ROL
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Provides the implementation of the smoothed probability of exceedance. More...
#include <ROL_SmoothedPOE.hpp>
Public Member Functions | |
SmoothedPOE (const Real threshold, const Real eps) | |
SmoothedPOE (ROL::ParameterList &parlist) | |
void | updateValue (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal storage for value computation. More... | |
Real | getValue (const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure value. More... | |
void | updateGradient (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal risk measure storage for gradient computation. More... | |
void | getGradient (Vector< Real > &g, std::vector< Real > &gstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure (sub)gradient. More... | |
void | updateHessVec (Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal risk measure storage for Hessian-time-a-vector computation. More... | |
void | getHessVec (Vector< Real > &hv, std::vector< Real > &hvstat, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure Hessian-times-a-vector. More... | |
Public Member Functions inherited from ROL::RandVarFunctional< Real > | |
virtual | ~RandVarFunctional () |
RandVarFunctional (void) | |
weight_ (0) | |
void | useStorage (bool storage) |
void | useHessVecStorage (bool storage) |
virtual void | setStorage (const Ptr< ScalarController< Real >> &value_storage, const Ptr< VectorController< Real >> &gradient_storage) |
virtual void | setHessVecStorage (const Ptr< ScalarController< Real >> &gradvec_storage, const Ptr< VectorController< Real >> &hessvec_storage) |
virtual void | resetStorage (bool flag=true) |
Reset internal storage. More... | |
virtual void | resetStorage (UpdateType type) |
virtual void | initialize (const Vector< Real > &x) |
Initialize temporary variables. More... | |
virtual void | setSample (const std::vector< Real > &point, const Real weight) |
virtual Real | computeStatistic (const Ptr< const std::vector< Real >> &xstat) const |
Compute statistic. More... | |
Private Member Functions | |
Real | smoothHeaviside (const Real x, const int deriv=0) const |
Private Attributes | |
Real | threshold_ |
Real | eps_ |
Additional Inherited Members | |
Protected Member Functions inherited from ROL::RandVarFunctional< Real > | |
Real | computeValue (Objective< Real > &obj, const Vector< Real > &x, Real &tol) |
void | computeGradient (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol) |
Real | computeGradVec (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
void | computeHessVec (Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Protected Attributes inherited from ROL::RandVarFunctional< Real > | |
Real | val_ |
Real | gv_ |
Ptr< Vector< Real > > | g_ |
Ptr< Vector< Real > > | hv_ |
Ptr< Vector< Real > > | dualVector_ |
bool | firstReset_ |
std::vector< Real > | point_ |
Real | weight_ |
Provides the implementation of the smoothed probability of exceedance.
Let \((\Omega,\mathcal{F},\mathbb{P})\) be a complete space. Here, \(\Omega\) is the set of outcomes, \(\mathcal{F}\subseteq 2^\Omega\) is a \(\sigma\)-algebra of events and \(\mathbb{P}:\mathcal{F}\to[0,1]\) is a probability measure. Moreover, let \(\mathcal{X}\) be a class of random variables.
ROL's SmoothedPOE class inherits from ROL::RandVarFunctional which is written in a way to exploit parallel sampling.
Definition at line 32 of file ROL_SmoothedPOE.hpp.
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Definition at line 70 of file ROL_SmoothedPOE.hpp.
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Definition at line 74 of file ROL_SmoothedPOE.hpp.
References ROL::SmoothedPOE< Real >::eps_, and ROL::SmoothedPOE< Real >::threshold_.
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inlineprivate |
Definition at line 51 of file ROL_SmoothedPOE.hpp.
References ROL::SmoothedPOE< Real >::eps_.
Referenced by ROL::SmoothedPOE< Real >::updateGradient(), ROL::SmoothedPOE< Real >::updateHessVec(), and ROL::SmoothedPOE< Real >::updateValue().
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Update internal storage for value computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 81 of file ROL_SmoothedPOE.hpp.
References ROL::RandVarFunctional< Real >::computeValue(), ROL::SmoothedPOE< Real >::smoothHeaviside(), ROL::SmoothedPOE< Real >::threshold_, ROL::RandVarFunctional< Real >::val_, and ROL::RandVarFunctional< Real >::weight_.
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inlinevirtual |
Return risk measure value.
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getValue returns \(\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 92 of file ROL_SmoothedPOE.hpp.
References ROL::SampleGenerator< Real >::sumAll(), and ROL::RandVarFunctional< Real >::val_.
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inlinevirtual |
Update internal risk measure storage for gradient computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | g | is the gradient of the random variable objective function at the current sample point |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 100 of file ROL_SmoothedPOE.hpp.
References ROL::RandVarFunctional< Real >::computeGradient(), ROL::RandVarFunctional< Real >::computeValue(), ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::g_, ROL::SmoothedPOE< Real >::smoothHeaviside(), ROL::SmoothedPOE< Real >::threshold_, and ROL::RandVarFunctional< Real >::weight_.
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inlinevirtual |
Return risk measure (sub)gradient.
[out] | g | is the (sub)gradient of the risk measure |
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getGradient returns \(\theta\in\partial\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\) and \(\partial\mathcal{R}(X)\) denotes the subdifferential of \(\mathcal{R}\) at \(X\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 112 of file ROL_SmoothedPOE.hpp.
References ROL::RandVarFunctional< Real >::g_, and ROL::SampleGenerator< Real >::sumAll().
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inlinevirtual |
Update internal risk measure storage for Hessian-time-a-vector computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | g | is the gradient of the random variable objective function at the current sample point |
[in] | gv | is the gradient of the random variable objective function at the current sample point applied to the vector v0 |
[in] | hv | is the Hessian of the random variable objective function at the current sample point applied to the vector v0 |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 120 of file ROL_SmoothedPOE.hpp.
References ROL::RandVarFunctional< Real >::computeGradVec(), ROL::RandVarFunctional< Real >::computeHessVec(), ROL::RandVarFunctional< Real >::computeValue(), ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::hv_, ROL::SmoothedPOE< Real >::smoothHeaviside(), ROL::SmoothedPOE< Real >::threshold_, and ROL::RandVarFunctional< Real >::weight_.
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Return risk measure Hessian-times-a-vector.
[out] | hv | is the Hessian-times-a-vector of the risk measure |
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getHessVec returns \(\nabla^2 \mathcal{R}(f(x_0))v_0\) (if available) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 141 of file ROL_SmoothedPOE.hpp.
References ROL::RandVarFunctional< Real >::hv_, and ROL::SampleGenerator< Real >::sumAll().
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Definition at line 34 of file ROL_SmoothedPOE.hpp.
Referenced by ROL::SmoothedPOE< Real >::SmoothedPOE(), ROL::SmoothedPOE< Real >::updateGradient(), ROL::SmoothedPOE< Real >::updateHessVec(), and ROL::SmoothedPOE< Real >::updateValue().
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private |
Definition at line 35 of file ROL_SmoothedPOE.hpp.
Referenced by ROL::SmoothedPOE< Real >::SmoothedPOE(), and ROL::SmoothedPOE< Real >::smoothHeaviside().