Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1234]
  details | |
   PolarizationIdentity | |
| ROL | |
| details | |
 VectorClone | |
| VectorCloneMap | |
| VectorWorkspace | |
| VectorKey | |
| VectorStack | |
| DynamicConstraint_CheckInterface | |
| DynamicObjective_CheckInterface | |
| SerialConstraint | |
| MINRES | |
| basic_nullstream | |
| ROL | |
| Constraint_SimOpt | |
| NonlinearLeastSquaresObjective_SimOpt | |
| Constraint_State | |
| Constraint_TimeSimOpt | |
| InteriorPoint | |
| PenalizedObjective | |
| PrimalDualSymmetrizer | |
| PrimalDualResidual | Express the Primal-Dual Interior Point gradient as an equality constraint |
| MeritFunction | |
| StringList | |
| Finite_Difference_Arrays | |
| Exception | |
| NotImplemented | |
| ZOO | |
| Objective_Beale | Beale's function |
| getBeale | |
| Objective_BVP | The discrete boundary value problem |
| getBVP | |
| Objective_Cantilever | |
| Constraint_Cantilever | |
| getCantilever | |
| Objective_CantileverBeam | |
| Constraint_CantileverBeam | |
| getCantileverBeam | |
| Objective_Cubic | |
| Constraint_Cubic | |
| getCubic | |
| Objective_CylinderHead | |
| Constraint_CylinderHead | |
| getCylinderHead | |
| Objective_DiodeCircuit | The diode circuit problem |
| Objective_FreudensteinRoth | Freudenstein and Roth's function |
| getFreudensteinRoth | |
| Objective_HS1 | W. Hock and K. Schittkowski 1st test function |
| getHS1 | |
| Objective_HS2 | W. Hock and K. Schittkowski 2nd test function |
| getHS2 | |
| Objective_HS24 | |
| Constraint_HS24 | |
| getHS24 | |
| Objective_HS25 | W. Hock and K. Schittkowski 25th test function |
| getHS25 | |
| Objective_HS29 | |
| InequalityConstraint_HS29 | |
| getHS29 | |
| Objective_HS3 | W. Hock and K. Schittkowski 3rd test function |
| getHS3 | |
| Objective_HS32 | |
| EqualityConstraint_HS32 | |
| InequalityConstraint_HS32 | |
| getHS32 | |
| Objective_HS38 | W. Hock and K. Schittkowski 38th test function |
| getHS38 | |
| Objective_HS39 | W. Hock and K. Schittkowski 39th test function |
| Constraint_HS39a | |
| Constraint_HS39b | |
| getHS39 | |
| Objective_HS4 | W. Hock and K. Schittkowski 4th test function |
| getHS4 | |
| Objective_HS45 | W. Hock and K. Schittkowski 45th test function |
| getHS45 | |
| Objective_HS5 | W. Hock and K. Schittkowski 5th test function |
| getHS5 | |
| Objective_LeastSquares | Least squares function |
| getLeastSquares | |
| Minimax1 | |
| getMinimax1 | |
| Minimax2 | |
| getMinimax2 | |
| Minimax3 | |
| getMinimax3 | |
| Objective_ParaboloidCircle | Objective function: f(x,y) = x^2 + y^2 |
| Constraint_ParaboloidCircle | Constraint c(x,y) = (x-2)^2 + y^2 - 1 |
| getParaboloidCircle | |
| Objective_PoissonControl | Poisson distributed control |
| getPoissonControl | |
| Objective_PoissonInversion | Poisson material inversion |
| getPoissonInversion | |
| Objective_Powell | Powell's badly scaled function |
| getPowell | |
| Objective_Quartic | |
| Constraint_Quartic | |
| getQuartic | |
| Objective_Rosenbrock | Rosenbrock's function |
| getRosenbrock | |
| Objective_SimpleEqConstrained | Objective function: f(x) = exp(x1*x2*x3*x4*x5) + 0.5*(x1^3+x2^3+1)^2 |
| EqualityConstraint_SimpleEqConstrained | Equality constraints c_i(x) = 0, where: c1(x) = x1^2+x2^2+x3^2+x4^2+x5^2 - 10 c2(x) = x2*x3-5*x4*x5 c3(x) = x1^3 + x2^3 + 1 |
| getSimpleEqConstrained | |
| Objective_SumOfSquares | Sum of squares function |
| getSumOfSquares | |
| Objective_Zakharov | Zakharov function |
| getZakharov | |
| ElementwiseVector | Intermediate abstract class which does not require users implements plus, set, scale, axpy, norm, dot, or zero if they implement the three elementwise functions: applyUnary, applyBinary, and reduce |
| InactiveSet_PrimalVector | Defines the a Vector which has a diagonally scaled dot product that neglects active set elements Used to simplify Semi-smooth Newton method implementation |
| InactiveSet_DualVector | Defines the a Vector which has a diagonally scaled dot product that neglects active set elements Used to simplify Semi-smooth Newton method implementation |
| PartitionedVector | Defines the linear algebra of vector space on a generic partitioned vector |
| VectorFunctionCalls | |
| ProfiledVector | By keeping a pointer to this in a derived Vector class, a tally of all methods is kept for profiling function calls |
