Merge branch 'devel' of https://cta-gitlab.irap.omp.eu/ctools/ctools into 2284-c…

…sphagen-load-off-regions

Merge branch 'devel' of https://cta-gitlab.irap.omp.eu/ctools/ctools into 2284-c…
…sphagen-load-off-regions
Andreas Specovius
2 parents 744f2625 88e351a6
Showing 39 changed files with 263 additions and 1829 deletions
cscripts/Makefile.am
examples/Makefile.am
examples/README.md
examples/generate_prod3_irfs.py
examples/make_spectrum.py
examples/make_ts_distributions.py
examples/pipeline_binned_disk.py
examples/pipeline_binned_mem.py
examples/pipeline_stacked_disk.py
examples/pipeline_stacked_mem.py
examples/pipeline_unbinned_disk.py
examples/pipeline_unbinned_mem.py
test/data/bkg_dummy.txt
test/data/crab.xml
test/data/crab_events.fits.gz
test/data/gauss.xml
test/data/disk.xml → test/data/model_crab_radialacceptance.xml
test/data/obs_stacked_two.xml
test/data/shell.xml
test/data/source1.xml
@@ -218,7 +218,8 @@ testdata = $(top_srcdir)/test/data/crab.xml \
            $(top_srcdir)/test/data/onoff_pha_on2.fits.gz \
            $(top_srcdir)/test/data/onoff_rmf.fits.gz \
            $(top_srcdir)/test/data/onoff_rmf1.fits.gz \
-           $(top_srcdir)/test/data/onoff_rmf2.fits.gz
+           $(top_srcdir)/test/data/onoff_rmf2.fits.gz \
+           $(top_srcdir)/test/data/model_crab_radialacceptance.xml
 # Test data to be distributed in $(pyexecdir)/cscripts/tests/data/iactdata
 testiactdata = $(top_srcdir)/test/data/iactdata/hdu-index.fits.gz \
@@ -21,16 +21,7 @@
 # Scripts to be install
 scripts = README.md \
-          generate_prod3_irfs.py \
           make_pointings.py \
-          make_spectrum.py \
-          make_ts_distributions.py \
-          pipeline_binned_disk.py \
-          pipeline_binned_mem.py \
-          pipeline_stacked_disk.py \
-          pipeline_stacked_mem.py \
-          pipeline_unbinned_disk.py \
-          pipeline_unbinned_mem.py \
           show_butterfly.py \
           show_irf.py \
           show_model.py \
@@ -4,47 +4,12 @@ ctools examples
 This folder contains Python example scripts that illustrate the usage of
 the ctools.
-`generate_prod3_irfs.py`
->  Generates Prod3 Instrument Response Functions from FITS files.
-
 `make_pointings.py`
 >  Creates pointings for CTA surveys. For the moment the Galactic Plane
 >  Survey (gps), the Extragalactic Survey (extgal), the Galactic Centre
 >  Survey (gc) and the LMC survey (lmc) are implemented. The script outputs
 >  and ASCII file that can be used by csobsdef.
-`make_spectrum.py`
->  Simulates events and generates a spectrum from the using csspec.
-
-`make_ts_distributions.py`
->  Creates TS distributions as function of energy for an OFF observaition
->  of 50 hours effective observing time. If the Python processing module is
->  installed the script can make use of multiple cores and runs in parallel.
-
-`pipeline_binned_disk.py`
->  Example pipeline for simulating events and performing a binned analysis
->  by saving intermediate results to disk.
-
-`pipeline_binned_mem.py`
->  Example pipeline for simulating events and performing a binned analysis
->  in memory. No files will be written to disk.
-
-`pipeline_stacked_disk.py`
->  Example pipeline for simulating events and performing a stacked analysis
->  by saving intermediate results to disk.
-
-`pipeline_stacked_mem.py`
->  Example pipeline for simulating events and performing a stacked analysis
->  in memory. No files will be written to disk.
-
-`pipeline_unbinned_disk.py`
->  Example pipeline for simulating events and performing an unbinned analysis
->  by saving intermediate results to disk.
-
-`pipeline_unbinned_mem.py`
->  Example pipeline for simulating events and performing an unbinned analysis
->  in memory. No files will be written to disk.
-
 `show_butterfly.py`
 >  Displays a butterfly generated using the ctbutterfly tool.
-#! /usr/bin/env python
-# ==========================================================================
-# Generates Prod3 IRFs from ROOT performance files
-#
-# Copyright (C) 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 cscripts
-
-
-# ======================= #
-# Set Prod3 DESY database #
-# ======================= #
-def set_prod3_desy(datadir):
-    """
-    Set Prod3 DESY database
-
-    This function sets the calibration database. By adding dictionaries to
-    the "db" list a number of calibrations can be defined for which IRFs
-    should be generated. All calibrations will be added to the calibration
-    database.
-
-    Parameters
-    ----------
-    datadir : str
-        Data directory
-
-    Returns
-    -------
-    db : list of dict
-        Database
-    """
-    # Set database content
-    db = [{'inst': 'prod3', 'id': 'South_50h', 'analysis': 'DESY',
-           'oversample': 3, 'norm1d': False, 'bgdinfill': False,
-           'bgdethres': 10.0, 'path': datadir, 'file': 'irf.root'}]
-
-    # Return database
-    return db
-
-
-# =================== #
-# Generate Prod3 IRFs #
-# =================== #
-def generate_prod3_irfs():
-    """
-    Generate Prod3 IRFs
-    """
-    # Get optional argument
-    if len(sys.argv) == 2:
-        datadir = sys.argv[1]
-    else:
-        datadir = 'data'
-
-    # Get database
-    entries = set_prod3_desy(datadir)
-
-    # Loop over entries
-    for entry in entries:
-
-        # Set filename
-        filename = entry['path']+'/'+entry['file']
-
-        # Set-up csroot2caldb
-        caldb = cscripts.csroot2caldb()
-        caldb['infile']        = filename
-        caldb['outdir']        = 'prod3'
-        caldb['inst']          = entry['inst']
-        caldb['id']            = entry['id']
-        caldb['version']       = entry['inst']
-        caldb['analysis']      = entry.setdefault('analysis', 'DESY')
-        caldb['zenith']        = entry.setdefault('zenith', 20.0)
-        caldb['azimuth']       = entry.setdefault('azimuth', 0.0)
-        caldb['psftype']       = entry.setdefault('psftype', 'Gauss')
-        caldb['norm1d']        = entry.setdefault('norm1d', False)
-        caldb['rebin']         = entry.setdefault('rebin', False)
-        caldb['eascale']       = entry.setdefault('eascale', 1.0)
-        caldb['bgdscale']      = entry.setdefault('bgdscale', 1.0)
-        caldb['bgdoversample'] = entry.setdefault('oversample', 1)
-        caldb['bgdethres']     = entry.setdefault('bgdethres', 1000.0)
-        caldb['bgdinfill']     = entry.setdefault('bgdinfill', False)
-        caldb['logfile']       = 'generate_prod3_irfs.log'
-
-        # Add CALDB entry
-        caldb.execute()
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Generate Prod3 IRFs
-    generate_prod3_irfs()
-#! /usr/bin/env python
-# ==========================================================================
-# Makes and optionally displays spectrum
-#
-# Copyright (C) 2014-2017 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 ctools
-import cscripts
-try:
-    import matplotlib.pyplot as plt
-    plt.figure()
-    plt.close()
-except (ImportError, RuntimeError):
-    print('This script needs the "matplotlib" module')
-    sys.exit()
-
-
-# =============== #
-# Create spectrum #
-# =============== #
-def create_spectrum(datadir):
-    """
-    Simulate events and generate a source spectrum
-
-    Returns
-    -------
-    datadir : str
-        Data directory
-    """
-    # Set script parameters
-    model_name  = datadir+'/crab.xml'
-    caldb       = 'prod2'
-    irf         = 'South_0.5h'
-    ra          =   83.63
-    dec         =   22.01
-    rad_sim     =    3.0
-    tstart      =    0.0
-    tstop       = 1800.0
-    emin        =    0.1
-    emax        =  100.0
-    enumbins    =     10
-
-    # Simulate events
-    sim = ctools.ctobssim()
-    sim['inmodel'] = model_name
-    sim['caldb']   = caldb
-    sim['irf']     = irf
-    sim['ra']      = ra
-    sim['dec']     = dec
-    sim['rad']     = rad_sim
-    sim['tmin']    = tstart
-    sim['tmax']    = tstop
-    sim['emin']    = emin
-    sim['emax']    = emax
-    sim.run()
-
-    # Create spectrum
-    spec = cscripts.csspec(sim.obs())
-    spec['srcname']  = 'Crab'
-    spec['method']   = 'AUTO'
-    spec['outfile']  = 'example_spectrum.fits'
-    spec['expcube']  = 'NONE'
-    spec['psfcube']  = 'NONE'
-    spec['bkgcube']  = 'NONE'
-    spec['edisp']    = False
-    spec['emin']     = emin
-    spec['emax']     = emax
-    spec['enumbins'] = enumbins
-    spec['ebinalg']  = 'LOG'
-    spec.run()
-    spec.save()
-
-    # Get copy of spectrum
-    spectrum = spec.spectrum().copy()
-
-    # Return
-    return spectrum
-
-
-# ============= #
-# Plot spectrum #
-# ============= #
-def plot_spectrum(spectrum, plotfile):
-    """
-    Plot spectrum
-
-    Parameters
-    ----------
-    spectrum : `~gammalib.GFits`
-        Spectrum FITS file
-    plotfile : str
-        Plot filename
-    """
-    # Extract columns from spectrum file
-    table    = spectrum.table(1)
-    c_energy = table['Energy']
-    c_ed     = table['ed_Energy']
-    c_eu     = table['eu_Energy']
-    c_flux   = table['Flux']
-    c_eflux  = table['e_Flux']
-    c_ts     = table['TS']
-    c_upper  = table['UpperLimit']
-
-    # Initialise arrays to be filled
-    energies    = []
-    flux        = []
-    ed_engs     = []
-    eu_engs     = []
-    e_flux      = []
-    ul_energies = []
-    ul_ed_engs  = []
-    ul_eu_engs  = []
-    ul_flux     = []
-
-    # Get number of spectral points
-    nrows = table.nrows()
-
-    # Loop over rows of the file
-    for row in range(nrows):
-
-        # Get TS value, flux and flux error
-        ts    = c_ts.real(row)
-        flx   = c_flux.real(row)
-        e_flx = c_eflux.real(row)
-
-        # If the TS > 9 and the flux error is smaller than the flux then
-        # take the fitted flux and flux error and append them to the
-        # arrays
-        if ts > 9.0 and e_flx < flx:
-
-            # Add information
-            energies.append(c_energy.real(row))
-            flux.append(c_flux.real(row))
-            ed_engs.append(c_ed.real(row))
-            eu_engs.append(c_eu.real(row))
-            e_flux.append(c_eflux.real(row))
-
-        # ... otherwise take the upper limit and append it to the upper
-        # limit array
-        else:
-
-            # Add information
-            ul_energies.append(c_energy.real(row))
-            ul_flux.append(c_upper.real(row))
-            ul_ed_engs.append(c_ed.real(row))
-            ul_eu_engs.append(c_eu.real(row))
-
-    # Create figure
-    plt.figure()
-    plt.title('Crab spectrum')
-
-    # Plot the spectrum 
-    plt.loglog()
-    plt.grid()
-
-    # Plot error bars for flux points and upper limits for upper limit
-    # points
-    plt.errorbar(energies, flux, yerr=e_flux, xerr=[ed_engs, eu_engs],
-                 fmt='ro')
