Documentation / Manuel développeur
Modules disponibles
Calibration,  DataServer,  Launcher,  MetaModelOptim,  Modeler,  Optimizer,  ReLauncher,  Reliability,  ReOptimizer,  Sampler,  Sensitivity,  UncertModeler,  XmlProblem,  
Uranie / Sampler v4.9.0
|
Description of the class TRafuSampling. More...
#include <TRafuSampling.h>
Public Types | |
enum | EProbaSampling { kLHS , kSRS , kUnknown } |
enum | EPossibSampling { kRandom , kSampling0 , kSampling1 } |
Public Member Functions | |
Constructor and Destructor | |
TRafuSampling (URANIE::DataServer::TDataServer *tds, Option_t *option="proba=lhs, possib=random_sampling", Int_t sampleSize=1000) | |
virtual | ~TRafuSampling () |
Default destructor. | |
Treats the TAttributes | |
virtual void | createListOfPossibilityAttributes () |
Creates the List of fuzzy attributes to sample | |
virtual void | fillSunsetInputFile () |
Constructs the input file for the Sunset software. | |
virtual TString | buildProbabilityModule (URANIE::DataServer::TStochasticAttribute *att, const char *indentation) |
Generates the sunset module for the given TStochasticAttribute. | |
virtual TString | buildPossibilityModule (URANIE::DataServer::TPossibilityAttribute *att, const char *indentation) |
Generates the sunset module for the given TPossibilityAttribute. | |
Generate the sample | |
virtual void | createTuple () |
Creates the TTree containing the generated sample. | |
void | generateSample (Option_t *option="") |
Generates the sample. | |
Printing Log | |
virtual void | printLog (Option_t *option="") |
Prints the log. | |
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 | createListOfAttributes () |
Creates the List of attributes to simulate. | |
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 | |
EProbaSampling | _nProbaSampling |
The type of sampling for the probability (SRS, LHS) | |
EPossibSampling | _nPossibSampling |
The type of sampling for the possibility (random, 0, 1) | |
Int_t | _nPossib |
number of TPossibilityAttribute to sample | |
TList * | _lstOfPossibilityAttributesToSample |
The list of TPossibilityAttribute to sample. | |
TString | _sunsetInputFileName |
Name of the sunset input file name. | |
TString | _sunsetInfFileName |
Name of the sunset inf output file name. | |
TString | _sunsetSupFileName |
Name of the sunset sup output file name. | |
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. | |
Detailed Description
Description of the class TRafuSampling.
This class defines a TSampler object for the RaFu method.
The RaFu method applies fuzzy logic to uncertainty propagation (citation needed). To achieve this, for each fuzzy variable, one has to compute an interval inside which the real value is likely to lie. This "likelyness" is the "possibility" of the interval and can be interpreted as the level of risk taken when choosing a value inside the corresponding interval (0 = low risk, 1 = high risk).
The goal of this sampler object is to use the IRSN code Sunset to generate a sampling containing fuzzy variables. The generated data will then be stored in a Data Server and used for uncertainty propagation and data analysis.
The current implementation creates a text file for the Sunset software, launch Sunset to generate the data, and retrieve the results.
Sunset generates 2 output files (one for each bound of the possibility intervals). The TRafuSampling object will join these two data set and store them in the Data Server. However, an attribute called s__rafu__dataset__ (where "%s" is the name of the TDataServer object) is given to distinguish the two. It equals to -1.0 for the lower bound, and +1.0 for the upper bound.
Member Enumeration Documentation
◆ EPossibSampling
◆ EProbaSampling
Constructor & Destructor Documentation
◆ TRafuSampling()
URANIE::Sampler::TRafuSampling::TRafuSampling | ( | URANIE::DataServer::TDataServer * | tds, |
Option_t * | option = "proba=lhs, possib=random_sampling" , |
||
Int_t | sampleSize = 1000 |
||
) |
Creates a TRafuSampling object from a TDataServer, a sampling method and the size of the sample to generate
The random variables to sample are the attributes of the TDataServer. These attributes must derive from the TStochasticAttribute and TPossibilityAttribute classes. The sampling method for the TStochasticAttribute objects can be either "proba=lhs" (Latin Hypercube Sampling) or "proba=srs" (Simple Random Sampling). If none of these is given, "proba=lhs" is chosen. The sampling method for the TPossibilityAttribute objects can be either "possib=random_interval" (random possibility), "possib=interval_sampling0" (possibility fixed to 0) or "possib=interval_sampling1" (possibility fixed to 1). If none of these is given, "possib=random_sampling" is chosen.
