NormalDistribution.h File Reference

#include "Random/Distribution.h"
#include "Random/Utility.h"

Include dependency graph for NormalDistribution.h:

Go to the source code of this file.

Classes
struct	ippl::random::normal_cdf< T >
	Functor to calculate the cumulative distribution function (CDF) for a normal distribution. More...
struct	ippl::random::normal_pdf< T >
	Functor to calculate the probability density function (PDF) for a normal distribution. More...
struct	ippl::random::normal_estimate< T >
	Functor to estimate the initial guess for sampling normal distribution. More...
struct	ippl::random::NormalDistributionFunctions< T >
struct	ippl::random::NormalDistributionFunctions< T >::PDF
struct	ippl::random::NormalDistributionFunctions< T >::CDF
struct	ippl::random::NormalDistributionFunctions< T >::Estimate
class	ippl::random::NormalDistribution< T, Dim >

Namespaces
namespace	ippl

Functions
template<typename T >
KOKKOS_FUNCTION T	ippl::random::normal_cdf_func (T x, T mean, T stddev)
	Calculate the cumulative distribution function (CDF) for a normal distribution.
template<typename T >
KOKKOS_FUNCTION T	ippl::random::normal_pdf_func (T x, T mean, T stddev)
	Calculate the probability density function (PDF) for a normal distribution.
template<typename T >
KOKKOS_FUNCTION T	ippl::random::normal_estimate_func (T u, T mean, T stddev)
	An estimator for the initial guess that is used in Newton-Raphson method of Inverste Transfrom Sampling.

Function Documentation

normal_cdf_func()

template<typename T >

KOKKOS_FUNCTION T ippl::random::normal_cdf_func	(	T	x,
		T	mean,
		T	stddev
	)

Calculate the cumulative distribution function (CDF) for a normal distribution.

Parameters

x	Input value.
mean	Mean of the distribution.
stddev	Standard deviation of the distribution.

Returns

The CDF value.

normal_estimate_func()

template<typename T >

KOKKOS_FUNCTION T ippl::random::normal_estimate_func	(	T	u,
		T	mean,
		T	stddev
	)

An estimator for the initial guess that is used in Newton-Raphson method of Inverste Transfrom Sampling.

Parameters

u	Input value.
mean	Mean of the distribution.
stddev	Standard deviation of the distribution.

Returns

The estimate value.

normal_pdf_func()

template<typename T >

KOKKOS_FUNCTION T ippl::random::normal_pdf_func	(	T	x,
		T	mean,
		T	stddev
	)

Calculate the probability density function (PDF) for a normal distribution.

Parameters

x	Input value.
mean	Mean of the distribution.
stddev	Standard deviation of the distribution.

Returns

The PDF value.