deltar Namespace Reference

Functions
def	bestMatch (object, matchCollection)
def	cleanObjectCollection (objects, masks, deltaRMin)
def	cleanObjectCollection2 (objects, masks, deltaRMin)
def	deltaPhi (p1, p2)
def	deltaR (args)
def	deltaR2 (e1, p1, e2=None, p2=None)
def	inConeCollection (pivot, particles, deltaRMax, deltaRMin=1e-5)
def	matchObjectCollection
def	matchObjectCollection2 (objects, matchCollection, deltaRMax=0.3)
def	matchObjectCollection3

Function Documentation

bestMatch()

def deltar.bestMatch	(		object,
			matchCollection
	)

Return the best match to object in matchCollection, which is the closest object in delta R

Definition at line 138 of file deltar.py.

References deltaR2(), and nano_mu_digi_cff.float.

Referenced by PrimaryVertexAnalyzer4PUSlimmed.fillResolutionAndPullHistograms(), HLTMuonPlotter.findMatches(), CSCMake2DRecHit.findWireBx(), objects.LeptonAnalyzer.LeptonAnalyzer.makeLeptons(), GlobalCosmicMuonTrajectoryBuilder.match(), matchObjectCollection(), and MuonIdTruthInfo.truthMatchMuon().

def bestMatch( object, matchCollection):
    '''Return the best match to object in matchCollection, which is the closest object in delta R'''
    deltaR2Min = float('+inf')
    bm = None
    for match in matchCollection:
        dR2 = deltaR2( object.eta(), object.phi(),
                       match.eta(), match.phi() )
        if dR2 < deltaR2Min:
            deltaR2Min = dR2
            bm = match
    return bm, deltaR2Min

cleanObjectCollection()

def deltar.cleanObjectCollection	(		objects,
			masks,
			deltaRMin
	)

Masks objects using a deltaR cut.

Definition at line 118 of file deltar.py.

References deltaR2().

Referenced by JetAnalyzer.JetAnalyzer.process().

def cleanObjectCollection( objects, masks, deltaRMin ):
    '''Masks objects using a deltaR cut.'''
    if len(objects)==0 or len(masks)==0:
        return objects, []
    deltaR2Min = deltaRMin*deltaRMin
    cleanObjects = []
    dirtyObjects = []
    for object in objects:
        ok = True 
        for mask in masks:
            dR2 = deltaR2( object.eta(), object.phi(),
                           mask.eta(), mask.phi() )
            if dR2 < deltaR2Min:
                ok = False
        if ok:
            cleanObjects.append( object )
        else:
            dirtyObjects.append( object )
    return cleanObjects, dirtyObjects

cleanObjectCollection2()

def deltar.cleanObjectCollection2	(		objects,
			masks,
			deltaRMin
	)

Masks objects using a deltaR cut, another algorithm (same results).

Definition at line 91 of file deltar.py.

References deltaR2().

def cleanObjectCollection2( objects, masks, deltaRMin ):
    '''Masks objects using a deltaR cut, another algorithm (same results).'''
    if len(objects)==0:
        return objects
    deltaR2Min = deltaRMin*deltaRMin
    cleanObjects = copy.copy( objects )
    for mask in masks:
        tooClose = []
        for idx, object in enumerate(cleanObjects):
            dR2 = deltaR2( object.eta(), object.phi(),
                           mask.eta(), mask.phi() )
            if dR2 < deltaR2Min:
                tooClose.append( idx )
        nRemoved = 0
        for idx in tooClose:
            # yes, everytime an object is removed, the list of objects is updated
            # so need to update the index accordingly.
            # example: to remove : ele 1 and 2
            #  first, ele 1 is removed
            #  -> ele 2 is now at index 1
            # one should again remove the element at index 1
            idx -= nRemoved
            del cleanObjects[idx]
            nRemoved += 1 
    return cleanObjects

deltaPhi()

def deltar.deltaPhi	(		p1,
			p2
	)

Computes delta phi, handling periodic limit conditions.

