AbsoluteDeviation Class Reference

#include <LossFunctions.h>

Inheritance diagram for AbsoluteDeviation:

Public Member Functions
	AbsoluteDeviation ()
Double_t	fit (std::vector< Event * > &v)
int	id ()
std::string	name ()
Double_t	target (Event *e)
	~AbsoluteDeviation ()

Detailed Description

Definition at line 71 of file LossFunctions.h.

Constructor & Destructor Documentation

AbsoluteDeviation::AbsoluteDeviation ( )

inline

Definition at line 74 of file LossFunctions.h.

{}

AbsoluteDeviation::~AbsoluteDeviation ( )

inline

Definition at line 75 of file LossFunctions.h.

{}

Member Function Documentation

Double_t AbsoluteDeviation::fit ( std::vector< Event * > &  v )

inlinevirtual

Implements LossFunction.

Definition at line 86 of file LossFunctions.h.

References alignCSCRings::e, i, Event::predictedValue, and Event::trueValue.

Referenced by trackingPlots.Iteration::modules().

        {
        // The median of the residuals minimizes absolute deviation.
            if(v.size()==0) return 0;
            std::vector<Double_t> residuals(v.size());
       
            // Load the residuals into a vector. 
            for(unsigned int i=0; i<v.size(); i++)
            {
                Event* e = v[i];
                residuals[i] = (e->trueValue - e->predictedValue);
            }

            // Get the median and return it.
            int median_loc = (residuals.size()-1)/2;

            // Odd.
            if(residuals.size()%2 != 0)
            {
                std::nth_element(residuals.begin(), residuals.begin()+median_loc, residuals.end());
                return residuals[median_loc];
            }
            
            // Even.
            else
            {
                std::nth_element(residuals.begin(), residuals.begin()+median_loc, residuals.end());
                Double_t low = residuals[median_loc];
                std::nth_element(residuals.begin()+median_loc+1, residuals.begin()+median_loc+1, residuals.end());
                Double_t high = residuals[median_loc+1];
                return (high + low)/2;
            }
        }

int AbsoluteDeviation::id ( void  )

inlinevirtual

Implements LossFunction.

Definition at line 120 of file LossFunctions.h.

{ return 2; }

std::string AbsoluteDeviation::name ( void  )

inlinevirtual

Implements LossFunction.

Definition at line 119 of file LossFunctions.h.

Referenced by cuy.divideElement::__init__(), cuy.plotElement::__init__(), cuy.additionElement::__init__(), cuy.superimposeElement::__init__(), cuy.graphElement::__init__(), config.CFG::__str__(), validation.Sample::digest(), and VIDSelectorBase.VIDSelectorBase::initialize().

{ return "Absolute_Deviation"; }

Double_t AbsoluteDeviation::target ( Event *  e )

inlinevirtual

Implements LossFunction.

Definition at line 77 of file LossFunctions.h.

References Event::predictedValue, and Event::trueValue.

        {
        // The gradient.
            if ((e->trueValue - e->predictedValue) >= 0)
                return 1;
            else
                return -1;
        }