weka.core.Drawable Java Examples

/**
 * Returns a string that describes a graph representing
 * the object. The string should be in XMLBIF ver.
 * 0.3 format if the graph is a BayesNet, otherwise
 * it should be in dotty format.
 *
 * @return the graph described by a string (label index as key)
 * @throws Exception if the graph can't be computed
 */
public Map<Integer,String> graph() throws Exception {
	Map<Integer,String>		result;
	int						i;

	result = new HashMap<Integer,String>();

	if (m_MultiClassifiers != null) {
		for (i = 0; i < m_MultiClassifiers.length; i++) {
			if (m_MultiClassifiers[i] instanceof Drawable) {
				result.put(i, ((Drawable) m_MultiClassifiers[i]).graph());
			}
		}
	}

	return result;
}
 

/**
 * Returns a string that describes a graph representing
 * the object. The string should be in XMLBIF ver.
 * 0.3 format if the graph is a BayesNet, otherwise
 * it should be in dotty format.
 *
 * @return the graph described by a string (label index as key)
 * @throws Exception if the graph can't be computed
 */
@Override
public Map<Integer,String> graph() throws Exception {
	Map<Integer,String>		result;

	result = new HashMap<Integer,String>();

	for (int i = 0; i < m_Classifiers.length; i++) {
		if (m_Classifiers[i] != null) {
			if (m_Classifiers[i] instanceof Drawable) {
				result.put(i, ((Drawable) m_Classifiers[i]).graph());
			}
		}
	}

	return result;
}
 

/**
 * Returns the type of graph representing
 * the object.
 *
 * @return the type of graph representing the object (label index as key)
 */
public Map<Integer,Integer> graphType() {
	Map<Integer,Integer>	result;
	int						i;

	result = new HashMap<Integer,Integer>();

	if (m_MultiClassifiers != null) {
		for (i = 0; i < m_MultiClassifiers.length; i++) {
			if (m_MultiClassifiers[i] instanceof Drawable) {
				result.put(i, ((Drawable) m_MultiClassifiers[i]).graphType());
			}
		}
	}

	return result;
}
 

/**
 * Returns a string that describes a graph representing
 * the object. The string should be in XMLBIF ver.
 * 0.3 format if the graph is a BayesNet, otherwise
 * it should be in dotty format.
 *
 * @return the graph described by a string (label index as key)
 * @throws Exception if the graph can't be computed
 */
public Map<Integer,String> graph() throws Exception {
	Map<Integer,String>		result;

	result = new HashMap<Integer,String>();

	if (getClassifier() != null) {
		if (getClassifier() instanceof Drawable) {
			result.put(0, ((Drawable) getClassifier()).graph());
		}
	}

	return result;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  
 *  @return the type of graph
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier != null && 
      m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + getClassifierSpec()
                           + " cannot be graphed");
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + getClassifierSpec()
	     + " cannot be graphed");
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  
 *  @return the type of graph
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + 
	     m_Classifier.getClass().getName() + " " +
	     Utils.joinOptions(m_BestClassifierOptions)
	     + " cannot be graphed");
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  
 *  @return the type of graph this classifier represents
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + getClassifierSpec()
	     + " cannot be graphed");
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  
 *  @return the type of graph this classifier represents
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + getClassifierSpec()
	     + " cannot be graphed");
}
 

/**
 * Returns the type of graph this classifier
 * represents.
 *  
 * @return the graph type of this classifier
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + getClassifierSpec()
	     + " cannot be graphed");
}
 

/**
 * Returns the type of graph this classifier
 * represents.
 *  
 * @return the type of graph this classifier represents
 */   
public int graphType() {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graphType();
  else 
    return Drawable.NOT_DRAWABLE;
}
 

/**
 * Returns the type of graph representing
 * the object.
 *
 * @return the type of graph representing the object (label index as key)
 */
public Map<Integer,Integer> graphType() {
	Map<Integer,Integer>	result;

	result = new HashMap<Integer,Integer>();

	if (getClassifier() != null) {
		if (getClassifier() instanceof Drawable) {
			result.put(0, ((Drawable) getClassifier()).graphType());
		}
	}

	return result;
}
 

/**
  * Make up the help string giving all the command line options
  *
  * @param clusterer the clusterer to include options for
  * @return a string detailing the valid command line options
  */
 private static String makeOptionString (Clusterer clusterer,
                                         boolean globalInfo) {
   StringBuffer optionsText = new StringBuffer("");
   // General options
   optionsText.append("\n\nGeneral options:\n\n");
   optionsText.append("-h or -help\n");
   optionsText.append("\tOutput help information.\n");
   optionsText.append("-synopsis or -info\n");
   optionsText.append("\tOutput synopsis for clusterer (use in conjunction "
       + " with -h)\n");
   optionsText.append("-t <name of training file>\n");
   optionsText.append("\tSets training file.\n");
   optionsText.append("-T <name of test file>\n");
   optionsText.append("\tSets test file.\n");
   optionsText.append("-l <name of input file>\n");
   optionsText.append("\tSets model input file.\n");
   optionsText.append("-d <name of output file>\n");
   optionsText.append("\tSets model output file.\n");
   optionsText.append("-p <attribute range>\n");
   optionsText.append("\tOutput predictions. Predictions are for " 
	       + "training file" 
	       + "\n\tif only training file is specified," 
	       + "\n\totherwise predictions are for the test file."
	       + "\n\tThe range specifies attribute values to be output"
	       + "\n\twith the predictions. Use '-p 0' for none.\n");
   optionsText.append("-x <number of folds>\n");
   optionsText.append("\tOnly Distribution Clusterers can be cross validated.\n");
   optionsText.append("-s <random number seed>\n");
   optionsText.append("\tSets the seed for randomizing the data in cross-validation\n");
   optionsText.append("-c <class index>\n");
   optionsText.append("\tSet class attribute. If supplied, class is ignored");
   optionsText.append("\n\tduring clustering but is used in a classes to");
   optionsText.append("\n\tclusters evaluation.\n");
   if (clusterer instanceof Drawable) {
     optionsText.append("-g <name of graph file>\n");
     optionsText.append("\tOutputs the graph representation of the clusterer to the file.\n");
   }

   // Get scheme-specific options
   if (clusterer instanceof OptionHandler) {
     optionsText.append("\nOptions specific to " 
		 + clusterer.getClass().getName() + ":\n\n");
     Enumeration enu = ((OptionHandler)clusterer).listOptions();

     while (enu.hasMoreElements()) {
Option option = (Option)enu.nextElement();
optionsText.append(option.synopsis() + '\n');
optionsText.append(option.description() + "\n");
     }
   }
   
   // Get global information (if available)
   if (globalInfo) {
     try {
       String gi = getGlobalInfo(clusterer);
       optionsText.append(gi);
     } catch (Exception ex) {
       // quietly ignore
     }
   }

   return  optionsText.toString();
 }
 

@Override
public int graphType() {
  return Drawable.TREE;
}
 

@Override
public int graphType() {
  return Drawable.Newick;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
  return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
  return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
  return Drawable.BayesNet;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}
 

/**
 *  Returns the type of graph this classifier
 *  represents.
 *  @return Drawable.TREE
 */   
public int graphType() {
    return Drawable.TREE;
}