Cast image filter added. ROI filter modified.

[cpPlugins.git] / lib / cpExtensions / Algorithms / IterativeGaussianModelEstimator.h

diff --git a/lib/cpExtensions/Algorithms/IterativeGaussianModelEstimator.h b/lib/cpExtensions/Algorithms/IterativeGaussianModelEstimator.h
index 5cf7332ce1957bbe313f70372b4e1f699d381be7..b38e06ede2d6732e86f4793a97964de10b0859b1 100644 (file)
--- a/lib/cpExtensions/Algorithms/IterativeGaussianModelEstimator.h
+++ b/lib/cpExtensions/Algorithms/IterativeGaussianModelEstimator.h
@@ -8,15 +8,22 @@
 #include <vector>
 #include <itkConceptChecking.h>
 #include <itkObject.h>
-#include <vnl/vnl_matrix.h>
+#include <itkObjectFactory.h>
+
+#include <itkCovariantVector.h>
+#include <itkMatrix.h>
+#include <itkPoint.h>
+#include <itkVector.h>
 
 namespace cpExtensions
 {
   namespace Algorithms
   {
     /**
+     * Recursive formulation taken from:
+     * http://lmb.informatik.uni-freiburg.de/lectures/mustererkennung/Englische_Folien/07_c_ME_en.pdf
      */
-    template< class S, unsigned int D >
+    template< class _TScalar, unsigned int _VDimension >
     class IterativeGaussianModelEstimator
       : public itk::Object
     {
@@ -26,61 +33,117 @@ namespace cpExtensions
       typedef itk::SmartPointer< Self >       Pointer;
       typedef itk::SmartPointer< const Self > ConstPointer;
 
-      typedef S TScalar;
-      itkStaticConstMacro( Dimension, unsigned int, D );
+      typedef _TScalar TScalar;
+      itkStaticConstMacro( Dimension, unsigned int, _VDimension );
 
       // Begin concept checking
 #ifdef ITK_USE_CONCEPT_CHECKING
       itkConceptMacro(
         ScalarTypeHasFloatResolution,
-        ( itk::Concept::IsFloatingPoint< S > )
+        ( itk::Concept::IsFloatingPoint< _TScalar > )
         );
 #endif
       // End concept checking
 
-      typedef vnl_matrix< S >        TMatrix;
-      typedef std::vector< TMatrix > TMatrices;
+      typedef itk::Matrix< TScalar, Dimension, Dimension > TMatrix;
+      typedef itk::Vector< TScalar, Dimension > TVector;
 
     public:
       itkNewMacro( Self );
       itkTypeMacro( IterativeGaussianModelEstimator, itkObject );
 
+      itkGetConstMacro( Mean, TVector );
+      itkGetConstMacro( Covariance, TMatrix );
+      itkGetConstMacro( UnbiasedCovariance, TMatrix );
+      itkGetConstMacro( NumberOfSamples, unsigned long );
+
+      itkSetMacro( Mean, TVector );
+      itkSetMacro( Covariance, TMatrix );
+      itkSetMacro( NumberOfSamples, unsigned long );
+
     public:
-      unsigned long GetNumberOfSamples( ) const
-        { return( ( unsigned long )( this->m_N ) ); }
-      const TMatrix& GetMu( ) const
-        { return( this->m_M ); }
-      const TMatrix& GetOmega( ) const
-        { return( this->m_O ); }
+      void Clear( );
 
-      void SetNumberOfSamples( unsigned long n );
-      void SetMu( const TMatrix& m );
-      void SetOmega( const TMatrix& O );
+      template< class _TOtherScalar >
+      void AddSample( const _TOtherScalar& x1, ... );
 
-      bool SaveModelToFile( const std::string& filename ) const;
-      bool LoadModelFromFile( const std::string& filename );
+      template< class _TOtherScalar >
+      void AddSample( const _TOtherScalar* array );
 
-      template< class V >
-      S Probability( const V& sample ) const;
+      template< class _TOtherScalar >
+      void AddSample( const vnl_vector< _TOtherScalar >& v );
 
-      S Probability( const S& s_x, const S& s_y, ... ) const;
+      template< class _TOtherScalar >
+      void AddSample(
+        const itk::CovariantVector< _TOtherScalar, _VDimension >& v
+        );
 
-      template< class V, class M >
-      void GetModel( V& m, M& E ) const;
+      template< class _TOtherScalar >
+      void AddSample( const itk::Point< _TOtherScalar, _VDimension >& p );
 
-      void Clear( );
+      template< class _TOtherScalar >
+      void AddSample( const itk::Vector< _TOtherScalar, _VDimension >& v );
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis( const _TOtherScalar& x1, ... ) const;
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis( const _TOtherScalar* array ) const;
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis(
+        const vnl_vector< _TOtherScalar >& v
+        ) const;
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis(
+        const itk::CovariantVector< _TOtherScalar, _VDimension >& v
+        ) const;
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis(
+        const itk::Point< _TOtherScalar, _VDimension >& p
+        ) const;
+
+      template< class _TOtherScalar >
+      _TScalar SquaredMahalanobis(
+        const itk::Vector< _TOtherScalar, _VDimension >& v
+        ) const;
+
+      template< class _TOtherScalar >
+      _TScalar Density( const _TOtherScalar& x1, ... ) const;
+
+      template< class _TOtherScalar >
+      _TScalar Density( const _TOtherScalar* array ) const;
+
+      template< class _TOtherScalar >
+      _TScalar Density(
+        const vnl_vector< _TOtherScalar >& v
+        ) const;
+
+      template< class _TOtherScalar >
+      _TScalar Density(
+        const itk::CovariantVector< _TOtherScalar, _VDimension >& v
+        ) const;
 
-      template< class V >
-      void AddSample( const V& sample );
+      template< class _TOtherScalar >
+      _TScalar Density(
+        const itk::Point< _TOtherScalar, _VDimension >& p
+        ) const;
 
-      void AddSample( const S& s_x, const S& s_y, ... );
+      template< class _TOtherScalar >
+      _TScalar Density(
+        const itk::Vector< _TOtherScalar, _VDimension >& v
+        ) const;
 
     protected:
       IterativeGaussianModelEstimator( );
       virtual ~IterativeGaussianModelEstimator( );
 
     protected:
-      void _UpdateModel( ) const;
+      void _AddSample( const TVector& v ) const;
+      _TScalar _SquaredMahalanobis( const TVector& v ) const;
+      _TScalar _Density( const TVector& v ) const;
 
     private:
       // Purposely not implemented
@@ -88,23 +151,20 @@ namespace cpExtensions
       void operator=( const Self& other );
 
     protected:
-      S m_N;
-      TMatrix m_M;
-      TMatrix m_O;
-
-      mutable bool m_Updated;
-      mutable TMatrix m_Cov;
-      mutable TMatrix m_Inv;
-      mutable S m_Norm;
+      // Recursive avg/cov values
+      mutable unsigned long m_NumberOfSamples;
+      mutable TVector m_Mean;
+      mutable TMatrix m_Covariance;
+      mutable TMatrix m_UnbiasedCovariance;
+      mutable bool m_InverseUpdated;
+      mutable TMatrix m_InverseUnbiasedCovariance;
     };
 
   } // ecapseman
 
 } // ecapseman
 
-#ifndef ITK_MANUAL_INSTANTIATION
 #include <cpExtensions/Algorithms/IterativeGaussianModelEstimator.hxx>
-#endif // ITK_MANUAL_INSTANTIATION
 
 #endif // __CPEXTENSIONS__ALGORITHMS__ITERATIVEGAUSSIANMODELESTIMATOR__H__