/usr/include/ITK-4.5/itkGaussianDerivativeSpatialFunction.hxx is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
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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.
*
*=========================================================================*/
#ifndef __itkGaussianDerivativeSpatialFunction_hxx
#define __itkGaussianDerivativeSpatialFunction_hxx
#include <cmath>
#include "vnl/vnl_math.h"
#include "itkGaussianDerivativeSpatialFunction.h"
namespace itk
{
template< typename TOutput, unsigned int VImageDimension, typename TInput >
GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >
::GaussianDerivativeSpatialFunction()
{
m_Mean = ArrayType::Filled(0.0);
m_Sigma = ArrayType::Filled(1.0);
m_Scale = 1.0;
m_Normalized = false;
m_Direction = 0;
}
template< typename TOutput, unsigned int VImageDimension, typename TInput >
GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >
::~GaussianDerivativeSpatialFunction()
{}
template< typename TOutput, unsigned int VImageDimension, typename TInput >
typename GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >::OutputType
GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >
::Evaluate(const TInput & position) const
{
// Normalizing the Gaussian is important for statistical applications
// but is generally not desirable for creating images because of the
// very small numbers involved (would need to use doubles)
double prefixDenom;
if ( m_Normalized )
{
prefixDenom = m_Sigma[m_Direction] * m_Sigma[m_Direction];
for ( unsigned int i = 0; i < VImageDimension; i++ )
{
prefixDenom *= m_Sigma[i];
}
prefixDenom *= 2 * vcl_pow(2 * vnl_math::pi, VImageDimension / 2.0);
}
else
{
prefixDenom = 1.0;
}
double suffixExp = 0;
for ( unsigned int i = 0; i < VImageDimension; i++ )
{
suffixExp += ( position[m_Direction] - m_Mean[m_Direction] )
* ( position[m_Direction] - m_Mean[m_Direction] )
/ ( 2 * m_Sigma[m_Direction] * m_Sigma[m_Direction] );
}
double value = -2 * ( position[m_Direction] - m_Mean[m_Direction] ) * m_Scale * ( 1 / prefixDenom ) * vcl_exp(
-1 * suffixExp);
return (TOutput)value;
}
/** Evaluate the function at a given position and return a vector */
template< typename TOutput, unsigned int VImageDimension, typename TInput >
typename GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >::VectorType
GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >
::EvaluateVector(const TInput & position) const
{
VectorType gradient;
for ( unsigned int i = 0; i < VImageDimension; i++ )
{
m_Direction = i;
gradient[i] = this->Evaluate(position);
}
return gradient;
}
template< typename TOutput, unsigned int VImageDimension, typename TInput >
void
GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Sigma: " << m_Sigma << std::endl;
os << indent << "Mean: " << m_Mean << std::endl;
os << indent << "Scale: " << m_Scale << std::endl;
os << indent << "Normalized?: " << m_Normalized << std::endl;
os << indent << "Direction: " << m_Direction << std::endl;
}
} // end namespace itk
#endif
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