| RieszPrimalVector | |
| RieszDualVector | |
| PrimalScaledStdVector | Provides the std::vector implementation of the ROL::Vector interface that handles scalings in the inner product. Also see ROL::DualScaledStdVector |
| DualScaledStdVector | Provides the std::vector implementation of the ROL::Vector interface that handles scalings in the inner product. Also see ROL::PrimalScaledStdVector |
| PrimalScaledVector | Provides the implementation of the ROL::Vector interface that handles scalings in the inner product. A more generic version of ROL::PrimalScaledStdVector |
| DualScaledVector | Provides the implementation of the ROL::Vector interface that handles scalings in the inner product. A more generic version of ROL::PrimalScaledStdVector |
| SingletonVector | |
| StdVector | Provides the ROL::Vector interface for scalar values, to be used, for example, with scalar constraints |
| Vector | Defines the linear algebra or vector space interface |
| Vector_SimOpt | Defines the linear algebra or vector space interface for simulation-based optimization |
| BoundConstraint | Provides the interface to apply upper and lower bound constraints |
| BoundConstraint_Partitioned | A composite composite BoundConstraint formed from bound constraints on subvectors of a PartitionedVector |
| Bounds | Provides the elementwise interface to apply upper and lower bound constraints |
| Active | |
| LowerBinding | |
| PruneBinding | |
| UpperBinding | |
| BinaryConstraint | Implements an equality constraint function that evaluates to zero on the surface of a bounded parallelpiped and is positive in the interior |
| BoundsCheck | |
| BoundToConstraint | Provides an implementation for bound constraints |
| Constraint | Defines the general constraint operator interface |
| Constraint_Partitioned | Has both inequality and equality constraints. Treat inequality constraint as equality with slack variable |
| ConstraintFromObjective | Creates a constraint from an objective function and a offset value |
| LinearConstraint | Provides the interface to evaluate linear constraints |
| LowerBoundToConstraint | Provides an implementation for lower bound constraints |
| ScalarLinearConstraint | This equality constraint defines an affine hyperplane |
| UpperBoundToConstraint | Provides an implementation for upper bound constraints |
| Constraint_DynamicState | |
| DynamicConstraint | Defines the time-dependent constraint operator interface for simulation-based optimization |
| DynamicConstraintCheck | |
| DynamicFunction | Provides update interface, casting and vector management to DynamicConstraint and DynamicObjective |
| DynamicObjective | Defines the time-dependent objective function interface for simulation-based optimization. Computes time-local contributions of value, gradient, Hessian-vector product etc to a larger composite objective defined over the simulation time. In contrast to other objective classes Objective_TimeSimOpt has a default implementation of value which returns zero, as time-dependent simulation based optimization problems may have an objective value which depends only on the final state of the system |
| DynamicObjectiveCheck | |
| DynamicTrackingObjective | Defines the time-local contribution to a quadratic tracking objective |
| NonlinearLeastSquaresObjective_Dynamic | Provides the interface to evaluate nonlinear least squares objective functions |
| ReducedDynamicObjective | Defines the reduced time-dependent objective function interface for simulation-based optimization |
| TimeStamp | Contains local time step information |
| NonlinearLeastSquaresObjective | Provides the interface to evaluate nonlinear least squares objective functions |
| Objective_FSsolver | |
| CompositeObjective | Provides the interface to evaluate composite objective functions |
| LinearCombinationObjective | |
| LinearObjective | Provides the interface to evaluate linear objective functions |
| Objective | Provides the interface to evaluate objective functions |
| ObjectiveFromConstraint | Form an objective function from a ROL::Constraint and a vector in the dual constraint space \(\lambda\in \mathcal{C}^\ast\) |
| QuadraticObjective | Provides the interface to evaluate quadratic objective functions |
