connections = BeanConnection
    .getConnections(m_mainKFPerspective.getCurrentTabIndex());
  detachFromLayout(beans);
  v.add(beans);
  v.add(connections);

  SerializedObject so = new SerializedObject(v);
  @SuppressWarnings("unchecked")
  Vector<Vector<?>> copy = (Vector<Vector<?>>) so.getObject();

  // tempWrite(beans, connections);

  integrateFlow(beans, connections, true, false);
  return copy;
}
项目:repo.kmeanspp.silhouette_score    文件:TransformationDictionary.java   
/**
 * Get a named DefineFunction. Returns a deep copy of the function.
 * 
 * @param functionName the name of the function to get
 * @return the named function or null if it cannot be found
 * @throws Exception if there is a problem deep copying the function
 */
protected DefineFunction getFunction(String functionName) throws Exception {

  DefineFunction copy = null;
  DefineFunction match = null;
  for (DefineFunction f : m_defineFunctions) {
    if (f.getName().equals(functionName)) {
      match = f;
      // System.err.println("Found a match!!!");
      break;
    }
  }

  if (match != null) {
    SerializedObject so = new SerializedObject(match, false);
    copy = (DefineFunction) so.getObject();
    // System.err.println(copy);
  }

  return copy;
}
项目:autoweka    文件:EditableBayesNet.java   
DelValueAction(int nTargetNode, String sValue) {
    try {
        m_nTargetNode = nTargetNode;
        m_sValue = sValue;
        m_att = m_Instances.attribute(nTargetNode);
        SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
        m_CPT = (Estimator[]) so.getObject();
        ;
        m_children = new FastVector();
        for (int iNode = 0; iNode < getNrOfNodes(); iNode++) {
            if (m_ParentSets[iNode].contains(nTargetNode)) {
                m_children.addElement(iNode);
            }
        }
        m_childAtts = new Estimator[m_children.size()][];
        for (int iChild = 0; iChild < m_children.size(); iChild++) {
            int nChild = (Integer) m_children.elementAt(iChild);
            m_childAtts[iChild] = m_Distributions[nChild];
        }
    } catch (Exception e) {
        e.printStackTrace();
    }
}
项目:autoweka    文件:KnowledgeFlowApp.java   
/**
 * Gets the current flow being edited. The flow is returned as a single
 * Vector containing two other Vectors: the beans and the connections.
 * These two vectors are deep-copied via serialization before being
 * returned.
 *
 * @return the current flow being edited
 */
public Vector getFlow() throws Exception {
  Vector v = new Vector();
  Vector beans = 
    BeanInstance.getBeanInstances(m_mainKFPerspective.getCurrentTabIndex());
  Vector connections = 
    BeanConnection.getConnections(m_mainKFPerspective.getCurrentTabIndex());
  detachFromLayout(beans);
  v.add(beans);
  v.add(connections);

  SerializedObject so = new SerializedObject(v);
  Vector copy = (Vector)so.getObject();

  //    tempWrite(beans, connections);

  integrateFlow(beans, connections, true, false);
  return copy;
}
项目:autoweka    文件:TransformationDictionary.java   
/**
 * Get a named DefineFunction. Returns a deep copy of the
 * function.
 * 
 * @param functionName the name of the function to get
 * @return the named function or null if it cannot be found
 * @throws Exception if there is a problem deep copying the function
 */
protected DefineFunction getFunction(String functionName) throws Exception {

  DefineFunction copy = null;
  DefineFunction match = null;
  for (DefineFunction f : m_defineFunctions) {
    if (f.getName().equals(functionName)) {
      match = f;
      //System.err.println("Found a match!!!");
      break;
    }
  }

  if (match != null) {
    SerializedObject so = new SerializedObject(match, false);
    copy = (DefineFunction)so.getObject();
    //System.err.println(copy);
  }