-    plt.errorbar(ul_energies, ul_flux, xerr=[ul_ed_engs, ul_eu_engs],
-                 yerr=1.0e-11, uplims=True, fmt='ro')
-
-    # Add plot labels
-    plt.xlabel('Energy (TeV)')
-    plt.ylabel(r'E$^{2}$dN/dE (erg cm$^{-2}$ s$^{-1}$)')
-
-    # Show spectrum or save it into file
-    if len(plotfile) > 0:
-        plt.savefig(plotfile)
-    else:
-        plt.show()
-
-    # Return
-    return
-
-
-# ============= #
-# Make spectrum #
-# ============= #
-def make_spectrum():
-    """
-    Make spectrum
-    """
-    # Set usage string
-    usage = 'make_spectrum.py [-d datadir] [-p plotfile]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'},
-               {'option': '-p', 'value': ''}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir  = options[0]['value']
-    plotfile = options[1]['value']
-
-    # Generate spectrum
-    spectrum = create_spectrum(datadir)
-
-    # Plot spectrum
-    plot_spectrum(spectrum, plotfile)
-
-    # Return
-    return
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Make spectrum
-    make_spectrum()
-#! /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 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
-    _, 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(18):
-
-        # Set energies
-        loge  = -1.3 + ieng * 0.2
-        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()
-#! /usr/bin/env python
-# ==========================================================================
-# Perform binned 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
-import cscripts
-
-
-# ================================ #
-# Simulation and analysis pipeline #
-# ================================ #
-def run_pipeline(obs, emin=0.1, emax=100.0,
-                 enumbins=20, nxpix=200, nypix=200, binsz=0.02,
-                 coordsys='CEL', proj='CAR',
-                 model='data/crab.xml',
-                 caldb='prod2', irf='South_0.5h',
-                 debug=False):
-    """
-    Simulation and binned analysis pipeline
-
-    Parameters
-    ----------
-    obs : `~gammalib.GObservations`
-        Observation container
-    emin : float, optional
-        Minimum energy (TeV)
-    emax : float, optional
-        Maximum energy (TeV)
-    enumbins : int, optional
-        Number of energy bins
-    nxpix : int, optional
-        Number of pixels in X axis
-    nypix : int, optional
-        Number of pixels in Y axis
-    binsz : float, optional
-        Pixel size (deg)
-    coordsys : str, optional
-        Coordinate system
-    proj : str, optional
-        Coordinate projection
-    model : str, optional
-        Model definition XML file
-    caldb : str, optional
-        Calibration database path
-    irf : str, optional
-        Instrument response function
-    debug : bool, optional
-        Debug function
-    """
-    # Simulate events
-    sim = ctools.ctobssim(obs)
-    sim['debug']     = debug
-    sim['outevents'] = 'obs.xml'
-    sim.execute()
-
-    # Bin events by looping over all observations in the container
-    sim_obs = gammalib.GObservations('obs.xml')
-    obs     = gammalib.GObservations()
-    for run in sim_obs:
-
-        # Get event filename and set counts cube filename
-        eventfile = run.eventfile().url()
-        cubefile  = 'cube_'+eventfile
-
-        # Bin events for that observation
-        binning = ctools.ctbin()
-        binning['inobs']    = eventfile
-        binning['outcube']  = cubefile
-        binning['ebinalg']  = 'LOG'
-        binning['emin']     = emin
-        binning['emax']     = emax
-        binning['enumbins'] = enumbins
-        binning['nxpix']    = nxpix
-        binning['nypix']    = nypix
-        binning['binsz']    = binsz
-        binning['coordsys'] = coordsys
-        binning['usepnt']   = True
-        binning['proj']     = proj
-        binning.execute()
-
-        # Set observation ID
-        binning.obs()[0].id(cubefile)
-        binning.obs()[0].eventfile(cubefile)
-
-        # Append result to observations
-        obs.extend(binning.obs())
-
-    # Save XML file
-    xml = gammalib.GXml()
-    obs.write(xml)
-    xml.save('obs_cube.xml')
-
-    # Perform maximum likelihood fitting
-    like = ctools.ctlike()
-    like['inobs']    = 'obs_cube.xml'
-    like['inmodel']  = model
-    like['outmodel'] = 'fit_results.xml'
-    like['expcube']  = 'NONE'
-    like['psfcube']  = 'NONE'
-    like['bkgcube']  = 'NONE'
-    like['caldb']    = caldb
-    like['irf']      = irf
-    like['debug']    = True # Switch this always on for results in console
-    like.execute()
-
-    # Return
-    return
-
-
-# ===================================================== #
-# Run binned pipeline with intermediate results on disk #
-# ===================================================== #
-def pipeline_binned_disk():
-    """
-    Run binned pipeline with intermediate results on disk
-    """
-    # Set usage string
-    usage = 'pipeline_binned_disk.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs, model=datadir+'/crab.xml', enumbins=10, nxpix=40,
-                 nypix=40, binsz=0.1)
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run binned pipeline with intermediate results on disk
-    pipeline_binned_disk()
-#! /usr/bin/env python
-# ==========================================================================
-# Perform binned 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
-import cscripts
-
-
-# ================================ #
-# Simulation and analysis pipeline #
-# ================================ #
-def run_pipeline(obs, emin=0.1, emax=100.0,
-                 enumbins=20, nxpix=200, nypix=200, binsz=0.02,
-                 coordsys='CEL', proj='CAR', debug=False):
-    """
-    Simulation and binned analysis pipeline
-
-    Parameters
-    ----------
-    obs : `~gammalib.GObservations`
-        Observation container
-    emin : float, optional
-        Minimum energy (TeV)
-    emax : float, optional
-        Maximum energy (TeV)
-    enumbins : int, optional
-        Number of energy bins
-    nxpix : int, optional
-        Number of pixels in X axis
-    nypix : int, optional
-        Number of pixels in Y axis
-    binsz : float, optional
-        Pixel size (deg)
-    coordsys : str, optional
-        Coordinate system
-    proj : str, optional
-        Coordinate projection
-    debug : bool, optional
-        Debug function
-    """
-    # Simulate events
-    sim = ctools.ctobssim(obs)
-    sim['debug'] = debug
-    sim.run()
-
-    # Bin events by looping over all observations in the container
-    obs = gammalib.GObservations()
-    obs.models(sim.obs().models())
-    for run in sim.obs():
-
-        # Create container with a single observation
-        container = gammalib.GObservations()
-        container.append(run)
-
-        # Bin events for that observation
-        binning = ctools.ctbin(container)
-        binning['ebinalg']  = 'LOG'
-        binning['emin']     = emin
-        binning['emax']     = emax
-        binning['enumbins'] = enumbins
-        binning['nxpix']    = nxpix
-        binning['nypix']    = nypix
-        binning['binsz']    = binsz
-        binning['coordsys'] = coordsys
-        binning['usepnt']   = True
-        binning['proj']     = proj
-        binning.run()
-
-        # Append result to observations
-        obs.extend(binning.obs())
-
-    # Perform maximum likelihood fitting
-    like = ctools.ctlike(obs)
-    like['debug'] = True # Switch this always on for results in console
-    like.run()
-
-    # Return
-    return
-
-
-# ============================= #
-# Run binned in-memory pipeline #
-# ============================= #
-def pipeline_binned_mem():
-    """
-    Run binned in-memory pipeline
-    """
-    # Set usage string
-    usage = 'pipeline_binned_mem.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs, enumbins=10, nxpix=40, nypix=40, binsz=0.1)
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run binned in-memory pipeline
-    pipeline_binned_mem()
-#! /usr/bin/env python
-# ==========================================================================
-# Perform stacked 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
-import cscripts
-
-
-# ================================ #
-# Simulation and analysis pipeline #
-# ================================ #
-def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0,
-                 enumbins=20, nxpix=200, nypix=200, binsz=0.02,
-                 coordsys='CEL', proj='CAR',
-                 model='data/crab.xml',
-                 caldb='prod2', irf='South_0.5h',
-                 debug=False):
-    """
-    Simulation and stacked analysis pipeline
-
-    Parameters
-    ----------
-    obs : `~gammalib.GObservations`
-        Observation container
-    ra : float, optional
-        Right Ascension of counts cube centre (deg)
-    dec : float, optional
-        Declination of Region of counts cube centre (deg)
-    emin : float, optional
-        Minimum energy (TeV)
-    emax : float, optional
-        Maximum energy (TeV)
-    enumbins : int, optional
-        Number of energy bins
-    nxpix : int, optional
-        Number of pixels in X axis
-    nypix : int, optional
-        Number of pixels in Y axis
-    binsz : float, optional
-        Pixel size (deg)
-    coordsys : str, optional
-        Coordinate system
-    proj : str, optional
-        Coordinate projection
-    model : str, optional
-        Model definition XML file
-    caldb : str, optional
-        Calibration database path
-    irf : str, optional
-        Instrument response function
-    debug : bool, optional
-        Debug function
-    """
-    # Simulate events
-    sim = ctools.ctobssim(obs)
-    sim['debug']     = debug
-    sim['outevents'] = 'obs.xml'
-    sim.execute()
-
-    # Bin events into counts map
-    binning = ctools.ctbin()
-    binning['inobs']    = 'obs.xml'
-    binning['outcube']  = 'cntcube.fits'
-    binning['ebinalg']  = 'LOG'
-    binning['emin']     = emin
-    binning['emax']     = emax
-    binning['enumbins'] = enumbins
-    binning['nxpix']    = nxpix
-    binning['nypix']    = nypix
-    binning['binsz']    = binsz
-    binning['coordsys'] = coordsys
-    binning['proj']     = proj
-    binning['xref']     = ra
-    binning['yref']     = dec
-    binning['debug']    = debug
-    binning.execute()
-
-    # Create exposure cube
-    expcube = ctools.ctexpcube()
-    expcube['inobs']    = 'obs.xml'
-    expcube['incube']   = 'cntcube.fits'
-    expcube['outcube']  = 'expcube.fits'
-    expcube['caldb']    = caldb
-    expcube['irf']      = irf
-    expcube['ebinalg']  = 'LOG'
-    expcube['emin']     = emin
-    expcube['emax']     = emax
-    expcube['enumbins'] = enumbins
-    expcube['nxpix']    = nxpix
-    expcube['nypix']    = nypix