| SlacklessObjective | This class strips out the slack variables from objective evaluations to create the new objective \( F(x,s) = f(x) \) |
| BlockOperator | Provides the interface to apply a block operator to a partitioned vector |
| BlockOperator2 | Provides the interface to apply a 2x2 block operator to a partitioned vector |
| BlockOperator2Determinant | Provides the interface to the block determinant of a 2x2 block operator |
| BlockOperator2Diagonal | Provides the interface to apply a 2x2 block diagonal operator to a partitioned vector |
| BlockOperator2UnitLower | Provides the interface to apply a 2x2 block unit lower operator to a partitioned vector |
| BlockOperator2UnitUpper | Provides the interface to apply a 2x2 block unit upper operator to a partitioned vector |
| DiagonalOperator | Provides the interface to apply a diagonal operator which acts like elementwise multiplication when apply() is used and elementwise division when applyInverse() is used |
| DyadicOperator | Interface to apply a dyadic operator to a vector |
| HouseholderReflector | Provides the interface to create a Householder reflector operator, that when applied to a vector x, produces a vector parallel to y |
| IdentityOperator | Multiplication by unity |
| LinearOperator | Provides the interface to apply a linear operator |
| LinearOperatorFromConstraint | A simple wrapper which allows application of constraint Jacobians through the LinearOperator interface |
| LinearOperatorProduct | Provides the interface to the sequential application of linear operators. |
| LinearOperatorSum | Provides the interface to sum of linear operators applied to a vector |
| NullOperator | Multiplication by zero |
| SchurComplement | Given a 2x2 block operator, perform the Schur reduction and return the decoupled system components |
| ConstraintManager | Provides a wrapper for multiple constraints |
| ObjectiveMMA | Provides the interface to to Method of Moving Asymptotes Objective function |
| SimController | |
| BoundConstraint_SimOpt | |
| CompositeConstraint_SimOpt | Defines a composite equality constraint operator interface for simulation-based optimization |
| CompositeObjective_SimOpt | Provides the interface to evaluate simulation-based composite objective functions |
| Constraint_SerialSimOpt | Unifies the constraint defined on a single time step that are defined through the Constraint_TimeSimOpt interface into a SimOpt constraint for all time. Primarily intended for use in testing the parallel-in-time implementation |
| Constraint_SimOpt | Defines the constraint operator interface for simulation-based optimization |
| Constraint_State | |
| Constraint_TimeSimOpt | Defines the time dependent constraint operator interface for simulation-based optimization |
| LinearCombinationObjective_SimOpt | |
| NonlinearLeastSquaresObjective_SimOpt | Provides the interface to evaluate nonlinear least squares objective functions |
| Objective_SerialSimOpt | |
| Objective_SimOpt | Provides the interface to evaluate simulation-based objective functions |
| Objective_TimeSimOpt | Defines the time-dependent objective function interface for simulation-based optimization. Computes time-local contributions of value, gradient, Hessian-vector product etc to a larger composite objective defined over the simulation time. In contrast to other objective classes Objective_TimeSimOpt has a default implementation of value which returns zero, as time-dependent simulation based optimization problems may have an objective value which depends only on the final state of the system |
| Reduced_Constraint_SimOpt | |
| Reduced_Objective_SimOpt | |
| Sketch | Provides an interface for randomized sketching |
| StdBoundConstraint | |
| StdConstraint | Defines the equality constraint operator interface for StdVectors |
| StdLinearOperator | Provides the std::vector implementation to apply a linear operator, which is a std::vector representation of column-stacked matrix |
| StdObjective | Specializes the ROL::Objective interface for objective functions that operate on ROL::StdVector's |
| StdTridiagonalOperator | Provides the std::vector implementation to apply a linear operator, which encapsulates a tridiagonal matrix |
| StepFactory | |
| StatusTestFactory | |
