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DeltaR.py
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1 from __future__ import print_function
2 #ROOTTOOLS
3 import math
4 import copy
5 
6 def deltaR2( e1, p1, e2, p2):
7  de = e1 - e2
8  dp = deltaPhi(p1, p2)
9  return de*de + dp*dp
10 
11 
12 def deltaR( *args ):
13  return math.sqrt( deltaR2(*args) )
14 
15 
16 def deltaPhi( p1, p2):
17  '''Computes delta phi, handling periodic limit conditions.'''
18  res = p1 - p2
19  while res > math.pi:
20  res -= 2*math.pi
21  while res < -math.pi:
22  res += 2*math.pi
23  return res
24 
25 def matchObjectCollection3 ( objects, matchCollection, deltaRMax = 0.3, filter = lambda x,y : True ):
26  '''Univoque association of an element from matchCollection to an element of objects.
27  Reco and Gen objects get the "matched" attribute, true if they are part of a matched tuple.
28  By default, the matching is true only if delta R is smaller than 0.3.
29  '''
30  #
31  pairs = {}
32  if len(objects)==0:
33  return pairs
34  if len(matchCollection)==0:
35  return dict( zip(objects, [None]*len(objects)) )
36  # build all possible combinations
37 
38  allPairs = sorted([(deltaR2 (object.eta(), object.phi(), match.eta(), match.phi()), (object, match)) for object in objects for match in matchCollection if list(filter(object,match)) ])
39  #
40  # to flag already matched objects
41  # FIXME this variable remains appended to the object, I do not like it
42 
43  for object in objects:
44  object.matched = False
45  for match in matchCollection:
46  match.matched = False
47  #
48 
49  deltaR2Max = deltaRMax * deltaRMax
50  for dR2, (object, match) in allPairs:
51  if dR2 > deltaR2Max:
52  break
53  if dR2 < deltaR2Max and object.matched == False and match.matched == False:
54  object.matched = True
55  match.matched = True
56  pairs[object] = match
57  #
58 
59  for object in objects:
60  if object.matched == False:
61  pairs[object] = None
62  #
63 
64  return pairs
65  # by now, the matched attribute remains in the objects, for future usage
66  # one could remove it with delattr (object, attrname)
67 
68 
69 def cleanObjectCollection2( objects, masks, deltaRMin ):
70  '''Masks objects using a deltaR cut, another algorithm (same results).'''
71  if len(objects)==0:
72  return objects
73  deltaR2Min = deltaRMin*deltaRMin
74  cleanObjects = copy.copy( objects )
75  for mask in masks:
76  tooClose = []
77  for idx, object in enumerate(cleanObjects):
78  dR2 = deltaR2( object.eta(), object.phi(),
79  mask.eta(), mask.phi() )
80  if dR2 < deltaR2Min:
81  tooClose.append( idx )
82  nRemoved = 0
83  for idx in tooClose:
84  # yes, everytime an object is removed, the list of objects is updated
85  # so need to update the index accordingly.
86  # example: to remove : ele 1 and 2
87  # first, ele 1 is removed
88  # -> ele 2 is now at index 1
89  # one should again remove the element at index 1
90  idx -= nRemoved
91  del cleanObjects[idx]
92  nRemoved += 1
93  return cleanObjects
94 
95 
96 def cleanObjectCollection( objects, masks, deltaRMin ):
97  '''Masks objects using a deltaR cut.'''
98  if len(objects)==0 or len(masks)==0:
99  return objects, []
100  deltaR2Min = deltaRMin*deltaRMin
101  cleanObjects = []
102  dirtyObjects = []
103  for object in objects:
104  ok = True
105  for mask in masks:
106  dR2 = deltaR2( object.eta(), object.phi(),
107  mask.eta(), mask.phi() )
108  if dR2 < deltaR2Min:
109  ok = False
110  if ok:
111  cleanObjects.append( object )
112  else:
113  dirtyObjects.append( object )
114  return cleanObjects, dirtyObjects
115 
116 
117 
118 def bestMatch( object, matchCollection):
119  '''Return the best match to object in matchCollection, which is the closest object in delta R'''
120  deltaR2Min = float('+inf')
121  bm = None
122  for match in matchCollection:
123  dR2 = deltaR2( object.eta(), object.phi(),
124  match.eta(), match.phi() )
125  if dR2 < deltaR2Min:
126  deltaR2Min = dR2
127  bm = match
128  return bm, deltaR2Min
129 
130 
131 def matchObjectCollection( objects, matchCollection, deltaR2Max):
132  pairs = {}
133  if len(objects)==0:
134  return pairs
135  if len(matchCollection)==0:
136  return dict( zip(objects, [None]*len(objects)) )
137  for object in objects:
138  bm, dr2 = bestMatch( object, matchCollection )
139  if dr2<deltaR2Max:
140  pairs[object] = bm
141  else:
142  pairs[object] = None
143  return pairs
144 
145 
146 def matchObjectCollection2 ( objects, matchCollection, deltaRMax = 0.3 ):
147  '''Univoque association of an element from matchCollection to an element of objects.
