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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include "itkMahalanobisDistanceThresholdImageFunction.h"
#include "itkImage.h"
#include "itkImageFunction.h"
#include "itkMath.h"
#include "itkTestingMacros.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();
EXERCISE_BASIC_OBJECT_METHODS( function, MahalanobisDistanceThresholdImageFunction,
ImageFunction );
function->SetInputImage( image );
const double threshold = 5.0;
function->SetThreshold( threshold );
FunctionType::CovarianceMatrixType covariance( Dimension, Dimension );
FunctionType::MeanVectorType 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 );
TEST_SET_GET_VALUE( covariance, function->GetCovariance() );
TEST_SET_GET_VALUE( mean, function->GetMean() );
ImageType::IndexType index;
index[0] = 25;
index[1] = 25;
index[2] = 25;
TEST_EXPECT_TRUE( function->EvaluateAtIndex( index ) );
const double distance = function->EvaluateDistanceAtIndex( index );
std::cout << "function->EvaluateDistanceAtIndex( index ): " << distance << std::endl;
const double expectedDistance = 0.244949;
if( ! itk::Math::FloatAlmostEqual( distance, expectedDistance, 10, 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;
TEST_EXPECT_TRUE( function->Evaluate( point ) );
const double distance2 = function->EvaluateDistance(point);
std::cout << "function->EvaluateDistance(point): " << distance2 << std::endl;
if( ! itk::Math::FloatAlmostEqual( distance2, expectedDistance, 10, 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;
TEST_EXPECT_TRUE( function->EvaluateAtContinuousIndex( cindex ) );
// Test GetConstReferenceMacro
const double & getThreshold = function->GetThreshold();
std::cout << "function->GetThreshold(): " << getThreshold << std::endl;
if( ! itk::Math::FloatAlmostEqual( threshold, getThreshold, 10, 1e-9 ) )
{
std::cerr << "Error: Set/Get Threshold do not match" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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