test_cssens.py
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#! /usr/bin/env python
# ==========================================================================
# This scripts performs unit tests for the cssens script
#
# Copyright (C) 2016-2021 Juergen Knoedlseder
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import gammalib
import cscripts
from testing import test
# ============================ #
# Test class for cssens script #
# ============================ #
class Test(test):
"""
Test class for cssens script
This test class makes unit tests for the cssens script by using it
from the command line and from Python.
"""
# Constructor
def __init__(self):
"""
Constructor
"""
# Call base class constructor
test.__init__(self)
# Set test data
self._model = self._datadir + '/model_crab_radialacceptance.xml'
# Return
return
# Set test functions
def set(self):
"""
Set all test functions
"""
# Set test name
self.name('cssens')
# Append tests
self.append(self._test_cmd, 'Test cssens on command line')
self.append(self._test_python, 'Test cssens from Python')
self.append(self._test_pickeling, 'Test cssens pickeling')
# Return
return
# Test cssens on command line
def _test_cmd(self):
"""
Test cssens on the command line
"""
# Set script name
cssens = self._script('cssens')
# Setup cssens command
cmd = cssens+' inmodel="'+self._model+'"'+ \
' srcname="Crab"'+ \
' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
' duration=180.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
' outfile="cssens_cmd1.fits"'+ \
' logfile="cssens_cmd1.log" chatter=1'
# Check if execution was successful
self.test_assert(self._execute(cmd) == 0,
'Check successful execution from command line')
# Check result file
self._check_result_file('cssens_cmd1.fits', 1)
# Setup cssens command
cmd = cssens+' inmodel="model_that_does_not_exist.xml"'+ \
' srcname="Crab"'+ \
' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
' duration=180.0 rad=3.0 emin=1.0 emax=10.0 bins=1'+ \
' outfile="cssens_cmd2.fits"'+ \
' logfile="cssens_cmd2.log" debug=yes chatter=2'
# Check if execution failed
self.test_assert(self._execute(cmd, success=False) != 0,
'Check invalid input file when executed from command line')
# Check cssens --help
self._check_help(cssens)
# Return
return
# Test cssens from Python
def _test_python(self):
"""
Test cssens from Python
"""
# Set-up cssens for differential sensitivity computation with
# multiprocessing
sens = cscripts.cssens()
sens['inobs'] = 'NONE'
sens['inmodel'] = self._model
sens['srcname'] = 'Crab'
sens['caldb'] = self._caldb
sens['irf'] = self._irf
sens['duration'] = 180.0
sens['rad'] = 3.0
sens['emin'] = 1.0
sens['emax'] = 10.0
sens['bins'] = 2
sens['outfile'] = 'cssens_py1.fits'
sens['logfile'] = 'cssens_py1.log'
sens['chatter'] = 4
# Run cssens script
sens.logFileOpen() # Make sure we get a log file
sens.run()
sens.save()
# Check sensitivity file
self._check_result_file('cssens_py1.fits', 2)
# Set-up cssens for integral sensitivity computation without
# multiprocessing
sens = cscripts.cssens()
sens['inobs'] = 'NONE'
sens['inmodel'] = self._model
sens['srcname'] = 'Crab'
sens['caldb'] = self._caldb
sens['irf'] = self._irf
sens['duration'] = 180.0
sens['rad'] = 3.0
sens['emin'] = 1.0
sens['emax'] = 10.0
sens['bins'] = 1
sens['type'] = 'Integral'
sens['outfile'] = 'cssens_py2.fits'
sens['logfile'] = 'cssens_py2.log'
sens['chatter'] = 4
sens['nthreads'] = 1
# Execute cssens script
sens.execute()
# Check sensitivity file
self._check_result_file('cssens_py2.fits', 1)
# Return
return
# Test cssens pickeling
def _test_pickeling(self):
"""
Test cssens pickeling
"""
# Perform pickeling tests of empty class
self._pickeling(cscripts.cssens())
# Set-up unbinned cssens
sens = cscripts.cssens()
sens['inobs'] = 'NONE'
sens['inmodel'] = self._model
sens['srcname'] = 'Crab'
sens['caldb'] = self._caldb
sens['irf'] = self._irf
sens['duration'] = 180.0
sens['rad'] = 3.0
sens['emin'] = 1.0
sens['emax'] = 10.0
sens['bins'] = 2
sens['outfile'] = 'cssens_py1_pickle.fits'
sens['logfile'] = 'cssens_py1_pickle.log'
sens['chatter'] = 4
# Perform pickeling tests of filled class
obj = self._pickeling(sens)
# Run csspec script and save light curve
obj.logFileOpen() # Make sure we get a log file
obj.run()
obj.save()
# Check result file
self._check_result_file('cssens_py1_pickle.fits', 2)
# Return
return
# Check result file
def _check_result_file(self, filename, nrows):
"""
Check result file
"""
# Open result file as FITS file
fits = gammalib.GFits(filename)
table = fits.table('SENSITIVITY')
# Check dimensions
self.test_value(table.nrows(), nrows,
'Check number of rows in sensitivity file')
self.test_value(table.ncols(), 10,
'Check number of columns in sensitivity file')
# Return
return