VTK
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A class for univariate descriptive statistics. More...
#include <vtkDescriptiveStatistics.h>
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typedef vtkStatisticsAlgorithm | Superclass |
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typedef vtkTableAlgorithm | Superclass |
enum | InputPorts { INPUT_DATA = 0, LEARN_PARAMETERS = 1, INPUT_MODEL = 2 } |
enum | OutputIndices { OUTPUT_DATA = 0, OUTPUT_MODEL = 1, ASSESSMENT = 2, OUTPUT_TEST = 2 } |
Public Member Functions | |
virtual int | IsA (const char *type) |
vtkDescriptiveStatistics * | NewInstance () const |
void | PrintSelf (ostream &os, vtkIndent indent) |
virtual void | SetUnbiasedVariance (int) |
virtual int | GetUnbiasedVariance () |
virtual void | UnbiasedVarianceOn () |
virtual void | UnbiasedVarianceOff () |
virtual void | SetG1Skewness (int) |
virtual int | GetG1Skewness () |
virtual void | G1SkewnessOn () |
virtual void | G1SkewnessOff () |
virtual void | SetG2Kurtosis (int) |
virtual int | GetG2Kurtosis () |
virtual void | G2KurtosisOn () |
virtual void | G2KurtosisOff () |
virtual void | SetSignedDeviations (int) |
virtual int | GetSignedDeviations () |
virtual void | SignedDeviationsOn () |
virtual void | SignedDeviationsOff () |
virtual void | Aggregate (vtkDataObjectCollection *, vtkMultiBlockDataSet *) |
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vtkStatisticsAlgorithm * | NewInstance () const |
void | PrintSelf (ostream &os, vtkIndent indent) |
virtual void | SetColumnStatus (const char *namCol, int status) |
virtual void | ResetAllColumnStates () |
virtual int | RequestSelectedColumns () |
virtual void | ResetRequests () |
virtual vtkIdType | GetNumberOfRequests () |
virtual vtkIdType | GetNumberOfColumnsForRequest (vtkIdType request) |
void | AddColumn (const char *namCol) |
void | AddColumnPair (const char *namColX, const char *namColY) |
virtual void | SetLearnOptionParameterConnection (vtkAlgorithmOutput *params) |
virtual void | SetLearnOptionParameters (vtkDataObject *params) |
virtual void | SetInputModelConnection (vtkAlgorithmOutput *model) |
virtual void | SetInputModel (vtkDataObject *model) |
virtual void | SetLearnOption (bool) |
virtual bool | GetLearnOption () |
virtual void | SetDeriveOption (bool) |
virtual bool | GetDeriveOption () |
virtual void | SetAssessOption (bool) |
virtual bool | GetAssessOption () |
virtual void | SetTestOption (bool) |
virtual bool | GetTestOption () |
virtual void | SetNumberOfPrimaryTables (vtkIdType) |
virtual vtkIdType | GetNumberOfPrimaryTables () |
virtual void | SetAssessNames (vtkStringArray *) |
virtual vtkStringArray * | GetAssessNames () |
virtual const char * | GetColumnForRequest (vtkIdType r, vtkIdType c) |
virtual int | GetColumnForRequest (vtkIdType r, vtkIdType c, vtkStdString &columnName) |
virtual bool | SetParameter (const char *parameter, int index, vtkVariant value) |
Static Public Member Functions | |
static int | IsTypeOf (const char *type) |
static vtkDescriptiveStatistics * | SafeDownCast (vtkObjectBase *o) |
static vtkDescriptiveStatistics * | New () |
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static int | IsTypeOf (const char *type) |
static vtkStatisticsAlgorithm * | SafeDownCast (vtkObjectBase *o) |
Protected Member Functions | |
virtual vtkObjectBase * | NewInstanceInternal () const |
vtkDescriptiveStatistics () | |
~vtkDescriptiveStatistics () | |
virtual void | Derive (vtkMultiBlockDataSet *) |
virtual vtkDoubleArray * | CalculatePValues (vtkDoubleArray *) |
virtual void | Learn (vtkTable *, vtkTable *, vtkMultiBlockDataSet *) |
virtual void | Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
virtual void | Assess (vtkTable *inData, vtkMultiBlockDataSet *inMeta, vtkTable *outData) |
virtual void | SelectAssessFunctor (vtkTable *outData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc) |
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vtkStatisticsAlgorithm () | |
~vtkStatisticsAlgorithm () | |
virtual int | FillInputPortInformation (int port, vtkInformation *info) |
virtual int | FillOutputPortInformation (int port, vtkInformation *info) |
virtual int | RequestData (vtkInformation *, vtkInformationVector **, vtkInformationVector *) |
void | Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *, int) |
Protected Attributes | |
int | UnbiasedVariance |
int | G1Skewness |
int | G2Kurtosis |
int | SignedDeviations |
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int | NumberOfPrimaryTables |
bool | LearnOption |
bool | DeriveOption |
bool | AssessOption |
bool | TestOption |
vtkStringArray * | AssessNames |
vtkStatisticsAlgorithmPrivate * | Internals |
A class for univariate descriptive statistics.