  return copy;
}
项目:umple    文件:EditableBayesNet.java   
DelValueAction(int nTargetNode, String sValue) {
  try {
    m_nTargetNode = nTargetNode;
    m_sValue = sValue;
    m_att = m_Instances.attribute(nTargetNode);
    SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
    m_CPT = (Estimator[]) so.getObject();
    ;
    m_children = new ArrayList<Integer>();
    for (int iNode = 0; iNode < getNrOfNodes(); iNode++) {
      if (m_ParentSets[iNode].contains(nTargetNode)) {
        m_children.add(iNode);
      }
    }
    m_childAtts = new Estimator[m_children.size()][];
    for (int iChild = 0; iChild < m_children.size(); iChild++) {
      int nChild = m_children.get(iChild);
      m_childAtts[iChild] = m_Distributions[nChild];
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:umple    文件:EditableBayesNet.java   
DelValueAction(int nTargetNode, String sValue) {
  try {
    m_nTargetNode = nTargetNode;
    m_sValue = sValue;
    m_att = m_Instances.attribute(nTargetNode);
    SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
    m_CPT = (Estimator[]) so.getObject();
    ;
    m_children = new ArrayList<Integer>();
    for (int iNode = 0; iNode < getNrOfNodes(); iNode++) {
      if (m_ParentSets[iNode].contains(nTargetNode)) {
        m_children.add(iNode);
      }
    }
    m_childAtts = new Estimator[m_children.size()][];
    for (int iChild = 0; iChild < m_children.size(); iChild++) {
      int nChild = m_children.get(iChild);
      m_childAtts[iChild] = m_Distributions[nChild];
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:umple    文件:Kernel.java   
/**
 * Creates a given number of deep or shallow (if the kernel implements
 * Copyable) copies of the given kernel using serialization.
 * 
 * @param model the kernel to copy
 * @param num the number of kernel copies to create.
 * @return an array of kernels.
 * @throws Exception if an error occurs
 */
public static Kernel[] makeCopies(Kernel model, int num) throws Exception {
  if (model == null) {
    throw new Exception("No model kernel set");
  }

  Kernel[] kernels = new Kernel[num];
  if (model instanceof Copyable) {
    for (int i = 0; i < kernels.length; i++) {
      kernels[i] = (Kernel) ((Copyable) model).copy();
    }
  } else {
    SerializedObject so = new SerializedObject(model);
    for (int i = 0; i < kernels.length; i++) {
      kernels[i] = (Kernel) so.getObject();
    }
  }

  return kernels;
}
项目:umple    文件:KnowledgeFlowApp.java   
/**
 * Gets the current flow being edited. The flow is returned as a single Vector
 * containing two other Vectors: the beans and the connections. These two
 * vectors are deep-copied via serialization before being returned.
 * 
 * @return the current flow being edited
 * @throws Exception if a problem occurs
 */
public Vector<Vector<?>> getFlow() throws Exception {
  Vector<Vector<?>> v = new Vector<Vector<?>>();
  Vector<Object> beans = BeanInstance.getBeanInstances(m_mainKFPerspective
    .getCurrentTabIndex());
  Vector<BeanConnection> connections = BeanConnection
    .getConnections(m_mainKFPerspective.getCurrentTabIndex());
  detachFromLayout(beans);
  v.add(beans);
  v.add(connections);

  SerializedObject so = new SerializedObject(v);
  @SuppressWarnings("unchecked")
  Vector<Vector<?>> copy = (Vector<Vector<?>>) so.getObject();

  // tempWrite(beans, connections);

  integrateFlow(beans, connections, true, false);
  return copy;
}
项目:umple    文件:TransformationDictionary.java   
/**
 * Get a named DefineFunction. Returns a deep copy of the function.
 * 
 * @param functionName the name of the function to get
 * @return the named function or null if it cannot be found
 * @throws Exception if there is a problem deep copying the function
 */
protected DefineFunction getFunction(String functionName) throws Exception {

