test_CTA.py
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# ==========================================================================
# This module performs unit tests for the GammaLib CTA module.
#
# Copyright (C) 2012-2018 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 os
import gammalib
import math
import test_support
# ================================== #
# Test class for GammaLib CTA module #
# ================================== #
class Test(gammalib.GPythonTestSuite):
"""
Test class for GammaLib CTA module
"""
# Constructor
def __init__(self):
"""
Constructor
"""
# Call base class constructor
gammalib.GPythonTestSuite.__init__(self)
# Set test directories
self._data = os.environ['TEST_CTA_DATA']
self._caldb = self._data + '/../caldb'
# Return
return
# Setup GCTAEventList container
def _setup_eventlist(self):
"""
Setup GCTAEventList container
Returns
-------
list : `~gammalib.GCTAEventList`
GCTAEventList container
"""
# Setup event list container
list = gammalib.GCTAEventList()
for i in range(10):
dir = gammalib.GCTAInstDir(gammalib.GSkyDir(),float(i),float(i))
energy = gammalib.GEnergy(float(i),'MeV')
time = gammalib.GTime(float(i),'sec')
atom = gammalib.GCTAEventAtom(dir, energy, time)
list.append(atom)
# Return event list container
return list
# Setup GCTAEventCube
def _setup_eventcube(self):
"""
Setup GCTAEventCube
Returns
-------
cube : `~gammalib.GCTAEventCube`
GCTAEventCube
"""
# Setup event cube
map = gammalib.GSkyMap('CAR','CEL',0.0,0.0,1.0,1.0,5,5,2)
ebds = gammalib.GEbounds(2, gammalib.GEnergy(1.0, 'TeV'),
gammalib.GEnergy(10.0, 'TeV'))
gti = gammalib.GGti(gammalib.GTime(0.0,'sec'),
gammalib.GTime(1.0,'sec'))
cube = gammalib.GCTAEventCube(map, ebds, gti)
counts = 0.0
for bin in cube:
counts += 1.0
bin.counts(1.0)
# Return event cube
return cube
# Test GCTAEventList class access operators
def _test_eventlist_access(self):
"""
Test GCTAEventList class observation access
"""
# Setup event list container
list = self._setup_eventlist()
# Perform event list access tests
test_support.energy_container_access_index(self, list)
# Return
return
# Test GCTAEventList class slicing
def _test_eventlist_slicing(self):
"""
Test GCTAEventList class slicing
"""
# Setup event list container
list = self._setup_eventlist()
# Perform slicing tests
test_support.energy_container_slicing(self, list)
# Return
return
# Test effective area response
def _test_aeff(self):
"""
Test GCTAAeff classes
"""
# Test GCTAAeff2D file constructor
filename = self._caldb + '/prod1_gauss.fits'
aeff = gammalib.GCTAAeff2D(filename)
# Test Aeff values
self.test_value(aeff(0.0, 0.0), 5535774176.75, 0.1,
'Test reference effective area value')
self.test_value(aeff(1.0, 0.0), 20732069462.7, 0.1,
'Test reference effective area value')
self.test_value(aeff(0.0, 0.01745), 5682897797.76, 0.1,
'Test reference effective area value')
self.test_value(aeff(1.0, 0.01745), 18446656815.1, 0.1,
'Test reference effective area value')
# Test that Aeff values outside boundaries are zero
self.test_value(aeff(-1.80001, 0.0), 0.0, 1.0e-6,
'Test that effective area is zero for energy below'
' minimum energy')
self.test_value(aeff(+2.20001, 0.0), 0.0, 1.0e-6,
'Test that effective area is zero for energy above'
' maximum energy')
