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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkMahalanobisDistanceThresholdImageFunctionTest.cxx,v $
Language: C++
Date: $Date: 2004-08-08 13:39:21 $
Version: $Revision: 1.5 $
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 <stdio.h>
#include "itkMahalanobisDistanceThresholdImageFunction.h"
#include "itkImage.h"
#include "itkRGBPixel.h"
int itkMahalanobisDistanceThresholdImageFunctionTest(int, char* [] )
{
const unsigned int Dimension = 3;
typedef unsigned char PixelComponentType;
typedef itk::RGBPixel<PixelComponentType> PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::MahalanobisDistanceThresholdImageFunction< ImageType > FunctionType;
// Create and allocate the image
ImageType::Pointer image = ImageType::New();
ImageType::SizeType size;
ImageType::IndexType start;
ImageType::RegionType region;
size[0] = 50;
size[1] = 50;
size[2] = 50;
start.Fill( 0 );
region.SetIndex( start );
region.SetSize( size );
image->SetRegions( region );
image->Allocate();
ImageType::PixelType initialValue;
initialValue[0] = 11;
initialValue[1] = 22;
initialValue[2] = 33;
image->FillBuffer( initialValue );
FunctionType::Pointer function = FunctionType::New();
function->SetInputImage( image );
const double threshold = 5.0;
function->SetThreshold( threshold );
typedef vnl_matrix<double> CovarianceType;
typedef vnl_vector<double> MeanType;
CovarianceType Covariance( Dimension, Dimension );
MeanType Mean( Dimension );
Mean[0] = 10.0;
Mean[1] = 20.0;
Mean[2] = 30.0;
Covariance.fill( 0.0 );
Covariance[0][0] = 100.0;
Covariance[1][1] = 200.0;
Covariance[2][2] = 300.0;
function->SetCovariance( Covariance );
function->SetMean( Mean );
ImageType::IndexType index;
index[0] = 25;
index[1] = 25;
index[2] = 25;
FunctionType::OutputType belongs;
belongs = function->EvaluateAtIndex( index );
std::cout << "function->EvaluateAtIndex( index ): " << belongs << std::endl;
if( !belongs )
{
std::cerr << "Error in EvaluateAtIndex() we were expecting true and got false" << std::endl;
return EXIT_FAILURE;
}
const double distance = function->EvaluateDistanceAtIndex( index );
std::cout << "function->EvaluateDistanceAtIndex( index ): " << distance << std::endl;
const double expectedDistance = 0.244949;
if( fabs(distance - expectedDistance) > 1e-5 )
{
std::cerr << "Error in distance computation in EvaluateDistanceAtIndex() !!" << std::endl;
std::cerr << "Expected distance value = " << expectedDistance << std::endl;
std::cerr << "Distance obtained value = " << distance << std::endl;
return EXIT_FAILURE;
}
// Test Evaluate
FunctionType::PointType point;
point[0] = 25;
point[1] = 25;
point[2] = 25;
FunctionType::OutputType belongs2;
belongs2 = function->Evaluate(point);
std::cout << "function->Evaluate(point): " << belongs2 << std::endl;
if( !belongs2 )
{
std::cerr << "Error in Evaluate() we were expecting true and got false" << std::endl;
return EXIT_FAILURE;
}
const double distance2 = function->EvaluateDistance(point);
std::cout << "function->EvaluateDistance(point): " << distance2 << std::endl;
if( fabs(distance2 - expectedDistance) > 1e-5 )
{
std::cerr << "Error in distance computation in EvaluateDistance() !!" << std::endl;
std::cerr << "Expected distance value = " << expectedDistance << std::endl;
std::cerr << "Distance obtained value = " << distance2 << std::endl;
return EXIT_FAILURE;
}
// Test EvaluateAtContinuousIndex
FunctionType::ContinuousIndexType cindex;
cindex[0] = 25;
cindex[1] = 25;
cindex[2] = 25;
FunctionType::OutputType belongs3;
belongs3 = function->EvaluateAtContinuousIndex(cindex);
std::cout << "function->EvaluateAtContinuousIndex(cindex): " << belongs3 << std::endl;
if( !belongs3 )
{
std::cerr << "Error in EvaluateAtContinuousIndex() we were expecting true and got false" << std::endl;
return EXIT_FAILURE;
}
// Test GetConstReferenceMacro
const double & getThreshold = function->GetThreshold();
std::cout << "function->GetThreshold(): " << getThreshold << std::endl;
if( fabs( threshold - getThreshold ) > 1e-9 )
{
std::cerr << "Error: Set/Get Threshold do not match" << std::endl;
return EXIT_FAILURE;
}
// Exercise GetMean() and GetCovariance()
Mean = function->GetMean();
Covariance = function->GetCovariance();
std::cout << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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