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Uranie / Sampler v4.9.0
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Abstract class for Vectorial Quantification (VQ) algorithms. More...
#include <TVQ.h>
Public Member Functions | |
Constructor and Destructor | |
TVQ (URANIE::DataServer::TDataServer *tds, Option_t *option, Int_t ns) | |
Constructor with a dataserver. | |
virtual | ~TVQ () |
Default destructor. | |
Setting and Getting global informations | |
Bool_t | getSaveAll () |
Returns the flag SaveAll. | |
void | setDrawProgressBar (Bool_t bbool=kTRUE) |
Set the "draw progress bar" flag. | |
Bool_t | getDrawProgressBar () |
Get the clean flag. | |
Treats the TAttributes | |
void | createListOfAttributes () |
Creates the list of attributes to select patterns. | |
void | shuffle () |
shuffle the learning database (original TDataServer) | |
Manipulate the sample | |
The method to get the subsample TDataServer | |
URANIE::DataServer::TDataServer * | getSubSample (Option_t *option="") |
Generate the Sample and return the TDataServer. | |
State machine | |
For the learning process, three states can be created
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virtual void | init () |
The pre-processing step. | |
virtual void | terminate () |
The post-processing step. | |
virtual void | learn (Int_t index)=0 |
The learning step for a pattern. | |
Printing Log | |
virtual void | printLog (Option_t *option="") |
Prints the log. | |
Public Member Functions inherited from URANIE::Sampler::TSamplerStochastic | |
TSamplerStochastic (URANIE::DataServer::TDataServer *tds, Option_t *option, Int_t nCalcul) | |
Constructor with a dataserver. | |
virtual | ~TSamplerStochastic () |
Default destructor. | |
void | setSeed (Int_t ind=0) |
Init the seed. | |
Int_t | getSeed () |
Returns the seed value. | |
Public Member Functions inherited from URANIE::Sampler::TSampler | |
TSampler (URANIE::DataServer::TDataServer *tds, Option_t *option, Int_t nCalcul) | |
Constructor with a TDataServer, the options and the size of the sample. | |
virtual | ~TSampler () |
Default destructor. | |
Int_t | GetID () |
Returns the ID of the class. | |
void | setMethodName (TString str) |
Sets the method name in a global variable. | |
TString | getMethodName () |
Gets the method name. | |
virtual URANIE::DataServer::TDataServer * | getTDS () |
Return the TDS filling by the sampling algorithm. | |
void | parseOption (Option_t *option) |
Parse the option. | |
virtual void | generateSample (Option_t *option="")=0 |
Generates the Sample. | |
virtual void | createTuple () |
Creates the TDSNtupleD of data with only the TStochasticAttributes. | |
URANIE::DataServer::TDSNtupleD * | getTuple () |
Returns the TDSNtupleD of data. | |
virtual void | fillOtherAttributes () |
Fills the TDSNtupleD of data with other TFormulaAttributes. | |
void | setLog () |
void | unsetLog () |
void | changeLog () |
Bool_t | getLog () |
Public Attributes | |
TVector | _vecindexorg |
The vector of index of the database. | |
URANIE::DataServer::TDataServer * | _subtds |
The subsampler returened by the getSubSample method. | |
Bool_t | _bsaveall |
The boolean to save all the data in the learning (default = kFALSE) | |
TString | _sattributes |
the list of attributes | |
Public Attributes inherited from URANIE::Sampler::TSampler | |
Int_t | _nS |
The size of the sample. | |
Int_t | _nX |
The size of attributes to sample. | |
URANIE::DataServer::TDSNtupleD * | _ntsample |
the tntuple of data | |
TString | _sMethod |
The title of the sampler method. | |
Bool_t | _blog |
Log Printing. | |
Bool_t | _bupdateFile |
Update the back up file when generating the attributeformula if there is some. | |
URANIE::DataServer::TDataServer * | _tds |
Pointer to a TDS. | |
TList * | _lstOfAttributesToSample |
The list of Stochastic Attributes to sample. | |
Protected Attributes | |
URANIE::DataServer::UMessageLogger * | _fLogger |
Bool_t | _bdrawProgressBar |
Boolean to know if the progress bar has to be drawn. | |
Protected Attributes inherited from URANIE::Sampler::TSamplerStochastic | |
Int_t | _nSeed |
Detailed Description
Abstract class for Vectorial Quantification (VQ) algorithms.
The generateSample method of these VQ classes can be considered as a machine with 3 states :
- Implementation
- The virtual methods to implement for a new VQ class are the learn(index) and generateSample methods.
- Implemented algorithms :
- TNeuralGas : The Neural Gas algorithm (Martinetz and Schulten, 1991)
Constructor & Destructor Documentation
◆ TVQ()
URANIE::Sampler::TVQ::TVQ | ( | URANIE::DataServer::TDataServer * | tds, |
Option_t * | option, | ||
Int_t | ns | ||
) |
Constructor with a dataserver.