-    expcube['binsz']    = binsz
-    expcube['coordsys'] = coordsys
-    expcube['proj']     = proj
-    expcube['xref']     = ra
-    expcube['yref']     = dec
-    expcube['debug']    = debug
-    expcube.execute()
-
-    # Create PSF cube
-    psfcube = ctools.ctpsfcube()
-    psfcube['inobs']    = 'obs.xml'
-    psfcube['incube']   = 'NONE'
-    psfcube['outcube']  = 'psfcube.fits'
-    psfcube['caldb']    = caldb
-    psfcube['irf']      = irf
-    psfcube['ebinalg']  = 'LOG'
-    psfcube['emin']     = emin
-    psfcube['emax']     = emax
-    psfcube['enumbins'] = enumbins
-    psfcube['nxpix']    = 10
-    psfcube['nypix']    = 10
-    psfcube['binsz']    = 1.0
-    psfcube['coordsys'] = coordsys
-    psfcube['proj']     = proj
-    psfcube['xref']     = ra
-    psfcube['yref']     = dec
-    psfcube['debug']    = debug
-    psfcube.execute()
-
-    # Create background cube
-    bkgcube = ctools.ctbkgcube()
-    bkgcube['inobs']    = 'obs.xml'
-    bkgcube['inmodel']  = model
-    bkgcube['incube']   = 'NONE'
-    bkgcube['outcube']  = 'bkgcube.fits'
-    bkgcube['outmodel'] = 'model_bkg.xml'
-    bkgcube['caldb']    = caldb
-    bkgcube['irf']      = irf
-    bkgcube['ebinalg']  = 'LOG'
-    bkgcube['emin']     = emin
-    bkgcube['emax']     = emax
-    bkgcube['enumbins'] = enumbins
-    bkgcube['nxpix']    = 10
-    bkgcube['nypix']    = 10
-    bkgcube['binsz']    = 1.0
-    bkgcube['coordsys'] = coordsys
-    bkgcube['proj']     = proj
-    bkgcube['xref']     = ra
-    bkgcube['yref']     = dec
-    bkgcube['debug']    = debug
-    bkgcube.execute()
-
-    # Perform maximum likelihood fitting
-    like = ctools.ctlike()
-    like['inobs']    = 'cntcube.fits'
-    like['inmodel']  = 'model_bkg.xml'
-    like['outmodel'] = 'fit_results.xml'
-    like['expcube']  = 'expcube.fits'
-    like['psfcube']  = 'psfcube.fits'
-    like['bkgcube']  = 'bkgcube.fits'
-    like['caldb']    = caldb
-    like['irf']      = irf
-    like['debug']    = True # Switch this always on for results in console
-    like.execute()
-
-    # Return
-    return
-
-
-# ====================================================== #
-# Run stacked pipeline with intermediate results on disk #
-# ====================================================== #
-def pipeline_stacked_disk():
-    """
-    Run stacked pipeline with intermediate results on disk
-    """
-    # Set usage string
-    usage = 'pipeline_stacked_disk.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs, model=datadir+'/crab.xml', enumbins=10, nxpix=40,
-                 nypix=40, binsz=0.1)
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run stacked pipeline with intermediate results on disk
-    pipeline_stacked_disk()
-#! /usr/bin/env python
-# ==========================================================================
-# Perform stacked in-memory analysis of simulated CTA 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 gammalib
-import ctools
-import cscripts
-
-
-# ================================ #
-# Simulation and analysis pipeline #
-# ================================ #
-def run_pipeline(obs, ra=83.63, dec=22.01, emin=0.1, emax=100.0,
-                 enumbins=20, nxpix=200, nypix=200, binsz=0.02,
-                 coordsys='CEL', proj='CAR', debug=False):
-    """
-    Simulation and stacked analysis pipeline
-
-    Parameters
-    ----------
-    obs : `~gammalib.GObservations`
-        Observation container
-    ra : float, optional
-        Right Ascension of counts cube centre (deg)
-    dec : float, optional
-        Declination of Region of counts cube centre (deg)
-    emin : float, optional
-        Minimum energy (TeV)
-    emax : float, optional
-        Maximum energy (TeV)
-    enumbins : int, optional
-        Number of energy bins
-    nxpix : int, optional
-        Number of pixels in X axis
-    nypix : int, optional
-        Number of pixels in Y axis
-    binsz : float, optional
-        Pixel size (deg)
-    coordsys : str, optional
-        Coordinate system
-    proj : str, optional
-        Coordinate projection
-    debug : bool, optional
-        Debug function
-    """
-    # Simulate events
-    sim = ctools.ctobssim(obs)
-    sim['debug']     = debug
-    sim.run()
-
-    # Bin events into counts map
-    binning = ctools.ctbin(sim.obs())
-    binning['ebinalg']  = 'LOG'
-    binning['emin']     = emin
-    binning['emax']     = emax
-    binning['enumbins'] = enumbins
-    binning['nxpix']    = nxpix
-    binning['nypix']    = nypix
-    binning['binsz']    = binsz
-    binning['coordsys'] = coordsys
-    binning['proj']     = proj
-    binning['xref']     = ra
-    binning['yref']     = dec
-    binning['debug']    = debug
-    binning.run()
-
-    # Create exposure cube
-    expcube = ctools.ctexpcube(sim.obs())
-    expcube['incube']   = 'NONE'
-    expcube['ebinalg']  = 'LOG'
-    expcube['emin']     = emin
-    expcube['emax']     = emax
-    expcube['enumbins'] = enumbins
-    expcube['nxpix']    = nxpix
-    expcube['nypix']    = nypix
-    expcube['binsz']    = binsz
-    expcube['coordsys'] = coordsys
-    expcube['proj']     = proj
-    expcube['xref']     = ra
-    expcube['yref']     = dec
-    expcube['debug']    = debug
-    expcube.run()
-
-    # Create PSF cube
-    psfcube = ctools.ctpsfcube(sim.obs())
-    psfcube['incube']   = 'NONE'
-    psfcube['ebinalg']  = 'LOG'
-    psfcube['emin']     = emin
-    psfcube['emax']     = emax
-    psfcube['enumbins'] = enumbins
-    psfcube['nxpix']    = 10
-    psfcube['nypix']    = 10
-    psfcube['binsz']    = 1.0
-    psfcube['coordsys'] = coordsys
-    psfcube['proj']     = proj
-    psfcube['xref']     = ra
-    psfcube['yref']     = dec
-    psfcube['debug']    = debug
-    psfcube.run()
-
-    # Create background cube
-    bkgcube = ctools.ctbkgcube(sim.obs())
-    bkgcube['incube']   = 'NONE'
-    bkgcube['ebinalg']  = 'LOG'
-    bkgcube['emin']     = emin
-    bkgcube['emax']     = emax
-    bkgcube['enumbins'] = enumbins
-    bkgcube['nxpix']    = 10
-    bkgcube['nypix']    = 10
-    bkgcube['binsz']    = 1.0
-    bkgcube['coordsys'] = coordsys
-    bkgcube['proj']     = proj
-    bkgcube['xref']     = ra
-    bkgcube['yref']     = dec
-    bkgcube['debug']    = debug
-    bkgcube.run()
-
-    # Attach background model to observation container
-    binning.obs().models(bkgcube.models())
-
-    # Set Exposure and Psf cube for first CTA observation
-    # (ctbin will create an observation with a single container)
-    binning.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
-
-    # Perform maximum likelihood fitting
-    like = ctools.ctlike(binning.obs())
-    like['debug'] = True # Switch this always on for results in console
-    like.run()
-
-    # Return
-    return
-
-
-# ============================== #
-# Run stacked in-memory pipeline #
-# ============================== #
-def pipeline_stacked_mem():
-    """
-    Run stacked in-memory pipeline
-    """
-    # Set usage string
-    usage = 'pipeline_stacked_mem.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs, enumbins=10, nxpix=40, nypix=40, binsz=0.1)
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run stacked in-memory pipeline
-    pipeline_stacked_mem()
-#! /usr/bin/env python
-# ==========================================================================
-# Perform unbinned 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
-import cscripts
-
-
-# ================================ #
-# 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,
-                 model='data/crab.xml',
-                 caldb='prod2', irf='South_0.5h',
-                 debug=False):
-    """
-    Simulation and unbinned 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)
-    model : str, optional
-        Model definition XML file
-    caldb : str, optional
-        Calibration database path
-    irf : str, optional
-        Instrument response function
-    debug : bool, optional
-        Debug function
-    """
-    # Get model
-
-    # Simulate events
-    sim = ctools.ctobssim(obs)
-    sim['debug']     = debug
-    sim['outevents'] = 'obs.xml'
-    sim.execute()
-
-    # Select events
-    select = ctools.ctselect()
-    select['inobs']  = 'obs.xml'
-    select['outobs'] = 'obs_selected.xml'
-    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.execute()
-
-    # Perform maximum likelihood fitting
-    like = ctools.ctlike()
-    like['inobs']    = 'obs_selected.xml'
-    like['inmodel']  = model
-    like['outmodel'] = 'fit_results.xml'
-    like['caldb']    = caldb
-    like['irf']      = irf
-    like['debug']    = True # Switch this always on for results in console
-    like.execute()
-
-    # Return
-    return
-
-
-# ======================================================= #
-# Run unbinned pipeline with intermediate results on disk #
-# ======================================================= #
-def pipeline_unbinned_disk():
-    """
-    Run unbinned pipeline with intermediate results on disk
-    """
-    # Set usage string
-    usage = 'pipeline_unbinned_disk.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs, model=datadir+'/crab.xml')
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run unbinned pipeline with intermediate results on disk
-    pipeline_unbinned_disk()
-#! /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
-import cscripts
-
-
-# ================================ #
-# 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
-
-
-# =============================== #
-# Run unbinned in-memory pipeline #
-# =============================== #
-def pipeline_unbinned_mem():
-    """
-    Run unbinned in-memory pipeline
-    """
-    # Set usage string
-    usage = 'pipeline_unbinned_mem.py [-d datadir]'
-
-    # Set default options
-    options = [{'option': '-d', 'value': 'data'}]
-
-    # Get arguments and options from command line arguments
-    _, options = cscripts.ioutils.get_args_options(options, usage)
-
-    # Extract script parameters from options
-    datadir = options[0]['value']
-
-    # Setup observations
-    obs = cscripts.obsutils.set_observations(83.63, 22.01, 5.0, 0.0, 180.0,
-                                             0.1, 100.0, 'South_0.5h', 'prod2',
-                                             pattern='four', offset=1.5)
-
-    # Setup model
-    obs.models(gammalib.GModels(datadir+'/crab.xml'))
-
-    # Run analysis pipeline
-    run_pipeline(obs)
-
-    # Return
-    return
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-
-    # Run unbinned in-memory pipeline
-    pipeline_unbinned_mem()
-19952.6231497 0.00758611874475
-31622.7766017 0.0453646736765
-50118.7233627 0.0434482007416
-79432.8234724 0.0178479909838
-125892.541179 0.00670562887729
-199526.231497 0.00084045162152
-316227.766017 0.000323808025007
