#include <CBAlgoShortestDistSmallCluster.h>

Inheritance diagram for cmtool::CBAlgoShortestDistSmallCluster:

Public Member Functions
	CBAlgoShortestDistSmallCluster ()
	Default constructor. More...

virtual	~CBAlgoShortestDistSmallCluster ()
	Default destructor. More...

virtual bool	Bool (const ::cluster::ClusterParamsAlg &cluster1, const ::cluster::ClusterParamsAlg &cluster2)
	Overloaded (from CBoolAlgoBase) Bool function. More...

void	SetSquaredDistanceCut (double d)
	Method to set cut value in cm^2 for distance compatibility test. More...

void	SetDebug (bool on)
	Method to set debug mode. More...

void	SetMinHits (size_t n)
	Set Minimum Number of Hits to consider Cluster. More...

void	SetMaxHits (size_t n)
	Set Maximum Number of Hits to consider Cluster. More...

double	ShortestDistanceSquared (double point_x, double point_y, double start_x, double start_y, double end_x, double end_y) const

Public Member Functions inherited from cmtool::CBoolAlgoBase
	CBoolAlgoBase ()
	Default constructor. More...

virtual	~CBoolAlgoBase ()
	Default destructor. More...

Public Member Functions inherited from cmtool::CMAlgoBase
	CMAlgoBase ()
	Default constructor. More...

virtual	~CMAlgoBase ()
	Default destructor. More...

virtual void	Reset ()
	Function to reset the algorithm instance called within CMergeManager/CMatchManager's Reset() ... maybe implemented via child class. More...

virtual void	EventBegin (const std::vector< cluster::ClusterParamsAlg > &clusters)

virtual void	EventEnd ()

virtual void	IterationBegin (const std::vector< cluster::ClusterParamsAlg > &clusters)

virtual void	IterationEnd ()

virtual void	Report ()

void	SetAnaFile (TFile *fout)
	Setter function for an output plot TFile pointer. More...

virtual void	SetVerbose (bool doit=true)
	Setter function for verbosity. More...

Protected Attributes
bool	_debug

size_t	_minHits
	bool to suppress lots of output if you want More...

size_t	_maxHits
	Min Number of hits for cluster to be considered. More...

double	_wire_2_cm
	Max Number of hits for cluster to be considered. More...

double	_time_2_cm

double	_min_distance_unit
	Conversion factors ogtten from GeometryUtilities. More...

double	_max_2D_dist2
	minimum distance b/t start and end point of cluster to use it More...

Protected Attributes inherited from cmtool::CMAlgoBase
TFile *	_fout
	TFile pointer to an output file. More...

bool	_verbose
	Boolean to choose verbose mode. Turned on if CMergeManager/CMatchManager's verbosity level is >= kPerMerging. More...

Detailed Description

User defined class CBAlgoShortestDistSmallCluster ... these comments are used to generate doxygen documentation!

Definition at line 26 of file CBAlgoShortestDistSmallCluster.h.

Constructor & Destructor Documentation

cmtool::CBAlgoShortestDistSmallCluster::CBAlgoShortestDistSmallCluster ( )

Default constructor.

Definition at line 9 of file CBAlgoShortestDistSmallCluster.cxx.

                                                                  {
 
     //this just sets default values
     SetDebug(false);
     SetMinHits(0);
 
     //1e9 is huge; everything will be merged
     SetSquaredDistanceCut(1e9);
 
     if(_verbose or _debug)
       std::cout << "wire2cm: " << _wire_2_cm << " time2cm: " << _time_2_cm << std::endl;
 
     ::util::GeometryUtilities geou;
     _wire_2_cm = geou.WireToCm();
     _time_2_cm = geou.TimeToCm();
 
     //shortest allowable length of a cluster (distance start->end point)
     //this is used in cases where the start/end points basically overlap
     _min_distance_unit = (_wire_2_cm < _time_2_cm) ? _wire_2_cm : _time_2_cm;
 
   } //end constructor

virtual cmtool::CBAlgoShortestDistSmallCluster::~CBAlgoShortestDistSmallCluster ( )

inlinevirtual

Default destructor.

Definition at line 34 of file CBAlgoShortestDistSmallCluster.h.

34 {};

Member Function Documentation

bool cmtool::CBAlgoShortestDistSmallCluster::Bool	(	const ::cluster::ClusterParamsAlg &	cluster1,
		const ::cluster::ClusterParamsAlg &	cluster2
	)

virtual

Overloaded (from CBoolAlgoBase) Bool function.

