/**
 * Copyright (C) 2001-2017 by RapidMiner and the contributors
 * 
 * Complete list of developers available at our web site:
 * 
 * http://rapidminer.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.postprocessing;

import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.io.AbstractReader;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.parameter.ParameterTypeString;

import java.util.List;


/**
 * This operator creates a user defined threshold for crisp classifying based on prediction
 * confidences.
 * 
 * @author Ingo Mierswa
 */
public class ThresholdCreator extends AbstractReader<Threshold> {

	/**
	 * The parameter name for "The confidence threshold to determine if the prediction should
	 * be positive."
	 */
	public static final String PARAMETER_THRESHOLD = "threshold";

	/**
	 * The parameter name for "The class which should be considered as the first one
	 * (confidence 0)."
	 */
	public static final String PARAMETER_FIRST_CLASS = "first_class";

	/**
	 * The parameter name for "The class which should be considered as the second one
	 * (confidence 1)."
	 */
	public static final String PARAMETER_SECOND_CLASS = "second_class";

	public ThresholdCreator(OperatorDescription description) {
		super(description, Threshold.class);
	}

	@Override
	public Threshold read() throws OperatorException {
		double threshold = getParameterAsDouble(PARAMETER_THRESHOLD);
		String negativeClass = getParameterAsString(PARAMETER_FIRST_CLASS);
		String positiveClass = getParameterAsString(PARAMETER_SECOND_CLASS);
		return new Threshold(threshold, negativeClass, positiveClass);
	}

	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> list = super.getParameterTypes();
		ParameterType type = new ParameterTypeDouble(PARAMETER_THRESHOLD,
				"The confidence threshold to determine if the prediction should be positive.", 0, 1.0d, 0.5d);
		type.setExpert(false);
		list.add(type);
		list.add(new ParameterTypeString(PARAMETER_FIRST_CLASS,
				"The class which should be considered as the first one (confidence 0).", false, false));
		list.add(new ParameterTypeString(PARAMETER_SECOND_CLASS,
				"The class which should be considered as the second one (confidence 1).", false, false));
		return list;
	}
}