-501187.233627 9.59822836926e-05
-794328.234724 6.37799870129e-05
-1258925.41179 1.03541320942e-05
-1995262.31497 1.64149835388e-05
-3162277.66017 3.15232118872e-06
-5011872.33627 2.15432019088e-06
-7943282.34724 6.16894263439e-07
-12589254.1179 8.04369168326e-07
-19952623.1497 3.8166590852e-07
-31622776.6017 3.00652101748e-07
-50118723.3627 3.33564542808e-07
-79432823.4724 1.02704085801e-07
-125892541.179 2.78291918566e-08
-199526231.497 8.18076720102e-09
@@ -11,7 +11,7 @@
       <parameter name="DEC" scale="1.0" value="22.0145" min="-90"  max="90"  free="0"/>
     </spatialModel>
   </source>
-  <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
+  <source name="Background" type="CTAIrfBackground" instrument="CTA">
     <spectrum type="PowerLaw">	
       <parameter name="Prefactor"   scale="1.0"  value="1.0"  min="1e-3" max="1e+3"   free="1"/>	
       <parameter name="Index"       scale="1.0"  value="0.0"  min="-5.0" max="+5.0"   free="1"/>
-<?xml version="1.0" standalone="no"?>
-<source_library title="source library">
-  <source name="CrabGauss" type="ExtendedSource">
-    <spectrum type="PowerLaw">
-       <parameter name="Prefactor"   scale="1e-16" value="5.7"  min="1e-07" max="1000.0" free="1"/>
-       <parameter name="Index"       scale="-1"    value="2.48" min="0.0"   max="+5.0"   free="1"/>
-       <parameter name="PivotEnergy" scale="1e6"   value="0.3"  min="0.01"  max="1000.0" free="0"/>
-    </spectrum>
-    <spatialModel type="RadialGaussian">
-      <parameter name="RA"    scale="1.0" value="83.6331" min="-360" max="360" free="1"/>
-      <parameter name="DEC"   scale="1.0" value="22.0145" min="-90"  max="90"  free="1"/>
-      <parameter name="Sigma" scale="1.0" value="0.20"    min="0.01" max="10"  free="1"/>
-    </spatialModel>
-  </source>
-  <source name="Background" type="RadialAcceptance" instrument="CTA">
-    <spectrum type="PowerLaw">
-       <parameter name="Prefactor"   scale="1e-6" value="61.8" min="0.0"  max="1000.0" free="1"/>
-       <parameter name="Index"       scale="-1"   value="1.85" min="0.0"  max="+5.0"   free="1"/>
-       <parameter name="PivotEnergy" scale="1e6"  value="1.0"  min="0.01" max="1000.0" free="0"/>
-    </spectrum>
-    <radialModel type="Gaussian">
-       <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="1"/>
-    </radialModel>
-  </source>
-</source_library>
 <?xml version="1.0" standalone="no"?>
 <source_library title="source library">
-  <source name="CrabDisk" type="ExtendedSource">
+  <source name="Crab" type="PointSource">
     <spectrum type="PowerLaw">
        <parameter name="Prefactor"   scale="1e-16" value="5.7"  min="1e-07" max="1000.0" free="1"/>
        <parameter name="Index"       scale="-1"    value="2.48" min="0.0"   max="+5.0"   free="1"/>
        <parameter name="PivotEnergy" scale="1e6"   value="0.3"  min="0.01"  max="1000.0" free="0"/>
     </spectrum>
-    <spatialModel type="RadialDisk">
-      <parameter name="RA"     scale="1.0" value="83.6331" min="-360" max="360" free="1"/>
-      <parameter name="DEC"    scale="1.0" value="22.0145" min="-90"  max="90"  free="1"/>
-      <parameter name="Radius" scale="1.0" value="0.45"    min="0.01" max="10"  free="1"/>
+    <spatialModel type="PointSource">
+      <parameter name="RA"  scale="1.0" value="83.6331" min="-360" max="360" free="0"/>
+      <parameter name="DEC" scale="1.0" value="22.0145" min="-90"  max="90"  free="0"/>
     </spatialModel>
   </source>
   <source name="Background" type="RadialAcceptance" instrument="CTA">
@@ -19,7 +18,7 @@
        <parameter name="PivotEnergy" scale="1e6"  value="1.0"  min="0.01" max="1000.0" free="0"/>
     </spectrum>
     <radialModel type="Gaussian">
-       <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="1"/>
+       <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="0"/>
     </radialModel>
   </source>
 </source_library>
@@ -3,7 +3,7 @@
   <observation name="Crab" id="000001" instrument="CTA">
     <parameter name="Pointing" ra="83.6331" dec="21.0145" />
     <parameter name="EnergyBoundaries" emin="50000" emax="1e+08" />
-    <parameter name="GoodTimeIntervals" tmin="0" tmax="1800" />
+    <parameter name="GoodTimeIntervals" tmin="0" tmax="180" />
     <parameter name="TimeReference" mjdrefi="51544" mjdreff="0.5" timeunit="s" timesys="TT" timeref="LOCAL" />
     <parameter name="RegionOfInterest" ra="83.6331" dec="21.0145" rad="1.5" />
     <parameter name="Deadtime" deadc="0.98" />
@@ -12,7 +12,7 @@
   <observation name="Crab" id="000002" instrument="CTA">
     <parameter name="Pointing" ra="83.6331" dec="23.0145" />
     <parameter name="EnergyBoundaries" emin="70000" emax="1e+08" />
-    <parameter name="GoodTimeIntervals" tmin="1800" tmax="3600" />
+    <parameter name="GoodTimeIntervals" tmin="180" tmax="360" />
     <parameter name="TimeReference" mjdrefi="51544" mjdreff="0.5" timeunit="s" timesys="TT" timeref="LOCAL" />
     <parameter name="RegionOfInterest" ra="83.6331" dec="23.0145" rad="1.5" />
     <parameter name="Deadtime" deadc="0.98" />
-<?xml version="1.0" standalone="no"?>
-<source_library title="source library">
-  <source name="CrabShell" type="ExtendedSource">
-    <spectrum type="PowerLaw">
-       <parameter name="Prefactor"   scale="1e-16" value="5.7"  min="1e-07" max="1000.0" free="1"/>
-       <parameter name="Index"       scale="-1"    value="2.48" min="0.0"   max="+5.0"   free="1"/>
-       <parameter name="PivotEnergy" scale="1e6"   value="0.3"  min="0.01"  max="1000.0" free="0"/>
-    </spectrum>
-    <spatialModel type="RadialShell">
-      <parameter name="RA"     scale="1.0" value="83.6331" min="-360" max="360" free="1"/>
-      <parameter name="DEC"    scale="1.0" value="22.0145" min="-90"  max="90"  free="1"/>
-      <parameter name="Radius" scale="1.0" value="0.30"    min="0.01" max="10"  free="1"/>
-      <parameter name="Width"  scale="1.0" value="0.10"    min="0.01" max="10"  free="1"/>
-    </spatialModel>
-  </source>
-  <source name="Background" type="RadialAcceptance" instrument="CTA">
-    <spectrum type="PowerLaw">
-       <parameter name="Prefactor"   scale="1e-6" value="61.8" min="0.0"  max="1000.0" free="1"/>
-       <parameter name="Index"       scale="-1"   value="1.85" min="0.0"  max="+5.0"   free="1"/>
-       <parameter name="PivotEnergy" scale="1e6"  value="1.0"  min="0.01" max="1000.0" free="0"/>
-    </spectrum>
-    <radialModel type="Gaussian">
-       <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="1"/>
-    </radialModel>
-  </source>
-</source_library>
-<?xml version="1.0" standalone="no"?>
-<source_library title="source library">
-    <source name="Source1" type="PointSource">
-        <spectrum type="PowerLaw">
-            <parameter scale="1e-07" name="Prefactor"   min="1e-07" max="1000.0"    value="1.0"   free="1"/>
-            <parameter scale="1.0"   name="Index"       min="-5.0"  max="+5.0"      value="-2.1"  free="1"/>
-            <parameter scale="1.0"   name="PivotEnergy" min="10.0"  max="1000000.0" value="100.0" free="0"/>
-        </spectrum>
-        <spatialModel type="PointSource">
-            <parameter free="0" max="360" min="-360" name="RA"  scale="1" value="117.0" />
-            <parameter free="0" max="90"  min="-90"  name="DEC" scale="1" value="-33.0" />
-        </spatialModel>
-    </source>
-</source_library>
-
@@ -8,12 +8,12 @@
             <parameter name="edisp"   value="no" />
             <parameter name="deadc"   value="0.98" />
             <parameter name="ra"      value="83.63" />
-            <parameter name="dec"     value="22.01" />
+            <parameter name="dec"     value="22.51" />
             <parameter name="target"  value="Crab" />
             <parameter name="emin"    value="0.1" />
             <parameter name="emax"    value="100.0" />
             <parameter name="tmin"    value="0.0" />
-            <parameter name="tmax"    value="1800.0" />
+            <parameter name="tmax"    value="300.0" />
             <parameter name="chatter" value="2" />
             <parameter name="clobber" value="yes" />
             <parameter name="debug"   value="no" />
@@ -31,7 +31,7 @@
             <parameter name="seed"    value="1" />
             <parameter name="ra"      value="ra" actor="input" />
             <parameter name="dec"     value="dec" actor="input" />
-            <parameter name="rad"     value="5.0" />
+            <parameter name="rad"     value="3.0" />
             <parameter name="tmin"    value="tmin" actor="input" />
             <parameter name="tmax"    value="tmax" actor="input" />
             <parameter name="emin"    value="emin" actor="input" />
@@ -56,7 +56,7 @@
             <parameter name="usepnt"   value="no" />
             <parameter name="ra"       value="ra" actor="input" />
             <parameter name="dec"      value="dec" actor="input" />
-            <parameter name="rad"      value="3.0" />
+            <parameter name="rad"      value="2.0" />
             <parameter name="tmin"     value="tmin" actor="input" />
             <parameter name="tmax"     value="tmax" actor="input" />
             <parameter name="emin"     value="emin" actor="input" />
@@ -77,7 +77,7 @@ class Test(test):
                          ' inmodel="'+self._model+'" srcname="Crab"'+ \
                          ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
                          ' tbinalg=LIN '+ \
-                         ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:30:00'+ \
+                         ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:05:00'+ \
                          ' tbins=3 method=3D enumbins=0 emin=0.1 emax=100.0'+ \
                          ' outfile="lightcurve_cmd1.fits"'+ \
                          ' logfile="cslightcrv_cmd1.log" chatter=1'
@@ -98,7 +98,7 @@ class Test(test):
                          ' inmodel="'+self._model+'" srcname="Crab"'+ \
                          ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
                          ' tbinalg=LIN '+ \
-                         ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:30:00'+ \
+                         ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:05:00'+ \
                          ' tbins=3 method=3D enumbins=0 emin=0.1 emax=100.0'+ \
                          ' outfile="lightcurve_cmd1.fits"'+ \
                          ' logfile="cslightcrv_cmd2.log" debug=yes'
@@ -127,7 +127,7 @@ class Test(test):
         lcrv['irf']      = self._irf
         lcrv['tbinalg']  = 'LIN'
         lcrv['tmin']     = '2020-01-01T00:00:00'
-        lcrv['tmax']     = '2020-01-01T00:30:00'
+        lcrv['tmax']     = '2020-01-01T00:05:00'
         lcrv['tbins']    = 3
         lcrv['method']   = '3D'
         lcrv['enumbins'] = 0
@@ -151,7 +151,7 @@ class Test(test):
