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

diff --git a/lib/cpExtensions/Algorithms/KalmanFilter.h b/lib/cpExtensions/Algorithms/KalmanFilter.h
index a96c6208c116e741bfc4d7c51670459bf66fb729..bd0c17a701a5505bbc7d93c43459ee916a44ae46 100644 (file)
--- a/lib/cpExtensions/Algorithms/KalmanFilter.h
+++ b/lib/cpExtensions/Algorithms/KalmanFilter.h
@@ -130,83 +130,85 @@ namespace cpExtensions
 
       void Configure( unsigned int s, unsigned int i, unsigned int m );
 
-      /// Iteration methods
-        virtual void Initialize( );
-        virtual void Predict( );
-        virtual void Innovate( );
-        virtual void Filtrate( );
-        virtual void OneStep( )
+      // Iteration methods
+      virtual void Initialize( );
+      virtual void Predict( );
+      virtual void Innovate( );
+      virtual void Filtrate( );
+      virtual void OneStep( )
         {
           this->Predict( );
           this->Innovate( );
           this->Filtrate( );
         }
-        virtual void NSteps( unsigned int n )
+      virtual void NSteps( unsigned int n )
         {
           for( unsigned int i = 0; i < n; i++ )
             this->OneStep( );
         }
-        unsigned int CurrentIteration( ) const
+      unsigned int CurrentIteration( ) const
         { return( this->m_I ); }
-        unsigned char CurrentStep( ) const
+      unsigned char CurrentStep( ) const
         { return( this->m_Step ); }
 
     protected:
-        KalmanFilter( );
-        virtual ~KalmanFilter( );
+      KalmanFilter( );
+      virtual ~KalmanFilter( );
 
     private:
-        // Purposely not implemented
-        KalmanFilter( const Self& );
-        void operator=( const Self& );
+      // Purposely not implemented
+      KalmanFilter( const Self& );
+      void operator=( const Self& );
 
     protected:
-        // Filter dimensions
-        unsigned int m_StateSize;
-        unsigned int m_InputSize;
-        unsigned int m_MeasureSize;
-
-        // Transition matrices
-        TMatrix m_A;  /// Transition
-          TMatrix m_B;  /// Input control
-            TMatrix m_H;  /// Measure
-              TMatrix m_Id; /// Identity matrix
-
-                // Noise matrices
-                TMatrix m_Q; /// Process noise covariance
-                  TMatrix m_R; /// Measure noise covariance
-
-                    // Initial values
-                    TVector m_x0; /// Initial state
-                      TMatrix m_P0; /// Initial error covariance
-
-                        // Loop vectors
-                        TVector m_u;  /// Last real input
-                          TVector m_m;  /// Last real measure
-                            TVector m_xm; /// A priori state
-                              TVector m_xp; /// A posteriori state
-
-                                // Loop matrices
-                                TMatrix m_K; /// kalman gain
-                                  TMatrix m_Pm; /// A priori error
-                                    TMatrix m_Pp; /// A posteriori error
-
-                                      // Loop values
-                                      unsigned int  m_I;    /// Current iteration
-                                        unsigned char m_Step; /// Current step within current iteration
-
-                                          // -----------------------------------------------------------------
-                                          // Classic kronecker product operator
-                                          // -----------------------------------------------------------------
-                                          template< class M >
-                                            static void Kronecker( M& AkB, const M& A, const M& B );
+      // Filter dimensions
+      unsigned int m_StateSize;
+      unsigned int m_InputSize;
+      unsigned int m_MeasureSize;
+
+      // Transition matrices
+      TMatrix m_A;  // Transition
+      TMatrix m_B;  // Input control
+      TMatrix m_H;  // Measure
+      TMatrix m_Id; // Identity matrix
+
+      // Noise matrices
+      TMatrix m_Q; // Process noise covariance
+      TMatrix m_R; // Measure noise covariance
+
+      // Initial values
+      TVector m_x0; // Initial state
+      TMatrix m_P0; // Initial error covariance
+
+      // Loop vectors
+      TVector m_u;  // Last real input
+      TVector m_m;  // Last real measure
+      TVector m_xm; // A priori state
+      TVector m_xp; // A posteriori state
+
+      // Loop matrices
+      TMatrix m_K; // kalman gain
+      TMatrix m_Pm; // A priori error
+      TMatrix m_Pp; // A posteriori error
+
+      // Loop values
+      unsigned int  m_I;    // Current iteration
+      unsigned char m_Step; // Current step within current iteration
+
+      // -------------------------------------------------------------------
+      // Classic kronecker product operator
+      // -------------------------------------------------------------------
+      template< class M >
+      static void Kronecker( M& AkB, const M& A, const M& B );
     };
 
   } // ecapseman
 
 } // ecapseman
 
+#ifndef ITK_MANUAL_INSTANTIATION
 #include <cpExtensions/Algorithms/KalmanFilter.hxx>
+#endif // ITK_MANUAL_INSTANTIATION
 
 #endif // __CPEXTENSIONS__ALGORITHMS__KALMANFILTER__H__