Andreas Specovius / ctools

Commit 4cf2e59ef455b0129ed6406690192a9813d463ca

Authored by Jürgen Knödlseder
1 parent 357f7fae

Update Crab test dataset. 

The Crab test event data are now derived from the Prod2 South_0.5h IRF with an offset angle of 0.5 deg and a simulation radius of 3 deg.
Inline Side-by-side
Showing 21 changed files with 187 additions and 183 deletions
cscripts/Makefile.am
  View file @4cf2e59
... ... @@ -175,7 +175,7 @@ testdata = $(top_srcdir)/test/data/crab.xml \
175 175 $(top_srcdir)/test/data/pntdef_maximal.dat \
176 176 $(top_srcdir)/test/data/models.txt \
177 177 $(top_srcdir)/test/data/tsmaps.txt \
178   - $(top_srcdir)/test/data/model_cube_background.xml \
  178 + $(top_srcdir)/test/data/model_cube_background1.xml \
179 179 $(top_srcdir)/test/data/model_cube_background2.xml \
180 180 $(top_srcdir)/test/data/crab_bkgcube.xml \
181 181 $(top_srcdir)/test/data/irf.root \
... ...
examples/make_ts_distributions.py
  View file @4cf2e59
... ... @@ -111,11 +111,10 @@ def make_ts_distribution():
111 111  
112 112 # Loop over energy bands. The energy bands are those that are also
113 113 # used for sensitivity computation.
114   - for ieng in range(20):
  114 + for ieng in range(18):
115 115  
116 116 # Set energies
117   - loge = -1.7 + ieng * 0.2
118   - #emean = pow(10.0, loge)
  117 + loge = -1.3 + ieng * 0.2
119 118 emin = pow(10.0, loge-0.1)
120 119 emax = pow(10.0, loge+0.1)
121 120 if loge < 0:
... ...
test/data/crab.xml
  View file @4cf2e59
... ... @@ -11,14 +11,11 @@
11 11 <parameter name="DEC" scale="1.0" value="22.0145" min="-90" max="90" free="0"/>
12 12 </spatialModel>
13 13 </source>
14   - <source name="Background" type="RadialAcceptance" instrument="CTA">
15   - <spectrum type="PowerLaw">
16   - <parameter name="Prefactor" scale="1e-6" value="61.8" min="0.0" max="1000.0" free="1"/>
17   - <parameter name="Index" scale="-1" value="1.85" min="0.0" max="+5.0" free="1"/>
18   - <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  14 + <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
  15 + <spectrum type="PowerLaw">
  16 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e+3" free="1"/>
  17 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  18 + <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
19 19 </spectrum>
20   - <radialModel type="Gaussian">
21   - <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="1"/>
22   - </radialModel>
23   - </source>
  20 + </source>
24 21 </source_library>
... ...
test/data/crab_events.fits.gz
View file @4cf2e59
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test/data/model_cube_background.xml renamed to test/data/model_cube_background1.xml
  View file @4cf2e59
1 1 <?xml version="1.0" standalone="no"?>
2 2 <source_library title="source library">
3   - <source name="CTABackgroundModel" type="CTACubeBackground" instrument="CTA">
  3 + <source name="CTABackgroundModel1" type="CTACubeBackground" instrument="CTA">
4 4 <spectrum type="PowerLaw">
5 5 <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e+3" free="1"/>
6 6 <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
... ...
test/data/model_temporal_phasecurve.xml
  View file @4cf2e59
... ... @@ -12,7 +12,7 @@
12 12 </spatialModel>
13 13 <temporal type="PhaseCurve" file="model_temporal_phasecurve.fits">
14 14 <parameter name="Normalization" scale="1" value="1.0" min="0.0" max="1000.0" free="0"/>
15   - <parameter name="MJD" scale="1" value="51544.5" min="0.0" max="100000.0" free="0"/>
  15 + <parameter name="MJD" scale="1" value="58849.0" min="0.0" max="100000.0" free="0"/>
16 16 <parameter name="Phase" scale="1" value="0.0" min="0.0" max="1.0" free="0"/>
17 17 <parameter name="F0" scale="1" value="1.0" min="0.0" max="1000.0" free="0"/>
18 18 <parameter name="F1" scale="1" value="0.1" min="0.0" max="1000.0" free="0"/>
... ...
test/data/models.txt
  View file @4cf2e59
1   -model_cube_background.xml
  1 +model_cube_background1.xml
2 2 model_cube_background2.xml
... ...
test/test_cslightcrv.py
  View file @4cf2e59
... ... @@ -76,8 +76,9 @@ class Test(test):
76 76 cmd = cslightcrv+' inobs="'+self._events+'"'+ \
77 77 ' inmodel="'+self._model+'" srcname="Crab"'+ \
78 78 ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
79   - ' tbinalg="LIN" tmin="MJD 51544.50" tmax="MJD 51544.53"'+ \
80   - ' tbins=3 method="3D" enumbins=0 emin=0.1 emax=100.0'+ \
  79 + ' tbinalg=LIN '+ \
  80 + ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:30:00'+ \
  81 + ' tbins=3 method=3D enumbins=0 emin=0.1 emax=100.0'+ \
81 82 ' outfile="lightcurve_cmd1.fits"'+ \
82 83 ' logfile="cslightcrv_cmd1.log" chatter=1'
83 84  
... ... @@ -90,14 +91,15 @@ class Test(test):
90 91 'Check successful execution from command line')
91 92  
92 93 # Check light curve
93   - self._check_light_curve('lightcurve_cmd1.fits', 3, 1.6e-16)
  94 + self._check_light_curve('lightcurve_cmd1.fits', 3)
94 95  
95 96 # Setup cslightcrv command
96 97 cmd = cslightcrv+' inobs="events_that_do_not_exist.fits"'+ \
97 98 ' inmodel="'+self._model+'" srcname="Crab"'+ \
98 99 ' caldb="'+self._caldb+'" irf="'+self._irf+'"'+ \
99   - ' tbinalg="LIN" tmin="MJD 51544.50" tmax="MJD 51544.53"'+ \
100   - ' tbins=3 method="3D" enumbins=0 emin=0.1 emax=100.0'+ \
  100 + ' tbinalg=LIN '+ \
  101 + ' tmin=2020-01-01T00:00:00 tmax=2020-01-01T00:30:00'+ \
  102 + ' tbins=3 method=3D enumbins=0 emin=0.1 emax=100.0'+ \
101 103 ' outfile="lightcurve_cmd1.fits"'+ \
102 104 ' logfile="cslightcrv_cmd2.log" debug=yes'
103 105  
... ... @@ -124,8 +126,8 @@ class Test(test):
124 126 lcrv['caldb'] = self._caldb
125 127 lcrv['irf'] = self._irf
126 128 lcrv['tbinalg'] = 'LIN'
127   - lcrv['tmin'] = 'MJD 51544.50'
128   - lcrv['tmax'] = 'MJD 51544.53'
  129 + lcrv['tmin'] = '2020-01-01T00:00:00'
  130 + lcrv['tmax'] = '2020-01-01T00:30:00'
129 131 lcrv['tbins'] = 3
130 132 lcrv['method'] = '3D'
131 133 lcrv['enumbins'] = 0
... ... @@ -142,14 +144,14 @@ class Test(test):
142 144 lcrv.save()
143 145  
144 146 # Check light curve
145   - self._check_light_curve('cslightcrv_py1.fits', 3, 1.6e-16)
  147 + self._check_light_curve('cslightcrv_py1.fits', 3)
146 148  
147 149 # Now use FILE as time bin algorithm. For this we need first to
148 150 # create an ASCII file. We use now 6 time bins. The ASCII file
149 151 # is saved into the file "lightcurve_py2.dat".
150 152 csv = gammalib.GCsv(2,2)
151   - tmin = 51544.50
152   - tdelta = 0.01
  153 + tmin = 58849.00
  154 + tdelta = 0.0104166
153 155 for i in range(csv.nrows()):
154 156 csv[i,0] = '%.5f' % (tmin + i * tdelta)
155 157 csv[i,1] = '%.5f' % (tmin + (i+1) * tdelta)
... ... @@ -177,7 +179,7 @@ class Test(test):
177 179 lcrv.execute()
178 180  
179 181 # Check light curve
180   - self._check_light_curve('cslightcrv_py2.fits', 2, 1.6e-16)
  182 + self._check_light_curve('cslightcrv_py2.fits', 2)
181 183  
182 184 # Now we setup an observation container on input. We attached the
183 185 # model to the observation container so that cslightcrv should
... ... @@ -206,7 +208,7 @@ class Test(test):
206 208 lcrv.execute()
207 209  
208 210 # Check light curve
209   - self._check_light_curve('cslightcrv_py3.fits', 1, 1.6e-16)
  211 + self._check_light_curve('cslightcrv_py3.fits', 1)
210 212  
211 213 # Binned cslightcrv
212 214 lcrv = cscripts.cslightcrv()
... ... @@ -216,8 +218,8 @@ class Test(test):
216 218 lcrv['caldb'] = self._caldb
217 219 lcrv['irf'] = self._irf
218 220 lcrv['tbinalg'] = 'LIN'
219   - lcrv['tmin'] = 'MJD 51544.50'
220   - lcrv['tmax'] = 'MJD 51544.53'
  221 + lcrv['tmin'] = '2020-01-01T00:00:00'
  222 + lcrv['tmax'] = '2020-01-01T00:30:00'
221 223 lcrv['tbins'] = 2
222 224 lcrv['method'] = '3D'
223 225 lcrv['emin'] = 0.1
... ... @@ -238,7 +240,7 @@ class Test(test):
238 240 lcrv.execute()
239 241  
240 242 # Check light curve
241   - self._check_light_curve('cslightcrv_py4.fits', 2, 1.6e-16)
  243 + self._check_light_curve('cslightcrv_py4.fits', 2)
242 244  
243 245 # cslightcrv with classical analysis
244 246 lcrv = cscripts.cslightcrv()
... ... @@ -268,13 +270,13 @@ class Test(test):
268 270 lcrv.execute()
269 271  
270 272 # Check light curve
271   - self._check_light_curve('cslightcrv_py5.fits', 2, 6.e-16)
  273 + self._check_light_curve('cslightcrv_py5.fits', 2)
272 274  
273 275 # Return
274 276 return
275 277  
276 278 # Check light curve result file
277   - def _check_light_curve(self, filename, bins,pref):
  279 + def _check_light_curve(self, filename, bins, prefactor=5.7e-16):
278 280 """
279 281 Check light curve file
280 282 """
... ... @@ -304,13 +306,11 @@ class Test(test):
304 306 self.test_assert(table.contains(col),
305 307 'FITS file contains "'+col+'" column')
306 308  
307   - # Check that table has been filled
308   - # Prefactor has right order of magnitude
  309 + # Check that the Prefactor has the right order of magnitude
309 310 for s in range(table.nrows()):
310   - self.test_value(table['Prefactor'][s], pref, 0.2*pref,
  311 + self.test_value(table['Prefactor'][s], prefactor, 0.2*prefactor,
311 312 'Check prefactor value')
312 313  
313   -
314 314 # Close FITS file
315 315 fits.close()
316 316  
... ...
test/test_csmodelmerge.py
  View file @4cf2e59
... ... @@ -44,7 +44,7 @@ class Test(test):
44 44  
45 45 # Set members
46 46 self._model1 = self._datadir + '/crab.xml'
47   - self._model2 = self._datadir + '/model_cube_background.xml'
  47 + self._model2 = self._datadir + '/model_cube_background1.xml'
48 48 self._model3 = self._datadir + '/model_cube_background*.xml'
49 49 self._model4 = '@' + self._datadir + '/models.txt'
50 50  
... ...
test/test_csspec.py
  View file @4cf2e59
... ... @@ -49,6 +49,7 @@ class Test(test):
49 49 self._psfcube = self._datadir + '/crab_psfcube.fits'
50 50 self._edispcube = self._datadir + '/crab_edispcube.fits'
51 51 self._bkgcube = self._datadir + '/crab_bkgcube.fits'
  52 + self._bkgmodel = self._datadir + '/crab_bkgcube.xml'
52 53 self._onoff_model = self._datadir + '/onoff_model.xml'
53 54  
54 55 # Return
... ... @@ -146,14 +147,14 @@ class Test(test):
146 147 # Check result file
147 148 self._check_result_file('csspec_py1.fits', 5)
148 149  
149   - # Set-up binned csspec
  150 + # Set-up stacked csspec
150 151 spec = cscripts.csspec()
151 152 spec['inobs'] = self._inobs
152 153 spec['expcube'] = self._expcube
153 154 spec['psfcube'] = self._psfcube
154 155 spec['edispcube'] = self._edispcube
155 156 spec['bkgcube'] = self._bkgcube
156   - spec['inmodel'] = self._model
  157 + spec['inmodel'] = self._bkgmodel
157 158 spec['srcname'] = 'Crab'
158 159 spec['method'] = 'AUTO'
159 160 spec['ebinalg'] = 'LOG'
... ...
test/test_cstsdist.py
  View file @4cf2e59
... ... @@ -145,7 +145,7 @@ class Test(test):
145 145 return
146 146  
147 147 # Check result file
148   - def _check_result_file(self, filename, ncols=11):
  148 + def _check_result_file(self, filename, ncols=9):
149 149 """
150 150 Check result file
151 151  
... ...
test/test_csworkflow.py
  View file @4cf2e59
... ... @@ -146,13 +146,11 @@ class Test(test):
146 146 self.test_value(models['Crab'][2].value(),
147 147 5.71055e-16, 1.0e-5, 'Crab prefactor')
148 148 self.test_value(models['Crab'][3].value(),
149   - -2.463392, 1.0e-5, 'Crab index')
150   - self.test_value(models['Background'][0].value(),
151   - 3.008828, 1.0e-5, 'Background model sigma')
152   - self.test_value(models['Background'][1].value(),
153   - 6.27131e-05, 1.0e-5, 'Background model prefactor')
154   - self.test_value(models['Background'][2].value(),
155   - -1.833184, 1.0e-5, 'Background model index')
  149 + -2.46174095362681, 1.0e-5, 'Crab index')
  150 + self.test_value(models['CTABackgroundModel'][0].value(),
  151 + 1.01831847752743, 1.0e-5, 'Background model prefactor')
  152 + self.test_value(models['CTABackgroundModel'][1].value(),
  153 + 0.00742512418279459, 1.0e-5, 'Background model index')
156 154  
157 155 # Return
158 156 return
... ...
test/test_ctbin.py
  View file @4cf2e59
... ... @@ -87,7 +87,7 @@ class Test(test):
87 87  
88 88 # Load counts cube and check content.
89 89 evt = gammalib.GCTAEventCube('cntmap_cmd1.fits')
90   - self._check_cube(evt, 5542)
  90 + self._check_cube(evt, 18483)
91 91  
92 92 # Setup ctbin command
93 93 cmd = ctbin+' inobs="events_that_do_not_exist.fits"'+ \
... ... @@ -115,7 +115,7 @@ class Test(test):
115 115  
116 116 # Load counts cube and check content.
117 117 evt = gammalib.GCTAEventCube('cntmap_cmd3.fits')
118   - self._check_cube(evt, 890)
  118 + self._check_cube(evt, 3689)
119 119  
120 120 # Check ctbin --help
121 121 self._check_help(ctbin)
... ... @@ -174,15 +174,15 @@ class Test(test):
174 174 binning.run()
175 175  
176 176 # Check content of observation container and counts cube
177   - self._check_observation(binning, 5542)
178   - self._check_cube(binning.cube(), 5542)
  177 + self._check_observation(binning, 18483)
  178 + self._check_cube(binning.cube(), 18483)
179 179  
180 180 # Copy ctbin tool
181 181 cpy_bin = binning.copy()
182 182  
183 183 # Check content of observation container and counts cube
184   - self._check_observation(cpy_bin, 5542)
185   - self._check_cube(cpy_bin.cube(), 5542)
  184 + self._check_observation(cpy_bin, 18483)
  185 + self._check_cube(cpy_bin.cube(), 18483)
186 186  
187 187 # Run copy of ctbin tool again
188 188 cpy_bin['logfile'] = 'ctbin_py2.log'
... ... @@ -201,7 +201,7 @@ class Test(test):
201 201  
202 202 # Load counts cube and check content
203 203 evt = gammalib.GCTAEventCube('ctbin_py1.fits')
204   - self._check_cube(evt, 5542)
  204 + self._check_cube(evt, 18483)
205 205  
206 206 # Now clear ctbin tool
207 207 binning.clear()
... ... @@ -241,12 +241,12 @@ class Test(test):
241 241  
242 242 # Check content of observation and cube (need multiplier=3 since
243 243 # three identical observations have been appended)
244   - self._check_observation(binning, 5542, multiplier=3)
245   - self._check_cube(binning.cube(), 5542, multiplier=3)
  244 + self._check_observation(binning, 18483, multiplier=3)
  245 + self._check_cube(binning.cube(), 18483, multiplier=3)
246 246  
247 247 # Load counts cube and check content.
248 248 evt = gammalib.GCTAEventCube('ctbin_py3.fits')
249   - self._check_cube(evt, 5542, multiplier=3)
  249 + self._check_cube(evt, 18483, multiplier=3)
250 250  
251 251 # And finally go for a fully Pythonic version with all parameters
252 252 # being specified in a dictionary
... ... @@ -262,7 +262,7 @@ class Test(test):
262 262  
263 263 # Load counts cube and check content
264 264 evt = gammalib.GCTAEventCube('ctbin_py4.fits')
265   - self._check_cube(evt, 5542)
  265 + self._check_cube(evt, 18483)
266 266  
267 267 # Return
268 268 return
... ... @@ -290,11 +290,11 @@ class Test(test):
290 290 'Check that the one observation is a CTA observation')
291 291 self.test_value(obs.ontime(), 1800.0*multiplier, 1.0e-6,
292 292 'Check ontime of observation')
293   - self.test_value(obs.livetime(), 1710.0*multiplier, 1.0e-6,
  293 + self.test_value(obs.livetime(), 1764.0*multiplier, 1.0e-6,
294 294 'Check livetime of observation')
295 295 self.test_value(pnt.dir().ra_deg(), 83.63, 1.0e-6,
296 296 'Check pointing Right Ascension of observation')
297   - self.test_value(pnt.dir().dec_deg(), 22.01, 1.0e-6,
  297 + self.test_value(pnt.dir().dec_deg(), 22.51, 1.0e-6,
298 298 'Check pointing Declination of observation')
299 299  
300 300 # Test event cube
... ...
test/test_cterror.py
  View file @4cf2e59
... ... @@ -263,26 +263,30 @@ class Test(test):
263 263  
264 264 # If there are models in the container then check them
265 265 if nmodels > 0:
266   - self.test_value(models['Crab']['Prefactor'].value(), 1.58907e-16,
267   - 1.0e-3, 'Check fitted Crab Prefactor')
268   - self.test_value(models['Crab']['Prefactor'].error(), 0.0529105e-16,
269   - 1.0e-3, 'Check Crab Prefactor error')
270   - self.test_value(models['Crab']['Index'].value(), -2.43549,
271   - 1.0e-3, 'Check fitted Crab Index')
272   - self.test_value(models['Crab']['Index'].error(), 0.027804,
273   - 1.0e-3, 'Check Crab Index error')
274   - self.test_value(models['Background']['Prefactor'].value(), 61.6919e-6,
275   - 1.0e-3, 'Check fitted background Prefactor')
276   - self.test_value(models['Background']['Prefactor'].error(), 1.49438e-6,
277   - 1.0e-3, 'Check background Prefactor error')
278   - self.test_value(models['Background']['Index'].value(), -2.20535,
279   - 1.0e-3, 'Check fitted background Index')
280   - self.test_value(models['Background']['Index'].error(), 0.0113269,
281   - 1.0e-3, 'Check background Index error')
282   - self.test_value(models['Background']['Sigma'].value(), 3.04252,
283   - 1.0e-3, 'Check fitted background Sigma')
284   - self.test_value(models['Background']['Sigma'].error(), 0.0307008,
285   - 1.0e-3, 'Check background Sigma error')
  266 + self.test_value(models['Crab']['Prefactor'].value(),
  267 + 5.767533e-16, 1.0e-4 * 5.767533e-16,
  268 + 'Check fitted Crab Prefactor')
  269 + self.test_value(models['Crab']['Prefactor'].error(),
  270 + 1.011887e-17, 1.0e-4 * 1.011887e-17,
  271 + 'Check Crab Prefactor error')
  272 + self.test_value(models['Crab']['Index'].value(),
  273 + -2.462279, 1.0e-4 * 2.462279,
  274 + 'Check fitted Crab Index')
  275 + self.test_value(models['Crab']['Index'].error(),
  276 + 0.0148518, 1.0e-4 * 0.0148518,
  277 + 'Check Crab Index error')
  278 + self.test_value(models['CTABackgroundModel']['Prefactor'].value(),
  279 + 1.0197698, 1.0e-4 * 1.0197698,
  280 + 'Check fitted background Prefactor')
  281 + self.test_value(models['CTABackgroundModel']['Prefactor'].error(),
  282 + 0.013578, 1.0e-4 * 0.013578,
  283 + 'Check background Prefactor error')
  284 + self.test_value(models['CTABackgroundModel']['Index'].value(),
  285 + 0.00836407, 1.0e-4 * 0.00836407,
  286 + 'Check fitted background Index')
  287 + self.test_value(models['CTABackgroundModel']['Index'].error(),
  288 + 0.00811674, 1.0e-4 * 0.00811674,
  289 + 'Check background Index error')
286 290  
287 291 # Return
288 292 return
... ...
test/test_ctlike.py
  View file @4cf2e59
... ... @@ -253,26 +253,30 @@ class Test(test):
253 253  
254 254 # If there are models in the container then check them
255 255 if nmodels > 0:
256   - self.test_value(models['Crab']['Prefactor'].value(), 1.58907e-16,
257   - 1.0e-3, 'Check fitted Crab Prefactor')
258   - self.test_value(models['Crab']['Prefactor'].error(), 0.0526982e-16,
259   - 1.0e-3, 'Check Crab Prefactor error')
260   - self.test_value(models['Crab']['Index'].value(), -2.43549,
261   - 1.0e-3, 'Check fitted Crab Index')
262   - self.test_value(models['Crab']['Index'].error(), 0.0248116,
263   - 1.0e-3, 'Check Crab Index error')
264   - self.test_value(models['Background']['Prefactor'].value(), 61.6919e-6,
265   - 1.0e-3, 'Check fitted background Prefactor')
266   - self.test_value(models['Background']['Prefactor'].error(), 1.49438e-6,
267   - 1.0e-3, 'Check background Prefactor error')
268   - self.test_value(models['Background']['Index'].value(), -2.20535,
269   - 1.0e-3, 'Check fitted background Index')
270   - self.test_value(models['Background']['Index'].error(), 0.0113269,
271   - 1.0e-3, 'Check background Index error')
272   - self.test_value(models['Background']['Sigma'].value(), 3.04252,
273   - 1.0e-3, 'Check fitted background Sigma')
274   - self.test_value(models['Background']['Sigma'].error(), 0.0307008,
275   - 1.0e-3, 'Check background Sigma error')
  256 + self.test_value(models['Crab']['Prefactor'].value(),
  257 + 5.767533e-16, 1.0e-4 * 5.767533e-16,
  258 + 'Check fitted Crab Prefactor')
  259 + self.test_value(models['Crab']['Prefactor'].error(),
  260 + 1.018351e-17, 1.0e-4 * 1.018351e-17,
  261 + 'Check Crab Prefactor error')
  262 + self.test_value(models['Crab']['Index'].value(),
  263 + -2.462279, 1.0e-4 * 2.462279,
  264 + 'Check fitted Crab Index')
  265 + self.test_value(models['Crab']['Index'].error(),
  266 + 0.0151608, 1.0e-4 * 0.0151608,
  267 + 'Check Crab Index error')
  268 + self.test_value(models['CTABackgroundModel']['Prefactor'].value(),
  269 + 1.0197698, 1.0e-4 * 1.0197698,
  270 + 'Check fitted background Prefactor')
  271 + self.test_value(models['CTABackgroundModel']['Prefactor'].error(),
  272 + 0.013578, 1.0e-4 * 0.013578,
  273 + 'Check background Prefactor error')
  274 + self.test_value(models['CTABackgroundModel']['Index'].value(),
  275 + 0.00836407, 1.0e-4 * 0.00836407,
  276 + 'Check fitted background Index')
  277 + self.test_value(models['CTABackgroundModel']['Index'].error(),
  278 + 0.00811674, 1.0e-4 * 0.00811674,
  279 + 'Check background Index error')
276 280  
277 281 # Return
278 282 return
... ...
test/test_ctobssim.py
  View file @4cf2e59
... ... @@ -90,7 +90,7 @@ class Test(test):
90 90  
91 91 # Load counts cube and check content.
92 92 evt = gammalib.GCTAEventList('ctobssim_cmd1.fits')
93   - self._test_list(evt, 7105)
  93 + self._test_list(evt, 23822)
94 94  
95 95 # Setup ctobssim command
96 96 cmd = ctobssim+' inmodel="model_that_does_not_exist.xml"'+ \
... ... @@ -156,14 +156,14 @@ class Test(test):
156 156  
157 157 # Check content of observation
158 158 self._test_observation(sim)
159   - self._test_list(sim.obs()[0].events(), 7105)
  159 + self._test_list(sim.obs()[0].events(), 23822)
160 160  
161 161 # Save events
162 162 sim.save()
163 163  
164 164 # Load counts cube and check content.
165 165 evt = gammalib.GCTAEventList('ctobssim_py1.fits')
166   - self._test_list(evt, 7105)
  166 + self._test_list(evt, 23822)
167 167  
168 168 # Set-up observation container
169 169 pnts = [{'ra': 83.63, 'dec': 21.01},
... ... @@ -191,10 +191,10 @@ class Test(test):
191 191  
192 192 # Retrieve observation and check content
193 193 self._test_observation(sim, nobs=4, pnts=pnts)
194   - self._test_list(sim.obs()[0].events(), 6199)
195   - self._test_list(sim.obs()[1].events(), 6305)
196   - self._test_list(sim.obs()[2].events(), 6092)
197   - self._test_list(sim.obs()[3].events(), 6192)
  194 + self._test_list(sim.obs()[0].events(), 22904)
  195 + self._test_list(sim.obs()[1].events(), 23130)
  196 + self._test_list(sim.obs()[2].events(), 22672)
  197 + self._test_list(sim.obs()[3].events(), 22549)
198 198  
199 199 # Save events
200 200 sim.save()
... ... @@ -203,20 +203,20 @@ class Test(test):
203 203 obs = gammalib.GObservations('ctobssim_py2.xml')
204 204  
205 205 # Retrieve observation and check content
206   - self._test_list(obs[0].events(), 6199)
207   - self._test_list(obs[1].events(), 6305)
208   - self._test_list(obs[2].events(), 6092)
209   - self._test_list(obs[3].events(), 6192)
  206 + self._test_list(obs[0].events(), 22904)
  207 + self._test_list(obs[1].events(), 23130)
  208 + self._test_list(obs[2].events(), 22672)
  209 + self._test_list(obs[3].events(), 22549)
210 210  
211 211 # Copy ctobssim tool
212 212 cpy_sim = sim.copy()
213 213  
214 214 # Retrieve observation and check content of copy
215 215 self._test_observation(cpy_sim, nobs=4, pnts=pnts)
216   - self._test_list(cpy_sim.obs()[0].events(), 6199)
217   - self._test_list(cpy_sim.obs()[1].events(), 6305)
218   - self._test_list(cpy_sim.obs()[2].events(), 6092)
219   - self._test_list(cpy_sim.obs()[3].events(), 6192)
  216 + self._test_list(cpy_sim.obs()[0].events(), 22904)
  217 + self._test_list(cpy_sim.obs()[1].events(), 23130)
  218 + self._test_list(cpy_sim.obs()[2].events(), 22672)
  219 + self._test_list(cpy_sim.obs()[3].events(), 22549)
220 220  
221 221 # Execute copy of ctobssim tool again, now with a higher chatter
222 222 # level than before
... ... @@ -230,10 +230,10 @@ class Test(test):
230 230 # Check result file
231 231 obs = gammalib.GObservations('ctobssim_py3.xml')
232 232 self.test_value(obs.size(), 4, 'Check for number of observations')
233   - self._test_list(obs[0].events(), 6199)
234   - self._test_list(obs[1].events(), 6305)
235   - self._test_list(obs[2].events(), 6092)
236   - self._test_list(obs[3].events(), 6192)
  233 + self._test_list(obs[0].events(), 22904)
  234 + self._test_list(obs[1].events(), 23130)
  235 + self._test_list(obs[2].events(), 22672)
  236 + self._test_list(obs[3].events(), 22549)
237 237  
238 238 # Return
239 239 return
... ...
test/test_ctphase.py
  View file @4cf2e59
... ... @@ -149,7 +149,7 @@ class Test(test):
149 149 phase['inobs'] = self._events
150 150 phase['inmodel'] = 'NONE'
151 151 phase['srcname'] = 'NONE'
152   - phase['mjd'] = 51544.5
  152 + phase['mjd'] = 58849.0
153 153 phase['phase'] = 0.0
154 154 phase['f0'] = 1.0
155 155 phase['f1'] = 0.1
... ... @@ -187,7 +187,7 @@ class Test(test):
187 187 phase['inobs'] = self._events
188 188 phase['inmodel'] = 'NONE'
189 189 phase['srcname'] = 'NONE'
190   - phase['mjd'] = 51500.0
  190 + phase['mjd'] = 58860.0
191 191 phase['phase'] = 0.0
192 192 phase['f0'] = 1.0
193 193 phase['f1'] = 0.1
... ... @@ -252,7 +252,7 @@ class Test(test):
252 252 return
253 253  
254 254 # Check result file
255   - def _check_result_file(self, filename, nevents=6141):
  255 + def _check_result_file(self, filename, nevents=22220):
256 256 """
257 257 Check result file
258 258  
... ...
test/test_ctprob.py
  View file @4cf2e59
... ... @@ -202,7 +202,7 @@ class Test(test):
202 202 return
203 203  
204 204 # Check result file
205   - def _check_result_file(self, filename, nevents=6141):
  205 + def _check_result_file(self, filename, nevents=22220):
206 206 """
207 207 Check result file
208 208  
... ... @@ -220,7 +220,7 @@ class Test(test):
220 220 self._check_events(events, nevents=nevents)
221 221  
222 222 # Check that probability columns exist
223   - colname1 = 'PROB_Background'
  223 + colname1 = 'PROB_CTABackgroundModel'
224 224 colname2 = 'PROB_Crab'
225 225 self._check_column(filename, colname1)
226 226 self._check_column(filename, colname2)
... ... @@ -232,7 +232,7 @@ class Test(test):
232 232 return
233 233  
234 234 # Check observation and event list
235   - def _check_obs(self, obs, nobs=1, nevents=6141):
  235 + def _check_obs(self, obs, nobs=1, nevents=22220):
236 236 """
237 237 Check observation and event list
238 238  
... ... @@ -257,7 +257,7 @@ class Test(test):
257 257 return
258 258  
259 259 # Check events
260   - def _check_events(self, events, nevents=6141):
  260 + def _check_events(self, events, nevents=22220):
261 261 """
262 262 Check event list
263 263  
... ...
test/test_ctselect.py
  View file @4cf2e59
... ... @@ -72,8 +72,8 @@ class Test(test):
72 72 # Setup ctselect command
73 73 cmd = ctselect+' inobs="'+self._events+'"'+ \
74 74 ' outobs="ctselect_cmd1.fits"'+ \
75   - ' ra=83.63 dec=22.01 rad=3.0'+ \
76   - ' tmin=500.0 tmax=1000.0'+ \
  75 + ' ra=83.63 dec=22.01 rad=2.0'+ \
  76 + ' tmin=2020-01-01T00:08:20 tmax=2020-01-01T00:16:40'+ \
77 77 ' emin=0.2 emax=80.0'+ \
78 78 ' logfile="ctselect_cmd1.log" chatter=1'
79 79  
... ... @@ -91,8 +91,8 @@ class Test(test):
91 91 # Setup ctselect command
92 92 cmd = ctselect+' inobs="event_file_that_does_not_exist.fits"'+ \
93 93 ' outobs="ctselect_cmd2.fits"'+ \
94   - ' ra=83.63 dec=22.01 rad=3.0'+ \
95   - ' tmin=500.0 tmax=1000.0'+ \
  94 + ' ra=83.63 dec=22.01 rad=2.0'+ \
  95 + ' tmin=2020-01-01T00:08:20 tmax=2020-01-01T00:16:40'+ \
96 96 ' emin=0.2 emax=80.0'+ \
97 97 ' logfile="ctselect_cmd2.log" debug=yes chatter=1'
98 98  
... ... @@ -132,9 +132,9 @@ class Test(test):
132 132 select['inobs'] = self._events
133 133 select['ra'] = 83.63
134 134 select['dec'] = 22.01
135   - select['rad'] = 3
136   - select['tmin'] = 500.0
137   - select['tmax'] = 1000.0
  135 + select['rad'] = 2.0
  136 + select['tmin'] = '2020-01-01T00:08:20'
  137 + select['tmax'] = '2020-01-01T00:16:40'
138 138 select['emin'] = 0.2
139 139 select['emax'] = 80.0
140 140 select['outobs'] = 'ctselect_py1.fits'
... ... @@ -181,7 +181,7 @@ class Test(test):
181 181 # to valid event selections, but since the maximum values are still
182 182 # 'NONE', no event selections should occur.
183 183 cpy_select['usepnt'] = True
184   - cpy_select['tmin'] = 500.0
  184 + cpy_select['tmin'] = '2020-01-01T00:08:20'
185 185 cpy_select['emin'] = 0.2
186 186 cpy_select['usethres'] = 'USER'
187 187 cpy_select['outobs'] = 'ctselect_py3.fits'
... ... @@ -213,9 +213,9 @@ class Test(test):
213 213 select = ctools.ctselect(obs)
214 214 select['ra'] = 83.63
215 215 select['dec'] = 22.01
216   - select['rad'] = 3.0
217   - select['tmin'] = 500.0
218   - select['tmax'] = 1000.0
  216 + select['rad'] = 2.0
  217 + select['tmin'] = '2020-01-01T00:08:20'
  218 + select['tmax'] = '2020-01-01T00:16:40'
219 219 select['emin'] = 120.0
220 220 select['emax'] = 130.0
221 221 select['expr'] = 'DETX == 0'
... ... @@ -236,9 +236,9 @@ class Test(test):
236 236 select['inobs'] = self._invalid_events
237 237 select['ra'] = 83.63
238 238 select['dec'] = 22.01
239   - select['rad'] = 3
240   - select['tmin'] = 500.0
241   - select['tmax'] = 1000.0
  239 + select['rad'] = 2.0
  240 + select['tmin'] = '2020-01-01T00:08:20'
  241 + select['tmax'] = '2020-01-01T00:16:40'
242 242 select['emin'] = 0.2
243 243 select['emax'] = 80.0
244 244 select['outobs'] = 'ctselect_py5.fits'
... ... @@ -260,9 +260,9 @@ class Test(test):
260 260 select['inobs'] = self._events+'[EVENTS]'
261 261 select['ra'] = 83.63
262 262 select['dec'] = 22.01
263   - select['rad'] = 3.0
264   - select['tmin'] = 500.0
265   - select['tmax'] = 1000.0
  263 + select['rad'] = 2.0
  264 + select['tmin'] = '2020-01-01T00:08:20'
  265 + select['tmax'] = '2020-01-01T00:16:40'
266 266 select['emin'] = 0.2
267 267 select['emax'] = 0.0 # Signals that "emax" should be ignored
268 268 select['outobs'] = 'ctselect_py6.fits'
... ... @@ -274,16 +274,16 @@ class Test(test):
274 274 select.execute()
275 275  
276 276 # Check result file
277   - self._check_result_file('ctselect_py6.fits', nevents=595)
  277 + self._check_result_file('ctselect_py6.fits')
278 278  
279 279 # Now ignore the "emin" value.
280 280 select = ctools.ctselect()
281 281 select['inobs'] = self._events+'[EVENTS]'
282 282 select['ra'] = 83.63
283 283 select['dec'] = 22.01
284   - select['rad'] = 3.0
285   - select['tmin'] = 500.0
286   - select['tmax'] = 1000.0
  284 + select['rad'] = 2.0
  285 + select['tmin'] = '2020-01-01T00:08:20'
  286 + select['tmax'] = '2020-01-01T00:16:40'
287 287 select['emin'] = 0.0 # Signals that "emin" should be ignored
288 288 select['emax'] = 80.0
289 289 select['outobs'] = 'ctselect_py7.fits'
... ... @@ -295,7 +295,7 @@ class Test(test):
295 295 select.execute()
296 296  
297 297 # Check result file
298   - self._check_result_file('ctselect_py7.fits', nevents=1684)
  298 + self._check_result_file('ctselect_py7.fits', nevents=4709)
299 299  
300 300 # Now set "emin > emax"
301 301 select['emin'] = 150.0
... ... @@ -318,9 +318,9 @@ class Test(test):
318 318 select['inobs'] = self._events
319 319 select['ra'] = 83.63
320 320 select['dec'] = 24.01
321   - select['rad'] = 5.0
322   - select['tmin'] = 500.0
323   - select['tmax'] = 1000.0
  321 + select['rad'] = 3.0
  322 + select['tmin'] = '2020-01-01T00:08:20'
  323 + select['tmax'] = '2020-01-01T00:16:40'
324 324 select['emin'] = 0.2
325 325 select['emax'] = 80.0
326 326 select['outobs'] = 'ctselect_py9.fits'
... ... @@ -332,7 +332,8 @@ class Test(test):
332 332 select.execute()
333 333  
334 334 # Check result file
335   - self._check_result_file('ctselect_py9.fits', nevents=466, dec=24.01)
  335 + self._check_result_file('ctselect_py9.fits', nevents=781, dec=24.01,
  336 + rad=1.5)
336 337  
337 338 # Now put the RoI outside the existing RoI. This should leave to
338 339 # an empty event list.
... ... @@ -348,14 +349,14 @@ class Test(test):
348 349  
349 350 # Check result file
350 351 self._check_result_file('ctselect_py10.fits', nevents=0, dec=-22.01,
351   - rad=5.0)
  352 + rad=3.0)
352 353  
353 354 # Now test phase cut
354 355 select = ctools.ctselect()
355 356 select['inobs'] = self._phased_events
356 357 select['ra'] = 83.63
357 358 select['dec'] = 22.01
358   - select['rad'] = 5.0
  359 + select['rad'] = 2.0
359 360 select['tmin'] = 'INDEF'
360 361 select['tmax'] = 'INDEF'
361 362 select['emin'] = 0.1
... ... @@ -370,14 +371,14 @@ class Test(test):
370 371 select.execute()
371 372  
372 373 # Check result file
373   - self._check_result_file('ctselect_py11.fits', nevents=1909, rad=5.0)
  374 + self._check_result_file('ctselect_py11.fits', nevents=1909)
374 375  
375   - # Now test anoother phase cut
  376 + # Now test another phase cut
376 377 select = ctools.ctselect()
377 378 select['inobs'] = self._phased_events
378 379 select['ra'] = 83.63
379 380 select['dec'] = 22.01
380   - select['rad'] = 5.0
  381 + select['rad'] = 2.0
381 382 select['tmin'] = 'INDEF'
382 383 select['tmax'] = 'INDEF'
383 384 select['emin'] = 0.1
... ... @@ -392,7 +393,7 @@ class Test(test):
392 393 select.execute()
393 394  
394 395 # Check result file
395   - self._check_result_file('ctselect_py12.fits', nevents=1995, rad=5.0)
  396 + self._check_result_file('ctselect_py12.fits', nevents=1995)
396 397  
397 398 # Test invalid minimum phase value
398 399 self.test_try('Test invalid minimum phase value')
... ... @@ -482,7 +483,7 @@ class Test(test):
482 483 return
483 484  
484 485 # Check result file
485   - def _check_result_file(self, filename, nevents=591, dec=22.01, rad=3.0):
  486 + def _check_result_file(self, filename, nevents=2307, dec=22.01, rad=2.0):
486 487 """
487 488 Check result file
488 489  
... ... @@ -507,7 +508,7 @@ class Test(test):
507 508 return
508 509  
509 510 # Check observation and event list
510   - def _check_obs(self, obs, nobs=1, nevents=591):
  511 + def _check_obs(self, obs, nobs=1, nevents=2307):
511 512 """
512 513 Check observation and event list
513 514  
... ... @@ -532,7 +533,7 @@ class Test(test):
532 533 return
533 534  
534 535 # Check events
535   - def _check_events(self, events, nevents=591, dec=22.01, rad=3.0):
  536 + def _check_events(self, events, nevents=2307, dec=22.01, rad=2.0):
536 537 """
537 538 Check event list
538 539  
... ...
test/test_ctulimit.py
  View file @4cf2e59
... ... @@ -143,11 +143,11 @@ class Test(test):
143 143 ulimit.save()
144 144  
145 145 # Check results
146   - self.test_value(ulimit.diff_ulimit(), 8.86803e-18, 1.0e-21,
  146 + self.test_value(ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
147 147 'Check differential upper limit')
148   - self.test_value(ulimit.flux_ulimit(), 6.10509e-12, 1.0e-16,
  148 + self.test_value(ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
149 149 'Check upper limit on photon flux')
150   - self.test_value(ulimit.eflux_ulimit(), 2.75669e-11, 1.0e-16,
  150 + self.test_value(ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
151 151 'Check upper limit on energy flux')
152 152  
153 153 # Check obs() method
... ... @@ -161,19 +161,19 @@ class Test(test):
161 161 cpy_ulimit = ulimit.copy()
162 162  
163 163 # Check results of copy
164   - self.test_value(cpy_ulimit.diff_ulimit(), 8.86803e-18, 1.0e-21,
  164 + self.test_value(cpy_ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
165 165 'Check differential upper limit')
166   - self.test_value(cpy_ulimit.flux_ulimit(), 6.10509e-12, 1.0e-16,
  166 + self.test_value(cpy_ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
167 167 'Check upper limit on photon flux')
168   - self.test_value(cpy_ulimit.eflux_ulimit(), 2.75669e-11, 1.0e-16,
  168 + self.test_value(cpy_ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
169 169 'Check upper limit on energy flux')
170 170  
171 171 # Check results
172   - self.test_value(cpy_ulimit.diff_ulimit(), 8.86803e-18, 1.0e-21,
  172 + self.test_value(cpy_ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
173 173 'Check differential upper limit')
174   - self.test_value(cpy_ulimit.flux_ulimit(), 6.10509e-12, 1.0e-16,
  174 + self.test_value(cpy_ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
175 175 'Check upper limit on photon flux')
176   - self.test_value(cpy_ulimit.eflux_ulimit(), 2.75669e-11, 1.0e-16,
  176 + self.test_value(cpy_ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
177 177 'Check upper limit on energy flux')
178 178  
179 179 # Now clear copy of ctulimit tool
... ... @@ -208,11 +208,11 @@ class Test(test):
208 208 ulimit.execute()
209 209  
210 210 # Check results
211   - self.test_value(ulimit.diff_ulimit(), 8.86803e-18, 1.0e-21,
  211 + self.test_value(ulimit.diff_ulimit(), 3.05020546110845e-17, 1.0e-21,
212 212 'Check differential upper limit')
213   - self.test_value(ulimit.flux_ulimit(), 6.10509e-12, 1.0e-16,
  213 + self.test_value(ulimit.flux_ulimit(), 2.07242046724517e-11, 1.0e-16,
214 214 'Check upper limit on photon flux')
215   - self.test_value(ulimit.eflux_ulimit(), 2.75669e-11, 1.0e-16,
  215 + self.test_value(ulimit.eflux_ulimit(), 9.20229587739368e-11, 1.0e-16,
216 216 'Check upper limit on energy flux')
217 217  
218 218 # Test invalid model name
... ...
test/test_obsutils.py
  View file @4cf2e59
... ... @@ -113,14 +113,14 @@ class Test(test):
113 113 # Check simulation results
114 114 self.test_value(res.size(), 1, 'Check number of observations')
115 115 self.test_value(res.models().size(), 2, 'Check number of models')
116   - self.test_value(res.nobserved(), 40, 'Check number of observed events')
  116 + self.test_value(res.nobserved(), 48, 'Check number of observed events')
117 117 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
118 118 self.test_value(res[0].eventtype(), 'EventList', 'Check event type')
119 119 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
120 120 'Check minimum energy')
121 121 self.test_value(res[0].events().ebounds().emax().TeV(), 10.0,
122 122 'Check minimum energy')
123   - self.test_value(res[0].events().number(), 40,
  123 + self.test_value(res[0].events().number(), 48,
124 124 'Check number of events in list')
125 125  
126 126 # Check energy dispersion flag
... ... @@ -144,7 +144,7 @@ class Test(test):
144 144 # Check simulation results
145 145 self.test_value(res.size(), 1, 'Check number of observations')
146 146 self.test_value(res.models().size(), 2, 'Check number of models')
147   - self.test_value(res.nobserved(), 40, 'Check number of observed events')
  147 + self.test_value(res.nobserved(), 48, 'Check number of observed events')
148 148 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
149 149 self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
150 150 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
... ... @@ -153,7 +153,7 @@ class Test(test):
153 153 'Check minimum energy')
154 154 self.test_value(res[0].events().ebounds().size(), 5,
155 155 'Check number of energy bins')
156   - self.test_value(res[0].events().number(), 40,
  156 + self.test_value(res[0].events().number(), 48,
157 157 'Check number of events in cube')
158 158  
159 159 # Check energy dispersion flag
... ... @@ -177,7 +177,7 @@ class Test(test):
177 177 # Check simulation results
178 178 self.test_value(res.size(), 1, 'Check number of observations')
179 179 self.test_value(res.models().size(), 2, 'Check number of models')
180   - self.test_value(res.nobserved(), 86, 'Check number of observed events')
  180 + self.test_value(res.nobserved(), 96, 'Check number of observed events')
181 181 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
182 182 self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
183 183 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
... ... @@ -186,7 +186,7 @@ class Test(test):
186 186 'Check minimum energy')
187 187 self.test_value(res[0].events().ebounds().size(), 5,
188 188 'Check number of energy bins')
189   - self.test_value(res[0].events().number(), 86,
  189 + self.test_value(res[0].events().number(), 96,
190 190 'Check number of events in cube')
191 191  
192 192 # Check energy dispersion flag
... ... @@ -211,7 +211,7 @@ class Test(test):
211 211 # Check simulation results
212 212 self.test_value(res.size(), 1, 'Check number of observations')
213 213 self.test_value(res.models().size(), 2, 'Check number of models')
214   - self.test_value(res.nobserved(), 82, 'Check number of observed events')
  214 + self.test_value(res.nobserved(), 98, 'Check number of observed events')
215 215 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
216 216 self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
217 217 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
... ... @@ -220,7 +220,7 @@ class Test(test):
220 220 'Check minimum energy')
221 221 self.test_value(res[0].events().ebounds().size(), 5,
222 222 'Check number of energy bins')
223   - self.test_value(res[0].events().number(), 82,
  223 + self.test_value(res[0].events().number(), 98,
224 224 'Check number of events in cube')
225 225  
226 226 # Check energy dispersion flag
... ... @@ -306,7 +306,7 @@ class Test(test):
306 306 # Check simulation results
307 307 self.test_value(res.size(), 1, 'Check number of observations')
308 308 self.test_value(res.models().size(), 2, 'Check number of models')
309   - self.test_value(res.nobserved(), 40, 'Check number of observed events')
  309 + self.test_value(res.nobserved(), 48, 'Check number of observed events')
310 310 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
311 311 self.test_value(res[0].eventtype(), 'EventList', 'Check event type')
312 312 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
... ...