PredicateContentEvent.java

package com.yahoo.labs.samoa.learners.classifiers.rules.distributed;

/*
 * #%L
 * SAMOA
 * %%
 * Copyright (C) 2013 - 2014 Yahoo! Inc.
 * %%
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 * 
 *      http://www.apache.org/licenses/LICENSE-2.0
 * 
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * #L%
 */

import com.yahoo.labs.samoa.core.ContentEvent;
import com.yahoo.labs.samoa.learners.classifiers.rules.common.RulePassiveRegressionNode;
import com.yahoo.labs.samoa.learners.classifiers.rules.common.RuleSplitNode;

/**
 * New features (of newly expanded rules) from Learners to Model Aggregators.
 * 
 * @author Anh Thu Vu
 *
 */
public class PredicateContentEvent implements ContentEvent {

	/**
	 * 
	 */
	private static final long serialVersionUID = 7909435830443732451L;
	
	private int ruleNumberID;
	private RuleSplitNode ruleSplitNode;
	private RulePassiveRegressionNode learningNode;
	
	/*
	 * Constructor
	 */
	public PredicateContentEvent() {
		this(0, null, null);
	}
	
	public PredicateContentEvent (int ruleID, RuleSplitNode ruleSplitNode, RulePassiveRegressionNode learningNode) {
		this.ruleNumberID = ruleID;
		this.ruleSplitNode = ruleSplitNode; // is this is null: this is for updating learningNode only
		this.learningNode = learningNode;
	}
	
	@Override
	public String getKey() {
		return Integer.toString(this.ruleNumberID);
	}

	@Override
	public void setKey(String key) {
		// do nothing
	}

	@Override
	public boolean isLastEvent() {
		return false; // N/A
	}
	
	public int getRuleNumberID() {
		return this.ruleNumberID;
	}
	
	public RuleSplitNode getRuleSplitNode() {
		return this.ruleSplitNode;
	}
	
	public RulePassiveRegressionNode getLearningNode() {
		return this.learningNode;
	}

}