this->SetInitValue( v );
}
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+unsigned long fpa::Base::Mori< _TAlgorithm >::
+GetSignalKernelSize( ) const
+{
+ return( this->m_PeakDetector.GetKernelSize( ) );
+}
+
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+double fpa::Base::Mori< _TAlgorithm >::
+GetSignalThreshold( ) const
+{
+ return( this->m_PeakDetector.GetThreshold( ) );
+}
+
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+double fpa::Base::Mori< _TAlgorithm >::
+GetSignalInfluence( ) const
+{
+ return( this->m_PeakDetector.GetInfluence( ) );
+}
+
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+void fpa::Base::Mori< _TAlgorithm >::
+SetSignalKernelSize( unsigned long k )
+{
+ this->m_PeakDetector.SetKernelSize( k );
+ this->Modified( );
+}
+
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+void fpa::Base::Mori< _TAlgorithm >::
+SetSignalThreshold( double t )
+{
+ this->m_PeakDetector.SetThreshold( t );
+ this->Modified( );
+}
+
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+void fpa::Base::Mori< _TAlgorithm >::
+SetSignalInfluence( double i )
+{
+ this->m_PeakDetector.SetInfluence( i );
+ this->Modified( );
+}
+
// -------------------------------------------------------------------------
template< class _TAlgorithm >
void fpa::Base::Mori< _TAlgorithm >::
this->AddThreshold( thr );
}
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+const typename fpa::Base::Mori< _TAlgorithm >::
+TThresholds& fpa::Base::Mori< _TAlgorithm >::
+GetThresholds( ) const
+{
+ return( this->m_Thresholds );
+}
+
// -------------------------------------------------------------------------
template< class _TAlgorithm >
unsigned long fpa::Base::Mori< _TAlgorithm >::
GetNumberOfEvaluatedThresholds( ) const
{
- return( this->m_Signal.size( ) );
+ return( this->m_PeakDetector.GetNumberOfSamples( ) );
}
// -------------------------------------------------------------------------
GetOptimumThreshold( ) const
{
TInputValue thr = TInputValue( 0 );
- if( this->m_Signal.size( ) > 1 )
- thr = this->m_Signal[ this->m_Signal.size( ) - 2 ].first;
+ unsigned long n = this->m_PeakDetector.GetNumberOfSamples( );
+ if( n > 1 )
+ thr = TInputValue( this->m_PeakDetector.GetXValues( )[ n - 2 ] );
return( thr );
}
+// -------------------------------------------------------------------------
+template< class _TAlgorithm >
+void fpa::Base::Mori< _TAlgorithm >::
+GetSignalValues( unsigned long i, double& x, double& y, TPeak& p ) const
+{
+ if( i < this->m_PeakDetector.GetNumberOfSamples( ) )
+ {
+ x = this->m_PeakDetector.GetXValues( )[ i ];
+ y = this->m_PeakDetector.GetYValues( )[ i ];
+ p = this->m_PeakDetector.GetPeaks( )[ i ];
+
+ } // fi
+}
+
// -------------------------------------------------------------------------
template< class _TAlgorithm >
fpa::Base::Mori< _TAlgorithm >::
Mori( )
: Superclass( ),
- m_SignalLag( 20 ),
- m_SignalThreshold( 500 ),
- m_SignalInfluence( 0.5 ),
- m_InsideValue( TOutputValue( 1 ) )
+ m_InsideValue( TOutputValue( 1 ) )
{
this->SetInitValue( TOutputValue( 0 ) );
this->m_Predicate = TPredicate::New( );
this->m_Predicate->StrictOff( );
-
if( std::numeric_limits< TInputValue >::is_integer )
this->m_MinimumThreshold = std::numeric_limits< TInputValue >::min( );
else
this->m_MinimumThreshold = -std::numeric_limits< TInputValue >::max( );
+ this->m_PeakDetector.SetKernelSize( 20 );
+ this->m_PeakDetector.SetThreshold( 500 );
+ this->m_PeakDetector.SetInfluence( 0.5 );
}
// -------------------------------------------------------------------------
{
this->Superclass::_BeforeGenerateData( );
+ // Prepare queues
this->_QueueClear( );
- this->m_CurrentQueue = 0;
- this->m_CurrentThreshold = this->m_Thresholds.begin( );
- this->m_Predicate->SetLower( *( this->m_CurrentThreshold ) );
- this->m_CurrentThreshold++;
- this->m_Predicate->SetUpper( *( this->m_CurrentThreshold ) );
- this->m_Count = 0;
- this->m_Signal.clear( );
- this->m_FilteredSignal.clear( );
- this->m_SignalAverages.clear( );
- this->m_SignalDeviations.clear( );
- this->m_SignalPeaks.clear( );
- this->m_CurrentAverage = double( 0 );
- this->m_CurrentVariance = double( 0 );
+ this->m_CurrQueue = 0;
+
+ // Prepare iteration over all thresholds
+ this->m_CurrThr = this->m_Thresholds.begin( );
+ this->m_Predicate->SetLower( *( this->m_CurrThr ) );
+ this->m_CurrThr++;
+ this->m_Predicate->SetUpper( *( this->m_CurrThr ) );
+
+ // Prepare counting signal
+ this->m_CurrCount = double( 0 );
