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details BlockwiseConvolutionOptions< N > Class Template Reference VIGRA

#include <vigra/multi_blockwise.hxx>

Inheritance diagram for BlockwiseConvolutionOptions< N >:
BlockwiseOptions ConvolutionOptions< N > ParallelOptions

Additional Inherited Members

- Public Types inherited from ParallelOptions
enum  { Auto = -1, Nice = -2, NoThreads = 0 }
 
- Public Member Functions inherited from BlockwiseOptions
BlockwiseOptionsblockShape (const Shape &blockShape)
 
template<class T , int N>
BlockwiseOptionsblockShape (const TinyVector< T, N > &blockShape)
 
BlockwiseOptionsblockShape (MultiArrayIndex blockShape)
 
Shape const & getBlockShape () const
 
template<int N>
TinyVector< MultiArrayIndex, N > getBlockShapeN () const
 
- Public Member Functions inherited from ParallelOptions
int getActualNumThreads () const
 Get desired number of threads. More...
 
int getNumThreads () const
 Get desired number of threads. More...
 
ParallelOptionsnumThreads (const int n)
 Set the number of threads or one of the constants Auto, Nice and NoThreads. More...
 
- Public Member Functions inherited from ConvolutionOptions< N >
ConvolutionOptions< dim > & filterWindowSize (double ratio)
 
ConvolutionOptions< dim > & innerScale (...)
 
ConvolutionOptions< dim > & outerScale (...)
 
ConvolutionOptions< dim > & resolutionStdDev (...)
 
ConvolutionOptions< dim > & stdDev (...)
 
ConvolutionOptions< dim > & stepSize (...)
 
ConvolutionOptions< dim > & subarray (Shape const &from, Shape const &to)
 

Detailed Description

template<unsigned int N>
class vigra::BlockwiseConvolutionOptions< N >

Option class for blockwise convolution algorithms.

Simply derives from vigra::BlockwiseOptions and vigra::ConvolutionOptions to join their capabilities.


The documentation for this class was generated from the following file:

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

html generated using doxygen and Python
vigra 1.11.1 (Fri May 19 2017)