Definition at line 20 of file deltar.py.

Referenced by deltaR2().

def deltaPhi( p1, p2):
    '''Computes delta phi, handling periodic limit conditions.'''
    res = p1 - p2
    while res > math.pi:
        res -= 2*math.pi
    while res < -math.pi:
        res += 2*math.pi
    return res

deltaR()

def deltar.deltaR

(

args

)

Definition at line 16 of file deltar.py.

References deltaR2().

def deltaR( *args ):
    return math.sqrt( deltaR2(*args) )

deltaR2()

def deltar.deltaR2	(		e1,
			p1,
			e2 = None,
			p2 = None
	)

Take either 4 arguments (eta,phi, eta,phi) or two objects that have 'eta', 'phi' methods)

Definition at line 7 of file deltar.py.

References deltaPhi().

Referenced by bestMatch(), cleanObjectCollection(), cleanObjectCollection2(), deltaR(), and inConeCollection().

def deltaR2( e1, p1, e2=None, p2=None):
    """Take either 4 arguments (eta,phi, eta,phi) or two objects that have 'eta', 'phi' methods)"""
    if (e2 == None and p2 == None):
        return deltaR2(e1.eta(),e1.phi(), p1.eta(), p1.phi())
    de = e1 - e2
    dp = deltaPhi(p1, p2)
    return de*de + dp*dp

inConeCollection()

def deltar.inConeCollection	(		pivot,
			particles,
			deltaRMax,
			deltaRMin = 1e-5
	)

Returns the list of particles that are less than deltaRMax away from pivot.

Definition at line 30 of file deltar.py.

References deltaR2().

def inConeCollection(pivot, particles, deltaRMax, deltaRMin=1e-5):
    '''Returns the list of particles that are less than deltaRMax away from pivot.'''
    dR2Max = deltaRMax ** 2
    dR2Min = deltaRMin ** 2 if deltaRMin  > 0 else -1
    results = []
    for ptc in particles:
        dR2 = deltaR2(pivot.eta(), pivot.phi(), ptc.eta(), ptc.phi()) 
        if dR2Min < dR2 and dR2 < dR2Max:
            results.append(ptc)
    return results

matchObjectCollection()

def deltar.matchObjectCollection	(		objects,
			matchCollection,
			deltaR2Max,
			filter = lambda x,
			y
	)

Definition at line 151 of file deltar.py.

References bestMatch(), ALCARECOTkAlBeamHalo_cff.filter, and reco.zip().

Referenced by SimpleJetAnalyzer.SimpleJetAnalyzer.process(), core.TriggerMatchAnalyzer.TriggerMatchAnalyzer.process(), Matcher.Matcher.process(), and JetAnalyzer.JetAnalyzer.process().

def matchObjectCollection( objects, matchCollection, deltaR2Max, filter = lambda x,y : True):
    pairs = {}
    if len(objects)==0:
        return pairs
    if len(matchCollection)==0:
        return dict( list(zip(objects, [None]*len(objects))) )
    for object in objects:
        bm, dr2 = bestMatch( object, [mob for mob in matchCollection if filter(object,mob)] )
        if dr2<deltaR2Max:
            pairs[object] = bm
        else:
            pairs[object] = None            
    return pairs

matchObjectCollection2()

def deltar.matchObjectCollection2	(		objects,
			matchCollection,
			deltaRMax = 0.3
	)

Univoque association of an element from matchCollection to an element of objects.
Reco and Gen objects get the "matched" attribute, true is they are re part of a matched tulpe.
By default, the matching is true only if delta R is smaller than 0.3.

Definition at line 166 of file deltar.py.

References reco.zip().

