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inst/cta/test/README.md
inst/cta/test/dev/README.md
test/README
test/README.md
test/test_python.py
@@ -3,19 +3,20 @@ CTA module unit tests
 This folder contains scripts and executables that are used for CTA
 module unit testing.
  
-benchmark_irf_computing.py
-  This script performs a benchmark of the response computation for all
-  different analysis methods (unbinned, binned, stacked). Specifically it
-  compares the total number of modelled counts to the expected number from
-  Monte-Carlo simulations. This script is used to validate the absolute
-  normalization of the CTA response computations.
+`benchmark_irf_computing.py`
  
-benchmark_ml_fitting.py
-  This script performs a benchmark for maximum likelihood fitting of CTA
-  data.
+>  This script performs a benchmark of the response computation for all
+>  different analysis methods (unbinned, binned, stacked). Specifically it
+>  compares the total number of modelled counts to the expected number from
+>  Monte-Carlo simulations. This script is used to validate the absolute
+>  normalization of the CTA response computations.
  
-test_CTA.cpp
-  Unit test C++ file for CTA specific GammaLib components.
+`benchmark_ml_fitting.py`
+>  This script performs a benchmark for maximum likelihood fitting of CTA
+>  data.
  
-test_CTA.py
-  Unit test Python script for CTA specific GammaLib components.
+`test_CTA.cpp`
+>  Unit test C++ file for CTA specific GammaLib components.
+
+`test_CTA.py`
+>  Unit test Python script for CTA specific GammaLib components.
@@ -5,51 +5,51 @@ during code development. None of the scripts actually needs to work, they
 may actually be outdated, but could still be useful for further testing
 if needed.
  
-example_binned_ml_fit.py
-  Illustrates a binned maximum likelihood fit of CTA data.
-  This script implements a full analysis chain, and computes
-  also the TS statistics value that estimates the significance
-  of the source detection.
+`example_binned_ml_fit.py`
+>  Illustrates a binned maximum likelihood fit of CTA data.
+>  This script implements a full analysis chain, and computes
+>  also the TS statistics value that estimates the significance
+>  of the source detection.
  
-example_make_model.py
-  Illustrates how to make a model in counts space for a counts
-  map given a specific model in XML format.
+`example_make_model.py`
+>  Illustrates how to make a model in counts space for a counts
+>  map given a specific model in XML format.
  
-example_sim_photons.py
-  Illustrates how photons are simulated from a source model. If
-  matplotlib is installed, the simulated photons are shown as
-  a spectrum.
+`example_sim_photons.py`
+>  Illustrates how photons are simulated from a source model. If
+>  matplotlib is installed, the simulated photons are shown as
+>  a spectrum.
  
-test_gauss.py
-  Test Gaussian.
+`test_gauss.py`
+>  Test Gaussian.
  
-test_irf_offset.py
-  Creates images of source models for various offset angles. This
-  tests the IRF variation with offset angle.
+`test_irf_offset.py`
+>  Creates images of source models for various offset angles. This
+>  tests the IRF variation with offset angle.
  
-test_irf_trafo.py
-  Test coordinate transformations for IRF computation.
+`test_irf_trafo.py`
+>  Test coordinate transformations for IRF computation.
  
-test_model.py
-  Creates images of sources models convolved with the CTA instrument
-  response function. Also allows the creation of gradient images.
+`test_model.py`
+>  Creates images of sources models convolved with the CTA instrument
+>  response function. Also allows the creation of gradient images.
  
-test_npred_computation.py
-  Test the Npred computation of the CTA response.
+`test_npred_computation.py`
+>  Test the Npred computation of the CTA response.
  
-test_npred_integration.py
-  Compare numerical to analytical Npred computation for CTA response.
+`test_npred_integration.py`
+>  Compare numerical to analytical Npred computation for CTA response.
  
-test_radial_acceptance.py
-  Displays the various radial acceptance models.
+`test_radial_acceptance.py`
+>  Displays the various radial acceptance models.
  
-test_response_table.py
-  Display CTA response table.
+`test_response_table.py`
+>  Display CTA response table.
  
