ITK  6.0.0
Insight Toolkit
Examples/Statistics/NeighborhoodSampler.cxx
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*
* Copyright NumFOCUS
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* 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
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*
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// Software Guide : BeginLatex
//
// \index{Statistics!Sampling measurement vectors using radius}
// \index{itk::Statistics::NeighborhoodSampler}
//
// When we want to create an \subdoxygen{Statistics}{Subsample} object that
// includes only the measurement vectors within a radius from a center in a
// sample, we can use the \subdoxygen{Statistics}{NeighborhoodSampler}. In
// this example, we will use the \subdoxygen{Statistics}{ListSample} as the
// input sample.
//
// We include the header files for the ListSample and the
// NeighborhoodSampler classes.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkListSample.h"
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We need another header for measurement vectors. We are going to use the
// \doxygen{Vector} class which is a subclass of the \doxygen{FixedArray}.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkVector.h"
// Software Guide : EndCodeSnippet
int
main()
{
// Software Guide : BeginLatex
//
// The following code snippet will create a ListSample object
// with two-component int measurement vectors and put the measurement
// vectors: [1,1] - 1 time, [2,2] - 2 times, [3,3] - 3 times, [4,4] -
// 4 times, [5,5] - 5 times into the \code{listSample}.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using MeasurementType = int;
constexpr unsigned int MeasurementVectorLength = 2;
using MeasurementVectorType =
auto sample = SampleType::New();
sample->SetMeasurementVectorSize(MeasurementVectorLength);
MeasurementVectorType mv;
for (unsigned int i = 1; i < 6; ++i)
{
for (unsigned int j = 0; j < 2; ++j)
{
mv[j] = (MeasurementType)i;
}
for (unsigned int j = 0; j < i; ++j)
{
sample->PushBack(mv);
}
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We plug-in the sample to the NeighborhoodSampler using the
// \code{SetInputSample(sample*)}. The two required inputs for the
// NeighborhoodSampler are a center and a radius. We set these two inputs
// using the \code{SetCenter(center vector*)} and the
// \code{SetRadius(double*)} methods respectively. And then we call the
// \code{Update()} method to generate the Subsample object. This
// sampling procedure subsamples measurement vectors within a
// hyper-spherical kernel that has the center and radius specified.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
auto sampler = SamplerType::New();
sampler->SetInputSample(sample);
SamplerType::CenterType center(MeasurementVectorLength);
center[0] = 3;
center[1] = 3;
double radius = 1.5;
sampler->SetCenter(&center);
sampler->SetRadius(&radius);
sampler->Update();
SamplerType::OutputType::Pointer output = sampler->GetOutput();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The \code{SamplerType::OutputType} is in fact
// \subdoxygen{Statistics}{Subsample}. The following code prints out
// the resampled measurement vectors.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
SamplerType::OutputType::Iterator iter = output->Begin();
while (iter != output->End())
{
std::cout << "instance identifier = " << iter.GetInstanceIdentifier()
<< "\t measurement vector = " << iter.GetMeasurementVector()
<< "\t frequency = " << iter.GetFrequency() << std::endl;
++iter;
}
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}
Pointer
SmartPointer< Self > Pointer
Definition: itkAddImageFilter.h:93
itk::Vector
A templated class holding a n-Dimensional vector.
Definition: itkVector.h:62
itk::Statistics::ListSample
This class is the native implementation of the a Sample with an STL container.
Definition: itkListSample.h:51
itkListSample.h
itkVector.h
itkNeighborhoodSampler.h
New
static Pointer New()
itk::Statistics::NeighborhoodSampler
Generates a Subsample out of a Sample, based on a user-provided distance to a MeasurementVector.
Definition: itkNeighborhoodSampler.h:44