Correct start time in CTA analysis benchmark.

The start time tstart was reused for the computation of the start time of the function execution, leading to invalid time intervals in the ctobssim step.

Correct start time in CTA analysis benchmark.
The start time tstart was reused for the computation of the start time of the function execution, leading to invalid time intervals in the ctobssim step.
Jürgen Knödlseder
1 parent 4380d4e2
Showing 1 changed file with 34 additions and 33 deletions
examples/benchmark_cta_analysis.py
@@ -32,12 +32,11 @@ except:
 # ========================== #
 # Unbinned analysis pipeline #
 # ========================== #
-def unbinned_pipeline(duration):
+def unbinned_pipeline(model_name, duration):
     """
     Unbinned analysis pipeline.
     """
     # Set script parameters
-    model_name  = "${CTOOLS}/share/models/crab.xml"
     caldb       = "prod2"
     irf         = "South_50h"
     ra          =   83.63
@@ -50,7 +49,7 @@ def unbinned_pipeline(duration):
     rad_select  =    3.0
     # Get start CPU time
-    tstart = time.clock()
+    cpu_start = time.clock()
     # Simulate events
     sim = ctools.ctobssim()
@@ -78,30 +77,29 @@ def unbinned_pipeline(duration):
     select.run()
     # Get ctlike start CPU time
-    tctlike = time.clock()
+    cpu_ctlike = time.clock()
     # Perform maximum likelihood fitting
     like = ctools.ctlike(select.obs())
     like.run()
-    # Get stop CPU time
-    tstop    = time.clock()
-    telapsed = tstop - tstart
-    tctlike  = tstop - tctlike
+    # Get stop CPU time and compute elapsed times
+    cpu_stop    = time.clock()
+    cpu_elapsed = cpu_stop - cpu_start
+    cpu_ctlike  = cpu_stop - cpu_ctlike
     # Return
-    return telapsed, tctlike
+    return cpu_elapsed, cpu_ctlike
 # ======================== #
 # Binned analysis pipeline #
 # ======================== #
-def binned_pipeline(duration):
+def binned_pipeline(model_name, duration):
     """
     Binned analysis pipeline.
     """
     # Set script parameters
-    model_name  = "${CTOOLS}/share/models/crab.xml"
     caldb       = "prod2"
     irf         = "South_50h"
     ra          =   83.63
@@ -119,7 +117,7 @@ def binned_pipeline(duration):
     proj        = "CAR"
     # Get start CPU time
-    tstart = time.clock()
+    cpu_start = time.clock()
     # Simulate events
     sim = ctools.ctobssim()
@@ -151,30 +149,29 @@ def binned_pipeline(duration):
     bin.run()
     # Get ctlike start CPU time
-    tctlike = time.clock()
+    cpu_ctlike = time.clock()
     # Perform maximum likelihood fitting
     like = ctools.ctlike(bin.obs())
     like.run()
-    # Get stop CPU time
-    tstop    = time.clock()
-    telapsed = tstop - tstart
-    tctlike  = tstop - tctlike
+    # Get stop CPU time and compute elapsed times
+    cpu_stop    = time.clock()
+    cpu_elapsed = cpu_stop - cpu_start
+    cpu_ctlike  = cpu_stop - cpu_ctlike
     # Return
-    return telapsed, tctlike
+    return cpu_elapsed, cpu_ctlike
 # ========================= #
 # Stacked analysis pipeline #
 # ========================= #
-def stacked_pipeline(duration):
+def stacked_pipeline(model_name, duration):
     """
     Stacked analysis pipeline.
     """
     # Set script parameters
-    model_name  = "${CTOOLS}/share/models/crab.xml"
     caldb       = "prod2"
     irf         = "South_50h"
     ra          =   83.63
@@ -192,7 +189,7 @@ def stacked_pipeline(duration):
     proj        = "CAR"
     # Get start CPU time
-    tstart = time.clock()
+    cpu_start = time.clock()
     # Simulate events
     sim = ctools.ctobssim()
@@ -283,19 +280,19 @@ def stacked_pipeline(duration):
     bin.obs()[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
     # Get ctlike start CPU time
-    tctlike = time.clock()
+    cpu_ctlike = time.clock()
     # Perform maximum likelihood fitting
     like = ctools.ctlike(bin.obs())
     like.run()
-    # Get stop CPU time
-    tstop    = time.clock()
-    telapsed = tstop - tstart
-    tctlike  = tstop - tctlike
+    # Get stop CPU time and compute elapsed times
+    cpu_stop    = time.clock()
+    cpu_elapsed = cpu_stop - cpu_start
+    cpu_ctlike  = cpu_stop - cpu_ctlike
     # Return
-    return telapsed, tctlike
+    return cpu_elapsed, cpu_ctlike
 #==========================#
@@ -304,7 +301,11 @@ def stacked_pipeline(duration):
 if __name__ == '__main__':
     """
     """
-    # Dump header
+    # Initialise parameters
+    title      = "CTA analysis benchmark"
+    model_name = "${CTOOLS}/share/models/crab.xml"
+
+    # Log header
     print("*************************************")
     print("*      CTA analysis benchmark       *")
     print("*************************************")
@@ -324,9 +325,9 @@ if __name__ == &#39;__main__&#39;:
     for i in range(10):
         # Perform analyses
-        t_unbinned, ct_unbinned = unbinned_pipeline(duration)
-        t_binned,   ct_binned   = binned_pipeline(duration)
-        t_stacked,  ct_stacked  = stacked_pipeline(duration)
+        t_unbinned, ct_unbinned = unbinned_pipeline(model_name, duration)
+        t_binned,   ct_binned   = binned_pipeline(model_name, duration)
+        t_stacked,  ct_stacked  = stacked_pipeline(model_name, duration)
         # Collect results
         a_duration.append(duration/3600.0)
@@ -348,14 +349,14 @@ if __name__ == &#39;__main__&#39;:
     # Optionally plot results
     if has_matplotlib:
         plt.figure(1)
-        plt.title("CTA analysis benchmark")
+        plt.title(title)
         plt.loglog(a_duration, a_unbinned, 'ro-', label='unbinned')
         plt.loglog(a_duration, a_binned, 'bo-', label='binned')
         plt.loglog(a_duration, a_stacked, 'go-', label='stacked')
         plt.loglog(a_duration, c_unbinned, 'ro--')
         plt.loglog(a_duration, c_binned, 'bo--')
         plt.loglog(a_duration, c_stacked, 'go--')
-        plt.xlabel("Duration (hours)")
+        plt.xlabel("Observation duration (hours)")
         plt.ylabel("CPU time (seconds)")
         plt.legend(loc="lower right")
         plt.show()