test_csmodelsois.py
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#! /usr/bin/env python
# ==========================================================================
# This scripts performs unit tests for the csmodelsois tool.
#
# Copyright (C) 2017-2020 Josh Cardenzana
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import os
import gammalib
import cscripts
from testing import test
# =============================== #
# Test class for csmodelsois tool #
# =============================== #
class Test(test):
"""
Test class for csmodelsois tool
This test class makes unit tests for the csmodelsois tool by using it from
the command line and from Python.
"""
# Constructor
def __init__(self):
"""
Constructor
"""
# Call base class constructor
test.__init__(self)
# Return
return
# Set test functions
def set(self):
"""
Set all test functions
"""
# Set test name
self.name('csmodelsois')
# Append tests
self.append(self._test_cmd, 'Test csmodelsois on command line')
self.append(self._test_python, 'Test csmodelsois from Python')
# Return
return
# Test csmodelsois on command line
def _test_cmd(self):
"""
Test csmodelsois on the command line
"""
# Set tool name
csmodelsois = self._script('csmodelsois')
# Setup csmodelsois command
cmd = csmodelsois+' inmodel="'+self._model+'"'+ \
' outcube="csmodelsois_cmd1.fits"'+\
' emin=0.1 emax=100.0 enumbins=10 ebinalg=LOG'+ \
' nxpix=100 nypix=100 binsz=0.04 coordsys=CEL'+ \
' soilist="" outmodel=NONE'+ \
' ra=83.63 dec=22.01 proj=CAR'+ \
' logfile="csmodelsois_cmd1.log" chatter=1'
# Check if execution was successful
self.test_assert(self._execute(cmd) == 0,
'Check successful execution from command line')
# Check map cube
self._check_result_file('csmodelsois_cmd1.fits')
# Setup csmodelsois command
cmd = csmodelsois+' inmodel="events_that_do_not_exist.fits"'+ \
' outcube="ccsmodelsois_cmd2.fits"'+\
' emin=0.1 emax=100.0 enumbins=10 ebinalg=LOG'+ \
' nxpix=100 nypix=100 binsz=0.04 coordsys=CEL'+ \
' soilist="" outmodel=NONE'+ \
' ra=83.63 dec=22.01 proj=CAR'+ \
' logfile="csmodelsois_cmd2.log" debug=yes'
# Check if execution failed
self.test_assert(self._execute(cmd, success=False) != 0,
'Check invalid input file when executed from command line')
# Check csmodelsois --help
self._check_help(csmodelsois)
# Return
return
# Test csmodelsois from Python
def _test_python(self):
"""
Test csmodelsois from Python
"""
# Allocate csmodelsois
modelsois = cscripts.csmodelsois()
# Check that empty csmodelsois tool holds an map cube that has no
# energy bins
self._check_cube(modelsois.mapcube(), nmaps=0, npixels=0)
# Check that saving does nothing
modelsois['outcube'] = 'csmodelsois_py0.fits'
modelsois['outmodel'] = 'NONE'
modelsois['logfile'] = 'csmodelsois_py0.log'
modelsois.logFileOpen()
modelsois.save()
self.test_assert(not os.path.isfile('csmodelsois_py0.fits'),
'Check that no map cube has been created')
# Check that clearing does not lead to an exception or segfault
modelsois.clear()
# Now set csmodelsois parameters
modelsois['inmodel'] = self._model
modelsois['ebinalg'] = 'LOG'
modelsois['emin'] = 0.1
modelsois['emax'] = 100.0
modelsois['enumbins'] = 10
modelsois['nxpix'] = 100
modelsois['nypix'] = 100
modelsois['binsz'] = 0.04
modelsois['coordsys'] = 'CEL'
modelsois['proj'] = 'CAR'
modelsois['ra'] = 83.63
modelsois['dec'] = 22.01
modelsois['ptsrcsig'] = 1.0
modelsois['outcube'] = 'csmodelsois_py1.fits'
modelsois['logfile'] = 'csmodelsois_py1.log'
modelsois['chatter'] = 2
modelsois['soilist'] = ''
modelsois['outmodel'] = 'NONE'
# Run csmodelsois tool
modelsois.logFileOpen() # Make sure we get a log file
modelsois.run()
# Save map cube
modelsois.save()
# Check map cube
self._check_result_file('csmodelsois_py1.fits')
# Allocate csmodelsois scripts, set models and do now a linear
# binning; also do not use Gaussian point sources
modelsois = cscripts.csmodelsois()
modelsois['inmodel'] = self._model
modelsois['ebinalg'] = 'LIN'
modelsois['emin'] = 0.1
modelsois['emax'] = 100.0
modelsois['enumbins'] = 10
modelsois['nxpix'] = 100
modelsois['nypix'] = 100
modelsois['binsz'] = 0.04
modelsois['coordsys'] = 'CEL'
modelsois['proj'] = 'CAR'
modelsois['ra'] = 83.63
modelsois['dec'] = 22.01
modelsois['ptsrcsig'] = 0.0
modelsois['outcube'] = 'csmodelsois_py2.fits'
modelsois['logfile'] = 'csmodelsois_py2.log'
modelsois['chatter'] = 4
modelsois['soilist'] = ''
modelsois['outmodel'] = 'NONE'
# Execute mapcube
modelsois.logFileOpen() # Needed to get a new log file
modelsois.execute()
# Check result file
self._check_result_file('csmodelsois_py2.fits')
# Update output filenames and output a new model file
modelsois['outcube'] = 'csmodelsois_py3.fits'
modelsois['logfile'] = 'csmodelsois_py3.log'
modelsois['outmodel'] = 'csmodelsois_py3.xml'
# Execute the file
modelsois.logFileOpen()
modelsois.execute()
# Now check that the output model file doesnt contain a Crab Sources
models3 = gammalib.GModels('csmodelsois_py3.xml')
self.test_assert(not models3.contains('Crab'),
'Check Crab model is not present')
self.test_assert(models3.contains(modelsois.cubemodelname()),
'Check cube model is present')
self._check_result_file('csmodelsois_py3.fits')
# Return
return
# Check result file
def _check_result_file(self, filename):
"""
Check content of map cube
Parameters
----------
filename : str
Map cube file name
"""
# Load map cube
cube = gammalib.GModelSpatialDiffuseCube(filename)
# Check map cube
self._check_cube(cube)
# Return
return
# Check map cube
def _check_cube(self, cube, nmaps=11, npixels=10000):
"""
Check map cube
Parameters
----------
cube : `~gammalib.GModelSpatialDiffuseCube`
Map cube
nmaps : int, optional
Number of maps
npixels : int, optional
Number of pixels
"""
# Get energies (this forces loading in case the map cube is not
# loaded)
self.test_value(len(cube.energies()), nmaps, 'Check number of energies')
# Check dimensions
self.test_value(cube.cube().nmaps(), nmaps, 'Check number of maps')
self.test_value(cube.cube().npix(), npixels, 'Check number of pixels')
# Return
return