weka.datagenerators.classifiers.regression

Class MexicanHat

java.lang.Object

weka.datagenerators.DataGenerator

weka.datagenerators.RegressionGenerator

weka.datagenerators.classifiers.regression.MexicanHat

All Implemented Interfaces:

java.io.Serializable, OptionHandler, Randomizable, RevisionHandler

Direct Known Subclasses:

Expression

public class MexicanHat
extends RegressionGenerator

A data generator for the simple 'Mexian Hat' function:
y = sin|x| / |x|
In addition to this simple function, the amplitude can be changed and gaussian noise can be added.

Valid options are:

 -h
  Prints this help.
 

 -o <file>
  The name of the output file, otherwise the generated data is
  printed to stdout.
 

 -r <name>
  The name of the relation.
 

 -d
  Whether to print debug informations.
 

 -S
  The seed for random function (default 1)
 

 -n <num>
  The number of examples to generate (default 100)
 

 -A <num>
  The amplitude multiplier (default 1.0).
 

 -R <num>..<num>
  The range x is randomly drawn from (default -10.0..10.0).
 

 -N <num>
  The noise rate (default 0.0).
 

 -V <num>
  The noise variance (default 1.0).
 

Version:

$Revision: 10203 $

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MexicanHat() initializes the generator

Method Summary

Modifier and Type	Method and Description
java.lang.String	amplitudeTipText() Returns the tip text for this property
Instances	defineDataFormat() Initializes the format for the dataset produced.
Instance	generateExample() Generates one example of the dataset.
Instances	generateExamples() Generates all examples of the dataset.
java.lang.String	generateFinished() Generates a comment string that documentats the data generator.
java.lang.String	generateStart() Generates a comment string that documentates the data generator.
double	getAmplitude() Gets the amplitude multiplier.
double	getMaxRange() Gets the upper boundary for the range of x
double	getMinRange() Gets the lower boundary for the range of x
double	getNoiseRate() Gets the gaussian noise rate.
double	getNoiseVariance() Gets the noise variance
java.lang.String[]	getOptions() Gets the current settings of the datagenerator BIRCHCluster.
java.lang.String	getRevision() Returns the revision string.
boolean	getSingleModeFlag() Return if single mode is set for the given data generator mode depends on option setting and or generator type.
java.lang.String	globalInfo() Returns a string describing this data generator.
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] args) Main method for testing this class.
java.lang.String	maxRangeTipText() Returns the tip text for this property
java.lang.String	minRangeTipText() Returns the tip text for this property
java.lang.String	noiseRateTipText() Returns the tip text for this property
java.lang.String	noiseVarianceTipText() Returns the tip text for this property
void	setAmplitude(double value) Sets the amplitude multiplier.
void	setMaxRange(double value) Sets the upper boundary for the range of x
void	setMinRange(double value) Sets the lower boundary for the range of x
void	setNoiseRate(double value) Sets the gaussian noise rate.
void	setNoiseVariance(double value) Sets the noise variance
void	setOptions(java.lang.String[] options) Parses a list of options for this object.

Methods inherited from class weka.datagenerators.RegressionGenerator

getNumExamples, numExamplesTipText, setNumExamples

Methods inherited from class weka.datagenerators.DataGenerator

debugTipText, defaultOutput, enumToVector, formatTipText, getDatasetFormat, getDebug, getEpilogue, getNumExamplesAct, getOutput, getPrologue, getRandom, getRelationName, getSeed, makeData, outputTipText, randomTipText, relationNameTipText, runDataGenerator, seedTipText, setDatasetFormat, setDebug, setOutput, setRandom, setRelationName, setSeed

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

MexicanHat

public MexicanHat()

initializes the generator

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this data generator.

Returns:

a description of the data generator suitable for displaying in the explorer/experimenter gui

listOptions

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

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class RegressionGenerator

Returns:

an enumeration of all the available options

setOptions

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

Parses a list of options for this object.

Valid options are:

 -h
  Prints this help.
 

