StratifiedSamplingOperator.java example

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rapidminer-vega-master
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package com.rapidminer.operator.preprocessing.sampling;

import java.util.Collections;
import java.util.List;

import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.set.SplittedExampleSet;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.ProcessSetupError.Severity;
import com.rapidminer.operator.annotation.ResourceConsumptionEstimator;
import com.rapidminer.operator.ports.metadata.ExampleSetMetaData;
import com.rapidminer.operator.ports.metadata.MDInteger;
import com.rapidminer.operator.ports.metadata.MetaDataInfo;
import com.rapidminer.operator.ports.metadata.SimpleMetaDataError;
import com.rapidminer.operator.ports.quickfix.ParameterSettingQuickFix;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeCategory;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.parameter.ParameterTypeInt;
import com.rapidminer.parameter.UndefinedParameterError;
import com.rapidminer.parameter.conditions.EqualTypeCondition;
import com.rapidminer.tools.OperatorResourceConsumptionHandler;
import com.rapidminer.tools.RandomGenerator;


/**
 * Stratified sampling.
 * 
 * @author Ingo Mierswa, Sebastian Land, Tobias Malbrecht
 */
public class StratifiedSamplingOperator extends AbstractSamplingOperator {

	public static final String PARAMETER_SAMPLE = "sample";
	
	public static final String[] SAMPLE_MODES = { "absolute" , "relative" };
	
	public static final int SAMPLE_ABSOLUTE = 0;
	
	public static final int SAMPLE_RELATIVE = 1;
	
	/** The parameter name for "The fraction of examples which should be sampled" */
	public static final String PARAMETER_SAMPLE_SIZE = "sample_size";

	/** The parameter name for "The fraction of examples which should be sampled" */
	public static final String PARAMETER_SAMPLE_RATIO = "sample_ratio";
	
	public StratifiedSamplingOperator(OperatorDescription description) {
		super(description);
	}

	/**
	 * This method should return the ratio used for stratifiedSampling
	 */
	public double getRatio(ExampleSet exampleSet) throws OperatorException {
		switch (getParameterAsInt(PARAMETER_SAMPLE)) {
		case SAMPLE_ABSOLUTE:
			double targetSize = getParameterAsInt(PARAMETER_SAMPLE_SIZE);
			if (targetSize > exampleSet.size()) {
				return 1d;
			} else {
				return targetSize / (exampleSet.size());
			}
		case SAMPLE_RELATIVE:
			return getParameterAsDouble(PARAMETER_SAMPLE_RATIO);
		default:
			return 1;
		}
	}
	
	@Override
	protected MDInteger getSampledSize(ExampleSetMetaData emd) throws UndefinedParameterError {
		switch (getParameterAsInt(PARAMETER_SAMPLE)) {
		case SAMPLE_ABSOLUTE:
			int absoluteNumber = getParameterAsInt(PARAMETER_SAMPLE_SIZE);

			if (emd.getNumberOfExamples().isAtLeast(absoluteNumber) == MetaDataInfo.NO)
				getExampleSetInputPort().addError(
						new SimpleMetaDataError(Severity.ERROR, getExampleSetInputPort(), 
								Collections.singletonList(new ParameterSettingQuickFix(this, PARAMETER_SAMPLE_SIZE, emd.getNumberOfExamples().getValue().toString())),
								"exampleset.need_more_examples", absoluteNumber + ""));
			return new MDInteger(absoluteNumber);
		case SAMPLE_RELATIVE:
			MDInteger number = emd.getNumberOfExamples();
			number.multiply(getParameterAsDouble(PARAMETER_SAMPLE_RATIO));
			return number;
		default:
			return new MDInteger();
		}
	}

	@Override
	public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
		// perform stratified sampling
		SplittedExampleSet splittedExampleSet = new SplittedExampleSet(exampleSet, getRatio(exampleSet), SplittedExampleSet.STRATIFIED_SAMPLING, getParameterAsBoolean(RandomGenerator.PARAMETER_USE_LOCAL_RANDOM_SEED), getParameterAsInt(RandomGenerator.PARAMETER_LOCAL_RANDOM_SEED));
		splittedExampleSet.selectSingleSubset(0);

		return splittedExampleSet;
	}

	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> types = super.getParameterTypes();
		ParameterType type = new ParameterTypeCategory(PARAMETER_SAMPLE, "Determines how the amount of data is specified.", SAMPLE_MODES, SAMPLE_ABSOLUTE);  
		type.setExpert(false);
		types.add(type);
		type = new ParameterTypeInt(PARAMETER_SAMPLE_SIZE, "The number of examples which should be sampled", 1, Integer.MAX_VALUE, 100);
		type.registerDependencyCondition(new EqualTypeCondition(this, PARAMETER_SAMPLE, SAMPLE_MODES, true, SAMPLE_ABSOLUTE));
		type.setExpert(false);
		types.add(type);
		type = new ParameterTypeDouble(PARAMETER_SAMPLE_RATIO, "The fraction of examples which should be sampled", 0.0d, 1.0d, 0.1d);
		type.registerDependencyCondition(new EqualTypeCondition(this, PARAMETER_SAMPLE, SAMPLE_MODES, true, SAMPLE_RELATIVE));
		type.setExpert(false);
		types.add(type);
		types.addAll(RandomGenerator.getRandomGeneratorParameters(this));
		return types;
	}
	
	@Override
	public ResourceConsumptionEstimator getResourceConsumptionEstimator() {
		return OperatorResourceConsumptionHandler.getResourceConsumptionEstimator(getInputPort(), StratifiedSamplingOperator.class, null);
	}
}