samplers Directory Reference

Files
file	ContUniformSampler.cpp [code]
	Represents a continuous uniform distribution X ~ U(min, max) f(x) = 1 / (max - min).
file	ContUniformSampler.h [code]
file	DiscreteUniformSampler.cpp [code]
	Represents a discrete uniform distribution X ~ U(min, max) p(x) = 1 / (max - min).
file	DiscreteUniformSampler.h [code]
file	EmitterSampler.cpp [code]
	Sampler which selects a point on an emitter (light source) in the scene with probability proportional to radiant exitance.
file	EmitterSampler.h [code]
file	ExponentialSampler.cpp [code]
	Represents an exponential distribution: X ~ Exp(lambda) ; lambda > 0 f(x) = lambda * exp(-lambda * x) ; x >= 0 E(X) = 1 / lambda Var(X) = 1 / (lambda ^ 2).
file	ExponentialSampler.h [code]
file	JointContUniformSampler.cpp [code]
	Represents a uniform distribution on [min,max)^N ; N > 0, which could be used, for example, for choosing a random UV coordinate (e.g, where N = 2, min = 0, max = 1).
file	JointContUniformSampler.h [code]
file	JointSampler.cpp [code]
	Represents an abstract joint random variable that can be sampled according to several discrete/continuous probability distribution(s).
file	JointSampler.h [code]
file	NormalSampler.cpp [code]
file	NormalSampler.h [code]
	Represents a normal distribution: X ~ N(u, sigma^2) f(x) = 1/(sqrt(2*pi*sigma^2)*exp(-(x-u)^2/(2*sigma^2))) The normal distribution (aka Gaussian) is parameterized by its mean and variance and is referred to as the standard normal distribution when when it has mean zero and variance one. The normal distribution is probably the single most important distribution in all of probability because of its ubiquity in describing natural phenomena and because of the Central Limit Theorem, which says that the sum of a sufficiently large number of iid random variables, each with finite mean and varirance, will be approximately normally distributed. This allows one to study almost any distribution in terms of one, standard normal, distribution, simplifying many computations and proofs all over both applied and theoretical statistics.
file	SensorSampler.h [code]
file	UniformOnSphereSampler.cpp [code]
	Represents a uniform distribution on the surface of an N-dimensional unit sphere (with parameter N > 0 and radius = 1).
file	UniformOnSphereSampler.h [code]
file	UniformSampler.cpp [code]
	Represents a uniform distribution (either discrete or continuous).
file	UniformSampler.h [code]