A class for inverse transform sampling. More...

#include <InverseTransformSampling.h>

Collaboration diagram for ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >:

Classes
struct	fill_random
	Functor that is used for generating samples. More...

Public Types
using	view_type = typename ippl::detail::ViewType< Vector< T, Dim >, 1 >::view_type

using	size_type = ippl::detail::size_type

Public Member Functions
template<class RegionLayout >
	InverseTransformSampling (Distribution &dist_r, Vector< T, Dim > &rmax_r, Vector< T, Dim > &rmin_r, RegionLayout &rlayout_r, size_type &ntotal_r)
	Constructor for InverseTransformSampling class with domain decomposition.

	InverseTransformSampling (Distribution &dist_r, Vector< T, Dim > &rmax_r, Vector< T, Dim > &rmin_r, Vector< T, Dim > &locrmax_r, Vector< T, Dim > &locrmin_r, size_type &ntotal_r)
	Constructor for InverseTransformSampling class without applying domain decomposition..

	InverseTransformSampling (Distribution &dist_r, Vector< T, Dim > &rmax_r, Vector< T, Dim > &rmin_r, size_type &ntotal_r)
	Constructor for InverseTransformSampling class. In this method, we do not consider any domain decomposition.

void	updateBounds (Vector< T, Dim > &rmax, Vector< T, Dim > &rmin, Vector< T, Dim > &locrmax, Vector< T, Dim > &locrmin)
	Updates the sampling bounds and reinitializes internal variables.

void	updateBounds (Vector< T, Dim > &rmax, Vector< T, Dim > &rmin)
	Updates the sampling bounds using the CDF without any domain decomposition.

	~InverseTransformSampling ()
	Deconstructor for InverseTransformSampling class.

KOKKOS_INLINE_FUNCTION size_type	getLocalSamplesNum () const
	Get the local number of samples.

KOKKOS_INLINE_FUNCTION void	setLocalSamplesNum (size_type nlocal)
	Set the local number of particles.

void	generate (view_type view, Kokkos::Random_XorShift64_Pool<> rand_pool64)
	Generate random samples using inverse transform sampling.

void	generate (view_type view, size_type startIndex, size_type endIndex, Kokkos::Random_XorShift64_Pool<> rand_pool64)
	Generate random samples using inverse transform sampling for a specific range of particles.

Public Attributes
Distribution	dist_m

size_type	ntotal_m

Vector< T, Dim >	umin_m

Vector< T, Dim >	umax_m

Detailed Description

template<typename T, unsigned Dim, class DeviceType, class Distribution>
class ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >

A class for inverse transform sampling.

This class performs inverse transform sampling for a given distribution.

Template Parameters

T	Data type.
Dim	Dimensionality of the sample space.
DeviceType	The device type for Kokkos.
Distribution	Type of the distribution to sample from.

Constructor & Destructor Documentation

◆ InverseTransformSampling() [1/3]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

template<class RegionLayout >

ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::InverseTransformSampling	(	Distribution &	dist_r,
		Vector< T, Dim > &	rmax_r,
		Vector< T, Dim > &	rmin_r,
		RegionLayout &	rlayout_r,
		size_type &	ntotal_r
	)

inline

Constructor for InverseTransformSampling class with domain decomposition.

Parameters

dist_r	The distribution to sample from.
rmax_r	Maximum global range.
rmin_r	Minimum global range.
rlayout_r	The region layout.
ntotal_r	Total number of samples to generate.

◆ InverseTransformSampling() [2/3]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::InverseTransformSampling	(	Distribution &	dist_r,
		Vector< T, Dim > &	rmax_r,
		Vector< T, Dim > &	rmin_r,
		Vector< T, Dim > &	locrmax_r,
		Vector< T, Dim > &	locrmin_r,
		size_type &	ntotal_r
	)

inline

Constructor for InverseTransformSampling class without applying domain decomposition..

Parameters

dist_r	The distribution to sample from.
rmax_r	Maximum global range.
rmin_r	Minimum global range.
locrmax_r	Maximum local (per rank) range.
locrmin_r	Minimum local (per rank) range.
ntotal_	Total number of samples to generate.