| Algorithm | Provides an interface to run optimization algorithms |
| OptimizationProblem | |
| OptimizationSolver | Provides a simplified interface for solving a wide range of optimization problems |
| BundleStatusTest | |
| CombinedStatusTest | Provides an interface to check two status tests of optimization algorithms |
| ConstraintStatusTest | Provides an interface to check status of optimization algorithms for problems with equality constraints |
| FletcherStatusTest | Provides an interface to check status of optimization algorithms for problems with equality constraints |
| StatusTest | Provides an interface to check status of optimization algorithms |
| AugmentedLagrangian | Provides the interface to evaluate the augmented Lagrangian |
| AugmentedLagrangian_SimOpt | Provides the interface to evaluate the SimOpt augmented Lagrangian |
| QuadraticPenalty | Provides the interface to evaluate the quadratic constraint penalty |
| QuadraticPenalty_SimOpt | Provides the interface to evaluate the quadratic SimOpt constraint penalty |
| Reduced_AugmentedLagrangian_SimOpt | Provides the interface to evaluate the reduced SimOpt augmented Lagrangian |
| Bundle | Provides the interface for and implements a bundle |
| Bundle_AS | Provides the interface for and implements an active set bundle |
| Bundle_TT | Provides the interface for and implements a bundle. The semidefinite quadratic subproblem is solved using TT algorithm by Antonio Frangioni (1996) |
| BoundFletcher | |
| AugSystemNonSym | |
| AugSystemPrecond | |
| AugSystemSym | |
| DiffLower | |
| DiffUpper | |
| FormDQ | |
| FormQ | |
| Fletcher | |
| AugSystem | |
| AugSystemPrecond | |
| FletcherBase | |
| InteriorPointPenalty | Provides the interface to evaluate the Interior Pointy log barrier penalty function with upper and lower bounds on some elements |
| Mask | |
| ModifiedDivide | |
| ModifiedLogarithm | |
| ModifiedReciprocal | |
| LogBarrierObjective | Log barrier objective for interior point methods |
| ObjectiveFromBoundConstraint | Create a penalty objective from upper and lower bound vectors |
| PrimalDualInteriorPointBlock11 | |
| PrimalDualInteriorPointBlock12 | |
| PrimalDualInteriorPointBlock21 | |
| PrimalDualInteriorPointBlock22 | |
| PrimalDualInteriorPointResidual | Symmetrized form of the KKT operator for the Type-EB problem with equality and bound multipliers |
| InFill | |
| SafeDivide | |
| SetZeros | |
| PrimalDualSystemStep | Provides the interface to compute approximate solutions to 2x2 block systems arising from primal-dual interior point methods |
| ConjugateGradients | Provides definitions of the Conjugate Gradient solver |
| ConjugateResiduals | Provides definition of the Conjugate Residual solver |
| GMRES | Preconditioned GMRES solver |
| Krylov | Provides definitions for Krylov solvers |
| Lanczos | Interface for computing the Lanczos vectors and approximate solutions to symmetric indefinite linear systems |
| BackTracking | Implements a simple back tracking line search |
| Bisection | Implements a bisection line search |
| Brents | Implements a Brent's method line search |
| testFunction | |
| CubicInterp | Implements cubic interpolation back tracking line search |
| GoldenSection | Implements a golden section line search |
| IterationScaling | Provides an implementation of iteration scaled line search |
| LineSearch | Provides interface for and implements line searches |
| PathBasedTargetLevel | Provides an implementation of path-based target leve line search |
| ScalarMinimizationLineSearch | Implements line search methods that attempt to minimize the scalar function \(\phi(t) := f(x+ts)\) |
| LineSearchStatusTest | |
| Phi | |
| MoreauYosidaPenalty | Provides the interface to evaluate the Moreau-Yosida penalty function |
| AugmentedLagrangianStep | Provides the interface to compute augmented Lagrangian steps |
| BundleStep | Provides the interface to compute bundle trust-region steps |
| CompositeStep | Implements the computation of optimization steps with composite-step trust-region methods |
| FletcherStep | Provides the interface to compute Fletcher steps |
| GradientStep | Provides the interface to compute optimization steps with the gradient descent method globalized using line search |
| InteriorPointStep | |
