From 7057753bac22df03d32a410a30bc6fe176627085 Mon Sep 17 00:00:00 2001 From: Jürgen Knödlseder Date: Fri, 7 Apr 2017 00:19:52 +0200 Subject: [PATCH] Change names of effective area ROOT histograms in csroot2caldb.py --- ChangeLog | 3 ++- NEWS | 7 ++++++- cscripts/csroot2caldb.py | 4 ++-- 3 files changed, 10 insertions(+), 4 deletions(-) diff --git a/ChangeLog b/ChangeLog index 26d0fb4..0321ded 100644 --- a/ChangeLog +++ b/ChangeLog @@ -1,8 +1,9 @@ -2017-04-05 +2017-04-06 * Version 1.3.0 released ======================== + Use correct ROOT histograms in csroot2caldb Implement regression scheme in cssens and remove num_avg parameter (#1989) Copy cscripts into bin directory instead of creating a symbolic links (#1987) If code originates from Git, always compile the Python bindings (#1985) diff --git a/NEWS b/NEWS index 649abee..ee050fe 100644 --- a/NEWS +++ b/NEWS @@ -1,6 +1,6 @@ New Features and Important Changes in ctools 1.3.0.dev1 -5 April 2017 +6 April 2017 Introduction @@ -137,6 +137,11 @@ A regression scheme now replaces the averaging scheme in cssens as this allows more accurately the prediction of the flux value at the threshold Test Statistic. The num_avg parameter has been removed (#1989). +The names of some ROOT histograms has been changed in the Monte Carlo data +and the "EffectiveAreaEtrue_offaxis" needed to be changed to +"EffectiveAreaEtrueNoTheta2cut_offaxis" and "EffectiveAreaEtrue" to +"EffectiveAreaEtrueNoTheta2cut" in csroot2caldb. + Examples -------- diff --git a/cscripts/csroot2caldb.py b/cscripts/csroot2caldb.py index 1a36e74..b89d770 100755 --- a/cscripts/csroot2caldb.py +++ b/cscripts/csroot2caldb.py @@ -551,13 +551,13 @@ class csroot2caldb(ctools.cscript): self._log_header1(gammalib.TERSE, 'Generate effective area extension') # Get relevant ROOT histograms - etrue = tfile.Get('EffectiveAreaEtrue_offaxis') + etrue = tfile.Get('EffectiveAreaEtrueNoTheta2cut_offaxis') # If requested then normalize the 2D histogram on the on-axis 1D # histogram. This assures that the 2D histogram has the same on-axis # effective area dependence as the 1D histogram. if self['norm1d'].boolean(): - etrue_1D = tfile.Get('EffectiveAreaEtrue') + etrue_1D = tfile.Get('EffectiveAreaEtrueNoTheta2cut') self._renorm_onaxis(etrue, etrue_1D) # If requested then rebin the effective area Etrue histogram. This -- libgit2 0.21.4