  DefineFunction copy = null;
  DefineFunction match = null;
  for (DefineFunction f : m_defineFunctions) {
    if (f.getName().equals(functionName)) {
      match = f;
      // System.err.println("Found a match!!!");
      break;
    }
  }

  if (match != null) {
    SerializedObject so = new SerializedObject(match, false);
    copy = (DefineFunction) so.getObject();
    // System.err.println(copy);
  }

  return copy;
}
项目:jbossBA    文件:EditableBayesNet.java   
DelValueAction(int nTargetNode, String sValue) {
    try {
        m_nTargetNode = nTargetNode;
        m_sValue = sValue;
        m_att = m_Instances.attribute(nTargetNode);
        SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
        m_CPT = (Estimator[]) so.getObject();
        ;
        m_children = new FastVector();
        for (int iNode = 0; iNode < getNrOfNodes(); iNode++) {
            if (m_ParentSets[iNode].contains(nTargetNode)) {
                m_children.addElement(iNode);
            }
        }
        m_childAtts = new Estimator[m_children.size()][];
        for (int iChild = 0; iChild < m_children.size(); iChild++) {
            int nChild = (Integer) m_children.elementAt(iChild);
            m_childAtts[iChild] = m_Distributions[nChild];
        }
    } catch (Exception e) {
        e.printStackTrace();
    }
}
项目:jbossBA    文件:Kernel.java   
/**
 * Creates a given number of deep or shallow (if the kernel implements Copyable) 
 * copies of the given kernel using serialization.
 * 
 * @param model     the kernel to copy
 * @param num   the number of kernel copies to create.
 * @return      an array of kernels.
 * @throws Exception    if an error occurs
 */
public static Kernel[] makeCopies(Kernel model, int num) throws Exception {
  if (model == null)
    throw new Exception("No model kernel set");

  Kernel[] kernels = new Kernel[num];
  if (model instanceof Copyable) {
    for (int i = 0; i < kernels.length; i++) {
      kernels[i] = (Kernel) ((Copyable) model).copy();
    }
  } else {
    SerializedObject so = new SerializedObject(model);
    for (int i = 0; i < kernels.length; i++)
      kernels[i] = (Kernel) so.getObject();
  }

  return kernels;
}
项目:jbossBA    文件:KnowledgeFlowApp.java   
/**
 * Instantiates (by making a serialized copy) the supplied template meta bean
 * for display in the user tool bar
 * 
 * @param bean the prototype MetaBean to display in the toolbar
 */
private JPanel instantiateToolBarMetaBean(MetaBean bean) {
  // copy the bean via serialization
  ((Visible) bean).getVisual().removePropertyChangeListener(this);
  bean.removePropertyChangeListenersSubFlow(this);
  Object copy = null;
  try {
    SerializedObject so = new SerializedObject(bean);
    copy = so.getObject();
  } catch (Exception ex) {
    ex.printStackTrace();
    return null;
  }
  ((Visible) bean).getVisual().addPropertyChangeListener(this);
  bean.addPropertyChangeListenersSubFlow(this);

  String displayName = "";
  //
  if (copy instanceof Visible) {
    ((Visible) copy).getVisual().scale(3);
    displayName = ((Visible) copy).getVisual().getText();
  }
  return makeHolderPanelForToolBarBean(displayName, copy, false, null, true);
}
项目:jbossBA    文件:KnowledgeFlowApp.java   
/**
 * Gets the current flow being edited. The flow is returned as a single Vector
 * containing two other Vectors: the beans and the connections. These two
 * vectors are deep-copied via serialization before being returned.
 * 
 * @return the current flow being edited
 */
public Vector getFlow() throws Exception {
  Vector v = new Vector();
  Vector beans = BeanInstance.getBeanInstances();
  Vector connections = BeanConnection.getConnections();
  detachFromLayout(beans);
  v.add(beans);
  v.add(connections);

  SerializedObject so = new SerializedObject(v);
  Vector copy = (Vector) so.getObject();

  // tempWrite(beans, connections);

  integrateFlow(beans, connections);
  return copy;
}
项目:jbossBA    文件:TransformationDictionary.java   
/**
 * Get a named DefineFunction. Returns a deep copy of the
 * function.
 * 
 * @param functionName the name of the function to get
 * @return the named function or null if it cannot be found
 * @throws Exception if there is a problem deep copying the function
 */
protected DefineFunction getFunction(String functionName) throws Exception {