| LineSearchStep | Provides the interface to compute optimization steps with line search |
| MoreauYosidaPenaltyStep | Implements the computation of optimization steps using Moreau-Yosida regularized bound constraints |
| NewtonKrylovStep | Provides the interface to compute optimization steps with projected inexact Newton's method using line search |
| HessianNK | |
| PrecondNK | |
| NewtonStep | Provides the interface to compute optimization steps with Newton's method globalized using line search |
| NonlinearCGStep | Provides the interface to compute optimization steps with nonlinear CG |
| PrimalDualActiveSetStep | Implements the computation of optimization steps with the Newton primal-dual active set method |
| HessianPD | |
| PrecondPD | |
| ProjectedNewtonKrylovStep | Provides the interface to compute optimization steps with projected inexact ProjectedNewton's method using line search |
| HessianPNK | |
| PrecondPNK | |
| ProjectedNewtonStep | Provides the interface to compute optimization steps with projected Newton's method using line search |
| ProjectedSecantStep | Provides the interface to compute optimization steps with projected secant method using line search |
| SecantStep | Provides the interface to compute optimization steps with a secant method |
| Step | Provides the interface to compute optimization steps |
| TrustRegionStep | Provides the interface to compute optimization steps with trust regions |
| BarzilaiBorwein | Provides definitions for Barzilai-Borwein operators |
| lBFGS | Provides definitions for limited-memory BFGS operators |
| lDFP | Provides definitions for limited-memory DFP operators |
| lSR1 | Provides definitions for limited-memory SR1 operators |
| SecantState | |
| Secant | Provides interface for and implements limited-memory secant operators |
| CauchyPoint | Provides interface for the Cauchy point trust-region subproblem solver |
| ColemanLiModel | Provides the interface to evaluate interior trust-region model functions from the Coleman-Li bound constrained trust-region algorithm |
| ConicApproximationModel | |
| DogLeg | Provides interface for dog leg trust-region subproblem solver |
| DoubleDogLeg | Provides interface for the double dog leg trust-region subproblem solver |
| KelleySachsModel | Provides the interface to evaluate projected trust-region model functions from the Kelley-Sachs bound constrained trust-region algorithm |
| LowerBinding | |
| PruneBinding | |
| PruneNonbinding | |
| UpperBinding | |
| LinMore | Provides interface for truncated CG trust-region subproblem solver |
| LowerBreakPoint | |
| PositiveMax | |
| PositiveMin | |
| UpperBreakPoint | |
| LinMoreModel | Provides the interface to evaluate projected trust-region model functions from the Kelley-Sachs bound constrained trust-region algorithm |
| TruncatedCG | Provides interface for truncated CG trust-region subproblem solver |
| TrustRegion | Provides interface for and implements trust-region subproblem solvers |
| TrustRegionModel | Provides the interface to evaluate trust-region model functions |
| LinearRegression | Provides the interface to construct linear regression problem |
| ProgressiveHedging | Provides the interface to solve a stochastic program using progressive hedging |
| Arcsine | |
| Beta | |
| Cauchy | |
| Dirac | |
| Distribution | |
| Exponential | |
| Gamma | |
| Gaussian | |
| Gumbel | |
| Kumaraswamy | |
| Laplace | |
| Logistic | |
| Parabolic | |
| RaisedCosine | |
| Smale | |
| Triangle | |
| TruncatedExponential | |
| TruncatedGaussian | |
| Uniform | |
| ExpectationQuad | Provides a general interface for risk and error measures generated through the expectation risk quadrangle |
| GenMoreauYosidaCVaR | |
| LogExponentialQuadrangle | Provides an interface for the entropic risk using the expectation risk quadrangle |
| LogQuantileQuadrangle | Provides an interface for the conditioanl entropic risk using the expectation risk quadrangle |
| MeanVarianceQuadrangle | Provides an interface for the mean plus variance risk measure using the expectation risk quadrangle |
| MoreauYosidaCVaR | Provides an interface for a smooth approximation of the conditional value-at-risk |
| QuantileQuadrangle | Provides an interface for a convex combination of the expected value and the conditional value-at-risk using the expectation risk quadrangle |
