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// -*- C++ -*-
/**
* @brief The test file of class SimulationSensitivityAnalysis for standard methods
*
* Copyright 2005-2025 Airbus-EDF-IMACS-ONERA-Phimeca
*
* This library is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this library. If not, see <http://www.gnu.org/licenses/>.
*
*/
#include "openturns/OT.hxx"
#include "openturns/OTtestcode.hxx"
using namespace OT;
using namespace OT::Test;
int main(int, char *[])
{
TESTPREAMBLE;
OStream fullprint(std::cout);
try
{
/* Uncertain parameters*/
Normal distribution(Point(3, 1.0), Point(3, 2.0), CorrelationMatrix(3));
distribution.setName("Unnamed");
/* Model */
Description input(3);
input[0] = "x";
input[1] = "y";
input[2] = "z";
Description formulas(1);
formulas[0] = "x-1.5*y+2*z";
SymbolicFunction f(input, formulas);
/* Sampling */
UnsignedInteger size = 100;
Sample inputSample(distribution.getSample(size));
Sample outputSample(f(inputSample));
Collection<ComparisonOperator> comparisonOperators(4);
comparisonOperators[0] = Less();
comparisonOperators[1] = LessOrEqual();
comparisonOperators[2] = Greater();
comparisonOperators[3] = GreaterOrEqual();
ResourceMap::SetAsUnsignedInteger("SimulationSensitivityAnalysis-DefaultSampleMargin", 10);
Scalar threshold = 3.0;
for (UnsignedInteger i = 0; i < 4; ++i)
{
/* Analysis based on an event */
RandomVector X(distribution);
CompositeRandomVector Y(f, X);
ThresholdEvent event(Y, comparisonOperators[i], threshold);
{
SimulationSensitivityAnalysis algo(event, inputSample, outputSample);
fullprint << "algo=" << algo << std::endl;
/* Perform the analysis */
fullprint << "Mean point in event domain=" << algo.computeMeanPointInEventDomain() << std::endl;
fullprint << "Importance factors at threshold " << threshold << " =" << algo.computeImportanceFactors() << std::endl;
fullprint << "Importance factors at threshold/2 " << threshold / 2 << " =" << algo.computeImportanceFactors(threshold / 2) << std::endl;
Graph importanceFactorsGraph(algo.drawImportanceFactors());
fullprint << "importanceFactorsGraph=" << importanceFactorsGraph << std::endl;
/* Importance factors evolution on probability scale */
Graph importanceFactorsRangeGraphProbability(algo.drawImportanceFactorsRange());
fullprint << "importanceFactorsRangeGraphProbability=" << importanceFactorsRangeGraphProbability << std::endl;
/* Importance factors evolution on threshold scale */
Graph importanceFactorsRangeGraphThreshold(algo.drawImportanceFactorsRange(false));
fullprint << "importanceFactorsRangeGraphThreshold=" << importanceFactorsRangeGraphThreshold << std::endl;
}
}
}
catch (TestFailed & ex)
{
std::cerr << ex << std::endl;
return ExitCode::Error;
}
return ExitCode::Success;
}
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