weka.filters.unsupervised.attribute
Class FastWavelet

java.lang.Object
  weka.filters.Filter
      weka.filters.SimpleFilter
          weka.filters.SimpleBatchFilter
              weka.filters.unsupervised.attribute.FastWavelet

All Implemented Interfaces:

Serializable, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.filters.UnsupervisedFilter

public class FastWavelet
extends weka.filters.SimpleBatchFilter
implements weka.core.TechnicalInformationHandler, weka.filters.UnsupervisedFilter

A filter for wavelet transformation using the JSci library's fast wavelet transform (FWT) algorithms.

For more information see:

(2009). JSci - A science API for Java.

BibTeX:

 @misc{missing_id,
    title = {JSci - A science API for Java},
    year = {2009},
    HTTP = {http://jsci.sourceforge.net/}
 }
 

Valid options are:

 -D
  Turns on output of debugging information.

 -A <HAAR|CDF2_4|DAUBECHIES2|SYMMLET8>
  The algorithm to use.
  (default: HAAR)

 -P <ZERO>
  The padding to use.
  (default: ZERO)

 -F <filter specification>
  The filter to use as preprocessing step (classname and options).
  (default: MultiFilter with ReplaceMissingValues and Normalize)

 -inverse
  Whether to perform the inverse transform (from wavelet space into
  normal space again).
  (default: off)

 Options specific to filter weka.filters.MultiFilter ('-F'):
 

 -D
  Turns on output of debugging information.

 -F <classname [options]>
  A filter to apply (can be specified multiple times).

Version:

$Revision: 4521 $

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

static int	ALGORITHM_CDF2_4 the type of algorithm: CDF2 4.
static int	ALGORITHM_DAUBECHIES2 the type of algorithm: Daubechies2.
static int	ALGORITHM_HAAR the type of algorithm: Haar.
static int	ALGORITHM_SYMMLET8 the type of algorithm: Symmlet8.
protected int	m_Algorithm the type of algorithm.
protected weka.filters.Filter	m_Filter an optional filter for preprocessing of the data.
protected boolean	m_InverseTransform whether to perform inverse transformation.
protected int	m_Padding the type of padding.
static int	PADDING_ZERO the type of padding: Zero padding.
static weka.core.Tag[]	TAGS_ALGORITHM the types of algorithm.
static weka.core.Tag[]	TAGS_PADDING the types of padding.

Fields inherited from class weka.filters.SimpleFilter

m_Debug

Fields inherited from class weka.filters.Filter

m_FirstBatchDone, m_InputRelAtts, m_InputStringAtts, m_NewBatch, m_OutputRelAtts, m_OutputStringAtts

Constructor Summary

FastWavelet()
default constructor.

Method Summary

String	algorithmTipText() Returns the tip text for this property.
protected weka.core.Instances	determineOutputFormat(weka.core.Instances inputFormat) Determines the output format based on the input format and returns this.
String	filterTipText() Returns the tip text for this property.
weka.core.SelectedTag	getAlgorithm() Gets the type of algorithm to use.
weka.core.Capabilities	getCapabilities() Returns the Capabilities of this filter.
weka.filters.Filter	getFilter() Get the preprocessing filter.
boolean	getInverseTransform() Gets whether to use the inverse transform.
String[]	getOptions() returns the options of the current setup.
weka.core.SelectedTag	getPadding() Gets the type of Padding to use.
String	getRevision() Returns the revision string.
weka.core.TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
String	globalInfo() Returns a string describing this classifier.
protected weka.core.Instances	inverse(weka.core.Instances data) Renames the attributes when using the inverse transform.
String	inverseTransformTipText() Returns the tip text for this property.
Enumeration	listOptions() Gets an enumeration describing the available options.
static void	main(String[] args) runs the filter with the given arguments.
protected static int	nextPowerOf2(int n) returns the next bigger number that's a power of 2.
protected weka.core.Instances	pad(weka.core.Instances data) pads the data to conform to the necessary number of attributes.
String	paddingTipText() Returns the tip text for this property.
protected weka.core.Instances	process(weka.core.Instances instances) Processes the given data (may change the provided dataset) and returns the modified version.
protected weka.core.Instances	processData(weka.core.Instances instances) processes the instances using the HAAR/JSci algorithm.
void	setAlgorithm(weka.core.SelectedTag value) Sets the type of algorithm to use.
void	setFilter(weka.filters.Filter value) Set the preprocessing filter (only used for setup).
void	setInverseTransform(boolean value) Sets whether to use the inverse tranform.
void	setOptions(String[] options) Parses the options for this object.
void	setPadding(weka.core.SelectedTag value) Sets the type of Padding to use.

