lsmodel.py
6.25 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
#! /usr/bin/env python
# ==========================================================================
# This script generates a model map from a counts map and a source model.
#
# Copyright (C) 2014 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 gammalib
import sys
# ============= #
# lsmodel class #
# ============= #
class lsmodel(gammalib.GApplication):
"""
This class implements the model map generation script. It derives from
the GammaLib::GApplication class which provides support for parameter
files, command line arguments, and logging. In that way the Python
script behaves just as a regular ctool.
"""
def __init__(self, *argv):
"""
Constructor.
"""
# Set name
self.name = "lsmodel"
self.version = "0.1.0"
# Make sure that parfile exists
file = self.parfile()
# Initialise application
if len(argv) == 0:
gammalib.GApplication.__init__(self, self.name, self.version)
elif len(argv) ==1:
gammalib.GApplication.__init__(self, self.name, self.version, *argv)
else:
raise TypeError("Invalid number of arguments given.")
# Set logger properties
self.log_header()
self.log.date(True)
# Return
return
def __del__(self):
"""
Destructor.
"""
# Write separator into logger
if self.logTerse():
self.log("\n")
# Return
return
def parfile(self):
"""
Check if parfile exists. If parfile does not exist then create a
default parfile. This kluge avoids shipping the script with a parfile.
"""
# Set parfile name
parfile = self.name+".par"
try:
pars = gammalib.GApplicationPars(parfile)
except:
# Signal if parfile was not found
sys.stdout.write("Parfile "+parfile+" not found. Create default parfile.\n")
# Create default parfile
pars = gammalib.GApplicationPars()
pars.append(gammalib.GApplicationPar("cntmap","f","a","cntmap.fits","","","Counts map"))
pars.append(gammalib.GApplicationPar("expmap","f","a","binned_expmap.fits","","","Exposure map"))
pars.append(gammalib.GApplicationPar("ltcube","f","a","ltcube.fits","","","Livetime cube"))
pars.append(gammalib.GApplicationPar("srcmdl","f","a","crab_model.xml","","","Source model"))
pars.append(gammalib.GApplicationPar("caldb","s","h","","","","Calibration database"))
pars.append(gammalib.GApplicationPar("irf","s","a","P7REP_SOURCE_V15","","","Instrument response function"))
pars.append(gammalib.GApplicationPar("outfile","f","a","model_cube.fits","","","Output file name"))
pars.append_standard()
pars.save(parfile)
# Return
return
def get_parameters(self):
"""
Get parameters from parfile and setup the observation.
"""
# Get parameters
self.m_cntmap = self["cntmap"].filename()
self.m_expmap = self["expmap"].filename()
self.m_ltcube = self["ltcube"].filename()
self.m_srcmdl = self["srcmdl"].filename()
self.m_caldb = self["caldb"].string()
self.m_irf = self["irf"].string()
self.m_outfile = self["outfile"].filename()
# Set some fixed parameters
self.m_log = False # Logging in client tools
self.m_debug = False # Debugging in client tools
# Return
return
def execute(self):
"""
Execute the script.
"""
# Run the script
self.run()
# Return
return
def run(self):
"""
Run the script.
"""
# Switch screen logging on in debug mode
if self.logDebug():
self.log.cout(True)
# Get parameters
self.get_parameters()
# Write input parameters into logger
if self.logTerse():
self.log_parameters()
self.log("\n")
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Generate model cube")
# Set LAT observation
obs = gammalib.GLATObservation()
obs.load_binned(self.m_cntmap, self.m_expmap, self.m_ltcube)
obs.response(self.m_irf, self.m_caldb)
# Set model (use first model for the moment)
models = gammalib.GModels(self.m_srcmdl)
model = models[0]
# Get deep copy of GLATEventCube from observation
cube = gammalib.GLATEventCube(obs.events())
# Fill cube with model values
for i in range(cube.size()):
event = cube[i]
value = model.eval(event, obs) * event.size()
event.counts(value)
cube[i] = event
# Log cube
if self.logTerse():
self.log(str(cube))
self.log("\n")
# Write header
if self.logTerse():
self.log("\n")
self.log.header1("Save model cube")
# Save model cube
cube.save(self.m_outfile, self.clobber())
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
"""
Generates a model map from a counts map and a source model.
"""
# Create instance of application
app = lsmodel(sys.argv)
# Open logfile
app.logFileOpen()
# Execute application
app.execute()