Veronika Vodeb / ctools

Commit c1981f9ae56fb584309478d44d2c6552f6a380c9

Authored by Jürgen Knödlseder
1 parent 15895c1e

CTA background rates are now per ontime (#2758)

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Showing 9 changed files with 56 additions and 48 deletions
ChangeLog
  View file @c1981f9
1   -2018-11-07
  1 +2018-11-16
2 2  
3 3 * Version 1.6.0 released
4 4 ========================
5 5  
  6 + CTA background rates are now per ontime (#2758)
6 7 Apply event bin weighting in ctmodel for stacked computation (#2721)
7 8 Enable ctbin to produce counts cubes for a joint binned analysis (#2714)
8 9 Add Jupyter notebooks for H.E.S.S. DR1 (#2712)
... ...
1 1 New Features and Important Changes in ctools 1.6.0
2 2  
3   -7 November 2018
  3 +16 November 2018
4 4  
5 5  
6 6 Introduction
... ... @@ -11,6 +11,10 @@ ctools release with respect to the precedent release.
11 11  
12 12 Configuration
13 13 -------------
  14 +CTA background rates are now per ontime and not livetime. This makes the IRF
  15 +background consistent with the cube background, and is also consistent with
  16 +the open gamma data format (#2758).
  17 +
14 18 A Code Generator was added to the development directory that can be started
15 19 using dev/codegen.py and that requires GammaLib to be installed. The code
16 20 generator allows adding ctools and cscripts, including unit tests and code
... ...
doc/source/admin/release_history/1.6.rst
  View file @c1981f9
... ... @@ -112,6 +112,8 @@ New features
112 112 Clean up
113 113 --------
114 114  
  115 +* [`2758 <https://cta-redmine.irap.omp.eu/issues/2758>`_] -
  116 + CTA background rates are now per ontime
115 117 * Remove ``ctools::is_valid_filename()`` method
116 118 * [`2045 <https://cta-redmine.irap.omp.eu/issues/2045>`_] -
117 119 Remove ``ctools::time_reference`` constant
... ...
test/test_cslightcrv.py
  View file @c1981f9
... ... @@ -241,30 +241,31 @@ class Test(test):
241 241  
242 242 # cslightcrv with classical analysis
243 243 lcrv = cscripts.cslightcrv()
244   - lcrv['inobs'] = self._offaxis_events
245   - lcrv['inmodel'] = self._model_onoff
246   - lcrv['srcname'] = 'Crab'
247   - lcrv['caldb'] = self._caldb
248   - lcrv['irf'] = self._irf
249   - lcrv['tbinalg'] = 'LIN'
250   - lcrv['tmin'] = '2020-01-01T00:00:00'
251   - lcrv['tmax'] = '2020-01-01T00:05:00'
252   - lcrv['tbins'] = 2
253   - lcrv['method'] = 'ONOFF'
254   - lcrv['emin'] = 1.0
255   - lcrv['emax'] = 100.0
256   - lcrv['enumbins'] = 2
257   - lcrv['coordsys'] = 'CEL'
258   - lcrv['xref'] = 83.63
259   - lcrv['yref'] = 22.01
260   - lcrv['rad'] = 0.2
261   - lcrv['etruemin'] = 1.0
262   - lcrv['etruemax'] = 100.0
263   - lcrv['etruebins'] = 5
264   - lcrv['statistic'] = 'WSTAT'
265   - lcrv['outfile'] = 'cslightcrv_py5.fits'
266   - lcrv['logfile'] = 'cslightcrv_py5.log'
267   - lcrv['chatter'] = 4
  244 + lcrv['inobs'] = self._offaxis_events
  245 + lcrv['inmodel'] = self._model_onoff
  246 + lcrv['srcname'] = 'Crab'
  247 + lcrv['caldb'] = self._caldb
  248 + lcrv['irf'] = self._irf
  249 + lcrv['tbinalg'] = 'LIN'
  250 + lcrv['tmin'] = '2020-01-01T00:00:00'
  251 + lcrv['tmax'] = '2020-01-01T00:05:00'
  252 + lcrv['tbins'] = 2
  253 + lcrv['method'] = 'ONOFF'
  254 + lcrv['use_irf_bkg'] = False # Needed even if WSTAT
  255 + lcrv['emin'] = 1.0
  256 + lcrv['emax'] = 100.0
  257 + lcrv['enumbins'] = 2
  258 + lcrv['coordsys'] = 'CEL'
  259 + lcrv['xref'] = 83.63
  260 + lcrv['yref'] = 22.01
  261 + lcrv['rad'] = 0.2
  262 + lcrv['etruemin'] = 1.0
  263 + lcrv['etruemax'] = 100.0
  264 + lcrv['etruebins'] = 5
  265 + lcrv['statistic'] = 'WSTAT'
  266 + lcrv['outfile'] = 'cslightcrv_py5.fits'
  267 + lcrv['logfile'] = 'cslightcrv_py5.log'
  268 + lcrv['chatter'] = 4
268 269  
269 270 # Execute cslightcrv script
270 271 lcrv.execute()
... ...
