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: 1.4 $
Author:: FracPete (fracpete at waikato dot ac dot nz)
See Also:: Serialized Form

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
`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`	`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, formatTipText, getDatasetFormat, getDebug, getNumExamplesAct, getOutput, getRandom, getRelationName, getSeed, makeData, outputTipText, randomTipText, relationNameTipText, seedTipText, setDatasetFormat, setDebug, setOutput, setRandom, setRelationName, setSeed

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

- 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 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:

Class MexicanHat

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

Constructor Detail

MexicanHat

Method Detail

globalInfo

listOptions

setOptions

getOptions

getAmplitude

setAmplitude

amplitudeTipText

setMinRange

getMinRange

minRangeTipText

setMaxRange

getMaxRange

maxRangeTipText

getNoiseRate

setNoiseRate

noiseRateTipText

getNoiseVariance

setNoiseVariance

noiseVarianceTipText

getSingleModeFlag

defineDataFormat

generateExample

generateExamples

generateStart

generateFinished

getRevision

main