pipeline_unbinned_mem.py
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#! /usr/bin/env python
# ==========================================================================
# Perform unbinned 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 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, ra=83.63, dec=22.01, rad=3.0,
emin=0.1, emax=100.0,
tmin=0.0, tmax=0.0,
debug=False):
"""
Simulation and binned analysis pipeline
Parameters
----------
obs : `~gammalib.GObservations`
Observation container
ra : float, optional
Right Ascension of Region of Interest centre (deg)
dec : float, optional
Declination of Region of Interest centre (deg)
rad : float, optional
Radius of Region of Interest (deg)
emin : float, optional
Minimum energy (TeV)
emax : float, optional
Maximum energy (TeV)
tmin : float, optional
Start time (s)
tmax : float, optional
Stop time (s)
debug : bool, optional
Debug function
"""
# Simulate events
sim = ctools.ctobssim(obs)
sim['debug'] = debug
sim.run()
# Select events
select = ctools.ctselect(sim.obs())
select['ra'] = ra
select['dec'] = dec
select['rad'] = rad
select['emin'] = emin
select['emax'] = emax
select['tmin'] = tmin
select['tmax'] = tmax
select['debug'] = debug
select.run()
# Perform maximum likelihood fitting
like = ctools.ctlike(select.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 unbinned analysis pipeline *')
print('********************************************')
# Setup observations
obs = setup_observations()
# Setup model
obs = setup_model(obs)
# Run analysis pipeline
run_pipeline(obs)