NominalExampleSetGenerator.java

/**
 * 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.generator;

import java.util.LinkedHashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Set;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.table.AttributeFactory;
import com.rapidminer.example.table.NominalMapping;
import com.rapidminer.example.table.PolynominalMapping;
import com.rapidminer.example.utils.ExampleSetBuilder;
import com.rapidminer.example.utils.ExampleSets;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.io.AbstractExampleSource;
import com.rapidminer.operator.ports.metadata.AttributeMetaData;
import com.rapidminer.operator.ports.metadata.ExampleSetMetaData;
import com.rapidminer.operator.ports.metadata.MetaData;
import com.rapidminer.operator.ports.metadata.SetRelation;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeInt;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.RandomGenerator;


/**
 * Generates a random example set for testing purposes. All attributes have only (random) nominal
 * values and a classification label.
 *
 * @author Ingo Mierswa
 */
public class NominalExampleSetGenerator extends AbstractExampleSource {

	/** The parameter name for "The number of generated examples." */
	public static final String PARAMETER_NUMBER_EXAMPLES = "number_examples";

	/** The parameter name for "The number of attributes." */
	public static final String PARAMETER_NUMBER_OF_ATTRIBUTES = "number_of_attributes";

	/** The parameter name for "The number of nominal values for each attribute." */
	public static final String PARAMETER_NUMBER_OF_VALUES = "number_of_values";

	public NominalExampleSetGenerator(OperatorDescription description) {
		super(description);
	}

	@Override
	public ExampleSet createExampleSet() throws OperatorException {
		// init
		int numberOfExamples = getParameterAsInt(PARAMETER_NUMBER_EXAMPLES);
		int numberOfAttributes = getParameterAsInt(PARAMETER_NUMBER_OF_ATTRIBUTES);
		int numberOfValues = getParameterAsInt(PARAMETER_NUMBER_OF_VALUES);
		if (numberOfValues < 2) {
			logWarning("Less than 2 different values used, change to '2'.");
			numberOfValues = 2;
		}
		getProgress().setTotal(numberOfAttributes + numberOfExamples);

		// create mapping once, clone for each attribute
		NominalMapping mapping = new PolynominalMapping();
		int type = Ontology.NOMINAL;
		for (int v = 0; v < numberOfValues; v++) {
			mapping.mapString("value" + v);
		}

		// create table
		List<Attribute> attributes = new LinkedList<Attribute>();
		for (int m = 0; m < numberOfAttributes; m++) {
			Attribute current = AttributeFactory.createAttribute("att" + (m + 1), type);
			current.setMapping((NominalMapping) mapping.clone());
			attributes.add(current);

			getProgress().step();
		}
		Attribute label = AttributeFactory.createAttribute("label", Ontology.NOMINAL);
		label.getMapping().mapString("negative");
		label.getMapping().mapString("positive");
		attributes.add(label);

		ExampleSetBuilder builder = ExampleSets.from(attributes).withExpectedSize(numberOfExamples);

		// create data
		RandomGenerator random = RandomGenerator.getRandomGenerator(this);
		for (int n = 0; n < numberOfExamples; n++) {
			double[] features = new double[numberOfAttributes];
			for (int a = 0; a < features.length; a++) {
				features[a] = random.nextIntInRange(0, numberOfValues);
			}
			double[] example = features;
			if (label != null) {
				example = new double[numberOfAttributes + 1];
				System.arraycopy(features, 0, example, 0, features.length);
				if (features.length >= 2) {
					example[example.length - 1] = features[0] == 0 || features[1] == 0
							? label.getMapping().mapString("positive") : label.getMapping().mapString("negative");
				} else if (features.length == 1) {
					example[example.length - 1] = features[0] == 0 ? label.getMapping().mapString("positive")
							: label.getMapping().mapString("negative");
				} else {
					example[example.length - 1] = label.getMapping().mapString("positive");
				}
			}
			builder.addRow(example);

			getProgress().step();
		}

		getProgress().complete();

		// create example set and return it
		return builder.withRole(label, Attributes.LABEL_NAME).build();
	}

	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> types = super.getParameterTypes();
		ParameterType type = new ParameterTypeInt(PARAMETER_NUMBER_EXAMPLES, "The number of generated examples.", 1,
				Integer.MAX_VALUE, 100);
		type.setExpert(false);
		types.add(type);
		type = new ParameterTypeInt(PARAMETER_NUMBER_OF_ATTRIBUTES, "The number of attributes.", 0, Integer.MAX_VALUE, 5);
		type.setExpert(false);
		types.add(type);
		type = new ParameterTypeInt(PARAMETER_NUMBER_OF_VALUES, "The number of nominal values for each attribute.", 2,
				Integer.MAX_VALUE, 5);
		type.setExpert(false);
		types.add(type);

		types.addAll(RandomGenerator.getRandomGeneratorParameters(this));

		return types;
	}

	@Override
	public MetaData getGeneratedMetaData() throws OperatorException {
		int numberOfExamples = getParameterAsInt(PARAMETER_NUMBER_EXAMPLES);
		int numberOfAttributes = getParameterAsInt(PARAMETER_NUMBER_OF_ATTRIBUTES);
		int maxNumberOfAttributes = ExampleSetMetaData.getMaximumNumberOfAttributes();
		int numberOfValues = getParameterAsInt(PARAMETER_NUMBER_OF_VALUES);
		ExampleSetMetaData emd = new ExampleSetMetaData();
		if (numberOfAttributes > maxNumberOfAttributes) {
			numberOfAttributes = maxNumberOfAttributes;
			emd.mergeSetRelation(SetRelation.SUPERSET);
		}
		emd.addAttribute(new AttributeMetaData("label", Attributes.LABEL_NAME, "positive", "negative"));

		int type = Ontology.NOMINAL;

		// create nominal values, in truncated form
		Set<String> valueSet = new LinkedHashSet<>();
		valueSet.add("value1");
		valueSet.add("value2");
		if (numberOfValues > 3) {
			valueSet.add("...");
		}
		valueSet.add("value" + numberOfValues);

		// attributes
		for (int i = 0; i < numberOfAttributes; i++) {
			AttributeMetaData amd = new AttributeMetaData("att" + (i + 1), null);
			amd.setType(type);
			amd.setValueSet(valueSet, SetRelation.EQUAL);
			emd.addAttribute(amd);
		}

		emd.setNumberOfExamples(numberOfExamples);
		return emd;
	}
}