  DefineFunction copy = null;
  DefineFunction match = null;
  for (DefineFunction f : m_defineFunctions) {
    if (f.getName().equals(functionName)) {
      match = f;
      //System.err.println("Found a match!!!");
      break;
    }
  }

  if (match != null) {
    SerializedObject so = new SerializedObject(match, false);
    copy = (DefineFunction)so.getObject();
    //System.err.println(copy);
  }

  return copy;
}
项目:repo.kmeanspp.silhouette_score    文件:AbstractClusterer.java   
/**
 * Creates copies of the current clusterer. Note that this method now uses
 * Serialization to perform a deep copy, so the Clusterer object must be fully
 * Serializable. Any currently built model will now be copied as well.
 * 
 * @param model an example clusterer to copy
 * @param num the number of clusterer copies to create.
 * @return an array of clusterers.
 * @exception Exception if an error occurs
 */
public static Clusterer[] makeCopies(Clusterer model, int num)
  throws Exception {
  if (model == null) {
    throw new Exception("No model clusterer set");
  }
  Clusterer[] clusterers = new Clusterer[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < clusterers.length; i++) {
    clusterers[i] = (Clusterer) so.getObject();
  }
  return clusterers;
}
项目:repo.kmeanspp.silhouette_score    文件:AbstractDensityBasedClusterer.java   
/**
 * Creates copies of the current clusterer. Note that this method
 * now uses Serialization to perform a deep copy, so the Clusterer
 * object must be fully Serializable. Any currently built model will
 * now be copied as well.
 *
 * @param model an example clusterer to copy
 * @param num the number of clusterer copies to create.
 * @return an array of clusterers.
 * @exception Exception if an error occurs 
 */
public static DensityBasedClusterer [] makeCopies(DensityBasedClusterer model,
                    int num) throws Exception {
   if (model == null) {
    throw new Exception("No model clusterer set");
  }
  DensityBasedClusterer [] clusterers = new DensityBasedClusterer [num];
  SerializedObject so = new SerializedObject(model);
  for(int i = 0; i < clusterers.length; i++) {
    clusterers[i] = (DensityBasedClusterer) so.getObject();
  }
  return clusterers;
}
项目:repo.kmeanspp.silhouette_score    文件:ASEvaluation.java   
/**
 * Creates copies of the current evaluator. Note that this method now uses
 * Serialization to perform a deep copy, so the evaluator object must be fully
 * Serializable. Any currently built model will now be copied as well.
 * 
 * @param model an example evaluator to copy
 * @param num the number of evaluator copies to create.
 * @return an array of evaluators.
 * @exception Exception if an error occurs
 */
public static ASEvaluation[] makeCopies(ASEvaluation model,
  int num) throws Exception {

  if (model == null) {
    throw new Exception("No model evaluator set");
  }
  ASEvaluation[] evaluators = new ASEvaluation[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < evaluators.length; i++) {
    evaluators[i] = (ASEvaluation) so.getObject();
  }
  return evaluators;
}
项目:repo.kmeanspp.silhouette_score    文件:ASSearch.java   
/**
 * Creates copies of the current search scheme. Note that this method
 * now uses Serialization to perform a deep copy, so the search
 * object must be fully Serializable. Any currently built model will
 * now be copied as well.
 *
 * @param model an example search scheme to copy
 * @param num the number of search scheme copies to create.
 * @return an array of search schemes.
 * @throws Exception if an error occurs 
 */
public static ASSearch[] makeCopies(ASSearch model, int num) throws Exception {

  if (model == null)
    throw new Exception("No model search scheme set");

  ASSearch[] result = new ASSearch[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < result.length; i++)
    result[i] = (ASSearch) so.getObject();

  return result;
}
项目:repo.kmeanspp.silhouette_score    文件:CheckAttributeSelection.java   
/**
 * returns deep copies of the given object
 * 
 * @param obj the object to copy
 * @param num the number of copies
 * @return the deep copies
 * @throws Exception if copying fails
 */
protected Object[] makeCopies(Object obj, int num) throws Exception {
  if (obj == null) {
    throw new Exception("No object set");
  }

