/usr/include/ITK-4.5/itkMeanSquaredErrorFunction.hxx is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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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 __itkMeanSquaredErrorFunction_hxx
#define __itkMeanSquaredErrorFunction_hxx
#include "itkMeanSquaredErrorFunction.h"
namespace itk
{
namespace Statistics
{
/** Constructor */
template<typename TMeasurementVector, typename ScalarType>
MeanSquaredErrorFunction<TMeasurementVector,ScalarType>
::MeanSquaredErrorFunction()
{
}
/** Destructor */
template<typename TMeasurementVector, typename ScalarType>
MeanSquaredErrorFunction <TMeasurementVector,ScalarType>
::~MeanSquaredErrorFunction()
{
}
/** Evaluate */
template<typename TMeasurementVector, typename ScalarType>
ScalarType
MeanSquaredErrorFunction <TMeasurementVector,ScalarType>
::Evaluate(const TMeasurementVector& errors) const
{
vnl_vector <ScalarType> temp(errors.Size());
for(unsigned int i=0; i<errors.Size(); i++)
{
temp[i]=errors[i];
}
return (temp.squared_magnitude() / temp.size());
}
/** Evaluate derivatives */
template<typename TMeasurementVector, typename ScalarType>
typename MeanSquaredErrorFunction <TMeasurementVector,ScalarType>
::InternalVectorType
MeanSquaredErrorFunction <TMeasurementVector,ScalarType>
::EvaluateDerivative(const TMeasurementVector& errors) const
{
ScalarType m = static_cast<ScalarType>(2) / errors.Size();
InternalVectorType temp(errors.Size());
for(unsigned int i=0; i<errors.Size(); i++)
{
temp[i]=errors[i]*m;
}
return temp;
}
/** Print the object */
template<typename TMeasurementVector, typename ScalarType>
void
MeanSquaredErrorFunction <TMeasurementVector,ScalarType>
::PrintSelf( std::ostream& os, Indent indent ) const
{
os << indent << "MeanSquaredErrorFunction(" << this << ")" << std::endl;
Superclass::PrintSelf( os, indent );
}
} // end namespace Statistics
} // end namespace itk
#endif
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