Add model for not-normalized and scaled map. Test all diffuse models.

Jürgen Knödlseder
1 parent 6593baf2
Showing 2 changed files with 48 additions and 2 deletions
test/data/sciver/crab_map_nn.xml
test/science_verification.py
+<?xml version="1.0" standalone="no"?>
+<source_library title="source library">
+  <source name="Crab" type="DiffuseSource">
+    <spectrum type="PowerLaw">
+      <parameter name="Prefactor" scale="1e-16" value="5.7"  min="1e-07" max="1000.0" free="1"/>
+      <parameter name="Index"     scale="-1"    value="2.48" min="0.0"   max="+5.0"   free="1"/>
+      <parameter name="Scale"     scale="1e6"   value="0.3"  min="0.01"  max="1000.0" free="0"/>
+    </spectrum>
+    <spatialModel type="SpatialMap" file="data/sciver/cena_lobes_parkes.fits" normalize="0">
+      <parameter scale="1" name="Prefactor" min="0.001" max="1000.0" value="3" free="0"/>
+    </spatialModel>
+  </source>
+  <source name="Background" type="CTAIrfBackground" instrument="CTA">
+    <spectrum type="PowerLaw">
+      <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e3"    free="1"/>
+      <parameter name="Index"     scale="1.0" value="0.0" min="-5.0" max="+5.0"   free="1"/>
+      <parameter name="Scale"     scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
+    </spectrum>
+  </source>
+</source_library>
@@ -199,19 +199,21 @@ class sciver(gammalib.GPythonTestSuite):
         #self.append(self.spat_egauss, "Test elliptical Gaussian model")
         self.append(self.spat_const, "Test diffuse isotropic model")
         self.append(self.spat_map, "Test diffuse map model")
+        self.append(self.spat_map_roi, "Test diffuse map model (small ROI)")
+        self.append(self.spat_map_nn, "Test diffuse map model (not normalized and scaled)")
         self.append(self.spat_cube, "Test diffuse cube model")
         # Return
         return
     # Generate and analyse pull distributions
-    def pull(self, model, trials=100, ra=83.63, dec=22.01):
+    def pull(self, model, trials=100, ra=83.63, dec=22.01, rad=5.0):
         """
         Generate and analyse pull distributions.
         """
         # Generate pull distribution
         outfile = generate_pull_distribution(model, trials=trials,
-                                             ra=ra, dec=dec)
+                                             ra=ra, dec=dec, rad=rad)
         # Analyse pull distribution
         self.results = analyse_pull_distribution(outfile)
@@ -460,6 +462,30 @@ class sciver(gammalib.GPythonTestSuite):
         self.test("Pull_Background_Index")
         return
+    # Test diffuse map model (small ROI)
+    def spat_map_roi(self):
+        """
+        Test diffuse map model (small ROI).
+        """
+        self.pull("data/sciver/crab_map_roi", ra=201.3651, dec=-43.0191, rad=1.5)
+        self.test("Pull_Crab_Prefactor")
+        self.test("Pull_Crab_Index")
+        self.test("Pull_Background_Prefactor")
+        self.test("Pull_Background_Index")
+        return
+
+    # Test diffuse map model (not normalized and scaled)
+    def spat_map_nn(self):
+        """
+        Test diffuse map model (not normalized and scaled).
+        """
+        self.pull("data/sciver/crab_map_nn", ra=201.3651, dec=-43.0191, rad=1.5)
+        self.test("Pull_Crab_Prefactor")
+        self.test("Pull_Crab_Index")
+        self.test("Pull_Background_Prefactor")
+        self.test("Pull_Background_Index")
+        return
+
     # Test diffuse cube model
     def spat_cube(self):
         """