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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkStatisticsImageFilter.txx,v $
Language: C++
Date: $Date: 2006-03-19 04:36:57 $
Version: $Revision: 1.19 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef _itkStatisticsImageFilter_txx
#define _itkStatisticsImageFilter_txx
#include "itkStatisticsImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "itkNumericTraits.h"
#include "itkProgressReporter.h"
namespace itk {
template<class TInputImage>
StatisticsImageFilter<TInputImage>
::StatisticsImageFilter(): m_ThreadSum(1), m_SumOfSquares(1), m_Count(1), m_ThreadMin(1), m_ThreadMax(1)
{
// first output is a copy of the image, DataObject created by
// superclass
//
// allocate the data objects for the outputs which are
// just decorators around pixel types
for (int i=1; i < 3; ++i)
{
typename PixelObjectType::Pointer output
= static_cast<PixelObjectType*>(this->MakeOutput(i).GetPointer());
this->ProcessObject::SetNthOutput(i, output.GetPointer());
}
// allocate the data objects for the outputs which are
// just decorators around real types
for (int i=3; i < 7; ++i)
{
typename RealObjectType::Pointer output
= static_cast<RealObjectType*>(this->MakeOutput(i).GetPointer());
this->ProcessObject::SetNthOutput(i, output.GetPointer());
}
this->GetMinimumOutput()->Set( NumericTraits<PixelType>::max() );
this->GetMaximumOutput()->Set( NumericTraits<PixelType>::NonpositiveMin() );
this->GetMeanOutput()->Set( NumericTraits<RealType>::max() );
this->GetSigmaOutput()->Set( NumericTraits<RealType>::max() );
this->GetVarianceOutput()->Set( NumericTraits<RealType>::max() );
this->GetSumOutput()->Set( NumericTraits<RealType>::Zero );
}
template<class TInputImage>
DataObject::Pointer
StatisticsImageFilter<TInputImage>
::MakeOutput(unsigned int output)
{
switch (output)
{
case 0:
return static_cast<DataObject*>(TInputImage::New().GetPointer());
break;
case 1:
return static_cast<DataObject*>(PixelObjectType::New().GetPointer());
break;
case 2:
return static_cast<DataObject*>(PixelObjectType::New().GetPointer());
break;
case 3:
case 4:
case 5:
case 6:
return static_cast<DataObject*>(RealObjectType::New().GetPointer());
break;
default:
// might as well make an image
return static_cast<DataObject*>(TInputImage::New().GetPointer());
break;
}
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::PixelObjectType*
StatisticsImageFilter<TInputImage>
::GetMinimumOutput()
{
return static_cast<PixelObjectType*>(this->ProcessObject::GetOutput(1));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::PixelObjectType*
StatisticsImageFilter<TInputImage>
::GetMinimumOutput() const
{
return static_cast<const PixelObjectType*>(this->ProcessObject::GetOutput(1));
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::PixelObjectType*
StatisticsImageFilter<TInputImage>
::GetMaximumOutput()
{
return static_cast<PixelObjectType*>(this->ProcessObject::GetOutput(2));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::PixelObjectType*
StatisticsImageFilter<TInputImage>
::GetMaximumOutput() const
{
return static_cast<const PixelObjectType*>(this->ProcessObject::GetOutput(2));
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetMeanOutput()
{
return static_cast<RealObjectType*>(this->ProcessObject::GetOutput(3));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetMeanOutput() const
{
return static_cast<const RealObjectType*>(this->ProcessObject::GetOutput(3));
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetSigmaOutput()
{
return static_cast<RealObjectType*>(this->ProcessObject::GetOutput(4));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetSigmaOutput() const
{
return static_cast<const RealObjectType*>(this->ProcessObject::GetOutput(4));
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetVarianceOutput()
{
return static_cast<RealObjectType*>(this->ProcessObject::GetOutput(5));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetVarianceOutput() const
{
return static_cast<const RealObjectType*>(this->ProcessObject::GetOutput(5));
}
template<class TInputImage>
typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetSumOutput()
{
return static_cast<RealObjectType*>(this->ProcessObject::GetOutput(6));
}
template<class TInputImage>
const typename StatisticsImageFilter<TInputImage>::RealObjectType*
