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[FrontAlgorithms.git] / lib / fpa / Base / Functors / GaussianModel.hxx

diff --git a/lib/fpa/Base/Functors/GaussianModel.hxx b/lib/fpa/Base/Functors/GaussianModel.hxx
index 49db8b04cbe5cd3afa41679b8847010611c1c971..6a44ff873f0f16b28a11eb124a36d90c0993a9b8 100644 (file)
--- a/lib/fpa/Base/Functors/GaussianModel.hxx
+++ b/lib/fpa/Base/Functors/GaussianModel.hxx
@@ -7,35 +7,85 @@ typename fpa::Base::Functors::GaussianModel< _TInput, _TOutput >::
 TOutput fpa::Base::Functors::GaussianModel< _TInput, _TOutput >::
 Evaluate( const TInput& x ) const
 {
-  TOutput r = TOutput( 0 );
-  if( this->m_Model->GetNumberOfSamples( ) > this->m_SupportSize )
+  double v = double( x );
+  double d = double( 0 );
+  if( this->m_N > 1 )
   {
-    r = this->m_Model->SquaredMahalanobis( TOutput( x ) );
-    if( r <= TOutput( 1 ) )
-      this->m_Model->AddSample( TOutput( x ) );
+    double N = double( this->m_N );
+    double m = this->m_S1 / N;
+    double s =
+      ( this->m_S2 - ( ( this->m_S1 * this->m_S1 ) / N ) ) /
+      ( N - double( 1 ) );
+    if( s > double( 0 ) )
+    {
+      d = ( v - m );
+      d *= d;
+      d /= s;
+      d = std::sqrt( d );
+      if( d <= double( 1.5 ) ) // 2sigma
+      {
+        this->m_S1 += v;
+        this->m_S2 += v * v;
+        this->m_N += 1;
+
+      } // fi
+    }
+    else
+    {
+      this->m_S1 += v;
+      this->m_S2 += v * v;
+      this->m_N += 1;
+
+    } // fi
   }
   else
   {
-    this->m_Model->AddSample( TOutput( x ) );
-    if( this->m_Model->GetNumberOfSamples( ) > 2 )
-      r = this->m_Model->SquaredMahalanobis( TOutput( x ) );
+    this->m_S1 += v;
+    this->m_S2 += v * v;
+    this->m_N += 1;
 
   } // fi
-  if( r < this->m_MinimumCost )
-    return( this->m_MinimumCost );
-  else
-    return( r );
+  return( d );
+
+  /* TODO
+     TOutput r = TOutput( 0 );
+     if( this->m_Model->GetNumberOfSamples( ) > this->m_SupportSize )
+     {
+     r = this->m_Model->SquaredMahalanobis( TOutput( x ) );
+     if( r <= TOutput( 1 ) )
+     this->m_Model->AddSample( TOutput( x ) );
+     }
+     else
+     {
+     this->m_Model->AddSample( TOutput( x ) );
+     if( this->m_Model->GetNumberOfSamples( ) > 2 )
+     r = this->m_Model->SquaredMahalanobis( TOutput( x ) );
+
+     } // fi
+     if( r < this->m_MinimumCost )
+     return( this->m_MinimumCost );
+     else
+     return( r );
+  */
 }
 
 // -------------------------------------------------------------------------
 template< class _TInput, class _TOutput >
 fpa::Base::Functors::GaussianModel< _TInput, _TOutput >::
 GaussianModel( )
-  : Superclass( ),
-    m_SupportSize( 30 ),
-    m_MinimumCost( TOutput( 1e-10 ) )
+  : Superclass( )
+  /* TODO
+     ,
+     m_SupportSize( 30 ),
+     m_MinimumCost( TOutput( 1e-10 ) )
+  */
 {
-  this->m_Model = TModel::New( );
+  /* TODO
+     this->m_Model = TModel::New( );
+  */
+  this->m_S1 = double( 0 );
+  this->m_S2 = double( 0 );
+  this->m_N = 0;
 }
 
 // -------------------------------------------------------------------------