         # is saved into the file "lightcurve_py2.dat".
         csv    = gammalib.GCsv(2,2)
         tmin   = 58849.00
-        tdelta = 0.0104166
+        tdelta = 0.0017361
         for i in range(csv.nrows()):
             csv[i,0] = '%.5f' % (tmin +  i    * tdelta)
             csv[i,1] = '%.5f' % (tmin + (i+1) * tdelta)
@@ -219,7 +219,7 @@ class Test(test):
         lcrv['irf']      = self._irf
         lcrv['tbinalg']  = 'LIN'
         lcrv['tmin']     = '2020-01-01T00:00:00'
-        lcrv['tmax']     = '2020-01-01T00:30:00'
+        lcrv['tmax']     = '2020-01-01T00:05:00'
         lcrv['tbins']    = 2
         lcrv['method']   = '3D'
         lcrv['emin']     = 0.1
@@ -250,8 +250,8 @@ class Test(test):
         lcrv['caldb']     = self._caldb
         lcrv['irf']       = self._irf
         lcrv['tbinalg']   = 'LIN'
-        lcrv['tmin']      = 'MJD 58849.0008'
-        lcrv['tmax']      = 'MJD 58849.0112'
+        lcrv['tmin']      = '2020-01-01T00:00:00'
+        lcrv['tmax']      = '2020-01-01T00:05:00'
         lcrv['tbins']     = 2
         lcrv['method']    = 'ONOFF'
         lcrv['emin']      = 0.1
@@ -261,6 +261,9 @@ class Test(test):
         lcrv['xref']      = 83.63
         lcrv['yref']      = 22.01
         lcrv['rad']       = 0.2
+        lcrv['etruemin']  = 0.05
+        lcrv['etruemax']  = 150.0
+        lcrv['etruebins'] = 5
         lcrv['statistic'] = 'WSTAT'
         lcrv['outfile']   = 'cslightcrv_py5.fits'
         lcrv['logfile']   = 'cslightcrv_py5.log'
@@ -49,7 +49,7 @@ class Test(test):
         self._nreg_with_excl = 5
         self._nreg_wo_excl   = 8
         self._nreg_mul       = [self._nreg_with_excl, 6]
-        self._nbins          = 20
+        self._nbins          = 10
         # number of expected background regions with/wo exclusion,
         # and for two different runs
@@ -84,6 +84,7 @@ class Test(test):
                          '" caldb="' + self._caldb + '" irf="' + self._irf + \
                          '" ebinalg="LOG" emin=0.1 emax=100. enumbins=' + \
                          str(self._nbins) + \
+                         ' etruemin=0.05 etruemax=150 etruebins=5'+ \
                          ' coordsys="CEL" ra=83.633 dec=22.0145' + \
                          ' rad=0.2 stack="no" inexclusion="' + \
                          self._exclusion + \
@@ -107,6 +108,7 @@ class Test(test):
                          'caldb="' + self._caldb + '" irf="' + self._irf + \
                          '" ebinalg="LOG" emin=0.1 emax=100. enumbins=' + \
                          str(self._nbins) + \
+                         ' etruemin=0.05 etruemax=150 etruebins=5'+ \
                          ' coordsys="CEL" ra=83.633 dec=22.0145' + \
                          ' rad=0.2 stack="no" inexclusion="' + \
                          self._exclusion + \
@@ -142,6 +144,9 @@ class Test(test):
         phagen['rad']         = 0.2
         phagen['stack']       = False
         phagen['inexclusion'] = self._exclusion
+        phagen['etruemin']    = 0.05
+        phagen['etruemax']    = 150.0
+        phagen['etruebins']   = 5
         phagen['outobs']      = 'csphagen_py1.xml'
         phagen['prefix']      = 'csphagen_py1'
         phagen['logfile']     = 'csphagen_py1.log'
@@ -156,22 +161,25 @@ class Test(test):
         # Now test without exclusion region
         phagen = cscripts.csphagen()
-        phagen['inobs']    = self._myevents1
-        phagen['caldb']    = self._caldb
-        phagen['irf']      = self._irf
-        phagen['ebinalg']  = 'LOG'
-        phagen['emin']     = 0.1
-        phagen['emax']     = 100.0
-        phagen['enumbins'] = self._nbins
-        phagen['coordsys'] = 'CEL'
-        phagen['ra']       = 83.633
-        phagen['dec']      = 22.0145
-        phagen['rad']      = 0.2
-        phagen['stack']    = False
-        phagen['outobs']   = 'csphagen_py2.xml'
-        phagen['prefix']   = 'csphagen_py2'
-        phagen['logfile']  = 'csphagen_py2.log'
-        phagen['chatter']  = 2
+        phagen['inobs']     = self._myevents1
+        phagen['caldb']     = self._caldb
+        phagen['irf']       = self._irf
+        phagen['ebinalg']   = 'LOG'
+        phagen['emin']      = 0.1
+        phagen['emax']      = 100.0
+        phagen['enumbins']  = self._nbins
+        phagen['coordsys']  = 'CEL'
+        phagen['ra']        = 83.633
+        phagen['dec']       = 22.0145
+        phagen['rad']       = 0.2
+        phagen['stack']     = False
+        phagen['etruemin']  = 0.05
+        phagen['etruemax']  = 150.0
+        phagen['etruebins'] = 5
+        phagen['outobs']    = 'csphagen_py2.xml'
+        phagen['prefix']    = 'csphagen_py2'
+        phagen['logfile']   = 'csphagen_py2.log'
+        phagen['chatter']   = 2
         # Run script
         phagen.execute()
@@ -201,6 +209,9 @@ class Test(test):
         phagen['rad']         = 0.2
         phagen['stack']       = False
         phagen['inexclusion'] = self._exclusion
+        phagen['etruemin']    = 0.05
+        phagen['etruemax']    = 150.0
+        phagen['etruebins']   = 5
         phagen['outobs']      = 'csphagen_py3.xml'
         phagen['prefix']      = 'csphagen_py3'
         phagen['logfile']     = 'csphagen_py3.log'
@@ -228,6 +239,9 @@ class Test(test):
         phagen['rad']         = 0.2
         phagen['stack']       = True
         phagen['inexclusion'] = self._exclusion
+        phagen['etruemin']    = 0.05
+        phagen['etruemax']    = 150.0
+        phagen['etruebins']   = 5
         phagen['outobs']      = 'csphagen_py4.xml'
         phagen['prefix']      = 'csphagen_py4'
         phagen['logfile']     = 'csphagen_py4.log'
@@ -339,7 +353,7 @@ class Test(test):
         # Return
         return
-    def _check_rmf(self, filename, bins, etruebins=102):
+    def _check_rmf(self, filename, bins, etruebins=17):
         """
         Check RMF file
         """
@@ -386,7 +400,7 @@ class Test(test):
         # OGIP files
         self._check_pha(filenameroot + '_pha_on.fits', bins)
         self._check_pha(filenameroot + '_pha_off.fits', bins)
-        self._check_arf(filenameroot + '_arf.fits', 102)
+        self._check_arf(filenameroot + '_arf.fits', 17)
         self._check_rmf(filenameroot + '_rmf.fits', bins)
         # Optionally check for regions
@@ -45,7 +45,7 @@ class Test(test):
         # Set test data
         self._phased_events  = self._datadir + '/phased_events.fits'
         self._offaxis_events = self._datadir + '/crab_offaxis1.fits'
-        self._model_onoff = self._datadir + '/crab_onoff.xml'
+        self._model_onoff    = self._datadir + '/crab_onoff.xml'
         # Return
         return
@@ -258,6 +258,9 @@ class Test(test):
         pcrv['xref']      = 83.63
         pcrv['yref']      = 22.01
         pcrv['rad']       = 0.2
+        pcrv['etruemin']  = 0.05
+        pcrv['etruemax']  = 150.0
+        pcrv['etruebins'] = 5
         pcrv['outfile']   = 'csphasecrv_py5.fits'
         pcrv['logfile']   = 'csphasecrv_py5.log'
         pcrv['chatter']   = 4
@@ -43,6 +43,7 @@ class Test(test):
         test.__init__(self)
         # Set members
+        self._model         = self._datadir + '/model_crab_radialacceptance.xml'
         self._inobs         = self._datadir + '/obs_stacked.xml'
         self._inobs_two     = self._datadir + '/obs_stacked_two.xml'
         self._stacked_model = self._datadir + '/crab_bkgcube.xml'
@@ -42,6 +42,9 @@ class Test(test):
         # Call base class constructor
         test.__init__(self)
+        # Set test data
+        self._model = self._datadir + '/model_crab_radialacceptance.xml'
+
         # Return
         return
@@ -72,7 +75,7 @@ class Test(test):
         cmd = cssens+' inmodel="'+self._model+'"'+ \
                      ' srcname="Crab"'+ \
                      ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
-                     ' duration=1800.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
+                     ' duration=180.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
                      ' outfile="cssens_cmd1.dat"'+ \
                      ' logfile="cssens_cmd1.log" chatter=1'
@@ -91,7 +94,7 @@ class Test(test):
         cmd = cssens+' inmodel="model_that_does_not_exist.xml"'+ \
                      ' srcname="Crab"'+ \
                      ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
-                     ' duration=1800.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
+                     ' duration=180.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
                      ' outfile="cssens_cmd2.dat"'+ \
                      ' logfile="cssens_cmd2.log" debug=yes chatter=2'
@@ -118,7 +121,7 @@ class Test(test):
         sens['caldb']    = self._caldb
         sens['irf']      = self._irf
         sens['outfile']  = 'cssens_py1.dat'
-        sens['duration'] = 1800.0
+        sens['duration'] = 180.0
         sens['rad']      = 3.0
         sens['emin']     = 1.0
         sens['emax']     = 10.0
@@ -142,7 +145,7 @@ class Test(test):
         sens['caldb']    = self._caldb
         sens['irf']      = self._irf
         sens['outfile']  = 'cssens_py2.dat'
-        sens['duration'] = 1800.0
+        sens['duration'] = 180.0
         sens['rad']      = 3.0
         sens['emin']     = 1.0
         sens['emax']     = 10.0
@@ -144,13 +144,17 @@ class Test(test):
         # Check fit result values
         self.test_value(models['Crab'][2].value(),
-                        5.71055e-16, 1.0e-5, 'Crab prefactor')
+                        5.65431687851392e-16, 1.0e-4 * 5.65431687851392e-16,
+                        'Check Crab prefactor')
         self.test_value(models['Crab'][3].value(),
-                        -2.46174095362681, 1.0e-5, 'Crab index')
-        self.test_value(models['CTABackgroundModel'][0].value(),
-                        1.01831847752743, 1.0e-5, 'Background model prefactor')
-        self.test_value(models['CTABackgroundModel'][1].value(),
-                        0.00742512418279459, 1.0e-5, 'Background model index')
+                        -2.45753747320273, 1.0e-4 * 2.45753747320273,
+                        'Check Crab index')
+        self.test_value(models['Background'][0].value(),
+                        1.0444753409474, 1.0e-4 * 1.0444753409474,
+                        'Check background model prefactor')
+        self.test_value(models['Background'][1].value(),
+                        0.0126628793551562, 1.0e-4 * 0.0126628793551562,
+                        'Check background model index')
         # Return
         return
@@ -87,7 +87,7 @@ class Test(test):
         # Load counts cube and check content.
         evt = gammalib.GCTAEventCube('cntmap_cmd1.fits')
-        self._check_cube(evt, 18483)
+        self._check_cube(evt, 3105)
         # Setup ctbin command
         cmd = ctbin+' inobs="events_that_do_not_exist.fits"'+ \
@@ -115,7 +115,7 @@ class Test(test):
         # Load counts cube and check content.
         evt = gammalib.GCTAEventCube('cntmap_cmd3.fits')
-        self._check_cube(evt, 3689)
+        self._check_cube(evt, 617)
         # Check ctbin --help
         self._check_help(ctbin)
@@ -174,15 +174,15 @@ class Test(test):
         binning.run()
         # Check content of observation container and counts cube
-        self._check_observation(binning, 18483)
-        self._check_cube(binning.cube(), 18483)
+        self._check_observation(binning, 3105)
+        self._check_cube(binning.cube(), 3105)
         # Copy ctbin tool
         cpy_bin = binning.copy()
         # Check content of observation container and counts cube
-        self._check_observation(cpy_bin, 18483)
-        self._check_cube(cpy_bin.cube(), 18483)
+        self._check_observation(cpy_bin, 3105)
+        self._check_cube(cpy_bin.cube(), 3105)
         # Run copy of ctbin tool again
         cpy_bin['logfile'] = 'ctbin_py2.log'
@@ -201,7 +201,7 @@ class Test(test):
         # Load counts cube and check content
         evt = gammalib.GCTAEventCube('ctbin_py1.fits')
-        self._check_cube(evt, 18483)
+        self._check_cube(evt, 3105)
         # Now clear ctbin tool
         binning.clear()
@@ -241,12 +241,12 @@ class Test(test):
         # Check content of observation and cube (need multiplier=3 since
         # three identical observations have been appended)
-        self._check_observation(binning, 18483, multiplier=3)
-        self._check_cube(binning.cube(), 18483, multiplier=3)
+        self._check_observation(binning, 3105, multiplier=3)
+        self._check_cube(binning.cube(), 3105, multiplier=3)