148  Reco and Gen objects get the "matched" attribute, true if they are part of a matched tuple.
149  By default, the matching is true only if delta R is smaller than 0.3.
150  '''
151 
152  pairs = {}
153  if len(objects)==0:
154  return pairs
155  if len(matchCollection)==0:
156  return dict( zip(objects, [None]*len(objects)) )
157  # build all possible combinations
158  allPairs = sorted([(deltaR2 (object.eta(), object.phi(), match.eta(), match.phi()), (object, match)) for object in objects for match in matchCollection])
159 
160  # to flag already matched objects
161  # FIXME this variable remains appended to the object, I do not like it
162  for object in objects:
163  object.matched = False
164  for match in matchCollection:
165  match.matched = False
166 
167  deltaR2Max = deltaRMax * deltaRMax
168  for dR2, (object, match) in allPairs:
169  if dR2 > deltaR2Max:
170  break
171  if dR2 < deltaR2Max and object.matched == False and match.matched == False:
172  object.matched = True
173  match.matched = True
174  pairs[object] = match
175 
176  for object in objects:
177  if object.matched == False:
178  pairs[object] = None
179 
180  return pairs
181  # by now, the matched attribute remains in the objects, for future usage
182  # one could remove it with delattr (object, attrname)
183 
184 
185 
186 if __name__ == '__main__':
187 
188  import sys
189  args = sys.argv[1:]
190  fargs = map( float, args )
191 
192  print('dR2 = ', deltaR2( *fargs ))
193  print('dR = ', deltaR( *fargs ))
194 
195 
196 
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DeltaR.matchObjectCollection
def matchObjectCollection(objects, matchCollection, deltaR2Max)
Definition: DeltaR.py:131
DeltaR.matchObjectCollection3
def matchObjectCollection3(objects, matchCollection, deltaRMax=0.3, filter=lambda x, True y)
Definition: DeltaR.py:25
ALCARECOTkAlBeamHalo_cff.filter
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DeltaR.cleanObjectCollection2
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Definition: DeltaR.py:69
DeltaR.bestMatch
def bestMatch(object, matchCollection)
Definition: DeltaR.py:118
DeltaR.deltaR
def deltaR(*args)
Definition: DeltaR.py:12
DeltaR.deltaPhi
def deltaPhi(p1, p2)
Definition: DeltaR.py:16
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DeltaR.cleanObjectCollection
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Definition: DeltaR.py:96
DeltaR.deltaR2
def deltaR2(e1, p1, e2, p2)
Definition: DeltaR.py:6
DeltaR.matchObjectCollection2
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Definition: DeltaR.py:146
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How EventSelector::AcceptEvent() decides whether to accept an event for output otherwise it is excluding the probing of A single or multiple positive and the trigger will pass if any such matching triggers are PASS or EXCEPTION[A criterion thatmatches no triggers at all is detected and causes a throw.] A single negative with an expectation of appropriate bit checking in the decision and the trigger will pass if any such matching triggers are FAIL or EXCEPTION A wildcarded negative criterion that matches more than one trigger in the trigger list("!*", "!HLTx*" if it matches 2 triggers or more) will accept the event if all the matching triggers are FAIL. It will reject the event if any of the triggers are PASS or EXCEPTION(this matches the behavior of "!*" before the partial wildcard feature was incorporated). Triggers which are in the READY state are completely ignored.(READY should never be returned since the trigger paths have been run
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Definition: genParticles_cff.py:11