/**
 * 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.visualization.dependencies;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.ports.InputPort;
import com.rapidminer.operator.ports.OutputPort;


/**
 * <p>
 * This operator calculates a dependency matrix between all attributes of the input example set.
 * This operator simply produces a dependency matrix like, for example, a correlation matrix. Such
 * matrixes up to now cannot be used by other operators but can be displayed to the user in the
 * result tab.
 * </p>
 *
 * <p>
 * Please note that this simple implementation performs a data scan for each attribute combination
 * and might therefore take some time for non-memory example tables.
 * </p>
 *
 * @author Ingo Mierswa
 */
public abstract class AbstractPairwiseMatrixOperator extends Operator {

	private InputPort exampleSetInput = getInputPorts().createPort("example set", ExampleSet.class);
	private OutputPort exampleSetOutput = getOutputPorts().createPort("example set");
	private OutputPort matrixOutput = getOutputPorts().createPort("matrix");

	public AbstractPairwiseMatrixOperator(OperatorDescription description) {
		super(description);

		getTransformer().addPassThroughRule(exampleSetInput, exampleSetOutput);
		getTransformer().addGenerationRule(matrixOutput, NumericalMatrix.class);
	}

	public abstract String getMatrixName();

	public abstract double getMatrixValue(ExampleSet exampleSet, Attribute firstAttribute, Attribute secondAttribute);

	/**
	 * This default implementation does nothing. Subclasses might calculate for example a
	 * discretization but should either deliver a new view or a fresh example set in order to not
	 * change the underlying data.
	 */
	protected ExampleSet performPreprocessing(ExampleSet exampleSet) throws OperatorException {
		return exampleSet;
	}

	@Override
	public void doWork() throws OperatorException {
		ExampleSet eSet = exampleSetInput.getData(ExampleSet.class);

		// discretize values (view!)
		ExampleSet exampleSet = performPreprocessing(eSet);

		// calculate mutual information
		NumericalMatrix matrix = new NumericalMatrix(getMatrixName(), exampleSet, true);
		Attribute[] regularAttributes = exampleSet.getAttributes().createRegularAttributeArray();
		int k = 0;
		for (Attribute firstAttribute : regularAttributes) {
			int l = 0;
			for (Attribute secondAttribute : regularAttributes) {
				matrix.setValue(k, l, getMatrixValue(exampleSet, firstAttribute, secondAttribute));
				checkForStop();
				l++;
			}
			k++;
		}

		exampleSetOutput.deliver(exampleSet);
		matrixOutput.deliver(matrix);
	}
}