Private implementation for bivariate statistics algorithms.
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 extremal values, sample mean, and M2, M3, and M4 aggregates (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) Derive: calculate unbiased variance estimator, standard deviation estimator, two skewness estimators, and two kurtosis excess estimators. Assess: given an input data set, a reference value and a non-negative deviation, mark each datum with corresponding relative deviation (1-dimensional Mahlanobis distance). If the deviation is zero, then mark each datum which are equal to the reference value with 0, and all others with 1. By default, the reference value and the deviation are, respectively, the mean and the standard deviation of the input model. Test: calculate Jarque-Bera statistic and, if VTK to R interface is available, retrieve corresponding p-value for normality testing.
The main purpose of this class is to avoid exposure of STL container through the APIs of the vtkStatistics classes APIs
Definition at line 66 of file vtkDescriptiveStatistics.h.
Definition at line 69 of file vtkDescriptiveStatistics.h.
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Reimplemented from vtkStatisticsAlgorithm.
Reimplemented in vtkDescriptiveStatisticsGnuR, and vtkPDescriptiveStatistics.
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Reimplemented from vtkStatisticsAlgorithm.
Reimplemented in vtkDescriptiveStatisticsGnuR, and vtkPDescriptiveStatistics.
vtkDescriptiveStatistics* vtkDescriptiveStatistics::NewInstance | ( | ) | const |
void vtkDescriptiveStatistics::PrintSelf | ( | ostream & | os, |
vtkIndent | indent | ||
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Set/get whether the unbiased estimator for the variance should be used, or if the population variance will be calculated. The default is that the unbiased estimator will be used.
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Set/get whether the unbiased estimator for the variance should be used, or if the population variance will be calculated. The default is that the unbiased estimator will be used.
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Set/get whether the unbiased estimator for the variance should be used, or if the population variance will be calculated. The default is that the unbiased estimator will be used.
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Set/get whether the unbiased estimator for the variance should be used, or if the population variance will be calculated. The default is that the unbiased estimator will be used.
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Set/get whether the G1 estimator for the skewness should be used, or if the g1 skewness will be calculated. The default is that the g1 skewness estimator will be used.
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Set/get whether the G1 estimator for the skewness should be used, or if the g1 skewness will be calculated. The default is that the g1 skewness estimator will be used.
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Set/get whether the G1 estimator for the skewness should be used, or if the g1 skewness will be calculated. The default is that the g1 skewness estimator will be used.
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Set/get whether the G1 estimator for the skewness should be used, or if the g1 skewness will be calculated. The default is that the g1 skewness estimator will be used.
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Set/get whether the G2 estimator for the kurtosis should be used, or if the g2 kurtosis will be calculated. The default is that the g2 kurtosis estimator will be used.
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Set/get whether the G2 estimator for the kurtosis should be used, or if the g2 kurtosis will be calculated. The default is that the g2 kurtosis estimator will be used.
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Set/get whether the G2 estimator for the kurtosis should be used, or if the g2 kurtosis will be calculated. The default is that the g2 kurtosis estimator will be used.
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Set/get whether the G2 estimator for the kurtosis should be used, or if the g2 kurtosis will be calculated. The default is that the g2 kurtosis estimator will be used.
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Set/get whether the deviations returned should be signed, or should only have their magnitude reported. The default is that signed deviations will be computed.
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Set/get whether the deviations returned should be signed, or should only have their magnitude reported. The default is that signed deviations will be computed.
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Set/get whether the deviations returned should be signed, or should only have their magnitude reported. The default is that signed deviations will be computed.
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Set/get whether the deviations returned should be signed, or should only have their magnitude reported. The default is that signed deviations will be computed.
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Given a collection of models, calculate aggregate model
Implements vtkStatisticsAlgorithm.
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Execute the calculations required by the Learn option, given some input Data NB: input parameters are unused.
Implements vtkStatisticsAlgorithm.
Reimplemented in vtkPDescriptiveStatistics.
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Execute the calculations required by the Derive option.
Implements vtkStatisticsAlgorithm.
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Execute the calculations required by the Test option.
Implements vtkStatisticsAlgorithm.
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Execute the calculations required by the Assess option.
Implements vtkStatisticsAlgorithm.
Definition at line 139 of file vtkDescriptiveStatistics.h.
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Calculate p-value. This will be overridden using the object factory with an R implementation if R is present.
Reimplemented in vtkDescriptiveStatisticsGnuR.
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Provide the appropriate assessment functor.
Implements vtkStatisticsAlgorithm.
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Definition at line 159 of file vtkDescriptiveStatistics.h.
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Definition at line 160 of file vtkDescriptiveStatistics.h.
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Definition at line 161 of file vtkDescriptiveStatistics.h.
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Definition at line 162 of file vtkDescriptiveStatistics.h.