Java DataRowReader.hasNext方法代码示例

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * After creation of a new MemoryExampleTable with given size all values are Double.NaN. Use
 * this method to fill the table with random values in the range specified by minimum and
 * maximum values of the attributes. Please note that the attributes in the example table must
 * already have proper minimum and maximum values. This works only for numerical attribute.
 * Nominal attribute values will be set to 0.
 */
private static void fillTableWithRandomValues(ExampleTable exampleTable, ExampleSet baseSet, RandomGenerator random) {
	DataRowReader reader = exampleTable.getDataRowReader();
	Attribute[] attributes = exampleTable.getAttributes();
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();
		for (int i = 0; i < attributes.length; i++) {
			if (attributes[i] != null) {
				if (!attributes[i].isNominal()) {
					double min = baseSet.getStatistics(attributes[i], Statistics.MINIMUM);
					double max = baseSet.getStatistics(attributes[i], Statistics.MAXIMUM);
					if (max > min) {
						dataRow.set(attributes[i], random.nextDoubleInRange(min, max));
					} else {
						dataRow.set(attributes[i], random.nextDouble() * 2 - 1);
					}
				} else {
					dataRow.set(attributes[i], 0);
				}
			}
		}
	}
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * After creation of a new ExampleTable with given size all values are 0. Use this method to
 * fill the table with random values in the range specified by minimum and maximum values of the
 * attributes. Please note that the attributes in the example table must already have proper
 * minimum and maximum values. This works only for numerical attribute. Nominal attribute values
 * will be set to 0.
 */
private static void fillTableWithRandomValues(ExampleTable exampleTable, ExampleSet baseSet, RandomGenerator random) {
	DataRowReader reader = exampleTable.getDataRowReader();
	Attribute[] attributes = exampleTable.getAttributes();
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();
		for (int i = 0; i < attributes.length; i++) {
			if (attributes[i] != null) {
				if (!attributes[i].isNominal()) {
					double min = baseSet.getStatistics(attributes[i], Statistics.MINIMUM);
					double max = baseSet.getStatistics(attributes[i], Statistics.MAXIMUM);
					if (max > min) {
						dataRow.set(attributes[i], random.nextDoubleInRange(min, max));
					} else {
						dataRow.set(attributes[i], random.nextDouble() * 2 - 1);
					}
				} else {
					dataRow.set(attributes[i], 0);
				}
			}
		}
	}
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * Creates a {@link Callable} which copies the values from the source to the target
 * {@link ExampleTable} by using the {@link DataRowReader}, only the values of the defined
 * {@link Attribute}s will be copied.
 */
private Callable<Void> prepareCopyValueTask(ExampleTable source, ExampleTable target, Attribute[] attributes) {
	return new Callable<Void>() {

