/usr/include/paraview/vtkPSciVizPCAStats.h is in paraview-dev 5.0.1+dfsg1-4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | /*=========================================================================
Program: ParaView
Module: vtkPSciVizPCAStats.h
Copyright (c) Kitware, Inc.
All rights reserved.
See Copyright.txt or http://www.paraview.org/HTML/Copyright.html 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.
=========================================================================*/
// .NAME vtkPSciVizPCAStats - Perform PCA on data and/or project data into a subspace defined by the PCA.
// .SECTION Description
// This filter either computes a statistical model of
// a dataset or takes such a model as its second input.
// Then, the model (however it is obtained) may
// optionally be used to assess the input dataset.
//
// This filter performs additional analysis above
// and beyond the vtkPSciVizMultiCorrelativeStats filter.
// It computes the eigenvalues and eigenvectors of the
// covariance matrix from the multicorrelative filter.
// Data is then assessed by projecting the original tuples
// into a possibly lower-dimensional space.
//
// Since the PCA filter uses the multicorrelative filter's analysis,
// it shares the same raw covariance table specified in the
// multicorrelative documentation.
// The second table in the multiblock dataset comprising the model output
// is an expanded version of the multicorrelative version.
//
// As with the multicorrlative filter, the second model table contains the
// mean values, the upper-triangular portion of the symmetric covariance
// matrix, and the non-zero lower-triangular portion of the Cholesky
// decomposition of the covariance matrix.
// Below these entries are the eigenvalues of the covariance matrix (in the
// column labeled "Mean") and the eigenvectors (as row vectors) in an
// additional NxN matrix.
#ifndef vtkPSciVizPCAStats_h
#define vtkPSciVizPCAStats_h
#include "vtkPVVTKExtensionsDefaultModule.h" //needed for exports
#include "vtkSciVizStatistics.h"
class VTKPVVTKEXTENSIONSDEFAULT_EXPORT vtkPSciVizPCAStats : public vtkSciVizStatistics
{
public:
static vtkPSciVizPCAStats* New();
vtkTypeMacro(vtkPSciVizPCAStats,vtkSciVizStatistics);
virtual void PrintSelf( ostream& os, vtkIndent indent );
vtkSetMacro(NormalizationScheme,int);
vtkGetMacro(NormalizationScheme,int);
vtkSetMacro(BasisScheme,int);
vtkGetMacro(BasisScheme,int);
vtkSetMacro(FixedBasisSize,int);
vtkGetMacro(FixedBasisSize,int);
vtkSetClampMacro(FixedBasisEnergy,double,0.,1.);
vtkGetMacro(FixedBasisEnergy,double);
vtkSetMacro(RobustPCA,bool);
vtkGetMacro(RobustPCA,bool);
vtkBooleanMacro(RobustPCA,bool);
protected:
vtkPSciVizPCAStats();
virtual ~vtkPSciVizPCAStats();
virtual int LearnAndDerive( vtkMultiBlockDataSet* model, vtkTable* inData );
virtual int AssessData( vtkTable* observations, vtkDataObject* dataset, vtkMultiBlockDataSet* model );
int NormalizationScheme;
int BasisScheme;
int FixedBasisSize;
double FixedBasisEnergy;
bool RobustPCA;
private:
vtkPSciVizPCAStats( const vtkPSciVizPCAStats& ); // Not implemented.
void operator = ( const vtkPSciVizPCAStats& ); // Not implemented.
};
#endif // vtkPSciVizPCAStats_h
|