◆ InverseTransformSampling() [3/3]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::InverseTransformSampling	(	Distribution &	dist_r,
		Vector< T, Dim > &	rmax_r,
		Vector< T, Dim > &	rmin_r,
		size_type &	ntotal_r
	)

inline

Constructor for InverseTransformSampling class. In this method, we do not consider any domain decomposition.

Parameters

dist_r	The distribution to sample from.
rmax_r	Maximum global range for sampling.
rmin_r	Minimum global range for sampling.
ntotal_r	Total number of samples to generate.

Member Function Documentation

◆ generate() [1/2]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

void ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::generate	(	view_type	view,
		Kokkos::Random_XorShift64_Pool<>	rand_pool64
	)

inline

Generate random samples using inverse transform sampling.

Parameters

view	The view to fill with random samples.
rand_pool64	The random number generator pool.

◆ generate() [2/2]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

void ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::generate	(	view_type	view,
		size_type	startIndex,
		size_type	endIndex,
		Kokkos::Random_XorShift64_Pool<>	rand_pool64
	)

inline

Generate random samples using inverse transform sampling for a specific range of particles.

Parameters

view	The view to fill with random samples.
startIndex	The starting index of view.
endIndex	The ending index of view.
rand_pool64	The random number generator pool.

◆ getLocalSamplesNum()

template<typename T , unsigned Dim, class DeviceType , class Distribution >

KOKKOS_INLINE_FUNCTION size_type ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::getLocalSamplesNum ( ) const

inline

Get the local number of samples.

Returns: The local number of samples.

◆ setLocalSamplesNum()

template<typename T , unsigned Dim, class DeviceType , class Distribution >

KOKKOS_INLINE_FUNCTION void ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::setLocalSamplesNum ( size_type nlocal )

inline

Set the local number of particles.

Parameters

nlocal The new number of local particles.

◆ updateBounds() [1/2]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

void ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::updateBounds	(	Vector< T, Dim > &	rmax,
		Vector< T, Dim > &	rmin
	)

inline

Updates the sampling bounds using the CDF without any domain decomposition.

This method allows the user to update the minimum and maximum bounds for the inverse transform sampling method. It recalculates the cumulative distribution function (CDF) values for the new bounds and updates the internal variables to reflect these changes.

Parameters

new_rmax	The new maximum range for sampling. This vector defines the upper bounds for each dimension.
new_rmin	The new minimum range for sampling. This vector defines the lower bounds for each dimension.

◆ updateBounds() [2/2]

template<typename T , unsigned Dim, class DeviceType , class Distribution >

void ippl::random::InverseTransformSampling< T, Dim, DeviceType, Distribution >::updateBounds	(	Vector< T, Dim > &	rmax,
		Vector< T, Dim > &	rmin,
		Vector< T, Dim > &	locrmax,
		Vector< T, Dim > &	locrmin
	)

inline

Updates the sampling bounds and reinitializes internal variables.

This method allows the user to update the minimum and maximum bounds for the sampling process It recalculates the cumulative distribution function (CDF) values for the new bounds and updates the internal variables to reflect these changes.

Parameters

rmax	The new maximum range for sampling. This vector defines the upper bounds for each dimension.
rmin	The new minimum range for sampling. This vector defines the lower bounds for each dimension.
locrmax	The new local maximum range for sampling. This vector defines the upper bounds for each dimension for a given rank.
locrmin	The new minimum range for sampling. This vector defines the lower bounds for each dimension for a given rank.

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

ippl-src/src/Random/InverseTransformSampling.h

Classes

Public Types

Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

◆ InverseTransformSampling() [1/3]

◆ InverseTransformSampling() [2/3]

◆ InverseTransformSampling() [3/3]

Member Function Documentation

◆ generate() [1/2]

◆ generate() [2/2]

◆ getLocalSamplesNum()

◆ setLocalSamplesNum()

◆ updateBounds() [1/2]

◆ updateBounds() [2/2]