Simon Bonnefoy / ctools

Commit b6c16ddee3641886a7dae84bf6640d0ae665b67b

Authored by Jürgen Knödlseder
2 parents 0b0c715d da850b0a

Merge branch '1555-science-verification' into integration

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Showing 9 changed files with 166 additions and 19 deletions
doc/source/user_manual/getting_started/models.rst
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... ... @@ -216,6 +216,21 @@ Elliptical source
216 216 </spectrum>
217 217 </source>
218 218  
  219 + .. code-block:: xml
  220 +
  221 + <source name="Crab" type="ExtendedSource">
  222 + <spatialModel type="EllipticalGauss">
  223 + <parameter name="RA" scale="1.0" value="83.6331" min="-360" max="360" free="1"/>
  224 + <parameter name="DEC" scale="1.0" value="22.0145" min="-90" max="90" free="1"/>
  225 + <parameter name="PA" scale="1.0" value="45.0" min="-360" max="360" free="1"/>
  226 + <parameter name="MinorRadius" scale="1.0" value="0.5" min="0.001" max="10" free="1"/>
  227 + <parameter name="MajorRadius" scale="1.0" value="2.0" min="0.001" max="10" free="1"/>
  228 + </spatialModel>
  229 + <spectrum type="...">
  230 + ...
  231 + </spectrum>
  232 + </source>
  233 +
219 234  
220 235 Diffuse source
221 236 ^^^^^^^^^^^^^^
... ...
test/data/sciver/cena_lobes_parkes.fits deleted
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test/data/sciver/cena_lobes_parkes.fits.gz 0 → 100644
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test/data/sciver/crab_const.xml 0 → 100644
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  1 +<?xml version="1.0" standalone="no"?>
  2 +<source_library title="source library">
  3 + <source name="Crab" type="DiffuseSource">
  4 + <spectrum type="PowerLaw">
  5 + <parameter name="Prefactor" scale="1e-12" value="2.0" min="1e-07" max="1000.0" free="1"/>
  6 + <parameter name="Index" scale="-1" value="2.48" min="0.0" max="+5.0" free="1"/>
  7 + <parameter name="Scale" scale="1e6" value="0.3" min="0.01" max="1000.0" free="0"/>
  8 + </spectrum>
  9 + <spatialModel type="ConstantValue">
  10 + <parameter name="Value" scale="1" value="1" min="0.1" max="10" free="0"/>
  11 + </spatialModel>
  12 + </source>
  13 + <source name="Background" type="CTAIrfBackground" instrument="CTA">
  14 + <spectrum type="PowerLaw">
  15 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e3" free="1"/>
  16 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  17 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  18 + </spectrum>
  19 + </source>
  20 +</source_library>
... ...
test/data/sciver/crab_cube.fits.gz 0 → 100644
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test/data/sciver/crab_cube.xml 0 → 100644
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  1 +<?xml version="1.0" standalone="no"?>
  2 +<source_library title="source library">
  3 + <source name="Crab" type="DiffuseSource">
  4 + <spectrum type="PowerLaw">
  5 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-07" max="1000.0" free="1"/>
  6 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  7 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  8 + </spectrum>
  9 + <spatialModel type="MapCubeFunction" file="data/sciver/crab_cube.fits">
  10 + <parameter name="Normalization" scale="1" value="1" min="0.1" max="10" free="0"/>
  11 + </spatialModel>
  12 + </source>
  13 + <source name="Background" type="CTAIrfBackground" instrument="CTA">
  14 + <spectrum type="PowerLaw">
  15 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e3" free="1"/>
  16 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  17 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  18 + </spectrum>
  19 + </source>
  20 +</source_library>
... ...
test/data/sciver/crab_map_nn.xml 0 → 100644
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  1 +<?xml version="1.0" standalone="no"?>
  2 +<source_library title="source library">
  3 + <source name="Crab" type="DiffuseSource">
  4 + <spectrum type="PowerLaw">
  5 + <parameter name="Prefactor" scale="1e-16" value="5.7" min="1e-07" max="1000.0" free="1"/>
  6 + <parameter name="Index" scale="-1" value="2.48" min="0.0" max="+5.0" free="1"/>
  7 + <parameter name="Scale" scale="1e6" value="0.3" min="0.01" max="1000.0" free="0"/>
  8 + </spectrum>
  9 + <spatialModel type="SpatialMap" file="data/sciver/cena_lobes_parkes.fits" normalize="0">
  10 + <parameter scale="1" name="Prefactor" min="0.001" max="1000.0" value="3" free="0"/>
  11 + </spatialModel>
  12 + </source>
  13 + <source name="Background" type="CTAIrfBackground" instrument="CTA">
  14 + <spectrum type="PowerLaw">
  15 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e3" free="1"/>
  16 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  17 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  18 + </spectrum>
  19 + </source>
  20 +</source_library>
... ...