test/test_csworkflow.py
  View file @c1981f9
... ... @@ -139,10 +139,10 @@ class Test(test):
139 139 models = gammalib.GModels(filename)
140 140  
141 141 # Set reference values
142   - prefactor = 3.6507089091164e-16
143   - index = 2.39314305030239
144   - pre_background = 1.0405193333791
145   - index_background = 0.0100808528325967
  142 + prefactor = 3.62775976898809e-16
  143 + index = 2.39100016863397
  144 + pre_background = 1.05367124323594
  145 + index_background = 0.0421705243014668
146 146  
147 147 # Check fit result values
148 148 self.test_value(models['Crab'][2].value(),
... ...
test/test_cterror.py
  View file @c1981f9
... ... @@ -264,8 +264,8 @@ class Test(test):
264 264 prefactor_error = 1.12920470341148e-16
265 265 index = 2.39356360626209
266 266 index_error = 0.128468611886618
267   - pre_background = 1.01409721534593
268   - pre_background_error = 0.122650321517162
  267 + pre_background = 0.993814959041969
  268 + pre_background_error = 0.120197277367473
269 269 index_background = 0.0436264224948547
270 270 index_background_error = 0.110703165254809
271 271  
... ...
test/test_ctlike.py
  View file @c1981f9
... ... @@ -252,8 +252,8 @@ class Test(test):
252 252 prefactor_error = 1.07582291031224e-16
253 253 index = 2.39356360626209
254 254 index_error = 0.126492171703747
255   - pre_background = 1.01409721534593
256   - pre_background_error = 0.122650321517162
  255 + pre_background = 0.993814959041969
  256 + pre_background_error = 0.120197277367473
257 257 index_background = 0.0436264224948547
258 258 index_background_error = 0.110703165254809
259 259  
... ...
test/test_ctobssim.py
  View file @c1981f9
... ... @@ -86,7 +86,7 @@ class Test(test):
86 86  
87 87 # Load counts cube and check content.
88 88 evt = gammalib.GCTAEventList('ctobssim_cmd1.fits')
89   - self._test_list(evt, 250)
  89 + self._test_list(evt, 251)
90 90  
91 91 # Setup ctobssim command
92 92 cmd = ctobssim+' inmodel="model_that_does_not_exist.xml"'+ \
... ... @@ -152,21 +152,21 @@ class Test(test):
152 152  
153 153 # Check content of observation
154 154 self._test_observation(sim)
155   - self._test_list(sim.obs()[0].events(), 250)
  155 + self._test_list(sim.obs()[0].events(), 251)
156 156  
157 157 # Save events
158 158 sim.save()
159 159  
160 160 # Load counts cube and check content.
161 161 evt = gammalib.GCTAEventList('ctobssim_py1.fits')
162   - self._test_list(evt, 250)
  162 + self._test_list(evt, 251)
163 163  
164 164 # Copy ctobssim tool
165 165 cpy_sim = sim.copy()
166 166  
167 167 # Retrieve observation and check content of copy
168 168 self._test_observation(cpy_sim)
169   - self._test_list(cpy_sim.obs()[0].events(), 250)
  169 + self._test_list(cpy_sim.obs()[0].events(), 251)
170 170  
171 171 # Execute copy of ctobssim tool again, now with a higher chatter
172 172 # level than before
... ... @@ -179,7 +179,7 @@ class Test(test):
179 179  
180 180 # Load counts cube and check content.
