Changes between Version 5 and Version 6 of HowToNuWro

Timestamp:

Nov 6, 2016, 10:35:55 AM (8 years ago)

Author:

Patrick Stowell

Comment:

--

HowToNuWro

@@ -35 +35 @@
 }}}
 
+The output file (specified with '-o') will be a ROOT file containing a series of useful histograms that compare the NuWro predictions to the MiniBooNE CCQE data.
+{{{
+$ root nuisance_comparison_nuwro_v12.root
+$ root[0]: _file0->ls();
+
+}}}
+
+'''MiniBooNE_CCQE_XSec_1DQ2_data:'''
+
+
+'''MiniBooNE_CCQE_XSec_1DQ2_MC:'''
+
+
+'''MiniBooNE_CCQE_XSec_1DQ2_MC_PDG:'''
+
+
+ 
 
 = Loading !NuWro <v12 events into NUISANCE =
@@ -83 +100 @@
 }}}
 
-A list of available dial strings can be found in "$NUWRO/src/reweight/NuWroSyst.h".
+A list of available dial strings can be found in "$NUWRO/src/reweight/NuWroSyst.h". Comparing the plots below with those shown earlier you can see the difference between the NuWro model predictions with MA = 0.0 and +1.0 sigma.
+
+'''MiniBooNE_CCQE_XSec_1DQ2_MC (reweighted):'''
+
+
 
 = Using !NuWro reweight for dial tuning =
 As for all other reweight engines any dial can be treated as a free parameter for dial tuning studies in nuismin. The following cardfile when used with nuismin will vary the CCQE and Resonant axial mass parameters until a best fit is found to the MiniBooNE CCQELike dataset.
  
+
+'''nuwro_reweighted_minimizer.card:'''
+{{{
+# par_type      dial_name    value
+###########################
+nuwro_parameter  MaCCQE  +1.0  -4.0  4.0  1.0  FREE   
+
+# sample   SAMPLE_ID    TYPE:INPUT_TYPE
+########################################
+sample    MiniBooNE_CCQE_XSec_1DQ2_nu    NUWRO:/path/to/nuwro/events.root
+}}}
+
+
+'''nuwro_reweighted_minimizer.card(without comments):'''
+{{{
+nuwro_parameter  MaCCQE  +1.0  -4.0  4.0  1.0  FREE   
+sample    MiniBooNE_CCQE_XSec_1DQ2_nu    NUWRO:/path/to/nuwro/events.root
+}}}
+
+
+This can be ran using the NUISANCE minimizer app "nuismin":
+{{{
+$ nuismin -c nuwro_reweighted_minimizer.card -o nuwro_minimizer_results.root
+}}}
+
+The contents of the nuismin outputfile will be the same as that in the comparison app, but with the predictions now shown for the best fit result. Also included are a series of histograms related to the tuning study (covariance, fit_results, etc)
+{{{
+$ root nuwro_minimizer_results.root
+$ root[0]: _file0->ls();
+}}}