test/data/sciver/crab_map_roi.xml 0 → 100644
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  1 +<?xml version="1.0" standalone="no"?>
  2 +<source_library title="source library">
  3 + <source name="Crab" type="DiffuseSource">
  4 + <spectrum type="PowerLaw">
  5 + <parameter name="Prefactor" scale="1e-16" value="5.7" min="1e-07" max="1000.0" free="1"/>
  6 + <parameter name="Index" scale="-1" value="2.48" min="0.0" max="+5.0" free="1"/>
  7 + <parameter name="Scale" scale="1e6" value="0.3" min="0.01" max="1000.0" free="0"/>
  8 + </spectrum>
  9 + <spatialModel type="SpatialMap" file="data/sciver/cena_lobes_parkes.fits">
  10 + <parameter scale="1" name="Prefactor" min="0.001" max="1000.0" value="1" free="0"/>
  11 + </spatialModel>
  12 + </source>
  13 + <source name="Background" type="CTAIrfBackground" instrument="CTA">
  14 + <spectrum type="PowerLaw">
  15 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e3" free="1"/>
  16 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  17 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  18 + </spectrum>
  19 + </source>
  20 +</source_library>
... ...
test/science_verification.py
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1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3 3 # This script performs the ctools science verification. It creates and
4   -# analyses the pull distributions for a variety of model in unbinned
  4 +# analyses the pull distributions for a variety of models in unbinned
5 5 # analysis mode. At the end the script produces a JUnit compliant
6 6 # science verification report.
7 7 #
... ... @@ -191,31 +191,35 @@ class sciver(gammalib.GPythonTestSuite):
191 191 self.append(self.spec_nodes, "Test nodes model")
192 192  
193 193 # Append spatial tests
194   - self.append(self.spec_ptsrc, "Test point source model")
195   - self.append(self.spec_rdisk, "Test radial disk model")
196   - self.append(self.spec_rgauss, "Test radial Gaussian model")
197   - self.append(self.spec_rshell, "Test radial shell model")
198   - self.append(self.spec_edisk, "Test elliptical disk model")
199   - self.append(self.spec_egauss, "Test elliptical Gaussian model")
200   - self.append(self.spec_map, "Test elliptical Gaussian model")
  194 + self.append(self.spat_ptsrc, "Test point source model")
  195 + self.append(self.spat_rdisk, "Test radial disk model")
  196 + self.append(self.spat_rgauss, "Test radial Gaussian model")
  197 + self.append(self.spat_rshell, "Test radial shell model")
  198 + self.append(self.spat_edisk, "Test elliptical disk model")
  199 + self.append(self.spat_egauss, "Test elliptical Gaussian model")
  200 + self.append(self.spat_const, "Test diffuse isotropic model")
  201 + self.append(self.spat_map, "Test diffuse map model")
  202 + self.append(self.spat_map_roi, "Test diffuse map model (small ROI)")
  203 + self.append(self.spat_map_nn, "Test diffuse map model (not normalized and scaled)")
  204 + self.append(self.spat_cube, "Test diffuse cube model")
201 205  
202 206 # Return
203 207 return
204 208  
205 209 # Generate and analyse pull distributions
206   - def pull(self, model, trials=100):
  210 + def pull(self, model, trials=100, ra=83.63, dec=22.01, rad=5.0):
207 211 """
208 212 Generate and analyse pull distributions.
209 213 """
210 214 # Generate pull distribution
211   - outfile = generate_pull_distribution(model, trials=trials)
  215 + outfile = generate_pull_distribution(model, trials=trials,
  216 + ra=ra, dec=dec, rad=rad)
212 217  
213 218 # Analyse pull distribution
214 219 self.results = analyse_pull_distribution(outfile)
215 220  
216 221 # Return
217 222 return
218   -
219 223  
220 224 # Test parameter result
221 225 def test(self, name):
... ... @@ -340,7 +344,7 @@ class sciver(gammalib.GPythonTestSuite):
340 344 return
341 345  
342 346 # Test point source model
343   - def spec_ptsrc(self):
  347 + def spat_ptsrc(self):
344 348 """
345 349 Test point source model.
