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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkWeightedCovarianceSampleFilter_h
#define itkWeightedCovarianceSampleFilter_h
#include "itkFunctionBase.h"
#include "itkCovarianceSampleFilter.h"
#include "itkDataObjectDecorator.h"
namespace itk
{
namespace Statistics
{
/**
* \class WeightedCovarianceSampleFilter
* \brief Calculates the covariance matrix of the target sample data.
* where each measurement vector has an associated weight value
*
* Weight values can be specified in two ways: using a weighting function
* or an array containing weight values. If none of these two is specified,
* the covariance matrix is generated with equal weights.
*
* \sa CovarianceSampleFilter
*
* \ingroup ITKStatistics
*/
template <typename TSample>
class ITK_TEMPLATE_EXPORT WeightedCovarianceSampleFilter : public CovarianceSampleFilter<TSample>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(WeightedCovarianceSampleFilter);
/** Standard class type aliases. */
using Self = WeightedCovarianceSampleFilter;
using Superclass = CovarianceSampleFilter<TSample>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(WeightedCovarianceSampleFilter);
itkNewMacro(Self);
/** Types derived from the base class */
using typename Superclass::SampleType;
using typename Superclass::MeasurementVectorType;
using typename Superclass::MeasurementVectorSizeType;
using typename Superclass::MeasurementType;
/** Types derived from the base class */
using typename Superclass::MeasurementVectorRealType;
using typename Superclass::MeasurementRealType;
/** Type of weight values */
using WeightValueType = double;
/** Array type for weights */
using WeightArrayType = Array<WeightValueType>;
/** Type of DataObjects to use for the weight array type */
using InputWeightArrayObjectType = SimpleDataObjectDecorator<WeightArrayType>;
/** Method to set the input value of the weight array */
itkSetGetDecoratedInputMacro(Weights, WeightArrayType);
/** Weight calculation function type */
using WeightingFunctionType = FunctionBase<MeasurementVectorType, WeightValueType>;
/** Type of DataObjects to use for Weight function */
using InputWeightingFunctionObjectType = DataObjectDecorator<WeightingFunctionType>;
/** Method to set/get the weighting function */
itkSetGetDecoratedObjectInputMacro(WeightingFunction, WeightingFunctionType);
/** Types derived from the base class */
using typename Superclass::MatrixType;
using typename Superclass::MatrixDecoratedType;
/** Types derived from the base class */
using typename Superclass::MeasurementVectorDecoratedType;
using typename Superclass::OutputType;
protected:
WeightedCovarianceSampleFilter();
~WeightedCovarianceSampleFilter() override = default;
void
GenerateData() override;
/** Compute covariance matrix with weights computed from a function */
void
ComputeCovarianceMatrixWithWeightingFunction();
/** Compute covariance matrix with weights specified in an array */
void
ComputeCovarianceMatrixWithWeights();
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkWeightedCovarianceSampleFilter.hxx"
#endif
#endif
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