self.test_value(aeff(0.0, -0.00001), 0.0, 1.0e-6,
'Test that effective area is zero for offset angle'
' below minimum offset angle')
self.test_value(aeff(0.0, 0.13963), 0.0, 1.0e-6,
'Test that effective area is zero for offset angle'
' above maximum offset angle')
# Test GCTAAeffPerfTable file constructor
filename = self._caldb + '/cta_dummy_irf.dat'
aeff = gammalib.GCTAAeffPerfTable(filename)
# Test Aeff values
self.test_value(aeff(0.0, 0.0), 2738898000.0, 0.1)
self.test_value(aeff(1.0, 0.0), 16742420500.0, 0.1)
self.test_value(aeff(0.0, 0.01745), 2590995083.29, 0.1)
self.test_value(aeff(1.0, 0.01745), 15838314971.2, 0.1)
# Test GCTAAeffArf file constructor
filename = self._caldb + '/dc1/arf.fits'
aeff = gammalib.GCTAAeffArf(filename)
# Test Aeff values
self.test_value(aeff(0.0, 0.0), 1607246236.98, 0.1)
self.test_value(aeff(1.0, 0.0), 4582282342.98, 0.1)
self.test_value(aeff(0.0, 0.01745), 1607246236.98, 0.1)
self.test_value(aeff(1.0, 0.01745), 4582282342.98, 0.1)
# Return
return
# Test point spread function response
def _test_psf(self):
"""
Test GCTAPsf classes
"""
# Test GCTAPsf2D file constructor
filename = self._caldb + '/prod1_gauss.fits'
psf = gammalib.GCTAPsf2D(filename)
# Test PSF values
self.test_value(psf(0.0, 0.0, 0.0), 163782.469465, 1.0e-6)
self.test_value(psf(0.001, 0.0, 0.0), 97904.9307797, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.0), 616076.98558, 1.0e-6)
self.test_value(psf(0.001, 1.0, 0.0), 88932.681708, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.01745), 433247.309504, 1.0e-6)
self.test_value(psf(0.001, 1.0, 0.01745), 111075.0692681, 1.0e-6)
# Test GCTAPsfKing file constructor
filename = self._caldb + '/prod1_king.fits'
psf = gammalib.GCTAPsfKing(filename)
# Test PSF values
self.test_value(psf(0.0, 0.0, 0.0), 213616.312600672, 1.0e-6)
self.test_value(psf(0.001, 0.0, 0.0), 90918.3030269623, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.0), 1126804.99931516, 1.0e-5)
self.test_value(psf(0.001, 1.0, 0.0), 54873.6646449112, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.01745), 660972.636049452, 1.0e-6)
self.test_value(psf(0.001, 1.0, 0.01745), 80272.4048345619, 1.0e-6)
# Test GCTAPsfPerfTable file constructor
filename = self._caldb + '/cta_dummy_irf.dat'
psf = gammalib.GCTAPsfPerfTable(filename)
# Test PSF values
self.test_value(psf(0.0, 0.0, 0.0), 537853.354917, 1.0e-6)
self.test_value(psf(0.001, 0.0, 0.0), 99270.360144, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.0), 1292604.7473727, 1.0e-6)
self.test_value(psf(0.001, 1.0, 0.0), 22272.4258111, 1.0e-6)
self.test_value(psf(0.0, 1.0, 0.01745), 1292604.7473727, 1.0e-6)
self.test_value(psf(0.001, 1.0, 0.01745), 22272.4258111, 1.0e-6)
# Test GCTAPsfVector file constructor
filename = self._caldb + '/dc1/psf_magic.fits'
psf = gammalib.GCTAPsfVector(filename)
# Print
self.test_value(psf(0.0, -1.0, 0.0), 42263.9572394, 1.0e-6)
self.test_value(psf(0.001, -1.0, 0.0), 37008.8652966, 1.0e-6)
self.test_value(psf(0.0, 0.0, 0.0), 208989.164294, 1.0e-6)
self.test_value(psf(0.001, 0.0, 0.0), 108388.031915, 1.0e-6)
self.test_value(psf(0.0, 0.0, 0.01745), 208989.164294, 1.0e-6)
self.test_value(psf(0.001, 0.0, 0.01745), 108388.031915, 1.0e-6)
# Return
return
# Test energy dispersion
def _test_edisp(self):
