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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 itkCovarianceSampleFilter_h
#define itkCovarianceSampleFilter_h
#include "itkProcessObject.h"
#include "itkVariableSizeMatrix.h"
#include "itkSimpleDataObjectDecorator.h"
namespace itk
{
namespace Statistics
{
/** \class CovarianceSampleFilter
* \brief Calculates the covariance matrix of the target sample data.
*
* The filter calculates first the sample mean and use it in the covariance
* calculation. The covariance is computed 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 component of the \f$\vec\mu\f$,
* and the \f$\sigma_{ij}\f$ is the \f$ij\f$th component \f$\Sigma\f$,
* \f$\sigma_{ij} = (x_{i} - \mu_{i})(x_{j} - \mu_{j})\f$
*
* This estimator is an unbiased one, because it divisor in the covariance
* computation takes into account that one degree of freedom has been taken
* for computing the mean.
*
* Without the plugged in mean vector, this calculator will perform
* the single pass mean and covariance calculation algorithm.
*
* \ingroup ITKStatistics
*/
template< typename TSample >
class ITK_TEMPLATE_EXPORT CovarianceSampleFilter:
public ProcessObject
{
public:
/** Standard class typedefs. */
typedef CovarianceSampleFilter Self;
typedef ProcessObject Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
typedef TSample SampleType;
/** Standard Macros */
itkTypeMacro(CovarianceSampleFilter, ProcessObject);
itkNewMacro(Self);
/** Type of each measurement vector in sample */
typedef typename SampleType::MeasurementVectorType MeasurementVectorType;
/** Type of the length of each measurement vector */
typedef typename SampleType::MeasurementVectorSizeType MeasurementVectorSizeType;
/** Type of measurement vector component value */
typedef typename SampleType::MeasurementType MeasurementType;
/** Type of a measurement vector, holding floating point values */
typedef typename NumericTraits< MeasurementVectorType >::RealType MeasurementVectorRealType;
/** Type of a floating point measurement component value */
typedef typename NumericTraits< MeasurementType >::RealType MeasurementRealType;
/** Method to set the sample */
using Superclass::SetInput;
void SetInput(const SampleType *sample);
/** Method to get the sample */
const SampleType * GetInput() const;
/** Type of covariance matrix output */
typedef VariableSizeMatrix< MeasurementRealType > MatrixType;
/** Return the covariance matrix */
const MatrixType GetCovarianceMatrix() const;
/** VariableSizeMatrix is not a DataObject, we need to decorate it to push it down
* a ProcessObject's pipeline */
typedef SimpleDataObjectDecorator< MatrixType > MatrixDecoratedType;
const MatrixDecoratedType * GetCovarianceMatrixOutput() const;
/** Return the mean vector */
const MeasurementVectorRealType GetMean() const;
/** MeasurementVector is not a DataObject, we need to decorate it to push it down
* a ProcessObject's pipeline */
typedef SimpleDataObjectDecorator< MeasurementVectorRealType > MeasurementVectorDecoratedType;
const MeasurementVectorDecoratedType * GetMeanOutput() const;
typedef MeasurementVectorDecoratedType OutputType;
MeasurementVectorSizeType GetMeasurementVectorSize() const;
protected:
CovarianceSampleFilter();
virtual ~CovarianceSampleFilter() ITK_OVERRIDE;
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** DataObject pointer */
typedef DataObject::Pointer DataObjectPointer;
typedef ProcessObject::DataObjectPointerArraySizeType DataObjectPointerArraySizeType;
using Superclass::MakeOutput;
virtual DataObjectPointer MakeOutput(DataObjectPointerArraySizeType idx) ITK_OVERRIDE;
virtual void GenerateData() ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(CovarianceSampleFilter);
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCovarianceSampleFilter.hxx"
#endif
#endif
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