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/*=========================================================================
Program: Visualization Toolkit
Module: vtkDotProductSimilarity.h
-------------------------------------------------------------------------
Copyright 2008 Sandia Corporation.
Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
the U.S. Government retains certain rights in this software.
-------------------------------------------------------------------------
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.
=========================================================================*/
// .NAME vtkDotProductSimilarity - compute dot-product similarity metrics.
//
// .SECTION Description
// Treats matrices as collections of vectors and computes dot-product similarity
// metrics between vectors.
//
// The results are returned as an edge-table that lists the index of each vector
// and their computed similarity. The output edge-table is typically used with
// vtkTableToGraph to create a similarity graph.
//
// This filter can be used with one or two input matrices. If you provide a single
// matrix as input, every vector in the matrix is compared with every other vector. If
// you provide two matrices, every vector in the first matrix is compared with every
// vector in the second matrix.
//
// Note that this filter *only* computes the dot-product between each pair of vectors;
// if you want to compute the cosine of the angles between vectors, you will need to
// normalize the inputs yourself.
//
// Inputs:
// Input port 0: (required) A vtkDenseArray<double> with two dimensions (a matrix).
// Input port 1: (optional) A vtkDenseArray<double> with two dimensions (a matrix).
//
// Outputs:
// Output port 0: A vtkTable containing "source", "target", and "similarity" columns.
//
// .SECTION Caveats
// Note that the complexity of this filter is quadratic! It also requires dense arrays
// as input, in the future it should be generalized to accept sparse arrays.
//
// .SECTION Thanks
// Developed by Timothy M. Shead (tshead@sandia.gov) at Sandia National Laboratories.
#ifndef vtkDotProductSimilarity_h
#define vtkDotProductSimilarity_h
#include "vtkInfovisCoreModule.h" // For export macro
#include "vtkTableAlgorithm.h"
class VTKINFOVISCORE_EXPORT vtkDotProductSimilarity : public vtkTableAlgorithm
{
public:
static vtkDotProductSimilarity* New();
vtkTypeMacro(vtkDotProductSimilarity, vtkTableAlgorithm);
void PrintSelf(ostream& os, vtkIndent indent);
// Description:
// Controls whether to compute similarities for row-vectors or column-vectors.
// 0 = rows, 1 = columns.
vtkGetMacro(VectorDimension, vtkIdType);
vtkSetMacro(VectorDimension, vtkIdType);
// Description:
// When computing similarities for a single input matrix, controls whether the
// results will include the upper diagonal of the similarity matrix. Default: true.
vtkGetMacro(UpperDiagonal, int);
vtkSetMacro(UpperDiagonal, int);
// Description:
// When computing similarities for a single input matrix, controls whether the
// results will include the diagonal of the similarity matrix. Default: false.
vtkGetMacro(Diagonal, int);
vtkSetMacro(Diagonal, int);
// Description:
// When computing similarities for a single input matrix, controls whether the
// results will include the lower diagonal of the similarity matrix. Default: false.
vtkGetMacro(LowerDiagonal, int);
vtkSetMacro(LowerDiagonal, int);
// Description:
// When computing similarities for two input matrices, controls whether the results
// will include comparisons from the first matrix to the second matrix.
vtkGetMacro(FirstSecond, int);
vtkSetMacro(FirstSecond, int);
// Description:
// When computing similarities for two input matrices, controls whether the results
// will include comparisons from the second matrix to the first matrix.
vtkGetMacro(SecondFirst, int);
vtkSetMacro(SecondFirst, int);
// Description:
// Specifies a minimum threshold that a similarity must exceed to be included in
// the output.
vtkGetMacro(MinimumThreshold, double);
vtkSetMacro(MinimumThreshold, double);
// Description:
// Specifies a minimum number of edges to include for each vector.
vtkGetMacro(MinimumCount, vtkIdType);
vtkSetMacro(MinimumCount, vtkIdType);
// Description:
// Specifies a maximum number of edges to include for each vector.
vtkGetMacro(MaximumCount, vtkIdType);
vtkSetMacro(MaximumCount, vtkIdType);
protected:
vtkDotProductSimilarity();
~vtkDotProductSimilarity();
int FillInputPortInformation(int, vtkInformation*);
int RequestData(
vtkInformation*,
vtkInformationVector**,
vtkInformationVector*);
private:
vtkDotProductSimilarity(const vtkDotProductSimilarity&); // Not implemented
void operator=(const vtkDotProductSimilarity&); // Not implemented
vtkIdType VectorDimension;
double MinimumThreshold;
vtkIdType MinimumCount;
vtkIdType MaximumCount;
int UpperDiagonal;
int Diagonal;
int LowerDiagonal;
int FirstSecond;
int SecondFirst;
};
#endif
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