SignificanceTestOperator.java example

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rapidminer-vega-master
/*
 *  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.
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 *  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.operator.validation.significance;

import java.util.List;

import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.performance.PerformanceVector;
import com.rapidminer.operator.ports.OutputPort;
import com.rapidminer.operator.ports.PortPairExtender;
import com.rapidminer.operator.ports.metadata.GenerateNewMDRule;
import com.rapidminer.operator.ports.metadata.MetaData;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.tools.math.SignificanceTestResult;


/**
 * Determines if the null hypothesis (all actual mean values are the same) holds
 * for the input performance vectors.
 * 
 * @author Ingo Mierswa
 *          ingomierswa Exp $
 */
public abstract class SignificanceTestOperator extends Operator {
	
	public static final String PARAMETER_ALPHA = "alpha";

	private PortPairExtender performanceExtender = new PortPairExtender("performance", getInputPorts(), getOutputPorts(), new MetaData(PerformanceVector.class));
	private OutputPort significanceOutput = getOutputPorts().createPort("significance");
	
	public SignificanceTestOperator(OperatorDescription description) {
		super(description);
		performanceExtender.start();
		getTransformer().addRule(new GenerateNewMDRule(significanceOutput, SignificanceTestResult.class));
		getTransformer().addRule(performanceExtender.makePassThroughRule());
	}

	/**
	 * Returns the result of the significance test for the given performance
	 * vector collection.
	 */
	public abstract SignificanceTestResult performSignificanceTest(PerformanceVector[] allVectors, double alpha) throws OperatorException;

	/**
	 * Returns the minimum number of performance vectors which can be compared
	 * by this significance test.
	 */
	public abstract int getMinSize();

	/**
	 * Returns the maximum number of performance vectors which can be compared
	 * by this significance test.
	 */
	public abstract int getMaxSize();

	/** Writes the attribute set to a file. */
	@Override
	public void doWork() throws OperatorException {
		List<PerformanceVector> allVectors = performanceExtender.getData();
		
		if (allVectors.size() < getMinSize()) {
			throw new UserError(this, 123, PerformanceVector.class, getMinSize() + "");
		}

		if (allVectors.size() > getMaxSize()) {
			throw new UserError(this, 124, PerformanceVector.class, getMaxSize() + "");
		}
		
		PerformanceVector[] allVectorsArray = new PerformanceVector[allVectors.size()];
		allVectors.toArray(allVectorsArray);
//		// create result array
//		IOObject[] resultArray = new IOObject[allVectors.size() + 1];
//		System.arraycopy(allVectorsArray, 0, resultArray, 0, allVectorsArray.length);
		
		SignificanceTestResult result = performSignificanceTest(allVectorsArray, getParameterAsDouble(PARAMETER_ALPHA));
		
		performanceExtender.passDataThrough();
		significanceOutput.deliver(result);
	}

	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> types = super.getParameterTypes();
		types.add(new ParameterTypeDouble(PARAMETER_ALPHA, "The probability threshold which determines if differences are considered as significant.", 0.0d, 1.0d, 0.05d));
		return types;
	}
}