| SmoothedWorstCaseQuadrangle | Provides an interface for a smoothed version of the worst-case scenario risk measure using the expectation risk quadrangle |
| TruncatedMeanQuadrangle | |
| PH_bPOEObjective | Provides the interface for the progressive hedging probability objective |
| PH_DeviationObjective | Provides the interface for the progressive hedging deviation objective |
| PH_ErrorObjective | Provides the interface for the progressive hedging error objective |
| PH_Objective | Provides the interface for the progressive hedging objective |
| PH_ProbObjective | Provides the interface for the progressive hedging probability objective |
| PH_RegretObjective | Provides the interface for the progressive hedging regret objective |
| PH_RiskObjective | Provides the interface for the progressive hedging risk objective |
| ExpectationQuadDeviation | |
| ExpectationQuadError | Provides a general interface for error measures generated through the expectation risk quadrangle |
| BPOE | Provides the implementation of the buffered probability of exceedance |
| SmoothedPOE | Provides the implementation of the smoothed probability of exceedance |
| ExpectationQuadRegret | Provides a general interface for regret measures generated through the expectation risk quadrangle |
| Chi2Divergence | Provides an interface for the chi-squared-divergence distributionally robust expectation |
| FDivergence | Provides a general interface for the F-divergence distributionally robust expectation |
| CoherentEntropicRisk | Provides the interface for the coherent entropic risk measure |
| ConvexCombinationRiskMeasure | Provides an interface for a convex combination of risk measures |
| CVaR | Provides an interface for a convex combination of the expected value and the conditional value-at-risk |
| EntropicRisk | Provides an interface for the entropic risk |
| ExpectationQuadRisk | |
| HMCR | Provides an interface for a convex combination of the expected value and the higher moment coherent risk measure |
| KLDivergence | Provides an interface for the Kullback-Leibler distributionally robust expectation |
| MeanDeviation | Provides an interface for the mean plus a sum of arbitrary order deviations |
| MeanDeviationFromTarget | Provides an interface for the mean plus a sum of arbitrary order deviations from targets |
| MeanSemiDeviation | Provides an interface for the mean plus upper semideviation of order 1 |
| MeanSemiDeviationFromTarget | |
| MeanVariance | Provides an interface for the mean plus a sum of arbitrary order variances |
| MeanVarianceFromTarget | Provides an interface for the mean plus a sum of arbitrary order variances from targets |
| MixedCVaR | Provides an interface for a convex combination of conditional value-at-risks |
| QuantileRadius | |
| ChebyshevSpectral | Provides an interface for the Chebyshev-Spectral risk measure |
| SecondOrderCVaR | Provides an interface for the risk measure associated with the super quantile quadrangle |
| SpectralRisk | Provides an interface for spectral risk measures |
| RandVarFunctional | Provides the interface to implement any functional that maps a random variable to a (extended) real number |
| SampledScalar | |
| SampledVector | |
| StochasticConstraint | |
| StochasticObjective | |
| AbsoluteValue | |
| AlmostSureConstraint | |
| PlusFunction | |
| PositiveFunction | |
| RegressionError | Provides the interface to evaluate linear regression error |
| RiskBoundConstraint | |
| RiskLessConstraint | |
| RiskLessObjective | |
| RiskMeasure | Provides the interface to implement risk measures |
| RiskNeutralConstraint | |
| RiskNeutralObjective | |
| SimulatedBoundConstraint | A BoundConstraint formed from a single bound constraint replacated according to a SampleGenerator |
| SimulatedConstraint | |
| SimulatedObjective | |
| SimulatedObjectiveCVaR | |
| BatchManager | |
| MonteCarloGenerator | |
| SampleGenerator | |
| SROMGenerator | |
| UserInputGenerator | |
| PrimalAtomVector | |
| DualAtomVector | |
| AtomVector | Provides the std::vector implementation of the ROL::Vector interface |
| BatchStdVector | Provides the std::vector implementation of the ROL::Vector interface |
| CDFObjective | |
