test_csbkgmodel.py
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#! /usr/bin/env python
# ==========================================================================
# This scripts performs unit tests for the csbkgmodel script.
#
# Copyright (C) 2019 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 cscripts
from testing import test
# ================================ #
# Test class for csbkgmodel script #
# ================================ #
class Test(test):
"""
Test class for csbkgmodel script
This test class makes unit tests for the csbkgmodel script by using it
from the command line and from Python.
"""
# Constructor
def __init__(self):
"""
Constructor
"""
# Call base class constructor
test.__init__(self)
# Set test datasets and parameters
self._myevents1 = self._datadir + '/crab_offaxis1.fits'
self._myevents2 = self._datadir + '/crab_offaxis2.fits'
self._lookup = self._datadir + '/hess_bkg_lookup.fits'
# Return
return
# Set test functions
def set(self):
"""
Set all test functions.
"""
# Set test name
self.name('csbkgmodel')
# Append tests
self.append(self._test_cmd, 'Test csbkgmodel on command line')
self.append(self._test_python, 'Test csbkgmodel from Python')
self.append(self._test_pickeling, 'Test csbkgmodel pickeling')
# Return
return
# Test csbkgmodel on command line
def _test_cmd(self):
"""
Test csbkgmodel on the command line.
"""
# Set script name
csbkgmodel = self._script('csbkgmodel')
# Setup csbkgmodel command
cmd = csbkgmodel+' inobs="'+self._events+'"'+ \
' caldb="'+self._caldb+'" irf="'+self._irf+'"' \
' instrument=CTA spatial=GAUSS gradient=yes'+ \
' spectral=NODES ebinalg=LOG emin=1.0 emax=100.0'+ \
' enumbins=8 runwise=yes rad=2.0'+ \
' outmodel="csbkgmodel_cmd1.xml"'+ \
' logfile="csbkgmodel_cmd1.log" chatter=4'
# Check if execution was successful
self.test_assert(self._execute(cmd) == 0,
'Check successful execution from command line')
# Check background model
self._check_bkg_model('csbkgmodel_cmd1.xml')
# Setup csbkgmodel command
cmd = csbkgmodel+' inobs="events_that_do_not_exist.fits"'+ \
' caldb="'+self._caldb+'" irf="'+self._irf+'"' \
' instrument=CTA spatial=GAUSS gradient=yes'+ \
' spectral=NODES ebinalg=LOG emin=1.0 emax=100.0'+ \
' enumbins=8 runwise=yes rad=2.0'+ \
' outmodel="csbkgmodel_cmd2.xml"' + \
' logfile="csbkgmodel_cmd2.log" chatter=1'
# Check if execution failed
self.test_assert(self._execute(cmd, success=False) != 0,
'Check invalid input file when executed from command line')
# Check csbkgmodel --help
self._check_help(csbkgmodel)
# Return
return
# Test csbkgmodel from Python
def _test_python(self):
"""
Test csbkgmodel from Python
"""
# Set-up csbkgmodel
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'GAUSS'
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py1.xml'
bkgmodel['logfile'] = 'csbkgmodel_py1.log'
# Run csbkgmodel script and save background model
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.run()
bkgmodel.save()
# Check background model
self._check_bkg_model('csbkgmodel_py1.xml')
# Now test without gradient, power law and not runwise
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'GAUSS'
bkgmodel['gradient'] = False
bkgmodel['spectral'] = 'PLAW'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = False
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 3
bkgmodel['outmodel'] = 'csbkgmodel_py2.xml'
bkgmodel['logfile'] = 'csbkgmodel_py2.log'
# Execute csbkgmodel script
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py2.xml')
# Now test AEFF model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'AEFF'
bkgmodel['gradient'] = False
bkgmodel['spectral'] = 'PLAW'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = False
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 4
bkgmodel['outmodel'] = 'csbkgmodel_py3.xml'
bkgmodel['logfile'] = 'csbkgmodel_py3.log'
# Execute csbkgmodel script
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py3.xml')
