/*
 *  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.operator.meta;

import java.util.List;

import com.rapidminer.operator.IOObject;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.SimpleOperatorChain;
import com.rapidminer.operator.ValueDouble;
import com.rapidminer.operator.performance.PerformanceVector;
import com.rapidminer.operator.ports.InputPort;
import com.rapidminer.operator.ports.OutputPort;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeBoolean;
import com.rapidminer.parameter.ParameterTypeInt;
import com.rapidminer.parameter.conditions.BooleanParameterCondition;

/**
 * This operator iterates several times through the inner operators and in each cycle evaluates a performance measure.
 * The IOObjects that are produced as output of the inner operators in the best cycle are then returned. The target of
 * this operator are methods that involve some non-deterministic elements such that the performance in each cycle may
 * vary. An example is k-means with random initialization.
 * 
 * @author Michael Wurst, Ingo Mierswa, Sebastian Land
 */
public class RandomOptimizationChain extends SimpleOperatorChain {

	/** The parameter name for "The number of iterations to perform" */
	public static final String PARAMETER_ITERATIONS = "iterations";

	/** The parameter name for "Timeout in minutes (-1 = no timeout)" */
	public static final String PARAMETER_TIMEOUT = "timeout";

	public static final String PARAMETER_ENABLE_TIMEOUT = "enable_timeout";

	private int iterationValue;
	private double bestPerformanceValue = 0.0;
	private double avgPerformanceValue = 0.0;

	private final InputPort innerPerformanceSink = getSubprocess(0).getInnerSinks().createPort("performance vector", PerformanceVector.class);
	private final OutputPort performanceOutput = getOutputPorts().createPort("performance");

	public RandomOptimizationChain(OperatorDescription description) {
		super(description, "Optimizing");

		getTransformer().addGenerationRule(performanceOutput, PerformanceVector.class);

		addValue(new ValueDouble("iteration", "The number of the current iteration.") {
			@Override
			public double getDoubleValue() {
				return iterationValue;
			}
		});

		addValue(new ValueDouble("performance", "The current best performance") {
			@Override
			public double getDoubleValue() {
				return bestPerformanceValue;
			}
		});

		addValue(new ValueDouble("avg_performance", "The average performance") {
			@Override
			public double getDoubleValue() {
				return avgPerformanceValue;
			}
		});

	}

	@Override
	public void doWork() throws OperatorException {
		int maxIterations = getParameterAsInt(PARAMETER_ITERATIONS);
		long stoptime;
		int timeout = getParameterAsInt(PARAMETER_TIMEOUT);
		if (!getParameterAsBoolean(PARAMETER_ENABLE_TIMEOUT))
			stoptime = Long.MAX_VALUE;
		else
			stoptime = System.currentTimeMillis() + 60L * 1000 * timeout;


		double perfSum = 0.0;
		List<IOObject> bestResult = null;
		PerformanceVector bestPerformance = null;
		for (iterationValue = 0; iterationValue < maxIterations; iterationValue++) {

			// executing sub process
			super.doWork();

			PerformanceVector performanceVector = innerPerformanceSink.getData();
			if (bestPerformance == null) {
				bestPerformance = performanceVector;
				bestResult = outputExtender.getData();
			} else {
				if (performanceVector.getMainCriterion().compareTo(bestPerformance.getMainCriterion()) == 1) {
					bestPerformance = performanceVector;
					bestResult = outputExtender.getData();
				}
			}
			this.bestPerformanceValue = bestPerformance.getMainCriterion().getFitness();

			perfSum = perfSum + performanceVector.getMainCriterion().getAverage();
			avgPerformanceValue = perfSum / iterationValue;

			if (java.lang.System.currentTimeMillis() > stoptime) {
				log("Runtime exceeded in iteration " + iterationValue + ".");
				break;
			}

			inApplyLoop();
		}

		outputExtender.deliver(bestResult);
		performanceOutput.deliver(bestPerformance);
	}

	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> types = super.getParameterTypes();

		types.add(new ParameterTypeInt(PARAMETER_ITERATIONS, "The number of iterations to perform", 1, Integer.MAX_VALUE, 10, false));
		types.add(new ParameterTypeBoolean(PARAMETER_ENABLE_TIMEOUT, "If used the processing will be aborted after the next completed execution of child operators.", false, true));
		ParameterType type = new ParameterTypeInt(PARAMETER_TIMEOUT, "Timeout in minutes", 1, Integer.MAX_VALUE, 1);
		type.registerDependencyCondition(new BooleanParameterCondition(this, PARAMETER_ENABLE_TIMEOUT, true, true));
		types.add(type);

		return types;
	}

}