fuzzyinfoclustering.java

一个用于排队系统仿真的开源软件,有非常形象的图象仿真过程!

/**    
  * Copyright (C) 2006, Laboratorio di Valutazione delle Prestazioni - Politecnico di Milano

  * This program is free software; you can redistribute it and/or modify
  * it under the terms of the GNU General Public License as published by
  * the Free Software Foundation; either version 2 of the License, or
  * (at your option) any later version.

  * This program is distributed in the hope that it will be useful,
  * but WITHOUT ANY WARRANTY; without even the implied warranty of
  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  * GNU General Public License for more details.

  * You should have received a copy of the GNU General Public License
  * along with this program; if not, write to the Free Software
  * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
  */
package jmt.engine.jwat.workloadAnalysis.clustering.fuzzyKMean.panels;

import java.awt.BorderLayout;
import java.awt.Color;
import java.awt.Dimension;
import java.awt.FlowLayout;
import java.awt.GridLayout;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;

import javax.swing.Box;
import javax.swing.JButton;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JScrollPane;
import javax.swing.JSpinner;
import javax.swing.JTable;
import javax.swing.ListSelectionModel;
import javax.swing.SpinnerNumberModel;
import javax.swing.table.AbstractTableModel;

import jmt.engine.jwat.MatrixOsservazioni;
import jmt.engine.jwat.workloadAnalysis.chart.DispFuzzyMatrix;
import jmt.engine.jwat.workloadAnalysis.clustering.fuzzyKMean.ClusteringInfosFuzzy;
import jmt.gui.common.CommonConstants;
import jmt.gui.jwat.DinamicFormat;
import jmt.gui.jwat.JWATConstants;

public class FuzzyInfoClustering extends JPanel implements CommonConstants,JWATConstants{
	private ClusteringInfosFuzzy infos = null; 
	private DispFuzzyMatrix matrix;
	private JTable clusteringFinalTable = null;
	private JLabel infoClustering = null;
	private JSpinner fuzzyError = null;
	private JButton selectErrore = null;
	private JLabel descrSetError = null;
	private int numClust = 0;
	private double entropy = 0.0;
	private MatrixOsservazioni m;
	private FuzzyInfoCluster fPanel = null;
	
	private String INFO_CLUSTERING = HTML_START + HTML_FONT_TITLE
		+ "CLUSTERING INFORMATION " + HTML_FONT_TIT_END + HTML_FONT_NORM + 
		"This clustering has been performed searching X clusters and the entropy for this<p>result is Y" + HTML_FONT_NOR_END + HTML_END;
	private String DESCR_ERRROR = HTML_START + HTML_FONT_TITLE
		+ "ERROR SETTING INFORMATION " + HTML_FONT_TIT_END + HTML_FONT_NORM + 
		"You can select which error to use to create each<p>single cluster according to Fuzzy K-Means<p>clustering results" + HTML_FONT_NOR_END + HTML_END;
	
	public FuzzyInfoClustering(MatrixOsservazioni m,DispFuzzyMatrix f,int numC,double ent,ClusteringInfosFuzzy c){
		matrix = f;
		numClust = numC;
		entropy = ent;
		infos = c;
		this.m = m;
		initPanel();
	}
	
