/usr/include/OTB-6.4/otbSOMWithMissingValue.txx is in libotb-dev 6.4.0+dfsg-1.
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 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 | /*
* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
* Copyright (C) 2007-2012 Institut Mines Telecom / Telecom Bretagne
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef otbSOMWithMissingValue_txx
#define otbSOMWithMissingValue_txx
#include "otbSOMWithMissingValue.h"
#include "itkNumericTraits.h"
#include "itkNeighborhoodIterator.h"
#include "otbMacro.h"
namespace otb
{
template <class TListSample, class TMap,
class TSOMLearningBehaviorFunctor,
class TSOMNeighborhoodBehaviorFunctor>
SOMWithMissingValue <TListSample, TMap, TSOMLearningBehaviorFunctor, TSOMNeighborhoodBehaviorFunctor>
::SOMWithMissingValue(void)
{}
template <class TListSample, class TMap,
class TSOMLearningBehaviorFunctor,
class TSOMNeighborhoodBehaviorFunctor>
SOMWithMissingValue <TListSample, TMap, TSOMLearningBehaviorFunctor, TSOMNeighborhoodBehaviorFunctor>
::~SOMWithMissingValue(void)
{}
/**
* Update the output map with a new sample by including the case when some
* components of this new sample may be missing.
* \param sample The new sample to learn,
* \param beta The learning coefficient,
* \param radius The radius of the nieghbourhood.
*/
template <class TListSample, class TMap,
class TSOMLearningBehaviorFunctor,
class TSOMNeighborhoodBehaviorFunctor>
void
SOMWithMissingValue<TListSample, TMap, TSOMLearningBehaviorFunctor, TSOMNeighborhoodBehaviorFunctor>
::UpdateMap(const NeuronType& sample, double beta, SizeType& radius)
{
// output map pointer
MapPointerType map = this->GetOutput(0);
// winner index in the map
IndexType position = map->GetWinner(sample);
NeuronType winner = map->GetPixel(position);
// Local neighborhood definition
typedef typename MapType::Superclass ImageMapType;
typedef itk::NeighborhoodIterator<ImageMapType> NeighborhoodIteratorType;
typename MapType::RegionType mapRegion = map->GetLargestPossibleRegion();
NeighborhoodIteratorType it(radius, map, mapRegion);
// Here, the periodic update is achieved 'by hand' since
// PeriodicBoundaryCondition does not allow modifying
// VectorImage contents
SizeType mapSize = mapRegion.GetSize();
IndexType positionToUpdate;
// Iterate over the neighborhood of the winner neuron
it.SetLocation(position);
for (unsigned int i = 0; i < it.Size(); ++i)
{
typename NeighborhoodIteratorType::OffsetType offset = it.GetOffset(i);
// The neighborhood is of elliptic shape
double theDistance = itk::NumericTraits<double>::Zero;
for (unsigned int j = 0; j < MapType::ImageDimension; ++j)
theDistance += pow(static_cast<double>(offset[j]), 2.0)
/ pow(static_cast<double>(radius[j]), 2.0);
if (theDistance <= 1.0)
{
for (unsigned int j = 0; j < MapType::ImageDimension; ++j)
{
int pos = offset[j] + position[j];
positionToUpdate[j] = (pos >= 0) ?
pos % mapSize[j] :
(mapSize[j] - ((-pos) % mapSize[j])) % mapSize[j];
}
NeuronType tempNeuron = it.GetPixel(i);
NeuronType newNeuron(tempNeuron);
double tempBeta = beta / (1.0 + theDistance);
for (unsigned int j = 0; j < newNeuron.Size(); ++j)
{
if (!DistanceType::IsMissingValue(sample[j]))
newNeuron[j] += static_cast<typename NeuronType::ValueType>(
(sample[j] - tempNeuron[j]) * tempBeta);
}
map->SetPixel(positionToUpdate, newNeuron);
}
}
}
template <class TListSample, class TMap,
class TSOMLearningBehaviorFunctor,
class TSOMNeighborhoodBehaviorFunctor>
void
SOMWithMissingValue<TListSample, TMap, TSOMLearningBehaviorFunctor, TSOMNeighborhoodBehaviorFunctor>
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
} // end PrintSelf
} // end iof namespace otb
#endif
|