"""
Test GCTAEdisp classes
"""
# Set some energies
eng0 = gammalib.GEnergy(1.0, 'TeV')
eng01 = gammalib.GEnergy(1.2589254, 'TeV')
eng001 = gammalib.GEnergy(1.023293, 'TeV')
eng0001 = gammalib.GEnergy(1.0023052, 'TeV')
eng1001 = gammalib.GEnergy(10.023052, 'TeV')
eng1 = gammalib.GEnergy(10.0, 'TeV')
eng30 = gammalib.GEnergy(30.0, 'TeV')
# Test GCTAEdispRmf file constructor
filename = self._caldb + '/dc1/rmf.fits'
edisp = gammalib.GCTAEdispRmf(filename)
# Test energy dispersion values
self.test_value(edisp(eng30, eng0), 0.0, 1.0e-9)
self.test_value(edisp(eng0, eng30), 0.0, 1.0e-9)
# Test GCTAEdispPerfTable file constructor
filename = self._caldb + '/cta_dummy_irf.dat'
edisp = gammalib.GCTAEdispPerfTable(filename)
# Test energy dispersion values
self.test_value(edisp(eng0, eng0), 4.3386871e-06, 1.0e-6)
self.test_value(edisp(eng0001, eng0), 4.3273514e-06, 1.0e-6)
self.test_value(edisp(eng001, eng0), 4.1090489e-06, 1.0e-6)
self.test_value(edisp(eng01, eng0), 1.4984969e-07, 1.0e-6)
self.test_value(edisp(eng1, eng1), 7.8454726e-07, 1.0e-6)
self.test_value(edisp(eng1001, eng1, 0.0), 7.8194077e-07, 1.0e-6)
# Test GCTAResponseIrf file constructor
db = gammalib.GCaldb(self._caldb)
irf = 'cta_dummy_irf'
rsp = gammalib.GCTAResponseIrf(irf, db)
# Test nedisp computations
#dir = gammalib.GSkyDir()
#pnt = gammalib.GCTAPointing()
#time = gammalib.GTime()
#self.test_value(rsp.nedisp(dir, GEnergy(3.7, "TeV"), time, pnt,
# GEbounds(GEnergy(0.1, "TeV"),
# GEnergy(10.0, "TeV"))),
# 1.0, 0.005)
#self.test_value(rsp.nedisp(dir, GEnergy(3.7, "TeV"), time, pnt,
# GEbounds(GEnergy(2.72345, "TeV"),
# GEnergy(5.026615, "TeV"))),
# 1.0, 0.005)
#self.test_value(rsp.nedisp(dir, GEnergy(3.7, "TeV"), time, pnt,
# GEbounds(GEnergy(3.7, "TeV"),
# GEnergy(10.0, "TeV"))),
# 0.5, 0.005)
# Test response
def _test_response(self):
"""
Test response classes
"""
# Load 1DC CTA observation (ARF, PSF, RMF)
filename = self._data + '/irf_1dc.xml'
obs = gammalib.GObservations(filename)
# Return
return
# Test On/Off analysis
def _test_onoff(self):
"""
Test On/Off analysis
"""
# Set Crab position
crab = gammalib.GSkyDir()
crab.radec_deg(83.6331, 22.0145)
# Set point-source spatial model based on Crab position
spatial = gammalib.GModelSpatialPointSource(crab)
# Create On region
on = gammalib.GSkyRegions()
on.append(gammalib.GSkyRegionCircle(crab, 0.2))
# Create Off region
offdir = gammalib.GSkyDir()
offdir.radec_deg(83.6331, 23.5145)
off = gammalib.GSkyRegions()
off.append(gammalib.GSkyRegionCircle(offdir, 0.5))
# Set energy binning
etrue = gammalib.GEbounds(40, gammalib.GEnergy(0.1, 'TeV'),
gammalib.GEnergy(10.0, 'TeV'))
ereco = gammalib.GEbounds(20, gammalib.GEnergy(0.1, 'TeV'),
gammalib.GEnergy(10.0, 'TeV'))
# Create On/Off observations from CTA observations
filename = self._data + '/irf_unbinned.xml'
inobs = gammalib.GObservations(filename)
outobs = gammalib.GObservations()
for run in inobs:
onoff = gammalib.GCTAOnOffObservation(run, spatial, etrue, ereco, on, off)
outobs.append(onoff)
# Load model container and attach it to the observations
models = gammalib.GModels(self._data + '/onoff_model.xml')
outobs.models(models)
# Perform maximum likelihood fit
lm = gammalib.GOptimizerLM()
outobs.optimize(lm)
outobs.errors(lm)