         # Load counts cube and check content.
         evt = gammalib.GCTAEventCube('ctbin_py3.fits')
-        self._check_cube(evt, 18483, multiplier=3)
+        self._check_cube(evt, 3105, multiplier=3)
         # And finally go for a fully Pythonic version with all parameters
         # being specified in a dictionary
@@ -262,7 +262,7 @@ class Test(test):
         # Load counts cube and check content
         evt = gammalib.GCTAEventCube('ctbin_py4.fits')
-        self._check_cube(evt, 18483)
+        self._check_cube(evt, 3105)
         # Return
         return
@@ -288,9 +288,9 @@ class Test(test):
              'Check that there is one observation on the observation container')
         self.test_value(obs.instrument(), 'CTA',
              'Check that the one observation is a CTA observation')
-        self.test_value(obs.ontime(), 1800.0*multiplier, 1.0e-6,
+        self.test_value(obs.ontime(), 300.0*multiplier, 1.0e-6,
              'Check ontime of observation')
-        self.test_value(obs.livetime(), 1764.0*multiplier, 1.0e-6,
+        self.test_value(obs.livetime(), 294.0*multiplier, 1.0e-6,
              'Check livetime of observation')
         self.test_value(pnt.dir().ra_deg(), 83.63, 1.0e-6,
              'Check pointing Right Ascension of observation')
@@ -264,28 +264,28 @@ class Test(test):
         # If there are models in the container then check them
         if nmodels > 0:
             self.test_value(models['Crab']['Prefactor'].value(),
-                            5.767533e-16, 1.0e-4 * 5.767533e-16,
+                            5.6530206356786e-16, 1.0e-4 * 5.6530206356786e-16,
                             'Check fitted Crab Prefactor')
             self.test_value(models['Crab']['Prefactor'].error(),
-                            1.011887e-17, 1.0e-4 * 1.011887e-17,
+                            2.45970361827369e-17, 1.0e-3 * 2.45970361827369e-17,
                             'Check Crab Prefactor error')
             self.test_value(models['Crab']['Index'].value(),
-                            -2.462279, 1.0e-4 * 2.462279,
+                            -2.45716228083265, 1.0e-4 * 2.45716228083265,
                             'Check fitted Crab Index')
             self.test_value(models['Crab']['Index'].error(),
-                            0.0148518, 1.0e-4 * 0.0148518,
+                            0.0366617454398694, 1.0e-3 * 0.0366617454398694,
                             'Check Crab Index error')
-            self.test_value(models['CTABackgroundModel']['Prefactor'].value(),
-                            1.0197698, 1.0e-4 * 1.0197698,
+            self.test_value(models['Background']['Prefactor'].value(),
+                            1.01525433446138, 1.0e-4 * 1.01525433446138,
                             'Check fitted background Prefactor')
-            self.test_value(models['CTABackgroundModel']['Prefactor'].error(),
-                            0.013578, 1.0e-4 * 0.013578,
+            self.test_value(models['Background']['Prefactor'].error(),
+                            0.0334412516391298, 1.0e-4 * 0.0334412516391298,
                             'Check background Prefactor error')
-            self.test_value(models['CTABackgroundModel']['Index'].value(),
-                            0.00836407, 1.0e-4 * 0.00836407,
+            self.test_value(models['Background']['Index'].value(),
+                            -0.005132848897274, 1.0e-3 * 0.005132848897274,
                             'Check fitted background Index')
-            self.test_value(models['CTABackgroundModel']['Index'].error(),
-                            0.00811674, 1.0e-4 * 0.00811674,
+            self.test_value(models['Background']['Index'].error(),
+                            0.0200624490548333, 1.0e-4 * 0.0200624490548333,
                             'Check background Index error')
         # Return
@@ -254,28 +254,28 @@ class Test(test):
         # If there are models in the container then check them
         if nmodels > 0:
             self.test_value(models['Crab']['Prefactor'].value(),
-                            5.767533e-16, 1.0e-4 * 5.767533e-16,
+                            5.6530206356786e-16, 1.0e-4 * 5.6530206356786e-16,
                             'Check fitted Crab Prefactor')
             self.test_value(models['Crab']['Prefactor'].error(),
-                            1.018351e-17, 1.0e-4 * 1.018351e-17,
+                            2.48304276536022e-17, 1.0e-4 * 2.48304276536022e-17,
                             'Check Crab Prefactor error')
             self.test_value(models['Crab']['Index'].value(),
-                            -2.462279, 1.0e-4 * 2.462279,
+                            -2.45716228083265, 1.0e-4 * 2.45716228083265,
                             'Check fitted Crab Index')
             self.test_value(models['Crab']['Index'].error(),
-                            0.0151608, 1.0e-4 * 0.0151608,
+                            0.0386777873333435, 1.0e-4 * 0.0386777873333435,
                             'Check Crab Index error')
-            self.test_value(models['CTABackgroundModel']['Prefactor'].value(),
-                            1.0197698, 1.0e-4 * 1.0197698,
+            self.test_value(models['Background']['Prefactor'].value(),
+                            1.01525433446138, 1.0e-4 * 1.01525433446138,
                             'Check fitted background Prefactor')
-            self.test_value(models['CTABackgroundModel']['Prefactor'].error(),
-                            0.013578, 1.0e-4 * 0.013578,
+            self.test_value(models['Background']['Prefactor'].error(),
+                            0.0334412516391298, 1.0e-4 * 0.0334412516391298,
                             'Check background Prefactor error')
-            self.test_value(models['CTABackgroundModel']['Index'].value(),
-                            0.00836407, 1.0e-4 * 0.00836407,
+            self.test_value(models['Background']['Index'].value(),
+                            -0.005132848897274, 1.0e-3 * 0.005132848897274,
                             'Check fitted background Index')
-            self.test_value(models['CTABackgroundModel']['Index'].error(),
-                            0.00811674, 1.0e-4 * 0.00811674,
+            self.test_value(models['Background']['Index'].error(),
+                            0.0200624490548333, 1.0e-4 * 0.0200624490548333,
                             'Check background Index error')
         # Return
@@ -74,9 +74,9 @@ class Test(test):
         cmd = ctobssim+' inmodel="'+self._model+'" '+ \
                        ' outevents="ctobssim_cmd1.fits"'+ \
                        ' caldb="'+self._caldb+'" irf="'+self._irf+'" '+ \
-                       ' ra=83.63 dec=22.01 rad=10.0'+ \
+                       ' ra=83.63 dec=22.01 rad=3.0'+ \
                        ' tmin="2020-01-01T00:00:00"'+ \
-                       ' tmax="2020-01-01T00:30:00"'+ \
+                       ' tmax="2020-01-01T00:05:00"'+ \
                        ' emin=0.1 emax=100.0'+ \
                        ' logfile="ctobssim_cmd1.log" chatter=1'
@@ -90,15 +90,15 @@ class Test(test):
         # Load counts cube and check content.
         evt = gammalib.GCTAEventList('ctobssim_cmd1.fits')
-        self._test_list(evt, 23822)
+        self._test_list(evt, 3776)
         # Setup ctobssim command
         cmd = ctobssim+' inmodel="model_that_does_not_exist.xml"'+ \
                        ' outevents="ctobssim_cmd2.fits"'+ \
                        ' caldb="'+self._caldb+'" irf="'+self._irf+'" '+ \
-                       ' ra=83.63 dec=22.01 rad=10.0'+ \
+                       ' ra=83.63 dec=22.01 rad=3.0'+ \
                        ' tmin="2020-01-01T00:00:00"'+ \
-                       ' tmax="2020-01-01T00:30:00"'+ \
+                       ' tmax="2020-01-01T00:05:00"'+ \
                        ' emin=0.1 emax=100.0'+ \
                        ' logfile="ctobssim_cmd2.log" debug=yes chatter=1'
@@ -141,9 +141,9 @@ class Test(test):
         sim['irf']       = self._irf
         sim['ra']        = 83.63
         sim['dec']       = 22.01
-        sim['rad']       = 10.0
+        sim['rad']       = 3.0
         sim['tmin']      = '2020-01-01T00:00:00'
-        sim['tmax']      = '2020-01-01T00:30:00'
+        sim['tmax']      = '2020-01-01T00:05:00'
         sim['emin']      = 0.1
         sim['emax']      = 100.0
         sim['outevents'] = 'ctobssim_py1.fits'
@@ -156,33 +156,52 @@ class Test(test):
         # Check content of observation
         self._test_observation(sim)
-        self._test_list(sim.obs()[0].events(), 23822)
+        self._test_list(sim.obs()[0].events(), 3776)
         # Save events
         sim.save()
         # Load counts cube and check content.
         evt = gammalib.GCTAEventList('ctobssim_py1.fits')
-        self._test_list(evt, 23822)
+        self._test_list(evt, 3776)
+
+        # Copy ctobssim tool
+        cpy_sim = sim.copy()
+
+        # Retrieve observation and check content of copy
+        self._test_observation(cpy_sim)
+        self._test_list(cpy_sim.obs()[0].events(), 3776)
+
+        # Execute copy of ctobssim tool again, now with a higher chatter
+        # level than before
+        cpy_sim['outevents'] = 'ctobssim_py2.fits'
+        cpy_sim['logfile']   = 'ctobssim_py2.log'
+        cpy_sim['chatter']   = 3
+        cpy_sim['publish']   = True
+        cpy_sim.logFileOpen()  # Needed to get a new log file
+        cpy_sim.execute()
+
+        # Load counts cube and check content.
+        evt = gammalib.GCTAEventList('ctobssim_py2.fits')
+        self._test_list(evt, 3776)
         # Set-up observation container
         pnts = [{'ra': 83.63, 'dec': 21.01},
-                {'ra': 84.63, 'dec': 22.01},
-                {'ra': 83.63, 'dec': 23.01},
-                {'ra': 82.63, 'dec': 22.01}]
-        obs = obsutils.set_obs_list(pnts, caldb=self._caldb, irf=self._irf)
+                {'ra': 84.63, 'dec': 22.01}]
+        obs = obsutils.set_obs_list(pnts, caldb=self._caldb, irf=self._irf,
+                                    duration=300.0, rad=3.0)
         # Set-up ctobssim tool from observation container
         sim = ctools.ctobssim(obs)
         sim['inmodel']   = self._model
-        sim['outevents'] = 'ctobssim_py2.xml'
-        sim['logfile']   = 'ctobssim_py2.log'
+        sim['outevents'] = 'ctobssim_py3.xml'
+        sim['logfile']   = 'ctobssim_py3.log'
         sim['chatter']   = 3
         # Double maximum event range
         max_rate = sim.max_rate()
-        sim.max_rate(2*max_rate)
-        self.test_value(sim.max_rate(), 2*max_rate, 1.0e-3,
+        sim.max_rate(2.0*max_rate)
+        self.test_value(sim.max_rate(), 2.0*max_rate, 1.0e-3,
                         'Check setting of maximum event rate')
         # Run ctobssim tool
@@ -190,57 +209,27 @@ class Test(test):
         sim.run()
         # Retrieve observation and check content
-        self._test_observation(sim, nobs=4, pnts=pnts)
-        self._test_list(sim.obs()[0].events(), 22904)
-        self._test_list(sim.obs()[1].events(), 23130)
-        self._test_list(sim.obs()[2].events(), 22672)
-        self._test_list(sim.obs()[3].events(), 22549)
+        self._test_observation(sim, nobs=2, pnts=pnts)
+        self._test_list(sim.obs()[0].events(), 3569)
+        self._test_list(sim.obs()[1].events(), 3515)
         # Save events
         sim.save()
         # Load events
-        obs = gammalib.GObservations('ctobssim_py2.xml')
+        obs = gammalib.GObservations('ctobssim_py3.xml')
         # Retrieve observation and check content
-        self._test_list(obs[0].events(), 22904)
-        self._test_list(obs[1].events(), 23130)
-        self._test_list(obs[2].events(), 22672)
-        self._test_list(obs[3].events(), 22549)
-
-        # Copy ctobssim tool
-        cpy_sim = sim.copy()
-
-        # Retrieve observation and check content of copy
-        self._test_observation(cpy_sim, nobs=4, pnts=pnts)
-        self._test_list(cpy_sim.obs()[0].events(), 22904)
-        self._test_list(cpy_sim.obs()[1].events(), 23130)
-        self._test_list(cpy_sim.obs()[2].events(), 22672)
-        self._test_list(cpy_sim.obs()[3].events(), 22549)
-
-        # Execute copy of ctobssim tool again, now with a higher chatter
-        # level than before
-        cpy_sim['outevents'] = 'ctobssim_py3.xml'