StatisticsImageFilter<TInputImage>
::GetSumOutput() const
{
return static_cast<const RealObjectType*>(this->ProcessObject::GetOutput(6));
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::GenerateInputRequestedRegion()
{
Superclass::GenerateInputRequestedRegion();
if ( this->GetInput() )
{
InputImagePointer image =
const_cast< typename Superclass::InputImageType * >( this->GetInput() );
image->SetRequestedRegionToLargestPossibleRegion();
}
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::EnlargeOutputRequestedRegion(DataObject *data)
{
Superclass::EnlargeOutputRequestedRegion(data);
data->SetRequestedRegionToLargestPossibleRegion();
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::AllocateOutputs()
{
// Pass the input through as the output
InputImagePointer image =
const_cast< TInputImage * >( this->GetInput() );
this->GraftOutput( image );
// Nothing that needs to be allocated for the remaining outputs
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::BeforeThreadedGenerateData()
{
int numberOfThreads = this->GetNumberOfThreads();
// Resize the thread temporaries
m_Count.SetSize(numberOfThreads);
m_SumOfSquares.SetSize(numberOfThreads);
m_ThreadSum.SetSize(numberOfThreads);
m_ThreadMin.SetSize(numberOfThreads);
m_ThreadMax.SetSize(numberOfThreads);
// Initialize the temporaries
m_Count.Fill(NumericTraits<long>::Zero);
m_ThreadSum.Fill(NumericTraits<RealType>::Zero);
m_SumOfSquares.Fill(NumericTraits<RealType>::Zero);
m_ThreadMin.Fill(NumericTraits<PixelType>::max());
m_ThreadMax.Fill(NumericTraits<PixelType>::NonpositiveMin());
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::AfterThreadedGenerateData()
{
int i;
long count;
RealType sumOfSquares;
int numberOfThreads = this->GetNumberOfThreads();
PixelType minimum;
PixelType maximum;
RealType mean;
RealType sigma;
RealType variance;
RealType sum;
sum = sumOfSquares = NumericTraits<RealType>::Zero;
count = 0;
// Find the min/max over all threads and accumulate count, sum and
// sum of squares
minimum = NumericTraits<PixelType>::max();
maximum = NumericTraits<PixelType>::NonpositiveMin();
for( i = 0; i < numberOfThreads; i++)
{
count += m_Count[i];
sum += m_ThreadSum[i];
sumOfSquares += m_SumOfSquares[i];
if (m_ThreadMin[i] < minimum)
{
minimum = m_ThreadMin[i];
}
if (m_ThreadMax[i] > maximum)
{
maximum = m_ThreadMax[i];
}
}
// compute statistics
mean = sum / static_cast<RealType>(count);
// unbiased estimate
variance = (sumOfSquares - (sum*sum / static_cast<RealType>(count)))
/ (static_cast<RealType>(count) - 1);
sigma = vcl_sqrt(variance);
// Set the outputs
this->GetMinimumOutput()->Set( minimum );
this->GetMaximumOutput()->Set( maximum );
this->GetMeanOutput()->Set( mean );
this->GetSigmaOutput()->Set( sigma );
this->GetVarianceOutput()->Set( variance );
this->GetSumOutput()->Set( sum );
}
template<class TInputImage>
void
StatisticsImageFilter<TInputImage>
::ThreadedGenerateData(const RegionType& outputRegionForThread,
int threadId)
{
RealType realValue;
PixelType value;
ImageRegionConstIterator<TInputImage> it (this->GetInput(), outputRegionForThread);
// support progress methods/callbacks
ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
// do the work
while (!it.IsAtEnd())
{
value = it.Get();
realValue = static_cast<RealType>( value );
if (value < m_ThreadMin[threadId])
{
m_ThreadMin[threadId] = value;
}
if (value > m_ThreadMax[threadId])
{
m_ThreadMax[threadId] = value;
}
m_ThreadSum[threadId] += realValue;
m_SumOfSquares[threadId] += (realValue * realValue);
m_Count[threadId]++;
++it;
progress.CompletedPixel();
}
}
template <class TImage>
void
StatisticsImageFilter<TImage>
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
os << indent << "Minimum: "
<< static_cast<typename NumericTraits<PixelType>::PrintType>(this->GetMinimum()) << std::endl;
os << indent << "Maximum: "
<< static_cast<typename NumericTraits<PixelType>::PrintType>(this->GetMaximum()) << std::endl;
os << indent << "Sum: " << this->GetSum() << std::endl;
os << indent << "Mean: " << this->GetMean() << std::endl;
os << indent << "Sigma: " << this->GetSigma() << std::endl;
os << indent << "Variance: " << this->GetVariance() << std::endl;
}
}// end namespace itk
#endif
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