Detailed Description

StandardHistFactoryPlotsWithCategories

This is a standard demo that can be used with any ROOT file prepared in the standard way. You specify:

name for input ROOT file
name of workspace inside ROOT file that holds model and data
name of ModelConfig that specifies details for calculator tools
name of dataset

With default parameters the macro will attempt to run the standard hist2workspace example and read the ROOT file that it produces.

The macro will scan through all the categories in a simPdf find the corresponding observable. For each category, it will loop through each of the nuisance parameters and plot

the data
the nominal model (blue)
the +Nsigma (red)
the -Nsigma (green)

You can specify how many sigma to vary by changing nSigmaToVary. You can also change the signal rate by changing muVal.

The script produces a lot plots, you can merge them by doing:

gs -q -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -sOutputFile=merged.pdf `ls *pdf`

pict1_StandardHistFactoryPlotsWithCategories.C.png

Processing /mnt/build/workspace/root-makedoc-v614/rootspi/rdoc/src/v6-14-00-patches/tutorials/roostats/StandardHistFactoryPlotsWithCategories.C...
[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby[0m 
                Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
                All rights reserved, please read http://roofit.sourceforge.net/license.txt
  1) 0x25a91e0 RooRealVar::               alpha_syst2 = 0  L(-5 - 5)  "alpha_syst2"
  2) 0x25b1420 RooRealVar::               alpha_syst3 = 0  L(-5 - 5)  "alpha_syst3"
  3) 0x25415d0 RooRealVar:: gamma_stat_channel1_bin_0 = 1  L(0 - 1.25)  "gamma_stat_channel1_bin_0"
  4) 0x255ce00 RooRealVar:: gamma_stat_channel1_bin_1 = 1  L(0 - 1.5)  "gamma_stat_channel1_bin_1"
 check expectedData by category
Is a simultaneous PDF
on type channel1 
channelCat==channelCat::channel1
channel1 channel1
[#1] INFO:Plotting -- RooTreeData::plotOn: plotting 234 events out of 234 total events
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
channelCat==channelCat::channel1
channel1 channel1
[#1] INFO:Plotting -- RooTreeData::plotOn: plotting 234 events out of 234 total events
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
channelCat==channelCat::channel1
channel1 channel1
[#1] INFO:Plotting -- RooTreeData::plotOn: plotting 234 events out of 234 total events
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
channelCat==channelCat::channel1
channel1 channel1
[#1] INFO:Plotting -- RooTreeData::plotOn: plotting 234 events out of 234 total events
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#0] ERROR:Eval -- RooAbsReal::logEvalError(channel1_model) evaluation error, 
 origin       : RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
 message      : p.d.f normalization integral is zero or negative
 server values: !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.25 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.75 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(channel1_model_Int[obs_x_channel1]) using numeric integrator RooBinIntegrator to calculate Int(obs_x_channel1)
[#0] ERROR:Eval -- RooAbsReal::logEvalError(channel1_model) evaluation error, 
 origin       : RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
 message      : p.d.f normalization integral is zero or negative
 server values: !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.25 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.5 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=1.75 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)
[#0] WARNING:Plotting -- At observable [x]=2 RooRealSumPdf::channel1_model[ binWidth_obs_x_channel1_0 * L_x_signal_channel1_overallSyst_x_Exp + binWidth_obs_x_channel1_1 * L_x_background1_channel1_overallSyst_x_StatUncert + binWidth_obs_x_channel1_2 * L_x_background2_channel1_overallSyst_x_StatUncert ]
     p.d.f normalization integral is zero or negative @ !funcList=(L_x_signal_channel1_overallSyst_x_Exp = 0,L_x_background1_channel1_overallSyst_x_StatUncert = 0,L_x_background2_channel1_overallSyst_x_StatUncert = 0), !coefList=(binWidth_obs_x_channel1_0 = 2,binWidth_obs_x_channel1_1 = 2,binWidth_obs_x_channel1_2 = 2)