181 181 evt = gammalib.GCTAEventList('ctobssim_py2.fits')
182   - self._test_list(evt, 250)
  182 + self._test_list(evt, 251)
183 183  
184 184 # Set-up observation container
185 185 pnts = [{'ra': 83.63, 'dec': 21.01},
... ... @@ -206,8 +206,8 @@ class Test(test):
206 206  
207 207 # Retrieve observation and check content
208 208 self._test_observation(sim, nobs=2, pnts=pnts)
209   - self._test_list(sim.obs()[0].events(), 3565)
210   - self._test_list(sim.obs()[1].events(), 3523)
  209 + self._test_list(sim.obs()[0].events(), 3626)
  210 + self._test_list(sim.obs()[1].events(), 3601)
211 211  
212 212 # Save events
213 213 sim.save()
... ... @@ -216,8 +216,8 @@ class Test(test):
216 216 obs = gammalib.GObservations('ctobssim_py3.xml')
217 217  
218 218 # Retrieve observation and check content
219   - self._test_list(obs[0].events(), 3565)
220   - self._test_list(obs[1].events(), 3523)
  219 + self._test_list(obs[0].events(), 3626)
  220 + self._test_list(obs[1].events(), 3601)
221 221  
222 222 # Return
223 223 return
... ...
test/test_obsutils.py
  View file @c1981f9
... ... @@ -217,7 +217,7 @@ class Test(test):
217 217 # Check simulation results
218 218 self.test_value(res.size(), 1, 'Check number of observations')
219 219 self.test_value(res.models().size(), 2, 'Check number of models')
220   - self.test_value(res.nobserved(), 19, 'Check number of observed events')
  220 + self.test_value(res.nobserved(), 20, 'Check number of observed events')
221 221 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
222 222 self.test_value(res[0].eventtype(), 'CountsCube', 'Check event type')
223 223 self.test_value(res[0].events().ebounds().emin().TeV(), 1.0,
... ... @@ -226,7 +226,7 @@ class Test(test):
226 226 'Check maximum energy')
227 227 self.test_value(res[0].events().ebounds().size(), 5,
228 228 'Check number of energy bins')
229   - self.test_value(res[0].events().number(), 19,
  229 + self.test_value(res[0].events().number(), 20,
230 230 'Check number of events in cube')
231 231  
232 232 # Check energy dispersion flag
... ... @@ -261,7 +261,7 @@ class Test(test):
261 261 # Check simulation results
262 262 self.test_value(res.size(), 2, 'Check number of observations')
263 263 self.test_value(res.models().size(), 2, 'Check number of models')
264   - self.test_value(res.nobserved(), 46, 'Check number of observed events')
  264 + self.test_value(res.nobserved(), 48, 'Check number of observed events')
265 265 self.test_value(res.npred(), 0.0, 'Check number of predicted events')
266 266  
267 267 # Check results of first observation
... ... @@ -271,7 +271,7 @@ class Test(test):
271 271 'Check maximum energy of On spectrum')
272 272 self.test_value(res[0].on_spec().ebounds().size(), 5,
273 273 'Check number of energy bins of On spectrum')
274   - self.test_value(res[0].on_spec().counts(), 24,
  274 + self.test_value(res[0].on_spec().counts(), 26,
275 275 'Check number of events in of On spectrum')
276 276 self.test_value(res[0].off_spec().ebounds().emin().TeV(), 1.0,
277 277 'Check minimum energy of Off spectrum')
... ... @@ -315,7 +315,7 @@ class Test(test):
315 315 'Check maximum energy of Off spectrum')
316 316 self.test_value(res[1].off_spec().ebounds().size(), 5,
317 317 'Check number of energy bins of Off spectrum')
318   - self.test_value(res[1].off_spec().counts(), 0,
  318 + self.test_value(res[1].off_spec().counts(), 1,
319 319 'Check number of events in of Off spectrum')
320 320 self.test_value(res[1].arf().ebounds().emin().TeV(), 0.5,
321 321 'Check minimum energy of ARF')
... ...