Proposals:Refactoring Statistics Framework 2007 Migration Users Guide

How To Migrate your code to the New Statistics Framework

Measurement Containers



Class Name	Fate	Deprecated API	New API
Sample	Refactored	Does not derives from Object anymore, now it derives from DataObject. typedef for InstanceIdentifier was replaced from unsigned long to std::vector<MeasurementVectorType>::size_type Size() method now returns InstanceIdentifier type, before it returned unsigned int, which was inconsistent with the declaration of InstanceIdentifier as unsigned long. The return type of Size() must be the same use for Id of the elements, since it may reach the same maximum number. Removing unnecessary const in identifiers GetMeasurementVector( const InstanceItentifier & id ) is now GetMeasurementVector( InstanceItentifier id ) GetFrequency( const InstanceItentifier & id ) is now GetFrequency( InstanceItentifier id ) SetMeasurementVectorSize( const MeasurementVectorSizeType s ) is now SetMeasurementVectorSize( MeasurementVectorSizeType s )	const-correctness is now enforced. It now derives from DataObject
Subsample	Refactored	The concept of Indices and InstanceIdentifiers was fixed. InstanceIdentifiers were previously referring to the original Sample, they are now referring to the current Subsample set of measurement vectors. It now derives from its template argument. Before, it was deriving from an explicit itk::Statistics::Sample<> whose template argument MeasurementVector was taken as a trait from the Subsample template argument. The current derivation is more consistent with the notion that the Subsample should behave as the sample from which the instances are taken. FrequencyType GetFrequencyByIndex(int index) const : was removed. This method becomes obsolete when the inconsistencies between index and identifier are removed. InstanceIdentifier GetInstanceIdentifier(int index) const; was removed. This method becomes obsolete when the inconsistencies between index and identifier are removed. Iterators Common GetInstanceIdentifier() now returns the integer distance to the Begin() element. Before it used to return the index of the instance in the real sample. Iterator& operator+(int n) and Iterator& operator-(int n) were removed. The methods were not used, and they were not consistent with other containers. They were also unsafe, given that with Begin() and End() there is no way to verify if an iterator has moved before Begin() or after End() (unless we rely on being aware of the underlying pointer implementation of the Iterators, which would be a violation of the class encapsulation). Constructor ConstIterator(typename InstanceIdentifierHolder::const_iterator iter, const Self* classSample) was made protected, since this constructor must only be called by the Sample owner class. ConstIterator removing Friendship to the Iterator non-const Iterator removing Friendship to the ConstIterator	The basic principle followed now in the design of the Subsample class is that the subsample should behave as a sample. That is, a user should be able to use a Subsample class in any algorithm that is expecting a Sample. AddInstance( InsitanceIdentifier Id ) Now throws an exception if the Id is larger than the Size of the Sample. Now it calls Modified() Iterators Now the non-const Iterator derives from the ConstIterator Methods declared protected and purposely not implemented Default constructor: This was a safety risk since it contained uninitialized variables The following method are in this category to enforce const correctness. All of them could have offered ways of removing constness without warning Iterator(const Self * sample); Iterator(typename InstanceIdentifierHolder::const_iterator iter, const Self* classSample); Iterator(const ConstIterator & it); ConstIterator& operator=(const ConstIterator& it);
ListSampleBase	Deprecated. The class was unecessary, it was providing only a Search() method that should in fact be provided by a process class, not a data container.	If you were deriving a class from the itk::Statistics::ListSampleBase, you should now derive directly from the itk::Statistics::Sample class. If you were using the Search() method you can get that functionality now from the (refactored) NeighborhoodSampler filter class. Note that the NeighborhoodSampler now allows users to setup a specific distance metric.
ListSample	Refactored Luis to add more here	The iterators API was updated, const-correctness is now enforced
MembershipSample	Refactoring in Progress Luis	It does not derive from itk::Sample anymore, instead it derives from DataObject.
Histogram	Refactored Luis to add more here
VariableDimensionHistogram	Pending
KdTree	Pending

