/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2011 by Rapid-I and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapid-i.com
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Affero General Public License as published by
 *  the Free Software Foundation, either version 3 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 Affero General Public License for more details.
 *
 *  You should have received a copy of the GNU Affero General Public License
 *  along with this program.  If not, see http://www.gnu.org/licenses/.
 */
package com.rapidminer.gui.viewer;

import javax.swing.table.AbstractTableModel;

import com.rapidminer.operator.learner.subgroups.RuleSet;
import com.rapidminer.operator.learner.subgroups.hypothesis.Rule;
import com.rapidminer.operator.learner.subgroups.utility.Coverage;
import com.rapidminer.operator.learner.subgroups.utility.Precision;
import com.rapidminer.operator.learner.subgroups.utility.Accuracy;
import com.rapidminer.operator.learner.subgroups.utility.Bias;
import com.rapidminer.operator.learner.subgroups.utility.Lift;
import com.rapidminer.operator.learner.subgroups.utility.Binomial;
import com.rapidminer.operator.learner.subgroups.utility.WRAcc;
import com.rapidminer.operator.learner.subgroups.utility.Squared;
import com.rapidminer.operator.learner.subgroups.utility.Odds;
import com.rapidminer.operator.learner.subgroups.utility.OddsRatio;


/**
 * The table model for the rule set visualization.
 *
 * @author Ingo Mierswa, Tobias Malbrecht
 */
public class RuleSetTableModel extends AbstractTableModel {

	private static final long serialVersionUID = -4323147898914632476L;

	private static final String[] COLUMN_NAMES = {
		"Premise",
		"Conclusion",
		"Pos",
		"Neg",
		"Size",
		"Coverage",
		"Precision",
		"Accuracy",
		"Bias",
		"Lift",
		"Binomial",
		"WRAcc",
		"Squared",
		"Odds",
		"Odds Ratio",
		"Length"
	};
	
	private static final int COLUMN_PREMISES   = 0;
	private static final int COLUMN_CONCLUSION = 1;
	private static final int COLUMN_POSITIVE   = 2;
	private static final int COLUMN_NEGATIVE   = 3;
	private static final int COLUMN_SIZE       = 4;
	private static final int COLUMN_COVERAGE   = 5;
	private static final int COLUMN_PRECISION  = 6;
	private static final int COLUMN_ACCURACY   = 7;
	private static final int COLUMN_BIAS       = 8;
	private static final int COLUMN_LIFT       = 9;
	private static final int COLUMN_BINOMIAL   = 10;
	private static final int COLUMN_WRACC      = 11;
	private static final int COLUMN_SQUARED    = 12;
	private static final int COLUMN_ODDS       = 13;
	private static final int COLUMN_OR         = 14;
	private static final int COLUMN_LENGTH	   = 15;
	
	private RuleSet rules;
	
	public RuleSetTableModel(RuleSet rules) {
		this.rules = rules;
	}

	@Override
	public Class<?> getColumnClass(int column) {
		if ((column != COLUMN_PREMISES) && (column != COLUMN_CONCLUSION)) {
			return Double.class;
		} else {
			return String.class;
		}
	}
	
	@Override
	public String getColumnName(int column) {
		return COLUMN_NAMES[column];
	}
	
	public int getColumnCount() {
		return COLUMN_NAMES.length;
	}

	public int getRowCount() {
		return rules.getNumberOfRules();
	}

	public Object getValueAt(int rowIndex, int columnIndex) {
		Rule rule = rules.getRule(rowIndex);
		switch (columnIndex) {
		case COLUMN_PREMISES:
			return rule.getPremise().toString();
		case COLUMN_CONCLUSION:
			return rule.getConclusion().getValueAsString();
		case COLUMN_POSITIVE:
			return rule.getPositiveWeight();
		case COLUMN_NEGATIVE:
			return rule.getNegativeWeight();
		case COLUMN_SIZE:
			return rule.getCoveredWeight();
		case COLUMN_COVERAGE:
			return rule.getUtility(Coverage.class);
		case COLUMN_PRECISION:
			return rule.getUtility(Precision.class);
		case COLUMN_ACCURACY:
			return rule.getUtility(Accuracy.class);
		case COLUMN_BIAS:
			return rule.getUtility(Bias.class);
		case COLUMN_LIFT:
			return rule.getUtility(Lift.class);
		case COLUMN_BINOMIAL:
			return rule.getUtility(Binomial.class);
		case COLUMN_WRACC:
			return rule.getUtility(WRAcc.class);
		case COLUMN_SQUARED:
			return rule.getUtility(Squared.class);
		case COLUMN_ODDS:
			return rule.getUtility(Odds.class);
		case COLUMN_OR:
			return rule.getUtility(OddsRatio.class);
		case COLUMN_LENGTH:
			return rule.getHypothesis().getNumberOfLiterals();
		default:
			// cannot happen
			return "?";
		}
	}
	
}