Methods inherited from class weka.filters.SimpleBatchFilter

batchFinished, hasImmediateOutputFormat, input

Methods inherited from class weka.filters.SimpleFilter

debugTipText, getDebug, reset, setDebug, setInputFormat

Methods inherited from class weka.filters.Filter

batchFilterFile, bufferInput, copyValues, copyValues, filterFile, flushInput, getCapabilities, getInputFormat, getOutputFormat, initInputLocators, initOutputLocators, inputFormatPeek, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, mayRemoveInstanceAfterFirstBatchDone, numPendingOutput, output, outputFormatPeek, outputPeek, push, resetQueue, runFilter, setOutputFormat, testInputFormat, toString, useFilter, wekaStaticWrapper

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

ALGORITHM_HAAR

public static final int ALGORITHM_HAAR

the type of algorithm: Haar.

See Also:

Constant Field Values

ALGORITHM_CDF2_4

public static final int ALGORITHM_CDF2_4

the type of algorithm: CDF2 4.

See Also:

Constant Field Values

ALGORITHM_DAUBECHIES2

public static final int ALGORITHM_DAUBECHIES2

the type of algorithm: Daubechies2.

See Also:

Constant Field Values

ALGORITHM_SYMMLET8

public static final int ALGORITHM_SYMMLET8

the type of algorithm: Symmlet8.

See Also:

Constant Field Values

TAGS_ALGORITHM

public static final weka.core.Tag[] TAGS_ALGORITHM

the types of algorithm.

PADDING_ZERO

public static final int PADDING_ZERO

the type of padding: Zero padding.

See Also:

Constant Field Values

TAGS_PADDING

public static final weka.core.Tag[] TAGS_PADDING

the types of padding.

m_Filter

protected weka.filters.Filter m_Filter

an optional filter for preprocessing of the data.

m_Algorithm

protected int m_Algorithm

the type of algorithm.

m_Padding

protected int m_Padding

the type of padding.

m_InverseTransform

protected boolean m_InverseTransform

whether to perform inverse transformation.

Constructor Detail

FastWavelet

public FastWavelet()

default constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier.

Specified by:

globalInfo in class weka.filters.SimpleFilter

Returns:

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

getTechnicalInformation

public weka.core.TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface weka.core.TechnicalInformationHandler

Returns:

the technical information about this class

listOptions

public Enumeration listOptions()

Gets an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.filters.SimpleFilter

Returns:

an enumeration of all the available options.

getOptions

public String[] getOptions()

returns the options of the current setup.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.filters.SimpleFilter

Returns:

the current options

setOptions

public void setOptions(String[] options)
                throws Exception

Parses the options for this object.

Valid options are:

 -D
  Turns on output of debugging information.

 -A <HAAR|CDF2_4|DAUBECHIES2|SYMMLET8>
  The algorithm to use.
  (default: HAAR)

 -P <ZERO>
  The padding to use.
  (default: ZERO)

 -F <filter specification>
  The filter to use as preprocessing step (classname and options).
  (default: MultiFilter with ReplaceMissingValues and Normalize)

 -inverse
  Whether to perform the inverse transform (from wavelet space into
  normal space again).
  (default: off)

 Options specific to filter weka.filters.MultiFilter ('-F'):
 

 -D
  Turns on output of debugging information.

