make_ts_distributions.py
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#! /usr/bin/env python
# ==========================================================================
# Generate TS distributions as function of energy for an OFF observation
#
# Copyright (C) 2011-2016 Jurgen Knodlseder
#
# 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 cscripts
# ====================== #
# Create TS distribution #
# ====================== #
def create_ts(datadir, loge, emin, emax, ntrials=100, duration=180000.0,
enumbins=0, log=False):
"""
Create TS distribution.
Parameters
----------
datadir : str
Data directory
loge : float
Logarithm of mean energy (TeV)
emin : float
Minimum energy (TeV)
emax : float
Maximum energy (TeV)
ntrials : int, optional
Number of MC samples
durations : float, optional
Observation duration (s)
enumbins : int, optional
Number of energy bins
log : bool, optional
Create log file(s)
"""
# Generate output filename
outfile = 'ts_'+str(loge)+'.dat'
# Setup cstsdist tool
tsdist = cscripts.cstsdist()
tsdist['inmodel'] = datadir+'/crab.xml'
tsdist['srcname'] = 'Crab'
tsdist['outfile'] = outfile
tsdist['ntrials'] = ntrials
tsdist['caldb'] = 'prod2'
tsdist['irf'] = 'South_50h'
tsdist['ra'] = 83.63
tsdist['dec'] = 22.01
tsdist['emin'] = emin
tsdist['emax'] = emax
tsdist['enumbins'] = enumbins
tsdist['tmin'] = 0
tsdist['tmax'] = duration
tsdist['rad'] = 5.0
tsdist['npix'] = 200
tsdist['binsz'] = 0.05
# Optionally open the log file
if log:
tsdist.logFileOpen()
# Run tool
tsdist.run()
# Return
return
# ==================== #
# Make TS distribution #
# ==================== #
def make_ts_distribution():
"""
Make TS distribution
"""
# Set usage string
usage = 'make_ts_distributions.py [-n ntrials] [-e enumbins]'\
' [-t duration] [-m max_threads] [-d datadir]'
# Set default options
options = [{'option': '-n', 'value': '100'},
{'option': '-e', 'value': '0'},
{'option': '-t', 'value': '180000.0'},
{'option': '-m', 'value': '1'},
{'option': '-d', 'value': 'data'}]
# Get arguments and options from command line arguments
args, options = cscripts.ioutils.get_args_options(options, usage)
# Extract script parameters from options
ntrials = int(options[0]['value'])
enumbins = int(options[1]['value'])
duration = float(options[2]['value'])
max_threads = int(options[3]['value'])
datadir = options[4]['value']
# Loop over energy bands. The energy bands are those that are also
# used for sensitivity computation.
for ieng in range(20):
# Set energies
loge = -1.7 + ieng * 0.2
emean = pow(10.0, loge)
emin = pow(10.0, loge-0.1)
emax = pow(10.0, loge+0.1)
if loge < 0:
loge = 'm'+str(abs(loge))
else:
loge = 'p'+str(abs(loge))
# Create TS
create_ts(datadir, loge, emin, emax, ntrials=ntrials, enumbins=enumbins,
duration=duration)
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Make TS distribution
make_ts_distribution()