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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 "itkGaussianSpatialFunction.h"
#include "itkMath.h"
#include "itkTestingMacros.h"
int itkGaussianSpatialFunctionTest( int argc, char* argv[] )
{
if ( argc < 3 )
{
std::cout << "Usage: " << argv[0]
<< " scale normalized" << std::endl;
return EXIT_FAILURE;
}
const unsigned int Dimension = 3;
typedef double PixeltType;
typedef itk::GaussianSpatialFunction< PixeltType, Dimension >
GaussianSpatialFunctionType;
typedef GaussianSpatialFunctionType::ArrayType ArrayType;
typedef GaussianSpatialFunctionType::InputType InputType;
// Create and initialize the Spatial function
GaussianSpatialFunctionType::Pointer gaussianSpatialFunction =
GaussianSpatialFunctionType::New();
EXERCISE_BASIC_OBJECT_METHODS( gaussianSpatialFunction, GaussianSpatialFunction,
SpatialFunction );
ArrayType mean;
mean[0] = 13;
mean[1] = 17;
mean[2] = 19;
gaussianSpatialFunction->SetMean( mean );
TEST_SET_GET_VALUE( mean, gaussianSpatialFunction->GetMean() );
ArrayType sigma;
sigma[0] = 5;
sigma[1] = 7;
sigma[2] = 9;
gaussianSpatialFunction->SetSigma( sigma );
TEST_SET_GET_VALUE( sigma, gaussianSpatialFunction->GetSigma() );
double scale = atof( argv[1] );
gaussianSpatialFunction->SetScale( scale );
TEST_SET_GET_VALUE( scale, gaussianSpatialFunction->GetScale() );
bool normalized = static_cast< bool >( atoi( argv[2] ) );
gaussianSpatialFunction->SetNormalized( normalized );
TEST_SET_GET_VALUE( normalized, gaussianSpatialFunction->GetNormalized() );
if( normalized )
{
gaussianSpatialFunction->NormalizedOn();
TEST_SET_GET_VALUE( true, gaussianSpatialFunction->GetNormalized() );
}
else
{
gaussianSpatialFunction->NormalizedOff();
TEST_SET_GET_VALUE( false, gaussianSpatialFunction->GetNormalized() );
}
// Test the evaluation of the Gaussian spatial funtion
//
// Evaluate it at the center of the Gaussian
InputType point;
point[0] = mean[0];
point[1] = mean[1];
point[2] = mean[2];
double computedValueAtMean = gaussianSpatialFunction->Evaluate( point );
double expectedValueAtMean = 1.0;
if( gaussianSpatialFunction->GetNormalized() )
{
const double oneDimensionalFactor = std::sqrt( 2.0 * itk::Math::pi );
const double factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
expectedValueAtMean = scale / ( sigma[0]*sigma[1]*sigma[2] * factor );
}
else
{
const double oneDimensionalFactor = 1.0;
const double factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
expectedValueAtMean = scale / factor;
}
if( itk::Math::NotAlmostEquals( expectedValueAtMean, computedValueAtMean ) )
{
std::cout << "Error in point " << point << ": ";
std::cout << "expected: " << expectedValueAtMean << ", but got "
<< computedValueAtMean << std::endl;
std::cout << "Test failed" << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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