Reimplemented from cmtool::CBoolAlgoBase.

Definition at line 31 of file CBAlgoShortestDistSmallCluster.cxx.

   {
 
     //if number of hits not large enough skip
     if ( (_minHits > 0) and ((cluster1.GetNHits() < _minHits) or (cluster2.GetNHits() < _minHits)) ) {
       return false;
     }
 
     //if number of hits is too large
     if ( (_maxHits > _minHits) and ((cluster1.GetNHits() > _maxHits) or (cluster2.GetNHits() > _maxHits)) ) {
       return false;
     }
 
 
     double w_start1 = cluster1.GetParams().start_point.w;// * _wire_2_cm;
     double t_start1 = cluster1.GetParams().start_point.t;// * _time_2_cm;
     double w_end1   = cluster1.GetParams().end_point.w;//   * _wire_2_cm;
     double t_end1   = cluster1.GetParams().end_point.t;//   * _time_2_cm;
 
     double w_start2 = cluster2.GetParams().start_point.w;// * _wire_2_cm;
     double t_start2 = cluster2.GetParams().start_point.t;// * _time_2_cm;
     double w_end2   = cluster2.GetParams().end_point.w;//   * _wire_2_cm;
     double t_end2   = cluster2.GetParams().end_point.t;//   * _time_2_cm;
 
     if (_debug){
       std::cout << "Start point Cluster 1: (" << cluster1.GetParams().start_point.w << ", " << cluster1.GetParams().start_point.t << ")"  << std::endl;
       std::cout << "End point Cluster 2: (" << cluster1.GetParams().end_point.w << ", " << cluster1.GetParams().end_point.t << ")"  << std::endl;
       std::cout << "Start point Cluster 1: (" << cluster2.GetParams().start_point.w << ", " << cluster2.GetParams().start_point.t << ")"  << std::endl;
       std::cout << "End point Cluster 2: (" << cluster2.GetParams().end_point.w << ", " << cluster2.GetParams().end_point.t << ")"  << std::endl;
     }
 
     //First, pretend the first cluster is a 2D line segment, from its start point to end point
     //Find the shortest distance between start point of the second cluster to this line segment.
     //Repeat for end point of second cluster to this line segment.
     //Then, pretend second cluster is a 2D line segment, from its start point to end point.
     //Find the shortest distance between start point of the first cluster to this line segment.
     //Repeat for end point of first cluster to this line segment.
     //If the shortest of these four distances is less than the cutoff,
     //return true (the clusters are merge-compatible). else, return false.
 
     // Step 1: inspect (w_start1, t_start1) vs. line (w_start2, t_start2) => (w_end2, t_end2)
     double shortest_distance2 = ShortestDistanceSquared(w_start1, t_start1,
                                                         w_start2, t_start2,
                                                         w_end2, t_end2);
 
     // Step 2: inspect (w_end1, t_end1) vs. line (w_start2, t_start2) => (w_end2, t_end2)
     double shortest_distance2_tmp = ShortestDistanceSquared(w_end1, t_end1,
                                                             w_start2, t_start2,
                                                             w_end2, t_end2);
 
     shortest_distance2 = (shortest_distance2_tmp < shortest_distance2) ?
       shortest_distance2_tmp : shortest_distance2;
 
     // Step 3: inspect (w_start2, t_start2) vs. line (w_start1, t_start1) => (w_end1, t_end1)
     shortest_distance2_tmp = ShortestDistanceSquared(w_start2, t_start2,
                                                      w_start1, t_start1,
                                                      w_end1, t_end1);
 
     shortest_distance2 = (shortest_distance2_tmp < shortest_distance2) ?
       shortest_distance2_tmp : shortest_distance2;
 
     // Step 4: inspect (w_end2, t_end2) vs. line (w_start1, t_start1) => (w_end1, t_end1)
     shortest_distance2_tmp = ShortestDistanceSquared(w_end2, t_end2,
                                                      w_start1, t_start1,
                                                      w_end1, t_end1);
 
     shortest_distance2 = (shortest_distance2_tmp < shortest_distance2) ?
       shortest_distance2_tmp : shortest_distance2;
 
     bool compatible = shortest_distance2 < _max_2D_dist2;
 
     if(_verbose or _debug) {
 
       if(compatible) std::cout<<Form(" Compatible in distance (%g).\n",shortest_distance2);
       else std::cout<<Form(" NOT compatible in distance (%g).\n",shortest_distance2);
 
     }
 
     return compatible;
 
 
   }//end Bool function

void cmtool::CBAlgoShortestDistSmallCluster::SetDebug ( bool on )

inline

Method to set debug mode.

