|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
|
import itertools
import ROOT
try:
ROOT.BTagEntry
except AttributeError:
ROOT.gROOT.ProcessLine('.L BTagCalibrationStandalone.cpp+')
try:
ROOT.BTagEntry
except AttributeError:
print('ROOT.BTagEntry is needed! Please copy ' \
'BTagCalibrationStandalone.[h|cpp] to the working directory. Exit.')
exit(-1)
separate_by_op = False
separate_by_flav = False
class DataLoader(object):
def __init__(self, csv_data, measurement_type, operating_point, flavour):
self.meas_type = measurement_type
self.op = operating_point
self.flav = flavour
# list of entries
ens = []
for l in csv_data:
if not l.strip():
continue # skip empty lines
try:
e = ROOT.BTagEntry(l)
if (e.params.measurementType == measurement_type
and ((not separate_by_op)
or e.params.operatingPoint == operating_point)
and ((not separate_by_flav)
or e.params.jetFlavor == flavour)
):
ens.append(e)
except TypeError:
raise RuntimeError("Error: can not interpret line: " + l)
self.entries = ens
if not ens:
return
# fixed data
self.ops = set(e.params.operatingPoint for e in ens)
self.flavs = set(e.params.jetFlavor for e in ens)
self.syss = set(e.params.sysType for e in ens)
self.etas = set((e.params.etaMin, e.params.etaMax) for e in ens)
self.pts = set((e.params.ptMin, e.params.ptMax) for e in ens)
self.discrs = set((e.params.discrMin, e.params.discrMax)
for e in ens
if e.params.operatingPoint == 3)
self.ETA_MIN = -2.4
self.ETA_MAX = 2.4
self.PT_MIN = min(e.params.ptMin for e in ens)
self.PT_MAX = max(e.params.ptMax for e in ens)
if any(e.params.operatingPoint == 3 for e in ens):
self.DISCR_MIN = min(
e.params.discrMin
for e in ens
if e.params.operatingPoint == 3
)
self.DISCR_MAX = max(
e.params.discrMax
for e in ens
if e.params.operatingPoint == 3
)
else:
self.DISCR_MIN = 0.
self.DISCR_MAX = 1.
# test points for variable data (using bound +- epsilon)
eps = 1e-4
eta_test_points = list(itertools.ifilter(
lambda x: self.ETA_MIN < x < self.ETA_MAX,
itertools.chain(
(a + eps for a, _ in self.etas),
(a - eps for a, _ in self.etas),
(b + eps for _, b in self.etas),
(b - eps for _, b in self.etas),
(self.ETA_MIN + eps, self.ETA_MAX - eps),
)
))
abseta_test_points = list(itertools.ifilter(
lambda x: 0. < x < self.ETA_MAX,
itertools.chain(
(a + eps for a, _ in self.etas),
(a - eps for a, _ in self.etas),
(b + eps for _, b in self.etas),
(b - eps for _, b in self.etas),
(eps, self.ETA_MAX - eps),
)
))
pt_test_points = list(itertools.ifilter(
lambda x: self.PT_MIN < x < self.PT_MAX,
itertools.chain(
(a + eps for a, _ in self.pts),
(a - eps for a, _ in self.pts),
(b + eps for _, b in self.pts),
(b - eps for _, b in self.pts),
(self.PT_MIN + eps, self.PT_MAX - eps),
)
))
discr_test_points = list(itertools.ifilter(
lambda x: self.DISCR_MIN < x < self.DISCR_MAX,
itertools.chain(
(a + eps for a, _ in self.discrs),
(a - eps for a, _ in self.discrs),
(b + eps for _, b in self.discrs),
(b - eps for _, b in self.discrs),
(self.DISCR_MIN + eps, self.DISCR_MAX - eps),
)
))
# use sets
self.eta_test_points = set(round(f, 5) for f in eta_test_points)
self.abseta_test_points = set(round(f, 5) for f in abseta_test_points)
self.pt_test_points = set(round(f, 5) for f in pt_test_points)
self.discr_test_points = set(round(f, 5) for f in discr_test_points)
def print_data(self):
print("\nFound operating points:")
print(self.ops)
print("\nFound jet flavors:")
print(self.flavs)
print("\nFound sys types (need at least 'central', 'up', 'down'; " \
"also 'up_SYS'/'down_SYS' compatibility is checked):")
print(self.syss)
print("\nFound eta ranges: (need everything covered from %g or 0. " \
"up to %g):" % (self.ETA_MIN, self.ETA_MAX))
print(self.etas)
print("\nFound pt ranges: (need everything covered from %g " \
"to %g):" % (self.PT_MIN, self.PT_MAX))
print(self.pts)
print("\nFound discr ranges: (only needed for operatingPoint==3, " \
"covered from %g to %g):" % (self.DISCR_MIN, self.DISCR_MAX))
print(self.discrs)
print("\nTest points for eta (bounds +- epsilon):")
print(self.eta_test_points)
print("\nTest points for pt (bounds +- epsilon):")
print(self.pt_test_points)
print("\nTest points for discr (bounds +- epsilon):")
print(self.discr_test_points)
print("")
def get_data_csv(csv_data):
# grab measurement types
meas_types = set(
l.split(',')[1].strip()
for l in csv_data
if len(l.split()) == 11
)
# grab operating points
ops = set(
int(l.split(',')[0])
for l in csv_data
if len(l.split()) == 11
) if separate_by_op else ['all']
# grab flavors
flavs = set(
int(l.split(',')[3])
for l in csv_data
if len(l.split()) == 11
) if separate_by_flav else ['all']
# make loaders and filter empty ones
lds = list(
DataLoader(csv_data, mt, op, fl)
for mt in meas_types
for op in ops
for fl in flavs
)
lds = [d for d in lds if d.entries]
return lds
def get_data(filename):
with open(filename) as f:
csv_data = f.readlines()
if not (csv_data and "OperatingPoint" in csv_data[0]):
print("Data file does not contain typical header: %s. Exit" % filename)
return False
csv_data.pop(0) # remove header
return get_data_csv(csv_data)
|