/usr/include/openturns/SubsetSampling.hxx is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
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/**
* @brief Subset simulation method
*
* Copyright 2005-2017 Airbus-EDF-IMACS-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
* along with this library. If not, see <http://www.gnu.org/licenses/>.
*
*/
#ifndef OPENTURNS_SUBSETSAMPLING_HXX
#define OPENTURNS_SUBSETSAMPLING_HXX
#include "openturns/Simulation.hxx"
#include "openturns/StandardEvent.hxx"
BEGIN_NAMESPACE_OPENTURNS
class OT_API SubsetSampling
: public Simulation
{
CLASSNAME
public:
/** Default Constructor */
SubsetSampling();
/** Constructor with parameters */
SubsetSampling(const Event & event,
const Scalar proposalRange = ResourceMap::GetAsScalar("SubsetSampling-DefaultProposalRange"),
const Scalar conditionalProbability = ResourceMap::GetAsScalar("SubsetSampling-DefaultConditionalProbability"));
/** Virtual constructor */
virtual SubsetSampling * clone() const;
/** The range of the uniform proposal pdf */
void setProposalRange(Scalar proposalRange);
Scalar getProposalRange() const;
/** Ratio parameter */
void setConditionalProbability(Scalar conditionalProbability);
Scalar getConditionalProbability() const;
/** Accessor to the achieved number of steps */
UnsignedInteger getNumberOfSteps();
/** Stepwise result accessors */
Point getThresholdPerStep() const;
Point getGammaPerStep() const;
Point getCoefficientOfVariationPerStep() const;
Point getProbabilityEstimatePerStep() const;
/** Keep event sample */
void setKeepEventSample(bool keepEventSample);
/** Event input/output sample accessor */
Sample getEventInputSample() const;
Sample getEventOutputSample() const;
/** i-subset */
void setISubset(Bool iSubset);
void setBetaMin(Scalar betaMin);
/** Performs the actual computation. */
void run();
/** String converter */
String __repr__() const;
/** Method save() stores the object through the StorageManager */
virtual void save(Advocate & adv) const;
/** Method load() reloads the object from the StorageManager */
virtual void load(Advocate & adv);
private:
/** Compute the block sample */
Sample computeBlockSample();
/** Compute the new threshold corresponding to the target failure probability */
Scalar computeThreshold();
/** compute probability estimate on the current sample */
Scalar computeProbability(Scalar probabilityEstimate, Scalar threshold);
/** Sort new seeds */
void initializeSeed(Scalar threshold);
/** Compute the correlation on markov chains at the current state of the algorithm */
Scalar computeVarianceGamma(Scalar currentFailureProbability, Scalar threshold);
/** Generate new points in the conditional failure domain */
void generatePoints(Scalar threshold);
// some parameters
Scalar proposalRange_;// width of the proposal pdf
Scalar conditionalProbability_;// target probability at each subset
Bool iSubset_;// conditional pre-sampling
Scalar betaMin_;// pre-sampling hypersphere exclusion radius
Bool keepEventSample_;// do we keep the event sample ?
// some results
UnsignedInteger numberOfSteps_;// number of subset steps
Point thresholdPerStep_;// intermediate thresholds
Point gammaPerStep_;// intermediate gammas
Point coefficientOfVariationPerStep_;// intermediate COVS
Point probabilityEstimatePerStep_;// intermediate PFs
Sample eventInputSample_;// event input sample
Sample eventOutputSample_;// event output sample
// attributes used for conveniency, not to be saved/loaded
StandardEvent standardEvent_;// the algorithm happens in U
UnsignedInteger dimension_;// input dimension
Sample currentPointSample_;// X
Sample currentLevelSample_;//f(X)
UnsignedInteger seedNumber_;// number of seed points
} ; /* class SubsetSampling */
END_NAMESPACE_OPENTURNS
#endif /* OPENTURNS_SUBSETSAMPLING_HXX */
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