Dakota
Version 6.20
Explore and Predict with Confidence
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Public Member Functions | |
DakotaROLEqConstraintsGrad (Model &model) | |
Constructor. More... | |
virtual | ~DakotaROLEqConstraintsGrad () |
Destructor. | |
void | applyJacobian (std::vector< Real > &jv, const std::vector< Real > &v, const std::vector< Real > &x, Real &tol) override |
Function to return the result of applying the constraint gradient to an arbitrary vector to ROL. | |
void | applyAdjointJacobian (std::vector< Real > &ajv, const std::vector< Real > &v, const std::vector< Real > &x, Real &tol) override |
Function to return the result of applying the constraint adjoint to an arbitrary vector to ROL. | |
Public Member Functions inherited from DakotaROLEqConstraints | |
DakotaROLEqConstraints (Model &model) | |
Constructor. More... | |
void | value (std::vector< Real > &c, const std::vector< Real > &x, Real &tol) override |
Function to return the constaint value to ROL. | |
Additional Inherited Members | |
Protected Attributes inherited from DakotaROLEqConstraints | |
Model & | dakotaModel |
Dakota problem data provided by user. | |
bool | haveNlnConst |
Whether or not problem has nonlinear equality constraints. | |
DakotaROLEqConstraintsGrad is derived from DakotaROLEqConstraints. It implements overrides of ROL member functions to provide a Dakota-specific application of the inequality constraint Jacobian to a vector. This separate class is needed to allow for the option of utilizing ROL's finite-differenced gradients
DakotaROLEqConstraintsGrad | ( | Model & | model | ) |
Constructor.
Implementation of the DakotaROLEqConstraintsGrad class.