	public void setPanelCluster(FuzzyInfoCluster f){
		fPanel = f;
	}
	
	private void initPanel(){
		this.setLayout(new GridLayout(1,1));
		Box mainPanel = Box.createHorizontalBox();
		mainPanel.add(Box.createHorizontalStrut(5));
		/** Pannello principale centrale **/
		JPanel centralMainP = new JPanel(new BorderLayout(5,10));
		/** Upper Panel **/
		JPanel upperP = new JPanel(new BorderLayout(5,5));
		/** Stringa infos clustering **/
		String current = new String(INFO_CLUSTERING);
		current = current.replaceFirst("X",Integer.toString(numClust));
		current = current.replaceFirst("Y",defaultFormat.format(entropy));
		infoClustering = new JLabel(current);
		upperP.add(infoClustering,BorderLayout.NORTH);
		/** Pannello selezione fuzzy error**/
		JPanel fuzzyErrorP = new JPanel(new GridLayout(1,2));
		/** Pannello text,spinner,button fuzzy error**/
		JPanel leftFuzzy = new JPanel(new FlowLayout(FlowLayout.LEFT,5,5));
		JLabel testoSpinner = new JLabel("Select the error: ");
		fuzzyError = new JSpinner(new SpinnerNumberModel(0.1,0.01,0.99,0.01));
		fuzzyError.setValue(new Double(infos.getError()));
		fuzzyError.setPreferredSize(new Dimension(60,25));
		selectErrore = new JButton("Apply error");
		selectErrore.addActionListener(new ActionListener(){
			public void actionPerformed(ActionEvent e) {
				/** Impostazione errore per visualizzazione matrice dispersione **/
				infos.setError(m,((Double)fuzzyError.getValue()).doubleValue());
				matrix.setFuzzyNess(((Double)fuzzyError.getValue()).doubleValue());
				((clustDetModel)clusteringFinalTable.getModel()).setInfos(infos.numElem,infos.percent);
				fPanel.setInfos();
				/** Impostazioni valori per tabella **/
			}
		});
		leftFuzzy.add(testoSpinner);
		leftFuzzy.add(fuzzyError);
		leftFuzzy.add(selectErrore);		
		/** Pannello con testo descrizione error **/
		descrSetError = new JLabel(DESCR_ERRROR);
		fuzzyErrorP.add(leftFuzzy);
		fuzzyErrorP.add(descrSetError);
		upperP.add(fuzzyErrorP,BorderLayout.SOUTH);
		/** Table results **/
		centralMainP.add(getUpperTable(),BorderLayout.CENTER);
		centralMainP.add(new JLabel("<HTML><b><font size = 4>WARNING</font></b><br><font size=3>The sum can be greater than 100% due to multiple observations assignement<br></font>"),BorderLayout.SOUTH);
		centralMainP.add(upperP,BorderLayout.NORTH);
		mainPanel.add(centralMainP);
		mainPanel.add(Box.createHorizontalStrut(5));
		this.add(mainPanel);
	}
	private JScrollPane getUpperTable(){
		clusteringFinalTable = new JTable(new clustDetModel(infos.numElem,infos.percent));
		clusteringFinalTable.setSelectionBackground(new Color(181,189,214));
		clusteringFinalTable.setSelectionForeground(Color.BLACK);
		clusteringFinalTable.setSelectionMode(ListSelectionModel.SINGLE_SELECTION);
		return new JScrollPane(clusteringFinalTable,JScrollPane.VERTICAL_SCROLLBAR_AS_NEEDED,JScrollPane.HORIZONTAL_SCROLLBAR_AS_NEEDED);
	}
	
	private class clustDetModel extends AbstractTableModel{
		private String[] colHeader={"Cluster","Num. observations","Percentage"};
		private int[] Elem = null;
		private double[] Perc = null;
		DinamicFormat f = new DinamicFormat("###.###%",0);	//????? CONTROLLARE A COSA E SE SERVE 
		
		public clustDetModel(int[] el,double perc[]){
			Elem = el;
			Perc = perc;
		}
		
		public int getRowCount() {
			return Elem.length; 
		}
		
		public int getColumnCount() {
			return colHeader.length;
		}
		
		public void setInfos(int[] el,double[] perc){
			Elem = el;
			Perc = perc;
			fireTableDataChanged();
		}
		
		public Object getValueAt(int rowIndex, int columnIndex) {
			if(rowIndex >= 0){
				if(columnIndex == 0) {
					if(rowIndex==Elem.length-1)return "Not assigned";
					else return "Cluster " + (rowIndex+1);
				}
				if(columnIndex == 1) {
					return Integer.toString(Elem[rowIndex]);
				}
				if(columnIndex == 2) {
					return f.format(Perc[rowIndex]);
				}
			}
			return null;
		}
		
		/**
		 * Returns name for each column (given its index) to be displayed inside
		 * table header
		 */
		public String getColumnName(int columnIndex) {
			if (columnIndex < colHeader.length)
				return colHeader[columnIndex];
			else
				return null;
		}
		
		/**
		 * Tells wether data contained in a specific cell(given row and column
		 * index) is editable or not. In this case distribution column is not
		 * editable, as editing functionality is implemented via edit button
		 */
		public boolean isCellEditable(int rowIndex, int columnIndex) {
			return false;
		}
	}
}