  Object[] objs = new Object[num];
  SerializedObject so = new SerializedObject(obj);
  for (int i = 0; i < objs.length; i++) {
    objs[i] = so.getObject();
  }

  return objs;
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
AddArcAction(int nParent, int nChild) {
  try {
    m_nParent = nParent;
    m_children = new ArrayList<Integer>();
    m_children.add(nChild);
    // m_nChild = nChild;
    SerializedObject so = new SerializedObject(m_Distributions[nChild]);
    m_CPT = new Estimator[1][];
    m_CPT[0] = (Estimator[]) so.getObject();
    ;
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
AddArcAction(int nParent, ArrayList<Integer> children) {
  try {
    m_nParent = nParent;
    m_children = new ArrayList<Integer>();
    m_CPT = new Estimator[children.size()][];
    for (int iChild = 0; iChild < children.size(); iChild++) {
      int nChild = children.get(iChild);
      m_children.add(nChild);
      SerializedObject so = new SerializedObject(m_Distributions[nChild]);
      m_CPT[iChild] = (Estimator[]) so.getObject();
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
@Override
public void undo() {
  try {
    for (int iChild = 0; iChild < m_children.size(); iChild++) {
      int nChild = m_children.get(iChild);
      deleteArc(m_nParent, nChild);
      SerializedObject so = new SerializedObject(m_CPT[iChild]);
      m_Distributions[nChild] = (Estimator[]) so.getObject();
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
DeleteArcAction(int nParent, int nChild) {
  try {
    m_nChild = nChild;
    m_nParent = nParent;
    m_nParents = new int[getNrOfParents(nChild)];
    for (int iParent = 0; iParent < m_nParents.length; iParent++) {
      m_nParents[iParent] = getParent(nChild, iParent);
    }
    SerializedObject so = new SerializedObject(m_Distributions[nChild]);
    m_CPT = (Estimator[]) so.getObject();
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
@Override
public void undo() {
  try {
    SerializedObject so = new SerializedObject(m_CPT);
    m_Distributions[m_nChild] = (Estimator[]) so.getObject();
    ParentSet parentSet = new ParentSet();
    for (int m_nParent2 : m_nParents) {
      parentSet.addParent(m_nParent2, m_Instances);
    }
    m_ParentSets[m_nChild] = parentSet;
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
SetDistributionAction(int nTargetNode, double[][] P) {
  try {
    m_nTargetNode = nTargetNode;
    SerializedObject so = new SerializedObject(m_Distributions[nTargetNode]);
    m_CPT = (Estimator[]) so.getObject();
    ;
    m_P = P;
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:EditableBayesNet.java   
@Override
public void undo() {
  try {
    SerializedObject so = new SerializedObject(m_CPT);
    m_Distributions[m_nTargetNode] = (Estimator[]) so.getObject();
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:GUI.java   
void updateStatus() {
  a_undo.setEnabled(m_BayesNet.canUndo());
  a_redo.setEnabled(m_BayesNet.canRedo());

  a_datagenerator.setEnabled(m_BayesNet.getNrOfNodes() > 0);

  if (!m_bViewMargins && !m_bViewCliques) {
    repaint();
    return;
  }

  try {
    m_marginCalculator = new MarginCalculator();
    m_marginCalculator.calcMargins(m_BayesNet);
    SerializedObject so = new SerializedObject(m_marginCalculator);
    m_marginCalculatorWithEvidence = (MarginCalculator) so.getObject();
    for (int iNode = 0; iNode < m_BayesNet.getNrOfNodes(); iNode++) {
      if (m_BayesNet.getEvidence(iNode) >= 0) {
        m_marginCalculatorWithEvidence.setEvidence(iNode,
          m_BayesNet.getEvidence(iNode));
      }
    }
    for (int iNode = 0; iNode < m_BayesNet.getNrOfNodes(); iNode++) {
      m_BayesNet.setMargin(iNode,
        m_marginCalculatorWithEvidence.getMargin(iNode));
    }
  } catch (Exception e) {
    e.printStackTrace();
  }
  repaint();
}
项目:repo.kmeanspp.silhouette_score    文件:AbstractClassifier.java   
/**
 * Creates a given number of deep copies of the given classifier using
 * serialization.
 *
 * @param model the classifier to copy
 * @param num the number of classifier copies to create.
 * @return an array of classifiers.
 * @exception Exception if an error occurs
 */
public static Classifier[] makeCopies(Classifier model, int num)
  throws Exception {

