Proposals:Statistics Framework Runtime Vector Size: Difference between revisions
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= Rationale for having compile time length = | = Rationale for having compile time length = | ||
The statistics classes in ITK have MeasurementVectorSize (length of each measurement vector) as a static const value. This has until now been sufficient since typical statistics operations involve sampling an image where the number of measurement vectors is a variable, but the measurement vector size is usually fixed and depends on the dimension of the parametric space. | |||
For algorithms such as Normalized cuts and other Kernel PCA feature space projection techniques, it may be necessary to keep the dimensionality of the feature space as a variable. This requires removing MeasurementVectorSize as a static method and making it an iVar. | |||
= Rationale for having run time length = | = Rationale for having run time length = | ||
Revision as of 20:21, 5 July 2005
Refactoring the Statistics Framework to have Runtime Length
Currently, the Statistics Framework requires the MeasurementVector to have a length defined at compile time.
Rationale for having compile time length
The statistics classes in ITK have MeasurementVectorSize (length of each measurement vector) as a static const value. This has until now been sufficient since typical statistics operations involve sampling an image where the number of measurement vectors is a variable, but the measurement vector size is usually fixed and depends on the dimension of the parametric space.
For algorithms such as Normalized cuts and other Kernel PCA feature space projection techniques, it may be necessary to keep the dimensionality of the feature space as a variable. This requires removing MeasurementVectorSize as a static method and making it an iVar.
