pipeline_binned_mem.py
5.85 KB
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
198
199
200
201
202
203
204
205
206
#! /usr/bin/env python
# ==========================================================================
# Perform binned in-memory analysis of simulated CTA data.
#
# Copyright (C) 2015-2016 Juergen Knoedlseder
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import sys
import gammalib
import ctools
from cscripts import obsutils
# ================== #
# Setup observations #
# ================== #
def setup_observations(pattern='four', ra=83.63, dec=22.01, offset=1.5,
emin=0.1, emax=100.0, rad=5.0, duration=180.0,
deadc=0.95, caldb='prod2', irf='South_0.5h'):
"""
Returns an observation container
Parameters
----------
pattern : str, optional
Pointing pattern, either 'single' or 'four'
ra : float, optional
Right Ascension of pattern centre (deg)
dec : float, optional
Declination of pattern centre (deg)
offset : float, optional
Offset between observations of pattern (deg)
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
rad : float, optional
ROI radius used for analysis (deg)
duration : float, optional
Duration of one CTA observation (s)
deadc : float, optional
Deadtime correction factor
caldb : str, optional
Calibration database path
irf : str, optional
Instrument response function
Returns
-------
obs : `~gammalib.GObservations`
Observation container
"""
# Set list of observations
obs_def_list = obsutils.set_obs_patterns(pattern,
ra=ra,
dec=dec,
offset=offset)
# Get observation container
obs = obsutils.set_obs_list(obs_def_list,
duration=duration,
emin=emin,
emax=emax,
rad=rad,
caldb=caldb,
irf=irf)
# Return observation container
return obs
# =========== #
# Setup model #
# =========== #
def setup_model(obs, model='data/crab.xml'):
"""
Setup model for analysis
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
model : str, optional
Model definition XML file
Returns
-------
obs : `~gammalib.GObservations`
Observation container
"""
# Append model from file to observation container
obs.models(gammalib.GModels(model))
# Return observation container
return obs
# ================================ #
# Simulation and analysis pipeline #
# ================================ #
def run_pipeline(obs, emin=0.1, emax=100.0,
enumbins=20, nxpix=200, nypix=200, binsz=0.02,
coordsys='CEL', proj='CAR', debug=False):
"""
Simulation and binned analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
enumbins : int, optional
Number of energy bins
nxpix : int, optional
Number of pixels in X axis
nypix : int, optional
Number of pixels in Y axis
binsz : float, optional
Pixel size (deg)
coordsys : str, optional
Coordinate system
proj : str, optional
Coordinate projection
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim.run()
# Bin events by looping over all observations in the container
obs = gammalib.GObservations()
obs.models(sim.obs().models())
for run in sim.obs():
# Create container with a single observation
container = gammalib.GObservations()
container.append(run)
# Bin events for that observation
bin = ctools.ctbin(container)
bin['ebinalg'] = 'LOG'
bin['emin'] = emin
bin['emax'] = emax
bin['enumbins'] = enumbins
bin['nxpix'] = nxpix
bin['nypix'] = nypix
bin['binsz'] = binsz
bin['coordsys'] = coordsys
bin['usepnt'] = True
bin['proj'] = proj
bin.run()
# Append result to observations
obs.extend(bin.obs())
# Perform maximum likelihood fitting
like = ctools.ctlike(obs)
like['debug'] = True # Switch this always on for results in console
like.run()
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Dump header
print('********************************************')
print('* CTA binned analysis pipeline *')
print('********************************************')
# Get optional arguments
if len(sys.argv) == 2:
datadir = sys.argv[1]
else:
datadir = 'data'
# Setup observations
obs = setup_observations()
# Setup model
obs = setup_model(obs, model=datadir+'/crab.xml')
# Run analysis pipeline
run_pipeline(obs)