/usr/include/ITK-4.5/itkMahalanobisDistanceThresholdImageFunction.hxx is in libinsighttoolkit4-dev 4.5.0-3.
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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 __itkMahalanobisDistanceThresholdImageFunction_hxx
#define __itkMahalanobisDistanceThresholdImageFunction_hxx
#include "itkMahalanobisDistanceThresholdImageFunction.h"
namespace itk
{
template< typename TInputImage, typename TCoordRep >
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::MahalanobisDistanceThresholdImageFunction()
{
m_Threshold = NumericTraits< double >::Zero;
m_MahalanobisDistanceMembershipFunction =
MahalanobisDistanceFunctionType::New();
}
template< typename TInputImage, typename TCoordRep >
void
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::SetMean(const MeanVectorType & mean)
{
// Cache the mean
m_Mean = mean;
// Set the mean on the membership function
typename MahalanobisDistanceFunctionType::MeanVectorType m;
NumericTraits<typename MahalanobisDistanceFunctionType::MeanVectorType>::SetLength(m, mean.size());
for (unsigned int i=0; i < mean.size(); ++i)
{
m[i] = mean[i];
}
m_MahalanobisDistanceMembershipFunction->SetMean(m);
}
template< typename TInputImage, typename TCoordRep >
void
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::SetCovariance(const CovarianceMatrixType & covariance)
{
// Cache the covariance
m_Covariance = covariance;
// Set the covariance on the membership function
typename MahalanobisDistanceFunctionType::CovarianceMatrixType c;
c = covariance;
m_MahalanobisDistanceMembershipFunction->SetCovariance(c);
}
template< typename TInputImage, typename TCoordRep >
const typename
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >::MeanVectorType &
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::GetMean() const
{
// return the cache mean (mean set on the membership function
// matches by design)
return m_Mean;
}
template< typename TInputImage, typename TCoordRep >
const typename
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >::CovarianceMatrixType &
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::GetCovariance() const
{
// return the cache covariance (covariance set on the membership function
// matches by design)
return m_Covariance;
}
template< typename TInputImage, typename TCoordRep >
bool
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::Evaluate(const PointType & point) const
{
IndexType index;
this->ConvertPointToNearestIndex(point, index);
return ( this->EvaluateAtIndex(index) );
}
template< typename TInputImage, typename TCoordRep >
bool
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::EvaluateAtContinuousIndex(const ContinuousIndexType & index) const
{
IndexType nindex;
this->ConvertContinuousIndexToNearestIndex (index, nindex);
return this->EvaluateAtIndex(nindex);
}
template< typename TInputImage, typename TCoordRep >
bool
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::EvaluateAtIndex(const IndexType & index) const
{
double mahalanobisDistance = this->EvaluateDistanceAtIndex(index);
return ( mahalanobisDistance <= m_Threshold );
}
template< typename TInputImage, typename TCoordRep >
double
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::EvaluateDistance(const PointType & point) const
{
IndexType index;
this->ConvertPointToNearestIndex(point, index);
const double mahalanobisDistance = this->EvaluateDistanceAtIndex(index);
return mahalanobisDistance;
}
template< typename TInputImage, typename TCoordRep >
double
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::EvaluateDistanceAtIndex(const IndexType & index) const
{
double mahalanobisDistanceSquared =
m_MahalanobisDistanceMembershipFunction->Evaluate(
this->GetInputImage()->GetPixel(index) );
double mahalanobisDistance;
// Deal with cases that are barely negative.
// In theory they should never appear, but
// they may happen and would produce NaNs
// in the vcl_sqrt
if ( mahalanobisDistanceSquared < 0.0 )
{
mahalanobisDistance = 0.0;
}
else
{
mahalanobisDistance = vcl_sqrt(mahalanobisDistanceSquared);
}
return mahalanobisDistance;
}
template< typename TInputImage, typename TCoordRep >
void
MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Threshold: " << m_Threshold << std::endl;
os << indent << "Mean: " << m_Mean << std::endl;
os << indent << "Covariance: " << m_Covariance << std::endl;
os << indent << "MahalanobisDistanceMembershipFunction: " << m_MahalanobisDistanceMembershipFunction << std::endl;
}
} // end namespace itk
#endif
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