Definition at line 45 of file CBAlgoShortestDistSmallCluster.h.

45 { _debug = on; }

cmtool::CBAlgoShortestDistSmallCluster::_debug

bool _debug

Definition: CBAlgoShortestDistSmallCluster.h:65

void cmtool::CBAlgoShortestDistSmallCluster::SetMaxHits ( size_t n )

inline

Set Maximum Number of Hits to consider Cluster.

Definition at line 51 of file CBAlgoShortestDistSmallCluster.h.

51 { _maxHits = n; }

cet::n

std::void_t< T > n

Definition: metaprogramming.h:28

cmtool::CBAlgoShortestDistSmallCluster::_maxHits

size_t _maxHits

Min Number of hits for cluster to be considered.

Definition: CBAlgoShortestDistSmallCluster.h:69

void cmtool::CBAlgoShortestDistSmallCluster::SetMinHits ( size_t n )

inline

Set Minimum Number of Hits to consider Cluster.

Definition at line 48 of file CBAlgoShortestDistSmallCluster.h.

48 { _minHits = n; }

cmtool::CBAlgoShortestDistSmallCluster::_minHits

size_t _minHits

bool to suppress lots of output if you want

Definition: CBAlgoShortestDistSmallCluster.h:67

cet::n

std::void_t< T > n

Definition: metaprogramming.h:28

void cmtool::CBAlgoShortestDistSmallCluster::SetSquaredDistanceCut ( double d )

inline

Method to set cut value in cm^2 for distance compatibility test.

Definition at line 42 of file CBAlgoShortestDistSmallCluster.h.

42 { _max_2D_dist2 = d; }

bump_copyright.d

string d

Definition: bump_copyright.py:70

cmtool::CBAlgoShortestDistSmallCluster::_max_2D_dist2

double _max_2D_dist2

minimum distance b/t start and end point of cluster to use it

Definition: CBAlgoShortestDistSmallCluster.h:75

double cmtool::CBAlgoShortestDistSmallCluster::ShortestDistanceSquared	(	double	point_x,
		double	point_y,
		double	start_x,
		double	start_y,
		double	end_x,
		double	end_y
	)		const

Function to compute a distance between a 2D point (point_x, point_y) to a 2D finite line segment (start_x, start_y) => (end_x, end_y).

Definition at line 115 of file CBAlgoShortestDistSmallCluster.cxx.

                                                                                                        {
 
     //This code finds the shortest distance between a point and a line segment.
     //code based off sample from
     //http://stackoverflow.com/questions/849211/shortest-distance-between-a-point-and-a-line-segment
     //note to self: rewrite this with TVector2 and compare time differences...
     //TVector2 code might be more understandable
 
     double distance_squared = -1;
 
     // Line segment: from ("V") = (start_x, start_y) to ("W")=(end_x, end_y)
     double length_squared = pow((end_x - start_x), 2) + pow((end_y - start_y), 2);
 
     // Treat the case start & end point overlaps
     if( (_verbose or _debug) and length_squared < _min_distance_unit) {
 
       std::cout << std::endl;
       std::cout << Form(" Provided very short line segment: (%g,%g) => (%g,%g)",
                         start_x,start_y,end_x,end_y) << std::endl;
       std::cout << " Likely this means one of two clusters have start & end point identical." << std::endl;
       std::cout << " Check the cluster output!" << std::endl;
       std::cout << std::endl;
       std::cout << Form(" At this time, the algorithm uses a point (%g,%g)",start_x,start_y) << std::endl;
       std::cout << " to represent this cluster's location." << std::endl;
       std::cout << std::endl;
 
       return (pow((point_x - start_x),2) + pow((point_y - start_y),2));
     }
 
     //Find shortest distance between point ("P")=(point_x,point_y) to this line segment
     double t = ( (point_x - start_x)*(end_x - start_x) + (point_y - start_y)*(end_y - start_y) ) / length_squared;
 
     if(t<0.0) distance_squared = pow((point_x - start_x), 2) + pow((point_y - start_y), 2);
 
     else if (t>1.0) distance_squared = pow((point_x - end_x), 2) + pow(point_y - end_y, 2);
 
     else distance_squared = pow((point_x - (start_x + t*(end_x - start_x))), 2) + pow((point_y - (start_y + t*(end_y - start_y))),2);
 
     return distance_squared;
 
   }//end ShortestDistanceSquared function