Class ClusterCleanerUtilities

java.lang.Object

org.jlab.rec.dc.cluster.ClusterCleanerUtilities

public class ClusterCleanerUtilities
extends Object

Constructor Summary

Constructors

Constructor	Description
ClusterCleanerUtilities()

Method Summary

Modifier and Type	Method	Description
List<List<Hit>>	byLayerListSorter(List<Hit> DCHits, int sector, int superlyr)
FittedCluster	ClusterCleaner(FittedCluster clus, ClusterFitter cf, DCGeant4Factory DcDetector)
List<FittedCluster>	ClusterSplitter(FittedCluster clus, int nextClsStartIndex, ClusterFitter cf)	Pattern Recognition step for identifying clusters in a clump: Find the points that are consistent with belonging to the same cluster.
Cluster	ClusterSticher(Cluster thisclus, Cluster nextclus, int cid)
int	count_nlayers_hit(Hit[] hits_inlayer)
List<Hit>	HitListPruner(List<Hit> hits)	Prunes the input hit list to remove noise candidates; the algorithm finds contiguous hits in a layer (column) and removes hits according to the number (Nc) of such contiguous hits in a given layer.If Nc=3, keep only the middle hit If Nc=4, keep only the first and last hit in that column; if Nc > 4, keep the first 2 and last 2 hits in that column, if Nc > 10 remove all hits in that column.
boolean	isExceptionalCluster(List hitsInClus)	Wrapper for checking if a cluster of Hit objects is exceptional.
boolean	isExceptionalFittedCluster(List hitsInClus)	Wrapper for checking if a cluster of FittedHit objects is exceptional.
FittedCluster	IsolatedHitsPruner(FittedCluster clus)
FittedCluster	LRAmbiguityResolver(DataEvent event, FittedCluster fClus, ClusterFitter cf, IndexedTable tab, DCGeant4Factory DcDetector, TimeToDistanceEstimator tde)
void	outOfTimersRemover(FittedCluster fClus, boolean removeHit)
FittedCluster	OverlappingClusterResolver(FittedCluster thisclus, List<FittedCluster> clusters)	A method to select the largest cluster among a set of clusters with 4 or more of overlaping hits
FittedCluster	SecondariesRemover(DataEvent event, FittedCluster clus, ClusterFitter cf, IndexedTable tab, DCGeant4Factory DcDetector, TimeToDistanceEstimator tde)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

ClusterCleanerUtilities

public ClusterCleanerUtilities()

Method Details

ClusterSplitter

public List<FittedCluster> ClusterSplitter(FittedCluster clus,
 int nextClsStartIndex,
 ClusterFitter cf)

Pattern Recognition step for identifying clusters in a clump: Find the points that are consistent with belonging to the same cluster. This step precedes the initial estimates of the track segments which require further refining. The method employed is that of Hough Transforms. Define the dimension of the r-theta accumulator array used for pattern recognition of (rho, phi) points.

Parameters:

clus - the fitted cluster. This cluster is examined for overlaps and // tracks.

nextClsStartIndex - the index of the next cluster in the splitted cluster.

cf -

Returns:

a list of fitted clusters

byLayerListSorter

public List<List<Hit>> byLayerListSorter(List<Hit> DCHits,
 int sector,
 int superlyr)

count_nlayers_hit

public int count_nlayers_hit(Hit[] hits_inlayer)

Parameters:

hits_inlayer - the hits in a given layer

Returns:

the number of layers hit at a certain wire coordinate

LRAmbiguityResolver

public FittedCluster LRAmbiguityResolver(DataEvent event,
 FittedCluster fClus,
 ClusterFitter cf,
 IndexedTable tab,
 DCGeant4Factory DcDetector,
 TimeToDistanceEstimator tde)

SecondariesRemover

public FittedCluster SecondariesRemover(DataEvent event,
 FittedCluster clus,
 ClusterFitter cf,
 IndexedTable tab,
 DCGeant4Factory DcDetector,
 TimeToDistanceEstimator tde)

OverlappingClusterResolver

public FittedCluster OverlappingClusterResolver(FittedCluster thisclus,
 List<FittedCluster> clusters)

A method to select the largest cluster among a set of clusters with 4 or more of overlaping hits

Parameters:

thisclus - the cluster to be compared to a list of other clusters

clusters - the list of clusters

Returns:

the selected cluster

HitListPruner

public List<Hit> HitListPruner(List<Hit> hits)

Prunes the input hit list to remove noise candidates; the algorithm finds contiguous hits in a layer (column) and removes hits according to the number (Nc) of such contiguous hits in a given layer.If Nc=3, keep only the middle hit If Nc=4, keep only the first and last hit in that column; if Nc > 4, keep the first 2 and last 2 hits in that column, if Nc > 10 remove all hits in that column.

Parameters:

hits - the unfitted hits

Returns:

IsolatedHitsPruner

public FittedCluster IsolatedHitsPruner(FittedCluster clus)

Parameters:

clus -

Returns:

a new cluster that is contiguous

outOfTimersRemover

public void outOfTimersRemover(FittedCluster fClus,
 boolean removeHit)

ClusterCleaner

public FittedCluster ClusterCleaner(FittedCluster clus,
 ClusterFitter cf,
 DCGeant4Factory DcDetector)

isExceptionalCluster

public boolean isExceptionalCluster(List hitsInClus)

Wrapper for checking if a cluster of Hit objects is exceptional.

isExceptionalFittedCluster

public boolean isExceptionalFittedCluster(List hitsInClus)

Wrapper for checking if a cluster of FittedHit objects is exceptional.

ClusterSticher

public Cluster ClusterSticher(Cluster thisclus,
 Cluster nextclus,
 int cid)