-test_sim_edisp.py
-  Compares energy dispersion simulation to energy dispersion
-  model.
+`test_sim_edisp.py`
+>  Compares energy dispersion simulation to energy dispersion
+>  model.
  
-test_sim_psf.py
-  Compares Point Spread function simulation to Point Spread function
-  model.
+`test_sim_psf.py`
+>  Compares Point Spread function simulation to Point Spread function
+>  model.
-This folder contains files used for GammaLib unit testing. More unit tests files can be found in the instrument specific test folders inst/xxx/test.
+GammaLib unit tests
+===================
+
+This folder contains files used for GammaLib unit testing. More unit tests are
+located in the instrument specific test folders inst/<INSTRUMENT>/test.
@@ -73,7 +73,7 @@ def test(installed=False):
     Perform unit testing for Python interface.
     """
     # Allocate test suites
-    suites = gammalib.GTestSuites("Python interface testing")
+    suites = gammalib.GTestSuites('Python interface testing')
  
     # Allocate test suites and append them to the container
     suite1  = test_GApplication.Test()
@@ -131,7 +131,7 @@ def test(installed=False):
         suite_cta = test_CTA.Test()
         suite_cta.set()
         if installed:
-            suite_cta.caldb_path("cta/caldb")
+            suite_cta.caldb_path('cta/caldb')
         suites.append(suite_cta)
  
     # Optionally handle LAT suite
@@ -161,43 +161,43 @@ def test(installed=False):
         head, tail = os.path.split(testdir)
  
         # Copy over test data
-        os.system("cp -r %s %s" % (head+"/data", "data"))
-        os.system("cp -r %s %s" % (head+"/cta",  "cta"))
+        os.system('cp -r %s %s' % (head+'/data', 'data'))
+        os.system('cp -r %s %s' % (head+'/cta',  'cta'))
  
         # Special post processing for CTA files. This is needed because
         # the XML files contain absolute PATH information. This is a kluge
         # that works for now, but it's not a very maintainable way to
         # handle this
         if has_cta:
-            xml = gammalib.GXml("cta/data/irf_unbinned.xml")
-            elements = xml.element("observation_list").element("observation")
+            xml = gammalib.GXml('cta/data/irf_unbinned.xml')
+            elements = xml.element('observation_list').element('observation')
             for element in elements:
-                filename   = element.attribute("file")
+                filename   = element.attribute('file')
                 head, tail = os.path.split(filename)
                 head, dir  = os.path.split(head)
                 if len(dir) > 0:
-                    filename   = "cta/"+dir+"/"+tail
-                element.attribute("file", filename)
-            xml.save("cta/data/irf_unbinned.xml")
-            xml = gammalib.GXml("cta/data/irf_1dc.xml")
-            elements = xml.element("observation_list").element("observation")
+                    filename   = 'cta/'+dir+'/'+tail
+                element.attribute('file', filename)
+            xml.save('cta/data/irf_unbinned.xml')
+            xml = gammalib.GXml('cta/data/irf_1dc.xml')
+            elements = xml.element('observation_list').element('observation')
             for element in elements:
-                filename   = element.attribute("file")
+                filename   = element.attribute('file')
                 head, tail = os.path.split(filename)
                 head, dir  = os.path.split(head)
-                if dir == "dc1":
-                    dir = "caldb/dc1"
+                if dir == 'dc1':
+                    dir = 'caldb/dc1'
                 if len(dir) > 0:
-                    filename = "cta/"+dir+"/"+tail
-                element.attribute("file", filename)
-            xml.save("cta/data/irf_1dc.xml")
+                    filename = 'cta/'+dir+'/'+tail
+                element.attribute('file', filename)
+            xml.save('cta/data/irf_1dc.xml')
  
     # Run test suite
     success = suites.run()
  
     # If we have a non-installed version then save test results
     if not installed:
-        suites.save("reports/python.xml")
+        suites.save('reports/python.xml')
  
     # Set return code
     if success:
@@ -213,8 +213,6 @@ def test(installed=False):
 # Main routine entry point #
 # ======================== #
 if __name__ == '__main__':
-    """
-    Perform unit testing for Python interface.
-    """
+
     # Run tests
     test()