/usr/include/vtk-6.2/vtkDescriptiveStatistics.h is in libvtk6-dev 6.2.0+dfsg1-10build1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 | /*=========================================================================
Program: Visualization Toolkit
Module: vtkDescriptiveStatistics.h
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
/*-------------------------------------------------------------------------
Copyright 2010 Sandia Corporation.
Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
the U.S. Government retains certain rights in this software.
-------------------------------------------------------------------------*/
// .NAME vtkDescriptiveStatistics - A class for univariate descriptive statistics
//
// .SECTION Description
// 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.
//
// .SECTION Thanks
// Thanks to Philippe Pebay and David Thompson from Sandia National Laboratories
// for implementing this class.
// Updated by Philippe Pebay, Kitware SAS 2012
#ifndef vtkDescriptiveStatistics_h
#define vtkDescriptiveStatistics_h
#include "vtkFiltersStatisticsModule.h" // For export macro
#include "vtkStatisticsAlgorithm.h"
class vtkMultiBlockDataSet;
class vtkStringArray;
class vtkTable;
class vtkVariant;
class vtkDoubleArray;
class VTKFILTERSSTATISTICS_EXPORT vtkDescriptiveStatistics : public vtkStatisticsAlgorithm
{
public:
vtkTypeMacro(vtkDescriptiveStatistics, vtkStatisticsAlgorithm);
void PrintSelf(ostream& os, vtkIndent indent);
static vtkDescriptiveStatistics* New();
// Description:
// 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.
vtkSetMacro(UnbiasedVariance,int);
vtkGetMacro(UnbiasedVariance,int);
vtkBooleanMacro(UnbiasedVariance,int);
// Description:
// 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.
vtkSetMacro(G1Skewness,int);
vtkGetMacro(G1Skewness,int);
vtkBooleanMacro(G1Skewness,int);
// Description:
// 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.
vtkSetMacro(G2Kurtosis,int);
vtkGetMacro(G2Kurtosis,int);
vtkBooleanMacro(G2Kurtosis,int);
// Description:
// 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.
vtkSetMacro(SignedDeviations,int);
vtkGetMacro(SignedDeviations,int);
vtkBooleanMacro(SignedDeviations,int);
// Description:
// Given a collection of models, calculate aggregate model
virtual void Aggregate( vtkDataObjectCollection*,
vtkMultiBlockDataSet* );
protected:
vtkDescriptiveStatistics();
~vtkDescriptiveStatistics();
// Description:
// Execute the calculations required by the Learn option, given some input Data
// NB: input parameters are unused.
virtual void Learn( vtkTable*,
vtkTable*,
vtkMultiBlockDataSet* );
// Description:
// Execute the calculations required by the Derive option.
virtual void Derive( vtkMultiBlockDataSet* );
// Description:
// Execute the calculations required by the Test option.
virtual void Test( vtkTable*,
vtkMultiBlockDataSet*,
vtkTable* );
// Description:
// Execute the calculations required by the Assess option.
virtual void Assess( vtkTable* inData,
vtkMultiBlockDataSet* inMeta,
vtkTable* outData )
{ this->Superclass::Assess( inData, inMeta, outData, 1 ); }
//BTX
// Description:
// Calculate p-value. This will be overridden using the object factory with an
// R implementation if R is present.
virtual vtkDoubleArray* CalculatePValues(vtkDoubleArray*);
// Description:
// Provide the appropriate assessment functor.
virtual void SelectAssessFunctor( vtkTable* outData,
vtkDataObject* inMeta,
vtkStringArray* rowNames,
AssessFunctor*& dfunc );
//ETX
int UnbiasedVariance;
int G1Skewness;
int G2Kurtosis;
int SignedDeviations;
private:
vtkDescriptiveStatistics( const vtkDescriptiveStatistics& ); // Not implemented
void operator = ( const vtkDescriptiveStatistics& ); // Not implemented
};
#endif
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