 -o <file>
  The name of the output file, otherwise the generated data is
  printed to stdout.
 

 -r <name>
  The name of the relation.
 

 -d
  Whether to print debug informations.
 

 -S
  The seed for random function (default 1)
 

 -n <num>
  The number of examples to generate (default 100)
 

 -A <num>
  The amplitude multiplier (default 1.0).
 

 -R <num>..<num>
  The range x is randomly drawn from (default -10.0..10.0).
 

 -N <num>
  The noise rate (default 0.0).
 

 -V <num>
  The noise variance (default 1.0).
 

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class RegressionGenerator

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 BIRCHCluster.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class RegressionGenerator

Returns:

an array of strings suitable for passing to setOptions

See Also:

DataGenerator.removeBlacklist(String[])

getAmplitude

public double getAmplitude()

Gets the amplitude multiplier.

Returns:

the amplitude multiplier

setAmplitude

public void setAmplitude(double value)

Sets the amplitude multiplier.

Parameters:

value - the amplitude multiplier

amplitudeTipText

public java.lang.String amplitudeTipText()

Returns the tip text for this property

Returns:

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

setMinRange

public void setMinRange(double value)

Sets the lower boundary for the range of x

Parameters:

value - the lower boundary

getMinRange

public double getMinRange()

Gets the lower boundary for the range of x

Returns:

the lower boundary for the range of x

minRangeTipText

public java.lang.String minRangeTipText()

Returns the tip text for this property

Returns:

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

setMaxRange

public void setMaxRange(double value)

Sets the upper boundary for the range of x

Parameters:

value - the upper boundary

getMaxRange

public double getMaxRange()

Gets the upper boundary for the range of x

Returns:

the upper boundary for the range of x

maxRangeTipText

public java.lang.String maxRangeTipText()

Returns the tip text for this property

Returns:

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

getNoiseRate

public double getNoiseRate()

Gets the gaussian noise rate.

Returns:

the gaussian noise rate

setNoiseRate

public void setNoiseRate(double value)

Sets the gaussian noise rate.

Parameters:

value - the gaussian noise rate

noiseRateTipText

public java.lang.String noiseRateTipText()

Returns the tip text for this property

Returns:

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

getNoiseVariance

public double getNoiseVariance()

Gets the noise variance

Returns:

the noise variance

setNoiseVariance

public void setNoiseVariance(double value)

Sets the noise variance

Parameters:

value - the noise variance

noiseVarianceTipText

public java.lang.String noiseVarianceTipText()

Returns the tip text for this property

Returns:

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

getSingleModeFlag

public 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.

Specified by:

getSingleModeFlag in class DataGenerator

Returns:

single mode flag

Throws:

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

defineDataFormat

public Instances defineDataFormat()
                           throws java.lang.Exception

Initializes the format for the dataset produced. Must be called before the generateExample or generateExamples methods are used. Re-initializes the random number generator with the given seed.

Overrides:

defineDataFormat in class DataGenerator

Returns:

the format for the dataset

Throws:

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

See Also:

DataGenerator.getSeed()

generateExample

public Instance generateExample()
                         throws java.lang.Exception

Generates one example of the dataset.

Specified by:

generateExample in class DataGenerator

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 Instances generateExamples()
                           throws java.lang.Exception

Generates all examples of the dataset. Re-initializes the random number generator with the given seed, before generating instances.

Specified by:

generateExamples in class DataGenerator

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

See Also:

DataGenerator.getSeed()

generateStart

public java.lang.String generateStart()

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.

Specified by:

generateStart in class DataGenerator

Returns:

string contains info about the generated rules

generateFinished

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

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

Specified by:

generateFinished in class DataGenerator

Returns:

string contains info about the generated rules

Throws:

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

getRevision

public java.lang.String getRevision()

Returns the revision string.

Returns:

the revision

main

public static void main(java.lang.String[] args)

Main method for testing this class.

Parameters:

args - should contain arguments for the data producer: