#! /usr/bin/env python # ========================================================================== # This scripts performs unit tests for the csmodelsois tool. # # Copyright (C) 2017-2018 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 . # # ========================================================================== 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.maps(), nmaps, 'Check number of maps') self.test_value(cube.pixels(), npixels, 'Check number of pixels') # Return return