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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkMaximumRatioDecisionRuleTest.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
#include "itkMaximumRatioDecisionRule2.h"
#include "itkObjectFactory.h"
int itkMaximumRatioDecisionRuleTest(int, char* [] )
{
typedef itk::Statistics::MaximumRatioDecisionRule2 MaximumRatioDecisionRuleType;
typedef MaximumRatioDecisionRuleType::MembershipVectorType MembershipVectorType;
MaximumRatioDecisionRuleType::Pointer decisionRule = MaximumRatioDecisionRuleType::New();
std::cout << decisionRule->GetNameOfClass() << std::endl;
std::cout << decisionRule->MaximumRatioDecisionRuleType::Superclass::GetNameOfClass() << std::endl;
decisionRule->Print(std::cout);
MembershipVectorType membershipScoreVector;
double membershipScore1;
membershipScore1 = 0.1;
membershipScoreVector.push_back( membershipScore1 );
double membershipScore2;
membershipScore2 = 0.5;
membershipScoreVector.push_back( membershipScore2 );
double membershipScore3;
membershipScore3 = 1.9;
membershipScoreVector.push_back( membershipScore3 );
//add discriminantscore with a value of zero
double membershipScore4;
membershipScore4 = 0.0;
membershipScoreVector.push_back( membershipScore4 );
unsigned int decisionValue;
try
{
decisionRule->Evaluate( membershipScoreVector);
std::cerr << "An exception should have been thrown since a priori"
<< " probability is not set yet " << std::endl;
return EXIT_FAILURE;
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception= " << excp << std::endl;
}
//Set aprior probablity
typedef MaximumRatioDecisionRuleType::APrioriVectorType APrioriVectorType;
typedef MaximumRatioDecisionRuleType::APrioriValueType APrioriValueType;
APrioriVectorType aprioriProbabilityVector;
//first class
APrioriValueType value1 = 0.4;
aprioriProbabilityVector.push_back( value1 );
//second class
APrioriValueType value2 = 0.2;
aprioriProbabilityVector.push_back( value2 );
decisionRule->SetAPriori( aprioriProbabilityVector );
//Evalue the membershipScore vector instantiated above ( 3 classes )
try
{
decisionRule->Evaluate( membershipScoreVector);
std::cerr << "An exception should have been thrown since the membership"
<< " score vector size doesn't match with the apriori vector" << std::endl;
return EXIT_FAILURE;
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception= " << excp << std::endl;
}
APrioriVectorType aprioriProbabilityVector2;
value1 = 0.3;
aprioriProbabilityVector2.push_back( value1 );
value2 = 0.3;
aprioriProbabilityVector2.push_back( value2 );
//Add a third and a fourth class
APrioriValueType value3 = 0.3;
aprioriProbabilityVector2.push_back( value3 );
//Zero priori probability
APrioriValueType value4 = 0.0;
aprioriProbabilityVector2.push_back( value4 );
decisionRule->SetAPriori( aprioriProbabilityVector2 );
try
{
decisionValue = decisionRule->Evaluate( membershipScoreVector);
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception= " << excp << std::endl;
return EXIT_FAILURE;
}
//Check if the computed decision value is correct
if( decisionValue != 2 )
{
std::cerr << "Decision rule computation is incorrect!" << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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