MexicanHat (interruptible-weka 0.1.4 API)

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).

See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected double`	`m_Amplitude` the amplitude of y
`protected double`	`m_MaxRange` the upper boundary of the range, x is drawn from
`protected double`	`m_MinRange` the lower boundary of the range, x is drawn from
`protected java.util.Random`	`m_NoiseRandom` the random number generator for the noise
`protected double`	`m_NoiseRate` the rate of the gaussian noise
`protected double`	`m_NoiseVariance` the variance of the gaussian noise

Fields inherited from class weka.datagenerators.RegressionGenerator
m_NumExamples

Fields inherited from class weka.datagenerators.DataGenerator
m_CreatingRelationName, m_DatasetFormat, m_Debug, m_DefaultOutput, m_NumExamplesAct, m_OptionBlacklist, m_Output, m_Random, m_RelationName, m_Seed

Constructor Summary

Constructors
Constructor and Description

MexicanHat()
initializes the generator

Constructors
Constructor and Description
`MexicanHat()` initializes the generator

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`amplitudeTipText()` Returns the tip text for this property
`protected double`	`defaultAmplitude()` returns the default amplitude
`protected double`	`defaultMaxRange()` returns the default max range
`protected double`	`defaultMinRange()` returns the default min range
`protected double`	`defaultNoiseRate()` returns the default gaussian noise rate
`protected double`	`defaultNoiseVariance()` returns the default variance of the noise rate
`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.
`protected java.lang.String`	`getRange()` Gets the upper and lower boundary for the range of x
`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
`protected java.lang.String`	`rangeTipText()` 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.
`protected void`	`setRange(java.lang.String fromTo)` Sets the upper and lower boundary for the range of x

Methods inherited from class weka.datagenerators.RegressionGenerator
defaultNumExamples, getNumExamples, numExamplesTipText, setNumExamples

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - m_Amplitude
```
protected double m_Amplitude
```
    the amplitude of y
  - m_MinRange
```
protected double m_MinRange
```
    the lower boundary of the range, x is drawn from
  - m_MaxRange
```
protected double m_MaxRange
```
    the upper boundary of the range, x is drawn from
  - m_NoiseRate
```
protected double m_NoiseRate
```
    the rate of the gaussian noise
  - m_NoiseVariance
```
protected double m_NoiseVariance
```
    the variance of the gaussian noise
  - m_NoiseRandom
```
protected java.util.Random m_NoiseRandom
```
    the random number generator for the noise
- 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[])
  - defaultAmplitude
```
protected double defaultAmplitude()
```
    returns the default amplitude
    
    Returns:
    
    the default amplitude
  - 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
  - setRange
```
protected void setRange(java.lang.String fromTo)
```
    Sets the upper and lower boundary for the range of x
    
    Parameters:
    
    fromTo - the string containing the upper and lower boundary for the range of x, separated by ..
  - getRange
```
protected java.lang.String getRange()
```
    Gets the upper and lower boundary for the range of x
    
    Returns:
    
    the string containing the upper and lower boundary for the range of x, separated by ..
  - rangeTipText
```
protected java.lang.String rangeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - defaultMinRange
```
protected double defaultMinRange()
```
    returns the default min range
    
    Returns:
    
    the default min range
  - 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
  - defaultMaxRange
```
protected double defaultMaxRange()
```
    returns the default max range
    
    Returns:
    
    the default max range
  - 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
  - defaultNoiseRate
```
protected double defaultNoiseRate()
```
    returns the default gaussian noise rate
    
    Returns:
    
    the default gaussian noise rate
  - 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
  - defaultNoiseVariance
```
protected double defaultNoiseVariance()
```
    returns the default variance of the noise rate
    
    Returns:
    
    the default variance of the noise rate
  - 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:

Class MexicanHat

Field Summary

Fields inherited from class weka.datagenerators.RegressionGenerator

Fields inherited from class weka.datagenerators.DataGenerator

Constructor Summary

Method Summary

Methods inherited from class weka.datagenerators.RegressionGenerator

Methods inherited from class weka.datagenerators.DataGenerator

Methods inherited from class java.lang.Object

Field Detail

m_Amplitude

m_MinRange

m_MaxRange

m_NoiseRate

m_NoiseVariance

m_NoiseRandom

Constructor Detail

MexicanHat

Method Detail

globalInfo

listOptions

setOptions

getOptions

defaultAmplitude

getAmplitude

setAmplitude

amplitudeTipText

setRange

getRange

rangeTipText

defaultMinRange

setMinRange

getMinRange

minRangeTipText

defaultMaxRange

setMaxRange

getMaxRange

maxRangeTipText

defaultNoiseRate

getNoiseRate

setNoiseRate

noiseRateTipText

defaultNoiseVariance

getNoiseVariance

setNoiseVariance

noiseVarianceTipText

getSingleModeFlag

defineDataFormat

generateExample

generateExamples

generateStart

generateFinished

getRevision

main