weka.datagenerators

Class DataGenerator

java.lang.Object

weka.datagenerators.DataGenerator

All Implemented Interfaces:

java.io.Serializable, OptionHandler, Randomizable, RevisionHandler

Direct Known Subclasses:

ClassificationGenerator, ClusterGenerator, RegressionGenerator

public abstract class DataGenerator
extends java.lang.Object
implements OptionHandler, Randomizable, java.io.Serializable, RevisionHandler

Abstract superclass for data generators that generate data for classifiers and clusterers.

Version:

$Revision: 15437 $

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DataGenerator() initializes with default settings.

Method Summary

Modifier and Type	Method and Description
java.lang.String	debugTipText() Returns the tip text for this property
java.io.PrintWriter	defaultOutput() Gets writer, which is used for outputting to stdout.
Instances	defineDataFormat() Constructs the Instances object representing the format of the generated data.
java.util.Vector<Option>	enumToVector(java.util.Enumeration<Option> enu) Convenience method.
java.lang.String	formatTipText() Returns the tip text for this property
abstract Instance	generateExample() Generates one example of the dataset.
abstract Instances	generateExamples() Generates all examples of the dataset.
abstract java.lang.String	generateFinished() Generates a comment string that documentates the data generator.
abstract java.lang.String	generateStart() Generates a comment string that documentates the data generator.
Instances	getDatasetFormat() Gets the format of the dataset that is to be generated.
boolean	getDebug() Gets the debug flag.
java.lang.String	getEpilogue() Gets the epilogue string.
int	getNumExamplesAct() Gets the number of examples the dataset should have.
java.lang.String[]	getOptions() Gets the current settings of the datagenerator RDG1.
java.io.PrintWriter	getOutput() Gets the print writer.
java.lang.String	getPrologue() Gets the prologue string.
java.util.Random	getRandom() Gets the random generator.
java.lang.String	getRelationName() Gets the relation name the dataset should have.
int	getSeed() Gets the random number seed.
abstract boolean	getSingleModeFlag() Return if single mode is set for the given data generator mode depends on option setting and or generator type.
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	makeData(DataGenerator generator, java.lang.String[] options) Calls the data generator.
java.lang.String	outputTipText() Returns the tip text for this property
java.lang.String	randomTipText() Returns the tip text for this property
java.lang.String	relationNameTipText() Returns the tip text for this property
static void	runDataGenerator(DataGenerator datagenerator, java.lang.String[] options) runs the datagenerator instance with the given options.
java.lang.String	seedTipText() Returns the tip text for this property
void	setDatasetFormat(Instances newFormat) Sets the format of the dataset that is to be generated.
void	setDebug(boolean debug) Sets the debug flag.
void	setOptions(java.lang.String[] options) Parses a list of options for this object.
void	setOutput(java.io.PrintWriter newOutput) Sets the print writer.
void	setRandom(java.util.Random newRandom) Sets the random generator.
void	setRelationName(java.lang.String relationName) Sets the relation name the dataset should have.
void	setSeed(int newSeed) Sets the random number seed.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler

makeCopy

Methods inherited from interface weka.core.RevisionHandler

getRevision

Constructor Detail

DataGenerator

public DataGenerator()

initializes with default settings.
Note: default values are set via a default<name> method. These default methods are also used in the listOptions method and in the setOptions method. Why? Derived generators can override the return value of these default methods, to avoid exceptions.

Method Detail

listOptions

public java.util.Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Returns:

an enumeration of all the available options

enumToVector

public java.util.Vector<Option> enumToVector(java.util.Enumeration<Option> enu)

Convenience method. Turns the given enumeration of options into a vector.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a list of options for this object.

For list of valid options see class description.

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the datagenerator RDG1. Removing of blacklisted options has to be done in the derived class, that defines the blacklist-entry.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions

See Also:

removeBlacklist(String[])

defineDataFormat

public Instances defineDataFormat()
                           throws java.lang.Exception

Constructs the Instances object representing the format of the generated data. This default implementation simply returns the Instances object that holds the dataset format currently stored in m_DatasetFormat.

Returns:

the format for the dataset

Throws:

java.lang.Exception - if the generating of the format failed

See Also:

defaultRelationName()

generateExample

public abstract Instance generateExample()
                                  throws java.lang.Exception

Generates one example of the dataset.

Returns:

the generated example

Throws:

java.lang.Exception - if the format of the dataset is not yet defined

java.lang.Exception - if the generator only works with generateExamples which means in non single mode

generateExamples

public abstract Instances generateExamples()
                                    throws java.lang.Exception

Generates all examples of the dataset.

Returns:

the generated dataset

Throws:

java.lang.Exception - if the format of the dataset is not yet defined

java.lang.Exception - if the generator only works with generateExample, which means in single mode

generateStart

public abstract java.lang.String generateStart()
                                        throws java.lang.Exception

Generates a comment string that documentates the data generator. By default this string is added at the beginning of the produced output as ARFF file type, next after the options.

Returns:

string contains info about the generated rules

Throws:

java.lang.Exception - if the generating of the documentation fails

generateFinished

public abstract java.lang.String generateFinished()
                                           throws java.lang.Exception

Generates a comment string that documentates the data generator. By default this string is added at the end of the produced output as ARFF file type.

Returns:

string contains info about the generated rules

Throws:

java.lang.Exception - if the generating of the documentation fails

getSingleModeFlag

public abstract boolean getSingleModeFlag()
                                   throws java.lang.Exception

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

Returns:

single mode flag

Throws:

java.lang.Exception - if mode is not set yet

setDebug

public void setDebug(boolean debug)

Sets the debug flag.

Parameters:

debug - the new debug flag

getDebug

public boolean getDebug()

Gets the debug flag.

Returns:

the debug flag

debugTipText

public java.lang.String debugTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setRelationName

public void setRelationName(java.lang.String relationName)

Sets the relation name the dataset should have.

Parameters:

relationName - the new relation name

getRelationName

public java.lang.String getRelationName()

Gets the relation name the dataset should have.

Returns:

the relation name the dataset should have

relationNameTipText

public java.lang.String relationNameTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getNumExamplesAct

public int getNumExamplesAct()

Gets the number of examples the dataset should have.

Returns:

the number of examples the dataset should have

setOutput

public void setOutput(java.io.PrintWriter newOutput)

Sets the print writer.

Parameters:

newOutput - the new print writer

getOutput

public java.io.PrintWriter getOutput()

Gets the print writer.

Returns:

print writer object

defaultOutput

public java.io.PrintWriter defaultOutput()

Gets writer, which is used for outputting to stdout. A workaround for the problem of closing stdout when closing the associated Printwriter.

Returns:

writer object

outputTipText

public java.lang.String outputTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setDatasetFormat

public void setDatasetFormat(Instances newFormat)

Sets the format of the dataset that is to be generated.

Parameters:

newFormat - the new dataset format of the dataset

getDatasetFormat

public Instances getDatasetFormat()

Gets the format of the dataset that is to be generated.

Returns:

the dataset format of the dataset

formatTipText

public java.lang.String formatTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getSeed

public int getSeed()

Gets the random number seed.

Specified by:

getSeed in interface Randomizable

Returns:

the random number seed.

setSeed

public void setSeed(int newSeed)

Sets the random number seed.

Specified by:

setSeed in interface Randomizable

Parameters:

newSeed - the new random number seed.

seedTipText

public java.lang.String seedTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getRandom

public java.util.Random getRandom()

Gets the random generator.

Returns:

the random generator

setRandom

public void setRandom(java.util.Random newRandom)

Sets the random generator.

Parameters:

newRandom - is the random generator.

randomTipText

public java.lang.String randomTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getPrologue

public java.lang.String getPrologue()
                             throws java.lang.Exception

Gets the prologue string.

Returns:

prologue

Throws:

java.lang.Exception

getEpilogue

public java.lang.String getEpilogue()
                             throws java.lang.Exception

Gets the epilogue string.

Returns:

epilogue

Throws:

java.lang.Exception

makeData

public static void makeData(DataGenerator generator,
                            java.lang.String[] options)
                     throws java.lang.Exception

Calls the data generator.

Parameters:

generator - one of the data generators

options - options of the data generator

Throws:

java.lang.Exception - if there was an error in the option list

runDataGenerator

public static void runDataGenerator(DataGenerator datagenerator,
                                    java.lang.String[] options)

runs the datagenerator instance with the given options.

Parameters:

datagenerator - the datagenerator to run

options - the commandline options