/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: MaximumRatioDecisionRule.cxx,v $
  Language:  C++
  Date:      $Date: 2005/07/26 19:51:21 $
  Version:   $Revision: 1.12 $

  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{itk::Statistics::Maximum\-Ratio\-Decision\-Rule}
//
// The \code{Evaluate()} method of the \doxygen{MaximumRatioDecisionRule}
// returns the index, $i$ if 
// \begin{equation}
//   \frac{f_{i}(\overrightarrow{x})}{f_{j}(\overrightarrow{x})} >
//   \frac{K_{j}}{K_{i}} \textrm{ for all } j \not= i 
// \end{equation} 
// where the $i$ is the index of a class which has membership function
// $f_{i}$ and its prior value (usually, the \emph{a priori}
// probability of the class) is $K_{i}$ 
//
// We include the header files for the class as well as the header file for
// the \code{std::vector} class that will be the container for the
// discriminant scores.  
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
#include "itkMaximumRatioDecisionRule.h"
#include <vector>
// Software Guide : EndCodeSnippet

int main(int, char*[])
{
  // 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::MaximumRatioDecisionRule DecisionRuleType;
  DecisionRuleType::Pointer decisionRule = DecisionRuleType::New();
  // Software Guide : EndCodeSnippet


  // Software Guide : BeginLatex
  //
  // We create the discriminant score vector and fill it with three
  // values. We also create a vector (\code{aPrioris}) for the \emph{a
  // priori} values. The \code{Evaluate( discriminantScores )} will
  // return 1. 
  //
  // Software Guide : EndLatex 

  // Software Guide : BeginCodeSnippet
  std::vector< double > discriminantScores;
  discriminantScores.push_back( 0.1 );
  discriminantScores.push_back( 0.3 );
  discriminantScores.push_back( 0.6 );

  DecisionRuleType::APrioriVectorType aPrioris;
  aPrioris.push_back( 0.1 );
  aPrioris.push_back( 0.8 );
  aPrioris.push_back( 0.1 );

  decisionRule->SetAPriori( aPrioris );
  std::cout << "MaximumRatioDecisionRule: The index of the chosen = " 
            << decisionRule->Evaluate( discriminantScores )
            << std::endl;
  // Software Guide : EndCodeSnippet

  return 0;
}