-        cpy_sim['logfile']   = 'ctobssim_py3.log'
-        cpy_sim['chatter']   = 4
-        cpy_sim['publish']   = True
-        cpy_sim.logFileOpen()  # Needed to get a new log file
-        cpy_sim.execute()
-
-        # Check result file
-        obs = gammalib.GObservations('ctobssim_py3.xml')
-        self.test_value(obs.size(), 4, 'Check for number of observations')
-        self._test_list(obs[0].events(), 22904)
-        self._test_list(obs[1].events(), 23130)
-        self._test_list(obs[2].events(), 22672)
-        self._test_list(obs[3].events(), 22549)
+        self._test_list(obs[0].events(), 3569)
+        self._test_list(obs[1].events(), 3515)
         # Return
         return
     # Check observation
     def _test_observation(self, obssim, nobs=1,
-                          pnts=[{'ra': 83.63, 'dec': 22.01}]):
+                          pnts=[{'ra': 83.63, 'dec': 22.01}],
+                          ontime=300.0, livetime=294.0):
         """
         Test content of an observation
@@ -255,20 +244,21 @@ class Test(test):
         """
         # Test observation container
         self.test_value(obssim.obs().size(), nobs,
-             'There is one observation')
-        for i in range(obssim.obs().size()):
-            obs = gammalib.GCTAObservation(obssim.obs()[i])
-            pnt = obs.pointing()
+                        'Check number of observations')
+        for i, obs in enumerate(obssim.obs()):
+            pnt = obs.pointing().dir()
+            ra  = pnts[i]['ra']
+            dec = pnts[i]['dec']
             self.test_assert(obs.instrument() == 'CTA',
-                 'Observation is CTA observation')
-            self.test_value(obs.ontime(), 1800.0, 1.0e-6,
-                 'Ontime is 1800 sec')
-            self.test_value(obs.livetime(), 1764.0, 1.0e-6,
-                 'Livetime is 1764 sec')
-            self.test_value(pnt.dir().ra_deg(), pnts[i]['ra'], 1.0e-6,
-                 'Pointing Right Ascension is '+str(pnts[i]['ra'])+' deg')
-            self.test_value(pnt.dir().dec_deg(), pnts[i]['dec'], 1.0e-6,
-                 'Pointing Declination is '+str(pnts[i]['dec'])+' deg')
+                 'Check if observation is CTA observation')
+            self.test_value(obs.ontime(), ontime, 1.0e-6,
+                 'Check if ontime is %f sec' % ontime)
+            self.test_value(obs.livetime(), livetime, 1.0e-6,
+                 'Check if livetime is %f sec' % livetime)
+            self.test_value(pnt.ra_deg(), ra, 1.0e-6,
+                 'Check if pointing Right Ascension is %f deg' % ra)
+            self.test_value(pnt.dec_deg(), dec, 1.0e-6,
+                 'Check if pointing Declination is %f deg' % dec)
         # Return
         return
@@ -252,7 +252,7 @@ class Test(test):
         return
     # Check result file
-    def _check_result_file(self, filename, nevents=22220):
+    def _check_result_file(self, filename, nevents=3736):
         """
         Check result file
@@ -202,7 +202,7 @@ class Test(test):
         return
     # Check result file
-    def _check_result_file(self, filename, nevents=22220):
+    def _check_result_file(self, filename, nevents=3736):
         """
         Check result file
@@ -220,7 +220,7 @@ class Test(test):
         self._check_events(events, nevents=nevents)
         # Check that probability columns exist
-        colname1 = 'PROB_CTABackgroundModel'
+        colname1 = 'PROB_Background'
         colname2 = 'PROB_Crab'
         self._check_column(filename, colname1)
         self._check_column(filename, colname2)        
@@ -73,7 +73,7 @@ class Test(test):
         cmd = ctselect+' inobs="'+self._events+'"'+ \
                        ' outobs="ctselect_cmd1.fits"'+ \
                        ' ra=83.63 dec=22.01 rad=2.0'+ \
-                       ' tmin=2020-01-01T00:08:20 tmax=2020-01-01T00:16:40'+ \
+                       ' tmin=2020-01-01T00:01:10 tmax=2020-01-01T00:03:40'+ \
                        ' emin=0.2 emax=80.0'+ \
                        ' logfile="ctselect_cmd1.log" chatter=1'
@@ -92,7 +92,7 @@ class Test(test):
         cmd = ctselect+' inobs="event_file_that_does_not_exist.fits"'+ \
                        ' outobs="ctselect_cmd2.fits"'+ \
                        ' ra=83.63 dec=22.01 rad=2.0'+ \
-                       ' tmin=2020-01-01T00:08:20 tmax=2020-01-01T00:16:40'+ \
+                       ' tmin=2020-01-01T00:01:10 tmax=2020-01-01T00:03:40'+ \
                        ' emin=0.2 emax=80.0'+ \
                        ' logfile="ctselect_cmd2.log" debug=yes chatter=1'
@@ -133,8 +133,8 @@ class Test(test):
         select['ra']      = 83.63
         select['dec']     = 22.01
         select['rad']     = 2.0
-        select['tmin']    = '2020-01-01T00:08:20'
-        select['tmax']    = '2020-01-01T00:16:40'
+        select['tmin']    = '2020-01-01T00:01:10'
+        select['tmax']    = '2020-01-01T00:03:40'
         select['emin']    = 0.2
         select['emax']    = 80.0
         select['outobs']  = 'ctselect_py1.fits'
@@ -181,7 +181,7 @@ class Test(test):
         # to valid event selections, but since the maximum values are still
         # 'NONE', no event selections should occur.
         cpy_select['usepnt']   = True
-        cpy_select['tmin']     = '2020-01-01T00:08:20'
+        cpy_select['tmin']     = '2020-01-01T00:01:10'
         cpy_select['emin']     = 0.2
         cpy_select['usethres'] = 'USER'
         cpy_select['outobs']   = 'ctselect_py3.fits'
@@ -214,8 +214,8 @@ class Test(test):
         select['ra']       = 83.63
         select['dec']      = 22.01
         select['rad']      = 2.0
-        select['tmin']     = '2020-01-01T00:08:20'
-        select['tmax']     = '2020-01-01T00:16:40'
+        select['tmin']     = '2020-01-01T00:01:10'
+        select['tmax']     = '2020-01-01T00:03:40'
         select['emin']     = 120.0
         select['emax']     = 130.0
         select['expr']     = 'DETX == 0'
@@ -237,8 +237,8 @@ class Test(test):
         select['ra']      = 83.63
         select['dec']     = 22.01
         select['rad']     = 2.0
-        select['tmin']    = '2020-01-01T00:08:20'
-        select['tmax']    = '2020-01-01T00:16:40'
+        select['tmin']    = '2020-01-01T00:01:10'
+        select['tmax']    = '2020-01-01T00:03:40'
         select['emin']    = 0.2
         select['emax']    = 80.0
         select['outobs']  = 'ctselect_py5.fits'
@@ -261,8 +261,8 @@ class Test(test):
         select['ra']      = 83.63
         select['dec']     = 22.01
         select['rad']     = 2.0
-        select['tmin']    = '2020-01-01T00:08:20'
-        select['tmax']    = '2020-01-01T00:16:40'
+        select['tmin']    = '2020-01-01T00:01:10'
+        select['tmax']    = '2020-01-01T00:03:40'
         select['emin']    = 0.2
         select['emax']    = 0.0     # Signals that "emax" should be ignored
         select['outobs']  = 'ctselect_py6.fits'
@@ -282,8 +282,8 @@ class Test(test):
         select['ra']      = 83.63
         select['dec']     = 22.01
         select['rad']     = 2.0
-        select['tmin']    = '2020-01-01T00:08:20'
-        select['tmax']    = '2020-01-01T00:16:40'
+        select['tmin']    = '2020-01-01T00:01:10'
+        select['tmax']    = '2020-01-01T00:03:40'
         select['emin']    = 0.0     # Signals that "emin" should be ignored
         select['emax']    = 80.0
         select['outobs']  = 'ctselect_py7.fits'
@@ -295,7 +295,7 @@ class Test(test):
         select.execute()
         # Check result file
-        self._check_result_file('ctselect_py7.fits', nevents=4709)
+        self._check_result_file('ctselect_py7.fits', nevents=1460)
         # Now set "emin > emax"
         select['emin']    = 150.0
@@ -319,8 +319,8 @@ class Test(test):
         select['ra']      = 83.63
         select['dec']     = 24.01
         select['rad']     = 3.0
-        select['tmin']    = '2020-01-01T00:08:20'
-        select['tmax']    = '2020-01-01T00:16:40'
+        select['tmin']    = '2020-01-01T00:01:10'
+        select['tmax']    = '2020-01-01T00:03:40'
         select['emin']    = 0.2
         select['emax']    = 80.0
         select['outobs']  = 'ctselect_py9.fits'
@@ -332,7 +332,7 @@ class Test(test):
         select.execute()
         # Check result file
-        self._check_result_file('ctselect_py9.fits', nevents=781, dec=24.01,
+        self._check_result_file('ctselect_py9.fits', nevents=240, dec=24.01,
                                 rad=1.5)
         # Now put the RoI outside the existing RoI. This should leave to
@@ -483,7 +483,7 @@ class Test(test):
         return
     # Check result file
-    def _check_result_file(self, filename, nevents=2307, dec=22.01, rad=2.0):
+    def _check_result_file(self, filename, nevents=719, dec=22.01, rad=2.0):
         """
         Check result file
@@ -508,7 +508,7 @@ class Test(test):
         return
     # Check observation and event list
-    def _check_obs(self, obs, nobs=1, nevents=2307):
+    def _check_obs(self, obs, nobs=1, nevents=719):
         """
         Check observation and event list
@@ -533,7 +533,7 @@ class Test(test):
         return
     # Check events
-    def _check_events(self, events, nevents=2307, dec=22.01, rad=2.0):
+    def _check_events(self, events, nevents=719, dec=22.01, rad=2.0):
         """
         Check event list
@@ -68,8 +68,8 @@ class Test(test):
         # Setup ctskymap command
         cmd = ctskymap+' inobs="'+self._events+'"'+\
                        ' outmap="ctskymap_cmd1.fits"'+ \
-                       ' emin=0.1 emax=100.0 nxpix=200 nypix=200'+ \
-                       ' binsz=0.02 coordsys="CEL" proj="CAR"'+ \
+                       ' emin=0.1 emax=100.0 nxpix=20 nypix=20'+ \
+                       ' binsz=0.2 coordsys="CEL" proj="CAR"'+ \
                        ' xref=83.63 yref=22.01 bkgsubtract="NONE"'+ \
                        ' logfile="ctskymap_cmd1.log" chatter=1'
@@ -87,8 +87,8 @@ class Test(test):
         # Setup ctskymap command
         cmd = ctskymap+' inobs="event_file_that_does_not_exist.fits"'+\
                        ' outmap="ctskymap_cmd2.fits"'+ \
-                       ' emin=0.1 emax=100.0 nxpix=200 nypix=200'+ \
-                       ' binsz=0.02 coordsys="CEL" proj="CAR"'+ \
+                       ' emin=0.1 emax=100.0 nxpix=20 nypix=20'+ \
+                       ' binsz=0.2 coordsys="CEL" proj="CAR"'+ \
                        ' xref=83.63 yref=22.01 bkgsubtract="NONE"'+ \
                        ' logfile="ctskymap_cmd2.log" debug=yes chatter=2'
@@ -128,9 +128,9 @@ class Test(test):
         skymap['inobs']       = self._events
         skymap['emin']        = 0.1
         skymap['emax']        = 100
-        skymap['nxpix']       = 200
-        skymap['nypix']       = 200
-        skymap['binsz']       = 0.02
+        skymap['nxpix']       = 20
+        skymap['nypix']       = 20
+        skymap['binsz']       = 0.2
         skymap['coordsys']    = 'CEL'
         skymap['proj']        = 'CAR'
         skymap['xref']        = 83.63
@@ -184,9 +184,9 @@ class Test(test):
         skymap = ctools.ctskymap(obs)
         skymap['emin']        = 0.1
         skymap['emax']        = 100
-        skymap['nxpix']       = 200
-        skymap['nypix']       = 200
-        skymap['binsz']       = 0.02
+        skymap['nxpix']       = 20
+        skymap['nypix']       = 20
+        skymap['binsz']       = 0.2
         skymap['coordsys']    = 'GAL'
         skymap['proj']        = 'CAR'
         skymap['xref']        = 184.5575
@@ -214,9 +214,9 @@ class Test(test):
         skymap = ctools.ctskymap(obs)
         skymap['emin']        = 0.1
         skymap['emax']        = 100
-        skymap['nxpix']       = 200
-        skymap['nypix']       = 200
-        skymap['binsz']       = 0.02
+        skymap['nxpix']       = 20
+        skymap['nypix']       = 20
+        skymap['binsz']       = 0.2
         skymap['coordsys']    = 'GAL'
         skymap['proj']        = 'CAR'
         skymap['xref']        = 184.5575
@@ -241,9 +241,9 @@ class Test(test):
         skymap = ctools.ctskymap(obs)
         skymap['emin']        = 0.1
         skymap['emax']        = 100
-        skymap['nxpix']       = 100  # Make region smaller since the 'RING'
-        skymap['nypix']       = 100  # method takes longer to run than 'IRF'
-        skymap['binsz']       = 0.02