Frequency Containers

Class Name	Fate	Deprecated API	New API
DenseFrequencyContainer
SparseFrequencyContainer

Process Objects

Class Name	Fate	Deprecated API	New API
SampleClassifier
SampleClassifierWithMask

Traits

Class Name	Fate	Deprecated API	New API
MeasurementVectorTraits	Refactored (same name)		Added Assert() instantiations for comparing length of FixedArray raw pointer, std::vector raw pointer FixedArray reference, std::vector reference Added Assign() method for generalizing the assignment of scalars and vector types Assign() vectorType to vectorType Assign() scalarType to FixedArray< scalarType, 1 > Added trait MeasurementVectorType to be used as MeasurementVectorPixelTraits< PixelType >::MeasurementVectorType This trait generalizes the mechanism for creating a measurement vector using as component type the pixel type of an image Added explicit testing up to 100% code coverage

MeanShift

Class Name	Fate	Deprecated API	New API

Adaptors

Class Name	Fate	Deprecated API	New API
ImageToCoocurrenceListAdaptor	UNDECIDED
ImageToListAdaptor	Refactored into "ImageToListSampleAdaptor". This class handles images with scalar, fixed size array (itk::FixedArray) and variable length vector (itk::VariableLengthVector) pixel types.	The class is not derived from ListSampleBase any more since ListSampleBase has been deprecated The second template parameter ( MeasurementVectorType ) is removed since it is redundant. The measurement vector type is determined from the input Image type using the newly added MeasurementVectorPixelTraits. GetUseBuffer() : This method is renamed as GetUsePointContainer(). The term "buffer" is misleading. This flag is used in the class to differentiate between accessing the pixel value directly from the pixel container or using GetPixel(Index) method after computing the index for the given id using ComputeIndex() method. In addition to the Get method, Set methods have been added as indicated in the new API column.	The class derives from ListSample with the measurement vector type determined from the input image type The Iterator and ConstIterator API is modified to be consistent with the iterator and constiterators of the ListSample class. Added SetUsePixelContainer( bool ) : To turn on and off the UsePixelContainer flag. Added UsePixelContainerOn(), UsePixelContainerOff() : convenient methods to turn on/off the UsePixelContainer flag.
ScalarImageToListAdaptor	Deprecated ( This class is redundant as the new ImageToListSampleAdaptor also handles scalar images with scalar pixel type. )
JointDomainImageToListAdaptor	Refactored into "JointDomainImageToListSampleAdaptor"	The class is not derived from the ImageToListSampleAdaptor. This design decision was made due to the new changes in the ImageToListSample adaptor to handle different pixel types ( scalar, Fixed length array, variable length vector). Search() method is removed. This class is not the appropriate place for such functionality.	Iterator and ConstIterator API added. (This was missing in the old API )
PointSetToListAdapor	Refactored into "PointSetToListSampleAdaptor"	The class is not derived from ListSampleBase any more since ListSampleBase has been deprecated	The class derives from ListSample with the measurement vector type determined from the point set type. GetPointSet() returns a const PointSet ( constant correctness ) GetSize() returns InstanceIdentifer type ( to have a consistent signature with the superclass ) The Iterator and ConstIterator API is modified to be consistent with the iterator and constiterators of the ListSample class.