| MomentObjective | |
| PointwiseCDFObjective | |
| PrimalProbabilityVector | |
| DualProbabilityVector | |
| ProbabilityVector | Provides the std::vector implementation of the ROL::Vector interface |
| SROMVector | Provides the std::vector implementation of the ROL::Vector interface |
| PH_StatusTest | Provides an interface to check status of the progressive hedging algorithm |
| RiskVector | |
| PrimalSimulatedVector | |
| DualSimulatedVector | |
| SimulatedVector | Defines the linear algebra of a vector space on a generic partitioned vector where the individual vectors are distributed in batches defined by ROL::BatchManager. This is a batch-distributed version of ROL::PartitionedVector |
| ProjectedObjective | |
| ScalarTraits_Magnitude | |
| ScalarTraits_Magnitude< std::complex< Real > > | |
| ScalarTraits | |
| AlgorithmState | State for algorithm class. Will be used for restarts |
| StepState | State for step class. Will be used for restarts |
| removeSpecialCharacters | |
| TypeCaster | |
| TypeCaster< Real, std::complex< Real > > | |
| TypeCaster< double, float > | |
| TestProblem | |
| VectorClone | Container for wrapping a reusable cloned vector. Declaring an object of this type as a class member variable will decrease the number of clones needed as memory need only be allocated once in the lifetime of the host object. Verifies that member and argument types and dimensions agree when called |
| VectorCloneMap | Container for wrapping a collection of uniquely-named reusable cloned vectors, which in are stored in a map. Uses string-valued ids for keys by default |
| VectorWorkspace | Provides a "smart" cloning manager to be used a member variable in a class and called in the member function of the same class |
| WrappedVector | Provides an interface layer which encapulates a pointer to a ROL::Vector and has the default behavior of calling its member Ptr<Vector> object. Makes creating derived classes with this idiom simpler as they need only override the methods where the desired implementation differs from the member Ptr<Vector>. For example, vectors which have a diagonal scaling that defines their inner product and dual spaces can derive from this class need overload only the methods basis, clone, dual, and dot |
| SerialConstraint | Evaluates ROL::DynamicConstraint over a sequential set of time intervals |
| StdLinearOperatorFactory | Creates StdLinearOperator objects which wrap random
matrices of the desired size and property |
| PenalizedObjective | Adds barrier term to generic objective |
| PrimalDualInteriorPointReducedResidual | Reduced form of the Primal Dual Interior Point residual and the action of its Jacobian |
| MINRES | Implements the MINRES algorithm for solving symmetric indefinite systems |
| SemismoothNewtonDualModel | Implements the dual variable model function for a semismooth Newton step |
| BoundConstraint_BurgersControl | |
| BurgersFEM | |
| CLExactModel | |
| CLTestObjective | |
| ConDualStdVector | |
| ConicApproximationModel | Provides the interface to evaluate conic approximation function |
| ConStdVector | |
| Constraint_BurgersControl | |
| DiffusionConstraint | |
| DiffusionObjective | |
| Example_Objective | Objective function:
\[f(x) = exp(x_1 x_2 x_3 x_4 x_5) + \frac{1}{2}*(x_1^3+x_2^3+1)^2 \] |
| FEM | |
| FiniteDifference | |
| FunctionZakharov | |
| H1BoundConstraint | |
| H1VectorBatchManager | |
| H1VectorDual | |
| H1VectorPrimal | |
| Identity | |
| IdentityOperator | |
| InnerProductMatrix | |
| InnerProductMatrixSolver | This class adds a solve method |
| L2BoundConstraint | |
| L2VectorBatchManager | |
| L2VectorDual | |
| L2VectorPrimal | |
| Lagrange | |
| NodalBasis | |
| Normalization_Constraint | |
| NullObjective | |
| Objective_BurgersControl | |
| Objective_GrossPitaevskii | |
| Objective_PoissonInversion | |
| ObjectiveFunctionTest06 | |
| ObjectiveFunctionTest07_1 | |
| ObjectiveFunctionTest07_2 | |
| ObjectiveFunctionTest07_scalarize | |
| ObjectiveFunctionTest08_1 | |
| ObjectiveFunctionTest08_2 | |
| ObjectiveFunctionTest08_scalarize | |
| OptDualStdVector | |
| OptStdVector | |
| redConstraint | |
| StatusTest_PDAS | |
| TestMulti | |
| TestSingle | |
| TridiagonalToeplitzOperator | |
| valConstraint | |
| Zakharov | |
| Zakharov_Sacado_Objective |