#include "TFile.h"
#include "TROOT.h"
#include "TCanvas.h"
#include "TList.h"
#include "TMath.h"
#include "TSystem.h"
#include "RooWorkspace.h"
#include "RooAbsData.h"
#include "RooRealVar.h"
#include "RooPlot.h"
#include "RooSimultaneous.h"
#include "RooCategory.h"
#include "RooStats/ModelConfig.h"
#include "RooStats/ProfileInspector.h"
using namespace RooFit;
using namespace RooStats;
using namespace std;
void StandardHistFactoryPlotsWithCategories(const char* infile = "",
                                            const char* workspaceName = "combined",
                                            const char* modelConfigName = "ModelConfig",
                                            const char* dataName = "obsData"){
   double nSigmaToVary=5.;
   double muVal=0;
   bool doFit=false;
   // -------------------------------------------------------
   // First part is just to access a user-defined file
   // or create the standard example file if it doesn't exist
   const char* filename = "";
   if (!strcmp(infile,"")) {
      filename = "results/example_combined_GaussExample_model.root";
      bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
                                                           // if file does not exists generate with histfactory
      if (!fileExist) {
#ifdef _WIN32
         cout << "HistFactory file cannot be generated on Windows - exit" << endl;
         return;
#endif
         // Normally this would be run on the command line
         cout <<"will run standard hist2workspace example"<<endl;
         gROOT->ProcessLine(".! prepareHistFactory .");
         gROOT->ProcessLine(".! hist2workspace config/example.xml");
         cout <<"\n\n---------------------"<<endl;
         cout <<"Done creating example input"<<endl;
         cout <<"---------------------\n\n"<<endl;
      }
   }
   else
      filename = infile;
   // Try to open the file
   TFile *file = TFile::Open(filename);
   // if input file was specified byt not found, quit
   if(!file ){
      cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
      return;
   }
   // -------------------------------------------------------
   // Tutorial starts here
   // -------------------------------------------------------
   // get the workspace out of the file
   RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
   if(!w){
      cout <<"workspace not found" << endl;
      return;
   }
   // get the modelConfig out of the file
   ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
   // get the modelConfig out of the file
   RooAbsData* data = w->data(dataName);
   // make sure ingredients are found
   if(!data || !mc){
      w->Print();
      cout << "data or ModelConfig was not found" <<endl;
      return;
   }
   // -------------------------------------------------------
   // now use the profile inspector
   RooRealVar* obs = (RooRealVar*)mc->GetObservables()->first();
   TList* list = new TList();
   RooRealVar * firstPOI = dynamic_cast<RooRealVar*>(mc->GetParametersOfInterest()->first());
   firstPOI->setVal(muVal);
   //  firstPOI->setConstant();
   if(doFit){
      mc->GetPdf()->fitTo(*data);
   }
   // -------------------------------------------------------
   mc->GetNuisanceParameters()->Print("v");
   int  nPlotsMax = 1000;
   cout <<" check expectedData by category"<<endl;
   RooDataSet* simData=NULL;
   RooSimultaneous* simPdf = NULL;
   if(strcmp(mc->GetPdf()->ClassName(),"RooSimultaneous")==0){
      cout <<"Is a simultaneous PDF"<<endl;
      simPdf = (RooSimultaneous *)(mc->GetPdf());
   } else {
      cout <<"Is not a simultaneous PDF"<<endl;
   }
   if(doFit) {
      RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat());
      TIterator* iter = channelCat->typeIterator() ;
      RooCatType* tt = NULL;
      tt=(RooCatType*) iter->Next();
      RooAbsPdf* pdftmp = ((RooSimultaneous*)mc->GetPdf())->getPdf(tt->GetName()) ;
      RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ;
      obs = ((RooRealVar*)obstmp->first());
      RooPlot* frame = obs->frame();
      cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl;
      cout << tt->GetName() << " " << channelCat->getLabel() <<endl;
      data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None));
      Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ;
      pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ;
      frame->Draw();
      cout <<"expected events = " << mc->GetPdf()->expectedEvents(*data->get()) <<endl;
      return;
   }
   int nPlots=0;
   if(!simPdf){
      TIterator* it = mc->GetNuisanceParameters()->createIterator();
      RooRealVar* var = NULL;
      while( (var = (RooRealVar*) it->Next()) != NULL){
         RooPlot* frame = obs->frame();
         frame->SetYTitle(var->GetName());
