Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
roboptim::detail::add_shared_ptr< CLIST >Transform a types list into a types list of shared pointers
roboptim::detail::AutopromoteTrait< T >
roboptim::detail::AutopromoteTrait< Minus< U, V > >
roboptim::detail::AutopromoteTrait< Plus< U, V > >
roboptim::detail::AutopromoteTrait< Product< U, V > >
roboptim::detail::AutopromoteTrait< Scalar< U > >
roboptim::BadGradient< T >Exception thrown when a gradient check fails
roboptim::BadJacobian< T >Exception thrown when a Jacobian check fails
roboptim::Bind< U >Bind some function input to a constant value
roboptim::CachedFunction< T >Store previous function computation
roboptim::detail::cast_constraint_type< C, CLIST >Get the constraint type of CLIST that best match C
roboptim::Chain< U, V >Chain two RobOptim functions
roboptim::detail::check_constraint_type< C, CLIST >Checks whether C is a valid constraint type in CLIST
roboptim::visualization::gnuplot::CommandGnuplot command
roboptim::visualization::matplotlib::CommandMatplotlib command
roboptim::Concatenate< U >Concatenate the output of two functions
roboptim::detail::contains_base_of< Sequence, Type >Whether a sequence of types contains a base of a given type
roboptim::detail::ConvertConstraint< CLIST >Convert a constraint to a proper type
roboptim::detail::ConvertConstraintVariant< P >Convert a constraint from a Boost.Variant to an adequate constraint type depending on the problem's constraints type
roboptim::Cos< T >Cos function
roboptim::DerivableParametrizedFunction< F >Parametrized function with parameter derivative available
roboptim::Derivative< U >Return the derivative of a function w.r.t
roboptim::derivativeSize< GenericDifferentiableFunction< T > >
roboptim::derivativeSize< GenericFunction< T > >
roboptim::derivativeSize< GenericTwiceDifferentiableFunction< T > >
roboptim::derivativeSize< NTimesDerivableFunction< N > >
roboptim::detail::derives_from_function< F >Checks whether the function types derives from Function or SparseFunction
roboptim::DummySolverDummy solver which always fails
roboptim::DummySolverTdDummy solver which always fails
roboptim::EigenMatrixDenseTag type for functions using Eigen dense matrices
roboptim::EigenMatrixSparseTag type for functions using Eigen sparse matrices
roboptim::detail::EvaluateConstraint< P >
roboptim::detail::EvaluateConstraintViolation< P >
roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >Precise finite difference gradient computation
roboptim::FunctionPool< F, FLIST >A pool of functions that will be processed together
roboptim::GenericConstantFunction< T >Constant function
roboptim::GenericDifferentiableFunction< T >Define an abstract derivable function ( $C^1$)
roboptim::GenericDummySolverLastState< F >Dummy solver which always fails, but returns the last state of the solver
roboptim::GenericFiniteDifferenceGradient< T, FdgPolicy >Compute automatically a gradient with finite differences
roboptim::GenericFunction< T >Define an abstract mathematical function ( $C^0$)
roboptim::GenericFunctionTraits< T >GenericFunction traits
roboptim::GenericFunctionTraits< EigenMatrixDense >Trait specializing GenericFunction for Eigen dense matrices
roboptim::GenericFunctionTraits< EigenMatrixSparse >Trait specializing GenericFunction for Eigen sparse matrices
roboptim::GenericIdentityFunction< T >Identity function
roboptim::GenericLinearFunction< T >Define an abstract linear function
roboptim::GenericNumericLinearFunction< T >Build a linear function from a vector and a matrix
roboptim::GenericNumericQuadraticFunction< T >Build a quadratic function from a matrix and a vector
roboptim::GenericQuadraticFunction< T >Define an abstract quadratic function
roboptim::GenericSolverAbstract interface satisfied by all solvers
roboptim::GenericSumOfC1Squares< T >Generic sum of the squares of differentiable functions
roboptim::GenericTwiceDifferentiableFunction< T >Define an abstract function which is twice-derivable ( $C^2$)
roboptim::detail::get_descendant< Type1, Type2 >Get the descendant among two relatives
roboptim::visualization::GnuplotGnuplot script
roboptim::visualization::matplotlib::ImportMatplotlib import
roboptim::detail::list_converter< CLIST >Converts CLIST to a boost::mpl::vector to ensure a similar behavior for codes using different random access sequences (vector, list, etc.)
roboptim::detail::list_derives_from_function< CLIST >Checks whether all the constraints derive from Function or SparseFunction
roboptim::detail::LogJacobianConstraint< P >
roboptim::LRUCache< K, V >LRU (Least Recently Used) cache
roboptim::Map< U >Apply a function several times to an input vector
roboptim::visualization::MatplotlibMatplotlib script
roboptim::Minus< U, V >Subtract two RobOptim functions
roboptim::callback::Multiplexer< S >Callback multiplexer
roboptim::NoSolutionTag a result if no solution has been found
roboptim::NTimesDerivableFunction< DerivabilityOrder >Define a $\mathbb{R} \rightarrow \mathbb{R}^m$ function, derivable n times ( $n \geq 2$)
roboptim::NTimesDerivableFunction< 2 >Explicit specialization for the stop case of NTimesDerivable class
roboptim::OptimizationLogger< T >Log the optimization process (values, Jacobians, time taken etc.)
roboptim::ParameterParameters type
roboptim::ParametrizedFunction< F >Define an abstract parametrized mathematical function ( $C^0$)
roboptim::Plus< U, V >Sum two RobOptim functions
roboptim::finiteDifferenceGradientPolicies::Policy< T >Interface for the finite difference gradient policies
roboptim::Polynomial< T >Polynomial function
roboptim::detail::PrecisionTrait< T >
roboptim::detail::printConstraint< P >
roboptim::Problem< F, CLIST >
roboptim::Problem< F, boost::mpl::vector<> >
roboptim::Product< U, V >Product of two RobOptim functions
roboptim::detail::ProductDifferentiationUtility structure used for product differentiation
roboptim::detail::promote2< T1, T2, promoteToT1 >
roboptim::detail::promote2< T1, T2, 0 >
roboptim::detail::PromoteTrait< T1_orig, T2_orig >
roboptim::ResultRepresents the solution of an optimization problem
roboptim::ResultWithWarningsRepresents the solution of an optimization problem when errors occurred during the solving process
roboptim::Scalar< U >Multiply by a constant scalar value
roboptim::Selection< U >Select a block of a function's output
roboptim::SelectionById< U >Select part of a function
roboptim::detail::shared_ptr_variant< CLIST >Generate a Boost.Variant of shared pointers from the static constraints types list
roboptim::finiteDifferenceGradientPolicies::Simple< T >Fast finite difference gradient computation
roboptim::Sin< T >Sin function
roboptim::Solver< F, C >Solver for a specific problem class
roboptim::SolverErrorBase exception class for solving errors
roboptim::SolverFactory< T >Define a solver factory that instanciate the plug-ins
roboptim::SolverState< P >State of the solver
roboptim::SolverWarningException used for non-critical errors during optimization
roboptim::Split< T >Select an element of a function's output
roboptim::StateParameter< F >Solver state parameters type
roboptim::detail::StateParameterPrintVisitorVisitor used to print state parameters (variant)
roboptim::detail::ProductDifferentiation::Types< U, V >Some useful types for product differentiation
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