+        skymap['nxpix']       = 10  # Make region smaller since the 'RING'
+        skymap['nypix']       = 10  # method takes longer to run than 'IRF'
+        skymap['binsz']       = 0.2
         skymap['coordsys']    = 'CEL'
         skymap['proj']        = 'CAR'
         skymap['xref']        = 83.63
@@ -264,15 +264,15 @@ class Test(test):
         skymap.execute()
         # Check result file
-        self._check_result_file('ctskymap_py5.fits', 100, 100)
-        self._check_result_file('ctskymap_py5.fits[BACKGROUND]', 100, 100)
-        self._check_result_file('ctskymap_py5.fits[SIGNIFICANCE]', 100, 100)
+        self._check_result_file('ctskymap_py5.fits', 10, 10)
+        self._check_result_file('ctskymap_py5.fits[BACKGROUND]', 10, 10)
+        self._check_result_file('ctskymap_py5.fits[SIGNIFICANCE]', 10, 10)
         # Return
         return
     # Check result file
-    def _check_result_file(self, filename, nx=200, ny=200):
+    def _check_result_file(self, filename, nx=20, ny=20):
         """
         Check result file
@@ -295,7 +295,7 @@ class Test(test):
         return
     # Check sky map
-    def _check_map(self, skymap, nx=200, ny=200):
+    def _check_map(self, skymap, nx=20, ny=20):
         """
         Check sky map
@@ -143,11 +143,11 @@ class Test(test):
         ulimit.save()
         # Check results
-        self.test_value(ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
+        self.test_value(ulimit.diff_ulimit(), 3.11978988143113e-17, 1.0e-21,
                         'Check differential upper limit')
-        self.test_value(ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
+        self.test_value(ulimit.flux_ulimit(), 2.11102478123946e-11, 1.0e-16,
                         'Check upper limit on photon flux')
-        self.test_value(ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
+        self.test_value(ulimit.eflux_ulimit(), 9.32520808361777e-11, 1.0e-16,
                         'Check upper limit on energy flux')
         # Check obs() method
@@ -161,19 +161,19 @@ class Test(test):
         cpy_ulimit = ulimit.copy()
         # Check results of copy
-        self.test_value(cpy_ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
+        self.test_value(cpy_ulimit.diff_ulimit(), 3.11978988143113e-17, 1.0e-21,
                         'Check differential upper limit')
-        self.test_value(cpy_ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
+        self.test_value(cpy_ulimit.flux_ulimit(), 2.11102478123946e-11, 1.0e-16,
                         'Check upper limit on photon flux')
-        self.test_value(cpy_ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
+        self.test_value(cpy_ulimit.eflux_ulimit(), 9.32520808361777e-11, 1.0e-16,
                         'Check upper limit on energy flux')
         # Check results
-        self.test_value(cpy_ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
+        self.test_value(cpy_ulimit.diff_ulimit(), 3.11978988143113e-17, 1.0e-21,
                         'Check differential upper limit')
-        self.test_value(cpy_ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
+        self.test_value(cpy_ulimit.flux_ulimit(), 2.11102478123946e-11, 1.0e-16,
                         'Check upper limit on photon flux')
-        self.test_value(cpy_ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
+        self.test_value(cpy_ulimit.eflux_ulimit(), 9.32520808361777e-11, 1.0e-16,
                         'Check upper limit on energy flux')
         # Now clear copy of ctulimit tool
@@ -208,11 +208,11 @@ class Test(test):
         ulimit.execute()
         # Check results
-        self.test_value(ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
+        self.test_value(ulimit.diff_ulimit(), 3.11978988143113e-17, 1.0e-21,
                         'Check differential upper limit')
-        self.test_value(ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
+        self.test_value(ulimit.flux_ulimit(), 2.11102478123946e-11, 1.0e-16,
                         'Check upper limit on photon flux')
-        self.test_value(ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
+        self.test_value(ulimit.eflux_ulimit(), 9.32520808361777e-11, 1.0e-16,
                         'Check upper limit on energy flux')
         # Test invalid model name
@@ -89,26 +89,26 @@ class Test(gammalib.GPythonTestSuite):
         self.name('examples')
         # Append tests
-        self.append(self.test_generate_prod3_irfs,
-                    'Test generate_prod3_irfs.py')
+        #self.append(self.test_generate_prod3_irfs,
+        #            'Test generate_prod3_irfs.py')
         self.append(self.test_make_pointings,
                     'Test make_pointings.py')
-        self.append(self.test_make_spectrum,
-                    'Test make_spectrum.py')
-        self.append(self.test_make_ts_distributions,
-                    'Test make_ts_distributions.py')
-        self.append(self.test_pipeline_binned_disk,
-                    'Test pipeline_binned_disk.py')
-        self.append(self.test_pipeline_binned_mem,
-                    'Test pipeline_binned_mem.py')
-        self.append(self.test_pipeline_stacked_disk,
-                    'Test pipeline_stacked_disk.py')
-        self.append(self.test_pipeline_stacked_mem,
-                    'Test pipeline_stacked_mem.py')
-        self.append(self.test_pipeline_unbinned_disk,
-                    'Test pipeline_unbinned_disk.py')
-        self.append(self.test_pipeline_unbinned_mem,
-                    'Test pipeline_unbinned_mem.py')
+        #self.append(self.test_make_spectrum,
+        #            'Test make_spectrum.py')
+        #self.append(self.test_make_ts_distributions,
+        #            'Test make_ts_distributions.py')
+        #self.append(self.test_pipeline_binned_disk,
+        #            'Test pipeline_binned_disk.py')
+        #self.append(self.test_pipeline_binned_mem,
+        #            'Test pipeline_binned_mem.py')
+        #self.append(self.test_pipeline_stacked_disk,
+        #            'Test pipeline_stacked_disk.py')
+        #self.append(self.test_pipeline_stacked_mem,
+        #            'Test pipeline_stacked_mem.py')
+        #self.append(self.test_pipeline_unbinned_disk,
+        #            'Test pipeline_unbinned_disk.py')
+        #self.append(self.test_pipeline_unbinned_mem,
+        #            'Test pipeline_unbinned_mem.py')
         self.append(self.test_show_butterfly,
                     'Test show_butterfly.py')
         self.append(self.test_show_irf,
@@ -39,6 +39,9 @@ class Test(test):
         # Call base class constructor
         test.__init__(self)
+        # Set test data
+        self._model = self._datadir + '/model_crab_radialacceptance.xml'
+
         # Return
         return
@@ -89,7 +92,7 @@ class Test(test):
         pnt = gammalib.GSkyDir()
         pnt.radec_deg(83.6331, 22.0145)
         obs = gammalib.GObservations()
-        run = obsutils.set_obs(pnt, duration=100.0, emin=1.0, emax=10.0)
+        run = obsutils.set_obs(pnt, duration=20.0, emin=1.0, emax=10.0)
         run.id('0')
         obs.append(run)
         if two:
@@ -113,14 +116,14 @@ class Test(test):
         # Check simulation results
         self.test_value(res.size(), 1, 'Check number of observations')
         self.test_value(res.models().size(), 2, 'Check number of models')
-        self.test_value(res.nobserved(), 48, 'Check number of observed events')
+        self.test_value(res.nobserved(), 4, 'Check number of observed events')
         self.test_value(res.npred(), 0.0, 'Check number of predicted events')
         self.test_value(res[0].eventtype(), 'EventList', 'Check event type')
         self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
                         'Check minimum energy')
         self.test_value(res[0].events().ebounds().emax().TeV(), 10.0,
                         'Check minimum energy')
-        self.test_value(res[0].events().number(), 48,
+        self.test_value(res[0].events().number(), 4,
                         'Check number of events in list')
         # Check energy dispersion flag
@@ -144,7 +147,7 @@ class Test(test):
         # Check simulation results
         self.test_value(res.size(), 1, 'Check number of observations')
         self.test_value(res.models().size(), 2, 'Check number of models')
-        self.test_value(res.nobserved(), 48, 'Check number of observed events')
+        self.test_value(res.nobserved(), 4, 'Check number of observed events')
         self.test_value(res.npred(), 0.0, 'Check number of predicted events')
         self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
         self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
@@ -153,7 +156,7 @@ class Test(test):
                         'Check minimum energy')
         self.test_value(res[0].events().ebounds().size(), 5,
                         'Check number of energy bins')
-        self.test_value(res[0].events().number(), 48,
+        self.test_value(res[0].events().number(), 4,
                         'Check number of events in cube')
         # Check energy dispersion flag
@@ -177,7 +180,7 @@ class Test(test):
         # Check simulation results
         self.test_value(res.size(), 1, 'Check number of observations')
         self.test_value(res.models().size(), 2, 'Check number of models')
-        self.test_value(res.nobserved(), 96, 'Check number of observed events')
+        self.test_value(res.nobserved(), 15, 'Check number of observed events')
         self.test_value(res.npred(), 0.0, 'Check number of predicted events')
         self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
         self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
@@ -186,7 +189,7 @@ class Test(test):
                         'Check minimum energy')
         self.test_value(res[0].events().ebounds().size(), 5,
                         'Check number of energy bins')
-        self.test_value(res[0].events().number(), 96,
+        self.test_value(res[0].events().number(), 15,
                         'Check number of events in cube')
         # Check energy dispersion flag
@@ -211,7 +214,7 @@ class Test(test):
         # Check simulation results
         self.test_value(res.size(), 1, 'Check number of observations')
         self.test_value(res.models().size(), 2, 'Check number of models')
-        self.test_value(res.nobserved(), 98, 'Check number of observed events')
+        self.test_value(res.nobserved(), 24, 'Check number of observed events')
         self.test_value(res.npred(), 0.0, 'Check number of predicted events')
         self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
         self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
@@ -220,7 +223,7 @@ class Test(test):
                         'Check minimum energy')
         self.test_value(res[0].events().ebounds().size(), 5,
                         'Check number of energy bins')
-        self.test_value(res[0].events().number(), 98,
+        self.test_value(res[0].events().number(), 24,
                         'Check number of events in cube')
         # Check energy dispersion flag
@@ -306,7 +309,7 @@ class Test(test):
         # Check simulation results
         self.test_value(res.size(), 1, 'Check number of observations')
         self.test_value(res.models().size(), 2, 'Check number of models')
-        self.test_value(res.nobserved(), 48, 'Check number of observed events')
+        self.test_value(res.nobserved(), 4, 'Check number of observed events')
         self.test_value(res.npred(), 0.0, 'Check number of predicted events')
         self.test_value(res[0].eventtype(), 'EventList', 'Check event type')
         self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
@@ -80,7 +80,7 @@ class Test(gammalib.GPythonTestSuite):
         rad_sim              =   10.0
         rad_select           =    3.0
         tstart               =    0.0
-        tstop                = 1800.0
+        tstop                =  300.0
         emin                 =    0.1
         emax                 =  100.0
@@ -135,7 +135,7 @@ class Test(gammalib.GPythonTestSuite):
         rad_sim    =   10.0
         rad_select =    3.0
         tstart     =    0.0
-        tstop      = 1800.0
+        tstop      =  300.0
         emin       =    0.1
         emax       =  100.0