ITK  4.13.0
Insight Segmentation and Registration Toolkit
Examples/Statistics/Histogram.cxx
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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.
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*=========================================================================*/
// Software Guide : BeginLatex
//
// This example shows how to create an \subdoxygen{Statistics}{Histogram}
// object and use it.
//
// \index{itk::Sample!Histogram}
//
// We call an instance in a \code{Histogram} object a \emph{bin}. The
// Histogram differs from the
// \subdoxygen{Statistics}{ListSample},
// \subdoxygen{Statistics}{ImageToListSampleAdaptor}, or
// \subdoxygen{Statistics}{PointSetToListSampleAdaptor} in significant ways.
// Histograms can have a variable number of values (\code{float}
// type) for each measurement vector, while the three other classes
// have a fixed value (one) for all measurement vectors. Also
// those array-type containers can have multiple instances (data
// elements) with identical measurement vector values. However,
// in a Histogram object, there is one unique instance for any
// given measurement vector.
//
// \begin{figure}
// \centering
// \includegraphics[width=0.4\textwidth]{Histogram}
// \itkcaption[Histogram]{Conceptual histogram data structure.}
// \protect\label{fig:StatHistogram}
// \end{figure}
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkHistogram.h"
// Software Guide : EndCodeSnippet
int main()
{
// Software Guide : BeginLatex
//
// Here we create a histogram with dense frequency containers. In
// this example we will not have any zero-frequency measurements,
// so the dense frequency container is the appropriate choice. If
// the histogram is expected to have many empty (zero) bins, a sparse
// frequency container would be the better option. Here we also set
// the size of the measurement vectors to be 2 components.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef float MeasurementType;
typedef itk::Statistics::DenseFrequencyContainer2 FrequencyContainerType;
typedef FrequencyContainerType::AbsoluteFrequencyType FrequencyType;
const unsigned int numberOfComponents = 2;
typedef itk::Statistics::Histogram< MeasurementType,
FrequencyContainerType > HistogramType;
HistogramType::Pointer histogram = HistogramType::New();
histogram->SetMeasurementVectorSize( numberOfComponents );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We initialize it as a $3\times3$ histogram with equal size intervals.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
HistogramType::SizeType size( numberOfComponents );
size.Fill(3);
HistogramType::MeasurementVectorType lowerBound( numberOfComponents );
HistogramType::MeasurementVectorType upperBound( numberOfComponents );
lowerBound[0] = 1.1;
lowerBound[1] = 2.6;
upperBound[0] = 7.1;
upperBound[1] = 8.6;
histogram->Initialize(size, lowerBound, upperBound );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Now the histogram is ready for storing frequency values. We will
// fill each bin's frequency according to the Figure
// \ref{fig:StatHistogram}. There are three ways of accessing data
// elements in the histogram:
// \begin{itemize}
// \item using instance identifiers---just like any other Sample object;
// \item using n-dimensional indices---just like an Image object;
// \item using an iterator---just like any other Sample object.
// \end{itemize}
// In this example, the index $(0, 0)$ refers the same bin as the instance
// identifier (0) refers to. The instance identifier of the index (0,
// 1) is (3), (0, 2) is (6), (2, 2) is (8), and so on.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
histogram->SetFrequency(0UL, static_cast<FrequencyType>(0.0));
histogram->SetFrequency(1UL, static_cast<FrequencyType>(2.0));
histogram->SetFrequency(2UL, static_cast<FrequencyType>(3.0));
histogram->SetFrequency(3UL, static_cast<FrequencyType>(2.0f));
histogram->SetFrequency(4UL, static_cast<FrequencyType>(0.5f));
histogram->SetFrequency(5UL, static_cast<FrequencyType>(1.0f));
histogram->SetFrequency(6UL, static_cast<FrequencyType>(5.0f));
histogram->SetFrequency(7UL, static_cast<FrequencyType>(2.5f));
histogram->SetFrequency(8UL, static_cast<FrequencyType>(0.0f));
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Let us examine if the frequency is set correctly by calling the
// \code{GetFrequency(index)} method. We can use the
// \code{GetFrequency(instance identifier)} method for the same purpose.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
HistogramType::IndexType index( numberOfComponents );
index[0] = 0;
index[1] = 2;
std::cout << "Frequency of the bin at index " << index
<< " is " << histogram->GetFrequency(index)
<< ", and the bin's instance identifier is "
<< histogram->GetInstanceIdentifier(index) << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// For test purposes, we create a measurement vector and an index
// that belongs to the center bin.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
HistogramType::MeasurementVectorType mv( numberOfComponents );
mv[0] = 4.1;
mv[1] = 5.6;
index.Fill(1);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We retrieve the measurement vector at the index value (1, 1), the center
// bin's measurement vector. The output is [4.1, 5.6].
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
std::cout << "Measurement vector at the center bin is "
<< histogram->GetMeasurementVector(index) << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Since all the measurement vectors are unique in the Histogram class, we
// can determine the index from a measurement vector.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
HistogramType::IndexType resultingIndex;
histogram->GetIndex(mv,resultingIndex);
std::cout << "Index of the measurement vector " << mv
<< " is " << resultingIndex << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// In a similar way, we can get the instance identifier from the index.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
std::cout << "Instance identifier of index " << index
<< " is " << histogram->GetInstanceIdentifier(index)
<< std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// If we want to check if an index is valid, we use the method
// \code{IsIndexOutOfBounds(index)}. The following code snippet fills the
// index variable with (100, 100). It is obviously not a valid index.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
index.Fill(100);
if ( histogram->IsIndexOutOfBounds(index) )
{
std::cout << "Index " << index << " is out of bounds." << std::endl;
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The following code snippets show how to get the histogram size
// and frequency dimension.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
std::cout << "Number of bins = " << histogram->Size()
<< " Total frequency = " << histogram->GetTotalFrequency()
<< " Dimension sizes = " << histogram->GetSize() << std::endl;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The Histogram class has a quantile calculation method,
// \code{Quantile(dimension, percent)}. The following code returns the 50th
// percentile along the first dimension. Note that the quantile calculation
// considers only one dimension.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
std::cout << "50th percentile along the first dimension = "
<< histogram->Quantile(0, 0.5) << std::endl;
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}