# Now test IRF model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'IRF'
bkgmodel['gradient'] = False
bkgmodel['spectral'] = 'PLAW'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = False
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 4
bkgmodel['outmodel'] = 'csbkgmodel_py4.xml'
bkgmodel['logfile'] = 'csbkgmodel_py4.log'
# Execute csbkgmodel script
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py4.xml')
# Test with multiple input observations
obs = gammalib.GObservations()
for s, events in enumerate([self._myevents1, self._myevents2]):
run = gammalib.GCTAObservation(events)
run.id(str(s + 1))
run.response(self._irf, gammalib.GCaldb('cta', self._caldb))
obs.append(run)
# Set-up csbkgmodel
bkgmodel = cscripts.csbkgmodel(obs)
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'GAUSS'
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'POW'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['ebingamma'] = 1.1
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py5.xml'
bkgmodel['logfile'] = 'csbkgmodel_py5.log'
# Execute csbkgmodel script
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py5.xml', nmodels=2)
# Test GAUSS(E) spatial model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'GAUSS(E)'
bkgmodel['snumbins'] = 2
bkgmodel['smin'] = 1.0
bkgmodel['smax'] = 10.0
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py6.xml'
bkgmodel['logfile'] = 'csbkgmodel_py6.log'
# Run csbkgmodel script and save background model
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py6.xml')
# Test LOOKUP spatial model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'LOOKUP'
bkgmodel['slufile'] = self._lookup
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py7.xml'
bkgmodel['logfile'] = 'csbkgmodel_py7.log'
# Run csbkgmodel script and save background model
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py7.xml')
# Test PROFILE spatial model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'PROFILE'
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py8.xml'
bkgmodel['logfile'] = 'csbkgmodel_py8.log'
# Run csbkgmodel script and save background model
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py8.xml')
# Test POLYNOM spatial model
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'POLYNOM'
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py9.xml'
bkgmodel['logfile'] = 'csbkgmodel_py9.log'
# Run csbkgmodel script and save background model
bkgmodel.logFileOpen() # Make sure we get a log file
bkgmodel.execute()
# Check background model
self._check_bkg_model('csbkgmodel_py9.xml')
# Return
return
# Test csbkgmodel pickeling
def _test_pickeling(self):
"""
Test csbkgmodel pickeling
"""
# Perform pickeling tests of empty class
self._pickeling(cscripts.csbkgmodel())
# Set-up csbkgmodel
bkgmodel = cscripts.csbkgmodel()
bkgmodel['inobs'] = self._events
bkgmodel['caldb'] = self._caldb
bkgmodel['irf'] = self._irf
bkgmodel['instrument'] = 'CTA'
bkgmodel['spatial'] = 'GAUSS'
bkgmodel['gradient'] = True
bkgmodel['spectral'] = 'NODES'
bkgmodel['ebinalg'] = 'LOG'
bkgmodel['emin'] = 1.0
bkgmodel['emax'] = 100.0
bkgmodel['enumbins'] = 8
bkgmodel['runwise'] = True
bkgmodel['rad'] = 2.0
bkgmodel['chatter'] = 2
bkgmodel['outmodel'] = 'csbkgmodel_py1_pickle.xml'
bkgmodel['logfile'] = 'csbkgmodel_py1_pickle.log'
# Perform pickeling tests of filled class
obj = self._pickeling(bkgmodel)
# Run csbkgmodel script and save background model
obj.logFileOpen() # Make sure we get a log file
obj.run()
obj.save()
# Check background model
self._check_bkg_model('csbkgmodel_py1_pickle.xml')
# Return
return
# Check background model
def _check_bkg_model(self, filename, nmodels=1):
"""
Check background model
"""
# Load model
models = gammalib.GModels(filename)
# Check model size
self.test_value(models.size(), nmodels,
'Check for %d model(s) in XML file' % nmodels)
# Return
return