mc::integrators::MontecarloIntegrator< dim > Class Template Reference

Uniform-sampling Monte Carlo integrator for N-dimensional domains. More...

#include <MCintegrator.hpp>

Inheritance diagram for mc::integrators::MontecarloIntegrator< dim >:

Collaboration diagram for mc::integrators::MontecarloIntegrator< dim >:

Public Member Functions
	MontecarloIntegrator (const mc::domains::IntegrationDomain< dim > &d)
	Construct a uniform Monte Carlo integrator for a domain.
double	OLDintegrate (const std::function< double(const mc::geom::Point< dim > &)> &f, int n_samples)
	Legacy integration routine (deprecated).
double	integrate (const std::function< double(const mc::geom::Point< dim > &)> &f, int n_samples, const mc::proposals::Proposal< dim > &proposal, std::uint32_t seed) override
	Compute the integral using uniform Monte Carlo sampling.
Public Member Functions inherited from mc::integrators::Integrator< dim >
	Integrator (const mc::domains::IntegrationDomain< dim > &d)
	Constructs an integrator for a specific domain.
virtual	~Integrator ()=default
	Virtual destructor for proper polymorphic cleanup.

Additional Inherited Members
Protected Member Functions inherited from mc::integrators::Integrator< dim >
std::vector< mc::geom::Point< dim > >	initializeRandomizer (int numbers)
	Initializes random samples uniformly distributed in the domain.
Protected Attributes inherited from mc::integrators::Integrator< dim >
const mc::domains::IntegrationDomain< dim > &	domain
	Reference to the integration domain.
std::vector< std::mt19937 >	randomizer
	Per-thread random number generators.

Detailed Description

template<std::size_t dim>
class mc::integrators::MontecarloIntegrator< dim >

Uniform-sampling Monte Carlo integrator for N-dimensional domains.

Template Parameters

dim	Dimensionality of the integration domain.

Computes the integral: ∫_Ω f(x) dx ≈ V_Ω · (1/N) ∑ᵢ f(xᵢ)

where xᵢ are samples drawn uniformly from the bounding box and f(xᵢ) is zero if xᵢ ∉ Ω (hit-or-miss style).

Modern implementation uses MCMeanEstimator for variance-reduced sampling.

Definition at line 40 of file MCintegrator.hpp.

Constructor & Destructor Documentation

MontecarloIntegrator()

template<std::size_t dim>

mc::integrators::MontecarloIntegrator< dim >::MontecarloIntegrator ( const mc::domains::IntegrationDomain< dim > &  d )

explicit

Construct a uniform Monte Carlo integrator for a domain.

Parameters

d	Reference to the integration domain.

Member Function Documentation

integrate()

template<std::size_t dim>

double mc::integrators::MontecarloIntegrator< dim >::integrate ( const std::function< double(const mc::geom::Point< dim > &)> &  f, int  n_samples, const mc::proposals::Proposal< dim > &  proposal, std::uint32_t  seed  )

overridevirtual

Compute the integral using uniform Monte Carlo sampling.

Parameters

f	Integrand function: ℝⁿ → ℝ.
n_samples	Number of sample points to evaluate.
proposal	Proposal distribution (ignored for uniform MC; for API consistency).
seed	Random seed for reproducibility.

Returns

Estimated value of ∫_Ω f(x) dx.

Uses MCMeanEstimator to compute mean of f over the domain, then multiplies by domain's bounding box volume.

Implements mc::integrators::Integrator< dim >.

OLDintegrate()

template<std::size_t dim>

double mc::integrators::MontecarloIntegrator< dim >::OLDintegrate	(	const std::function< double(const mc::geom::Point< dim > &)> &	f,
		int	n_samples
	)

Legacy integration routine (deprecated).

Deprecated:

Use integrate() instead with proposal and seed.

Parameters

f	Integrand function.
n_samples	Number of sample points.

Returns

Estimated integral value.

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The documentation for this class was generated from the following file:

• src/montecarlo/integrators/MCintegrator.hpp