jwatunivariatestatstablemodel.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!

package jmt.engine.jwat.workloadAnalysis.tables;

import javax.swing.table.AbstractTableModel;

import jmt.engine.jwat.MatrixOsservazioni;
import jmt.gui.jwat.JWATConstants;

public class JWatUnivariateStatsTableModel extends AbstractTableModel implements JWATConstants{
	// TODO: Deve essergli passata una istanza di matrixOsservazioni o array di variabili
	// Nomi delle colonne della tabella
	protected String[] columnNames = new String[] { "Variable", "Mean", "Variance","Std. Dev.", 
			"Coeff. of var.","Minimum", "Maximum", "Range","Median","Kurtosis","Skewness","Num. Obs." };
	
	private MatrixOsservazioni data = null;
	//private DecimalFormat format = new DecimalFormat("####.####E0");
	
	public JWatUnivariateStatsTableModel(MatrixOsservazioni model){
		data = model;
	}
	
	public int getRowCount() {
		if(data == null) return 0;
		return data.getVariables().length;
	}

	public int getColumnCount() {
		return columnNames.length;
	}

	public Object getValueAt(int rowIndex, int columnIndex) {
		if(rowIndex >= 0){
			if(columnIndex == 0) {
				return data.getVariables()[rowIndex].getName(); 
			}if(columnIndex == 1) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getMean()); 
			}if(columnIndex == 2) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getVariance()); 
			}if(columnIndex == 3) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getDevStd()); 
			}if(columnIndex == 4) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getDevStd() / 
						data.getVariables()[rowIndex].getUniStats().getMean()); 
			}if(columnIndex == 5) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getMinValue()); 
			}if(columnIndex == 6) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getMaxValue()); 
			}if(columnIndex == 7) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getRangeValue()); 
			}if(columnIndex == 8) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getMedian()); 
			}if(columnIndex == 9) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getKurtosis()); 
			}if(columnIndex == 10) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getSkewness()); 
			}if(columnIndex == 11) {
				return defaultFormat.format(data.getVariables()[rowIndex].getUniStats().getNumObs()); 
			}
		}
		return null;
	}

	/**
	 * Returns name for each column (given its index) to be displayed inside
	 * table header
	 */
	public String getColumnName(int columnIndex) {
		if (columnIndex < columnNames.length)
			return columnNames[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;
	}
	
	public Class getColumnClass(int index) {
		return String.class;
	}
	
	public void setMatrixObs(MatrixOsservazioni m){
		data = m;
	}
}