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MCKL
Monte Carlo Kernel Library
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Sampler for iterative Monte Carlo algorithms. More...
#include <mckl/core/sampler.hpp>
Public Types | |
| using | estimator_type = typename SamplerTrait< Derived >::estimator_type |
| using | eval_type = typename SamplerTrait< Derived >::eval_type |
Public Member Functions | |
| void | clear () |
| Clear all estimator histories. More... | |
| template<typename CharT , typename Traits > | |
| std::basic_ostream< CharT, Traits > & | print (std::basic_ostream< CharT, Traits > &os, char sepchar=' ') const |
| Print the summary matrix in textual form. More... | |
| void | reserve (std::size_t n) |
| Reserve space for additional iterations. More... | |
| void | reset () |
| Remove all evaluation and estimation methods. More... | |
| template<typename T , MatrixLayout Layout> | |
| Matrix< T, Layout > | summary () const |
| Return a combined matrix of all estimates. More... | |
Protected Member Functions | |
| Sampler (std::size_t steps) | |
| Vector< estimator_type > & | estimator (std::size_t step) |
| const Vector< estimator_type > & | estimator (std::size_t step) const |
| template<typename Estimator > | |
| std::size_t | estimator (std::size_t step, Estimator &&estimator, std::enable_if_t<!std::is_integral< Estimator >::value > *=nullptr) |
| estimator_type & | estimator (std::size_t step, std::size_t k) |
| const estimator_type & | estimator (std::size_t step, std::size_t k) const |
| Vector< eval_type > & | eval (std::size_t step) |
| const Vector< eval_type > & | eval (std::size_t step) const |
| template<typename Eval > | |
| std::size_t | eval (std::size_t step, Eval &&eval, std::enable_if_t<!std::is_integral< Eval >::value > *=nullptr) |
| eval_type & | eval (std::size_t step, std::size_t k) |
| const eval_type & | eval (std::size_t step, std::size_t k) const |
Friends | |
| template<typename CharT , typename Traits > | |
| std::basic_ostream< CharT, Traits > & | operator<< (std::basic_ostream< CharT, Traits > &os, const Sampler< Derived > &sampler) |
| Output the summary mtrix through an output stream. More... | |
Sampler for iterative Monte Carlo algorithms.
Definition at line 46 of file sampler.hpp.
| using mckl::Sampler< Derived >::estimator_type = typename SamplerTrait<Derived>::estimator_type |
Definition at line 50 of file sampler.hpp.
| using mckl::Sampler< Derived >::eval_type = typename SamplerTrait<Derived>::eval_type |
Definition at line 49 of file sampler.hpp.
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Definition at line 161 of file sampler.hpp.
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Clear all estimator histories.
Definition at line 74 of file sampler.hpp.
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inlineprotected |
Definition at line 172 of file sampler.hpp.
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inlineprotected |
Definition at line 177 of file sampler.hpp.
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inlineprotected |
Definition at line 202 of file sampler.hpp.
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inlineprotected |
Definition at line 210 of file sampler.hpp.
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inlineprotected |
Definition at line 215 of file sampler.hpp.
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inlineprotected |
Definition at line 165 of file sampler.hpp.
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inlineprotected |
Definition at line 167 of file sampler.hpp.
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inlineprotected |
Definition at line 183 of file sampler.hpp.
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inlineprotected |
Definition at line 191 of file sampler.hpp.
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inlineprotected |
Definition at line 196 of file sampler.hpp.
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inline |
Print the summary matrix in textual form.
| os | The output stream |
| sepchar | The character used to seperate fields |
Definition at line 130 of file sampler.hpp.
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inline |
Reserve space for additional iterations.
Definition at line 53 of file sampler.hpp.
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inline |
Remove all evaluation and estimation methods.
Definition at line 63 of file sampler.hpp.
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Return a combined matrix of all estimates.
Definition at line 85 of file sampler.hpp.
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Output the summary mtrix through an output stream.
Definition at line 154 of file sampler.hpp.
1.8.13