Referenced by objects.JetAnalyzer.JetAnalyzer.matchJets().

def matchObjectCollection2 ( objects, matchCollection, deltaRMax = 0.3 ):
    '''Univoque association of an element from matchCollection to an element of objects.
    Reco and Gen objects get the "matched" attribute, true is they are re part of a matched tulpe.
    By default, the matching is true only if delta R is smaller than 0.3.
    '''

    pairs = {}
    if len(objects)==0:
        return pairs
    if len(matchCollection)==0:
        return dict( list(zip(objects, [None]*len(objects))) )
    # build all possible combinations
    allPairs = sorted([(deltaR2 (object.eta(), object.phi(), match.eta(), match.phi()), (object, match)) for object in objects for match in matchCollection])

    # to flag already matched objects
    # FIXME this variable remains appended to the object, I do not like it
    for object in objects:
        object.matched = False
    for match in matchCollection:
        match.matched = False

    deltaR2Max = deltaRMax * deltaRMax
    for dR2, (object, match) in allPairs:
        if dR2 > deltaR2Max:
            break
        if dR2 < deltaR2Max and object.matched == False and match.matched == False:
            object.matched = True
            match.matched = True
            pairs[object] = match

    for object in objects:
        if object.matched == False:
            pairs[object] = None

    return pairs
    # by now, the matched attribute remains in the objects, for future usage
    # one could remove it with delattr (object, attrname)

matchObjectCollection3()

def deltar.matchObjectCollection3	(		objects,
			matchCollection,
			deltaRMax = 0.3,
			filter = lambda x,
			y
	)

Definition at line 41 of file deltar.py.

References funct.abs(), ALCARECOTkAlBeamHalo_cff.filter, and reco.zip().

Referenced by objects.LeptonAnalyzer.LeptonAnalyzer.matchAnyLeptons(), objects.IsoTrackAnalyzer.matchIsoTrack(), objects.LeptonAnalyzer.LeptonAnalyzer.matchLeptons(), objects.PhotonAnalyzer.PhotonAnalyzer.matchPhotons(), objects.TauAnalyzer.TauAnalyzer.matchTaus(), objects.LeptonAnalyzer.LeptonAnalyzer.matchToPhotons(), and core.TriggerMatchAnalyzer.TriggerMatchAnalyzer.process().

def matchObjectCollection3 ( objects, matchCollection, deltaRMax = 0.3, filter = lambda x,y : True ):
    '''Univoque association of an element from matchCollection to an element of objects.
    Reco and Gen objects get the "matched" attribute, true is they are re part of a matched tulpe.
    By default, the matching is true only if delta R is smaller than 0.3. 
    '''
    #

    pairs = {}
    if len(objects)==0:
        return pairs
    if len(matchCollection)==0:
        return dict( list(zip(objects, [None]*len(objects))) )
    # build all possible combinations

    objectCoords = [ (o.eta(),o.phi(),o) for o in objects ]
    matchdCoords = [ (o.eta(),o.phi(),o) for o in matchCollection ]
    allPairs = sorted([(deltaR2 (oeta, ophi, meta, mphi), (object, match)) for (oeta,ophi,object) in objectCoords for (meta,mphi,match) in matchdCoords if abs(oeta-meta)<=deltaRMax and filter(object,match) ])
    #allPairs = [(deltaR2 (object.eta(), object.phi(), match.eta(), match.phi()), (object, match)) for object in objects for match in matchCollection if filter(object,match) ]
    #
    # to flag already matched objects
    # FIXME this variable remains appended to the object, I do not like it

    for object in objects:
        object.matched = False
    for match in matchCollection:
        match.matched = False
    #

    deltaR2Max = deltaRMax * deltaRMax
    for dR2, (object, match) in allPairs:
        if dR2 > deltaR2Max:
            break
        if dR2 < deltaR2Max and object.matched == False and match.matched == False:
            object.matched = True
            match.matched = True
            pairs[object] = match
    #

    for object in objects:
        if object.matched == False:
            pairs[object] = None
    #

    return pairs
    # by now, the matched attribute remains in the objects, for future usage
    # one could remove it with delattr (object, attrname)

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