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
|
# author : S. Mandalia
# s.p.mandalia@qmul.ac.uk
#
# date : March 17, 2018
"""
Useful GolemFit wrappers for the BSM flavour ratio analysis
"""
from __future__ import absolute_import, division
import argparse
import socket
from functools import partial
import GolemFitPy as gf
from utils.enums import DataType, SteeringCateg
from utils.misc import enum_parse, thread_factors
def steering_params(args):
steering_categ = args.ast
params = gf.SteeringParams()
params.quiet = False
params.fastmode = True
params.simToLoad= steering_categ.name.lower()
params.spline_dom_efficiency = False
params.spline_hole_ice = False
params.spline_anisotrophy = False
params.evalThreads = args.threads
# params.evalThreads = thread_factors(args.threads)[1]
params.diffuse_fit_type = gf.DiffuseFitType.SinglePowerLaw
return params
def set_up_as(fitter, params):
print 'Injecting the model', params
asimov_params = gf.FitParameters(gf.sampleTag.HESE)
for parm in params:
asimov_params.__setattr__(parm.name, parm.value)
fitter.SetupAsimov(asimov_params)
def setup_fitter(args, asimov_paramset):
datapaths = gf.DataPaths()
sparams = steering_params(args)
npp = gf.NewPhysicsParams()
fitter = gf.GolemFit(datapaths, sparams, npp)
set_up_as(fitter, asimov_paramset)
return fitter
def get_llh(fitter, params):
fitparams = gf.FitParameters(gf.sampleTag.HESE)
for parm in params:
fitparams.__setattr__(parm.name, parm.value)
llh = -fitter.EvalLLH(fitparams)
return llh
def get_llh_freq(fitter, params):
print 'setting to {0}'.format(params)
fitparams = gf.FitParameters(gf.sampleTag.HESE)
for parm in params:
fitparams.__setattr__(parm.name, parm.value)
fitter.SetFitParametersSeed(fitparams)
return -fitter.MinLLH().likelihood
def data_distributions(fitter):
hdat = fitter.GetDataDistribution()
binedges = np.asarray([fitter.GetZenithBinsData(), fitter.GetEnergyBinsData()])
return hdat, binedges
def gf_argparse(parser):
parser.add_argument(
'--data', default='real', type=partial(enum_parse, c=DataType),
choices=DataType, help='select datatype'
)
parser.add_argument(
'--ast', default='p2_0', type=partial(enum_parse, c=SteeringCateg),
choices=SteeringCateg,
help='use asimov/fake dataset with specific steering'
)
|