+ this->m_PeakDetector.Clear( );
}
// -------------------------------------------------------------------------
void fpa::Base::Mori< _TAlgorithm >::
_FinishOneLoop( )
{
- if( this->m_Queues[ this->m_CurrentQueue ].size( ) == 0 )
+ if( this->m_Queues[ this->m_CurrQueue ].size( ) == 0 )
{
- this->m_Signal.push_back(
- TSignalData( *this->m_CurrentThreshold, this->m_Count )
+ // Update peak detector
+ TPeak p = this->m_PeakDetector.AddValue(
+ *this->m_CurrThr, this->m_CurrCount
);
- this->m_CurrentThreshold++;
- this->m_CurrentQueue = ( this->m_CurrentQueue + 1 ) % 2;
- if( this->m_CurrentThreshold != this->m_Thresholds.end( ) )
+ std::cout << *( this->m_CurrThr ) << " " << this->m_CurrCount << std::endl;
+ this->m_CurrThr++;
+ if( this->m_CurrThr != this->m_Thresholds.end( ) )
{
- if( this->m_FilteredSignal.size( ) < this->m_SignalLag )
- {
- double v = double( this->m_Count );
- double n = double( this->m_FilteredSignal.size( ) + 1 );
- this->m_FilteredSignal.push_back( v );
- this->m_SignalAverages.push_back( double( 0 ) );
- this->m_SignalDeviations.push_back( double( 0 ) );
- this->m_SignalPeaks.push_back( 0 );
- if( n > double( 1 ) )
- this->m_CurrentVariance =
- ( ( ( n - 2.0 ) / ( n - 1.0 ) ) * this->m_CurrentVariance ) +
- ( (
- ( v - this->m_CurrentAverage ) *
- ( v - this->m_CurrentAverage )
- ) / n );
- this->m_CurrentAverage += ( v - this->m_CurrentAverage ) / n;
- if( this->m_FilteredSignal.size( ) == this->m_SignalLag )
- {
- this->m_SignalAverages.push_back( this->m_CurrentAverage );
- this->m_SignalDeviations.push_back(
- std::sqrt( this->m_CurrentVariance )
- );
-
- } // fi
- }
- else
- {
- unsigned long i = this->m_Signal.size( ) - 1;
- double v = double( this->m_Count );
- if(
- ( std::fabs( v - this->m_SignalAverages[ i - 1 ] ) ) >
- ( this->m_SignalThreshold * this->m_SignalDeviations[ i - 1 ] )
- )
- {
- if( v > this->m_SignalAverages[ i - 1 ] )
- this->m_SignalPeaks.push_back( 1 );
- else
- this->m_SignalPeaks.push_back( -1 );
- this->m_FilteredSignal.push_back(
- ( this->m_SignalInfluence * v ) +
- (
- ( 1.0 - this->m_SignalInfluence ) *
- this->m_FilteredSignal[ i - 1 ]
- )
- );
- }
- else
- {
- this->m_SignalPeaks.push_back( 0 );
- this->m_FilteredSignal.push_back( v );
-
- } // fi
-
- double avg = double( 0 );
- double var = double( 0 );
- unsigned long k = 0;
- for( unsigned long j = i - this->m_SignalLag; j <= i; ++j, ++k )
- {
- double v = this->m_FilteredSignal[ j ];
- double n = double( k + 1 );
- if( k > 1 )
- var =
- ( ( ( n - 2.0 ) / ( n - 1.0 ) ) * var ) +
- ( ( ( v - avg ) * ( v - avg ) ) / n );
- avg += ( v - avg ) / n;
-
- } // rof
- this->m_SignalAverages.push_back( avg );
- this->m_SignalDeviations.push_back( std::sqrt( var ) );
-
- } // fi
- this->m_Predicate->SetUpper( *( this->m_CurrentThreshold ) );
- this->m_Count = 0;
+ // Update predicate and counting value
+ this->m_Predicate->SetUpper( *( this->m_CurrThr ) );
+ this->m_CurrCount = double( 0 );
// Peak detected? -> stop!
- if( this->m_SignalPeaks.back( ) == 1 && this->m_MinimumThreshold < *( this->m_CurrentThreshold ) )
+ if(
+ p == TPeakDetector::PosPeak &&
+ this->m_MinimumThreshold < *( this->m_CurrThr )
+ )
this->_QueueClear( );
}
else
{
n.Value = this->m_InitValue;
n.FrontId++;
- this->m_Queues[ ( this->m_CurrentQueue + 1 ) % 2 ].push_back( n );
+ this->m_Queues[ ( this->m_CurrQueue + 1 ) % 2 ].push_back( n );
n.FrontId = 0;
}
else
{
n.Value = this->m_InsideValue;
- this->m_Count++;
+ this->m_CurrCount += double( 1 );
} // fi
this->Superclass::_UpdateOutputValue( n );
TNode fpa::Base::Mori< _TAlgorithm >::
_QueuePop( )
{
- TNode n = this->m_Queues[ this->m_CurrentQueue ].front( );
- this->m_Queues[ this->m_CurrentQueue ].pop_front( );
+ TNode n = this->m_Queues[ this->m_CurrQueue ].front( );
+ this->m_Queues[ this->m_CurrQueue ].pop_front( );
return( n );
}
void fpa::Base::Mori< _TAlgorithm >::
_QueuePush( const TNode& node )
{
- this->m_Queues[ this->m_CurrentQueue ].push_back( node );
+ this->m_Queues[ this->m_CurrQueue ].push_back( node );
}
// -------------------------------------------------------------------------
unsigned long fpa::Base::Mori< _TAlgorithm >::
_QueueSize( ) const
{
- return( this->m_Queues[ this->m_CurrentQueue ].size( ) );
+ return( this->m_Queues[ this->m_CurrQueue ].size( ) );
}
// -------------------------------------------------------------------------
git://git.creatis.insa-lyon.fr / FrontAlgorithms.git / blobdiff