# Test On/Off model fitting results
sky = outobs.models()['Crab']
bgd = outobs.models()['Background']
self.test_value(sky['Prefactor'].value(), 6.456877e-16, 1.0e-18,
'Check sky model prefactor value')
self.test_value(sky['Prefactor'].error(), 2.176260e-17, 1.0e-20,
'Check sky model prefactor error')
self.test_value(sky['Index'].value(), -2.575639, 1.0e-4,
'Check sky model index value')
self.test_value(sky['Index'].error(), 0.030702, 1.0e-4,
'Check sky model index error')
self.test_value(bgd['Prefactor'].value(), 1.182291, 0.01,
'Check background model prefactor value')
self.test_value(bgd['Prefactor'].error(), 0.152625, 0.01,
'Check background model prefactor error')
self.test_value(bgd['Index'].value(), 0.520937, 0.01,
'Check background model index value')
self.test_value(bgd['Index'].error(), 0.086309, 0.01,
'Check background model index error')
# Save PHA, ARF and RMFs
for run in outobs:
run.on_spec().save('test_cta_onoff_pha_on.fits', True)
run.off_spec().save('test_cta_onoff_pha_off.fits', True)
run.arf().save('test_cta_onoff_arf.fits', True)
run.rmf().save('test_cta_onoff_rmf.fits', True)
# Save On/Off observations
outobs.save('test_cta_onoff.xml')
# Return
return
# Test class pickeling
def _test_pickeling(self):
"""
Test class pickeling
"""
# Set CALDB
os.environ['CALDB'] = os.environ['TEST_DATA']+'/caldb'
# Perform pickeling tests of empty classes
test_support.pickeling(self, gammalib.GCTAAeff2D())
#test_support.pickeling(self, gammalib.GCTAAeffArf())
#test_support.pickeling(self, gammalib.GCTAAeffPerfTable())
test_support.pickeling(self, gammalib.GCTABackground3D())
#test_support.pickeling(self, gammalib.GCTABackgroundPerfTable())
test_support.pickeling(self, gammalib.GCTACubeBackground())
test_support.pickeling(self, gammalib.GCTACubeEdisp())
test_support.pickeling(self, gammalib.GCTACubeExposure())
test_support.pickeling(self, gammalib.GCTACubePsf())
#test_support.pickeling(self, gammalib.GCTACubeSourceDiffuse())
#test_support.pickeling(self, gammalib.GCTACubeSourcePoint())
test_support.pickeling(self, gammalib.GCTAEdisp2D())
#test_support.pickeling(self, gammalib.GCTAEdispPerfTable())
#test_support.pickeling(self, gammalib.GCTAEdispRmf())
test_support.pickeling(self, gammalib.GCTAEventAtom())
test_support.pickeling(self, gammalib.GCTAEventBin())
test_support.pickeling(self, gammalib.GCTAEventCube())
test_support.pickeling(self, gammalib.GCTAEventList())
test_support.pickeling(self, gammalib.GCTAInstDir())
test_support.pickeling(self, gammalib.GCTAModelBackground())
test_support.pickeling(self, gammalib.GCTAModelAeffBackground())
test_support.pickeling(self, gammalib.GCTAModelCubeBackground())
test_support.pickeling(self, gammalib.GCTAModelIrfBackground())
test_support.pickeling(self, gammalib.GCTAModelRadialAcceptance())
test_support.pickeling(self, gammalib.GCTAModelRadialGauss())
test_support.pickeling(self, gammalib.GCTAModelRadialPolynom())
test_support.pickeling(self, gammalib.GCTAModelRadialProfile())
test_support.pickeling(self, gammalib.GCTAModelSpatialGradient())
test_support.pickeling(self, gammalib.GCTAModelSpatialMultiplicative())
test_support.pickeling(self, gammalib.GCTAObservation())
test_support.pickeling(self, gammalib.GCTAOnOffObservation())
test_support.pickeling(self, gammalib.GCTAPointing())