 -F <classname [options]>
  A filter to apply (can be specified multiple times).

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.filters.SimpleFilter

Parameters:

options - the options to use

Throws:

Exception - if the option setting fails

filterTipText

public String filterTipText()

Returns the tip text for this property.

Returns:

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

setFilter

public void setFilter(weka.filters.Filter value)

Set the preprocessing filter (only used for setup).

Parameters:

value - the preprocessing filter.

getFilter

public weka.filters.Filter getFilter()

Get the preprocessing filter.

Returns:

the preprocessing filter

algorithmTipText

public String algorithmTipText()

Returns the tip text for this property.

Returns:

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

setAlgorithm

public void setAlgorithm(weka.core.SelectedTag value)

Sets the type of algorithm to use.

Parameters:

value - the algorithm type

getAlgorithm

public weka.core.SelectedTag getAlgorithm()

Gets the type of algorithm to use.

Returns:

the current algorithm type.

paddingTipText

public String paddingTipText()

Returns the tip text for this property.

Returns:

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

setPadding

public void setPadding(weka.core.SelectedTag value)

Sets the type of Padding to use.

Parameters:

value - the Padding type

getPadding

public weka.core.SelectedTag getPadding()

Gets the type of Padding to use.

Returns:

the current Padding type.

inverseTransformTipText

public String inverseTransformTipText()

Returns the tip text for this property.

Returns:

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

setInverseTransform

public void setInverseTransform(boolean value)

Sets whether to use the inverse tranform.

Parameters:

value - true if to use inverse transform

getInverseTransform

public boolean getInverseTransform()

Gets whether to use the inverse transform.

Returns:

true if inverse transform is used

nextPowerOf2

protected static int nextPowerOf2(int n)

returns the next bigger number that's a power of 2. If the number is already a power of 2 then this will be returned. The number will be at least 2^2..

Parameters:

n - the number to start from

Returns:

the next bigger number

pad

protected weka.core.Instances pad(weka.core.Instances data)

pads the data to conform to the necessary number of attributes.

Parameters:

data - the data to pad

Returns:

the padded data

inverse

protected weka.core.Instances inverse(weka.core.Instances data)

Renames the attributes when using the inverse transform.

Parameters:

data - the data to transform.

Returns:

the transformed data

determineOutputFormat

protected weka.core.Instances determineOutputFormat(weka.core.Instances inputFormat)
                                             throws Exception

Determines the output format based on the input format and returns this. In case the output format cannot be returned immediately, i.e., immediateOutputFormat() returns false, then this method will be called from batchFinished().

Specified by:

determineOutputFormat in class weka.filters.SimpleFilter

Parameters:

inputFormat - the input format to base the output format on

Returns:

the output format

Throws:

Exception - in case the determination goes wrong

See Also:

SimpleBatchFilter.hasImmediateOutputFormat(), SimpleBatchFilter.batchFinished()

processData

protected weka.core.Instances processData(weka.core.Instances instances)
                                   throws Exception

processes the instances using the HAAR/JSci algorithm.

Parameters:

instances - the data to process

Returns:

the modified data

Throws:

Exception - in case the processing goes wrong

See Also:

FastHaar

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns the Capabilities of this filter.

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.filters.Filter

Returns:

the capabilities of this object

See Also:

Capabilities

process

protected weka.core.Instances process(weka.core.Instances instances)
                               throws Exception

Processes the given data (may change the provided dataset) and returns the modified version. This method is called in batchFinished().

Specified by:

process in class weka.filters.SimpleFilter

Parameters:

instances - the data to process

Returns:

the modified data

Throws:

Exception - in case the processing goes wrong

See Also:

SimpleBatchFilter.batchFinished()

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.filters.Filter

Returns:

the revision

main

public static void main(String[] args)

runs the filter with the given arguments.

Parameters:

args - the commandline arguments