Changes between Version 8 and Version 9 of HowToUseNUISCOMP-GENIE

Timestamp:

Jun 12, 2017, 6:52:24 PM (7 years ago)

Author:

Patrick Stowell

Comment:

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HowToUseNUISCOMP-GENIE

@@ -300 +300 @@
 [[Image(screenshot_2.png​, 600px)]]
 
-We can also directly compare the MC and data histograms, by drawing the data with the option 'E1' then drawing the MC histogram with the option "HIST SAME".
+We can also directly compare the MC and data histograms, by drawing the data with the option 'E1' then drawing the MC histogram with the option "same hist".
 
 [[Image(screenshot_1.png​, 600px)]]
+
+- ** MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_FINE ** : A finer binned version of the MC histogram that can be used to make smoother more detailed curves for comparison.
+
+[[Image(screenshot.png​, 600px)]]
+
+- **  MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_SHAPE ** : A histogram with the same binning as the MC histogram, but this time the MC prediction has been normalised to match the total cross-section of the data. Useful for comparing the shape of the MC to the data whilst neglecting normalisation differences.
+
+[[Image(screenshot.png​, 600px)]]
+
+- ** MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO ** : A copy of the MC histogram that has been divided by the MC histogram. This should return a flat histogram with each bin content equal to 1.0, and is used to set the unity line in a data/MC ratio histogram.
+
+- ** MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO ** : A copy of the data histogram that has been divided by the MC histogram. This is provided to make it easier to make data/MC comparisons by combining it with MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO.
+
+[[Image(screenshot_8.png​, 600px)]]
 
 == Providing reweight parameters ==
@@ -415 +429 @@
 
 
-