         data->plotOn(frame,MarkerSize(1));
         var->setVal(0);
         mc->GetPdf()->plotOn(frame,LineWidth(1.));
         var->setVal(1);
         mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(1));
         var->setVal(-1);
         mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(1));
         list->Add(frame);
         var->setVal(0);
      }
   } else {
      RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat());
      //    TIterator* iter = simPdf->indexCat().typeIterator() ;
      TIterator* iter = channelCat->typeIterator() ;
      RooCatType* tt = NULL;
      while(nPlots<nPlotsMax && (tt=(RooCatType*) iter->Next())) {
         cout << "on type " << tt->GetName() << " " << endl;
         // Get pdf associated with state from simpdf
         RooAbsPdf* pdftmp = simPdf->getPdf(tt->GetName()) ;
         // Generate observables defined by the pdf associated with this state
         RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ;
         //      obstmp->Print();
         obs = ((RooRealVar*)obstmp->first());
         TIterator* it = mc->GetNuisanceParameters()->createIterator();
         RooRealVar* var = NULL;
         while(nPlots<nPlotsMax && (var = (RooRealVar*) it->Next())){
            TCanvas* c2 = new TCanvas("c2");
            RooPlot* frame = obs->frame();
            frame->SetName(Form("frame%d",nPlots));
            frame->SetYTitle(var->GetName());
            cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl;
            cout << tt->GetName() << " " << channelCat->getLabel() <<endl;
            data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None));
            Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ;
            if(strcmp(var->GetName(),"Lumi")==0){
               cout <<"working on lumi"<<endl;
               var->setVal(w->var("nominalLumi")->getVal());
               var->Print();
            } else{
               var->setVal(0);
            }
            // w->allVars().Print("v");
            // mc->GetNuisanceParameters()->Print("v");
            // pdftmp->plotOn(frame,LineWidth(2.));
            // mc->GetPdf()->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            //pdftmp->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            normCount = pdftmp->expectedEvents(*obs);
            pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ;
            if(strcmp(var->GetName(),"Lumi")==0){
               cout <<"working on lumi"<<endl;
               var->setVal(w->var("nominalLumi")->getVal()+0.05);
               var->Print();
            } else{
               var->setVal(nSigmaToVary);
            }
            // pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2));
            // mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            //pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            normCount = pdftmp->expectedEvents(*obs);
            pdftmp->plotOn(frame,LineWidth(2.),LineColor(kRed),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ;
            if(strcmp(var->GetName(),"Lumi")==0){
               cout <<"working on lumi"<<endl;
               var->setVal(w->var("nominalLumi")->getVal()-0.05);
               var->Print();
            } else{
               var->setVal(-nSigmaToVary);
            }
            // pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2));
            // mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            //pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data));
            normCount = pdftmp->expectedEvents(*obs);
            pdftmp->plotOn(frame,LineWidth(2.),LineColor(kGreen),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ;
            // set them back to normal
            if(strcmp(var->GetName(),"Lumi")==0){
               cout <<"working on lumi"<<endl;
               var->setVal(w->var("nominalLumi")->getVal());
               var->Print();
            } else{
               var->setVal(0);
            }
            list->Add(frame);
            // quit making plots
            ++nPlots;
            frame->Draw();
            c2->SaveAs(Form("%s_%s_%s.pdf",tt->GetName(),obs->GetName(),var->GetName()));
            delete c2;
         }
      }
   }
   // -------------------------------------------------------
   // now make plots
   TCanvas* c1 = new TCanvas("c1","ProfileInspectorDemo",800,200);
   if(list->GetSize()>4){
      double n = list->GetSize();
      int nx = (int)sqrt(n) ;
      int ny = TMath::CeilNint(n/nx);
      nx = TMath::CeilNint( sqrt(n) );
      c1->Divide(ny,nx);
   } else
      c1->Divide(list->GetSize());
   for(int i=0; i<list->GetSize(); ++i){
      c1->cd(i+1);
      list->At(i)->Draw();
   }
}

Author: Kyle Cranmer

Definition in file StandardHistFactoryPlotsWithCategories.C.