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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 itkMeanSampleFilter_hxx
#define itkMeanSampleFilter_hxx
#include "itkMeanSampleFilter.h"
#include <vector>
#include "itkCompensatedSummation.h"
#include "itkMeasurementVectorTraits.h"
namespace itk
{
namespace Statistics
{
template< typename TSample >
MeanSampleFilter< TSample >
::MeanSampleFilter()
{
this->ProcessObject::SetNumberOfRequiredInputs(1);
this->ProcessObject::SetNumberOfRequiredOutputs(1);
this->ProcessObject::SetNthOutput( 0, this->MakeOutput(0) );
}
template< typename TSample >
MeanSampleFilter< TSample >
::~MeanSampleFilter()
{}
template< typename TSample >
void
MeanSampleFilter< TSample >
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
template< typename TSample >
void
MeanSampleFilter< TSample >
::SetInput(const SampleType *sample)
{
this->ProcessObject::SetNthInput( 0, const_cast< SampleType * >( sample ) );
}
template< typename TSample >
const TSample *
MeanSampleFilter< TSample >
::GetInput() const
{
return itkDynamicCastInDebugMode< const SampleType * >( this->GetPrimaryInput() );
}
template< typename TSample >
typename MeanSampleFilter< TSample >::DataObjectPointer
MeanSampleFilter< TSample >
::MakeOutput( DataObjectPointerArraySizeType itkNotUsed(idx) )
{
MeasurementVectorRealType mean;
(void)mean; // for complainty pants : valgrind
NumericTraits<MeasurementVectorRealType>::SetLength( mean, this->GetMeasurementVectorSize() );
// NumericTraits::SetLength also initializes array to zero
typename MeasurementVectorDecoratedType::Pointer decoratedMean = MeasurementVectorDecoratedType::New();
decoratedMean->Set( mean );
return decoratedMean.GetPointer();
}
template< typename TSample >
const typename MeanSampleFilter< TSample >::MeasurementVectorDecoratedType *
MeanSampleFilter< TSample >
::GetOutput() const
{
return itkDynamicCastInDebugMode< const MeasurementVectorDecoratedType * >(this->ProcessObject::GetOutput(0) );
}
template< typename TSample >
const typename MeanSampleFilter< TSample >::MeasurementVectorRealType
MeanSampleFilter< TSample >
::GetMean() const
{
const MeasurementVectorDecoratedType * decorator = this->GetOutput();
return decorator->Get();
}
template< typename TSample >
typename MeanSampleFilter< TSample >::MeasurementVectorSizeType
MeanSampleFilter< TSample >
::GetMeasurementVectorSize() const
{
const SampleType *input = this->GetInput();
if ( input )
{
return input->GetMeasurementVectorSize();
}
// Test if the Vector type knows its length
MeasurementVectorType vector;
MeasurementVectorSizeType measurementVectorSize = NumericTraits<MeasurementVectorType>::GetLength(vector);
if ( measurementVectorSize )
{
return measurementVectorSize;
}
measurementVectorSize = 1; // Otherwise set it to an innocuous value
return measurementVectorSize;
}
template< typename TSample >
void
MeanSampleFilter< TSample >
::GenerateData()
{
// set up input / output
const SampleType *input = this->GetInput();
const MeasurementVectorSizeType measurementVectorSize =
input->GetMeasurementVectorSize();
MeasurementVectorDecoratedType *decoratedOutput =
itkDynamicCastInDebugMode< MeasurementVectorDecoratedType * >( this->ProcessObject::GetOutput(0) );
MeasurementVectorRealType output = decoratedOutput->Get();
NumericTraits<MeasurementVectorRealType>::SetLength( output, this->GetMeasurementVectorSize() );
// algorithm start
typedef CompensatedSummation< MeasurementRealType > MeasurementRealAccumulateType;
std::vector< MeasurementRealAccumulateType > sum( measurementVectorSize );
typedef typename SampleType::TotalAbsoluteFrequencyType TotalFrequencyType;
TotalFrequencyType totalFrequency = NumericTraits< TotalFrequencyType >::ZeroValue();
typename SampleType::ConstIterator iter = input->Begin();
const typename SampleType::ConstIterator end = input->End();
for (; iter != end; ++iter )
{
const MeasurementVectorType & measurement = iter.GetMeasurementVector();
const typename SampleType::AbsoluteFrequencyType frequency = iter.GetFrequency();
totalFrequency += frequency;
for ( unsigned int dim = 0; dim < measurementVectorSize; dim++ )
{
const MeasurementRealType component =
static_cast< MeasurementRealType >( measurement[dim] );
sum[dim] += ( component * static_cast< MeasurementRealType >( frequency ) );
}
}
// compute the mean if the total frequency is different from zero
if ( totalFrequency > itk::Math::eps )
{
for ( unsigned int dim = 0; dim < measurementVectorSize; dim++ )
{
output[dim] = ( sum[dim].GetSum() / static_cast< MeasurementRealType >( totalFrequency ) );
}
}
else
{
itkExceptionMacro("Total frequency was too close to zero: " << totalFrequency );
}
decoratedOutput->Set( output );
}
} // end of namespace Statistics
} // end of namespace itk
#endif
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