#include <FsmwModeFinder3d.h>

Inheritance diagram for FsmwModeFinder3d:

Public Member Functions
virtual FsmwModeFinder3d *	clone () const
	FsmwModeFinder3d (float fraction=.5, float weightExponent=-2., float cutoff=10, int no_weights_above=10)
virtual GlobalPoint	operator() (const std::vector< PointAndDistance > &) const
Private Attributes
float	theCutoff
float	theFraction
int	theNoWeightsAbove
float	theWeightExponent

Detailed Description

this is a half sample mode finder that works coordinate wise, in 3d.

Definition at line 12 of file FsmwModeFinder3d.h.

Constructor & Destructor Documentation

FsmwModeFinder3d::FsmwModeFinder3d	(	float	fraction = `.5`,
		float	weightExp = `-2.`,
		float	cutoff = `10`,
		int	no_w_a = `10`
	)

Constructor

Parameters:

fraction	the fraction of data points that have to be within the interval.
weightExponent	The exponent by which the weights are taken into account. Default is "w^-1", w being the track distance + cutoff (see below).
cutoff	weight = ( cutoff + 10000 * distance ) * weightExponent
no_weights_above	ignore weights as long as the number of data points is > x

Half sample mode in 3d, as a functional class.

Definition at line 10 of file FsmwModeFinder3d.cc.

References theFraction.

Referenced by clone().

                                                               : theFraction ( fraction ),
        theWeightExponent ( weightExp ), theCutoff(cutoff),
        theNoWeightsAbove ( no_w_a )
{
    assert ( theFraction > 0. && theFraction < 1. );
}

Member Function Documentation

FsmwModeFinder3d * FsmwModeFinder3d::clone ( void ) const [virtual]

Implements ModeFinder3d.

Definition at line 62 of file FsmwModeFinder3d.cc.

References FsmwModeFinder3d().

{
    return new FsmwModeFinder3d( *this );
}

GlobalPoint FsmwModeFinder3d::operator() ( const std::vector< PointAndDistance > & values ) const [virtual]

Implements ModeFinder3d.

Definition at line 18 of file FsmwModeFinder3d.cc.

References algo, i, funct::pow(), run_regression::ret, theCutoff, theFraction, theNoWeightsAbove, theWeightExponent, create_public_lumi_plots::tmp_x, create_public_lumi_plots::tmp_y, and CommonMethods::weight().

{
    typedef Cluster1D<void> SimpleCluster;
    std::vector< SimpleCluster > vx, vy, vz;
    vx.reserve ( values.size() - 1 );
    vy.reserve ( values.size() - 1 );
    vz.reserve ( values.size() - 1 );
    std::vector < const void * > emptyvec;

    for ( std::vector< PointAndDistance >::const_iterator i = values.begin();
          i != values.end(); ++i )
    {
        float weight = 1.;
        if ( static_cast<int>( values.size() ) < theNoWeightsAbove )
        {
            // compute weights if we have fewer than theNoWeightsAbove
            // data points
            weight = pow ( theCutoff + 10000 * i->second, theWeightExponent );
        };

        SimpleCluster tmp_x ( Measurement1D ( i->first.x(), 1.0 ),
                              emptyvec, weight );
        SimpleCluster tmp_y ( Measurement1D ( i->first.y(), 1.0 ),
                              emptyvec, weight );
        SimpleCluster tmp_z ( Measurement1D ( i->first.z(), 1.0 ),
                              emptyvec, weight );
        vx.push_back ( tmp_x );
        vy.push_back ( tmp_y );
        vz.push_back ( tmp_z );
    };

    FsmwClusterizer1D<void> algo( theFraction );
    std::vector < SimpleCluster > cresx = algo(vx).first;
    std::vector < SimpleCluster > cresy = algo(vy).first;
    std::vector < SimpleCluster > cresz = algo(vz).first;
    assert ( cresx.size() && cresy.size() && cresz.size() );

    GlobalPoint ret ( cresx.begin()->position().value(),
                      cresy.begin()->position().value(),
                      cresz.begin()->position().value() );
    return ret;
}