		@Override
		public Void call() {
			try {
				startSignal.await();
				DataRowReader sourceReader = source.getDataRowReader();
				DataRowReader targetReader = target.getDataRowReader();
				DataRow sourceRow = null;
				DataRow targetRow = null;
				while (sourceReader.hasNext() && targetReader.hasNext()) {
					sourceRow = sourceReader.next();
					targetRow = targetReader.next();
					for (Attribute a : attributes) {
						targetRow.set(a, sourceRow.get(a));
					}
				}
			} catch (InterruptedException e) {
				Assert.fail(Thread.currentThread().getName() + " " + e.getMessage());
			}
			return null;
		}
	};
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * After creation of a new MemoryExampleTable with given size all values are
 * Double.NaN. Use this method to fill the table with random values in the
 * range specified by minimum and maximum values of the attributes. Please
 * note that the attributes in the example table must already have proper
 * minimum and maximum values. This works only for numerical attribute.
 * Nominal attribute values will be set to 0.
 */
private static void fillTableWithRandomValues(ExampleTable exampleTable, ExampleSet baseSet, RandomGenerator random) {
	DataRowReader reader = exampleTable.getDataRowReader();
	Attribute[] attributes = exampleTable.getAttributes();
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();
		for (int i = 0; i < attributes.length; i++) {
			if (attributes[i] != null) {
				if (!attributes[i].isNominal()) {
					double min = baseSet.getStatistics(attributes[i], Statistics.MINIMUM);
					double max = baseSet.getStatistics(attributes[i], Statistics.MAXIMUM);
					if (max > min)
						dataRow.set(attributes[i], random.nextDoubleInRange(min, max));
					else
						dataRow.set(attributes[i], random.nextDouble()*2 - 1);
				} else {
					dataRow.set(attributes[i], 0);
				}
			}
		}
	}
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * Fills the table with the length of the given complex numbers in the column of the attribute.
 */
private void fillTable(ExampleTable table, Attribute attribute, Peak[] values) throws OperatorException {
	DataRowReader reader = table.getDataRowReader();
	int k = 0;
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();
		dataRow.set(attribute, values[k++].getMagnitude());
		checkForStop();
	}
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * Writes the values provided by the {@link #columnFillers} into the table.
 */
private void writeColumnValues() {
	DataRowReader tableReader = table.getDataRowReader();
	int k = 0;
	while (tableReader.hasNext()) {
		DataRow dataRow = tableReader.next();
		for (Entry<Attribute, IntToDoubleFunction> entry : columnFillers.entrySet()) {
			dataRow.set(entry.getKey(), entry.getValue().applyAsDouble(k));
		}
		k++;
	}
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
@Override
public final void doWork() throws OperatorException {
	ExampleSet inputExampleSet = exampleSetInput.getData(ExampleSet.class);
	ExampleSet applySet = null;
	// check for needed copy of original exampleset
	if (writesIntoExistingData()) {
		int type = DataRowFactory.TYPE_DOUBLE_ARRAY;
		if (inputExampleSet.getExampleTable() instanceof MemoryExampleTable) {
			DataRowReader dataRowReader = inputExampleSet.getExampleTable().getDataRowReader();
			if (dataRowReader.hasNext()) {
				type = dataRowReader.next().getType();
			}
		}
		// check if type is supported to be copied
		if (type >= 0) {
			applySet = MaterializeDataInMemory.materializeExampleSet(inputExampleSet, type);
		}
	}

	if (applySet == null) {
		applySet = (ExampleSet) inputExampleSet.clone();
	}

	// we apply on the materialized data, because writing can't take place in views anyway.
	ExampleSet result = apply(applySet);
	originalOutput.deliver(inputExampleSet);
	exampleSetOutput.deliver(result);
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
@Override
public final void doWork() throws OperatorException {
	ExampleSet inputExampleSet = exampleSetInput.getData(ExampleSet.class);
	ExampleSet applySet = null;
	// check for needed copy of original exampleset
	if (originalOutput.isConnected() && writesIntoExistingData()) {
		int type = DataRowFactory.TYPE_DOUBLE_ARRAY;
		if (inputExampleSet.getExampleTable() instanceof MemoryExampleTable) {
			DataRowReader dataRowReader = inputExampleSet.getExampleTable().getDataRowReader();
			if (dataRowReader.hasNext()) {
				type = dataRowReader.next().getType();
			}
		}
		// check if type is supported to be copied
		if (type >= 0) {
			applySet = MaterializeDataInMemory.materializeExampleSet(inputExampleSet, type);
		}
	}
	
	if (applySet == null)
		applySet = (ExampleSet) inputExampleSet.clone();

	// we apply on the materialized data, because writing can't take place in views anyway. 
	ExampleSet result = apply(applySet);
	originalOutput.deliver(inputExampleSet);
	exampleSetOutput.deliver(result);
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
@Override
public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
	Tools.onlyNonMissingValues(exampleSet, "Fourier Transform");