- Parameters
-
tds (TDataServer *) pointer to the TDataServer. option (Option_t *) option string containing the sampling method for random variables ("proba=") and fuzy variables ("possib=") (Default = "proba=lhs, possib=random_sampling"). sampleSize (Int_t) number of values to generate for each random variable (Default = 1000).
- Exceptions
-
UErrorExceptions if the DataServer doesn't contain any stochastic attribute AND possibility sampling is different from "random_interval"
Referenced by ClassImp().
◆ ~TRafuSampling()
|
virtual |
Default destructor.
Referenced by ClassImp().
Member Function Documentation
◆ buildPossibilityModule()
|
virtual |
Generates the sunset module for the given TPossibilityAttribute.
In a Sunset input file, the details of the attribute are stored in a "module". This function create a TString containing the definition of this module.
- Parameters
-
att (TStochasticAttribute *) the attribute which details are used to build the module string indentation (char *) for aesthetical reason, this parameter provides the level of indentation of the module.
- Exceptions
-
UErrorExceptions if the type of the attribute is not supported.
Referenced by ClassImp().
◆ buildProbabilityModule()
|
virtual |
Generates the sunset module for the given TStochasticAttribute.
In a Sunset input file, the details of the attribute are stored in a "module". This function create a TString containing the definition of this module.
- Parameters
-
att (TStochasticAttribute *) the attribute which details are used to build the module string indentation (char *) for aesthetical reason, this parameter provides the level of indentation of the module.
- Exceptions
-
UErrorExceptions if the type of the attribute is not supported.
Referenced by ClassImp().
◆ createListOfPossibilityAttributes()
|
virtual |
Creates the List of fuzzy attributes to sample
Retrieve the list of TPossibilityAttribute objects stored in the TDataServer.
Referenced by ClassImp().
◆ createTuple()
|
virtual |
Creates the TTree containing the generated sample.
Reimplemented from URANIE::Sampler::TSampler.
Referenced by ClassImp().
◆ fillSunsetInputFile()
|
virtual |
Constructs the input file for the Sunset software.
This function create and fill the file containing all details to command Sunset to generate a sampling of probability and possibility variables.
Referenced by ClassImp().
◆ generateSample()
|
virtual |
Generates the sample.
Creates the input file for Sunset, calls Sunset, retrieves the results and stores them in the TDataServer.
- Parameters
-
option (Option_t *) option string (Default = "")
Implements URANIE::Sampler::TSampler.
Referenced by ClassImp().
◆ printLog()
|
virtual |
Prints the log.
- Parameters
-
option (Option_t *) option string (Default = "")
Reimplemented from URANIE::Sampler::TSampler.
Referenced by ClassImp().
Member Data Documentation
◆ _lstOfPossibilityAttributesToSample
TList* URANIE::Sampler::TRafuSampling::_lstOfPossibilityAttributesToSample |
The list of TPossibilityAttribute to sample.
Referenced by ClassImp().
◆ _nPossib
Int_t URANIE::Sampler::TRafuSampling::_nPossib |
number of TPossibilityAttribute to sample
Referenced by ClassImp().
◆ _nPossibSampling
EPossibSampling URANIE::Sampler::TRafuSampling::_nPossibSampling |
The type of sampling for the possibility (random, 0, 1)
Referenced by ClassImp().
◆ _nProbaSampling
EProbaSampling URANIE::Sampler::TRafuSampling::_nProbaSampling |
The type of sampling for the probability (SRS, LHS)
Referenced by ClassImp().
◆ _sunsetInfFileName
TString URANIE::Sampler::TRafuSampling::_sunsetInfFileName |
Name of the sunset inf output file name.
Referenced by ClassImp().
◆ _sunsetInputFileName
TString URANIE::Sampler::TRafuSampling::_sunsetInputFileName |
Name of the sunset input file name.
Referenced by ClassImp().
◆ _sunsetSupFileName
TString URANIE::Sampler::TRafuSampling::_sunsetSupFileName |
Name of the sunset sup output file name.
Referenced by ClassImp().