/*
* 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.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();
// discretize values (view!)
ExampleSet exampleSet = performPreprocessing(eSet);
// calculate mutual information
NumericalMatrix matrix = new NumericalMatrix(getMatrixName(), exampleSet, true);
int k = 0;
for (Attribute firstAttribute : exampleSet.getAttributes()) {
int l = 0;
for (Attribute secondAttribute : exampleSet.getAttributes()) {
matrix.setValue(k, l, getMatrixValue(exampleSet, firstAttribute, secondAttribute));
checkForStop();
l++;
}
k++;
}
exampleSetOutput.deliver(exampleSet);
matrixOutput.deliver(matrix);
}
}