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virtual int | IsA (const char *type) |
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vtkMultiCorrelativeStatistics * | NewInstance () const |
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virtual void | PrintSelf (ostream &os, vtkIndent indent) |
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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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| vtkMultiCorrelativeStatistics () |
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| ~vtkMultiCorrelativeStatistics () |
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virtual void | Derive (vtkMultiBlockDataSet *) |
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virtual void | Learn (vtkTable *, vtkTable *, vtkMultiBlockDataSet *) |
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virtual void | Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
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virtual void | Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
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virtual void | SelectAssessFunctor (vtkTable *inData, 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 multivariate linear correlation.
Given a selection of sets of columns of interest, this class provides the following functionalities, depending on the operation in which it is executed: Learn: calculates means, unbiased variance and covariance estimators of column pairs coefficient. More precisely, Learn calculates the averages and centered variance/covariance sums; if finalize
is set to true (default), the final statistics are calculated. The output metadata on port OUTPUT_MODEL is a multiblock dataset containing at a minimum one vtkTable holding the raw sums in a sparse matrix style. If finalize is true, then one additional vtkTable will be present for each requested set of column correlations. These additional tables contain column averages, the upper triangular portion of the covariance matrix (in the upper right hand portion of the table) and the Cholesky decomposition of the covariance matrix (in the lower portion of the table beneath the covariance triangle). The leftmost column will be a vector of column averages. The last entry in the column averages vector is the number of samples. As an example, consider a request for a 3-column correlation with columns named ColA, ColB, and ColC. The resulting table will look like this:
Column |Mean |ColA |ColB |ColC
--------+---------+---------+---------+---------
ColA |avg(A) |cov(A,A) |cov(A,B) |cov(A,C)
ColB |avg(B) |chol(1,1)|cov(B,B) |cov(B,C)
ColC |avg(C) |chol(2,1)|chol(2,2)|cov(C,C)
Cholesky|length(A)|chol(3,1)|chol(3,2)|chol(3,3)
Assess: given a set of results matrices as specified above in input port INPUT_MODEL and tabular data on input port INPUT_DATA that contains column names matching those of the tables on input port INPUT_MODEL, the assess mode computes the relative deviation of each observation in port INPUT_DATA's table according to the linear correlations implied by each table in port INPUT_MODEL.
- Thanks:
- Thanks to Philippe Pebay, Jackson Mayo, and David Thompson of Sandia National Laboratories for implementing this class. Updated by Philippe Pebay, Kitware SAS 2012
- Tests:
- vtkMultiCorrelativeStatistics (Tests)
Definition at line 75 of file vtkMultiCorrelativeStatistics.h.