test_support.pickeling(self, gammalib.GCTAPsf2D())
test_support.pickeling(self, gammalib.GCTAPsfKing())
#test_support.pickeling(self, gammalib.GCTAPsfPerfTable())
test_support.pickeling(self, gammalib.GCTAPsfTable())
#test_support.pickeling(self, gammalib.GCTAPsfVector())
test_support.pickeling(self, gammalib.GCTAResponseCube())
test_support.pickeling(self, gammalib.GCTAResponseIrf())
test_support.pickeling(self, gammalib.GCTAResponseTable())
test_support.pickeling(self, gammalib.GCTARoi())
# Setup test
list = self._setup_eventlist()
cube = self._setup_eventcube()
atom = list[0]
dir = gammalib.GSkyDir()
instdir = gammalib.GCTAInstDir(dir, 2.0, -3.0)
pivot = gammalib.GEnergy(1.0,'TeV')
plaw = gammalib.GModelSpectralPlaw(1.0,-2.0,pivot)
irfname = os.environ['TEST_DATA']+'/caldb/data/cta/prod2/bcf/North_0.5h/irf_file.fits.gz'
bin = gammalib.GCTAEventBin()
bin.dir(instdir)
bin.energy(pivot)
bin.time(gammalib.GTime(1.0,'sec'))
bin.counts(1.0)
bin.solidangle(0.1)
bin.ewidth(pivot)
bin.ontime(100.0)
bin.weight(1.0)
emin = gammalib.GEnergy(1.0,'TeV')
emax = gammalib.GEnergy(10.0,'TeV')
engs = gammalib.GEnergies(10,emin,emax)
ebds = gammalib.GEbounds(2,emin,emax)
region = gammalib.GSkyRegionCircle(dir, 0.2)
regs = gammalib.GSkyRegions()
regs.append(region)
ptsrc = gammalib.GModelSpatialPointSource()
expcube = gammalib.GCTACubeExposure('CAR','CEL',0.,0.,0.1,0.1,10,10,engs)
psfcube = gammalib.GCTACubePsf('CAR','CEL',0.,0.,0.1,0.1,10,10,engs,1.0,10)
bgdcube = gammalib.GCTACubeBackground('CAR','CEL',0.,0.,0.1,0.1,10,10,ebds)
edispcube = gammalib.GCTACubeEdisp('CAR','CEL',0.,0.,0.1,0.1,10,10,engs,1.0,10)
caldb = gammalib.GCaldb('cta','prod2')
rspirf = gammalib.GCTAResponseIrf('North_0.5h', caldb)
rspcube1 = gammalib.GCTAResponseCube(expcube, psfcube, bgdcube)
rspcube2 = gammalib.GCTAResponseCube(expcube, psfcube, edispcube, bgdcube)
bin.energy(pivot)
obs1 = gammalib.GCTAObservation()
obs1.events(list)
obs1.response(rspirf)
obs2 = gammalib.GCTAObservation()
obs2.events(cube)
obs2.response(rspirf)
obs3 = gammalib.GCTAObservation()
obs3.events(cube)
obs3.response(rspcube1)
obs4 = gammalib.GCTAObservation()
obs4.events(cube)
obs4.response(rspcube2)
obs5 = gammalib.GCTAOnOffObservation(obs1, ptsrc, ebds, ebds, regs, regs)
radgauss = gammalib.GCTAModelRadialGauss(1.0)
radacc = gammalib.GCTAModelRadialAcceptance(radgauss, plaw)
multi = gammalib.GCTAModelSpatialMultiplicative()
multi.append(radgauss, 'Src1')
multi.append(radgauss, 'Src2')
kingname = self._caldb + '/prod1_king.fits'
hessaeff = self._data + '/irf_hess_aeff.fits.gz'
hesspsf = self._data + '/irf_hess_psf.fits.gz'
hessedisp = self._data + '/irf_hess_edisp.fits.gz'
hessbkg = self._data + '/irf_hess_bkg.fits.gz'
hessirf = gammalib.GCTAResponseIrf()
hessirf.load_aeff(hessaeff)
hessirf.load_psf(hesspsf)
hessirf.load_edisp(hessedisp)
hessirf.load_background(hessbkg)
# Perform pickeling tests of filled classes
test_support.pickeling(self, gammalib.GCTAAeff2D(irfname))
#test_support.pickeling(self, gammalib.GCTAAeffArf())
#test_support.pickeling(self, gammalib.GCTAAeffPerfTable())
test_support.pickeling(self, gammalib.GCTABackground3D(irfname))
#test_support.pickeling(self, gammalib.GCTABackgroundPerfTable())
test_support.pickeling(self, gammalib.GCTACubeBackground(bgdcube))
