package ca.pfv.spmf.patterns.rule_itemset_array_integer_with_count;

/* This file is copyright (c) 2008-2012 Philippe Fournier-Viger
* 
* This file is part of the SPMF DATA MINING SOFTWARE
* (http://www.philippe-fournier-viger.com/spmf).
* 
* SPMF 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 3 of the License, or (at your option) any later
* version.
* SPMF 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
* SPMF. If not, see .
*/


import ca.pfv.spmf.patterns.itemset_array_integers_with_count.Itemset;

/**
 * This class represent an association rule, where itemsets are arrays of integers.
 * 
 * @see Itemset
 * @see Rules
 * @author Philippe Fournier-Viger
 */
public class Rule {
	/** antecedent */
	private int[] itemset1; 
	/** consequent */
	private int[] itemset2;
	/** coverage (support of the antecedent)*/
	private int coverage;
	/** relative support */
	private int transactionCount; 
	/** confidence of the rule */
	private double confidence; 

	/**
	 * Constructor
	 * 
	 * @param itemset1
	 *            the antecedent of the rule (an itemset)
	 * @param itemset2
	 *            the consequent of the rule (an itemset)
	 * @param coverage the support of the antecedent as a number of transactions
	 * @param transactionCount
	 *            the absolute support of the rule (integer - a number of transactions)
	 * @param confidence
	 *            the confidence of the rule
	 */
	public Rule(int[] itemset1, int[] itemset2, int coverage,
			int transactionCount, double confidence) {
		this.itemset1 = itemset1;
		this.itemset2 = itemset2;
		this.coverage = coverage;
		this.transactionCount = transactionCount;
		this.confidence = confidence;
	}

	/**
	 * Get the relative support of the rule (percentage)
	 * 
	 * @param databaseSize
	 *            the number of transactions in the database where this rule was
	 *            found.
	 * @return the support (double)
	 */
	public double getRelativeSupport(int databaseSize) {
		return ((double) transactionCount) / ((double) databaseSize);
	}

	/**
	 * Get the absolute support of this rule (integer).
	 * 
	 * @return the absolute support.
	 */
	public int getAbsoluteSupport() {
		return transactionCount;
	}

	/**
	 * Get the confidence of this rule.
	 * 
	 * @return the confidence
	 */
	public double getConfidence() {
		return confidence;
	}
	
	/**
	 * Get the coverage of the rule (the support of the rule antecedent) as a number of transactions
	 * @return the coverage (int)
	 */
	public int getCoverage() {
		return coverage;
	}
	

	/**
	 * Print this rule to System.out.
	 */
	public void print() {
		System.out.println(toString());
	}

	/**
	 * Return a String representation of this rule
	 * 
	 * @return a String
	 */
	public String toString() {
		StringBuffer buffer = new StringBuffer();
		// write itemset 1
		for (int i = 0; i < itemset1.length; i++) {
			buffer.append(itemset1[i]);
			if (i != itemset1.length - 1) {
				buffer.append(" ");
			}
		}
		// write separator
		buffer.append(" ==> ");
		// write itemset 2
		for (int i = 0; i < itemset2.length; i++) {
			buffer.append(itemset2[i]);
			buffer.append(" ");
		}
		return buffer.toString();
	}

	/**
	 * Get the left itemset of this rule (antecedent).
	 * 
	 * @return an itemset.
	 */
	public int[] getItemset1() {
		return itemset1;
	}

	/**
	 * Get the right itemset of this rule (consequent).
	 * 
	 * @return an itemset.
	 */
	public int[] getItemset2() {
		return itemset2;
	}
}