- Parameters
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tds (URANIE::DataServer::TDataServer *) the original data option (Option_t) contains the options - "saveall" Save all the data generate by the algorithm ( _bsaveall = kTRUE). When is TRUE, all points during the learning process are store in the TDataServer, and when is FALSE, only points at the last iteration are store.
ns (Int_t) the size of the subsample
References _bsaveall.
◆ ~TVQ()
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virtual |
Default destructor.
References _subtds.
Member Function Documentation
◆ createListOfAttributes()
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virtual |
Creates the list of attributes to select patterns.
Reimplemented from URANIE::Sampler::TSampler.
References URANIE::Sampler::TSampler::_blog, URANIE::Sampler::TSampler::_lstOfAttributesToSample, URANIE::Sampler::TSampler::_nX, and URANIE::Sampler::TSampler::_tds.
Referenced by init().
◆ getDrawProgressBar()
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inline |
◆ getSaveAll()
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inline |
Returns the flag SaveAll.
- When is TRUE, all points during the learning process are store in the TDataServer.
- When is FALSE, only points at the last iteration are store in the TDataServer.
References _bsaveall.
◆ getSubSample()
URANIE::DataServer::TDataServer * URANIE::Sampler::TVQ::getSubSample | ( | Option_t * | option = "" | ) |
Generate the Sample and return the TDataServer.
- Parameters
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option (Option_t) contains the options - "loop=" Defines the number of loop to stop the algorithm. ("loop=10" for example)
References _subtds, and URANIE::Sampler::TSampler::generateSample().
◆ init()
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virtual |
The pre-processing step.
Reimplemented from URANIE::Sampler::TSamplerStochastic.
Reimplemented in URANIE::Sampler::TNeuralGas.
References URANIE::Sampler::TSampler::_blog, URANIE::Sampler::TSampler::_lstOfAttributesToSample, _sattributes, _subtds, URANIE::Sampler::TSampler::_tds, _vecindexorg, and createListOfAttributes().
Referenced by URANIE::Sampler::TNeuralGas::init().
◆ learn()
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pure virtual |
The learning step for a pattern.
Implemented in URANIE::Sampler::TNeuralGas.
◆ printLog()
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virtual |
Prints the log.
Reimplemented from URANIE::Sampler::TSamplerStochastic.
Reimplemented in URANIE::Sampler::TNeuralGas.
◆ setDrawProgressBar()
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inline |
Set the "draw progress bar" flag.
The progress bar will be drawn if and only if the "draw progress bar" flag is true.
References _bdrawProgressBar.
◆ shuffle()
void URANIE::Sampler::TVQ::shuffle | ( | ) |
shuffle the learning database (original TDataServer)
References URANIE::Sampler::TSampler::_blog, and _vecindexorg.
Referenced by URANIE::Sampler::TNeuralGas::generateSample(), and URANIE::Sampler::TNeuralGas::init().
◆ terminate()
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virtual |
The post-processing step.
Reimplemented from URANIE::Sampler::TSamplerStochastic.
References URANIE::Sampler::TSampler::_blog.
Referenced by URANIE::Sampler::TNeuralGas::generateSample().
Member Data Documentation
◆ _bdrawProgressBar
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protected |
Boolean to know if the progress bar has to be drawn.
Referenced by URANIE::Sampler::TNeuralGas::generateSample(), getDrawProgressBar(), and setDrawProgressBar().
◆ _bsaveall
Bool_t URANIE::Sampler::TVQ::_bsaveall |
The boolean to save all the data in the learning (default = kFALSE)
Referenced by URANIE::Sampler::TNeuralGas::generateSample(), getSaveAll(), URANIE::Sampler::TNeuralGas::init(), URANIE::Sampler::TNeuralGas::learn(), URANIE::Sampler::TNeuralGas::printLog(), and TVQ().
◆ _fLogger
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protected |
◆ _sattributes
TString URANIE::Sampler::TVQ::_sattributes |
the list of attributes
Referenced by URANIE::Sampler::TNeuralGas::generateSample(), and init().
◆ _subtds
URANIE::DataServer::TDataServer* URANIE::Sampler::TVQ::_subtds |
The subsampler returened by the getSubSample method.
Referenced by getSubSample(), URANIE::Sampler::TNeuralGas::init(), init(), URANIE::Sampler::TNeuralGas::learn(), and ~TVQ().
◆ _vecindexorg
TVector URANIE::Sampler::TVQ::_vecindexorg |
The vector of index of the database.
Referenced by URANIE::Sampler::TNeuralGas::generateSample(), URANIE::Sampler::TNeuralGas::init(), init(), and shuffle().