+++ /dev/null
-// -------------------------------------------------------------------------
-// @author Leonardo Florez-Valencia (florez-l@javeriana.edu.co)
-// -------------------------------------------------------------------------
-
-#ifndef __CPEXTENSIONS__ALGORITHMS__ITERATIVEGAUSSIANMODELESTIMATOR__HXX__
-#define __CPEXTENSIONS__ALGORITHMS__ITERATIVEGAUSSIANMODELESTIMATOR__HXX__
-
-#include <cstdarg>
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Clear( )
-{
- this->m_NumberOfSamples = 0;
- this->m_Mean.Fill( TScalar( 0 ) );
- this->m_Covariance.Fill( TScalar( 0 ) );
- this->m_InverseUpdated = false;
- this->m_InverseUnbiasedCovariance.Fill( TScalar( 0 ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const _TOtherScalar& x1, ... )
-{
- TVector s;
- std::va_list lst;
- va_start( lst, x1 );
- s[ 0 ] = TScalar( x1 );
- for( unsigned int d = 1; d < _VDimension; ++d )
- s[ d ] = TScalar( va_arg( lst, double ) );
- va_end( lst );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const _TOtherScalar* array )
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( array[ d ] );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const vnl_vector< _TOtherScalar >& v )
-{
- unsigned int len = ( v.size( ) < _VDimension )? v.size: _VDimension;
- TVector s;
- for( unsigned d = 0; d < len; ++d )
- s[ d ] = TScalar( v[ d ] );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const itk::CovariantVector< _TOtherScalar, _VDimension >& v )
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const itk::Point< _TOtherScalar, _VDimension >& p )
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( p[ d ] );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-AddSample( const itk::Vector< _TOtherScalar, _VDimension >& v )
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- this->_AddSample( s );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis( const _TOtherScalar& x1, ... ) const
-{
- TVector s;
- std::va_list lst;
- va_start( lst, x1 );
- s[ 0 ] = TScalar( x1 );
- for( unsigned int d = 1; d < _VDimension; ++d )
- s[ d ] = TScalar( va_arg( lst, double ) );
- va_end( lst );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis( const _TOtherScalar* array ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( array[ d ] );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis( const vnl_vector< _TOtherScalar >& v ) const
-{
- unsigned int len = ( v.size( ) < _VDimension )? v.size: _VDimension;
- TVector s;
- for( unsigned d = 0; d < len; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis(
- const itk::CovariantVector< _TOtherScalar, _VDimension >& v
- ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis( const itk::Point< _TOtherScalar, _VDimension >& p ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( p[ d ] );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-SquaredMahalanobis( const itk::Vector< _TOtherScalar, _VDimension >& v ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_SquaredMahalanobis( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density( const _TOtherScalar& x1, ... ) const
-{
- TVector s;
- std::va_list lst;
- va_start( lst, x1 );
- s[ 0 ] = TScalar( x1 );
- for( unsigned int d = 1; d < _VDimension; ++d )
- s[ d ] = TScalar( va_arg( lst, double ) );
- va_end( lst );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density( const _TOtherScalar* array ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( array[ d ] );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density( const vnl_vector< _TOtherScalar >& v ) const
-{
- unsigned int len = ( v.size( ) < _VDimension )? v.size: _VDimension;
- TVector s;
- for( unsigned d = 0; d < len; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density(
- const itk::CovariantVector< _TOtherScalar, _VDimension >& v
- ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density( const itk::Point< _TOtherScalar, _VDimension >& p ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( p[ d ] );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-template< class _TOtherScalar >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-Density( const itk::Vector< _TOtherScalar, _VDimension >& v ) const
-{
- TVector s;
- for( unsigned d = 0; d < _VDimension; ++d )
- s[ d ] = TScalar( v[ d ] );
- return( this->_Density( s ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-IterativeGaussianModelEstimator( )
- : Superclass( )
-{
- this->Clear( );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-~IterativeGaussianModelEstimator( )
-{
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-void cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-_AddSample( const TVector& v ) const
-{
- this->m_NumberOfSamples += 1;
- TScalar a = TScalar( 1 ) / TScalar( this->m_NumberOfSamples );
- TScalar b = TScalar( 1 ) - a;
- TVector c = v - this->m_Mean;
- TMatrix m;
- for( unsigned int i = 0; i < _VDimension; ++i )
- {
- m[ i ][ i ] = c[ i ] * c[ i ];
- for( unsigned int j = i + 1; j < _VDimension; ++j )
- m[ i ][ j ] = m[ j ][ i ] = c[ i ] * c[ j ];
-
- } // rof
- this->m_Covariance = ( this->m_Covariance + ( m * a ) ) * b;
- this->m_Mean = ( this->m_Mean * b ) + ( v * a );
-
- TScalar u =
- TScalar( this->m_NumberOfSamples ) /
- TScalar( this->m_NumberOfSamples - 1 );
- this->m_UnbiasedCovariance = this->m_Covariance * u;
- this->m_InverseUpdated = false;
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-_SquaredMahalanobis( const TVector& v ) const
-{
- if( !this->m_InverseUpdated )
- {
- double d =
- double(
- vnl_determinant( this->m_UnbiasedCovariance.GetVnlMatrix( ) )
- );
- if( std::fabs( d ) > double( 0 ) )
- this->m_InverseUnbiasedCovariance =
- this->m_UnbiasedCovariance.GetInverse( );
- else
- this->m_InverseUnbiasedCovariance.SetIdentity( );
- this->m_InverseUpdated = true;
-
- } // fi
- TVector x = v - this->m_Mean;
- return( x * ( this->m_InverseUnbiasedCovariance * x ) );
-}
-
-// -------------------------------------------------------------------------
-template< class _TScalar, unsigned int _VDimension >
-_TScalar cpExtensions::Algorithms::
-IterativeGaussianModelEstimator< _TScalar, _VDimension >::
-_Density( const TVector& v ) const
-{
- static const double _2pik =
- std::pow( double( 2 ) * double( vnl_math::pi ), _VDimension );
-
- double s = double( this->_SquaredMahalanobis( v ) ) / double( 2 );
- double d =
- double(
- vnl_determinant( this->m_UnbiasedCovariance.GetVnlMatrix( ) )
- );
- return( _TScalar( std::exp( -s ) / std::sqrt( _2pik * d ) ) );
-}
-
-#endif // __CPEXTENSIONS__ALGORITHMS__ITERATIVEGAUSSIANMODELESTIMATOR__HXX__
-
-// eof - $RCSfile$