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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 "itkCovarianceImageFunction.h"
#include "itkImageFunction.h"
#include "itkTestingMacros.h"
int itkCovarianceImageFunctionTest( int, char* [] )
{
const unsigned int Dimension = 3;
typedef unsigned char PixelComponentType;
const unsigned int VectorDimension = 4;
typedef itk::FixedArray< PixelComponentType, VectorDimension > PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef itk::CovarianceImageFunction< ImageType > FunctionType;
// Create and allocate the image
ImageType::Pointer image = ImageType::New();
ImageType::SizeType size;
ImageType::IndexType start;
ImageType::RegionType region;
size[0] = 20;
size[1] = 20;
size[2] = 20;
ImageType::IndexValueType imageValue = 0;
start.Fill( imageValue );
region.SetIndex( start );
region.SetSize( size );
image->SetRegions( region );
image->Allocate();
ImageType::PixelType initialValue;
initialValue[0] = 11;
initialValue[1] = 13;
initialValue[2] = 17;
initialValue[3] = 19;
image->FillBuffer( initialValue );
FunctionType::Pointer function = FunctionType::New();
EXERCISE_BASIC_OBJECT_METHODS( function, CovarianceImageFunction,
ImageFunction );
function->SetInputImage( image );
unsigned int neighborhoodRadius = 5;
function->SetNeighborhoodRadius( neighborhoodRadius );
TEST_SET_GET_VALUE( neighborhoodRadius, function->GetNeighborhoodRadius() );
ImageType::IndexType index;
index[0] = 10;
index[1] = 10;
index[2] = 10;
FunctionType::OutputType covariance;
covariance = function->EvaluateAtIndex( index );
std::cout << "function->EvaluateAtIndex( index ): " << covariance << std::endl;
// Test Evaluate
FunctionType::PointType point;
point[0] = 25;
point[1] = 25;
point[2] = 25;
FunctionType::OutputType covariance2;
covariance2 = function->Evaluate(point);
std::cout << "function->Evaluate(point): " << covariance2 << std::endl;
// Test EvaluateAtContinuousIndex
FunctionType::ContinuousIndexType cindex;
cindex[0] = 25;
cindex[1] = 25;
cindex[2] = 25;
FunctionType::OutputType covariance3;
covariance3 = function->EvaluateAtContinuousIndex(cindex);
std::cout << "function->EvaluateAtContinuousIndex(cindex): " << covariance3 << std::endl;
// Since the input image is constant, the covariance should be equal to
// the initial value
for( unsigned int ix = 0; ix < VectorDimension; ++ix )
{
for( unsigned int iy = 0; iy < VectorDimension; ++iy )
{
// Covariance must be zero in this image with constant values
if( ! itk::Math::FloatAlmostEqual( itk::Math::abs( covariance[ix][iy] ),
static_cast< FunctionType::OutputType::element_type >( imageValue ), 10, 10e-7 ) )
{
std::cerr << "Error in covariance computation" << std::endl;
return EXIT_FAILURE;
}
}
}
std::cout << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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