	// create new example table
	int numberOfNewExamples = FastFourierTransform.getGreatestPowerOf2LessThan(exampleSet.size()) / 2;
	ExampleTable exampleTable = new MemoryExampleTable(new LinkedList<Attribute>(), new DataRowFactory(DataRowFactory.TYPE_DOUBLE_ARRAY, '.'), numberOfNewExamples);

	// create frequency attribute (for frequency)
	Attribute frequencyAttribute = AttributeFactory.createAttribute("frequency", Ontology.REAL);
	exampleTable.addAttribute(frequencyAttribute);
	DataRowReader drr = exampleTable.getDataRowReader();
	int k = 0;
	while (drr.hasNext()) {
		DataRow dataRow = drr.next();
		dataRow.set(frequencyAttribute, FastFourierTransform.convertFrequency(k++, numberOfNewExamples, exampleSet.size()));
	}

	// create FFT values
	Attribute label = exampleSet.getAttributes().getLabel();

	// add FFT values
	FastFourierTransform fft = new FastFourierTransform(WindowFunction.BLACKMAN_HARRIS);
	SpectrumFilter filter = new SpectrumFilter(SpectrumFilter.NONE);
	for (Attribute current : exampleSet.getAttributes()) {
		if (current.isNumerical()) {
			Complex[] result = fft.getFourierTransform(exampleSet, label, current);
			Peak[] spectrum = filter.filter(result, exampleSet.size());
			// create new attribute and fill table with values
			Attribute newAttribute = AttributeFactory.createAttribute("fft(" + current.getName() + ")", Ontology.REAL);
			exampleTable.addAttribute(newAttribute);
			fillTable(exampleTable, newAttribute, spectrum);
		}
	}

	ExampleSet resultSet = new SimpleExampleSet(exampleTable);

	return resultSet;
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * Generates all new attributes and updates the ExampleTable. Returns a list of Attributes for
 * the newly generated attributes.
 * 
 * @param exampleTable
 *            the source example table
 * @param generatorList
 *            List of FeatureGenerators
 * @return A list of Attributes
 */
public static List<Attribute> generateAll(ExampleTable exampleTable, Collection<FeatureGenerator> generatorList)
		throws GenerationException {
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.starting_feature_generation",
			generatorList.size());

	Iterator<FeatureGenerator> gi = generatorList.iterator();
	while (gi.hasNext()) {
		gi.next().setExampleTable(exampleTable);
	}

	// for performance reasons convert the list to an array
	FeatureGenerator[] generators = new FeatureGenerator[generatorList.size()];
	generatorList.toArray(generators);

	List<Attribute> newAttributeList = newAttributes(generators, exampleTable);
	// add the attributes to the example table and ensure length of the
	// DataRows
	exampleTable.addAttributes(newAttributeList);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.generator_list", generatorList);
	LogService.getRoot().log(Level.FINE,
			"com.rapidminer.generator.FeatureGenerator.input_has_feature_count_and_example_count",
			new Object[] { exampleTable.getAttributeCount(), exampleTable.size() });

	// generate the attribute values:
	DataRowReader reader = exampleTable.getDataRowReader();
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();

		for (int j = 0; j < generators.length; j++) {
			generators[j].generate(dataRow);
		}
	}

	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.finished_feature_generation");
	LogService.getRoot().log(Level.FINE,
			"com.rapidminer.generator.FeatureGenerator.generated_set_has_feature_count_and_example_count",
			new Object[] { exampleTable.getAttributeCount(), exampleTable.size() });

	return newAttributeList;
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
@Override
public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
	Tools.onlyNonMissingValues(exampleSet, getOperatorClassName(), this);

	// create new example table
	int numberOfNewExamples = FastFourierTransform.getGreatestPowerOf2LessThan(exampleSet.size()) / 2;
	ExampleTable exampleTable = new MemoryExampleTable(new LinkedList<Attribute>(), new DataRowFactory(
			DataRowFactory.TYPE_DOUBLE_ARRAY, '.'), numberOfNewExamples);

