#include <Gaussian.h>
Static Public Methods  
util::Matrix< double >  create2DGaussian (double radius, int size, double width=1) 
Create a simple, centersymmetric 2D Gaussian function.  
util::Matrix< double >  create2DNormal (double radius, int size, double deviation) 
Create a 2D normal distribution.  
util::List< double >  create1DGaussian (double range, int size, double width=1) 
Create a list of values containing a sampled 1D representation of a Gaussian function.  
double  gaussian (double x, double mean=0, double deviation=1) 
Get the value of the normal distribution N(mean,deviation) at x.  
double  erf (double x) 
The "error function" (erf). 

Create a list of values containing a sampled 1D representation of a Gaussian function. The first item of the returned list equals to G(range), and the last to G(range). The size parameter specified the number of sample taken between (and including) these extrema.


Create a simple, centersymmetric 2D Gaussian function. The center of the Gaussian "hill" is at the center of the returned matrix. The width of the Gaussian function can be controlled by two parameters: radius and width. Radius specifies the range of values the Gaussian is calculated on, and width specifies the width of the Gaussian itself. The default width is one, which results in a Gaussian function with a variance of 0.5. The size parameter effectively specifies the sampling resolution of the Gaussian function. The maximum value of the returned matrix is 1.


Create a 2D normal distribution. The larger radius and matrix size you use, the closer the sum of the result will be to unity.


The "error function" (erf). Erf is encountered in integrating the normal distribution (normalized Gaussian). erf(x) = int Inf>x G(t)dt, where G(t) is a Gaussian distribution with zero mean and unit variance. The value of the error function is calculated as a Maclaurin series, which may take quite a lot of time. 

Get the value of the normal distribution N(mean,deviation) at x. If mean is set to 0 and deviation to 1, the distribution is the "standard" normal distribution N(0,1). 