346 350 """
... ... @@ -354,7 +358,7 @@ class sciver(gammalib.GPythonTestSuite):
354 358 return
355 359  
356 360 # Test radial disk model
357   - def spec_rdisk(self):
  361 + def spat_rdisk(self):
358 362 """
359 363 Test radial disk model.
360 364 """
... ... @@ -369,7 +373,7 @@ class sciver(gammalib.GPythonTestSuite):
369 373 return
370 374  
371 375 # Test radial Gaussian model
372   - def spec_rgauss(self):
  376 + def spat_rgauss(self):
373 377 """
374 378 Test radial Gaussian model.
375 379 """
... ... @@ -384,7 +388,7 @@ class sciver(gammalib.GPythonTestSuite):
384 388 return
385 389  
386 390 # Test radial shell model
387   - def spec_rshell(self):
  391 + def spat_rshell(self):
388 392 """
389 393 Test radial shell model.
390 394 """
... ... @@ -400,7 +404,7 @@ class sciver(gammalib.GPythonTestSuite):
400 404 return
401 405  
402 406 # Test elliptical disk model
403   - def spec_edisk(self):
  407 + def spat_edisk(self):
404 408 """
405 409 Test elliptical disk model.
406 410 """
... ... @@ -417,7 +421,7 @@ class sciver(gammalib.GPythonTestSuite):
417 421 return
418 422  
419 423 # Test elliptical Gaussian model
420   - def spec_egauss(self):
  424 + def spat_egauss(self):
421 425 """
422 426 Test elliptical Gaussian model.
423 427 """
... ... @@ -433,12 +437,60 @@ class sciver(gammalib.GPythonTestSuite):
433 437 self.test("Pull_Background_Index")
434 438 return
435 439  
  440 + # Test diffuse isotropic model
  441 + def spat_const(self):
  442 + """
  443 + Test diffuse isotropic model.
  444 + """
  445 + self.pull("data/sciver/crab_const")
  446 + self.test("Pull_Crab_Prefactor")
  447 + self.test("Pull_Crab_Index")
  448 + self.test("Pull_Background_Prefactor")
  449 + self.test("Pull_Background_Index")
  450 + return
  451 +
436 452 # Test diffuse map model
437   - def spec_map(self):
  453 + def spat_map(self):
438 454 """
439 455 Test diffuse map model.
440 456 """
441   - self.pull("data/sciver/crab_map")
  457 + self.pull("data/sciver/crab_map", ra=201.3651, dec=-43.0191)
  458 + self.test("Pull_Crab_Prefactor")
  459 + self.test("Pull_Crab_Index")
  460 + self.test("Pull_Background_Prefactor")
  461 + self.test("Pull_Background_Index")
  462 + return
  463 +
  464 + # Test diffuse map model (small ROI)
  465 + def spat_map_roi(self):
  466 + """
  467 + Test diffuse map model (small ROI).
  468 + """
  469 + self.pull("data/sciver/crab_map_roi", ra=201.3651, dec=-43.0191, rad=1.5)
  470 + self.test("Pull_Crab_Prefactor")
  471 + self.test("Pull_Crab_Index")
  472 + self.test("Pull_Background_Prefactor")
  473 + self.test("Pull_Background_Index")
  474 + return
  475 +
  476 + # Test diffuse map model (not normalized and scaled)
  477 + def spat_map_nn(self):
  478 + """
  479 + Test diffuse map model (not normalized and scaled).
  480 + """
  481 + self.pull("data/sciver/crab_map_nn", ra=201.3651, dec=-43.0191, rad=1.5)
  482 + self.test("Pull_Crab_Prefactor")
  483 + self.test("Pull_Crab_Index")
  484 + self.test("Pull_Background_Prefactor")
  485 + self.test("Pull_Background_Index")
  486 + return
  487 +
  488 + # Test diffuse cube model
  489 + def spat_cube(self):
  490 + """
  491 + Test diffuse cube model.
  492 + """
  493 + self.pull("data/sciver/crab_cube")
442 494 self.test("Pull_Crab_Prefactor")
443 495 self.test("Pull_Crab_Index")
444 496 self.test("Pull_Background_Prefactor")
... ...