Univariate Distributions

Class Name	Fate	Deprecated API	New API

Algorithms

Class Name	Fate	Deprecated API	New API

Calculators

Class Name	Fate	Deprecated API	New API
MeanCalculator	Refactored into MeanFilter	SetSample() method replaced with SetInput() GetOutput() method return type modified ( the new signature returns a data object decorator )	Derives from ProcessObject and the following methods added to integrate the class into the pipeline SetInput() GetOutput() (returns a data object decorated type of the mean vector ) GetMean() (returns the mean vector as it is without any decoration )
WeightedMeanCalculator	Refactored into WeightedMeanFilter	SetSample() method replaced with SetInput() SetWeights() method input argument modified ( the new signature takes dataobject decorated weight array) SetWeightFunction() method replaced with SetWeightingFunction() GetWeights() method return type modified ( new signature returns a data object decorator of the weight array) GetWeightingFunction() method replaced with GetWeightingFunction() GetOutput() method return type modified ( the new signature returns a data object decorator of the mean )	Derives from ProcessObject and the following methods added to integrate the class into the pipeline SetInput() GetOutput() (returns a data object decorated type of the mean vector ) SetWeights() (Takes dataObjecte decorated version of weight array type ) SetWeightingFunction (Takes dataObject decorated version of weighting function type )
CovarianceCalculator	Refactored into CovarianceFilter	SetMean() removed ( the mean will always be computed inside the class. Keeping track of mean computed internally and set from outside creates lots of inconsistencies in the pipeline). SetSample() replaced with SetInput() GetOutput() replaced with GetCovarianceMatrixOutput() which returns a decorated version of the covariance matrix	Derived from process object and the following methods added to integrate the class into the pipeline SetInput() GetMeanOutput() ( returns a decorated version of the mean vector ) GetCovarianceMatrixOutput() ( returns a decorated version of the covariance matrix )
WeightedCovarianceCalculator	Refactored into WeightedCovarianceFilter	SetSample() method replaced with SetInput() SetWeights() method input argument modified ( the new signature takes dataobject decorated weight array) SetWeightFunction() method replaced with SetWeightingFunction() GetWeights() method return type modified ( new signature returns a data object decorator of the weight array) GetWeightingFunction() method replaced with GetWeightingFunction()	Derives from itk::CovarianceFilter and all the methods defined in the CovarianceFilter for pipeline integration (SetInput(), GetMeanOutput(), GetCovarianceMatrixOutput() )should be used SetWeights() (Takes dataObjecte decorated version of weight array type ) SetWeightingFunction (Takes dataObject decorated version of weighting function type ) GetWeights() returns decorated version of the weight array GetWeightingFunction() returns decorated version of the weighting function
GreyLevelCooccurrenceMatrixTextureCoefficientsCalculator	Refactored into HistogramToTextureFeaturesFilter	Compute() removed ( Update() method should be used in the new API ) SetHistogram() removed ( replaced by SetInput() in the new API )	Derives from ProcessObject and the following methods added to integrate it to the pipeline SetInput() GenerateData() ( user should invoke Update() to compute the features ) Data object decorated versions of the Get methods for each feature was added. GetEnergyOutput() GetEntropyOutput() GetCorrelationOutput() GetInverseDifferenceMomentOutput() GetInertiaOutput() GetClusterShadeOutput() GetClusterProminenceOutput() GetHaralickCorrelationOutput()
ScalarImageTextureCalculator	To be Refactored into ScalarImageToTextureFeaturesFilter

Generators

Class Name	Fate	Deprecated API	New API
ListSampleToHistogramGenerator	Refactored into SampleToHistogramFilter
ImageToListGenerator	Refactored into ImageToListSampleFilter
ScalarImageToGreyLevelCooccurrenceMatrixGenerator	Refactored into ScalarImageToCooccurrenceMatrixFilter		derives from Process Object
MaskedScalarImageToGreyLevelCooccurrenceMatrixGenerator	Deprecated ( ScalarImageToCooccurrenceMatrixFilter accepts a mask image in addition to the input image )

Filters

Class Name	Fate	Deprecated API	New API
ListSampleToHistogramFilter

Multivariate Density Functions

Class Name	Fate	Deprecated API	New API

Distance Metrics

Class Name	Fate	Deprecated API	New API

Components

Class Name	Fate	Deprecated API	New API

Estimators

Class Name	Fate	Deprecated API	New API