test_support.pickeling(self, gammalib.GCTACubeEdisp(edispcube))
test_support.pickeling(self, gammalib.GCTACubeExposure(expcube))
test_support.pickeling(self, gammalib.GCTACubePsf(psfcube))
#test_support.pickeling(self, gammalib.GCTACubeSourceDiffuse())
#test_support.pickeling(self, gammalib.GCTACubeSourcePoint())
test_support.pickeling(self, gammalib.GCTAEdisp2D(irfname))
#test_support.pickeling(self, gammalib.GCTAEdispPerfTable())
#test_support.pickeling(self, gammalib.GCTAEdispRmf())
test_support.pickeling(self, gammalib.GCTAEventAtom(atom))
test_support.pickeling(self, gammalib.GCTAEventBin(bin))
test_support.pickeling(self, gammalib.GCTAEventCube(cube))
test_support.pickeling(self, gammalib.GCTAEventList(list))
test_support.pickeling(self, gammalib.GCTAInstDir(instdir))
test_support.pickeling(self, gammalib.GCTAModelBackground(radgauss,plaw))
test_support.pickeling(self, gammalib.GCTAModelAeffBackground(plaw))
test_support.pickeling(self, gammalib.GCTAModelCubeBackground(plaw))
test_support.pickeling(self, gammalib.GCTAModelIrfBackground(plaw))
test_support.pickeling(self, gammalib.GCTAModelRadialAcceptance(radacc))
test_support.pickeling(self, gammalib.GCTAModelRadialGauss(1.0))
test_support.pickeling(self, gammalib.GCTAModelRadialPolynom([1.0,2.0]))
test_support.pickeling(self, gammalib.GCTAModelRadialProfile(1.0,2.0,3.0))
test_support.pickeling(self, gammalib.GCTAModelSpatialGradient(1.0,2.0))
test_support.pickeling(self, gammalib.GCTAModelSpatialMultiplicative(multi))
test_support.pickeling(self, gammalib.GCTAObservation(obs1))
test_support.pickeling(self, gammalib.GCTAObservation(obs2))
test_support.pickeling(self, gammalib.GCTAObservation(obs3))
test_support.pickeling(self, gammalib.GCTAObservation(obs4))
test_support.pickeling(self, gammalib.GCTAOnOffObservation(obs5))
test_support.pickeling(self, gammalib.GCTAPointing(dir))
test_support.pickeling(self, gammalib.GCTAPsf2D(irfname))
test_support.pickeling(self, gammalib.GCTAPsfKing(kingname))
#test_support.pickeling(self, gammalib.GCTAPsfPerfTable())
test_support.pickeling(self, gammalib.GCTAPsfTable(hesspsf))
#test_support.pickeling(self, gammalib.GCTAPsfVector())
test_support.pickeling(self, gammalib.GCTAResponseCube(rspcube1))
test_support.pickeling(self, gammalib.GCTAResponseCube(rspcube2))
test_support.pickeling(self, gammalib.GCTAResponseIrf(rspirf))
test_support.pickeling(self, gammalib.GCTAResponseIrf(hessirf))
#test_support.pickeling(self, gammalib.GCTAResponseTable()) # No constructor
test_support.pickeling(self, gammalib.GCTARoi(instdir,2.0))
# Return
return
# Set test functions
def set(self):
"""
Set all test functions.
"""
# Set test name
self.name('CTA')
# Append tests
self.append(self._test_eventlist_access, 'Test GCTAEventList event access')
self.append(self._test_eventlist_slicing, 'Test GCTAEventList slicing')
self.append(self._test_aeff, 'Test CTA effective area classes')
self.append(self._test_psf, 'Test CTA PSF classes')
self.append(self._test_edisp, 'Test CTA energy dispersion classes')
self.append(self._test_response, 'Test CTA response classes')
self.append(self._test_onoff, 'Test CTA On/Off analysis')
self.append(self._test_pickeling, 'Test CTA class pickeling')
# Return
return