	// create frequency attribute (for frequency)
	Attribute frequencyAttribute = AttributeFactory.createAttribute("frequency", Ontology.REAL);
	exampleTable.addAttribute(frequencyAttribute);
	DataRowReader drr = exampleTable.getDataRowReader();
	int k = 0;
	while (drr.hasNext()) {
		DataRow dataRow = drr.next();
		dataRow.set(frequencyAttribute,
				FastFourierTransform.convertFrequency(k++, numberOfNewExamples, exampleSet.size()));
	}

	// create FFT values
	Attribute label = exampleSet.getAttributes().getLabel();

	// add FFT values
	FastFourierTransform fft = new FastFourierTransform(WindowFunction.BLACKMAN_HARRIS);
	SpectrumFilter filter = new SpectrumFilter(SpectrumFilter.NONE);
	for (Attribute current : exampleSet.getAttributes()) {
		if (current.isNumerical()) {
			Complex[] result = fft.getFourierTransform(exampleSet, label, current);
			Peak[] spectrum = filter.filter(result, exampleSet.size());
			// create new attribute and fill table with values
			Attribute newAttribute = AttributeFactory.createAttribute("fft(" + current.getName() + ")", Ontology.REAL);
			exampleTable.addAttribute(newAttribute);
			fillTable(exampleTable, newAttribute, spectrum);
		}
	}

	ExampleSet resultSet = new SimpleExampleSet(exampleTable);

	return resultSet;
}
 

import com.rapidminer.example.table.DataRowReader; //导入方法依赖的package包/类
/**
 * Generates all new attributes and updates the ExampleTable. Returns a list
 * of Attributes for the newly generated attributes.
 * 
 * @param exampleTable
 *            the source example table
 * @param generatorList
 *            List of FeatureGenerators
 * @return A list of Attributes
 */
public static List<Attribute> generateAll(ExampleTable exampleTable, Collection<FeatureGenerator> generatorList) throws GenerationException {
	//LogService.getGlobal().log("Starting feature generation with " + generatorList.size() + " generators.", LogService.STATUS);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.starting_feature_generation",generatorList.size());
	
	Iterator<FeatureGenerator> gi = generatorList.iterator();
	while (gi.hasNext())
		gi.next().setExampleTable(exampleTable);

	// for performance reasons convert the list to an array
	FeatureGenerator[] generators = new FeatureGenerator[generatorList.size()];
	generatorList.toArray(generators);

	List<Attribute> newAttributeList = newAttributes(generators, exampleTable);
	// add the attributes to the example table and ensure length of the
	// DataRows
	exampleTable.addAttributes(newAttributeList);
	//LogService.getGlobal().log("Generator list: " + generatorList, LogService.STATUS);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.generator_list",generatorList);
	//LogService.getGlobal().log("Input set has " + exampleTable.getAttributeCount() + " features, " + exampleTable.size() + " examples.", LogService.STATUS);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.input_has_feature_count_and_example_count",
			new Object[] {exampleTable.getAttributeCount(), exampleTable.size()});

	// generate the attribute values:
	DataRowReader reader = exampleTable.getDataRowReader();
	while (reader.hasNext()) {
		DataRow dataRow = reader.next();

		for (int j = 0; j < generators.length; j++) {
			generators[j].generate(dataRow);
		}
	}

	//LogService.getGlobal().log("Finished feature generation.", LogService.STATUS);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.finished_feature_generation");
	//LogService.getGlobal().log("Generated set has " + exampleTable.getAttributeCount() + " features, " + exampleTable.size() + " examples.", LogService.STATUS);
	LogService.getRoot().log(Level.FINE, "com.rapidminer.generator.FeatureGenerator.generated_set_has_feature_count_and_example_count", 
			new Object[] {exampleTable.getAttributeCount(), exampleTable.size()});
	
	return newAttributeList;
}