DiffEq - Modern C++ ODE Integration Library 1.0.0
High-performance C++ library for solving ODEs with async signal processing
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SRA (Stochastic Runge-Kutta for additive noise SDEs) integrator. More...
#include <sra.hpp>
Public Types | |
using | base_type = sde::AbstractSDEIntegrator< StateType > |
using | state_type = typename base_type::state_type |
using | time_type = typename base_type::time_type |
using | value_type = typename base_type::value_type |
using | tableau_type = SRATableau< value_type > |
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using | state_type = StateType |
using | time_type = typename StateType::value_type |
using | value_type = typename StateType::value_type |
using | sde_problem_type = SDEProblem< StateType > |
using | wiener_process_type = WienerProcess< StateType > |
Public Member Functions | |
SRAIntegrator (std::shared_ptr< typename base_type::sde_problem_type > problem, std::shared_ptr< typename base_type::wiener_process_type > wiener=nullptr, tableau_type tableau=SRAIntegrator::create_sra1_tableau()) | |
void | step (state_type &state, time_type dt) override |
std::string | name () const override |
void | set_tableau (const tableau_type &tableau) |
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AbstractSDEIntegrator (std::shared_ptr< sde_problem_type > problem, std::shared_ptr< wiener_process_type > wiener=nullptr) | |
void | integrate (state_type &state, time_type dt, time_type end_time) |
time_type | current_time () const |
void | set_time (time_type t) |
std::shared_ptr< sde_problem_type > | get_problem () const |
std::shared_ptr< wiener_process_type > | get_wiener_process () const |
void | set_wiener_process (std::shared_ptr< wiener_process_type > wiener) |
Additional Inherited Members | |
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void | advance_time (time_type dt) |
virtual size_t | get_default_dimension () |
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std::shared_ptr< sde_problem_type > | problem_ |
std::shared_ptr< wiener_process_type > | wiener_ |
time_type | current_time_ |
SRA (Stochastic Runge-Kutta for additive noise SDEs) integrator.
Implements the SRA family of methods for additive noise SDEs: dX = f(t, X) dt + g(t, X) dW
Strong order: 1.5 Weak order: 2.0
Reference: Rößler A., Runge–Kutta Methods for the Strong Approximation of Solutions of Stochastic Differential Equations, SIAM J. Numer. Anal., 48 (3), pp. 922–952. DOI:10.1137/09076636X
using diffeq::SRAIntegrator< StateType >::base_type = sde::AbstractSDEIntegrator<StateType> |
using diffeq::SRAIntegrator< StateType >::state_type = typename base_type::state_type |
using diffeq::SRAIntegrator< StateType >::tableau_type = SRATableau<value_type> |
using diffeq::SRAIntegrator< StateType >::time_type = typename base_type::time_type |
using diffeq::SRAIntegrator< StateType >::value_type = typename base_type::value_type |
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inlineexplicit |
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inlineoverridevirtual |
Implements diffeq::sde::AbstractSDEIntegrator< StateType >.
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inline |
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inlineoverridevirtual |
Implements diffeq::sde::AbstractSDEIntegrator< StateType >.