/usr/include/OTB-5.8/otbGaussianModelComponent.txx is in libotb-dev 5.8.0+dfsg-3.
This file is owned by root:root, with mode 0o644.
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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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 | /*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
Some parts of this code are covered by the IMT copyright.
See IMTCopyright.txt 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 notices for more information.
=========================================================================*/
#ifndef otbGaussianModelComponent_txx
#define otbGaussianModelComponent_txx
#include <iostream>
#include "itkNumericTraits.h"
#include "otbMacro.h"
#include "otbGaussianModelComponent.h"
namespace otb
{
namespace Statistics
{
template<class TSample>
GaussianModelComponent<TSample>
::GaussianModelComponent()
{
m_CovarianceEstimator = ITK_NULLPTR;
m_GaussianMembershipFunction = ITK_NULLPTR;
}
template<class TSample>
void
GaussianModelComponent<TSample>
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Mean Estimator: " << m_CovarianceEstimator << std::endl;
os << indent << "Covariance Estimator: " << m_CovarianceEstimator << std::endl;
os << indent << "GaussianMembershipFunction: " << m_GaussianMembershipFunction << std::endl;
}
template <class TSample>
void
GaussianModelComponent<TSample>
::ShowParameters(std::ostream& os, itk::Indent indent) const
{
unsigned int i, j;
os << indent << "Gaussian model component : \n";
os << indent << "Mean : ";
for (i = 0; i < m_Mean.Size(); ++i)
os << m_Mean[i] << "\t";
os << "\n" << indent << "Covariance : ";
for (i = 0; i < m_Mean.Size(); ++i)
{
for (j = 0; j < m_Mean.Size(); ++j)
os << m_Covariance(i, j) << "\t";
os << "\n" << indent << " ";
}
os << "\n";
}
template<class TSample>
void
GaussianModelComponent<TSample>
::SetSample(const TSample* sample)
{
Superclass::SetSample(sample);
const MeasurementVectorSizeType measurementVectorLength = sample->GetMeasurementVectorSize();
this->m_Parameters.SetSize(measurementVectorLength * (1 + measurementVectorLength));
// Set the size of the mean vector
m_Mean.SetSize(measurementVectorLength);
// Set the parameters of the mean (internally) and the covariance estimator
m_Covariance.SetSize(measurementVectorLength,
measurementVectorLength);
m_CovarianceEstimator = CovarianceEstimatorType::New();
m_CovarianceEstimator->SetInput(sample);
m_CovarianceEstimator->Update();
m_GaussianMembershipFunction = NativeMembershipFunctionType::New();
this->m_PdfFunction = (MembershipFunctionType *) m_GaussianMembershipFunction;
m_GaussianMembershipFunction->SetMeasurementVectorSize(
measurementVectorLength);
this->SetPdfMembershipFunction((MembershipFunctionType *)
m_GaussianMembershipFunction.GetPointer());
}
template<class TSample>
void
GaussianModelComponent<TSample>
::SetParameters(const ParametersType& parameters)
{
Superclass::SetParameters(parameters);
unsigned int paramIndex = 0;
unsigned int i, j;
MeasurementVectorSizeType measurementVectorSize
= this->GetSample()->GetMeasurementVectorSize();
m_Mean.SetSize (measurementVectorSize);
for (i = 0; i < measurementVectorSize; i++)
{
m_Mean[i] = parameters[paramIndex];
paramIndex++;
}
m_Covariance.SetSize(measurementVectorSize, measurementVectorSize);
for (i = 0; i < measurementVectorSize; i++)
for (j = 0; j < measurementVectorSize; j++)
{
m_Covariance(i, j) = parameters[paramIndex];
paramIndex++;
}
this->m_GaussianMembershipFunction->SetMean(m_Mean);
this->m_GaussianMembershipFunction->SetCovariance(&m_Covariance);
}
template<class TSample>
void
GaussianModelComponent<TSample>
::GenerateData()
{
if (this->IsSampleModified() == 0) return;
MeasurementVectorSizeType measurementVectorSize = this->GetSample()->GetMeasurementVectorSize();
unsigned int i, j;
int paramIndex = 0;
// Get the mean using the convariance estimator (computed internally)
typename CovarianceEstimatorType::MeasurementVectorType meanOutput = m_CovarianceEstimator->GetMean();
for (i = 0; i < measurementVectorSize; i++)
{
m_Mean.SetElement(i,meanOutput.GetElement(i));
this->m_Parameters[paramIndex] = meanOutput.GetElement(i);
++paramIndex;
}
// Get the covariance matrix and fill the parameters vector
const typename CovarianceEstimatorType::MatrixType covariance = m_CovarianceEstimator->GetCovarianceMatrix();
for (i = 0; i < measurementVectorSize; i++)
for (j = 0; j < measurementVectorSize; j++)
{
this->m_Parameters[paramIndex] = covariance.GetVnlMatrix().get(i, j);
m_Covariance(i, j) = covariance.GetVnlMatrix().get(i, j);
paramIndex++;
}
this->m_GaussianMembershipFunction->SetMean(meanOutput);
this->m_GaussianMembershipFunction->SetCovariance(m_Covariance);
Superclass::GenerateData();
}
} // end of namespace Statistics
} // end of namesapce otb
#endif
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