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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: GaussianDensityFunction.cxx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
// Software Guide : BeginLatex
//
// \index{Statistics!Gaussian (normal) probability density function}
//
// \index{itk::Statistics::GaussianDensityFunction}
//
// The Gaussian probability density function
// \subdoxygen{Statistics}{GaussianDensityFunction} requires two
// distribution parameters---the mean vector and the covariance matrix.
//
// We include the header files for the class and the \doxygen{Vector}.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkVector.h"
#include "itkGaussianDensityFunction.h"
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We define the type of the measurement vector that will be input to
// the Gaussian density function.
//
// Software Guide : EndLatex
int main(int, char*[])
{
// Software Guide : BeginCodeSnippet
typedef itk::Vector< float, 2 > MeasurementVectorType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The instantiation of the function is done through the usual
// \code{New()} method and a smart pointer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::Statistics::GaussianDensityFunction< MeasurementVectorType >
DensityFunctionType;
DensityFunctionType::Pointer densityFunction = DensityFunctionType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The length of the measurement vectors in the density function, in this
// case a vector of length 2, is specified using the
// \code{SetMeasurementVectorSize()} method.
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
densityFunction->SetMeasurementVectorSize( 2 );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We create the two distribution parameters and set them. The mean is
// [0, 0], and the covariance matrix is a 2 x 2 matrix:
// \[
// \begin{pmatrix}
// 4 & 0 \cr
// 0 & 4
// \end{pmatrix}
// \]
// We obtain the probability density for the measurement vector: [0, 0]
// using the \code{Evaluate(measurement vector)} method and print it out.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
DensityFunctionType::MeanType mean( 2 );
mean.Fill( 0.0 );
DensityFunctionType::CovarianceType cov;
cov.SetSize( 2, 2 );
cov.SetIdentity();
cov *= 4;
densityFunction->SetMean( &mean );
densityFunction->SetCovariance( &cov );
MeasurementVectorType mv;
mv.Fill( 0 );
std::cout << densityFunction->Evaluate( mv ) << std::endl;
// Software Guide : EndCodeSnippet
return 0;
}
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