  if (model == null) {
    throw new Exception("No model classifier set");
  }
  Classifier[] classifiers = new Classifier[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < classifiers.length; i++) {
    classifiers[i] = (Classifier) so.getObject();
  }
  return classifiers;
}
项目:repo.kmeanspp.silhouette_score    文件:Script.java   
/**
 * Executes the script without loading it first.
 * 
 * @param file the script to execute
 * @param args the commandline parameters for the script
 */
public void run(File file, String[] args) {
  Script script;

  try {
    script = (Script) new SerializedObject(this).getObject();
    script.m_Filename = file;
    script.m_Modified = false;
    script.start(args);
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:ArffTable.java   
/**
 * sets the cell renderer and calcs the optimal column width
 */
private void setLayout() {
  ArffSortedTableModel arffModel;
  int i;
  JComboBox combo;
  Enumeration<Object> enm;

  arffModel = (ArffSortedTableModel) getModel();

  for (i = 0; i < getColumnCount(); i++) {
    // optimal colwidths (only according to header!)
    JTableHelper.setOptimalHeaderWidth(this, i);

    // CellRenderer
    getColumnModel().getColumn(i)
      .setCellRenderer(new ArffTableCellRenderer());

    // CellEditor
    if (i > 0) {
      if (arffModel.getType(i) == Attribute.NOMINAL) {
        combo = new JComboBox();
        combo.addItem(null);
        enm = arffModel.getInstances().attribute(i - 1).enumerateValues();
        while (enm.hasMoreElements()) {
          Object o = enm.nextElement();
          if (o instanceof SerializedObject) {
            ((SerializedObject) o).getObject();
          }
          combo.addItem(o);
        }
        getColumnModel().getColumn(i).setCellEditor(
          new DefaultCellEditor(combo));
      } else {
        getColumnModel().getColumn(i).setCellEditor(null);
      }
    }
  }
}
项目:repo.kmeanspp.silhouette_score    文件:KnowledgeFlowApp.java   
/**
 * Set the flow for the KnowledgeFlow to edit. Assumes that client has loaded
 * a Vector of beans and a Vector of connections. the supplied beans and
 * connections are deep-copied via serialization before being set in the
 * layout. The beans get added to the flow at position 0.
 * 
 * @param v a Vector containing a Vector of beans and a Vector of connections
 * @exception Exception if something goes wrong
 */
@SuppressWarnings("unchecked")
public void setFlow(Vector<Vector<?>> v) throws Exception {
  // Vector beansCopy = null, connectionsCopy = null;
  // clearLayout();
  if (getAllowMultipleTabs()) {
    throw new Exception("[KnowledgeFlow] setFlow() - can only set a flow in "
      + "singe tab only mode");
  }

  /*
   * int tabI = 0;
   * 
   * BeanInstance.
   * removeAllBeansFromContainer((JComponent)m_mainKFPerspective.
   * getBeanLayout(tabI), tabI); BeanInstance.setBeanInstances(new Vector(),
   * m_mainKFPerspective.getBeanLayout(tabI));
   * BeanConnection.setConnections(new Vector());
   */
  // m_mainKFPerspective.removeTab(0);
  // m_mainKFPerspective.addTab("Untitled");
  m_beanLayout.removeAll();
  BeanInstance.init();
  BeanConnection.init();

  SerializedObject so = new SerializedObject(v);
  Vector<Vector<?>> copy = (Vector<Vector<?>>) so.getObject();

  Vector<Object> beans = (Vector<Object>) copy.elementAt(0);
  Vector<BeanConnection> connections = (Vector<BeanConnection>) copy
    .elementAt(1);

  // reset environment variables
  m_flowEnvironment = new Environment();
  integrateFlow(beans, connections, true, false);
  revalidate();
  notifyIsDirty();
}
项目:repo.kmeanspp.silhouette_score    文件:RunPanel.java   
public ExperimentRunner(final Experiment exp) throws Exception {

