lsmodel.py
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#! /usr/bin/env python
# ==========================================================================
# Generates model cube for Fermi/LAT data.
#
# Copyright (C) 2014-2016 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
# ============= #
# lsmodel class #
# ============= #
class lsmodel(gammalib.GApplication):
"""
Generates model cube for Fermi/LAT data.
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.
"""
# Constructor
def __init__(self, *argv):
"""
Constructor.
"""
# Set name and version
self._name = "lsmodel"
self._version = "1.1.0"
# 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
# Private methods
def _get_parameters(self):
"""
Get parameters from parfile.
"""
# Query user parameters
self["cntmap"].filename()
self["expmap"].filename()
self["ltcube"].filename()
self["srcmdl"].filename()
self["caldb"].string()
self["irf"].string()
# Read ahead output parameters
if (self._read_ahead()):
self["outfile"].filename()
# Write input parameters into logger
if self._logTerse():
self._log_parameters()
self._log("\n")
# Return
return
# Public methods
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 header
if self._logTerse():
self._log("\n")
self._log.header1("Generate model cube")
# Get user parameters
cntmap = self["cntmap"].filename()
expmap = self["expmap"].filename()
ltcube = self["ltcube"].filename()
srcmdl = self["srcmdl"].filename()
caldb = self["caldb"].string()
irf = self["irf"].string()
# Set LAT observation
obs = gammalib.GLATObservation()
obs.load_binned(cntmap, expmap, ltcube)
obs.response(irf, caldb)
# Set model (use first model for the moment)
models = gammalib.GModels(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")
# Return
return
def execute(self):
"""
Execute the script.
"""
# Open logfile
self._logFileOpen()
# Read ahead output parameters
self._read_ahead(True)
# Run the script
self.run()
# Save event cube
self.save()
# Return
return
def save(self):
"""
Save model cube.
"""
# Write header
if self._logTerse():
self._log("\n")
self._log.header1("Save model cube")
# Get outfile parameter
outfile = self["outfile"].filename()
# Log file name
if self._logTerse():
self._log(gammalib.parformat("Model cube"))
self._log(outfile.url())
self._log("\n")
# Save event cube
self._cube.save(outfile, self._clobber())
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Create instance of application
app = lsmodel(sys.argv)
# Execute application
app.execute()