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virtual int | IsA (const char *type) |
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vtkAutoCorrelativeStatistics * | NewInstance () const |
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void | PrintSelf (ostream &os, vtkIndent indent) |
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virtual void | SetSliceCardinality (vtkIdType) |
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virtual vtkIdType | GetSliceCardinality () |
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virtual void | Aggregate (vtkDataObjectCollection *, vtkMultiBlockDataSet *) |
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vtkStatisticsAlgorithm * | NewInstance () const |
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void | PrintSelf (ostream &os, vtkIndent indent) |
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virtual void | SetColumnStatus (const char *namCol, int status) |
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virtual void | ResetAllColumnStates () |
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virtual int | RequestSelectedColumns () |
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virtual void | ResetRequests () |
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virtual vtkIdType | GetNumberOfRequests () |
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virtual vtkIdType | GetNumberOfColumnsForRequest (vtkIdType request) |
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void | AddColumn (const char *namCol) |
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void | AddColumnPair (const char *namColX, const char *namColY) |
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virtual void | SetLearnOptionParameterConnection (vtkAlgorithmOutput *params) |
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virtual void | SetLearnOptionParameters (vtkDataObject *params) |
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virtual void | SetInputModelConnection (vtkAlgorithmOutput *model) |
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virtual void | SetInputModel (vtkDataObject *model) |
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virtual void | SetLearnOption (bool) |
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virtual bool | GetLearnOption () |
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virtual void | SetDeriveOption (bool) |
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virtual bool | GetDeriveOption () |
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virtual void | SetAssessOption (bool) |
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virtual bool | GetAssessOption () |
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virtual void | SetTestOption (bool) |
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virtual bool | GetTestOption () |
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virtual void | SetNumberOfPrimaryTables (vtkIdType) |
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virtual vtkIdType | GetNumberOfPrimaryTables () |
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virtual void | SetAssessNames (vtkStringArray *) |
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virtual vtkStringArray * | GetAssessNames () |
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virtual const char * | GetColumnForRequest (vtkIdType r, vtkIdType c) |
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virtual int | GetColumnForRequest (vtkIdType r, vtkIdType c, vtkStdString &columnName) |
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virtual bool | SetParameter (const char *parameter, int index, vtkVariant value) |
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virtual vtkObjectBase * | NewInstanceInternal () const |
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| vtkAutoCorrelativeStatistics () |
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| ~vtkAutoCorrelativeStatistics () |
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virtual void | Derive (vtkMultiBlockDataSet *) |
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virtual vtkDoubleArray * | CalculatePValues (vtkDoubleArray *) |
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virtual void | Learn (vtkTable *, vtkTable *, vtkMultiBlockDataSet *) |
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virtual void | Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
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virtual void | Assess (vtkTable *inData, vtkMultiBlockDataSet *inMeta, vtkTable *outData) |
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virtual void | SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc) |
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| vtkStatisticsAlgorithm () |
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| ~vtkStatisticsAlgorithm () |
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virtual int | FillInputPortInformation (int port, vtkInformation *info) |
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virtual int | FillOutputPortInformation (int port, vtkInformation *info) |
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virtual int | RequestData (vtkInformation *, vtkInformationVector **, vtkInformationVector *) |
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void | Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *, int) |
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A class for univariate auto-correlative statistics.
Given a selection of columns of interest in an input data table, this class provides the following functionalities, depending on the chosen execution options: Learn: calculate sample mean and M2 aggregates for each variable w.r.t. itself (cf. P. Pebay, Formulas for robust, one-pass parallel computation of covariances and Arbitrary-Order Statistical Moments, Sandia Report SAND2008-6212, Sep 2008, http://infoserve.sandia.gov/sand_doc/2008/086212.pdf for details) for each specified time lag. Derive: calculate unbiased autocovariance matrix estimators and its determinant, linear regressions, and Pearson correlation coefficient, for each specified time lag. Assess: given an input data set, two means and a 2x2 covariance matrix, mark each datum with corresponding relative deviation (2-dimensional Mahlanobis distance).
- Thanks:
- This class was written by Philippe Pebay, Kitware SAS 2012
- Tests:
- vtkAutoCorrelativeStatistics (Tests)
Definition at line 54 of file vtkAutoCorrelativeStatistics.h.