      // Create a full copy using serialization
      if (exp == null) {
    System.err.println("Null experiment!!!");
      } else {
    System.err.println("Running experiment: " + exp.toString());
      }
      System.err.println("Writing experiment copy");
      SerializedObject so = new SerializedObject(exp);
      System.err.println("Reading experiment copy");
      m_ExpCopy = (Experiment) so.getObject();
      System.err.println("Made experiment copy");
    }
项目:repo.kmeanspp.silhouette_score    文件:AlgorithmListPanel.java   
/**
 * Makes a copy of an object using serialization
 * 
 * @param source the object to copy
 * @return a copy of the source object
 */
protected Object copyObject(Object source) {

  Object result = null;
  try {
    SerializedObject so = new SerializedObject(source);
    result = so.getObject();
  } catch (Exception ex) {
    System.err.println("AlgorithmListPanel: Problem copying object");
    System.err.println(ex);
  }
  return result;
}
项目:repo.kmeanspp.silhouette_score    文件:Filter.java   
/**
 * Creates a given number of deep copies of the given filter using
 * serialization.
 *
 * @param model the filter to copy
 * @param num the number of filter copies to create.
 * @return an array of filters.
 * @throws Exception if an error occurs
 */
public static Filter[] makeCopies(Filter model, int num) throws Exception {

  if (model == null) {
    throw new Exception("No model filter set");
  }
  Filter[] filters = new Filter[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < filters.length; i++) {
    filters[i] = (Filter) so.getObject();
  }
  return filters;
}
项目:repo.kmeanspp.silhouette_score    文件:FilteredNeighbourSearch.java   
/**
 * Sets the instances to build the filtering model from.
 * 
 * @param insts the Instances object
 */
public void setInstances(Instances data) {

  try {
    super.setInstances(data);

    // Apply user-specified filter
    Instances filteredData = new Instances(data);
    getFilter().setInputFormat(filteredData);
    filteredData = Filter.useFilter(data, getFilter());
    if (data.numInstances() != filteredData.numInstances()) {
      throw new IllegalArgumentException(
        "FilteredNeighbourSearch: Filter has changed the number of instances!");
    }

    // Set up filter to add ID
    m_IndexOfID = filteredData.numAttributes();
    m_AddID.setIDIndex("" + (filteredData.numAttributes() + 1));
    ;
    m_AddID.setInputFormat(filteredData);
    filteredData = Filter.useFilter(filteredData, m_AddID);

    // Modify distance function for base method to skip ID
    // User-specified range setting for the distance function is simply
    // ignored
    m_ModifiedSearchMethod = (NearestNeighbourSearch) new SerializedObject(
      getSearchMethod()).getObject();
    m_ModifiedSearchMethod.getDistanceFunction().setAttributeIndices(
      "1-" + m_IndexOfID);
    m_ModifiedSearchMethod.getDistanceFunction().setInvertSelection(false);

    // Set up the distance function
    m_ModifiedSearchMethod.setInstances(filteredData);
  } catch (Exception e) {
    e.printStackTrace();
  }
}
项目:repo.kmeanspp.silhouette_score    文件:Estimator.java   
/**
 * Creates a given number of deep copies of the given estimator using
 * serialization.
 * 
 * @param model the estimator to copy
 * @param num the number of estimator copies to create.
 * @return an array of estimators.
 * @exception Exception if an error occurs
 */
public static Estimator[] makeCopies(Estimator model, int num)
  throws Exception {

  if (model == null) {
    throw new Exception("No model estimator set");
  }
  Estimator[] estimators = new Estimator[num];
  SerializedObject so = new SerializedObject(model);
  for (int i = 0; i < estimators.length; i++) {
    estimators[i] = (Estimator) so.getObject();
  }
  return estimators;
}
项目:Keel3.0    文件:Classifier.java   
/**
 * Creates a given number of deep copies of the given classifier using serialization.
 *
 * @param model the classifier to copy
 * @param num the number of classifier copies to create.
 * @return an array of classifiers.
 * @exception Exception if an error occurs
 */
public static Classifier [] makeCopies(Classifier model,
             int num) throws Exception {

  if (model == null) {
    throw new Exception("No model classifier set");
  }
  Classifier [] classifiers = new Classifier [num];
  SerializedObject so = new SerializedObject(model);
  for(int i = 0; i < classifiers.length; i++) {
    classifiers[i] = (Classifier) so.getObject();
  }
  return classifiers;
}