Proposals:Refactoring Statistics Framework 2007 Class Manifesto: Difference between revisions

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Line 279: Line 279:
StatisticsAlgorithm [shape=diamond,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1StatisticsAlgorithm.html"];
StatisticsAlgorithm [shape=diamond,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1StatisticsAlgorithm.html"];
NeigborhoodSampler [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1NeighborhoodSampler.html"];
NeigborhoodSampler [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1NeighborhoodSampler.html"];
Calculators  [label="Calculators \n see below"]
Object -> SampleAlgorithmBase;
Object -> SampleAlgorithmBase;
SampleAlgorithmBase -> NeigborhoodSampler;
SampleAlgorithmBase -> NeigborhoodSampler;
SampleAlgorithmBase -> Calculators;
}
}
</graphviz>
</graphviz>

Revision as of 15:18, 2 April 2007

Statistics Class Manifesto

Summary Table

They are categorized in the following table


Conceptual Class Number
Measurement Containers 8
Frequency Containers 2
Process Objects 2
Traits 1
Mean shift 3
Adaptors 5
Univariate Distributions 4
Algorithms 3
Calculators 6
Generators 12
Filters 10
Multivariate Density Functions 8
Distance Metrics 2
Components 4
Estimators 2
Total 72

List of Classes per Category

Measurement Containers



  • KdTree
  • Histogram
  • VariableDimensionHistogram
  • ListSampleBase
  • ListSample
  • Sample
  • Subsample
  • MembershipSample

Frequency Containers

  • DenseFrequencyContainer
  • SparseFrequencyContainer

Process Objects

  • SampleClassifier
  • SampleClassifierWithMask

Traits

  • MeasurementVectorTraits

MeanShift

  • HypersphereKernelMeanShiftModeSeeker
  • MeanShiftModeCacheMethod
  • MeanShiftModeSeekerBase

Adaptors

  • ImageToCooccurrenceListAdaptor
  • ImageToListAdaptor
  • JointDomainImageToListAdaptor
  • PointSetToListAdaptor
  • ScalarImageToListAdaptor

Univariate Distributions

  • ChiSquareDistribution
  • GaussianDistribution
  • ProbabilityDistribution
  • TDistribution

Algorithms

  • SampleAlgorithmBase
  • StatisticsAlgorithm
  • NeighborhoodSampler

Calculators

  • CovarianceCalculator
  • GreyLevelCooccurrenceMatrixTextureCoefficientsCalculator
  • MeanCalculator
  • ScalarImageTextureCalculator
  • WeightedCovarianceCalculator
  • WeightedMeanCalculator

Generators

  • ImageToHistogramGenerator
  • ImageToListGenerator
  • KdTreeGenerator
  • ListSampleToHistogramGenerator
  • MaskedScalarImageToGreyLevelCooccurrenceMatrixGenerator
  • MembershipSampleGenerator
  • NormalVariateGenerator
  • RandomVariateGeneratorBase
  • ScalarImageToGreyLevelCooccurrenceMatrixGenerator
  • ScalarImageToHistogramGenerator
  • SelectiveSubsampleGenerator
  • WeightedCentroidKdTreeGenerator

Filters

* HistogramToEntropyImageFilter

  • HistogramToImageFilter
  • HistogramToIntensityImageFilter
  • HistogramToLogProbabilityImageFilter
  • HistogramToProbabilityImageFilter
  • ListSampleToHistogramFilter
  • SampleMeanShiftBlurringFilter
  • SampleMeanShiftClusteringFilter
  • SampleSelectiveMeanShiftBlurringFilter
  • SampleToHistogramProjectionFilter

Multivariate Density Functions

* DensityFunction

  • DistanceToCentroidMembershipFunction
  • GaussianDensityFunction
  • GoodnessOfFitFunctionBase
  • GoodnessOfFitMixtureModelCostFunction
  • LogLikelihoodGoodnessOfFitFunction
  • MahalanobisDistanceMembershipFunction
  • MembershipFunctionBase

Distance Metrics

  • DistanceMetric
  • EuclideanDistance

Components

  • GaussianGoodnessOfFitComponent
  • GaussianMixtureModelComponent
  • GoodnessOfFitComponentBase
  • MixtureModelComponentBase

Estimators

  • ExpectationMaximizationMixtureModelEstimator
  • KdTreeBasedKmeansEstimator


Class Diagrams

Measurement Containers

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.


Frequency Containers

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Process Objects

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Traits

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

MeanShift

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Adaptors

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Univariate Distributions

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Algorithms

This is a graph with borders and nodes. Maybe there is an Imagemap used so the nodes may be linking to some Pages.

Calculators

Generators

Filters

Multivariate Density Functions

Distance Metrics

Components

Estimators

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