13.5.8. Macro “sensitivityRegressionFunctionFlowrate.C”

13.5.8.1. Objective

The objective of this macro is to perform a regression with “SRC” method on a database generated with a function using sampling of parameters obeying uniform laws with 4000 patterns. flowrateModel is a function defined in Presentation of the problem and “loaded” through the macro UserFunctions.C (the file can be found in ${URANIESYS}/share/uranie/macros). Function flowrateModel uses the eight variables defined in Presentation of the problem and set in the main macro.

13.5.8.2. Macro Uranie

void sensitivityRegressionFunctionFlowrate(const string& figure="figure.png", const string& style="", 
    const string& filename="", const string& treename="", int seed=0)
{
    gROOT->LoadMacro("UserFunctions.C");

    // Define the DataServer
    TDataServer *tds = new TDataServer("tdsflowreate", "DataBase flowreate");
    tds->addAttribute( new TUniformDistribution("rw", 0.05, 0.15));
    tds->addAttribute( new TUniformDistribution("r", 100.0, 50000.0));
    tds->addAttribute( new TUniformDistribution("tu", 63070.0, 115600.0));
    tds->addAttribute( new TUniformDistribution("tl", 63.1, 116.0));
    tds->addAttribute( new TUniformDistribution("hu", 990.0, 1110.0));
    tds->addAttribute( new TUniformDistribution("hl", 700.0, 820.0));
    tds->addAttribute( new TUniformDistribution("l", 1120.0, 1680.0));
    tds->addAttribute( new TUniformDistribution("kw", 9855.0, 12045.0));
      
    // \param Size of a sampling.
    Int_t nS = 4000;

    TSampling *sampling = new TSampling(tds, "lhs", nS);
    sampling->generateSample();	
      

    TLauncherFunction * tlf = new TLauncherFunction(tds, "flowrateModel");
    tlf->setDrawProgressBar(kFALSE);
    tlf->run();
      

    TRegression * treg = new TRegression(tds, "rw:r:tu:tl:hu:hl:l:kw","flowrateModel", "SRC");
    treg->computeIndexes();
    treg->getResultTuple()->SetScanField(60);

    treg->getResultTuple()->Scan("Out:Inp:Method:Algo:Value:CILower:CIUpper","Order==\"First\"", "colsize=5 col=6:8::9:8:8:8");
      

    TCanvas  *can = new TCanvas("c1", "Graph for the Macro sensitivityRegressionFunctionFlowrate",5,64,1270,667);
    treg->drawIndexes("Flowrate", "", "hist,first,nonewcanv");
}

Each attribute is related to a TAttribute obeying uniform laws on specific intervals:

    tds->addAttribute( new TUniformDistribution("rw", 0.05, 0.15));
    tds->addAttribute( new TUniformDistribution("r", 100.0, 50000.0));
    tds->addAttribute( new TUniformDistribution("tu", 63070.0, 115600.0));
    tds->addAttribute( new TUniformDistribution("tl", 63.1, 116.0));
    tds->addAttribute( new TUniformDistribution("hu", 990.0, 1110.0));
    tds->addAttribute( new TUniformDistribution("hl", 700.0, 820.0));
    tds->addAttribute( new TUniformDistribution("l", 1120.0, 1680.0));
    tds->addAttribute( new TUniformDistribution("kw", 9855.0, 12045.0));

The sampling is generated on 4000 patterns with a LHS method:

    TSampling *sampling = new TSampling(tds, "lhs", nS);
    sampling->generateSample();

Function flowrateModel is set to perform calculation on the sampling:

    TLauncherFunction * tlf = new TLauncherFunction(tds, "flowrateModel");
    tlf->run();

The regression is performed over all variables:

    TRegression * treg = new TRegression(tds, "rw:r:tu:tl:hu:hl:l:kw","flowrateModel", "SRC");
    treg->computeIndexes();

Sensitivity indexes are then displayed through an histogram:

    TCanvas  *can = new TCanvas("c1", "Graph for the Macro sensitivityRegressionFunctionFlowrate",5,64,1270,667);
    treg->drawIndexes("Flowrate", "", "hist,first,nonewcanv");

13.5.8.3. Graph

../../_images/sensitivityRegressionFunctionFlowrate.png

Figure 13.24 Graph of the macro “sensitivityRegressionFunctionFlowrate.C”

13.5.8.4. Console

--- Uranie v4.11/0 --- Developed with ROOT (6.36.06)
                      Copyright (C) 2013-2026 CEA/DES 
                      Contact: support-uranie@cea.fr 
                      Date: Thu Feb 12, 2026

*************************************************************************************
*    Row   *    Out *      Inp * Metho *      Algo *    Value *  CILower *  CIUpper *
*************************************************************************************
*        0 * flowra *       rw * SRC^2 * --first-- * 0.820265 *       -1 *       -1 *
*        2 * flowra *       rw * SRC^2 * --rho^2-- *  0.81668 * 0.805846 * 0.826888 *
*        4 * flowra *        r * SRC^2 * --first-- * 5.97e-06 *       -1 *       -1 *
*        6 * flowra *        r * SRC^2 * --rho^2-- * 1.92e-06 * 2.65e-07 * 0.001339 *
*        8 * flowra *       tu * SRC^2 * --first-- * 8.64e-06 *       -1 *       -1 *
*       10 * flowra *       tu * SRC^2 * --rho^2-- * 4.03e-06 * 3.14e-07 * 0.001306 *
*       12 * flowra *       tl * SRC^2 * --first-- * 5.73e-05 *       -1 *       -1 *
*       14 * flowra *       tl * SRC^2 * --rho^2-- * 0.000209 * 7.34e-07 * 0.002085 *
*       16 * flowra *       hu * SRC^2 * --first-- * 0.039645 *       -1 *       -1 *
*       18 * flowra *       hu * SRC^2 * --rho^2-- * 0.037119 * 0.026221 * 0.049000 *
*       20 * flowra *       hl * SRC^2 * --first-- * 0.040597 *       -1 *       -1 *
*       22 * flowra *       hl * SRC^2 * --rho^2-- * 0.039708 * 0.028688 * 0.052470 *
*       24 * flowra *        l * SRC^2 * --first-- * 0.040895 *       -1 *       -1 *
*       26 * flowra *        l * SRC^2 * --rho^2-- * 0.041241 * 0.029896 * 0.054454 *
*       28 * flowra *       kw * SRC^2 * --first-- * 0.009174 *       -1 *       -1 *
*       30 * flowra *       kw * SRC^2 * --rho^2-- * 0.009090 * 0.004191 * 0.015767 *
*       32 * flowra *  __sum__ * SRC^2 * --first-- *  0.95065 *       -1 *       -1 *
*       34 * flowra *   __R2__ * SRC^2 * --first-- * 0.947296 *       -1 *       -1 *
*       36 * flowra *  __R2A__ * SRC^2 * --first-- *  0.94719 *       -1 *       -1 *
*************************************************************************************
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