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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkCovarianceCalculator.h
Language: C++
Date: $Date$
Version: $Revision$
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 __itkCovarianceCalculator_h
#define __itkCovarianceCalculator_h
#include "itkSampleAlgorithmBase.h"
#include "itkArray.h"
#include "itkVariableSizeMatrix.h"
namespace itk {
namespace Statistics {
/** \class CovarianceCalculator
* \brief Calculates the covariance matrix of the target sample data.
*
* If there is a mean vector provided by the SetMean method, this
* calculator will do the caculation as follows:
* Let \f$\Sigma\f$ denotes covariance matrix for the sample, then:
* When \f$x_{i}\f$ is \f$i\f$th component of a measurement vector
* \f$\vec x\f$, \f$\mu_{i}\f$ is the \f$i\f$th componet of the \f$\vec\mu\f$,
* and the \f$\sigma_{ij}\f$ is the \f$ij\f$th componet \f$\Sigma\f$,
* \f$\sigma_{ij} = (x_{i} - \mu_{i})(x_{j} - \mu_{j})\f$
*
* Without the plugged in mean vector, this calculator will perform
* the single pass mean and covariance calculation algorithm.
*
* Recent API changes:
* The static const macro to get the length of a measurement vector,
* 'MeasurementVectorSize' has been removed to allow the length of a measurement
* vector to be specified at run time. It is now obtained from the input sample.
* Please use the function GetMeasurementVectorSize() to obtain the length.
* The mean output is an Array rather than a Vector. The covariance matrix is
* represented by a VariableSizeMatrix rather than a Matrix.
*/
template< class TSample >
class CovarianceCalculator :
public SampleAlgorithmBase< TSample >
{
public:
/** Standard class typedefs. */
typedef CovarianceCalculator Self;
typedef SampleAlgorithmBase< TSample > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Standard Macros */
itkTypeMacro(CovarianceCalculator, SampleAlgorithmBase);
itkNewMacro(Self);
/** Length of a measurement vector */
typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;
/** Measurement vector type */
typedef typename Superclass::MeasurementVectorType MeasurementVectorType;
/** Typedef for the mean output */
typedef Array< double > MeanType;
/** Typedef for Covariance output */
typedef VariableSizeMatrix< double > OutputType;
/** Stores the sample pointer */
void SetMean( MeanType* mean );
/** Returns the sample pointer */
MeanType* GetMean( void );
/** Returns the covariance matrix of the target sample data */
const OutputType * GetOutput( void ) const;
protected:
CovarianceCalculator();
virtual ~CovarianceCalculator();
void PrintSelf(std::ostream& os, Indent indent) const;
/** Calculates the covariance and save it. This method calls
* ComputeCovarianceWithGivenMean, if the user provides mean vector
* using SetMean method. Otherwise, it calls
* ComputeCovarianceWithoutGivenMethod depending on */
void GenerateData( void );
/** Calculates the covariance matrix using the given mean */
void ComputeCovarianceWithGivenMean( void );
/** Calculates the covariance matrix and the mean in a single pass */
void ComputeCovarianceWithoutGivenMean( void );
private:
MeanType* m_Mean;
MeanType* m_InternalMean;
OutputType m_Output;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCovarianceCalculator.txx"
#endif
#endif
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